Review Open Access
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Jan 15, 2020; 12(1): 1-20
Published online Jan 15, 2020. doi: 10.4251/wjgo.v12.i1.1
Precision medicine for gastrointestinal cancer: Recent progress and future perspective
Tasuku Matsuoka, Masakazu Yashiro, Department of Gastroenterological Surgery, Osaka City University Graduate School of Medicine, Osaka 5458585, Japan
Masakazu Yashiro, Oncology Institute of Geriatrics and Medical Science, Osaka City University Graduate School of Medicine, Osaka 5458585, Japan
ORCID number: Tasuku Matsuoka (0000-0001-5019-8519); Masakazu Yashiro (0000-0001-5743-7228).
Author contributions: Matsuoka T and Yahiro M performed literature research; Matsuoka T wrote the manuscript and performed the revision and approval of the final version; Yahiro M designed research, coordinated and corrected the writing of the paper.
Supported by KAKENHI (Grant-in-Aid for Scientific Research), No. 18H02883.
Conflict-of-interest statement: There are not any financial or other interests regarding the submitted manuscript that might be construed as a conflict of interest.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Masakazu Yashiro, MD, PhD, Associate Professor, Department of Surgical Oncology, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 5458585, Japan. m9312510@med.osaka-cu.ac.jp
Received: March 14, 2019
Peer-review started: March 15, 2019
First decision: July 31, 2019
Revised: October 12, 2019
Accepted: November 4, 2019
Article in press: November 4, 2019
Published online: January 15, 2020

Abstract

Gastrointestinal (GI) cancer has a high tumor incidence and mortality rate worldwide. Despite significant improvements in radiotherapy, chemotherapy, and targeted therapy for GI cancer over the last decade, GI cancer is characterized by high recurrence rates and a dismal prognosis. There is an urgent need for new diagnostic and therapeutic approaches. Recent technological advances and the accumulation of clinical data are moving toward the use of precision medicine in GI cancer. Here we review the application and status of precision medicine in GI cancer. Analyses of liquid biopsy specimens provide comprehensive real-time data of the tumor-associated changes in an individual GI cancer patient with malignancy. With the introduction of gene panels including next-generation sequencing, it has become possible to identify a variety of mutations and genetic biomarkers in GI cancer. Although the genomic aberration of GI cancer is apparently less actionable compared to other solid tumors, novel informative analyses derived from comprehensive gene profiling may lead to the discovery of precise molecular targeted drugs. These progressions will make it feasible to incorporate clinical, genome-based, and phenotype-based diagnostic and therapeutic approaches and apply them to individual GI cancer patients for precision medicine.

Key Words: Gastrointestinal cancer, Esophageal cancer, Gastric cancer, Colorectal cancer, Precision medicine, Liquid biopsy, Gene panel, Precision surgery, Biomarkers

Core tip: Gastrointestinal (GI) cancer is one of the most common leading causes of cancer death worldwide. Hence, any effort in early diagnosis, choice of appropriate therapeutic strategies can have a pivotal role in reducing the disease related mortalities. Our review purpose to clarify the current advancement for precision medicine in GI cancer by elucidating the benefit of liquid biopsy, multiple gene panel, novel biomarkers and surgery in GI cancer.



INTRODUCTION

Precision medicine is a strategy designed to treat individual patients with the most suitable therapy at the most appropriate time based on the patient’s biologic and molecular features, using the analyses of genes of the patient’s cancer cells with next-generation sequencing (NGS). Such analyses can detect cancer-specific gene mutations, and molecular targeted drugs can be designed to be effective for one or more specific gene mutations. Precision medicine is thus a type of tailor-made and personalized therapy. The use of inappropriate medicine may not only do not benefit, but lead to cancer progression. As the accessibility to tumor genome sequencing technologies increases, genome-driven cancer treatment has emerged as a favorable approach[1]. The increasing number of patients who undergo multigene sequencing of their cancer can thus expect to be informed of their genomic alterations that could effectively be targeted with corresponding drugs[2].

Gastrointestinal (GI) cancer has a high tumor incidence and mortality rate worldwide[3]. Although colorectal cancer (CRC) could be largely managed, which results in long-term survival by a combination of drugs even in patients with widespread stage and GI lymphoma (e.g., MALT) may also be associated with good response and prolonged survival, the overall prognosis of patients with advanced GI cancer remains poor. Precision medicine approaches are currently being applied with molecular targeted and immune-based therapeutics across a variety of malignancies, such as advanced melanoma and non-small-cell lung cancer (NSCLC)[4,5]. Although GI cancer has been investigated with biomarkers (e.g., Ras and HER2 status), the development of biomarkers as well as targeted therapies for GI cancer has fallen behind compared to those developed for other malignancies. Analyses of liquid biopsies, multiple gene panels, and well-designed prospective trials are necessary to move the treatment of GI cancer forward. In this review, we summarize the progression of precision medicine in GI cancer in terms of specimens, assays, further biomarker information, surgery, and future perspectives.

LITERATURE SEARCH

We first conducted a search of the PubMed database for English articles using the medical subject heading terms in combination with “gastrointestinal cancer”, “esophageal cancer”, “gastric cancer”, “colorectal cancer”, “precision medicine”, “liquid biopsy”, “gene expression profiling”, “biomarker”, “molecular targeted therapy”, and “gene panel”. Relevant articles which were chosen from experimental studies and clinical trials since 1989 were involved as well as articles which were related to the disease processes. Articles which did not deal with the precision medicine of GI cancer were excluded from this review. Liver and pancreatic cancer and GI stromal tumor were not covered in this review due to the limited scope of the topic.

LIQUID BIOPSY

Conventionally, tissue biopsies have been used to access the molecular information of tumors, such as the histology and gene mutation[6]. However, the practical use of consecutive tissue biopsies to monitor for mutations is limited due to patient discomfort, pain, and risks associated with repeat tissue biopsies, and difficulty in capturing intra-tumor heterogeneity[6]. These shortcomings highlight the need for more innovative screening. One promising alternative to tissue biopsy is a new approach that may change the principles of cancer treatment. The term ‘liquid biopsy’ refers to the analysis of tumor-derived biomarkers identified from biological fluids of patients with malignancies. Even though peripheral blood is the major specimen for the liquid biopsy approach, tumor biomarkers can be isolated from various body fluids including urine, pleural effusions, ascites, and cerebrospinal fluid[7].

The liquid biopsy technique been studied to a great extent and is attracting further attention as it leads to efficient therapeutic interventions, reducing the therapeutic cost and significantly improving patient outcomes and overall survival[8]. Analyses of liquid biopsy specimens can provide comprehensive real-time data of the tumor-associated changes in an individual patient with a malignancy. These data can be used for cancer screening, the detection of minimal residual disease, drug selection (including sensitivity to anticancer agents), monitoring recurrence, and monitoring the patient’s response to targeted agents (including drug resistance)[9]. For example, an analysis of NSCLC patients’ plasma for epidermal growth factor receptor (EGFR) to determine the existence of a T790M mutation is widely used[10]. Liquid biopsies could become a new tool with a significant impact on cancer therapy.

Studies of liquid biopsy methodology have focused on the analysis of circulating tumor cells (CTCs), circulating tumor free (cf) DNA or RNA, and tumor-derived extracellular vesicles (exosomes)[11]. For the most effective discussion of the details of liquid biopsy methodology, it is essential to understand the different types of cancer-related biomarkers and their respective molecular aspects.

CTCs

CTCs are tumor cells that are mainly detached from primary or metastatic lesions. They circulate through the body fluid to metastatic sites, either as a single cell or in clusters, which lead to the establishment of one or more secondary tumor foci[12]. The United States Food and Drug Administration (FDA)-cleared CellSearch system has enabled the enumeration of CTCs in cancer patients, and this has made it possible to determine disease activity and patients’ treatment responses, which rely on the expressions of epithelial cell adhesion molecule and cytokeratin on cancer cells in blood[13]. The authors of a previous study described the establishment of colon CTC cultures and permanent cell lines which provided in vivo experimental models. These experiments may provide genetic and epigenetic information on tumor biology, and they may help assess the cells' sensitivity to anticancer drugs[13]. However, the number of CTCs is generally low in patients with GI cancer[14], and this limits the clinical applications of CTC analyses in site of the progression of various methods[14].

Circulating tumor DNA (ctDNA)

ctDNA has emerged as another component of liquid biopsies as a quantitative marker of tumor DNA, reflecting genomic alterations in the blood[15,16]. Compared to the detection of CTCs, the ctDNA-based approach provides more information about a patient-specific disease and treatment. Further benefits of the use of ctDNA as a marker is that ctDNA measurements can provide the real-time pathology of the patient’s disease and higher sensitivity for the early detection of cancers[17]. A previous study showed a significantly broad range for ctDNA among patients with CRC (22–3922 ng/mL of blood) compared to healthy subjects (5-16 ng/mL of blood)[18]. Liquid biopsy analyses may take the place of tissue testing for assessing the mutational status of RAS in patients with CRC. The OncoBEAM RAS CRC Assay identifies the cfDNA of the most frequent KRAS and NRAS mutations by using BEAMing technology[19].

MicroRNAs (miRNAs)

In addition to the quantification of cfDNA, circulating transcriptome is also detectable in the serum of individuals with malignancies. The circulating transcriptome consists of both coding and noncoding RNAs, such as miRNAs or long noncoding RNAs (lncRNAs)[20]. Although RNA is generally unstable in blood, microRNA (miRNA) comprises stable, short, noncoding molecules made of 18-25 nucleotides. This endogenous, single-stranded RNA mediates the expression of nearly 30% of protein-encoding genes in humans[21]. MiRNAs can be analyzed by targeted or RNA sequencing methods, with miRNA signatures observed to be significantly deregulated in cancer patients compared to healthy parsons, and these analyses may become useful in cancer diagnosis and prognosis.

Exosomes

Exosomes are nanosized vesicles (40-150 nm)[22]. These small, membrane-bound vesicles can transport a number of biomolecules which lead to the modification of the activity of recipient cells[22]. Compared to CTCs and ctDNA, exosomes have advantages in several aspects, including their homogeneous size distribution. In addition, due to the particular form of exosomes, they can be distinguishable by electron microscopy. Previous studies have obtained evidence that the exosome-mediated recruitment and manipulation of the tumor microenvironment is a critical step in the formation process of metastasis[23].

Liquid biopsy in GI cancer: Toward clinical applications

The clinical utility of a liquid biopsy has been studied in different clinical phases of GI cancer, from the screening for this disease to the identification of outcome factors in early GI cancer, the detection of minimal residual tumor, drug selection, and monitoring for recurrence and the patients’ response to targeted agents. Current advances of liquid biopsy as diagnostic, monitoring and predictive markers in GI cancer are summarized in Table 1 and Table 2.

Table 1 Current progress of circulating tumor cells, circulating tumor DNA and stool DNA as diagnostic, monitoring and predictive markers in gastrointestinal cancer.
Liquid biopsyPatients/ controlsOrgansSource of fluidAbnormalitiesTechnologyTargetClinical settingRef.
CTCs140/0ECBFIHCCK19, CD45PrognosisLi et al[82], 2016
CTCsNAECBISETNAPrognosisHan et al[83], 2019
CTCs116/31GCBFAST-discEpCAM, CK, CD45-DiagnosticKang et al[84], 2017
CTCs81/31GCBISETCK8/18/19, Vimentin, CD45PrognosticZheng et al, 2017
CTCs101/31GCBCellSearch and IF-FISHEpCAM, CK8, CK18, CK19, CD45-, HER2PredictiveMishima et al[86], 2017
CTCs121/0CRCBCyttel method/imFISHCD45PrognosticWang et al[87], 2019
ctDNA11/0ECP, T, NTMutationWES and NGS panelDiagnostic /TherapeuticLuo et al[88], 2016
ctDNA13/0ECP, TMutationNGS panelPredictiveUeda et al[89], 2016
ctDNA63/0ECPCopy number statusqPCRCCND1PredictiveKomatsu et al[90], 2014
cfDNA32/0GCPCopy number statuscfDNA NGS testingERBBB2TherapeuticKim et al[91], 2018
ctDNA277/0EC/GCP, TMutationMassARRAYTP53, PIK3CA, ERBB2, KRASDiagnostic /PrognosticKato et al, 2018
ctDNA70/0GCP, TMutationNGS panelHER2TherapeuticGao et al[93], 2017
cfDNA60/30GCPMutationDroplet digital PCRHER2TherapeuticShoda et al[94], 2017
ctDNA1/0GCP, TMutationNGS panelMETTherapeuticDu et al30], 2017
ctDNA230/0CRCBMutationSafe-SeqS assayNAPrognosticTie et al[95], 2016
cfDNA22/0CRCSMutationNGS/dPCRTP53, KRAS, APC, PIK3CA, BRAF, FBXW7, NRASDiagnostic /PrognosticFuruki et al[96], 2018
cfDNA3/0CRCPMutationBEAMingRAS, BRAF, PIK3CAPredictiveKlein-Scory et al, 2018
cfDNA20/0CRCPMutationDroplet digital PCRAPC, TP53, KRAS, PI3CAPredictiveVandeputte et al[97], 2018
Stool DNA71/22CRCStoolMethylationQIAamp DNA Stool Mini KitSDC2DiagnosticOh et al[98], 2017
Table 2 Current progress of microRNAs and exosome as diagnostic, monitoring and predictive markers in gastrointestinal cancer.
Liquid biopsyPatients/ controlsOrgansSource of fluidAbnormalitiesTechnologyTargetClinical settingRef.
MiRNAs231/0ECPeripheral blood lymphocytesPolymorphismSNPShotKIAA0423 rs1053667, GEMIN3 rs197412PrognosticFaluyi et al[99], 2017
MiRNAs3156/0ECS/PUpregulation/DownregulationNAmiR-15a, miR-22, miR-31, miR-451, miR-506, miR-613, miR-1297Diagnostic /PrognosticYao et al[100], 2018
MiRNAs125/0ECS/PUpregulation/DownregulationRT-PCRmiR-21, miR-223, miR-100, miR-25, miR-375Diagnostic /PrognosticZhang et al[101], 2018
MiRNAs250/538GCGastric juiceUpregulationmiScript RT kitmiR-421, miR-21, miR-106a, miR-129DiagnosticVirgilio et al[102], 2018
MiRNAs20/20GCSUpregulationTaqMan OpenArray assaysmiR-331 and miR-21DiagnosticSierzega et al[103], 2017
MiRNAsThe miRNA expression profile (GSE29298)CRCNA -UpregulationNAmiR-198, miR-765, miR-630, miR-371-5p, miR-575, miR-202, miR-513a-5pPredictiveZhu et al[104], 2017
MiRNAs232/0CRCSUpregulationNAmiR-21, miR-29b, miR-92.DiagnosticCarter et al[105], 2017
MiRNAs61/0CRCPUpregulationmiRVANA PARIS kitmiR-20b, miR-29b, miR-155Prognosis /PredivtiveUlivi et al[106], 2018
Exosome66/20ECPUpregulationAChE activityExosomesPrognosticMatsumoto et al[107], 2016
Exosome30/0GCPLFUpregulationMiRNA microarraymiR-21, miR-1225-5pDiagnostic /TherapeuticTokuhisa et al[108], 2015
Exosome232/20GCPDownregula-tionTaqman microRNA assaysmiR-23bPrediction /PrognosticKumata et al[109], 2018
Exosome227/28CRCSUpregulation/Downregula-tionqRT-PCR microarraymiR-17, miR-18a, miR-19a, miR-19b, miR20a, miR-92a, hsa-miR-25-106b, hsa-miR-17-92aPredictive /PrognosisMatsumura et al[110], 2015
Exosome108/0CRCSDownregula-tionThe total exosome isolation kitmiR-548c-5pPrognosisPeng et al[111], 2018

Cancer screening: The noninvasive nature of a liquid biopsy makes this approach ideal for the early detection of cancer. The evaluation of molecular biomarkers in early-stage cancer patients is necessary for the development of more personalized monitoring and treatment schedules. However, the possibility of detecting a malignancy at an early stage with a liquid biopsy is somewhat limited by the low concentration of circulating biomarkers associated with the low tumor burden. With respect to CRC, screening has been impacted using colonoscopy as the gold standard, mainly because of its high sensitivity and specificity for detecting cancerous and precancerous lesions. Despite its strengths, colonoscopy has certain disadvantages and limitations (e.g., bowel preparation, sedation, aspiration, perforation, and splenic injury).Therefore, continued progress in novel assays, such as fecal immunochemical test, fecal DNA and other molecular markers, can be expected to further displace screening colonoscopy[24]. The Epi proColon® 2.0 assay (also referred to as the mSEPT9 assay), which was FDA-approved for CRC screening in April 2016, is a qualitative in vitro diagnostic polymerase chain reaction (PCR) test for the detection of mutated methylated septin9 DNA in EDTA plasma derived from patient whole-blood specimens[25].

