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. 2021 Mar 15;11(1):6047.
doi: 10.1038/s41598-021-84787-5.

Pancancer survival analysis of cancer hallmark genes

Ádám Nagy  1   2 , Gyöngyi Munkácsy  1 , Balázs Győrffy  3   4
Affiliations

Pancancer survival analysis of cancer hallmark genes

Ádám Nagy et al. Sci Rep. .

Abstract

Cancer hallmark genes are responsible for the most essential phenotypic characteristics of malignant transformation and progression. In this study, our aim was to estimate the prognostic effect of the established cancer hallmark genes in multiple distinct cancer types. RNA-seq HTSeq counts and survival data from 26 different tumor types were acquired from the TCGA repository. DESeq was used for normalization. Correlations between gene expression and survival were computed using the Cox proportional hazards regression and by plotting Kaplan-Meier survival plots. The false discovery rate was calculated to correct for multiple hypothesis testing. Signatures based on genes involved in genome instability and invasion reached significance in most individual cancer types. Thyroid and glioblastoma were independent of hallmark genes (61 and 54 genes significant, respectively), while renal clear cell cancer and low grade gliomas harbored the most prognostic changes (403 and 419 genes significant, respectively). The eight genes with the highest significance included BRCA1 (genome instability, HR 4.26, p < 1E-16), RUNX1 (sustaining proliferative signaling, HR 2.96, p = 3.1E-10) and SERPINE1 (inducing angiogenesis, HR 3.36, p = 1.5E-12) in low grade glioma, CDK1 (cell death resistance, HR = 5.67, p = 2.1E-10) in kidney papillary carcinoma, E2F1 (tumor suppressor, HR 0.38, p = 2.4E-05) and EREG (enabling replicative immortality, HR 3.23, p = 2.1E-07) in cervical cancer, FBP1 (deregulation of cellular energetics, HR 0.45, p = 2.8E-07) in kidney renal clear cell carcinoma and MYC (invasion and metastasis, HR 1.81, p = 5.8E-05) in bladder cancer. We observed unexpected heterogeneity and tissue specificity when correlating cancer hallmark genes and survival. These results will help to prioritize future targeted therapy development in different types of solid tumors.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Overview of cutoff determination and survival distribution in the database. The determination of the best cutoff value in the survival analysis demonstrated with the CDK1 gene in kidney papillary carcinoma (A) and ovarian cancer (B). Survival time characteristics of tumors with observed events (C).
Figure 2
Figure 2
The prognostic power of cancer hallmark genes.
Figure 3
Figure 3
Effect of hallmark signatures (A) and tumor mutation burden (C) on patient survival. Summary of the significant prognostic hallmark signatures in different types of tumors (B).
Figure 4
Figure 4
Best performing genes in at least 10 distinct tumor types.
See this image and copyright information in PMC

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