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Tippareddy C, Martinez OM, Benza AR, Bera K, Ramaiya N, Tirumani SH. From guidelines to radiology practice: navigating the 2023 ASCO guidelines for advanced gastroesophageal cancer and beyond. Abdom Radiol (NY) 2025; 50:78-93. [PMID: 39123051 PMCID: PMC11711647 DOI: 10.1007/s00261-024-04499-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 07/09/2024] [Accepted: 07/13/2024] [Indexed: 08/12/2024]
Abstract
The American Society of Clinical Oncology (ASCO) updated the guidelines for the treatment of advanced gastroesophageal (GE) cancer in 2023, signifying a major shift towards targeted therapeutics and precision medicine. This article serves as an imaging-based review of recent developments in the care of patients with GE cancer. We cover the epidemiology, the developing treatment paradigms, and the imaging assessment of GE malignancy. In addition, this review aims to familiarize radiologists with the unique adverse effects pertaining to therapeutics, surgeries, radiation therapies, and associated imaging corollaries. A case-based approach will be used to both explore the efficacy of modern treatments and demonstrate their adverse effects, such as chemotherapy-associated pneumonitis, radiation esophagitis, and anastomotic failure. With this comprehensive exploration of gastroesophageal cancer, radiologists will be equipped with the essential tools to inform the treatment decisions made by medical oncologists, radiation oncologists, and surgical oncologists in the new era of precision medicine.
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Affiliation(s)
- Charit Tippareddy
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, 1110 Euclid Ave, Cleveland, OH, 44106, USA.
- Case Western Reserve University School of Medicine, Cleveland, OH, USA.
| | | | - Andrew R Benza
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, 1110 Euclid Ave, Cleveland, OH, 44106, USA
- Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kaustav Bera
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, 1110 Euclid Ave, Cleveland, OH, 44106, USA
- Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Nikhil Ramaiya
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, 1110 Euclid Ave, Cleveland, OH, 44106, USA
- Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Sree Harsha Tirumani
- Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, 1110 Euclid Ave, Cleveland, OH, 44106, USA
- Case Western Reserve University School of Medicine, Cleveland, OH, USA
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Otálora-Otálora BA, Payán-Gómez C, López-Rivera JJ, Pedroza-Aconcha NB, Aristizábal-Guzmán C, Isaza-Ruget MA, Álvarez-Moreno CA. Global transcriptomic network analysis of the crosstalk between microbiota and cancer-related cells in the oral-gut-lung axis. Front Cell Infect Microbiol 2024; 14:1425388. [PMID: 39228892 PMCID: PMC11368877 DOI: 10.3389/fcimb.2024.1425388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Accepted: 07/15/2024] [Indexed: 09/05/2024] Open
Abstract
Background The diagnosis and treatment of lung, colon, and gastric cancer through the histologic characteristics and genomic biomarkers have not had a strong impact on the mortality rates of the top three global causes of death by cancer. Methods Twenty-five transcriptomic analyses (10 lung cancer, 10 gastric cancer, and 5 colon cancer datasets) followed our own bioinformatic pipeline based on the utilization of specialized libraries from the R language and DAVID´s gene enrichment analyses to identify a regulatory metafirm network of transcription factors and target genes common in every type of cancer, with experimental evidence that supports its relationship with the unlocking of cell phenotypic plasticity for the acquisition of the hallmarks of cancer during the tumoral process. The network's regulatory functional and signaling pathways might depend on the constant crosstalk with the microbiome network established in the oral-gut-lung axis. Results The global transcriptomic network analysis highlighted the impact of transcription factors (SOX4, TCF3, TEAD4, ETV4, and FOXM1) that might be related to stem cell programming and cancer progression through the regulation of the expression of genes, such as cancer-cell membrane receptors, that interact with several microorganisms, including human T-cell leukemia virus 1 (HTLV-1), the human papilloma virus (HPV), the Epstein-Barr virus (EBV), and SARS-CoV-2. These interactions can trigger the MAPK, non-canonical WNT, and IFN signaling pathways, which regulate key transcription factor overexpression during the establishment and progression of lung, colon, and gastric cancer, respectively, along with the formation of the microbiome network. Conclusion The global transcriptomic network analysis highlights the important interaction between key transcription factors in lung, colon, and gastric cancer, which regulates the expression of cancer-cell membrane receptors for the interaction with the microbiome network during the tumorigenic process.
