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Identification of a seven autophagy-related gene pairs signature for the diagnosis of colorectal cancer using the RankComp algorithm.
Song, Qi-Shi; Wu, Hai-Jun; Lin, Qian; Tang, Yu-Kai.
Affiliation
  • Song QS; Department of Oncology, Xiangya Hospital of Central South University, Changsha, P. R. China.
  • Wu HJ; Department of Oncology, Xiangya Hospital of Central South University, Changsha, P. R. China.
  • Lin Q; Department of Oncology, Xiangya Hospital of Central South University, Changsha, P. R. China.
  • Tang YK; Department of Oncology, Xiangya Hospital of Central South University, Changsha, P. R. China.
J Bioinform Comput Biol ; 21(3): 2350012, 2023 06.
Article in En | MEDLINE | ID: mdl-37325865
ABSTRACT
Based on the colorectal cancer microarray sets gene expression data series (GSE) GSE10972 and GSE74602 in colon cancer and 222 autophagy-related genes, the differential signature in colorectal cancer and paracancerous tissues was analyzed by RankComp algorithm, and a signature consisting of seven autophagy-related reversal gene pairs with stable relative expression orderings (REOs) was obtained. Scoring based on these gene pairs could significantly distinguish colorectal cancer samples from adjacent noncancerous samples, with an average accuracy of 97.5% in two training sets and 90.25% in four independent validation GSE21510, GSE37182, GSE33126, and GSE18105. Scoring based on these gene pairs also accurately identifies 99.85% of colorectal cancer samples in seven other independent datasets containing a total of 1406 colorectal cancer samples.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Colonic Neoplasms Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: J Bioinform Comput Biol Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Colonic Neoplasms Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: J Bioinform Comput Biol Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2023 Document type: Article
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