Detection of minimal residual disease: One of the major fields of the application of liquid biopsy would be the detection of minimal residual disease in patients with surgically treatable tumors. The tumor burden of GI cancer at diagnosis is acknowledged as a pivotal factor of disease assessment before the beginning of treatment. A recent study indicated that somatic KRAS- and BRAF-mutated DNA in the peripheral blood of CRC patients may be a good estimate of CTCs and of surgical clearance of the disease[26].

Drug selection: Chemotherapy is often administered for patients with metastatic disease (e.g., metastasis of regional lymph nodes) in a resected tumor specimen. Although there are a number of different chemotherapeutic agents that can be combined in a variety of chemotherapeutic regimens, the effect of chemotherapy on a specific patient cannot be predicted. Specific ctDNA identification has also been used as guidance for specific systemic chemotherapy and targeted agents. For instance, emerging RAS mutations during therapy with anti-EGFR antibody revealed resistance in patients with metastatic CRC (mCRC)[27]. Some studies found that undetectable low-frequency KRAS-mutant clones may be selected for anti-EGFR treatment by assessing ctDNA in the blood of mCRC patients during anti-EGFR therapy[28,29]. In similar, resistance to crizotinib has been emerged by using serial ctDNA measurements in gastric cancer (GC)[30].

Monitoring recurrence: One of the most challenging tasks in GI oncology is the identification of patients who will benefit from postoperative adjuvant chemotherapy after curative surgery. The histopathologic and molecular tumor features correlated with greater relapse risk (e.g., the TNM classification) only imply a tendency for metastasis; they do not reveal whether metastatic cells were seeded during surgery. The identification of postoperative ctDNA is a definite sign that occult tumor cells remain in the patient.

The authors of a recent study proposed that in patients with CRC, the postoperative detection of ctDNA can be used to monitor the patients for residual disease and predict their future relapse risk with high probability[31]. Moreover, serial ctDNA serves as a tool for the early detection of recurrence during patient follow-up and for the patient’s response to relapse intervention[31]. In CRC, the novel BCAT1/IKZF1 blood test was found to be more sensitive for recurrence compared to carcinoembryonic antigen (CEA) as a marker, and the likelihood of recurrence given a positive BCAT1/IKZF1 result was twice that compared to a positive CEA result[32].

Monitoring patients’ responses to cytotoxic and targeted agents: The most potentially beneficial application of the liquid biopsy approach is the possibility of using this approach to monitor patients' therapeutic responses. In general, ctDNA has seemed to be an early biomarker that can be used to deduce the tumor burden of patients with CRC during chemotherapy and to predict the early therapeutic reaction. Molecular alterations that are related to drug resistance can be identified at an early stage by evaluating ctDNA, and this evaluation can be performed easily for the same patient at different time intervals.

A single-arm phase II trial (Erbitux Study of CPT11, Oxaliplatin, UFToral Targeted-therapy) was carried out in patients with previously untreated KRAS wild-type advanced CRC, using a regimen of irinotecan, oxaliplatin, and tegafur-uracil with leucovorin and cetuximab. The stratification of patients by the CTC count can identify the patients who might benefit the most from an intensive four-drug regimen, avoiding the use of high-toxicity regimens in low-CTC groups[33].

GENE PANEL SEQUENCING IN GI CANCER

Sequencing is often performed to identify cancer-associated gene mutations in patients with advanced cancer. Sequencing panels allow the targeting of multiple genes simultaneously, quickly and accurately through comprehensive bioinformatics in order to exploit the useful information from a single study. The NGS of tumor sample DNA can lead to the optimal clinical treatment by offering diagnostic and/or prognostic data and by contributing to the selection of potential treatment regimens (e.g., molecular-targeted and immune checkpoint blockade therapies). Recent advances in NGS has enabled the performance of whole-genome sequencing, whole-exome sequencing, whole-transcriptome sequencing and RNA sequencing, as well as the detection of enormous genetic aberrations[34].

Due to the progress in sequencing technologies, tissue comprehensive genome profiling has become more widely available in clinical practice. For example, the current National Comprehensive Cancer Network guidelines recommend comprehensive genome profiling in patients with advanced non-small-cell lung adenocarcinoma[4]. Currently, NGS provides faster, cheaper, and more accurate whole-genome sequencing. The Cancer Genome Atlas has revealed the genome profiles of many cancers, including GI cancer[35,36]. Current progress of multiplex gene panels in GI cancer is summarized in Table 3.

Table 3 Current progress of multiplex gene panels in gastrointestinal cancer.
OrgansPanel testedNumber of genes testedNumber of patientsThe type of sampleCompanion diagnostic indicationsRef.
ECHiSeq2000N/A144Tumor tissue DNACCND1, CDKN2A, FBXW7, MLL2, EP300, CREBBP, TET2, NOTCH1, NOTCH3, FAT1, YAP1, AJUBA, PIK3CA, EGFR, ERBB2Sawada et al[44], 2016
ECExiqon miRNA qPCR panel168miRNA140Serum miRNAmiR-20b-5p, miR-28-3p, miR-192-5p, miR-223-3p, and miR-296-5pHuang et al[50], 2017
ECIon AmpliSeq Custom DNA Panel1227Tumor tissue/Serum DNABRAF, DDR2, ERBB2, HRAS, KEAP1, KRAS, NFE2L2, NRAS, PIK3CA, PTEN, RHOAPasternack et al[112], 2018
GCIllumina HiSeq 200038138Tumor tissue DNARHOA, CDH1, PIK3CA, CTNNB1, APC, ARID1A, KMT2C, KRASKakiuchi et al[42], 2014
GCIllumina HiSeq 2000N/A100Tumor tissue DNAARID1A, CDH1, MUC6, CTNNA2, GLI3, RNF43, RHOAWang et al[43], 2014
GCCANCERPLEX435207Tumor tissue DNAARID1A, CDH1, ERBB2, CCNE1, KRASIchikawa et al[41], 2017
GCIon-Proton sequencer5029Tumor tissue DNAAPC, CTNNB, KRAS, NPM1, FBXW7 ERBB2, FGFR2, KITYoshida et al[113], 2019
CRCCANCERPLEX415201Tumor tissue DNAERBB2, APC, CDKN2A, NRAS, ATM, BLM, BRCA2, NBN, NRE11ANagahashi et al[39], 2016
CRCIT-PGM seqencing2277Tumor tissue DNARAS, PIK3CA, FBXW7, BRAF, SMAD4, MET, FGFR1Capalbo et al [114], 2019
CRCOncoAim™ DNA panel39648Tumor tissue DNAKRAS, APC, PIK3CA, SMAD4, BRAF, FBXW7, NRASWang et al[115], 2018
CRCMiSeq20722Tumor tissue DNAKRAS, PIK3CA, FBXW7, PTEN, SMAD4, BRAF, CTNNB1, NRASGao et al[116], 2019
CRCcfDNA panel14101Plasma cfDNAAKT1, BRAF, CTNNB1, EGFR, ERBB2, FBXW7, GNAS, KRAS, MAP2K1, NRAS, PIK3CA, SMAD4, APC,Osumi et al, 2018
CRCTruSight Cancer Sequencing Panel42N/ABlood ctDNAMLH1, MSH6, PMS2 APC, SMAD4, TP53, BRIP1, CHEK2, MUTYH, HNF1A, XPCSeifert et al[117], 2019

Gene panaels contains the most commonly mutated genes or candidate actionable genes in many cancers. In CRC, KRAS, BRAF, PIK3CA, TP53, CTNNB1, APC, SMAD4, and PTEN are among the most commonly altered genes[37,38]. Patients with CRC in Japan were recently studied using an NGS - based comprehensive genomic panel test[39]. Significant differences in ERBB2, APC, TP53, CDKN2A, and NRAS mutations were identified in the Japanese patients compared to United States patients. Genomic alterations in DNA repair genes (e.g., ATM, BLM, BRCA2, NBN, NRE11A), which are observed in a significant proportion of CRC patients, were also detected. A novel, positive correlation between APC and TP53 mutations with tumors that presented on the left side was reported. A study through deep sequencing in patients with mCRC presented that mutations in TP53, KRAS, APC, KRAS, GNAS, and SMAD4 genes were detected in 69.3%, 39.6%, 23.7%, 16.8% and 13.8% patients, respectively. The mutations in KRAS, GNAS, and SMAD4 were significantly associated with lung metastasis[40].

In GC, comprehensive genomic sequencing using a 435-gene panel in Japanese gastric cancers (GCs) showed that the most frequently mutated gene was TP53 (53.1%), followed by ARID1A (15.9%) and CDH1 (14.0%); ERBB2 amplification (12.1%) was the most frequently observed somatic copy number alteration, followed by CCNE1 (7.2%) and KRAS (5.8%) amplification[41]. Specific subcategories of GCs harbor characteristic genetic aberrations, such as somatic mutations in RHOA and a chimeric gene fusion of CLDN18-ARHGAP26 in diffuse-type GCs[42,43]. The landscape of esophageal cancer (EC)-related gene mutations that regulate the cell cycle (TP53, CCND1, CDKN2A, FBXW7), epigenetic processes (MLL2, EP300, CREBBP, TET2), and the signaling pathways involving NOTCH (NOTCH1, NOTCH3), WNT (FAT1, YAP1, AJUBA) and receptor-tyrosine kinase-phosphoinositide 3-kinase (PIK3CA, EGFR, ERBB2) has been described[44].

Current advances in cancer genome analyses using NGS have revealed an increased mutation burden (a high rate of somatic mutation) in some solid tumors. In GI cancers, one of the leading causes of hypermutation - which is closely related to the generation of neo-antigens - is a defect in DNA mismatch repair (MMR), leading to microsatellite instability (MSI). Several research groups have stated that the tumor mutated burden correlates with the clinical response to immunotherapy[45,46]. GI cancer patients with MMR deficiency and a subsequent hypermutated phenotype achieved outstanding outcomes after anti-PD-1 therapy[47]. This highlights the clinical significance of identifying hypermutated tumors for immunotherapy treatment.

In CRC, mutations in transforming growth factor-beta (TGF-β) signaling genes and BRAF were markedly increased in hypermutated tumors[35]. Mutations in DNA polymerase D1 (POLD1) and DNA polymerase E (POLE) genes have also been described as a cause of hypermutated CRC[48]. The mutation rate of MSI-High GCs was significantly higher than that of MSS tumors[41]. TGFBR2, ACVR2A, SMAD4, and ELF3 as well as the TGF-β pathway are frequently mutated, suggesting a pivotal role in GC pathogenesis, including MSI[43,49].

Given the advances in NGS, it may well become possible in the near future to identify the predominant cancer genes and pathways and tumor-specific genes and pathways. Several multigene assays are available to estimate the risk of relapse after definitive surgery, including the MSK-IMPACT, NCC Oncopanel, Todai OncoPanel, Oncomine Dx Target test, Foundation OneCDx, and CANCERPLEX.

A recent study using the Exiqon panel identified miR-20b-5p, miR-28-3p, miR-192-5p, miR-223-3p, and miR-296-5p as significantly upregulated in the serum of patients with EC, suggesting that these 5-miRNA signatures may serve as potential diagnostic biomarkers for ECs[50]. Similarly, the expressions of seven miRNAs (miR-103a-3p, miR-127-3p, miR-151a-5p, miR-17-5p, miR-181a-5p, miR-18a-5p, and miR-18b-5p) were significantly higher in CRC compared to normal controls[51].

BIOMARKERS FOR GI CANCER

Convincing biomarkers are a crucial aspect of precision medicine, used to match appropriate patients with the right treatment at the right time. Clinically relevant biomarkers are genetic, epigenetic, proteinic, or cellular alterations that are intrinsic to cancer cells. These biomarkers can be used to predict patients' responses to chemotherapy, targeted therapy, or immune checkpoint inhibitors. To date, the most reliable molecular marker in clinical practice is the KRAS gene for patients receiving EGFR - targeted therapy for CRC metastatic disease and HER2 overexpression for patients with HER2-positive GC[52,53]. Detection of BRAF mutation status was also recommended due to the ineffectiveness of anti-EGFR therapy for CRC patients with BRAF mutations[54]. Although there is a crucial need for novel diagnostic and prognostic biomarkers to improve GI cancer prognosis, these tools are still being investigated. In this section, we summarize the current advances of biomarkers in GI cancer, with a focus on the development of new biomarkers that are of predictive and/or prognostic values.

Another biomarker for therapeutic target in GI cancer may be MET. A multicenter phase II study demonstrated antitumor activity of small-molecule MET inhibitor was shown in MRT-amplifier gastric/gastroesophageal/esophageal adenocarcinoma[55]. A recent study using whole-exome sequencing characterized KDR/VEGFR2 somatic mutations as potential genetic biomarkers of patients’ responses to antiangiogenic cancer therapies[56]. Interestingly, a recent cohort study presented that ALK, ROS1, and NTRK rearrangements classified a new subtype of mCRC with particularly poor outcome[57]. Rearrangements of ALK, ROS1, and NTRK were more frequently observed in elderly patients with right-sided tumors and node-spreading, RAS wild-type, and MSI-high cancers. As noted above, ctDNA and RNA-based biomarkers provide high specificity and are ideal as predictive markers for monitoring patients' responses to chemotherapy as well as tumor progression[52]. MMR-deficiency deficiency has emerged as another meaningful biomarker. MMR deficiency has been shown to be positively prognostic for outcome in patients with GC and CRC[58,59]. Notably, MMR deficiency is a variety of cancer predictor for response to anti-PD-1/PD-L1 blockade therapies[60]. Tumor-infiltrating lymphocytes (TILs) are the major type of infiltrating immune cells[36]. The density of TILs is considered to be an indication of the host immune response against tumor cells. To date, the density of TILs have been investigated as a useful prognostic factor in GI cancer[61]. Collectively, research has moved towards the identification of mutations in key genes involved in the progression of GI cancer. In the meanwhile, large-scale prospective clinical studies for evaluating the sensitivity and specificity of these biomarkers are required before their application in clinical practice, due to their low mutational burden and insufficient specificity. The approved biomarkers and candidate biomarkers of GI cancer are summarized in Table 4.