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Affiliation(s)
| | - César Payán-Gómez
- Dirección Académica, Universidad Nacional de Colombia, Sede de La Paz, La Paz, Colombia
| | - Juan Javier López-Rivera
- Grupo de Investigación INPAC, Specialized Laboratory, Clinica Universitaria Colombia, Clínica Colsanitas S.A., Bogotá, Colombia
| | | | - Claudia Aristizábal-Guzmán
- Grupo de Investigación INPAC, Unidad de Investigación, Fundación Universitaria Sanitas, Bogotá, Colombia
| | - Mario Arturo Isaza-Ruget
- Keralty, Sanitas International Organization, Grupo de Investigación INPAC, Fundación Universitaria Sanitas, Bogotá, Colombia
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Wang YK, Wang SN, Liao XH, Wang ZQ, Li P, Yun T, Meng DQ. Histogenetic insights and genetic landscape of fibromatosis-like undifferentiated gastric carcinoma: a focused study. World J Surg Oncol 2024; 22:189. [PMID: 39049011 PMCID: PMC11267673 DOI: 10.1186/s12957-024-03479-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 07/17/2024] [Indexed: 07/27/2024] Open
Abstract
BACKGROUND The aim of this study was to elucidate the histogenesis and genetic underpinnings of fibromatosis-like undifferentiated gastric carcinoma (FLUGC), a rare pathological entity. METHOD Through a detailed analysis of seven cases, including histopathological evaluation, CTNNB1 gene mutation screening, human epidermal growth factor receptor 2 (HER2) protein level quantification, and HER2 gene amplification assessment to identify the pathological and molecular characteristics of FLUGC. RESULTS Of the seven patients in this study, five were male and two were female (age: 39-73 years). Four patients presented with lesions in the gastric antrum and three had lesions in the lateral curvature of the stomach. Histopathologically, over 90% of the tumor consisted of aggressive fibromatosis-like tissue, including proliferating spindle fibroblasts and myofibroblasts and varying amounts of collagenous fibrous tissues. Undifferentiated cancer cells, accounting for less than 10%, were dispersed among the aggressive fibromatosis-like tissues. These cells were characterized by their small size and were relatively sparse without glandular ducts or nested mass-like structures. Immunophenotyping results showed positive expression of CKpan, CDX2, villin, and p53 in undifferentiated cancer cells; positive expression of vimentin in aggressive fibromatosis-like tissue; positive cytoplasmic expression of β-catenin; and focal cytoplasmic positive expression of smooth muscle actin (SMA). Genetic analysis did not reveal any mutations in the CTNNB1 gene test, nor was there amplification in the HER2 gene fluorescence in situ hybridization (FISH) test. Additionally, the Epstein-Barr encoding region (EBER) of in situ hybridization was negative; and the mismatch repair (MMR) protein was positive. Programmed cell death-1 (PD-1) was < 1-5%; programmed cell death ligand 1 (PD-L1): TPS = 1-4%, CPS = 3-8. CONCLUSION The study highlights the significance of CTNNB1, HER2, EBER, and MMR as pivotal genetic markers in FLUGC, underscoring their relevance for diagnosis and clinical management. The rarity and distinct pathological features of FLUGC emphasize the importance of accurate diagnosis to prevent underdiagnosis or misdiagnosis and to raise awareness within the medical community.
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Affiliation(s)
- Yang-Kun Wang
- Department of Pathology, The Fourth People's Hospital, 22 Longshan Industrial Zone, Nanwan Street, Longgang District, Shenzhen, 518123, China
| | - Su-Nan Wang
- Shenzhen Polytechnic, Shenzhen, 518055, China
| | - Xing-Hai Liao
- Department of Pathology, Shenzhen Hospital, Southern Medical University, Shenzhen, 518101, China
| | - Zhi-Qiang Wang
- Department of Pathology, Foresea Life Insurance Guangzhou General Hospital, Guangzhou, 511300, China
| | - Ping Li
- Department of Pathology, Peking University Shenzhen Hospital, Shenzhen, 518036, China
| | - Tian Yun
- Department of Pathology, The 989th Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army, Luoyang, 471031, Henan, China
| | - De-Qi Meng
- Department of Pathology, The Fourth People's Hospital, 22 Longshan Industrial Zone, Nanwan Street, Longgang District, Shenzhen, 518123, China.
