||5R01CA207456-03 Interpret this number
||H. Lee Moffitt Cancer Ctr & Res Inst
||Epidemiology and Biology of Lncrnas in Ovarian Cancer
Genome-wide association studies (GWAS) have been unequivocally successful. For epithelial
ovarian cancer (EOC), our international Ovarian Cancer Association Consortium (OCAC) has
contributed to the discovery of all known risk loci. Although more loci certainly exist, the
anticipated modest effect sizes require large sample sizes to permit discrimination at accepted
levels of genome-wide significance. Since virtually every case-control study in the world is
already collaborating on these efforts as part of NCI's GAME-On OncoArray genotyping
initiative, increasing the sample size is not an option in the near term. Rather, further progress
requires innovative use of largely existing epidemiologic and molecular datasets. In the
proposed study, we seek to build upon the observation that most GWAS ?hits? reside in non-
coding regions of the genome and our preliminary data that support the hypothesis that a
significant portion of inter-individual variability in EOC susceptibility reflects single nucleotide
polymorphisms (SNPs) in long non-coding RNAs (lncRNAs). Our project will include three
phases. First, we will catalogue all known germline genetic variants associated with lncRNAs
and EOC susceptibility using existing genotype data on more than 28,000 cases and 36,000
controls from OCAC imputed to 1000 Genomes Project density, annotation from the most
comprehensive lncRNA database (GENCODE), and data from the largest RNA-sequencing
project performed to identify EOC-specific lncRNAs. We will then detect lncRNAs associated
with EOC using existing RNA-sequencing (RNA-seq) and microarray data plus data to be
generated from a whole transcriptome array. LncRNA expression quantitative trait loci (lnc-
eQTL) analysis will be performed to identify the most promising lncRNA SNPs and lncRNAs,
and network analyses will be conducted to highlight regulatory networks that may underlie EOC
development. In the final phase, we will follow-up the most promising findings in the laboratory
to explore the functional and biological basis. This integrative molecular epidemiologic approach
which capitalizes on resources and expertise that are unique to OCAC may lead to the
identification and characterization of novel SNPs and lncRNAs that may be of clinical utility in
reducing the burden of EOC.
Integration Of Population-level Genotype Data With Functional Annotation Reveals Over-representation Of Long Noncoding Rnas At Ovarian Cancer Susceptibility Loci
, Permuth J.B.
, Chen Y.A.
, Teer J.K.
, Monteiro A.N.
, Chen Z.
, Tyrer J.
, Berchuck A.
, Chenevix-Trench G.
, Doherty J.A.
, et al.
Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2017 Jan; 26(1), p. 116-125.