Table 4 Current progress of biomarkers associated with diagnosis, prognosis, prediction of therapeutic response in gastrointestinal cancer (excluding liquid biopsy).
MarketTumor typeAlterationClinical settingRef.
HER2GC, CRCAmplification, OverexpressionPredictiveBang et al[118], 2010; Sartore-Bianchi et al[119], 2016
KRASCRCActivating mutation within catalytic RAS domainPredictiveWormald et al, 2013; Febbo et al, 2011; Schmoll et al[122], 2012; Locker et al[123], 2006
NRAS,CRCOverexpressionPrognostic/PredictiveHu et al[124], 2018
BRAFCRCMutationPrognostic/TherapeuticTie et al[54], 2011
KDRCRCMutationPredictiveLoaiza-Bonilla et al[125], 2016
VEGF-DCRCOverexpressionPredictiveTabernero et al[126], 2018
AKTGCActivationPredictiveIto et al[127], 2017
PTENGCDownregulationPredictiveKim et al, 2017
NTRK fusionCRCOverexpressionPredictiveDrilon et al[129], 2018
ALKCRCRearrangementPrognosticPietrantonio et al[57], 2017
POLECRCMutationPredictiveDomingo et al[130], 2016
MMRGC, CRCPredictiveLlosa et al[131], 2015
PD-L1CRCMutatoinPrognosticEriksen et al[132], 2019
Tumor infiltrating lymphocyteGC, CRCOverexpressionPrognosticIseki et al[133], 2018
CagAGCUpregulatedDiagnosticSaju et al[134], 2016
Gastrokine 1GCDownregulatedDiagnosticAltieri et al[135], 2017
MEKCRCActivationPredictiveMartinelli et al[136], 2017
PIK3CACRCMutationPrognostic/ TherapeuticJehan et al[137], 2019; Schmoll et al[122], 2012
TP53EC, GC, CRCMutationPrognosticSchmoll et al[122], Guo et al[138], 2017
CTNNB1CRC EC, GCMutation OverexpressionPrognostic PrognosticGao et al[116], 2019; Szász et al[139], 2016; Ishiguro et al[140], 2016
APCCRCMutationPrognosticLiang et al[141], 2017; Chen et al[142], 2013
IGFR-!RCRCUpregulationPrognosticCodony-Servat et al[143], 2017
SFRP2CRCHypermethylationDiagnostic/PrognosticTang et al, 2011
UGT1A1CRCHypermethylationPredictiveCrea et al[145], 2011
SMAD4,EC, GC, CRCDownregulationPrognostic/PredictiveSalem et al[146], 2018; Wasserman et al[147], 2019
METEC, GCAmplificatoinPredictiveVan Cutsem et al[55], 2018
CDKN2AEC,MethylationDiagnosticZhou et al, 2017
ATMGC, CRCMutaion/DownregulationPrognosticRandon et al[149], 2019; Han et al[83], 2017
BLM,CRCMutaion/PolymorphismsDiagnosticde Voer et al[150], 2015; Frank et al[151], 2010
BRCA1/2,CRCMutaionDiagnosticOh et al[152], 2018
ARID1AGCMutationPredictiveWei et al[153], 2014
CRCOverexpresionPrognosticRonchetti et al[154], 2017
CDH1GCMutationDiagnosticHansford et al[155], 2015
CRCPolymorphismDiagnosticGrünhage et al[156], 2008
CCNE1GCAmplificationTherapeuticOoi et al[157], 2017
RHOAGC, CRCOverexpressionPrognosticChang et al[158], 2016
CCND1ECAmplification/OverexpressionDiagnosticHu et al[159], 2016
CRCPolymorphismDiagnosticGrünhage et al[156], 2008
FBXW7CRCMutationPrognosticKorphaisarn et al[160], 2017
NOTCH1ECMutationPrognosticSong et al[161], 2016
CRCGene copy numberPrognosticArcaroli et al[162], 2016
NOTCH3CRCOverexpressionPredictiveOzawa et al[163], 2014
YAP1EC, GC, CRCOverexpressionPrognosticZhang et al[164], 2018

Future research may identify biomarkers that enable cost-effective and noninvasiveness treatments for GI cancer. It is also necessary to determine the best prognostic panel of biomarkers and to find predictive biomarkers to help in the selection of the most suitable therapy.

PRECISION SURGERY IN GI CANCER

Precision medicine is a general concept and is thus not limited to genetic detection. Although surgery is the most effective treatment for localized GI cancer and is often curative, an insufficient removal of a tumor results in secondary tumor foci for which the existing chemotherapeutics and/or radiation would be ineffective. In this finally section, we would like to discuss the progress of the precision treatment of GI cancers through surgery.

Fluorescence-guided surgery for GI cancer

Surgery has been said to provide the most benefit for patients with GI cancer. When R0 resection was carried out in a series of GI cancer patients, the local 5-year relapse rate was significantly improved[62]. The reported rates of local recurrence and distant metastasis were high at 2.6% and 30% of patients who underwent an R0 resection[63,64]. Real-time imaging to find positive surgical margins during a surgical procedure may be useful to diminish the rates of recurrence. Intraoperative fluorescence imaging, or fluorescence-guided surgery (FGS), can offer highly reliable tumor visualization for localization and margin identification[65]. The targeted fluorescent labeling of cancer cells may therefore alter the ways we detect and treat cancer.

Indocyanine green (ICG) is applied clinically to define liver tumor margins and biliary anatomy. The authors of a recent meta-analysis stated that intraoperative ICG fluorescence angiography has been demonstrated to reduce anastomotic leakage rates after colorectal resection[66]. In CRC, ICG fluorescence lymphangiography can be used to detect the primary tumor, its lymphatic drainage, and potentially malignant nodes, which may change the operative plan[67]. FGS can thus serve as a surgical guide with the potential to provide benefits for patients with GI cancer.

Sentinel node navigation surgery

Many investigators have described the potential usage of sentinel node (SN) navigation surgery in patients with early-stage EC and GC who have no lymph node metastasis preoperatively[68,69]. In early stage upper GI cancer, SN mapping provides significant information about an individual patient’s metastatic situation and enables the modification of the patient’s surgery. Several single-institution investigations have noted pivotal benefits of SN mapping for early EC, especially when using the radio-guided method[70]. Clinically T1 esophageal cancers were suitable targets for SN mapping, because in T3 or T4 tumors as well as those with lymph node metastasis, the original lymphatic routes can be obstructed, which leads to a high rate of false-negative outcomes. SNs were detected in 95% of patients, and the accuracy was as high as 94%[71]. Moreover, SNs were identified widely from the cervical area to the abdominal area, which allows the partial resection of the distal esophagus via the laparoscopic trans-hiatal approach without extensive mediastinal lymph node dissection when the SNs are identified only in the abdominal region and are pathologically negative in cT1N0 cases of the distal esophagus[71]. The precise indications for laparoscopic surgeries (e.g., partial resection and segmental gastrectomy for cT1N0 GC) based on the SN status could be individually determined. SN navigation surgery could be a strategy to ensure a better prognosis than conventional operative strategies.

FUTURE PERSPECTIVES

Precision medicine is the application of the latest biological technology that takes into account the patient’s living environment along with the patient’s clinical data (as well as molecular imaging techniques and bioinformatics technology) to achieve accurate diagnoses and treatments. It is difficult to determine the precise clinical and biological significance for each individual patient because of the inconsistency in biological features on the human genome[71]. Moreover, the complexity of the NGS data-analysis process makes it impractical for oncologists to understand the meanings and uncertainties of the results easily. A systematic and easily interpreted system with an accessible database is immediately necessary for detecting specific genomic alterations and genotype-matched therapeutic options with clinical practice. Although it would be impossible to completely prepare a treatment plan for each individual case, more suitable treatment based on the unique genomic changes of each patient's tumor could be adapted.

The recent progress in the use of precision medicine in GI cancer was summarized in this review. Regarding treatment, we expect that the narrowing down of the number of eligible patients in accord with dose setting, schedule setting, and the selection of concomitant drugs based on the mechanism of molecular targeted agents will lead to effective therapy customized to each individual. For GI cancers, there is an urgent need for preclinical models to identify and select suitable target for therapy. Recent developments in stem cell biology have enabled the in vitro generation of complex three-dimensional (3D) multicellular stem cell-derived constructs that mimic their corresponding organ in vivo[72]. These organ-like structures denoted as organoids. Patient-derived organoids (PDOs) may be an attractive candidate for an appropriate cancer model that is able to identify the most effective therapy for individual patients with currently available drugs in a timely manner, but also the future of regenerative medicine. therapies, 3D organoids have been advanced for several cancer types and been shown to effectively recapitulate tumor specific characteristics, which may lead to facilitate the development of precision medicine[73]. A recent study demonstrated that the feasibility of GC PODs from endoscopic biopsies and also suggest that endoscopic-derived PDOs may serve as an precise surrogates of the primary lesion of tumor, which may lead to possess the superiority to drug sensitivity screening and precision therapies[74]. Other study using patient-derived CRC organoids presented that of all RASGTPases activating proteins, only neurofibromin (NF1) deficiency facilitate cell survival and prompted EGF-independent tumor cell growth in human CRC samples, suggesting that NF1 protein levels should be measured in CRCs prior to initiate of targeted therapy against the MAPK pathway[75].

Our understanding of the fundamental biology of GI cancer is continually advancing. GI cancer is a heterogeneous disease with significant differences between patients in prognosis and therapeutic response. Part of these differences can be explained by the molecular diversity detected in GI cancer. So as to provide a more overall insight into this complexity, biologically distinct molecular subtypes of GI cancer based on gene expression analyses were defined and validated. EC is classified into three distinct molecular subgroups based on gene analysis findings[76]. The first subgroup (ESCC1) includes tumors that respond poorly to chemoradiotherapy, leading to poor prognoses. The principal gene alteration identified is NRF2 pathway disruption. The second subgroup is ESCC2, characterized by the mutation of NOTCH1, ZNF750, KDM6A, KDM2D, PTEN, PIK3R1, and CDK6 amplification. This subgroup is also associated with white blood cell infiltration. The last molecular subgroup (ESCC3) is characterized by PI3K pathway disruption. Similarly, GC is sub-classified into four major subtypes based on the molecular pattern; the EBV group, MSI group, chromosomal instability group, and genomically stable group[36]. In CRC, four consensus molecular subtypes (CMS) were shown. CMS1 is enriched for MSI tumors that reveal marked immune activation. CMS2 reflects the classical subtype encompassing higher CIN and strong WNT/MYC-driven tumors with epithelial characteristics, whereas CMS3 is enriched for KRAS-mutated tumors with activation of metabolic pathways. CMS4 has mesenchymal features, shows a high stromal content and activation of TGF-β and VEGFR pathways[77]. Apparent clinical distinctions are distinct with poor prognosis for CMS4 and a relatively good prognosis for CMS1. A study classifying CRC by both tumor side and location using NGS panel presented that RAS mutations are seen in 70% of cecal tumors but only 57% of ascending colon and 43% of hepatic flexure tumors. BRAFV600 mutations occur in 10% of cecal, 16% of ascending colon, and 22% of hepatic flexure tumors. PIK3CA mutations are seen in 26% of descending colon but only 14% of sigmoid and 9% of rectosigmoid tumors. CTNNB1 mutations are almost absent in the sigmoid (1%), rectosigmoid junction (0%), and rectum (1%), but are still present in the descending colon (6%). This study also revealed increasing rates of CMS2 moving from right to left, accompanied by a fall in CMS1, while CMS3 and CMS4 were relatively stable when we compared CMS by tumor side[78]. In summary, the region from the sigmoid colon to the rectum appears unique and the transverse colon appears distinct from other right sided locations.

Another study define the colorectal cancer intrinsic subtypes (CRIS) distinguished by specific molecular, functional and pathogenic features; (1) CRIS-A: Mucinous subtype, glycolytic metabolism, with marked MSI, mutated BRAF or KRAS; (2) CRIS-B: Active TGF-β signaling, epithelial–mesenchymal transition, bad prognosis; (3) CRIS-C: High EGFR signaling, and to EGFR inhibitors (i.e., cetuximab); (4) CRIS-D: High WNT signaling, IGF2 gene amplification/ overexpression; and (5) CRIS-E: Paneth-like phenotype and TP53-mutated genotype[79]. Recent work revealed that subtype-specific analysis can be used to predict therapy response, which provides a great opportunity to improve patients’ management regarding precision medicine[80,81].

Although subclassification systems proposed for each GI cancer type have also possessed major challenges and caused important questions that need to be further investigated still it is applied for patient care timely, there is the possibility that these subgroup analyses revolutionize our approach towards precision medicine. Advances in tumor genomics and the immunologic landscape based on “big data” will allow the identification of expanding indications for molecular target drugs and chemotherapy in GI cancer and its predictive biomarkers. Clinical trials for targeted therapies, coupled with genomic profiling for optimum patient selection, are required to demonstrate clinical utility, including treatment outcomes and cost-effectiveness. Investigations of the safety and efficacy of clinical cancer therapies may reveal novel research directions for treating GI cancer. Increasing our knowledge of the signaling that mediates the driver mutations in GI cancer will improved our understanding of GI cancer and serve to guide future precision medicine applications for this disease. At present, we are in the very early phases of this transition towards precision and personalized medicine. We hope that this review can be a guideline for clinical and bench investigators to further develop precision medicine.

