Complex regulatory mechanisms involved in cancer development and progression in many cases are not reflected on mRNA expression level. In this case, the expression level of a gene may not correlate to survival while the gene can play essential role in cancer. Nevertheless the gene expression itself might not be predictive of a patient survival, multiple interaction partners of the gene (gene "interactome") might demonstrate significant correlation and, thus, could be indicative of the gene potential primary role in cancer. PPISURV allows you to test potential of the gene "iteractome" (compare to the gene itself) to predict survival in multiple cancer types based on more then 40 currently publicly available gene expression datasets covering ~ 8000 patients in total.


View PPISURV online video tutorial


Please specify a gene (Gene Symbol):
Additional options:
Select the source of gene interactions: By default, all interaction sources are used.
IntAct (PPI interactions)
Select a cancer type: By default, all datasets are used.
breast cancer (17 datasets,3337 patients)
ovarian cancer (4 datasets,790 patients)
lung cancer (6 datasets,638 patients)
multiple myeloma (1 datasets,559 patients)
diffuse large b cell lymphoma (1 datasets,412 patients)
hepatocellular carcinoma (2 datasets,324 patients)
colon cancer (2 datasets,316 patients)
prostate cancer (1 datasets,281 patients)
meningioma (1 datasets,252 patients)
chronic lymphocytic leukemia (2 datasets,236 patients)
glioblastoma (1 datasets,191 patients)
liposarcoma (1 datasets,140 patients)
bladder cancer (1 datasets,103 patients)
high-grade glioma (1 datasets,77 patients)
urothelial carcinomas (1 datasets,73 patients)
astrocytic gliomas (1 datasets,51 patients)
cervical cancer (1 datasets,48 patients)