Abstract PS18-12: Comparative analysis of differential gene expression by ancestry using primary breast cancers from Nigeria and the cancer genome atlas (TCGA)
Authors: Rajagopal Padma Sheila , Tsai Yi-Hsuan S , Hardeman Ashley , Hurley Ian , Sallam Aminah , Zheng Yonglan , Yoshimatsu Toshio , Woodard Anna , Huo Dezheng , Gao Guimin , Perou Charles M , Parker Joel S , Chen Mengjie , Olopade Olufunmilayo I 
Published: February 2021

Introduction: Breast cancers differ between genomic and transcriptomic features by ancestry within the TCGA, but current understanding of how gene expression differs across global ancestral populations is extremely limited. We hypothesized that differential expression performed by ancestry and geography may provide insight into population-specific, clinically relevant expression patterns.

Objective: To compare differentially expressed protein-coding genes and pathways among primary breast tumors of Nigerian origin versus African- and European-American ancestry in TCGA

Methods: We analyzed an integrated dataset of RNA-seq from 93 women in Nigeria, 31 African-ancestry women (TCGA AA), and 39 European-ancestry women from TCGA (TCGA EA) with whole-genome data. Ancestry within TCGA was classified by principal component analysis, with African ancestry as &gt;50% contribution and European ancestry as &gt;90% contribution. RNA was obtained from tumors in Nigeria using Qiagen PAXgene kits. A STAR/HTSeq pipeline generated read counts. To optimize assay-associated batch effects, we performed differential expression within each PAM50 subtype using limma-voom with quantile normalization. Significance was defined as a &gt; 1.5-fold change in gene expression (log2 scale) with a false-discovery-rate-adjusted p-value of 0.05. Pathway analysis was performed via Gene Ontology and the Web-Based Gene Set Analysis Toolkit. We also compared gene expression, claudin-low (30 genes) and VEGF (13 genes) signatures to an additional set of 189 primary breast cancers from Nigeria assayed on the NanoString nCounter System using a custom Nano110 probe set (PAM50 + claudin-low & VEGF genes). RNA for these cancers was isolated from paraffin-embedded tumor using the Roche High Pure paraffin kit.

Results: Differential expression was performed pairwise across ancestry groups within PAM50 subtypes (see Table). Fewer genes were differentially expressed, and fold change smaller across shared genes, when comparing Nigerian vs. TCGA AA versus Nigerian vs. TCGA EA comparisons, supporting quantile normalization. The strongest gene ontology pathway associations, seen for all subtypes, were intracellular protein targeting and viral gene expression. The epigenetic regulation pathway was significantly associated with comparisons in Basal-like tumors (padj=1.54e-7 for TCGA EA, padj=0.001 for TCGA AA). The PI3K-Akt pathway was significantly associated with Nigerian vs. TCGA-EA within Luminal A (padj=0.006). The Nanostring cohort shared a similar distribution of PAM50 subtypes (see Table, X2 p=0.21). We found concordance in both Nigerian cohorts of relative claudin-low and VEGF expression signature patterns across subtypes. Of 17 genes with significant differential expression by ancestry in the Nanostring dataset, 9 (ADM, ACTB, BIRC5, CDC6, CENPF, MKI67, MPP1, RAD17, and VEGFA) showed significant differential expression by ancestry in the PAXgene dataset.

Discussion: This is one of the first analyses of differential gene expression across tumors from a global population. We identified differential pathways in breast tumors between African and European ancestry populations to target for future work. We also validated several ancestry-specific genes across platforms with potential clinical relevance. Understanding how molecular features differ across global populations will improve precision oncology for all patients.

PAM50ClassificationNigerian: PAXgene (n=93)TCGA AA (n=31)TCGA EA (n=39)Nigerian: Nanostring (n=189)Nigerian (PAXgene) vs. TCGA EA ComparisonNigerian (PAXgene) vs. TCGA AAComparisonBasal-like41 (42.8%)23 (74.1%)17 (43.6%)78 (41.3%)4893 genes4687 genesHer2-enriched27 (28.1%)05 (12.8%)31 (16.4%)961 genesN/ALuminal A14 (14.5%)4 (12.9%)8 (20.5%)39 (20.6%)2596 genes480 genesLuminal B11 (11.4%)4 (12.9%)9 (23.1%)25 (13.2%)2112 genes222 genes

Citation Format: Padma Sheila Rajagopal, Yi-Hsuan S Tsai, Ashley Hardeman, Ian Hurley, Aminah Sallam, Yonglan Zheng, Toshio Yoshimatsu, Anna Woodard, Dezheng Huo, Guimin Gao, Charles M Perou, Joel S Parker, Mengjie Chen, Olufunmilayo I Olopade. Comparative analysis of differential gene expression by ancestry using primary breast cancers from Nigeria and the cancer genome atlas (TCGA) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS18-12.