Footnotes

Manuscript source: Invited manuscript

Specialty type: Oncology

Country of origin: Japan

Peer-review report classification

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P-Reviewer: Friedel D, Usta J S-Editor: Dou Y L-Editor: A E-Editor: Liu MY

References
1.  Hyman DM, Taylor BS, Baselga J. Implementing Genome-Driven Oncology. Cell. 2017;168:584-599.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 324]  [Cited by in F6Publishing: 310]  [Article Influence: 44.3]  [Reference Citation Analysis (0)]
2.  Zehir A, Benayed R, Shah RH, Syed A, Middha S, Kim HR, Srinivasan P, Gao J, Chakravarty D, Devlin SM, Hellmann MD, Barron DA, Schram AM, Hameed M, Dogan S, Ross DS, Hechtman JF. DeLair DF, Yao J, Mandelker DL, Cheng DT, Chandramohan R, Mohanty AS, Ptashkin RN, Jayakumaran G, Prasad M, Syed MH, Rema AB, Liu ZY, Nafa K, Borsu L, Sadowska J, Casanova J, Bacares R, Kiecka IJ, Razumova A, Son JB, Stewart L, Baldi T, Mullaney KA, Al-Ahmadie H, Vakiani E, Abeshouse AA, Penson AV, Jonsson P, Camacho N, Chang MT, Won HH, Gross BE, Kundra R, Heins ZJ, Chen HW, Phillips S, Zhang H, Wang J, Ochoa A, Wills J, Eubank M, Thomas SB, Gardos SM, Reales DN, Galle J, Durany R, Cambria R, Abida W, Cercek A, Feldman DR, Gounder MM, Hakimi AA, Harding JJ, Iyer G, Janjigian YY, Jordan EJ, Kelly CM, Lowery MA, Morris LGT, Omuro AM, Raj N, Razavi P, Shoushtari AN, Shukla N, Soumerai TE, Varghese AM, Yaeger R, Coleman J, Bochner B, Riely GJ, Saltz LB, Scher HI, Sabbatini PJ, Robson ME, Klimstra DS, Taylor BS, Baselga J, Schultz N, Hyman DM, Arcila ME, Solit DB, Ladanyi M, Berger MF. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med. 2017;23:703-713.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1826]  [Cited by in F6Publishing: 2179]  [Article Influence: 311.3]  [Reference Citation Analysis (0)]
3.  Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin. 2005;55:74-108.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 13286]  [Cited by in F6Publishing: 13429]  [Article Influence: 706.8]  [Reference Citation Analysis (1)]
4.  Ettinger DS, Wood DE, Aisner DL, Akerley W, Bauman J, Chirieac LR, D'Amico TA, DeCamp MM, Dilling TJ, Dobelbower M, Doebele RC, Govindan R, Gubens MA, Hennon M, Horn L, Komaki R, Lackner RP, Lanuti M, Leal TA, Leisch LJ, Lilenbaum R, Lin J, Loo BW, Martins R, Otterson GA, Reckamp K, Riely GJ, Schild SE, Shapiro TA, Stevenson J, Swanson SJ, Tauer K, Yang SC, Gregory K, Hughes M. Non-Small Cell Lung Cancer, Version 5.2017, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw. 2017;15:504-535.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 677]  [Cited by in F6Publishing: 898]  [Article Influence: 128.3]  [Reference Citation Analysis (0)]
5.  Gladfelter P, Darwish NHE, Mousa SA. Current status and future direction in the management of malignant melanoma. Melanoma Res. 2017;27:403-410.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 31]  [Cited by in F6Publishing: 36]  [Article Influence: 6.0]  [Reference Citation Analysis (0)]
6.  Crowley E, Di Nicolantonio F, Loupakis F, Bardelli A. Liquid biopsy: monitoring cancer-genetics in the blood. Nat Rev Clin Oncol. 2013;10:472-484.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1114]  [Cited by in F6Publishing: 1225]  [Article Influence: 111.4]  [Reference Citation Analysis (0)]
7.  Mader S, Pantel K. Liquid Biopsy: Current Status and Future Perspectives. Oncol Res Treat. 2017;40:404-408.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 130]  [Cited by in F6Publishing: 140]  [Article Influence: 20.0]  [Reference Citation Analysis (0)]
8.  Gao Y, Zhang K, Xi H, Cai A, Wu X, Cui J, Li J, Qiao Z, Wei B, Chen L. Diagnostic and prognostic value of circulating tumor DNA in gastric cancer: a meta-analysis. Oncotarget. 2017;8:6330-6340.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 48]  [Cited by in F6Publishing: 52]  [Article Influence: 8.7]  [Reference Citation Analysis (0)]
9.  Cohen JD, Li L, Wang Y, Thoburn C, Afsari B, Danilova L, Douville C, Javed AA, Wong F, Mattox A, Hruban RH, Wolfgang CL, Goggins MG, Dal Molin M, Wang TL, Roden R, Klein AP, Ptak J, Dobbyn L, Schaefer J, Silliman N, Popoli M, Vogelstein JT, Browne JD, Schoen RE, Brand RE, Tie J, Gibbs P, Wong HL, Mansfield AS, Jen J, Hanash SM, Falconi M, Allen PJ, Zhou S, Bettegowda C, Diaz LA, Tomasetti C, Kinzler KW, Vogelstein B, Lennon AM, Papadopoulos N. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science. 2018;359:926-930.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1752]  [Cited by in F6Publishing: 1588]  [Article Influence: 264.7]  [Reference Citation Analysis (0)]
10.  Díaz-Serrano A, Gella P, Jiménez E, Zugazagoitia J, Paz-Ares Rodríguez L. Targeting EGFR in Lung Cancer: Current Standards and Developments. Drugs. 2018;78:893-911.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 42]  [Cited by in F6Publishing: 45]  [Article Influence: 9.0]  [Reference Citation Analysis (0)]
11.  Zhang W, Xia W, Lv Z, Ni C, Xin Y, Yang L. Liquid Biopsy for Cancer: Circulating Tumor Cells, Circulating Free DNA or Exosomes? Cell Physiol Biochem. 2017;41:755-768.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 150]  [Cited by in F6Publishing: 156]  [Article Influence: 22.3]  [Reference Citation Analysis (0)]
12.  Ferreira MM, Ramani VC, Jeffrey SS. Circulating tumor cell technologies. Mol Oncol. 2016;10:374-394.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 357]  [Cited by in F6Publishing: 353]  [Article Influence: 44.1]  [Reference Citation Analysis (0)]
13.  Riethdorf S, Fritsche H, Müller V, Rau T, Schindlbeck C, Rack B, Janni W, Coith C, Beck K, Jänicke F, Jackson S, Gornet T, Cristofanilli M, Pantel K. Detection of circulating tumor cells in peripheral blood of patients with metastatic breast cancer: a validation study of the CellSearch system. Clin Cancer Res. 2007;13:920-928.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 996]  [Cited by in F6Publishing: 988]  [Article Influence: 58.1]  [Reference Citation Analysis (0)]
14.  Sumanasuriya S, Lambros MB, de Bono JS. Application of Liquid Biopsies in Cancer Targeted Therapy. Clin Pharmacol Ther. 2017;102:745-747.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 18]  [Article Influence: 2.6]  [Reference Citation Analysis (0)]
15.  Wan JCM, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C, Pacey S, Baird R, Rosenfeld N. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer. 2017;17:223-238.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1634]  [Cited by in F6Publishing: 1519]  [Article Influence: 217.0]  [Reference Citation Analysis (0)]
16.  Diaz LA, Bardelli A. Liquid biopsies: genotyping circulating tumor DNA. J Clin Oncol. 2014;32:579-586.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1413]  [Cited by in F6Publishing: 1571]  [Article Influence: 157.1]  [Reference Citation Analysis (0)]
17.  Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y. Agrawal N, Bartlett BR, Wang H, Luber B, Alani RM, Antonarakis ES, Azad NS, Bardelli A, Brem H, Cameron JL, Lee CC, Fecher LA, Gallia GL, Gibbs P, Le D, Giuntoli RL, Goggins M, Hogarty MD, Holdhoff M, Hong SM, Jiao Y, Juhl HH, Kim JJ, Siravegna G, Laheru DA, Lauricella C, Lim M, Lipson EJ, Marie SK, Netto GJ, Oliner KS, Olivi A, Olsson L, Riggins GJ, Sartore-Bianchi A, Schmidt K, Shih lM, Oba-Shinjo SM, Siena S, Theodorescu D, Tie J, Harkins TT, Veronese S, Wang TL, Weingart JD, Wolfgang CL, Wood LD, Xing D, Hruban RH, Wu J, Allen PJ, Schmidt CM, Choti MA, Velculescu VE, Kinzler KW, Vogelstein B, Papadopoulos N, Diaz LA JrDetection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med. 2014;6:224ra24.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2770]  [Cited by in F6Publishing: 3181]  [Article Influence: 318.1]  [Reference Citation Analysis (0)]
18.  Schwarzenbach H, Stoehlmacher J, Pantel K, Goekkurt E. Detection and monitoring of cell-free DNA in blood of patients with colorectal cancer. Ann N Y Acad Sci. 2008;1137:190-196.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 131]  [Cited by in F6Publishing: 136]  [Article Influence: 8.5]  [Reference Citation Analysis (0)]
19.  García-Foncillas J, Alba E, Aranda E, Díaz-Rubio E, López-López R, Tabernero J, Vivancos A. Incorporating BEAMing technology as a liquid biopsy into clinical practice for the management of colorectal cancer patients: an expert taskforce review. Ann Oncol. 2017;28:2943-2949.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 54]  [Cited by in F6Publishing: 66]  [Article Influence: 11.0]  [Reference Citation Analysis (0)]
20.  Tóth K, Barták BK, Tulassay Z, Molnár B. Circulating cell-free nucleic acids as biomarkers in colorectal cancer screening and diagnosis. Expert Rev Mol Diagn. 2016;16:239-252.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 14]  [Cited by in F6Publishing: 18]  [Article Influence: 2.3]  [Reference Citation Analysis (0)]
21.  Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116:281-297.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 25833]  [Cited by in F6Publishing: 26896]  [Article Influence: 1344.8]  [Reference Citation Analysis (0)]
22.  Munson P, Shukla A. Exosomes: Potential in Cancer Diagnosis and Therapy. Medicines (Basel). 2015;2:310-327.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 56]  [Cited by in F6Publishing: 64]  [Article Influence: 7.1]  [Reference Citation Analysis (0)]
23.  Rahbari M, Rahbari N, Reissfelder C, Weitz J, Kahlert C. Exosomes: novel implications in diagnosis and treatment of gastrointestinal cancer. Langenbecks Arch Surg. 2016;401:1097-1110.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 20]  [Article Influence: 2.5]  [Reference Citation Analysis (0)]
24.  van Lanschot MC, Carvalho B, Coupé VM, van Engeland M, Dekker E, Meijer GA. Molecular stool testing as an alternative for surveillance colonoscopy: a cross-sectional cohort study. BMC Cancer. 2017;17:116.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 36]  [Cited by in F6Publishing: 31]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
25.  Issa IA, Noureddine M. Colorectal cancer screening: An updated review of the available options. World J Gastroenterol. 2017;23:5086-5096.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 332]  [Cited by in F6Publishing: 338]  [Article Influence: 48.3]  [Reference Citation Analysis (9)]
26.  Norcic G, Jelenc F, Cerkovnik P, Stegel V, Novakovic S. Role of specific DNA mutations in the peripheral blood of colorectal cancer patients for the assessment of tumor stage and residual disease following tumor resection. Oncol Lett. 2016;12:3356-3362.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 6]  [Article Influence: 0.8]  [Reference Citation Analysis (0)]
27.  Klein-Scory S, Maslova M, Pohl M, Eilert-Micus C, Schroers R, Schmiegel W, Baraniskin A. Significance of Liquid Biopsy for Monitoring and Therapy Decision of Colorectal Cancer. Transl Oncol. 2018;11:213-220.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 29]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
28.  Morelli MP, Overman MJ, Dasari A, Kazmi SM, Mazard T, Vilar E, Morris VK, Lee MS, Herron D, Eng C, Morris J, Kee BK, Janku F, Deaton FL, Garrett C, Maru D, Diehl F, Angenendt P, Kopetz S. Characterizing the patterns of clonal selection in circulating tumor DNA from patients with colorectal cancer refractory to anti-EGFR treatment. Ann Oncol. 2015;26:731-736.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 197]  [Cited by in F6Publishing: 188]  [Article Influence: 20.9]  [Reference Citation Analysis (1)]
29.  Diaz LA, Williams RT, Wu J, Kinde I, Hecht JR, Berlin J, Allen B, Bozic I, Reiter JG, Nowak MA, Kinzler KW, Oliner KS, Vogelstein B. The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature. 2012;486:537-540.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1259]  [Cited by in F6Publishing: 1301]  [Article Influence: 108.4]  [Reference Citation Analysis (0)]
30.  Du J, Wu X, Tong X, Wang X, Wei J, Yang Y, Chang Z, Mao Y, Shao YW, Liu B. Circulating tumor DNA profiling by next generation sequencing reveals heterogeneity of crizotinib resistance mechanisms in a gastric cancer patient with MET amplification. Oncotarget. 2017;8:26281-26287.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 17]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
31.  Schøler LV, Reinert T, Ørntoft MW, Kassentoft CG, Árnadóttir SS, Vang S, Nordentoft I, Knudsen M, Lamy P, Andreasen D, Mortensen FV, Knudsen AR, Stribolt K, Sivesgaard K, Mouritzen P, Nielsen HJ, Laurberg S, Ørntoft TF, Andersen CL. Clinical Implications of Monitoring Circulating Tumor DNA in Patients with Colorectal Cancer. Clin Cancer Res. 2017;23:5437-5445.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 151]  [Cited by in F6Publishing: 204]  [Article Influence: 29.1]  [Reference Citation Analysis (0)]
32.  Young GP, Pedersen SK, Mansfield S, Murray DH, Baker RT, Rabbitt P, Byrne S, Bambacas L, Hollington P, Symonds EL. A cross-sectional study comparing a blood test for methylated BCAT1 and IKZF1 tumor-derived DNA with CEA for detection of recurrent colorectal cancer. Cancer Med. 2016;5:2763-2772.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 64]  [Cited by in F6Publishing: 68]  [Article Influence: 8.5]  [Reference Citation Analysis (0)]
33.  Krebs MG, Renehan AG, Backen A, Gollins S, Chau I, Hasan J, Valle JW, Morris K, Beech J, Ashcroft L, Saunders MP, Dive C. Circulating Tumor Cell Enumeration in a Phase II Trial of a Four-Drug Regimen in Advanced Colorectal Cancer. Clin Colorectal Cancer. 2015;14:115-22.e1-2.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39]  [Cited by in F6Publishing: 37]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
34.  Mäbert K, Cojoc M, Peitzsch C, Kurth I, Souchelnytskyi S, Dubrovska A. Cancer biomarker discovery: current status and future perspectives. Int J Radiat Biol. 2014;90:659-677.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 74]  [Cited by in F6Publishing: 79]  [Article Influence: 7.9]  [Reference Citation Analysis (0)]
