Meta-dimensional data integration identifies critical pathways for susceptibility, tumorigenesis and progression of endometrial cancer.

Runmin Wei,Xun Zhu,Sijia Huang,Immaculata De Vivo,Herbert Yu,Jason H Moore,Lana X Garmire,Harvey Risch

doi:10.18632/oncotarget.10509

Abstract

Endometrial Cancer (EC) is one of the most common female cancers. Genome-wide association studies (GWAS) have been investigated to identify genetic polymorphisms that are predictive of EC risks. Here we utilized a meta-dimensional integrative approach to seek genetically susceptible pathways that may be associated with tumorigenesis and progression of EC. We analyzed GWAS data obtained from Connecticut Endometrial Cancer Study (CECS) and identified the top 20 EC susceptible pathways. To further verify the significance of top 20 EC susceptible pathways, we conducted pathway-level multi-omics analyses using EC exome-Seq, RNA-Seq and survival data, all based on The Cancer Genome Atlas (TCGA) samples. We measured the overall consistent rankings of these pathways in all four data types. Some well-studied pathways, such as p53 signaling and cell cycle pathways, show consistently high rankings across different analyses. Additionally, other cell signaling pathways (e.g. IGF-1/mTOR, rac-1 and IL-5 pathway), genetic information processing pathway (e.g. homologous recombination) and metabolism pathway (e.g. sphingolipid metabolism) are also highly associated with EC risks, diagnosis and prognosis. In conclusion, the meta-dimensional integration of EC cohorts has suggested some common pathways that may be associated from predisposition, tumorigenesis to progression.

Highlights

Endometrial cancer (EC) arises from the endometrium, the inner lining of the uterus
Seven single nucleotide polymorphisms (SNPs) exceeded the moderate threshold of genomic-control corrected p-value (GC-P) < 1e-5 (Supplementary Figure 1, Supplementary data 1)
Our result suggests that the SNPs in CTNNA2 and CASP3 may have a synergistic effect on Endometrial Cancer (EC) risk

Summary

Introduction

Endometrial cancer (EC) arises from the endometrium, the inner lining of the uterus. It is the most prevalent gynecologic malignancy and one of the most common cause of deaths of women’s cancers. To seek genetic causality of EC, a series of genome-wide association studies (GWAS) have been conducted recently [2,3,4], with the focus on the association between single nucleotide polymorphisms (SNPs) and EC, inconsistencies abound in these studies. Besides the lack of replicability exemplified by the EC studies above, there exist other issues of SNPbased GWAS approach. Highly significant SNPs usually can only explain a small proportion of heritability while moderately significant SNPs may harbor predictive information [5,6,7]. Set-level GWAS is an appropriate approach to allow the consideration of effects from the moderately significant SNPs. Set-level GWAS is an appropriate approach to allow the consideration of effects from the moderately significant SNPs

Methods

Discussion

Conclusion