Our lab is affiliated with Vanderbilt University Medical Center, Departments of Medicine and Bioinformatical Informatics. We have a broad interest in the research of cancer etiology, prevention and precision medicine through developing bioinformatic and statistical approaches and intergraring multi-omics data, with a major goal of identifying genetic susceptibility factors for human
i) We are applying and developing bioinformatics tools and pipelines to process large multi-omics data, including whole genome sequencing (WGS), whole exome sequencing (WES), RNA-seq, array-based genotype, epigenetics and proteomics data, as well as metabolomics data. We have established computing platforms via our local university computing resource (Advanced Computing Center for Research & Education, ACCRE) and Amazon Web Services (AWS) to handle population-based sequencing and high-dimensional omicis data for identifying risk genetic variants (i.e. coding and structure variants) and somatic mutations in human cancers.
ii) We are highly interested in developing computational epigenetics (i.e. ChIP-seq and ATAC-seq) and statistical approaches to improve discovery of susceptibility non-coding variants (i.e. regulatory variants) and genes from current study designs of genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS).
iii) We are building statistical models to explore the inter-relationship of somatic alterations in tumor tissues (i.e. tumor mutational budern/mutational signatures/tumor-infiltrating lymphocytes (TILs)) with genetic susceptibility and carcinogens environmental exposures in human cancers.
iv) In order to understand the underlying molecular mechanisms of carcinogenesis, we are conducting cell and molecular biology studies, including in vitro functional assays and ChIP-seq to investigate transcription factor regulation mechanisms and biological functions of genes in cell proliferation, invasion, and clonogenesis.
Selected publications (# corresponding author):
Wen W#, Chen Z, Bao J, Long Q, Shu XO, Zheng W, Guo X#. Genetic variations of DNA bindings of FOXA1 and co-factors in breast cancer susceptibility. Nature communcations 10.1038/s41467-021-25670-9.
Holowatyj AN#, Eng C, Wen W, Idrees K, Guo X#. Spectrum of Somatic Cancer Gene Variations Among Adults With Appendiceal Cancer by Age at Disease Onset. JAMA Netw Open. 2020 Dec 1;3(12):e2028644. doi: 10.1001/jamanetworkopen.2020.28644. PMID: 33295976.
Guo X#,*, Lin W,*, Wen W, Huyghe J, Bien S, Cai Q, Harrison T, Chen Z, Qu C, Bao J, Long J, ... Casey G, Hsu L, Jenkins MA, Gruber SB, Peters U, Zheng W. Identifying Novel Susceptibility Genes for Colorectal Cancer Risk From a Transcriptome-Wide Association Study of 125,478 Subjects. Gastroenterology. 2021 Mar;160(4):1164-1178.e6. PMID: 33058866.
Chen Z, Wen W, Beeghly-Fadiel A, Shu XO, Díez-Obrero V, Long J, Bao J, Wang J, Liu Q, Cai Q, Moreno V, Zheng W, Guo X#. Identifying Putative Susceptibility Genes and Evaluating Their Associations with Somatic Mutations in Human Cancers. Am J Hum Genet. 2019 Jul 26. pii: S0002-9297(19)30269-1. PMID: 31402092.
Guo X#,* , Lin W*, Bao J, Cai Q, Pan X, Bai M, Yuan Y, Shi J, Sun Y, Han MR, Wang J, Liu Q, Wen W, Li B, Long J, Chen J, Zheng W. A Comprehensive cis-eQTL Analysis Revealed Target Genes in Breast Cancer Susceptibility Loci Identified in Genome-wide Association Studies. Am J Hum Genet. 2018 May 3;102(5):890-903. PMID: 29727689. PMCID: PMC5986971.
We are looking for enthusiastic postdoctoral associates to join our group. Candidates should have PhD in bioinformatics, computational biology, biostatistics, epidemiology, genetics/genomics, molecular biology or other related fields. Please contact the PI, Xingyi Guo, for details.