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Díaz Del Arco C, Fernández Aceñero MJ, Ortega Medina L. Molecular Classifications in Gastric Cancer: A Call for Interdisciplinary Collaboration. Int J Mol Sci 2024; 25:2649. [PMID: 38473896 DOI: 10.3390/ijms25052649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 02/21/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
Gastric cancer (GC) is a heterogeneous disease, often diagnosed at advanced stages, with a 5-year survival rate of approximately 20%. Despite notable technological advancements in cancer research over the past decades, their impact on GC management and outcomes has been limited. Numerous molecular alterations have been identified in GC, leading to various molecular classifications, such as those developed by The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG). Other authors have proposed alternative perspectives, including immune, proteomic, or epigenetic-based classifications. However, molecular stratification has not yet transitioned into clinical practice for GC, and little attention has been paid to alternative molecular classifications. In this review, we explore diverse molecular classifications in GC from a practical point of view, emphasizing their relationships with clinicopathological factors, prognosis, and therapeutic approaches. We have focused on classifications beyond those of TCGA and the ACRG, which have been less extensively reviewed previously. Additionally, we discuss the challenges that must be overcome to ensure their impact on patient treatment and prognosis. This review aims to serve as a practical framework to understand the molecular landscape of GC, facilitate the development of consensus molecular categories, and guide the design of innovative molecular studies in the field.
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Affiliation(s)
- Cristina Díaz Del Arco
- Department of Legal Medicine, Psychiatry and Pathology, School of Medicine, Complutense University of Madrid, 28040 Madrid, Spain
- Department of Pathology, Hospital Clínico San Carlos, Health Research Institute of the Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
| | - María Jesús Fernández Aceñero
- Department of Legal Medicine, Psychiatry and Pathology, School of Medicine, Complutense University of Madrid, 28040 Madrid, Spain
- Department of Pathology, Hospital Clínico San Carlos, Health Research Institute of the Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
| | - Luis Ortega Medina
- Department of Legal Medicine, Psychiatry and Pathology, School of Medicine, Complutense University of Madrid, 28040 Madrid, Spain
- Department of Pathology, Hospital Clínico San Carlos, Health Research Institute of the Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
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Spirina LV, Avgustinovich AV, Bakina OV, Afanas'ev SG, Volkov MY, Vtorushin SV, Kovaleva IV, Klyushina TS, Munkuev IO. Targeted Sequencing in Gastric Cancer: Association with Tumor Molecular Characteristics and FLOT Therapy Effectiveness. Curr Issues Mol Biol 2024; 46:1281-1290. [PMID: 38392199 PMCID: PMC10887746 DOI: 10.3390/cimb46020081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 02/24/2024] Open
Abstract
Heterogeneity of gastric cancer (GC) is the main trigger of the disease's relapse. The aim of this study was to investigate the connections between targeted genes, cancer clinical features, and the effectiveness of FLOT chemotherapy. Twenty-one patients with gastric cancers (GCs) were included in this study. Tumor-targeted sequencing was conducted, and real-time PCR was used to assess the expression of molecular markers in tumors. Seven patients with stabilization had mutations that were related to their response to therapy and were relevant to the tumor phenotype. Two patients had two mutations. The number of patients with TP53 mutations increased in HER2-positive tumor status. PD-L1-positive cancers had mutations in KRAS, TP53, PIK3CA, PTEN, and ERBB, which resulted in an increase in PD-1 expression. TP53 mutation and PTEN mutation are associated with changes in factors associated with neoangiogenesis. In concusion, patients who did not have aggressive growth markers that were verified by molecular features had the best response to treatment, including complete morphologic regression.
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Affiliation(s)
- Liudmila V Spirina
- Biochemistry and Molecular Biology Division, Siberian State Medical University, 2 Moskovsky Trakt, Tomsk 634050, Russia
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 5 Kooperativny Street, Tomsk 634050, Russia
| | - Alexandra V Avgustinovich
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 5 Kooperativny Street, Tomsk 634050, Russia
| | - Olga V Bakina
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 5 Kooperativny Street, Tomsk 634050, Russia
- Institute of Strength Physics and Materials Science, Siberian Branch of the Russian Academy of Sciences, 2/4 Pr. Akademicheskii, Tomsk 634055, Russia
| | - Sergey G Afanas'ev
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 5 Kooperativny Street, Tomsk 634050, Russia
| | - Maxim Yu Volkov
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 5 Kooperativny Street, Tomsk 634050, Russia
| | - Sergey V Vtorushin
- Biochemistry and Molecular Biology Division, Siberian State Medical University, 2 Moskovsky Trakt, Tomsk 634050, Russia
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 5 Kooperativny Street, Tomsk 634050, Russia
| | - Irina V Kovaleva
- Biochemistry and Molecular Biology Division, Siberian State Medical University, 2 Moskovsky Trakt, Tomsk 634050, Russia
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 5 Kooperativny Street, Tomsk 634050, Russia
| | - Tatyana S Klyushina
- Biochemistry and Molecular Biology Division, Siberian State Medical University, 2 Moskovsky Trakt, Tomsk 634050, Russia
| | - Igor O Munkuev
- Biochemistry and Molecular Biology Division, Siberian State Medical University, 2 Moskovsky Trakt, Tomsk 634050, Russia
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Chevalier A, Guo T, Gurevich NQ, Xu J, Yajima M, Campbell JD. Characterization of highly active mutational signatures in tumors from a large Chinese population. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.03.23297964. [PMID: 37961450 PMCID: PMC10635259 DOI: 10.1101/2023.11.03.23297964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The majority of mutational signatures have been characterized in tumors from Western countries and the degree to which mutational signatures are similar or different in Eastern populations has not been fully explored. We leveraged a large-scale clinical sequencing cohort of tumors from a Chinese population containing 25 tumor types and found that the highly active mutational signatures were similar to those previously characterized1,2. The aristolochic acid signature SBS22 was observed in four soft tissue sarcomas and the POLE-associated signature SBS10 was observed in a gallbladder carcinoma. In lung adenocarcinoma, the polycyclic aromatic hydrocarbon (PAH) signature SBS4 was significantly higher in males compared to females but not associated with smoking status. The UV-associated signature SBS7 was significantly lower in cutaneous melanomas from the Chinese population compared to a similar American cohort. Overall, these results add to our understanding of the mutational processes that contribute to tumors from the Chinese population.
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Affiliation(s)
- Aaron Chevalier
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Bioinformatics Program, Boston University, Boston, Massachusetts
| | - Tao Guo
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Mathematics & Statistics, Boston University, Boston, Massachusetts
| | - Natasha Q. Gurevich
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Bioinformatics Program, Boston University, Boston, Massachusetts
| | - Jingwen Xu
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Mathematics & Statistics, Boston University, Boston, Massachusetts
| | - Masanao Yajima
- Department of Mathematics & Statistics, Boston University, Boston, Massachusetts
| | - Joshua D. Campbell
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
- Bioinformatics Program, Boston University, Boston, Massachusetts
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