Hispanic or Latino study with RNA-Seq, WXS data on dbGaP (140 participants)

phs003218 — Whole Exome Sequencing and RNA-Seq to Characterize the Somatic Breast    Cancer Landscape Among Latinas in California

Somatic mutational profiles are increasingly being used to guide treatment. However, there is a dearth of data from non-European populations. To address this gap, we conducted paired tumor/normal whole exome paired-end sequencing and tumor RNA-Seq on 146 breast tumors from 140 Hispanic/Latina (H/L) women with breast cancer. We characterized somatic mutations, copy number alterations, tumor subtypes [Prediction Analysis of Microarray 50 (PAM50)], <a href="https://cancer.sanger.ac.uk/cosmic">Catalogue Of Somatic Mutations In Cancer </a>(COSMIC) mutation signatures and expression profiles, and compared them to breast tumors from non-Hispanic White (White) women in <a href="https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga">The Cancer Genome Atlas</a> (TCGA). Using MutSigCV, we found that the most commonly mutated genes, including <a href="https://www.ncbi.nlm.nih.gov/gene/7157">TP53</a>, <a href="https://www.ncbi.nlm.nih.gov/gene/861">RUNX1</a>, <a href="https://www.ncbi.nlm.nih.gov/gene/5728">PTEN</a>, <a href="https://www.ncbi.nlm.nih.gov/gene/5290">PIK3CA</a>, <a href="https://www.ncbi.nlm.nih.gov/gene/4214">MAP3K1</a>, <a href="https://www.ncbi.nlm.nih.gov/gene/2625">GATA3</a>, <a href="https://www.ncbi.nlm.nih.gov/gene/999">CDH1</a> and <a href="https://www.ncbi.nlm.nih.gov/gene/865">CBFB</a>, were similar to those in breast tumors from non-Hispanic white women. Novel findings were that outliers of <a href="https://www.ncbi.nlm.nih.gov/gene/9703">BLTP2</a> (aka KIAA0100) over-expression and COSMIC mutational signature 16 were more common in tumors from H/L women than White women. We also identified that the known germline APOBEC3A/B deletion variant was significantly more common in H/L women and was associated with indigenous American ancestry. Data available through dbGaP will be whole-exome sequencing (WES) and RNA sequencing (RNA-Seq) data, as well as phenotypic data, including estrogen receptor, progesterone receptor, and HER2 receptor status, tumor histology, stage, and grade, and age at diagnosis.