학술논문
RNA expression of 6 genes from metastatic mucosal gastric cancer serves as the global prognostic marker for gastric cancer with functional validation.
Document Type
Academic Journal
Author
Suh YS; Department of Surgery, Seoul National University College of Medicine, Seoul, South Korea.; Department of Surgery, Seoul National University Hospital, Seoul, South Korea.; Department of Surgery, Seoul National University Bundang Hospital, Seongnam, South Korea.; The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.; Lee J; Department of Surgery, Seoul National University Bundang Hospital, Seongnam, South Korea.; George J; The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.; Seol D; Department of Surgery, Seoul National University Bundang Hospital, Seongnam, South Korea.; Jeong K; Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea.; Oh SY; Department of Surgery, Seoul National University College of Medicine, Seoul, South Korea.; Department of Surgery, Seoul National University Hospital, Seoul, South Korea.; Bang C; Department of Surgery, Seoul National University Bundang Hospital, Seongnam, South Korea.; Jun Y; The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.; Center for Supercomputing Applications, Division of National Supercomputing, Korea Institute of Science and Technology Information, Daejeon, South Korea.; Kong SH; Department of Surgery, Seoul National University College of Medicine, Seoul, South Korea.; Department of Surgery, Seoul National University Hospital, Seoul, South Korea.; Lee HJ; Department of Surgery, Seoul National University College of Medicine, Seoul, South Korea.; Department of Surgery, Seoul National University Hospital, Seoul, South Korea.; Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea.; Kim JI; Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea.; Genomic Medicine Institute, Medical Research Center, Seoul National University College of Medicine, Seoul, South Korea.; Kim WH; Department of Pathology, Seoul National University College of Medicine, Seoul, South Korea.; Yang HK; Department of Surgery, Seoul National University College of Medicine, Seoul, South Korea. hkyang@snu.ac.kr.; Department of Surgery, Seoul National University Hospital, Seoul, South Korea. hkyang@snu.ac.kr.; Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea. hkyang@snu.ac.kr.; Lee C; The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA. Charles.lee@jax.org.
Source
Publisher: Nature Publishing Group on behalf of Cancer Research UK Country of Publication: England NLM ID: 0370635 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1532-1827 (Electronic) Linking ISSN: 00070920 NLM ISO Abbreviation: Br J Cancer Subsets: MEDLINE
Subject
Language
English
Abstract
Background: Molecular analysis of advanced tumors can increase tumor heterogeneity and selection bias. We developed a robust prognostic signature for gastric cancer by comparing RNA expression between very rare early gastric cancers invading only mucosal layer (mEGCs) with lymph node metastasis (Npos) and those without metastasis (Nneg).
Methods: Out of 1003 mEGCs, all Npos were matched to Nneg using propensity scores. Machine learning approach comparing Npos and Nneg was used to develop prognostic signature. The function and robustness of prognostic signature was validated using cell lines and external datasets.
Results: Extensive machine learning with cross-validation identified the prognostic classifier consisting of four overexpressed genes (HDAC5, NPM1, DTX3, and PPP3R1) and two downregulated genes (MED12 and TP53), and enabled us to develop the risk score predicting poor prognosis. Cell lines engineered to high-risk score showed increased invasion, migration, and resistance to 5-FU and Oxaliplatin but maintained sensitivity to an HDAC inhibitor. Mouse models after tail vein injection of cell lines with high-risk score revealed increased metastasis. In three external cohorts, our risk score was identified as the independent prognostic factor for overall and recurrence-free survival.
Conclusion: The risk score from the 6-gene classifier can successfully predict the prognosis of gastric cancer.
(© 2024. The Author(s).)
Methods: Out of 1003 mEGCs, all Npos were matched to Nneg using propensity scores. Machine learning approach comparing Npos and Nneg was used to develop prognostic signature. The function and robustness of prognostic signature was validated using cell lines and external datasets.
Results: Extensive machine learning with cross-validation identified the prognostic classifier consisting of four overexpressed genes (HDAC5, NPM1, DTX3, and PPP3R1) and two downregulated genes (MED12 and TP53), and enabled us to develop the risk score predicting poor prognosis. Cell lines engineered to high-risk score showed increased invasion, migration, and resistance to 5-FU and Oxaliplatin but maintained sensitivity to an HDAC inhibitor. Mouse models after tail vein injection of cell lines with high-risk score revealed increased metastasis. In three external cohorts, our risk score was identified as the independent prognostic factor for overall and recurrence-free survival.
Conclusion: The risk score from the 6-gene classifier can successfully predict the prognosis of gastric cancer.
(© 2024. The Author(s).)