Derivation of a fifteen gene prognostic panel for six cancers.
The hallmarks of cancer deem biological pathways and molecules to be conserved. This approach may be useful for deriving a prognostic gene signature. Weighted Gene Co-expression Network Analysis of gene expression datasets in eleven cancer types identified modules of highly correlated genes and interactive networks conserved across glioblastoma, breast, ovary, colon, rectal and lung cancers, from which a universal classifier for tumor stratification was extracted. Specific conserved gene modules were validated across different microarray platforms and datasets. Strikingly, preserved genes within these modules defined regulatory networks associated with immune regulation, cell differentiation, metastases, cell migration, metastases, oncogenic transformation, and resistance to apoptosis and senescence, with AIF1 and PRRX1 being suggested to be master regulators governing these biological processes. A universal classifier from these conserved networks enabled execution of common set of principles across different cancers that revealed distinct, differential correlation of biological functions with patient survival in a cancer-specific manner. Correlation analysis further identified a panel of 15 risk genes with potential prognostic value, termed as the GBOCRL-IIPr panel [(GBM-Breast-Ovary-Colon-Rectal-Lung)-Immune-Invasion-Prognosis], that surprisingly, were not amongst the master regulators or important network hubs. This panel may now be integrated in predicting patient outcomes in the six cancers.
National Centre for Cell Science, NCCS Complex, Pune 411007, India.
Mamata F
MF
Khirade
National Centre for Cell Science, NCCS Complex, Pune 411007, India.
Girdhari
G
Lal
National Centre for Cell Science, NCCS Complex, Pune 411007, India.
Sharmila A
SA
Bapat
D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods; D052138:Genes, Neoplasm; D005819:Genetic Markers / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006801:Humans; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000235:genetics / Q000378:metabolism*; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D015398:Signal Transduction / Q000235:genetics
D014408:Biomarkers, Tumor; D005819:Genetic Markers; D009363:Neoplasm Proteins