35.  Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487:330-337.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5743]  [Cited by in F6Publishing: 6208]  [Article Influence: 517.3]  [Reference Citation Analysis (0)]
36.  Cancer Genome Atlas Research Network. Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 2014;513:202-209.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4230]  [Cited by in F6Publishing: 4373]  [Article Influence: 437.3]  [Reference Citation Analysis (2)]
37.  Pino MS, Chung DC. The chromosomal instability pathway in colon cancer. Gastroenterology. 2010;138:2059-2072.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 576]  [Cited by in F6Publishing: 549]  [Article Influence: 39.2]  [Reference Citation Analysis (0)]
38.  Ciombor KK, Wu C, Goldberg RM. Recent therapeutic advances in the treatment of colorectal cancer. Annu Rev Med. 2015;66:83-95.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 127]  [Cited by in F6Publishing: 139]  [Article Influence: 15.4]  [Reference Citation Analysis (0)]
39.  Nagahashi M, Wakai T, Shimada Y, Ichikawa H, Kameyama H, Kobayashi T, Sakata J, Yagi R, Sato N, Kitagawa Y, Uetake H, Yoshida K, Oki E, Kudo SE, Izutsu H, Kodama K, Nakada M, Tse J, Russell M, Heyer J, Powers W, Sun R, Ring JE, Takabe K, Protopopov A, Ling Y, Okuda S, Lyle S. Genomic landscape of colorectal cancer in Japan: clinical implications of comprehensive genomic sequencing for precision medicine. Genome Med. 2016;8:136.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 50]  [Cited by in F6Publishing: 53]  [Article Influence: 6.6]  [Reference Citation Analysis (0)]
40.  Osumi H, Shinozaki E, Takeda Y, Wakatsuki T, Ichimura T, Saiura A, Yamaguchi K, Takahashi S, Noda T, Zembutsu H. Clinical relevance of circulating tumor DNA assessed through deep sequencing in patients with metastatic colorectal cancer. Cancer Med. 2019;8:408-417.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 41]  [Cited by in F6Publishing: 58]  [Article Influence: 9.7]  [Reference Citation Analysis (0)]
41.  Ichikawa H, Nagahashi M, Shimada Y, Hanyu T, Ishikawa T, Kameyama H, Kobayashi T, Sakata J, Yabusaki H, Nakagawa S, Sato N, Hirata Y, Kitagawa Y, Tanahashi T, Yoshida K, Nakanishi R, Oki E, Vuzman D, Lyle S, Takabe K, Ling Y, Okuda S, Akazawa K, Wakai T. Actionable gene-based classification toward precision medicine in gastric cancer. Genome Med. 2017;9:93.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 56]  [Article Influence: 8.0]  [Reference Citation Analysis (0)]
42.  Kakiuchi M, Nishizawa T, Ueda H, Gotoh K, Tanaka A, Hayashi A, Yamamoto S, Tatsuno K, Katoh H, Watanabe Y, Ichimura T, Ushiku T, Funahashi S, Tateishi K, Wada I, Shimizu N, Nomura S, Koike K, Seto Y, Fukayama M, Aburatani H, Ishikawa S. Recurrent gain-of-function mutations of RHOA in diffuse-type gastric carcinoma. Nat Genet. 2014;46:583-587.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 354]  [Cited by in F6Publishing: 387]  [Article Influence: 38.7]  [Reference Citation Analysis (0)]
43.  Wang K, Yuen ST, Xu J, Lee SP, Yan HH, Shi ST, Siu HC, Deng S, Chu KM, Law S, Chan KH, Chan AS, Tsui WY, Ho SL, Chan AK, Man JL, Foglizzo V, Ng MK, Chan AS, Ching YP, Cheng GH, Xie T, Fernandez J, Li VS, Clevers H, Rejto PA, Mao M, Leung SY. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat Genet. 2014;46:573-582.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 694]  [Cited by in F6Publishing: 769]  [Article Influence: 76.9]  [Reference Citation Analysis (0)]
44.  Sawada G, Niida A, Uchi R, Hirata H, Shimamura T, Suzuki Y, Shiraishi Y, Chiba K, Imoto S, Takahashi Y, Iwaya T, Sudo T, Hayashi T, Takai H, Kawasaki Y, Matsukawa T, Eguchi H, Sugimachi K, Tanaka F, Suzuki H, Yamamoto K, Ishii H, Shimizu M, Yamazaki H, Yamazaki M, Tachimori Y, Kajiyama Y, Natsugoe S, Fujita H, Mafune K, Tanaka Y, Kelsell DP, Scott CA, Tsuji S, Yachida S, Shibata T, Sugano S, Doki Y, Akiyama T, Aburatani H, Ogawa S, Miyano S, Mori M, Mimori K. Genomic Landscape of Esophageal Squamous Cell Carcinoma in a Japanese Population. Gastroenterology. 2016;150:1171-1182.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 227]  [Cited by in F6Publishing: 227]  [Article Influence: 28.4]  [Reference Citation Analysis (0)]
45.  Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, Lee W, Yuan J, Wong P, Ho TS, Miller ML, Rekhtman N, Moreira AL, Ibrahim F, Bruggeman C, Gasmi B, Zappasodi R, Maeda Y, Sander C, Garon EB, Merghoub T, Wolchok JD, Schumacher TN, Chan TA. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348:124-128.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6065]  [Cited by in F6Publishing: 5932]  [Article Influence: 659.1]  [Reference Citation Analysis (0)]
46.  McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, Jamal-Hanjani M, Wilson GA, Birkbak NJ, Hiley CT, Watkins TB, Shafi S, Murugaesu N, Mitter R, Akarca AU, Linares J, Marafioti T, Henry JY, Van Allen EM, Miao D, Schilling B, Schadendorf D, Garraway LA, Makarov V, Rizvi NA, Snyder A, Hellmann MD, Merghoub T, Wolchok JD, Shukla SA, Wu CJ, Peggs KS, Chan TA, Hadrup SR, Quezada SA, Swanton C. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351:1463-1469.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2292]  [Cited by in F6Publishing: 2217]  [Article Influence: 277.1]  [Reference Citation Analysis (0)]
47.  Le DT, Durham JN, Smith KN, Wang H, Bartlett BR, Aulakh LK, Lu S, Kemberling H, Wilt C, Luber BS, Wong F, Azad NS, Rucki AA, Laheru D, Donehower R, Zaheer A, Fisher GA, Crocenzi TS, Lee JJ, Greten TF, Duffy AG, Ciombor KK, Eyring AD, Lam BH, Joe A, Kang SP, Holdhoff M, Danilova L, Cope L, Meyer C, Zhou S, Goldberg RM, Armstrong DK, Bever KM, Fader AN, Taube J, Housseau F, Spetzler D, Xiao N, Pardoll DM, Papadopoulos N, Kinzler KW, Eshleman JR, Vogelstein B, Anders RA, Diaz LA. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357:409-413.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3799]  [Cited by in F6Publishing: 4394]  [Article Influence: 627.7]  [Reference Citation Analysis (0)]
48.  Bourdais R, Rousseau B, Pujals A, Boussion H, Joly C, Guillemin A, Baumgaertner I, Neuzillet C, Tournigand C. Polymerase proofreading domain mutations: New opportunities for immunotherapy in hypermutated colorectal cancer beyond MMR deficiency. Crit Rev Oncol Hematol. 2017;113:242-248.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 54]  [Cited by in F6Publishing: 55]  [Article Influence: 7.9]  [Reference Citation Analysis (0)]
49.  Nagarajan N, Bertrand D, Hillmer AM, Zang ZJ, Yao F, Jacques PÉ, Teo AS, Cutcutache I, Zhang Z, Lee WH, Sia YY, Gao S, Ariyaratne PN, Ho A, Woo XY. Veeravali L, Ong CK, Deng N, Desai KV, Khor CC, Hibberd ML, Shahab A, Rao J, Wu M, Teh M, Zhu F, Chin SY, Pang B, So JB, Bourque G, Soong R, Sung WK, Tean Teh B, Rozen S, Ruan X, Yeoh KG, Tan PB, Ruan Y. Whole-genome reconstruction and mutational signatures in gastric cancer. Genome Biol. 2012;13:R115.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 105]  [Cited by in F6Publishing: 114]  [Article Influence: 9.5]  [Reference Citation Analysis (0)]
50.  Huang Z, Zhang L, Zhu D, Shan X, Zhou X, Qi LW, Wu L, Zhu J, Cheng W, Zhang H, Chen Y, Zhu W, Wang T, Liu P. A novel serum microRNA signature to screen esophageal squamous cell carcinoma. Cancer Med. 2017;6:109-119.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 50]  [Cited by in F6Publishing: 62]  [Article Influence: 7.8]  [Reference Citation Analysis (0)]
51.  Zhang H, Zhu M, Shan X, Zhou X, Wang T, Zhang J, Tao J, Cheng W, Chen G, Li J, Liu P, Wang Q, Zhu W. A panel of seven-miRNA signature in plasma as potential biomarker for colorectal cancer diagnosis. Gene. 2019;687:246-254.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 57]  [Cited by in F6Publishing: 86]  [Article Influence: 14.3]  [Reference Citation Analysis (0)]
52.  Vacante M, Borzì AM, Basile F, Biondi A. Biomarkers in colorectal cancer: Current clinical utility and future perspectives. World J Clin Cases. 2018;6:869-881.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 81]  [Cited by in F6Publishing: 91]  [Article Influence: 15.2]  [Reference Citation Analysis (2)]
53.  Matsuoka T, Yashiro M. Biomarkers of gastric cancer: Current topics and future perspective. World J Gastroenterol. 2018;24:2818-2832.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 230]  [Cited by in F6Publishing: 260]  [Article Influence: 43.3]  [Reference Citation Analysis (5)]
54.  Tie J, Gibbs P, Lipton L, Christie M, Jorissen RN, Burgess AW, Croxford M, Jones I, Langland R, Kosmider S, McKay D, Bollag G, Nolop K, Sieber OM, Desai J. Optimizing targeted therapeutic development: analysis of a colorectal cancer patient population with the BRAF(V600E) mutation. Int J Cancer. 2011;128:2075-2084.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 160]  [Cited by in F6Publishing: 179]  [Article Influence: 13.8]  [Reference Citation Analysis (0)]
55.  Van Cutsem E, Karaszewska B, Kang YK, Chung HC, Shankaran V, Siena S, Go NF, Yang H, Schupp M, Cunningham D. A Multicenter Phase II Study of AMG 337 in Patients with MET-Amplified Gastric/Gastroesophageal Junction/Esophageal Adenocarcinoma and Other MET-Amplified Solid Tumors. Clin Cancer Res. 2019;25:2414-2423.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 47]  [Article Influence: 7.8]  [Reference Citation Analysis (0)]
56.  Toledo RA, Garralda E, Mitsi M, Pons T, Monsech J, Vega E, Otero Á, Albarran MI, Baños N, Durán Y, Bonilla V. Sarno F, Camacho-Artacho M, Sanchez-Perez T, Perea S, Álvarez R, De Martino A, Lietha D, Blanco-Aparicio C, Cubillo A, Domínguez O, Martínez-Torrecuadrada JL, Hidalgo M. Exome Sequencing of Plasma DNA Portrays the Mutation Landscape of Colorectal Cancer and Discovers Mutated VEGFR2 Receptors as Modulators of Antiangiogenic Therapies. Clin Cancer Res. 2018;24:3550-3559.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 27]  [Cited by in F6Publishing: 28]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
57.  Pietrantonio F, Di Nicolantonio F, Schrock AB, Lee J, Tejpar S, Sartore-Bianchi A, Hechtman JF, Christiansen J, Novara L, Tebbutt N, Fucà G, Antoniotti C, Kim ST, Murphy D, Berenato R, Morano F, Sun J, Min B, Stephens PJ, Chen M, Lazzari L, Miller VA, Shoemaker R, Amatu A, Milione M, Ross JS, Siena S, Bardelli A, Ali SM, Falcone A, de Braud F, Cremolini C. ALK, ROS1, and NTRK Rearrangements in Metastatic Colorectal Cancer. J Natl Cancer Inst. 2017;109.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 143]  [Cited by in F6Publishing: 157]  [Article Influence: 31.4]  [Reference Citation Analysis (0)]
58.  Papadopoulos N, Nicolaides NC, Wei YF, Ruben SM, Carter KC, Rosen CA, Haseltine WA, Fleischmann RD, Fraser CM, Adams MD. Mutation of a mutL homolog in hereditary colon cancer. Science. 1994;263:1625-1629.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1335]  [Cited by in F6Publishing: 1249]  [Article Influence: 41.6]  [Reference Citation Analysis (0)]
59.  Smyth EC, Wotherspoon A, Peckitt C, Gonzalez D, Hulkki-Wilson S, Eltahir Z, Fassan M, Rugge M, Valeri N, Okines A, Hewish M, Allum W, Stenning S, Nankivell M, Langley R, Cunningham D. Mismatch Repair Deficiency, Microsatellite Instability, and Survival: An Exploratory Analysis of the Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) Trial. JAMA Oncol. 2017;3:1197-1203.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 343]  [Cited by in F6Publishing: 331]  [Article Influence: 47.3]  [Reference Citation Analysis (0)]
60.  Viale G, Trapani D, Curigliano G. Mismatch Repair Deficiency as a Predictive Biomarker for Immunotherapy Efficacy. Biomed Res Int. 2017;2017:4719194.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 61]  [Cited by in F6Publishing: 56]  [Article Influence: 8.0]  [Reference Citation Analysis (0)]
61.  Yu PC, Long D, Liao CC, Zhang S. Association between density of tumor-infiltrating lymphocytes and prognoses of patients with gastric cancer. Medicine (Baltimore). 2018;97:e11387.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 27]  [Article Influence: 4.5]  [Reference Citation Analysis (0)]
62.  Hohenberger W, Weber K, Matzel K, Papadopoulos T, Merkel S. Standardized surgery for colonic cancer: complete mesocolic excision and central ligation--technical notes and outcome. Colorectal Dis. 2009;11:354-64; discussion 364-5.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 990]  [Cited by in F6Publishing: 986]  [Article Influence: 65.7]  [Reference Citation Analysis (0)]
63.  Campos FG, Calijuri-Hamra MC, Imperiale AR, Kiss DR, Nahas SC, Cecconello I. Locally advanced colorectal cancer: results of surgical treatment and prognostic factors. Arq Gastroenterol. 2011;48:270-275.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 19]  [Article Influence: 1.6]  [Reference Citation Analysis (0)]
64.  Shao H, Ma X, Gao Y, Wang J, Wu J, Wang B, Li J, Tian J. Comparison of the diagnostic efficiency for local recurrence of rectal cancer using CT, MRI, PET and PET-CT: A systematic review protocol. Medicine (Baltimore). 2018;97:e12900.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 7]  [Cited by in F6Publishing: 6]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
65.  Olson MT, Ly QP, Mohs AM. Fluorescence Guidance in Surgical Oncology: Challenges, Opportunities, and Translation. Mol Imaging Biol. 2019;21:200-218.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 38]  [Article Influence: 7.6]  [Reference Citation Analysis (0)]
66.  Shen R, Zhang Y, Wang T. Indocyanine Green Fluorescence Angiography and the Incidence of Anastomotic Leak After Colorectal Resection for Colorectal Cancer: A Meta-analysis. Dis Colon Rectum. 2018;61:1228-1234.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 68]  [Cited by in F6Publishing: 73]  [Article Influence: 12.2]  [Reference Citation Analysis (0)]
67.  Chand M, Keller DS, Joshi HM, Devoto L, Rodriguez-Justo M, Cohen R. Feasibility of fluorescence lymph node imaging in colon cancer: FLICC. Tech Coloproctol. 2018;22:271-277.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 44]  [Cited by in F6Publishing: 45]  [Article Influence: 7.5]  [Reference Citation Analysis (0)]
