A comprehensive genomic characterization of esophageal squamous cell carcinoma: from prognostic analysis to in vivo assay. Issue 1 (11th August 2016)

• Record Type: Journal Article
• Authors: Chen, Yuan‐Bin; Jia, Wei‐Hua
• Is Part Of: Cancer communications. Volume 35:Issue 1(2016)
• Page Start: 1
• Page End: 3
• Publication Date: 2016-08-11
• Subjects: Esophageal squamous cell carcinoma -- Copy number variation -- Prognostic analysis; Cancer -- Periodicals; Neoplasms; Electronic journals; Periodical; Fulltext; Internet Resources; Periodicals; Periodicals; 616.994005
• DOI: 10.1186/s40880-016-0142-y
• Languages: English
• ISSNs: 2523-3548

Abstract

Abstract: Background: Esophageal squamous cell carcinoma (ESCC) is a leading cause of cancer death worldwide and is characterized by numerous genetic mutations. TNM staging is not sufficient for predicting patient outcomes. Additionally, ESCC shows poor responsiveness to chemotherapy and radiation. Thus, there is an urgent need to find efficient therapy targets. Previous ESCC high‐throughput genomic studies have lacked intensive survival analysis, particularly for copy number variation (CNV) and the genes involved. Main body: In the study "Genomic Characterization of Esophageal Squamous Cell Carcinoma Reveals Critical Genes Underlying Tumorigenesis and Poor Prognosis" recently published in the American Journal of Human Genetics, we comprehensively analyzed the effects of CNVs, mutations, and relative gene expression on patient outcomes. To validate our findings for our 67 sequencing samples, we collected a 321‐patient retrospective cohort with detailed 5‐year follow‐up information and carried out univariate and multivariate survival analyses. In addition, the biological functions of the survival predictors in ESCC were investigated both in vitro and in vivo. Conclusions: We found the independent ESCC survival predictors and potential therapy targets. Nevertheless, the effects of numerous low‐frequency mutations need to be explored using larger sample sequencing. Overall, constructing multi‐gene prognostic signatures will remain a great challenge in the future.