Conditional transcriptional relationships may serve as cancer prognostic markers

BMC Medical Genomics

Hui Yu¹  Yan Guo¹  Danqian Chen²  Jin Li³  Limei Wang⁴ 

[1] Department of Internal Medicine, University of New Mexico, 87131, Albuquerque, NM, USA;Key Laboratory of Resource Biology and Biotechnology in Western China, School of Life Sciences, Northwest University, 710069, Xi’an, Shaanxi, China;Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, 571199, Kaikou, Hainan, China;Key Laboratory of Tropical Translational Medicine of Ministry of Education, Hainan Medical University, 571199, Kaikou, Hainan, China;College of Intelligent Systems Science and Engineering, Harbin Engineering University, 150001, Harbin, Heilongjiang, China;

关键词: Cancer prognosis;    Correlation by Individual Level Product;    Conditional transcriptional relationships;   

DOI  :  10.1186/s12920-021-00958-3

来源: Springer

【 摘 要 】

BackgroundWhile most differential coexpression (DC) methods are bound to quantify a single correlation value for a gene pair across multiple samples, a newly devised approach under the name Correlation by Individual Level Product (CILP) revolutionarily projects the summary correlation value to individual product correlation values for separate samples. CILP greatly widened DC analysis opportunities by allowing integration of non-compromised statistical methods.MethodsHere, we performed a study to verify our hypothesis that conditional relationships, i.e., gene pairs of remarkable differential coexpression, may be sought as quantitative prognostic markers for human cancers. Alongside the seeking of prognostic gene links in a pan-cancer setting, we also examined whether a trend of global expression correlation loss appeared in a wide panel of cancer types and revisited the controversial subject of mutual relationship between the DE approach and the DC approach.ResultsBy integrating CILP with classical univariate survival analysis, we identified up to 244 conditional gene links as potential prognostic markers in five cancer types. In particular, five prognostic gene links for kidney renal papillary cell carcinoma tended to condense around cancer gene ESPL1, and the transcriptional synchrony between ESPL1 and PTTG1 tended to be elevated in patients of adverse prognosis. In addition, we extended the observation of global trend of correlation loss in more than ten cancer types and empirically proved DC analysis results were independent of gene differential expression in five cancer types.ConclusionsCombining the power of CILP and the classical survival analysis, we successfully fetched conditional transcriptional relationships that conferred prognosis power for five cancer types. Despite a general trend of global correlation loss in tumor transcriptomes, most of these prognosis conditional links demonstrated stronger expression correlation in tumors, and their stronger coexpression was associated with poor survival.

【 授权许可】

CC BY