68.  Takeuchi H, Kitagawa Y. Sentinel lymph node biopsy in gastric cancer. Cancer J. 2015;21:21-24.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 29]  [Cited by in F6Publishing: 31]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
69.  Yashiro M, Matsuoka T. Sentinel node navigation surgery for gastric cancer: Overview and perspective. World J Gastrointest Surg. 2015;7:1-9.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 22]  [Cited by in F6Publishing: 21]  [Article Influence: 2.3]  [Reference Citation Analysis (0)]
70.  Takeuchi H, Kawakubo H, Nakamura R, Fukuda K, Takahashi T, Wada N, Kitagawa Y. Clinical Significance of Sentinel Node Positivity in Patients with Superficial Esophageal Cancer. World J Surg. 2015;39:2941-2947.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 14]  [Cited by in F6Publishing: 12]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
71.  Takeuchi M, Takeuchi H, Kawakubo H, Kitagawa Y. Update on the indications and results of sentinel node mapping in upper GI cancer. Clin Exp Metastasis. 2018;35:455-461.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 7]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
72.  Roth AD, Tejpar S, Delorenzi M, Yan P, Fiocca R, Klingbiel D, Dietrich D, Biesmans B, Bodoky G, Barone C, Aranda E, Nordlinger B, Cisar L, Labianca R, Cunningham D, Van Cutsem E, Bosman F. Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60-00 trial. J Clin Oncol. 2010;28:466-474.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 801]  [Cited by in F6Publishing: 886]  [Article Influence: 59.1]  [Reference Citation Analysis (0)]
73.  Lin M, Gao M, Cavnar MJ, Kim J. Utilizing gastric cancer organoids to assess tumor biology and personalize medicine. World J Gastrointest Oncol. 2019;11:509-517.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 16]  [Cited by in F6Publishing: 16]  [Article Influence: 3.2]  [Reference Citation Analysis (1)]
74.  Gao M, Lin M, Rao M, Thompson H, Hirai K, Choi M, Georgakis GV, Sasson AR, Bucobo JC, Tzimas D, D'Souza LS, Buscaglia JM, Davis J, Shroyer KR, Li J, Powers S, Kim J. Development of Patient-Derived Gastric Cancer Organoids from Endoscopic Biopsies and Surgical Tissues. Ann Surg Oncol. 2018;25:2767-2775.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 34]  [Cited by in F6Publishing: 44]  [Article Influence: 7.3]  [Reference Citation Analysis (0)]
75.  Post JB, Hami N, Mertens AEE, Elfrink S, Bos JL, Snippert HJG. CRISPR-induced RASGAP deficiencies in colorectal cancer organoids reveal that only loss of NF1 promotes resistance to EGFR inhibition. Oncotarget. 2019;10:1440-1457.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 15]  [Article Influence: 3.0]  [Reference Citation Analysis (0)]
76.  Xiong T, Wang M, Zhao J, Liu Q, Yang C, Luo W, Li X, Yang H, Kristiansen K, Roy B, Zhou Y. An esophageal squamous cell carcinoma classification system that reveals potential targets for therapy. Oncotarget. 2017;8:49851-49860.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 14]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
77.  Guinney J, Dienstmann R, Wang X, de Reyniès A, Schlicker A, Soneson C, Marisa L, Roepman P, Nyamundanda G, Angelino P, Bot BM, Morris JS, Simon IM, Gerster S, Fessler E, De Sousa E Melo F, Missiaglia E, Ramay H, Barras D, Homicsko K, Maru D, Manyam GC, Broom B, Boige V, Perez-Villamil B, Laderas T, Salazar R, Gray JW, Hanahan D, Tabernero J, Bernards R, Friend SH, Laurent-Puig P, Medema JP, Sadanandam A, Wessels L, Delorenzi M, Kopetz S, Vermeulen L, Tejpar S. The consensus molecular subtypes of colorectal cancer. Nat Med. 2015;21:1350-1356.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3408]  [Cited by in F6Publishing: 3091]  [Article Influence: 343.4]  [Reference Citation Analysis (0)]
78.  Loree JM, Pereira AAL, Lam M, Willauer AN, Raghav K, Dasari A, Morris VK, Advani S, Menter DG, Eng C, Shaw K, Broaddus R, Routbort MJ, Liu Y, Morris JS, Luthra R, Meric-Bernstam F, Overman MJ, Maru D, Kopetz S. Classifying Colorectal Cancer by Tumor Location Rather than Sidedness Highlights a Continuum in Mutation Profiles and Consensus Molecular Subtypes. Clin Cancer Res. 2018;24:1062-1072.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 145]  [Cited by in F6Publishing: 189]  [Article Influence: 27.0]  [Reference Citation Analysis (0)]
79.  Isella C, Brundu F, Bellomo SE, Galimi F, Zanella E, Porporato R, Petti C, Fiori A, Orzan F, Senetta R, Boccaccio C, Ficarra E, Marchionni L, Trusolino L, Medico E, Bertotti A. Selective analysis of cancer-cell intrinsic transcriptional traits defines novel clinically relevant subtypes of colorectal cancer. Nat Commun. 2017;8:15107.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 156]  [Cited by in F6Publishing: 183]  [Article Influence: 26.1]  [Reference Citation Analysis (0)]
80.  Linnekamp JF, Hooff SRV, Prasetyanti PR, Kandimalla R, Buikhuisen JY, Fessler E, Ramesh P, Lee KAST, Bochove GGW, de Jong JH, Cameron K, Leersum RV, Rodermond HM, Franitza M, Nürnberg P, Mangiapane LR, Wang X, Clevers H, Vermeulen L, Stassi G, Medema JP. Consensus molecular subtypes of colorectal cancer are recapitulated in in vitro and in vivo models. Cell Death Differ. 2018;25:616-633.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 100]  [Cited by in F6Publishing: 105]  [Article Influence: 17.5]  [Reference Citation Analysis (0)]
81.  Okita A, Takahashi S, Ouchi K, Inoue M, Watanabe M, Endo M, Honda H, Yamada Y, Ishioka C. Consensus molecular subtypes classification of colorectal cancer as a predictive factor for chemotherapeutic efficacy against metastatic colorectal cancer. Oncotarget. 2018;9:18698-18711.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 119]  [Cited by in F6Publishing: 105]  [Article Influence: 17.5]  [Reference Citation Analysis (0)]
82.  Li SP, Guan QL, Zhao D, Pei GJ, Su HX, Du LN, He JX, Liu ZC. Detection of Circulating Tumor Cells by Fluorescent Immunohistochemistry in Patients with Esophageal Squamous Cell Carcinoma: Potential Clinical Applications. Med Sci Monit. 2016;22:1654-1662.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 7]  [Article Influence: 0.9]  [Reference Citation Analysis (0)]
83.  Han L, Li YJ, Zhang WD, Song PP, Li H, Li S. Clinical significance of tumor cells in the peripheral blood of patients with esophageal squamous cell carcinoma. Medicine (Baltimore). 2019;98:e13921.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 6]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
84.  Kang HM, Kim GH, Jeon HK, Kim DH, Jeon TY, Park DY, Jeong H, Chun WJ, Kim MH, Park J, Lim M, Kim TH, Cho YK. Circulating tumor cells detected by lab-on-a-disc: Role in early diagnosis of gastric cancer. PLoS One. 2017;12:e0180251.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 45]  [Cited by in F6Publishing: 45]  [Article Influence: 6.4]  [Reference Citation Analysis (0)]
85.  Zheng X, Fan L, Zhou P, Ma H, Huang S, Yu D, Zhao L, Yang S, Liu J, Huang A, Cai C, Dai X, Zhang T. Detection of Circulating Tumor Cells and Circulating Tumor Microemboli in Gastric Cancer. Transl Oncol. 2017;10:431-441.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 29]  [Cited by in F6Publishing: 33]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
86.  Mishima Y, Matsusaka S, Chin K, Mikuniya M, Minowa S, Takayama T, Shibata H, Kuniyoshi R, Ogura M, Terui Y, Mizunuma N, Hatake K. Detection of HER2 Amplification in Circulating Tumor Cells of HER2-Negative Gastric Cancer Patients. Target Oncol. 2017;12:341-351.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 28]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
87.  Wang L, Zhou S, Zhang W, Wang J, Wang M, Hu X, Liu F, Zhang Y, Jiang B, Yuan H. Circulating tumor cells as an independent prognostic factor in advanced colorectal cancer: a retrospective study in 121 patients. Int J Colorectal Dis. 2019;34:589-597.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 19]  [Cited by in F6Publishing: 22]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
88.  Luo H, Li H, Hu Z, Wu H, Liu C, Li Y, Zhang X, Lin P, Hou Q, Ding G, Wang Y, Li S, Wei D, Qiu F, Li Y, Wu S. Noninvasive diagnosis and monitoring of mutations by deep sequencing of circulating tumor DNA in esophageal squamous cell carcinoma. Biochem Biophys Res Commun. 2016;471:596-602.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 35]  [Cited by in F6Publishing: 38]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
89.  Ueda M, Iguchi T, Masuda T, Nakahara Y, Hirata H, Uchi R, Niida A, Momose K, Sakimura S, Chiba K, Eguchi H, Ito S, Sugimachi K, Yamasaki M, Suzuki Y, Miyano S, Doki Y, Mori M, Mimori K. Somatic mutations in plasma cell-free DNA are diagnostic markers for esophageal squamous cell carcinoma recurrence. Oncotarget. 2016;7:62280-62291.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 51]  [Cited by in F6Publishing: 52]  [Article Influence: 8.7]  [Reference Citation Analysis (0)]
90.  Komatsu S, Ichikawa D, Hirajima S, Takeshita H, Shiozaki A, Fujiwara H, Kawaguchi T, Miyamae M, Konishi H, Kubota T, Okamoto K, Yagi N, Otsuji E. Clinical impact of predicting CCND1 amplification using plasma DNA in superficial esophageal squamous cell carcinoma. Dig Dis Sci. 2014;59:1152-1159.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 11]  [Article Influence: 1.1]  [Reference Citation Analysis (0)]
91.  Kim ST, Banks KC, Pectasides E, Kim SY, Kim K, Lanman RB, Talasaz A, An J, Choi MG, Lee JH, Sohn TS, Bae JM, Kim S, Park SH, Park JO, Park YS, Lim HY, Kim NKD, Park W, Lee H, Bass AJ, Kim K, Kang WK, Lee J. Impact of genomic alterations on lapatinib treatment outcome and cell-free genomic landscape during HER2 therapy in HER2+ gastric cancer patients. Ann Oncol. 2018;29:1037-1048.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 64]  [Cited by in F6Publishing: 76]  [Article Influence: 15.2]  [Reference Citation Analysis (0)]
92.  Kato S, Okamura R, Baumgartner JM, Patel H, Leichman L, Kelly K, Sicklick JK, Fanta PT, Lippman SM, Kurzrock R. Analysis of Circulating Tumor DNA and Clinical Correlates in Patients with Esophageal, Gastroesophageal Junction, and Gastric Adenocarcinoma. Clin Cancer Res. 2018;24:6248-6256.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 64]  [Cited by in F6Publishing: 77]  [Article Influence: 12.8]  [Reference Citation Analysis (0)]
93.  Gao J, Wang H, Zang W, Li B, Rao G, Li L, Yu Y, Li Z, Dong B, Lu Z, Jiang Z, Shen L. Circulating tumor DNA functions as an alternative for tissue to overcome tumor heterogeneity in advanced gastric cancer. Cancer Sci. 2017;108:1881-1887.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 40]  [Cited by in F6Publishing: 47]  [Article Influence: 6.7]  [Reference Citation Analysis (0)]
94.  Shoda K, Ichikawa D, Fujita Y, Masuda K, Hiramoto H, Hamada J, Arita T, Konishi H, Komatsu S, Shiozaki A, Kakihara N, Okamoto K, Taniguchi H, Imoto I, Otsuji E. Monitoring the HER2 copy number status in circulating tumor DNA by droplet digital PCR in patients with gastric cancer. Gastric Cancer. 2017;20:126-135.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 83]  [Cited by in F6Publishing: 95]  [Article Influence: 13.6]  [Reference Citation Analysis (0)]
95.  Tie J, Wang Y, Tomasetti C, Li L, Springer S, Kinde I, Silliman N, Tacey M, Wong HL, Christie M, Kosmider S, Skinner I, Wong R, Steel M, Tran B, Desai J, Jones I, Haydon A, Hayes T, Price TJ, Strausberg RL, Diaz LA, Papadopoulos N, Kinzler KW, Vogelstein B, Gibbs P. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci Transl Med. 2016;8:346ra92.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 729]  [Cited by in F6Publishing: 905]  [Article Influence: 129.3]  [Reference Citation Analysis (0)]
96.  Furuki H, Yamada T, Takahashi G, Iwai T, Koizumi M, Shinji S, Yokoyama Y, Takeda K, Taniai N, Uchida E. Evaluation of liquid biopsies for detection of emerging mutated genes in metastatic colorectal cancer. Eur J Surg Oncol. 2018;44:975-982.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 29]  [Article Influence: 4.8]  [Reference Citation Analysis (0)]
97.  Vandeputte C, Kehagias P, El Housni H, Ameye L, Laes JF, Desmedt C, Sotiriou C, Deleporte A, Puleo F, Geboes K, Delaunoit T, Demolin G, Peeters M, D'Hondt L, Janssens J, Carrasco J, Marechal R, Galdon MG, Heimann P, Paesmans M, Flamen P, Hendlisz A. Circulating tumor DNA in early response assessment and monitoring of advanced colorectal cancer treated with a multi-kinase inhibitor. Oncotarget. 2018;9:17756-17769.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23]  [Cited by in F6Publishing: 28]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
98.  Oh TJ, Oh HI, Seo YY, Jeong D, Kim C, Kang HW, Han YD, Chung HC, Kim NK, An S. Feasibility of quantifying SDC2 methylation in stool DNA for early detection of colorectal cancer. Clin Epigenetics. 2017;9:126.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 49]  [Cited by in F6Publishing: 62]  [Article Influence: 8.9]  [Reference Citation Analysis (0)]
99.  Faluyi OO, Eng L, Qiu X, Che J, Zhang Q, Cheng D, Ying N, Tse A, Kuang Q, Dodbiba L, Renouf DJ, Marsh S, Savas S, Mackay HJ, Knox JJ, Darling GE, Wong RK, Xu W, Azad AK, Liu G. Validation of microRNA pathway polymorphisms in esophageal adenocarcinoma survival. Cancer Med. 2017;6:361-373.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 9]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
100.  Yao C, Liu HN, Wu H, Chen YJ, Li Y, Fang Y, Shen XZ, Liu TT. Diagnostic and Prognostic Value of Circulating MicroRNAs for Esophageal Squamous Cell Carcinoma: a Systematic Review and Meta-analysis. J Cancer. 2018;9:2876-2884.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 6]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
101.  Zhang L, Dong B, Ren P, Ye H, Shi J, Qin J, Wang K, Wang P, Zhang J. Circulating plasma microRNAs in the detection of esophageal squamous cell carcinoma. Oncol Lett. 2018;16:3303-3318.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 13]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]
