Background Endocrine-resistant HR+/HER2- breast cancer (BC) and triple-negative BC (TNBC) are of interest for molecularly informed treatment due to their aggressive natures and limited treatment profiles. Patients of African Ancestry (AA) experience higher rates of TNBC and mortality than European Ancestry (EA) patients, despite lower overall BC incidence. Here, we compare the molecular landscapes of AA and EA patients with HR+/HER2- BC and TNBC in a real-world cohort to promote equity in precision oncology by illuminating the heterogeneity of potentially druggable genomic and transcriptomic pathways. Methods De-identified records from patients with TNBC or HR+/HER2- BC in the Tempus Database were randomly selected (N = 5000), with most having stage IV disease. Mutations, gene expression, and transcriptional signatures were evaluated from next-generation sequencing data. Genetic ancestry was estimated from DNA-seq. Differences in mutational prevalence, gene expression, and transcriptional signatures between AA and EA were compared. EA patients were used as the reference population for log fold-changes (logFC) in expression. Results After applying inclusion criteria, 3433 samples were evaluated (n = 623 AA and n = 2810 EA). Observed patterns of dysregulated pathways demonstrated significant heterogeneity among the two groups. Notably, PIK3CA mutations were significantly lower in AA HR+/HER2- tumors (AA = 34% vs. EA = 42%, P < 0.05) and the overall cohort (AA = 28% vs. EA = 37%, P = 2.08e−05). Conversely, KMT2C mutation was significantly more frequent in AA than EA TNBC (23% vs. 12%, P < 0.05) and HR+/HER2- (24% vs. 15%, P = 3e−03) tumors. Across all subtypes and stages, over 8000 genes were differentially expressed between the two ancestral groups including RPL10 (logFC = 2.26, P = 1.70e−162), HSPA1A (logFC = − 2.73, P = 2.43e−49), ATRX (logFC = − 1.93, P = 5.89e−83), and NUTM2F (logFC = 2.28, P = 3.22e−196). Ten differentially expressed gene sets were identified among stage IV HR+/HER2- tumors, of which four were considered relevant to BC treatment and were significantly enriched in EA: ERBB2_UP.V1_UP (P = 3.95e−06), LTE2_UP.V1_UP (P = 2.90e−05), HALLMARK_FATTY_ACID_METABOLISM (P = 0.0073), and HALLMARK_ANDROGEN_RESPONSE (P = 0.0074). Conclusions We observed significant differences in mutational spectra, gene expression, and relevant transcriptional signatures between patients with genetically determined African and European ancestries, particularly within the HR+/HER2- BC and TNBC subtypes. These findings could guide future development of treatment strategies by providing opportunities for biomarker-informed research and, ultimately, clinical decisions for precision oncology care in diverse populations.

The incidence and mortality of early-onset colorectal cancer (EOCRC) are rising; outcomes appear to differ by race and ethnicity. We aimed to assess differences in mutational landscape and gene expression of EOCRC by racial and ethnic groups (Non-Hispanic Asian, Non-Hispanic Black, Non-Hispanic White, White Hispanic) using data from AACR Project GENIE (10.2) and University of Texas Southwestern, the latter enriched in Hispanic patients. All statistical tests were 2-sided. Of 1,752 EOCRC patients, Non-Hispanic Black patients had higher rates of KRAS mutations (60.9%, p = .001, q = 0.015) and Non-Hispanic White and Non-Hispanic Black patients had higher rates of APC mutations (77.1% and 76.6% among Non-Hispanic White and Non-Hispanic Black patients, respectively; p = .001, q = 0.015) via the Fisher exact test with Benjamini-Hochberg correction. Using R packages DESeq2 and clusterProfiler, we found that White Hispanic patients had increased expression of genes involved in oxidative phosphorylation (p &lt; .001, q = 0.025). Genomic profiling has the potential to identify novel diagnostics and influence individualized treatment options to address the currently limited prognosis of EOCRC.

Purpose: Prior research in the molecular correlates of disparities in incidence and outcomes of colorectal cancer (CRC) by race and ethnicity have typically used self-reported or observed categories, which can be missing or inaccurate. Furthermore, race and ethnicity do not always capture genetic similarity well, particularly in admixed populations. To overcome these limitations, we examined associations of CRC tumor molecular profiles with genetic ancestry. Experimental Design: Sequencing was performed with the Tempus xT NGS 648-gene panel and whole exome capture RNA-Seq for 8,454 CRC patients. Genetic ancestry proportions were estimated for five continental groups, Africa (AFR), Americas (AMR), East Asia (EAS), Europe (EUR), and South Asia (SAS), using ancestry informative markers. We assessed association of genetic ancestry proportions and genetic ancestry-imputed race and ethnicity categories with somatic mutations in relevant CRC genes and in expression profiles, including consensus molecular subtypes (CMS). Results: Increased AFR ancestry was associated with higher odds of somatic mutations in APC, KRAS and PIK3CA and lower odds of BRAF mutations. Additionally, increased EAS ancestry was associated with lower odds of mutations in KRAS, EUR with higher odds in BRAF, and the Hispanic/Latino category with lower odds in BRAF. Greater AFR ancestry and the non-Hispanic Black category were associated with higher than expected CMS3, while patients in the Hispanic/Latino category had higher indeterminate CMS. Conclusions: Use of genetic ancestry enables identification of molecular differences in CRC tumor mutation frequencies and gene expression that may underlie observed differences by race and ethnicity, and suggests that subtype classifications such as CMS may benefit from more diversity in representation.