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Song J, Yan XX, Zhang FL, Lei YY, Ke ZY, Li F, Zhang K, He YQ, Li W, Li C, Pan YM. Unveiling the secrets of gastrointestinal mucous adenocarcinoma survival after surgery with artificial intelligence: A population-based study. World J Gastrointest Oncol 2024; 16:2404-2418. [PMID: 38994138 PMCID: PMC11236227 DOI: 10.4251/wjgo.v16.i6.2404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/27/2024] [Accepted: 04/03/2024] [Indexed: 06/14/2024] Open
Abstract
BACKGROUND Research on gastrointestinal mucosal adenocarcinoma (GMA) is limited and controversial, and there is no reference tool for predicting postoperative survival. AIM To investigate the prognosis of GMA and develop predictive model. METHODS From the Surveillance, Epidemiology, and End Results database, we collected clinical information on patients with GMA. After random sampling, the patients were divided into the discovery (70% of the total, for model training), validation (20%, for model evaluation), and completely blind test cohorts (10%, for further model evaluation). The main assessment metric was the area under the receiver operating characteristic curve (AUC). All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA's prognosis. RESULTS This model had an AUC of 0.7433 [95% confidence intervals (95%CI): 0.7424-0.7442] in the discovery cohort, 0.7244 (GMA: 0.7234-0.7254) in the validation cohort, and 0.7388 (95%CI: 0.7378-0.7398) in the test cohort. We packaged it into Windows software for doctors' use and uploaded it. Mucinous gastric adenocarcinoma had the worst prognosis, and these were protective factors of GMA: Regional nodes examined [hazard ratio (HR): 0.98, 95%CI: 0.97-0.98, P < 0.001)] and chemotherapy (HR: 0.62, 95%CI: 0.58-0.66, P < 0.001). CONCLUSION The deep learning-based tool developed can accurately predict the overall survival of patients with GMA postoperatively. Combining surgery, chemotherapy, and adequate lymph node dissection during surgery can improve patient outcomes.
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Affiliation(s)
- Jie Song
- Department of Gastroenterology, Dongying People’s Hospital, Dongying Hospital of Shandong Provincial Hospital Group, Dongying 257000, Shandong Province, China
| | - Xiang-Xiu Yan
- Department of Gastroenterology, Dongying People’s Hospital, Dongying Hospital of Shandong Provincial Hospital Group, Dongying 257000, Shandong Province, China
| | - Fang-Liang Zhang
- Gastrointestinal Surgery Department, Suining Central Hospital, Suining 629000, Sichuan Province, China
| | - Yong-Yi Lei
- Obstetrical Department, Suining Central Hospital, Suining 629000, Sichuan Province, China
| | - Zi-Yin Ke
- School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, Guangdong Province, China
| | - Fang Li
- Department of Pathology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing 100049, China
| | - Kai Zhang
- General Department, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
| | - Yu-Qi He
- Department of Gastroenterology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
| | - Wei Li
- Department of Thoracic Surgery, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu 610072, Sichuan Province, China
| | - Chao Li
- Department of Gastroenterology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing 100049, China
| | - Yuan-Ming Pan
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
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Song J, Yan XX, Zhang FL, Lei YY, Ke ZY, Li F, Zhang K, He YQ, Li W, Li C, Pan YM. Unveiling the secrets of gastrointestinal mucous adenocarcinoma survival after surgery with artificial intelligence: A population-based study. World J Gastrointest Oncol 2024; 16:2392-2406. [DOI: 10.4251/wjgo.v16.i6.2392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/27/2024] [Accepted: 04/03/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Research on gastrointestinal mucosal adenocarcinoma (GMA) is limited and controversial, and there is no reference tool for predicting postoperative survival.
AIM To investigate the prognosis of GMA and develop predictive model.
METHODS From the Surveillance, Epidemiology, and End Results database, we collected clinical information on patients with GMA. After random sampling, the patients were divided into the discovery (70% of the total, for model training), validation (20%, for model evaluation), and completely blind test cohorts (10%, for further model evaluation). The main assessment metric was the area under the receiver operating characteristic curve (AUC). All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA’s prognosis.
RESULTS This model had an AUC of 0.7433 [95% confidence intervals (95%CI): 0.7424-0.7442] in the discovery cohort, 0.7244 (GMA: 0.7234-0.7254) in the validation cohort, and 0.7388 (95%CI: 0.7378-0.7398) in the test cohort. We packaged it into Windows software for doctors’ use and uploaded it. Mucinous gastric adenocarcinoma had the worst prognosis, and these were protective factors of GMA: Regional nodes examined [hazard ratio (HR): 0.98, 95%CI: 0.97-0.98, P < 0.001)] and chemotherapy (HR: 0.62, 95%CI: 0.58-0.66, P < 0.001).
