Fig 1.
PESSA (v1.0.0) currently incorporates a total of 238 datasets from TCGA and GEO and a total of 13,434 predefined tumor-related gene sets from MSigDB. After data preprocessing in the background, PESSA provides the user with attractive and informative Kaplan–Meier curves and allows the user to customize the settings. Abbreviations: GEO: the Gene Expression Omnibus; MSigDB: the Molecular Signatures Database; TCGA: The Cancer Genome Atlas. Fig 1 cliparts are from Openclipart.
Fig 2.
Survival analysis feedback Kaplan–Meier curve.
Survival analysis of patients in the median-grouped TCGA-BLCA dataset using the gene set TGF-beta Receptor Activation Levels in Emt Epithelial to Mesenchymal Transition (TGF-beta Receptor Activation Levels in Emt Epithelial to Mesenchymal Transition) sourced from the Reactome database. The results from the TCGA-BLCA dataset indicate that BLCA patients with high levels of activation of the TGF-beta Receptor EMT-related gene set (TGF-beta Receptor Signalling in Emt Epithelial to Mesenchymal Transition) had significantly shorter OS times than patients with low levels of activation. Abbreviations: BLCA: Bladder Cancer; OS: Overall Survival; TCGA: The Cancer Genome Atlas.
Fig 3.
Feedback Kaplan-Meier curves for survival analysis based on immunosuppressive therapy data.
A. Using the median dichotomous group-based dataset of patients with bladder cancer after PD1 inhibitor treatment, GSE176307, the results of the survival analysis demonstrated that the highly activated DNA damage repair pathway possessed a longer overall survival time. B. Examined using a built-in dataset derived from PMID 26997480 and 35243413 based on median dichotomous subgroups of PD1 inhibitor-treated melanoma patients, the results of the survival analyses demonstrated that the highly activated DNA damage repair pathway possessed a longer overall survival time.