Integrated analysis of public datasets for the discovery and validation of survival-associated genes in solid tumors
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PUBLIC SUMMARY
- ■ We established a large integrated transcriptomic database of colorectal cancer suitable for biomarker discovery.
- ■ The cohort was used to uncover genes with the highest correlation to relapse-free survival in colon cancer.
- ■ The top genes were filtered to include hits with higher expression and potential druggability.
- ■ This pipeline can be used to prioritize clinically useful biomarkers of solid tumors by excluding likely failures.
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ABSTRACT
Identifying genes with prognostic significance that can act as biomarkers in solid tumors can help stratify patients and uncover novel therapy targets. Here, our goal was to expand our previous ranking analysis of survival-associated genes in various solid tumors to include colon cancer specimens with available transcriptomic and clinical data. A Gene Expression Omnibus search was performed to identify available datasets with clinical data and raw gene expression measurements. A combined database was set up and integrated into our Kaplan-Meier plotter, making it possible to identify genes with expression changes linked to altered survival. As a demonstration of the utility of the platform, the most powerful genes linked to overall survival in colon cancer were identified using uniand multivariate Cox regression analysis. The combined colon cancer database includes 2, 137 tumor samples from 17 independent cohorts. The most significant genes associated with relapse-free survival with a false discovery rate below 1% in colon cancer carcinoma were RBPMS(hazard rate [HR] = 2.52), TIMP1 (HR = 2.44), and COL4A2 (HR = 2.36). The three strongest genes associated with shorter survival in stage Ⅱ colon cancer include CSF1R (HR = 2.86), FLNA (HR = 2.88), and TPBG (HR = 2.65). In summary, a new integrated database for colon cancer is presented. A colon cancer analysis subsystem was integrated into our Kaplan-Meier plotter that can be used to mine the entire database (https://www.kmplot.com). The portal has the potential to be employed for the identification and prioritization of promising biomarkers and therapeutic target candidates in multiple solid tumors including, among others, breast, lung, ovarian, gastric, pancreatic, and colon cancers. -
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REFERENCES
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Győrffy B. (2024). Integrated analysis of public datasets for the discovery and validation of survival-associated genes in solid tumors. The Innovation 5(3), 100625. https://doi.org/10.1016/j.xinn.2024.100625
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Győrffy B. (2024). Integrated analysis of public datasets for the discovery and validation of survival-associated genes in solid tumors. The Innovation 5(3), 100625. https://doi.org/10.1016/j.xinn.2024.100625
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Figure 1.
Clinicopathological characteristics of all tumor samples contained within the integrated database
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Figure 2.
Most robust genes associated with relapse-free survival in colon carcinoma
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Figure 3.
Most significant druggable genes associated with shorter relapse-free survival
