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Pancancer survival analysis of cancer hallmark genes
Open accessAbstract
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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“Kaplan–Meier analysis using public breast cancer meta-analysis database11,30 reveals that TNBC patients with higher hypoxia gene signature are associated with worse disease outcomes, including both overall survival (OS) and distant metastasis-free survival (DMFS), compared to those with lower expression of hypoxia gene signature (Fig. 1h).”
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Identification of mRNA Prognostic Markers for TGCT by Integration of Co-Expression and CeRNA Network
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Aberrant Expression and Prognostic Potential of IL-37 in Human Lung Adenocarcinoma
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Metadata
- Authors
- Nagy, Á., Munkácsy, G., & Győrffy, B.
- Affiliations
- Semmelweis University (HU)
- Corresponding author
- Győrffy, Balázs
- Venue
- Scientific Reports
- Published
- 2021-03-15
- Volume
- 11
- Issue
- 1
- Pages
- 6047-6047
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC7961001
- OpenAlex
- W3139511935
- Cited by
- 1,381
- References
- 40
- Citations by year
- 2026: 38 · 2025: 84 · 2024: 145 · 2023: 504 · 2022: 311 · 2021: 298
- FWCI
- 101.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Semmelweis Egyetem
- Innovációs és Technológiai Minisztérium (ÚNKP-19-3, 2018-2.1.17-TET-KR-00001)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- prognostic gene signature, survival analysis, genomic instability, invasion and metastasis, replicative immortality, cell death resistance, angiogenesis, tumor suppressor, BRCA1, RUNX1, SERPINE1, CDK1, E2F1, epiregulin, c-Myc, clear cell renal cell carcinoma, low-grade glioma, cervical cancer, bladder cancer, thyroid cancer, glioblastoma, tissue specificity, targeted therapy
- MeSH terms
- RNA-Seq, Humans, Neoplasms, Biomarkers, Tumor, Survival Rate, Disease-Free Survival, Databases, Nucleic Acid, Kaplan-Meier Estimate
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