ArticleScientific reports2017
Robust method for identification of prognostic gene signatures from gene expression profiles.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Improved prognostic survival models for pediatric medulloblastoma using high dimensional gene expression data.BMC medical genomics · 2026Article
- VSTM2L is a promising therapeutic target and a prognostic soluble-biomarker in cholangiocarcinoma.BMB reports · 2024Article
- Article
- Soluble TGFBI aggravates the malignancy of cholangiocarcinoma through activation of the ITGB1 dependent PPARγ signalling pathway.Cellular oncology (Dordrecht, Netherlands) · 2022Article
- Transcriptomic Profiling Identifies DCBLD2 as a Diagnostic and Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma.Frontiers in molecular biosciences · 2021Article
- Predicting the effect of 5-fluorouracil-based adjuvant chemotherapy on colorectal cancer recurrence: A model using gene expression profiles.Cancer medicine · 2020Article
- Blockade of integrin α3 attenuates human pancreatic cancer via inhibition of EGFR signalling.Scientific reports · 2019Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the last decade, many attempts have been made to use gene expression profiles to identify prognostic genes for various types of cancer. Previous studies evaluating the prognostic value of genes suffered by failing to solve the critical problem of classifying patients into different risk groups based on specific gene expression threshold levels. Here, we present a novel method, called iterative patient partitioning (IPP), which was inspired by the receiver operating characteristic (ROC) curve, is based on the log-rank test and overcomes the threshold decision problem. We applied IPP to analyze datasets pertaining to various subtypes of breast cancer. Using IPP, we discovered both novel and well-studied prognostic genes related to cell cycle/proliferation or the immune response. The novel genes were further analyzed using copy-number alteration and mutation data, and these results supported their relationship with prognosis.
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Registered trials
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