• Humans
• Female
• Breast Neoplasms/genetics
• Breast Neoplasms/ethnology
• Breast Neoplasms/pathology
• Middle Aged
• Mutation
• Genomics/methods
• DNA Copy Number Variations
• Adult
• Aged
• Socioeconomic Factors
• Black or African American/genetics
• Age Factors
• Biomarkers, Tumor/genetics
• White

• P01 CA151135 NCI NIH HHS
• P50 CA058223 NCI NIH HHS
• P30CA016086 National Cancer Institute (NCI)
• HEI-23-003 Breast Cancer Research Foundation (BCRF)
• T32CA057726 National Cancer Institute (NCI)
• HT94252310235 U.S. Department of Defense (DOD)
• OGUNC1202 Susan G. Komen (SGK)
• P01CA151135 National Cancer Institute (NCI)
• P30 CA016086 NCI NIH HHS
• T32 CA057726 NCI NIH HHS
• R01 CA253450 NCI NIH HHS

• Carboplatin
• Clinical trial
• Endometrial Cancer
• Metformin
• Paclitaxel

• Humans
• Female
• Metformin/administration & dosage
• Metformin/adverse effects
• Endometrial Neoplasms/drug therapy
• Endometrial Neoplasms/pathology
• Paclitaxel/administration & dosage
• Paclitaxel/adverse effects
• Carboplatin/administration & dosage
• Carboplatin/adverse effects
• Antineoplastic Combined Chemotherapy Protocols/therapeutic use
• Antineoplastic Combined Chemotherapy Protocols/adverse effects
• Antineoplastic Combined Chemotherapy Protocols/administration & dosage
• Middle Aged
• Neoplasm Recurrence, Local/drug therapy
• Neoplasm Recurrence, Local/pathology
• Aged
• Adult
• Neoplasm Staging
• Progression-Free Survival
• Aged, 80 and over

• Head and neck cancer
• human papilloma virus
• oral cancer
• oropharyngeal cancer
• risk factors
• survival

• P30 CA047904 NCI NIH HHS
• P50 CA097190 NCI NIH HHS
• R01 CA090731 NCI NIH HHS
• R01 DE025712 NIDCR NIH HHS

• RNA
• deep learning
• machine learning
• non-small cell lung cancer
• sequence
• statistical analysis
• transcriptome

• Chinese patients
• Non-small cell lung cancer (NSCLC)
• driver mutations
• targeted sequencing panel

• Roche Italia

• Endometrial cancer
• Genomics
• ITC
• Molecular profile

• P30 CA016059 NCI NIH HHS
• U10 CA181009 NCI NIH HHS
• UG1 CA233333 NCI NIH HHS

• CD31
• basic fibroblast growth factor
• intratumoral hemorrhage
• melanoma brain metastases
• pericyte
• peritumoral edema
• tumor infiltrating lymphocytes
• vascular endothelial growth factor

• P30 CA016086 NCI NIH HHS

• next-generation sequencing
• light microscopy
• computer tumor purity analysis

• Adolescent
• Adult
• Aged
• Aged, 80 and over
• Algorithms
• Child
• Child, Preschool
• Cohort Studies
• Computational Biology/methods
• Female
• High-Throughput Nucleotide Sequencing/methods
• Humans
• Male
• Microscopy/methods
• Middle Aged
• Mutation/genetics
• Neoplasms/diagnosis
• Neoplasms/genetics
• Neoplasms/pathology
• Practice Guidelines as Topic
• Retrospective Studies
• Young Adult

Lymph node (LN) metastases correspond with a worse prognosis in nearly all cancers, yet the occurrence of cancer spreading from LNs remains controversial. Additionally, the mechanisms explaining how cancers survive and exit LNs are largely unknown. Here, we show that breast cancer patients frequently have LN metastases that closely resemble distant metastases. In addition, using a microsurgical model, we show how LN metastasis development and dissemination is regulated by the expression of a chromatin modifier, histone deacetylase 11 (HDAC11). Genetic and pharmacologic blockade of HDAC11 decreases LN tumor growth, yet substantially increases migration and distant metastasis formation. Collectively, we reveal a mechanism explaining how HDAC11 plasticity promotes breast cancer growth as well as dissemination from LNs and suggest caution with the use of HDAC inhibitors.

The prognosis of cancer patients with lymph node (LN) metastasis is worse than those without. Here, the authors report that while histone deacetylase 11 (HDAC11) inhibition suppresses tumor growth within the LN, it also promotes cancer cell migration out of the LN to form distant metastasis, and therefore suggest caution with HDAC inhibitors.

