Leveraging Methylation Alterations to Discover Potential Causal Genes Associated With the Survival Risk of Cervical Cancer in TCGA Through a Two-Stage Inference Approach

Abstract

BackgroundMultiple genes were previously identified to be associated with cervical cancer; however, the genetic architecture of cervical cancer remains unknown and many potential causal genes are yet to be discovered.MethodsTo explore potential causal genes related to cervical cancer, a two-stage causal inference approach was proposed within the framework of Mendelian randomization, where the gene expression was treated as exposure, with methylations located within the promoter regions of genes serving as instrumental variables. Five prediction models were first utilized to characterize the relationship between the expression and methylations for each gene; then, the methylation-regulated gene expression (MReX) was obtained and the association was evaluated via Cox mixed-effect model based on MReX. We further implemented the aggregated Cauchy association test (ACAT) combination to take advantage of respective strengths of these prediction models while accounting for dependency among the p-values.ResultsA total of 14 potential causal genes were discovered to be associated with the survival risk of cervical cancer in TCGA when the five prediction models were separately employed. The total number of potential causal genes was brought to 23 when conducting ACAT. Some of the newly discovered genes may be novel (e.g., YJEFN3, SPATA5L1, IMMP1L, C5orf55, PPIP5K2, ZNF330, CRYZL1, PPM1A, ESCO2, ZNF605, ZNF225, ZNF266, FICD, and OSTC). Functional analyses showed that these genes were enriched in tumor-associated pathways. Additionally, four genes (i.e., COL6A1, SYDE1, ESCO2, and GIPC1) were differentially expressed between tumor and normal tissues.ConclusionOur study discovered promising candidate genes that were causally associated with the survival risk of cervical cancer and thus provided new insights into the genetic etiology of cervical cancer.

IUSMMT: Survival mediation analysis of gene expression with multiple DNA methylation exposures and its application to cancers of TCGA

“…The distance of 500 bps is to some extent arbitrary and experience-based. In fact, the optimal extension distance upstream of TSS is not clear and various choices were applied in prior literature [139]. To examine the robustness of various extension distances, we performed a sensitivity analysis by incorporating methylation CpG sites within distinct extended regions, and found that the extension of the distance upstream of TSS in defining methylation loci seems to be very robust and has little influence on our final identification of mediating genes for methylation levels measured with the 450K platform (S9 Fig).…”

Zinc finger protein 330 regulates Ramie mosaic virus infection in the whitefly Bemisia tabaciMED

“…15 Recent studies have found that ZNF330 is associated with the survival risk of cervical cancer. 19 However, the function of ZNF330 in B. tabaci still needs to be determined.…”

“…When apoptosis is initiated, it is released to the cytosol and contributes to the release of cytochrome C. It is a mediator of the mitochondrial apoptotic pathway 15 . Recent studies have found that ZNF330 is associated with the survival risk of cervical cancer 19 . However, the function of ZNF330 in B. tabaci still needs to be determined.…”

Racial Bias Can Confuse AI for Genomic Studies

“…In this work, we took the TCGA dataset as a case study and conducted a comprehensive investigation of the effects of race imbalance on the statistical and machine learning analytical strategies and discoveries of the project. We quantitatively evaluated how the racial bias could affect the biological outcomes by conducting racial-biased tests in two respective machine learning tasks, i.e., the causal gene discoveries [32] and patient survivorship predictions [33]. In the causal gene discoveries, we found causal genes identified from overall populations were significantly different from those on minor race samples only, even using the race identity as a confounding adjustment.…”