Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients

Oncotarget
Yun Hak KimSae-Ock Oh

Abstract

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison ...Continue Reading

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Citations

Sep 12, 2018·Journal of Cellular Biochemistry·Mihyang HaYun Hak Kim
Nov 9, 2019·Animal Cells and Systems·Mihyang HaSae-Ock Oh
Oct 26, 2018·Scientific Reports·Myoung-Eun HanSae-Ock Oh
May 6, 2020·Journal of Medical Internet Research·Kyoungjune PakYun Hak Kim
Feb 8, 2019·Journal of Cellular and Molecular Medicine·Kyoungjune PakSae-Ock Oh
Feb 2, 2021·Frontiers in Oncology·Enrique Hernández-Lemus, Mireya Martínez-García
Feb 28, 2020·Genetic Testing and Molecular Biomarkers·Mihyang HaSae-Ock Oh

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Datasets Mentioned

BETA
GSE22219
GSE37181
GSE42568
GSE7390

Software Mentioned

METABRIC
R package ‘ coxnet
R package ‘ glmnet
GEOquery
R package ‘ survival
R
Net
R package ‘ survAUC ’
survAUC
score

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