Lung cancer is the leading cause of deaths related to cancer and accounts for more than a million deaths per year. Various new strategies have been developed and adapted for treatment; still the survival for 5 years is just 16% in patients with non‐small cell lung cancer (NSCLC). Most of these strategies to combat NSCLC whether it is a drug molecule or immunotherapy/vaccine candidate require a big cost and time. Integration of computational modeling with systems biology has opened new avenues for understanding complex cancer biology. Resolving the complex interactions of various pathways and their crosstalk leading to oncogenic changes could identify new therapeutic targets with lesser cost and time. Herein, this review provides an overview of various aspects of NSCLC along with available strategies for its cure concluding with our insight into how systems approach could serve as a therapeutic intervention dissecting the immunologic parameters and cross talk between various pathways involved.

• EGFR
• IL-1RB
• MAPK
• NF-kB
• NSCLC
• systems biology

• Animals
• Antineoplastic Agents, Immunological/therapeutic use
• Cancer Vaccines/therapeutic use
• Carcinoma, Non-Small-Cell Lung/diagnosis
• Carcinoma, Non-Small-Cell Lung/genetics
• Carcinoma, Non-Small-Cell Lung/immunology
• Carcinoma, Non-Small-Cell Lung/therapy
• Cytokines/immunology
• Humans
• Immunotherapy
• Lung Neoplasms/diagnosis
• Lung Neoplasms/genetics
• Lung Neoplasms/immunology
• Lung Neoplasms/therapy

The range of potential applications of liquid biopsies for non-small cell lung cancer management is expanded by the use of circulating tumor deoxyribonucleic acid and circulating tumor cells. Principal studies have demonstrated the predictive accuracy of droplet digital polymerase chain reaction detection, next-generation sequencing, and circulating tumor cells detection in patients with non-small cell lung cancer. The translational potential of these liquid biopsy technologies promotes the improvement of sensitivity and specificity in genomic and molecular methods. Here, we highlight the realities and challenges associated with the use of liquid biopsies for the detection of non-small cell lung cancer in patients. However, liquid biopsy technologies including circulating tumor cells detection, droplet digital polymerase chain reaction detection, and next-generation sequencing detection for precision therapy in non-small cell lung cancer will show substantive clinical applications in the future.

• circulating tumor DNA
• circulating tumor cells
• liquid biopsy
• non-small cell lung cancer
• precision therapy

• RAC1
• RNA sequencing
• SPEN
• The Cancer Genome Atlas Project
• UV signature
• cutaneous melanoma
• next generation sequencing
• prognostic significance

• K12 CA090625 NCI NIH HHS
• P30 CA016086 NCI NIH HHS
• P50 CA121974 NCI NIH HHS
• U10 CA181009 NCI NIH HHS

The majority of urothelial cancers (UC) harbor alterations in retinoblastoma (Rb) pathway genes that can lead to loss of Rb tumour suppressor function. Palbociclib is an oral, selective inhibitor of CDK 4/6 that restores Rb function and promotes cell cycle arrest.

In this phase II trial, patients with metastatic platinum-refractory UC molecularly selected for p16 loss and intact Rb by tumour immunohistochemistry received palbociclib 125 mg p.o. daily for 21 days of a 28-day cycle. Primary endpoint was progression-free survival at 4 months (PFS4) using a Simon’s two-stage design. Next-generation sequencing including Rb pathway alterations was conducted.

Twelve patients were enrolled and two patients (17%) achieved PFS4 with insufficient activity to advance to stage 2. No responses were seen. Median PFS was 1.9 months (95% CI 1.8–3.7 months) and median overall survival was 6.3 months (95% CI 2.2–12.6 months). Fifty-eight percent of patients had grade ≥3 hematologic toxicity. There were no CDKN2A alterations found and no correlation of Rb pathway alterations with clinical outcome.

Palbociclib did not demonstrate meaningful activity in selected patients with platinum-refractory metastatic UC. Further development of palbociclib should only be considered with improved integral biomarker selection or in rational combination with other therapies.

• Brain metastases
• Breast cancer
• Metastases
• PI3K, MEK
• Targeted therapy

• Breast cancer
• Oncology

• Adult
• Aged
• Breast Neoplasms/genetics
• Breast Neoplasms/metabolism
• DNA Copy Number Variations
• DNA, Neoplasm/genetics
• DNA, Neoplasm/metabolism
• Gene Expression Regulation, Neoplastic
• Humans
• Middle Aged
• Mutation
• Neoplasm Metastasis
• RNA, Neoplasm/biosynthesis
• RNA, Neoplasm/genetics
• Sequence Analysis, DNA
• Sequence Analysis, RNA
• Tumor Suppressor Protein p53/biosynthesis
• Tumor Suppressor Protein p53/genetics

• K23 CA157728 NCI NIH HHS
• P50 CA058223 NCI NIH HHS
• P30 CA016086 NCI NIH HHS
• F30 CA200345 NCI NIH HHS
• P30 ES010126 NIEHS NIH HHS
• T32 GM008719 NIGMS NIH HHS
• R01 CA195754 NCI NIH HHS
• T32 CA071341 NCI NIH HHS
• R01 CA148761 NCI NIH HHS
• P30 CA016058 NCI NIH HHS
• National Cancer Institute