10573 Background: The incidence and mortality of cancer vary widely across race and ethnicity. This is attributed to an interplay of socioeconomic factors, environmental exposures, and genetic background. Cancer genomic studies have underrepresented minorities and individuals of non-European descent, thus limiting a comprehensive understanding of disparities in the diagnosis, prognosis, and treatment of cancer among these populations. Furthermore, the social constructs of race and ethnicity are far from precise categories to understand the biological underpinnings of such differences. In this study, we use a large real-world data (RWD) patient cohort to examine associations of genetic ancestry with somatic alterations in known cancer driver genes. Methods: We inferred genetic ancestry from approximately 50,000 de-identified records from cancer patients of diverse histology who underwent tumor genomic profiling with the Tempus xT next-generation sequencing (NGS) assay. Our cohort includes patients with brain, breast, colorectal, hematopoietic, lung, and ovarian cancers, among others. We used 654 ancestry informative markers selected to overlap the target regions of the 648-gene Tempus xT NGS assay to infer global ancestry proportions at the continental level: Africa (AFR), America (AMR), Europe (EUR), East Asia (EAS), and South Asia (SAS). We imputed race/ethnicity categories using ancestry proportions on subjects lacking such metadata. Results: Most patients were of European descent (72%), however, continental genetic ancestry inference identified 4.7 and 3.8-fold more patients with substantial (> 50%) AFR and AMR ancestry, correspondingly, compared with TCGA. We observed higher percentages of AFR ancestry patients with prostate, breast, and colorectal cancer (1.8-3.1%) and AMR ancestry patients with colorectal cancer (2.4%) compared to the overall cohort-level distributions (p < 0.05). Using imputation, we identified 60% and 121% more patients as likely Black and Hispanic/Latino, respectively. We observed several associations between genetic ancestry with tumor mutation burden (TMB), e.g., a reduction in median TMB in Asian breast cancer patients (Asian TMB mean = 2.3 m/Mb vs 4.4 for Black, 3.3 for Hispanic, and 4.2 for White; p < 0.0001), in paired tumor/normal sequencing data. Furthermore, we found associations between ancestry and nonsynonymous somatic mutations in cancer genes, e.g. in CTNNB1 with EAS ancestry (OR = 1.18) and EGFR with EAS (OR = 1.24), AMR (OR = 1.30), and EUR (OR = 0.89) ancestries (all p < 0.001) in lung cancer patients. Conclusions: Our results support the use of genetic ancestry inference on RWD to improve upon the social constructs of race and ethnicity, allowing us to better understand the impact of shared germline genetic or exposure backgrounds into cancer mutational processes that influence incidence, progression, and outcomes.

3138 Background: TMB is routinely reported in cancer patients tested with broad-panel next generation sequencing and has become a predictive biomarker associated with response to checkpoint inhibitor (CPI) therapy. Sequencing of paired tumor and normal specimens allows correction of TMB estimates with patient-specific germline variants. When a paired normal specimen is unavailable, TMB estimates are corrected using germline variant annotations derived from population-scale germline variant surveys. Germline variants do not generate neoantigens, which is the putative target of the immune response in CPI treated patients. To evaluate TMB differences in paired sequencing (PS) and tumor-only sequencing (TOS), we compared TMB assessments—stratified by race—in two common malignancies. Methods: Using de identified records from the Tempus clinico-genomic database, cohorts of patients with non-small cell lung cancer (NSCLC) and breast cancer sequenced using the Tempus xT NGS platform (DNA-seq of 595-648 genes at 500x coverage, whole exome capture RNA-seq) and noted to not have microsatellite instability, were identified for analyses. The Kruskall-Wallis test was used to compare TMB distributions. Results: Among 4,817 NSCLC patients with race information (13% Black (B), 5% Asian (A), 82% White (W), 3,052 had PS, and 1,765 had TOS performed. Median TMB for B, A, and W patients was 5.8, 2.6, and 4.7 (within group p < 0.0001), respectively in patients with PS, and 9.5, 6, and 7.4 (within group p < 0.0001), in patients with TOS. Comparisons across PS and TOS were highly significant (p < 0.0001). The absolute difference in median TMB was 3.7, 3.4, and 2.5, respectively. Among 3,191 patients with breast cancer (17% B, 4% A, 78% W), 2,220 had PS, and 971 had TOS. Median TMB for B, A, and W patients was 2.6, 2.1, and 2.6 (within group p = 0.11), respectively, in patients with PS, and 6.3, 5.8, and 4.7 (within group p < 0.0001) in patients with TOS. Comparisons across PS and TOS were highly significant (p < 0.0001). The absolute difference in median TMB was 3.7, 3.7, and 2.1, respectively. Conclusions: PS reduces estimated TMB compared to TOS across all racial groups with a pronounced difference in Black and Asian racial groups. This is expected as population databases of germline variation are based on cohorts predominantly from individuals of European ancestry, leading to artifactually high TMB in minorities tested with TOS. As a result, artifactually elevated TMB estimates from TOS may promote treatment with CPI in patients with a low probability of response which could exacerbate known race-based outcome disparities. PS provides a more accurate estimate of TMB regardless of race and could reduce the use of CPI in patients with a low likelihood of response.