ArticleOncogene2014
PPISURV: a novel bioinformatics tool for uncovering the hidden role of specific genes in cancer survival outcome.
Article in Oncogene, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
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Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Multiple clinical studies have correlated gene expression with survival outcome in cancer on a genome-wide scale. However, in many cases, no obvious correlation between expression of well-known tumour-related genes (that is, p53, p73 and p21) and survival rates of patients has been observed. This can be mainly explained by the complex molecular mechanisms involved in cancer, which mask the clinical relevance of a gene with multiple functions if only gene expression status is considered. As we demonstrate here, in many such cases, the expression of the gene interaction partners (gene 'interactome') correlates significantly with cancer survival and is indicative of the role of that gene in cancer. On the basis of this principle, we have implemented a free online datamining tool (http://www.bioprofiling.de/PPISURV). PPISURV automatically correlates expression of an input gene interactome with survival rates on >40 publicly available clinical expression data sets covering various tumours involving about 8000 patients in total. To derive the query gene interactome, PPISURV employs several public databases including protein-protein interactions, regulatory and signalling pathways and protein post-translational modifications.
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23686313What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.