102.  Virgilio E, Giarnieri E, Giovagnoli MR, Montagnini M, Proietti A, D'Urso R, Mercantini P, Balducci G, Cavallini M. Gastric Juice MicroRNAs as Potential Biomarkers for Screening Gastric Cancer: A Systematic Review. Anticancer Res. 2018;38:613-616.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 15]  [Article Influence: 2.5]  [Reference Citation Analysis (0)]
103.  Sierzega M, Kaczor M, Kolodziejczyk P, Kulig J, Sanak M, Richter P. Evaluation of serum microRNA biomarkers for gastric cancer based on blood and tissue pools profiling: the importance of miR-21 and miR-331. Br J Cancer. 2017;117:266-273.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 64]  [Cited by in F6Publishing: 71]  [Article Influence: 10.1]  [Reference Citation Analysis (0)]
104.  Zhu Y, Peng Q, Lin Y, Zou L, Shen P, Chen F, Min M, Shen L, Chen J, Shen B. Identification of biomarker microRNAs for predicting the response of colorectal cancer to neoadjuvant chemoradiotherapy based on microRNA regulatory network. Oncotarget. 2017;8:2233-2248.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 31]  [Cited by in F6Publishing: 33]  [Article Influence: 5.5]  [Reference Citation Analysis (0)]
105.  Carter JV, Galbraith NJ, Yang D, Burton JF, Walker SP, Galandiuk S. Blood-based microRNAs as biomarkers for the diagnosis of colorectal cancer: a systematic review and meta-analysis. Br J Cancer. 2017;116:762-774.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 76]  [Cited by in F6Publishing: 97]  [Article Influence: 13.9]  [Reference Citation Analysis (0)]
106.  Ulivi P, Canale M, Passardi A, Marisi G, Valgiusti M, Frassineti GL, Calistri D, Amadori D, Scarpi E. Circulating Plasma Levels of miR-20b, miR-29b and miR-155 as Predictors of Bevacizumab Efficacy in Patients with Metastatic Colorectal Cancer. Int J Mol Sci. 2018;19.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 41]  [Cited by in F6Publishing: 46]  [Article Influence: 7.7]  [Reference Citation Analysis (0)]
107.  Matsumoto Y, Kano M, Akutsu Y, Hanari N, Hoshino I, Murakami K, Usui A, Suito H, Takahashi M, Otsuka R, Xin H, Komatsu A, Iida K, Matsubara H. Quantification of plasma exosome is a potential prognostic marker for esophageal squamous cell carcinoma. Oncol Rep. 2016;36:2535-2543.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 80]  [Cited by in F6Publishing: 68]  [Article Influence: 8.5]  [Reference Citation Analysis (0)]
108.  Tokuhisa M, Ichikawa Y, Kosaka N, Ochiya T, Yashiro M, Hirakawa K, Kosaka T, Makino H, Akiyama H, Kunisaki C, Endo I. Exosomal miRNAs from Peritoneum Lavage Fluid as Potential Prognostic Biomarkers of Peritoneal Metastasis in Gastric Cancer. PLoS One. 2015;10:e0130472.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 115]  [Cited by in F6Publishing: 127]  [Article Influence: 14.1]  [Reference Citation Analysis (0)]
109.  Kumata Y, Iinuma H, Suzuki Y, Tsukahara D, Midorikawa H, Igarashi Y, Soeda N, Kiyokawa T, Horikawa M, Fukushima R. Exosomeencapsulated microRNA23b as a minimally invasive liquid biomarker for the prediction of recurrence and prognosis of gastric cancer patients in each tumor stage. Oncol Rep. 2018;40:319-330.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 19]  [Cited by in F6Publishing: 30]  [Article Influence: 5.0]  [Reference Citation Analysis (0)]
110.  Matsumura T, Sugimachi K, Iinuma H, Takahashi Y, Kurashige J, Sawada G, Ueda M, Uchi R, Ueo H, Takano Y, Shinden Y, Eguchi H, Yamamoto H, Doki Y, Mori M, Ochiya T, Mimori K. Exosomal microRNA in serum is a novel biomarker of recurrence in human colorectal cancer. Br J Cancer. 2015;113:275-281.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 332]  [Cited by in F6Publishing: 372]  [Article Influence: 41.3]  [Reference Citation Analysis (0)]
111.  Peng ZY, Gu RH, Yan B. Downregulation of exosome-encapsulated miR-548c-5p is associated with poor prognosis in colorectal cancer. J Cell Biochem.  2018.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 57]  [Cited by in F6Publishing: 66]  [Article Influence: 13.2]  [Reference Citation Analysis (0)]
112.  Pasternack H, Fassunke J, Plum PS, Chon SH, Hescheler DA, Gassa A, Merkelbach-Bruse S, Bruns CJ, Perner S, Hallek M, Büttner R, Bollschweiler E, Hölscher AH, Quaas A, Zander T, Weiss J, Alakus H. Somatic alterations in circulating cell-free DNA of oesophageal carcinoma patients during primary staging are indicative for post-surgical tumour recurrence. Sci Rep. 2018;8:14941.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 11]  [Cited by in F6Publishing: 13]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]
113.  Yoshida T, Yamaguchi T, Maekawa S, Takano S, Kuno T, Tanaka K, Iwamoto F, Tsukui Y, Kobayashi S, Asakawa Y, Shindo H, Fukasawa M, Nakayama Y, Inoue T, Uetake T, Ohtaka M, Sato T, Mochizuki K, Enomoto N. Identification of early genetic changes in well-differentiated intramucosal gastric carcinoma by target deep sequencing. Gastric Cancer. 2019;22:742-750.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 13]  [Cited by in F6Publishing: 13]  [Article Influence: 2.6]  [Reference Citation Analysis (0)]
114.  Capalbo C, Belardinilli F, Raimondo D, Milanetti E, Malapelle U, Pisapia P, Magri V, Prete A, Pecorari S, Colella M, Coppa A, Bonfiglio C, Nicolussi A, Valentini V, Tessitore A, Cardinali B, Petroni M, Infante P, Santoni M, Filetti M, Colicchia V, Paci P, Mezi S, Longo F, Cortesi E, Marchetti P, Troncone G, Bellavia D, Canettieri G, Giannini G. A Simplified Genomic Profiling Approach Predicts Outcome in Metastatic Colorectal Cancer. Cancers (Basel). 2019;11.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 9]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
115.  Wang Y, Liu H, Hou Y, Zhou X, Liang L, Zhang Z, Shi H, Xu S, Hu P, Zheng Z, Liu R, Tang T, Ye F, Liang Z, Bu H. Performance validation of an amplicon-based targeted next-generation sequencing assay and mutation profiling of 648 Chinese colorectal cancer patients. Virchows Arch. 2018;472:959-968.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 10]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
116.  Gao XH, Yu GY, Hong YG, Lian W, Chouhan H, Xu Y, Liu LJ, Bai CG, Zhang W. Clinical significance of multiple gene detection with a 22-gene panel in formalin-fixed paraffin-embedded specimens of 207 colorectal cancer patients. Int J Clin Oncol. 2019;24:141-152.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10]  [Cited by in F6Publishing: 10]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
117.  Seifert BA, McGlaughon JL, Jackson SA, Ritter DI, Roberts ME, Schmidt RJ, Thompson BA, Jimenez S, Trapp M, Lee K, Plon SE, Offit K, Stadler ZK, Zhang L, Greenblatt MS, Ferber MJ. Determining the clinical validity of hereditary colorectal cancer and polyposis susceptibility genes using the Clinical Genome Resource Clinical Validity Framework. Genet Med. 2019;21:1507-1516.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 19]  [Cited by in F6Publishing: 16]  [Article Influence: 3.2]  [Reference Citation Analysis (0)]
118.  Bang YJ, Van Cutsem E, Feyereislova A, Chung HC, Shen L, Sawaki A, Lordick F, Ohtsu A, Omuro Y, Satoh T, Aprile G, Kulikov E, Hill J, Lehle M, Rüschoff J, Kang YK; ToGA Trial Investigators. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet. 2010;376:687-697.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4615]  [Cited by in F6Publishing: 4894]  [Article Influence: 349.6]  [Reference Citation Analysis (1)]
119.  Sartore-Bianchi A, Trusolino L, Martino C, Bencardino K, Lonardi S, Bergamo F, Zagonel V, Leone F, Depetris I, Martinelli E, Troiani T, Ciardiello F, Racca P, Bertotti A, Siravegna G, Torri V, Amatu A, Ghezzi S, Marrapese G, Palmeri L, Valtorta E, Cassingena A, Lauricella C, Vanzulli A, Regge D, Veronese S, Comoglio PM, Bardelli A, Marsoni S, Siena S. Dual-targeted therapy with trastuzumab and lapatinib in treatment-refractory, KRAS codon 12/13 wild-type, HER2-positive metastatic colorectal cancer (HERACLES): a proof-of-concept, multicentre, open-label, phase 2 trial. Lancet Oncol. 2016;17:738-746.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 549]  [Cited by in F6Publishing: 654]  [Article Influence: 81.8]  [Reference Citation Analysis (0)]
120.  Wormald S, Milla L, O'Connor L. Association of candidate single nucleotide polymorphisms with somatic mutation of the epidermal growth factor receptor pathway. BMC Med Genomics. 2013;6:43.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 6]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
121.  Febbo PG, Ladanyi M, Aldape KD, De Marzo AM, Hammond ME, Hayes DF, Iafrate AJ, Kelley RK, Marcucci G, Ogino S, Pao W, Sgroi DC, Birkeland ML. NCCN Task Force report: Evaluating the clinical utility of tumor markers in oncology. J Natl Compr Canc Netw. 2011;9 Suppl 5:S1-32; quiz S33.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 167]  [Cited by in F6Publishing: 199]  [Article Influence: 16.6]  [Reference Citation Analysis (0)]
122.  Schmoll HJ, Van Cutsem E, Stein A, Valentini V, Glimelius B, Haustermans K, Nordlinger B, van de Velde CJ, Balmana J, Regula J, Nagtegaal ID, Beets-Tan RG, Arnold D, Ciardiello F, Hoff P, Kerr D, Köhne CH, Labianca R, Price T, Scheithauer W, Sobrero A, Tabernero J, Aderka D, Barroso S, Bodoky G, Douillard JY, El Ghazaly H, Gallardo J, Garin A, Glynne-Jones R, Jordan K, Meshcheryakov A, Papamichail D, Pfeiffer P, Souglakos I, Turhal S, Cervantes A. ESMO Consensus Guidelines for management of patients with colon and rectal cancer. a personalized approach to clinical decision making. Ann Oncol. 2012;23:2479-2516.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1035]  [Cited by in F6Publishing: 1047]  [Article Influence: 87.3]  [Reference Citation Analysis (1)]
123.  Locker GY, Hamilton S, Harris J, Jessup JM, Kemeny N, Macdonald JS, Somerfield MR, Hayes DF, Bast RC; ASCO. ASCO 2006 update of recommendations for the use of tumor markers in gastrointestinal cancer. J Clin Oncol. 2006;24:5313-5327.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1057]  [Cited by in F6Publishing: 1042]  [Article Influence: 57.9]  [Reference Citation Analysis (0)]
124.  Hu Y, Tao SY, Deng JM, Hou ZK, Liang JQ, Huang QG, Li LH, Li HB, Chen YM, Yi H, Chen XL, Liu H. Prognostic Value of NRAS Gene for Survival of Colorectal Cancer Patients: A Systematic Review and Meta-Analysis. Asian Pac J Cancer Prev. 2018;19:3001-3008.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 7]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
125.  Loaiza-Bonilla A, Jensen CE, Shroff S, Furth E, Bonilla-Reyes PA, Deik AF, Morrissette J. KDR Mutation as a Novel Predictive Biomarker of Exceptional Response to Regorafenib in Metastatic Colorectal Cancer. Cureus. 2016;8:e478.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 7]  [Cited by in F6Publishing: 11]  [Article Influence: 1.4]  [Reference Citation Analysis (0)]
126.  Tabernero J, Hozak RR, Yoshino T, Cohn AL, Obermannova R, Bodoky G, Garcia-Carbonero R, Ciuleanu TE, Portnoy DC, Prausová J, Muro K, Siegel RW, Konrad RJ, Ouyang H, Melemed SA, Ferry D, Nasroulah F, Van Cutsem E. Analysis of angiogenesis biomarkers for ramucirumab efficacy in patients with metastatic colorectal cancer from RAISE, a global, randomized, double-blind, phase III study. Ann Oncol. 2018;29:602-609.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 76]  [Cited by in F6Publishing: 73]  [Article Influence: 12.2]  [Reference Citation Analysis (0)]
127.  Ito C, Nishizuka SS, Ishida K, Uesugi N, Sugai T, Tamura G, Koeda K, Sasaki A. Analysis of PIK3CA mutations and PI3K pathway proteins in advanced gastric cancer. J Surg Res. 2017;212:195-204.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 17]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
128.  Kim C, Lee CK, Chon HJ, Kim JH, Park HS, Heo SJ, Kim HJ, Kim TS, Kwon WS, Chung HC, Rha SY. PTEN loss and level of HER2 amplification is associated with trastuzumab resistance and prognosis in HER2-positive gastric cancer. Oncotarget. 2017;8:113494-113501.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23]  [Cited by in F6Publishing: 31]  [Article Influence: 4.4]  [Reference Citation Analysis (0)]
129.  Drilon A, Laetsch TW, Kummar S, DuBois SG, Lassen UN, Demetri GD, Nathenson M, Doebele RC, Farago AF, Pappo AS, Turpin B, Dowlati A, Brose MS, Mascarenhas L, Federman N, Berlin J, El-Deiry WS, Baik C, Deeken J, Boni V, Nagasubramanian R, Taylor M, Rudzinski ER, Meric-Bernstam F, Sohal DPS, Ma PC, Raez LE, Hechtman JF, Benayed R, Ladanyi M, Tuch BB, Ebata K, Cruickshank S, Ku NC, Cox MC, Hawkins DS, Hong DS, Hyman DM. Efficacy of Larotrectinib in TRK Fusion-Positive Cancers in Adults and Children. N Engl J Med. 2018;378:731-739.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1577]  [Cited by in F6Publishing: 1704]  [Article Influence: 284.0]  [Reference Citation Analysis (0)]
130.  Domingo E, Freeman-Mills L, Rayner E, Glaire M, Briggs S, Vermeulen L, Fessler E, Medema JP, Boot A, Morreau H, van Wezel T, Liefers GJ, Lothe RA, Danielsen SA, Sveen A, Nesbakken A, Zlobec I, Lugli A, Koelzer VH, Berger MD, Castellví-Bel S, Muñoz J; Epicolon consortium, de Bruyn M, Nijman HW, Novelli M, Lawson K, Oukrif D, Frangou E, Dutton P, Tejpar S, Delorenzi M, Kerr R, Kerr D, Tomlinson I, Church DN. Somatic POLE proofreading domain mutation, immune response, and prognosis in colorectal cancer: a retrospective, pooled biomarker study. Lancet Gastroenterol Hepatol. 2016;1:207-216.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 212]  [Cited by in F6Publishing: 201]  [Article Influence: 25.1]  [Reference Citation Analysis (0)]
131.  Llosa NJ, Cruise M, Tam A, Wicks EC, Hechenbleikner EM, Taube JM, Blosser RL, Fan H, Wang H, Luber BS, Zhang M, Papadopoulos N, Kinzler KW, Vogelstein B, Sears CL, Anders RA, Pardoll DM, Housseau F. The vigorous immune microenvironment of microsatellite instable colon cancer is balanced by multiple counter-inhibitory checkpoints. Cancer Discov. 2015;5:43-51.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 889]  [Cited by in F6Publishing: 1057]  [Article Influence: 105.7]  [Reference Citation Analysis (0)]