Personalized medicine has emerged as the future of cancer care to ensure that patients receive individualized treatment specific to their needs. In order to provide such care, molecular techniques that enable oncologists to diagnose, treat, and monitor tumors are necessary. In the field of lung cancer, cell free DNA (cfDNA) shows great potential as a less invasive liquid biopsy technique, and next-generation sequencing (NGS) is a promising tool for analysis of tumor mutations. In this review, we outline the evolution of cfDNA and NGS and discuss the progress of using them in a clinical setting for patients with lung cancer. We also present an analysis of the role of cfDNA as a liquid biopsy technique and NGS as an analytical tool in studying EGFR and MET, two frequently mutated genes in lung cancer. Ultimately, we hope that using cfDNA and NGS for cancer diagnosis and treatment will become standard for patients with lung cancer and across the field of oncology.

• biomarkers
• cell-free DNA
• lung cancer
• next-generation sequencing
• personalized medicine

• next generation sequencing (NGS)
• pathways
• personalized medicine
• precision oncology
• systems biology

Next‐generation sequencing (NGS) has emerged as an affordable and reproducible means to query tumors for somatic genetic anomalies. To help interpret somatic NGS data, many institutions have created a molecular tumor board to analyze the results of NGS and make recommendations. This article evaluates the utility of cognitive computing systems to analyze data for clinical decision‐making.

Using next‐generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human “molecular tumor boards” (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB.

One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis.

Using a WfG‐curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker‐selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took <3 minutes per case.

These results demonstrate that the interpretation and actionability of somatic NGS results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing could potentially improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of up‐to‐date availability of clinical trials.

The results of this study demonstrate that the interpretation and actionability of somatic next‐generation sequencing results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing can significantly improve patient care by providing a fast, cost‐effective, and comprehensive approach for data analysis in the delivery of precision medicine. Patients and physicians who are considering enrollment in clinical trials may benefit from the support of such tools applied to genomic data.

• Artificial intelligence
• Genomics
• High‐throughput nucleotide sequencing
• Precision medicine

• Antineoplastic Combined Chemotherapy Protocols/therapeutic use
• Biomarkers, Tumor
• Case-Control Studies
• Combined Modality Therapy
• Follow-Up Studies
• Gene Expression Regulation, Neoplastic
• High-Throughput Nucleotide Sequencing
• Humans
• Lymphatic Metastasis
• Neoplasm Invasiveness
• Neoplasm Recurrence, Local/drug therapy
• Neoplasm Recurrence, Local/pathology
• Neoplasms/drug therapy
• Neoplasms/pathology
• Prognosis
• Retrospective Studies
• Survival Rate

• P30 CA016086 NCI NIH HHS
• R01 CA202053 NCI NIH HHS
• U10 CA181009 NCI NIH HHS

The zinc transporter SLC39A4 influences epithelial cell morphology and migration in various cancers; however, its role in regulating cell invasion and chemotherapeutic resistance in human lung cancer is not yet clear. Here, integrated analysis of gene expression in non-small cell lung cancer revealed that SLC39A4 expression is significantly correlated with increased tumour size and regional lymph node spread, as well as shorter overall survival (OS) and disease-free survival (DFS). SLC39A4 silencing by lentivirus-mediated shRNA blocked human lung cancer cell epithelial-mesenchymal transition and metastasis in vitro and in vivo, respectively. Moreover, SLC39A4 knockdown enhanced cancer cell sensitivity to cisplatin-induced death by inhibiting stemness in lung cancer cells. Collectively, these data suggest that SLC39A4 may be a novel therapeutic target and predictive marker of tumour metastasis in non-small cell lung cancer.

• K12 CA139160 NCI NIH HHS
• K23 GM112128 NIGMS NIH HHS
• P30 CA016086 NCI NIH HHS
• U10 CA181009 NCI NIH HHS

Changes in the quantity of genetic material, known as somatic copy number alterations (CNAs), can drive tumorigenesis. Many methods exist for assessing CNAs using microarrays, but considerable technical issues limit current CNA calling based upon DNA sequencing. We present SynthEx, a novel tool for detecting CNAs from whole exome and genome sequencing. SynthEx utilizes a “synthetic-normal” strategy to overcome technical and financial issues. In terms of accuracy and precision, SynthEx is highly comparable to array-based methods and outperforms sequencing-based CNA detection tools. SynthEx robustly identifies CNAs using sequencing data without the additional costs associated with matched normal specimens.

• Breast cancer
• Copy number
• Sequencing
• Synthetic normal
• The Cancer Genome Atlas
• Whole exome
• Whole genome