CONCLUSION The deep learning-based tool developed can accurately predict the overall survival of patients with GMA postoperatively. Combining surgery, chemotherapy, and adequate lymph node dissection during surgery can improve patient outcomes.
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Affiliation(s)
- Jie Song
- Department of Gastroenterology, Dongying People’s Hospital, Dongying Hospital of Shandong Provincial Hospital Group, Dongying 257000, Shandong Province, China
| | - Xiang-Xiu Yan
- Department of Gastroenterology, Dongying People’s Hospital, Dongying Hospital of Shandong Provincial Hospital Group, Dongying 257000, Shandong Province, China
| | - Fang-Liang Zhang
- Gastrointestinal Surgery Department, Suining Central Hospital, Suining 629000, Sichuan Province, China
| | - Yong-Yi Lei
- Obstetrical Department, Suining Central Hospital, Suining 629000, Sichuan Province, China
| | - Zi-Yin Ke
- School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, Guangdong Province, China
| | - Fang Li
- Department of Pathology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing 100049, China
| | - Kai Zhang
- General Department, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
| | - Yu-Qi He
- Department of Gastroenterology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
| | - Wei Li
- Department of Thoracic Surgery, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu 610072, Sichuan Province, China
| | - Chao Li
- Department of Gastroenterology, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing 100049, China
| | - Yuan-Ming Pan
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
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Liu Y, Cui H, Xu X, Liang W. Prognostic value of lymph node density on cancer staging system for gastric cancer without distal metastasis: a population-based analysis of SEER database. World J Surg Oncol 2022; 20:325. [PMID: 36175896 PMCID: PMC9520926 DOI: 10.1186/s12957-022-02795-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/24/2022] [Indexed: 11/21/2022] Open
Abstract
Background Accurate tumor staging is the cornerstone of tumor treatment. Current tumor staging system for gastric cancer (GC) is based on regional positive lymph nodes while ignoring the total number of examined lymph nodes. We aim to assess the prognostic value of lymph node density (LND), the ratio of positive nodes to the total number examined nodes, in GC without distal metastasis. Methods Clinical information of patients with histologically confirmed GC and without distal metastasis was identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The X-Tile software was used to identify the ideal prognosis-related cutoff point for LND. The prognostic value of LND on cancer-specific survival (CSS) and overall survival (OS) was assessed in Cox regression models. Subgroup analysis stratified by LND was performed on current lymph node staging system to further explore the interaction between LND and current lymph node staging system. Results A total of 4281 participants were identified from the SEER database for the final analysis. The optimal prognosis-related cutoff values of LND were calculated as 0.1 and 0.4, and LND was divided into three levels: LND1 (< 0.1), LND2 (> = 0.1, < 0.4), and LND3 (> = 0.4). LND3 was associated with worse CSS and OS in GC patients. Compared to patients with LND1, those with LND2 and LND3 had 2.43 (HR = 2.43, 95% CI 2.09–2.84, P < 0.001) and 4.69 (HR = 4.69, 95% CI 4.02–5.48, P < 0.001) folds increase in mortality in CSS, respectively. Similar results were found in the evaluation of OS in GC patients. Subgroup analysis stratified by LND also found that patients in the same current lymph node stage still had different prognosis due to the different LND levels after adjustment for other prognosis-related covariates (all P values < 0.001). Conclusion LND is an independent prognostic factor for GC without distal metastasis. In the current lymph node staging system, LND has potential value in further accurately classifying GC patients without distal metastasis. Supplementary Information The online version contains supplementary material available at 10.1186/s12957-022-02795-9.
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Affiliation(s)
- Yuhua Liu
- Chinese PLA General Hospital & Medical School of Chinese PLA, Beijing, 100853, China.,Institution of Hospital Management, Department of Medical Innovation and Research, Chinese PLA General Hospital, Beijing, 100853, China
| | - Hao Cui
- Chinese PLA General Hospital & Medical School of Chinese PLA, Beijing, 100853, China.,Department of General Surgery & Institute of General Surgery, the First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Xinxin Xu
- Chinese PLA General Hospital & Medical School of Chinese PLA, Beijing, 100853, China.,Department of General Surgery & Institute of General Surgery, the First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Wenquan Liang
- Chinese PLA General Hospital & Medical School of Chinese PLA, Beijing, 100853, China. .,Department of General Surgery & Institute of General Surgery, the First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China.
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