Literature DB >> 33542224

A universal molecular prognostic score for gastrointestinal tumors.

Hideyuki Shimizu1, Keiichi I Nakayama2.   

Abstract

Colorectal and gastric cancers are a leading cause of cancer deaths in developed countries. Precise estimation of prognosis is important with regard to clinical decision making for individuals with such cancers. We here comprehensively compiled a complete atlas of prognostic genes based on an integrated meta-analysis of one of the largest assembled colorectal cancer cohorts. A simple yet robust machine learning approach was then applied to establish a universal molecular prognostic score (mPS_colon) that relies on the expression status of only 16 genes and which was validated with independent data sets. This score was found to be an independent prognostic indicator in multivariate models including cancer stage, to be valid independent of tumor characteristics or patient ethnicity, and to be also applicable to gastric cancer. We conclude that mPS_colon is a universal prognostic classifier for patients with gastrointestinal cancers and that it should prove informative for optimization of personalized therapy for such patients.

Entities:  

Year:  2021        PMID: 33542224      PMCID: PMC7862603          DOI: 10.1038/s41525-021-00172-1

Source DB:  PubMed          Journal:  NPJ Genom Med        ISSN: 2056-7944            Impact factor:   8.617


  36 in total

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3.  Complementary strand microRNAs mediate acquisition of metastatic potential in colonic adenocarcinoma.

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Journal:  Hum Mutat       Date:  2003-03       Impact factor: 4.878

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Review 7.  Global Cancer Incidence and Mortality Rates and Trends--An Update.

Authors:  Lindsey A Torre; Rebecca L Siegel; Elizabeth M Ward; Ahmedin Jemal
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8.  Interaction between Tumor-Associated Dendritic Cells and Colon Cancer Cells Contributes to Tumor Progression via CXCL1.

Authors:  Ya-Ling Hsu; Yi-Jen Chen; Wei-An Chang; Shu-Fang Jian; Hsiao-Li Fan; Jaw-Yuan Wang; Po-Lin Kuo
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9.  A 23 gene-based molecular prognostic score precisely predicts overall survival of breast cancer patients.

Authors:  Hideyuki Shimizu; Keiichi I Nakayama
Journal:  EBioMedicine       Date:  2019-07-26       Impact factor: 8.143

10.  TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data.

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Journal:  Nucleic Acids Res       Date:  2015-12-23       Impact factor: 16.971

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  1 in total

1.  A Tumor Progression Related 7-Gene Signature Indicates Prognosis and Tumor Immune Characteristics of Gastric Cancer.

Authors:  Fen Liu; Zongcheng Yang; Lixin Zheng; Wei Shao; Xiujie Cui; Yue Wang; Jihui Jia; Yue Fu
Journal:  Front Oncol       Date:  2021-06-14       Impact factor: 6.244

  1 in total

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