132.  Eriksen AC, Sørensen FB, Lindebjerg J, Hager H, dePont Christensen R, Kjær-Frifeldt S, Hansen TF. Programmed Death Ligand-1 expression in stage II colon cancer - experiences from a nationwide populationbased cohort. BMC Cancer. 2019;19:142.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 20]  [Article Influence: 4.0]  [Reference Citation Analysis (0)]
133.  Iseki Y, Shibutani M, Maeda K, Nagahara H, Fukuoka T, Matsutani S, Kashiwagi S, Tanaka H, Hirakawa K, Ohira M. A new method for evaluating tumor-infiltrating lymphocytes (TILs) in colorectal cancer using hematoxylin and eosin (H-E)-stained tumor sections. PLoS One. 2018;13:e0192744.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 27]  [Article Influence: 4.5]  [Reference Citation Analysis (0)]
134.  Saju P, Murata-Kamiya N, Hayashi T, Senda Y, Nagase L, Noda S, Matsusaka K, Funata S, Kunita A, Urabe M, Seto Y, Fukayama M, Kaneda A, Hatakeyama M. Host SHP1 phosphatase antagonizes Helicobacter pylori CagA and can be downregulated by Epstein-Barr virus. Nat Microbiol. 2016;1:16026.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 59]  [Cited by in F6Publishing: 66]  [Article Influence: 8.3]  [Reference Citation Analysis (0)]
135.  Altieri F, Di Stadio CS, Federico A, Miselli G, De Palma M, Rippa E, Arcari P. Epigenetic alterations of gastrokine 1 gene expression in gastric cancer. Oncotarget. 2017;8:16899-16911.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 18]  [Article Influence: 2.6]  [Reference Citation Analysis (0)]
136.  Martinelli E, Morgillo F, Troiani T, Ciardiello F. Cancer resistance to therapies against the EGFR-RAS-RAF pathway: The role of MEK. Cancer Treat Rev. 2017;53:61-69.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 76]  [Cited by in F6Publishing: 95]  [Article Influence: 11.9]  [Reference Citation Analysis (0)]
137.  Jehan Z, Bavi P, Sultana M, Abubaker J, Bu R, Hussain A, Alsbeih G, Al-Sanea N, Abduljabbar A, Ashari LH, Alhomoud S, Al-Dayel F, Uddin S, Al-Kuraya KS. Frequent PIK3CA gene amplification and its clinical significance in colorectal cancer. J Pathol. 2009;219:337-346.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 41]  [Cited by in F6Publishing: 44]  [Article Influence: 3.1]  [Reference Citation Analysis (0)]
138.  Guo J, Yu W, Su H, Pang X. Genomic landscape of gastric cancer: molecular classification and potential targets. Sci China Life Sci. 2017;60:126-137.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 15]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]
139.  Szász AM, Lánczky A, Nagy Á, Förster S, Hark K, Green JE, Boussioutas A, Busuttil R, Szabó A, Győrffy B. Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients. Oncotarget. 2016;7:49322-49333.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 582]  [Cited by in F6Publishing: 733]  [Article Influence: 122.2]  [Reference Citation Analysis (0)]
140.  Ishiguro H, Wakasugi T, Terashita Y, Sakamoto N, Tanaka T, Mizoguchi K, Sagawa H, Okubo T, Takeyama H. Decreased expression of CDH1 or CTNNB1 affects poor prognosis of patients with esophageal cancer. World J Surg Oncol. 2016;14:240.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 8]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
141.  Liang TJ, Wang HX, Zheng YY, Cao YQ, Wu X, Zhou X, Dong SX. APC hypermethylation for early diagnosis of colorectal cancer: a meta-analysis and literature review. Oncotarget. 2017;8:46468-46479.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 36]  [Cited by in F6Publishing: 39]  [Article Influence: 6.5]  [Reference Citation Analysis (0)]
142.  Chen TH, Chang SW, Huang CC, Wang KL, Yeh KT, Liu CN, Lee H, Lin CC, Cheng YW. The prognostic significance of APC gene mutation and miR-21 expression in advanced-stage colorectal cancer. Colorectal Dis. 2013;15:1367-1374.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 46]  [Cited by in F6Publishing: 54]  [Article Influence: 4.9]  [Reference Citation Analysis (0)]
143.  Codony-Servat J, Cuatrecasas M, Asensio E, Montironi C, Martínez-Cardús A, Marín-Aguilera M, Horndler C, Martínez-Balibrea E, Rubini M, Jares P, Reig O, Victoria I, Gaba L, Martín-Richard M, Alonso V, Escudero P, Fernández-Martos C, Feliu J, Méndez JC, Méndez M, Gallego J, Salud A, Rojo F, Castells A, Prat A, Rosell R, García-Albéniz X, Camps J, Maurel J. Nuclear IGF-1R predicts chemotherapy and targeted therapy resistance in metastatic colorectal cancer. Br J Cancer. 2017;117:1777-1786.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 45]  [Cited by in F6Publishing: 46]  [Article Influence: 6.6]  [Reference Citation Analysis (0)]
144.  Tang D, Liu J, Wang DR, Yu HF, Li YK, Zhang JQ. Diagnostic and prognostic value of the methylation status of secreted frizzled-related protein 2 in colorectal cancer. Clin Invest Med. 2011;34:E88-E95.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 61]  [Cited by in F6Publishing: 60]  [Article Influence: 4.6]  [Reference Citation Analysis (0)]
145.  Crea F, Nobili S, Paolicchi E, Perrone G, Napoli C, Landini I, Danesi R, Mini E. Epigenetics and chemoresistance in colorectal cancer: an opportunity for treatment tailoring and novel therapeutic strategies. Drug Resist Updat. 2011;14:280-296.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 83]  [Cited by in F6Publishing: 97]  [Article Influence: 7.5]  [Reference Citation Analysis (0)]
146.  Salem ME, Puccini A, Xiu J, Raghavan D, Lenz HJ, Korn WM, Shields AF, Philip PA, Marshall JL, Goldberg RM. Comparative Molecular Analyses of Esophageal Squamous Cell Carcinoma, Esophageal Adenocarcinoma, and Gastric Adenocarcinoma. Oncologist. 2018;23:1319-1327.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 105]  [Cited by in F6Publishing: 118]  [Article Influence: 19.7]  [Reference Citation Analysis (0)]
147.  Wasserman I, Lee LH, Ogino S, Marco MR, Wu C, Chen X, Datta J, Sadot E, Szeglin B, Guillem JG, Paty PB, Weiser MR, Nash GM, Saltz L, Barlas A, Manova-Todorova K, Uppada SPB, Elghouayel AE, Ntiamoah P, Glickman JN, Hamada T, Kosumi K, Inamura K, Chan AT, Nishihara R, Cercek A, Ganesh K, Kemeny NE, Dhawan P, Yaeger R, Sawyers CL, Garcia-Aguilar J, Giannakis M, Shia J, Smith JJ. SMAD4 Loss in Colorectal Cancer Patients Correlates with Recurrence, Loss of Immune Infiltrate, and Chemoresistance. Clin Cancer Res. 2019;25:1948-1956.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 47]  [Cited by in F6Publishing: 53]  [Article Influence: 8.8]  [Reference Citation Analysis (0)]
148.  Zhou C, Li J, Li Q. CDKN2A methylation in esophageal cancer: a meta-analysis. Oncotarget. 2017;8:50071-50083.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 16]  [Cited by in F6Publishing: 20]  [Article Influence: 3.3]  [Reference Citation Analysis (0)]
149.  Randon G, Fucà G, Rossini D, Raimondi A, Pagani F, Perrone F, Tamborini E, Busico A, Peverelli G, Morano F, Niger M, Antista M, Corallo S, Saggio S, Borelli B, Zucchelli G, Milione M, Pruneri G, Di Bartolomeo M, Falcone A, de Braud F, Cremolini C, Pietrantonio F. Prognostic impact of ATM mutations in patients with metastatic colorectal cancer. Sci Rep. 2019;9:2858.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 28]  [Cited by in F6Publishing: 28]  [Article Influence: 5.6]  [Reference Citation Analysis (0)]
150.  de Voer RM, Hahn MM, Mensenkamp AR, Hoischen A, Gilissen C, Henkes A, Spruijt L, van Zelst-Stams WA, Kets CM, Verwiel ET, Nagtegaal ID, Schackert HK, van Kessel AG, Hoogerbrugge N, Ligtenberg MJ, Kuiper RP. Deleterious Germline BLM Mutations and the Risk for Early-onset Colorectal Cancer. Sci Rep. 2015;5:14060.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 52]  [Cited by in F6Publishing: 69]  [Article Influence: 7.7]  [Reference Citation Analysis (0)]
151.  Frank B, Hoffmeister M, Klopp N, Illig T, Chang-Claude J, Brenner H. Colorectal cancer and polymorphisms in DNA repair genes WRN, RMI1 and BLM. Carcinogenesis. 2010;31:442-445.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 26]  [Article Influence: 1.7]  [Reference Citation Analysis (0)]
152.  Oh M, McBride A, Yun S, Bhattacharjee S, Slack M, Martin JR, Jeter J, Abraham I. BRCA1 and BRCA2 Gene Mutations and Colorectal Cancer Risk: Systematic Review and Meta-analysis. J Natl Cancer Inst. 2018;110:1178-1189.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 64]  [Cited by in F6Publishing: 76]  [Article Influence: 15.2]  [Reference Citation Analysis (1)]
153.  Wei XL, Wang DS, Xi SY, Wu WJ, Chen DL, Zeng ZL, Wang RY, Huang YX, Jin Y, Wang F, Qiu MZ, Luo HY, Zhang DS, Xu RH. Clinicopathologic and prognostic relevance of ARID1A protein loss in colorectal cancer. World J Gastroenterol. 2014;20:18404-18412.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 32]  [Cited by in F6Publishing: 35]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
154.  Ronchetti L, Melucci E, De Nicola F, Goeman F, Casini B, Sperati F, Pallocca M, Terrenato I, Pizzuti L, Vici P, Sergi D, Di Lauro L, Amoreo CA, Gallo E, Diodoro MG, Pescarmona E, Vitale I, Barba M, Buglioni S, Mottolese M, Fanciulli M, De Maria R, Maugeri-Saccà M. DNA damage repair and survival outcomes in advanced gastric cancer patients treated with first-line chemotherapy. Int J Cancer. 2017;140:2587-2595.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 21]  [Cited by in F6Publishing: 23]  [Article Influence: 3.3]  [Reference Citation Analysis (0)]
155.  Hansford S, Kaurah P, Li-Chang H, Woo M, Senz J, Pinheiro H, Schrader KA, Schaeffer DF, Shumansky K, Zogopoulos G, Santos TA, Claro I, Carvalho J, Nielsen C, Padilla S, Lum A, Talhouk A, Baker-Lange K, Richardson S, Lewis I, Lindor NM, Pennell E, MacMillan A, Fernandez B, Keller G, Lynch H, Shah SP, Guilford P, Gallinger S, Corso G, Roviello F, Caldas C, Oliveira C, Pharoah PD, Huntsman DG. Hereditary Diffuse Gastric Cancer Syndrome: CDH1 Mutations and Beyond. JAMA Oncol. 2015;1:23-32.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 481]  [Cited by in F6Publishing: 440]  [Article Influence: 48.9]  [Reference Citation Analysis (0)]
156.  Grünhage F, Jungck M, Lamberti C, Berg C, Becker U, Schulte-Witte H, Plassmann D, Rahner N, Aretz S, Friedrichs N, Buettner R, Sauerbruch T, Lammert F. Association of familial colorectal cancer with variants in the E-cadherin (CDH1) and cyclin D1 (CCND1) genes. Int J Colorectal Dis. 2008;23:147-154.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 43]  [Cited by in F6Publishing: 47]  [Article Influence: 2.9]  [Reference Citation Analysis (0)]
157.  Ooi A, Oyama T, Nakamura R, Tajiri R, Ikeda H, Fushida S, Dobashi Y. Gene amplification of CCNE1, CCND1, and CDK6 in gastric cancers detected by multiplex ligation-dependent probe amplification and fluorescence in situ hybridization. Hum Pathol. 2017;61:58-67.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 16]  [Cited by in F6Publishing: 16]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
158.  Chang HR, Nam S, Lee J, Kim JH, Jung HR, Park HS, Park S, Ahn YZ, Huh I, Balch C, Ku JL, Powis G, Park T, Jeong JH, Kim YH. Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer. Oncotarget. 2016;7:81435-81451.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 13]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]
159.  Hu X, Moon JW, Li S, Xu W, Wang X, Liu Y, Lee JY. Amplification and overexpression of CTTN and CCND1 at chromosome 11q13 in Esophagus squamous cell carcinoma (ESCC) of North Eastern Chinese Population. Int J Med Sci. 2016;13:868-874.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 12]  [Cited by in F6Publishing: 13]  [Article Influence: 1.6]  [Reference Citation Analysis (0)]
160.  Korphaisarn K, Morris VK, Overman MJ, Fogelman DR, Kee BK, Raghav KPS, Manuel S, Shureiqi I, Wolff RA, Eng C, Menter D, Hamilton SR, Kopetz S, Dasari A. FBXW7 missense mutation: a novel negative prognostic factor in metastatic colorectal adenocarcinoma. Oncotarget. 2017;8:39268-39279.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 38]  [Cited by in F6Publishing: 53]  [Article Influence: 8.8]  [Reference Citation Analysis (0)]
161.  Song B, Cui H, Li Y, Cheng C, Yang B, Wang F, Kong P, Li H, Zhang L, Jia Z, Bi Y, Wang J, Zhou Y, Liu J, Wang J, Zhao Z, Zhang Y, Hu X, Shi R, Yang J, Liu H, Yan T, Li Y, Xu E, Qian Y, Xi Y, Guo S, Chen Y, Wang J, Li G, Liang J, Jia J, Chen X, Guo J, Wang T, Zhang Y, Li Q, Wang C, Cheng X, Zhan Q, Cui Y. Mutually exclusive mutations in NOTCH1 and PIK3CA associated with clinical prognosis and chemotherapy responses of esophageal squamous cell carcinoma in China. Oncotarget. 2016;7:3599-3613.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 14]  [Cited by in F6Publishing: 15]  [Article Influence: 1.9]  [Reference Citation Analysis (0)]
162.  Arcaroli JJ, Tai WM, McWilliams R, Bagby S, Blatchford PJ, Varella-Garcia M, Purkey A, Quackenbush KS, Song EK, Pitts TM, Gao D, Lieu C, McManus M, Tan AC, Zheng X, Zhang Q, Ozeck M, Olson P, Jiang ZQ, Kopetz S, Jimeno A, Keysar S, Eckhardt G, Messersmith WA. A NOTCH1 gene copy number gain is a prognostic indicator of worse survival and a predictive biomarker to a Notch1 targeting antibody in colorectal cancer. Int J Cancer. 2016;138:195-205.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 31]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
163.  Ozawa T, Kazama S, Akiyoshi T, Murono K, Yoneyama S, Tanaka T, Tanaka J, Kiyomatsu T, Kawai K, Nozawa H, Kanazawa T, Yamaguchi H, Ishihara S, Sunami E, Kitayama J, Morikawa T, Fukayama M, Watanabe T. Nuclear Notch3 expression is associated with tumor recurrence in patients with stage II and III colorectal cancer. Ann Surg Oncol. 2014;21:2650-2658.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 31]  [Cited by in F6Publishing: 34]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
164.  Zhang L, Song X, Li X, Wu C, Jiang J. Yes-Associated Protein 1 as a Novel Prognostic Biomarker for Gastrointestinal Cancer: A Meta-Analysis. Biomed Res Int. 2018;2018:4039173.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 13]  [Article Influence: 2.2]  [Reference Citation Analysis (0)]