Genetic Ancestry Analysis Research Articles

Molecular profile of driver genes in lung adenocarcinomas of Brazilian patients who have never smoked: implications for targeted therapies.

Lung cancer in never-smoker (LCINS) patients accounts for 20% of lung cancer cases, and its biology remains poorly understood, particularly in genetically admixed populations. We elucidated the molecular profile of driver genes in Brazilian LCINS. The mutational and gene fusion status of 119 lung adenocarcinomas from self-reported never-smoker patients, was assessed using targeted sequencing (NGS), nCounter, and immunohistochemistry. A panel of 46 ancestry-informative markers determined patients' genetic ancestry. The most frequently mutated gene was EGFR (49.6%), followed by TP53 (39.5%), ALK (12.6%), ERBB2 (7.6%), KRAS (5.9%), PIK3CA (1.7%), and less than 1% alterations in RET, NTRK1, MET∆ex14, PDGFRA, and BRAF. Except for TP53 and PIK3CA, all other alterations were mutually exclusive. Genetic ancestry analysis revealed a predominance of European (71.1%), and a higher African ancestry was associated with TP53 mutations. Brazilian LCINS exhibited a similar molecular profile to other populations, except the increased ALK and TP53 alterations. Importantly, 73% of these patients have actionable alterations that are suitable for targeted treatments.

329 (PB317): Bioinformatic Analysis of Genetic Ancestry and Germline Variant Correlation in Colombian Women with Triple-Negative Breast Cancer and High-Grade Serous Ovarian Cancer Using Hereditary Cancer Panel

329 (PB317): Bioinformatic Analysis of Genetic Ancestry and Germline Variant Correlation in Colombian Women with Triple-Negative Breast Cancer and High-Grade Serous Ovarian Cancer Using Hereditary Cancer Panel

Abstract C102: Polyethnic-1000: Advancing cancer genomics by studying ethnically diverse, underserved patient populations in New York

Abstract Prompted by the considerable biases toward European ancestry cases in large cancer genomics repositories, the New York Genome Center initiated an effort to diversify the public datasets that are forming the foundations of current cancer research, in order to optimize the unbiased applications of modern genomically-driven discoveries to a larger population. Our effort was focused on 8 cancer types (breast, prostate, bladder, lung, pancreatic, colon and endometrial cancer, as well as multiple myeloma) and generated Illumina tumor-normal whole-genome sequencing and tumor transcriptome sequencing. The majority of the samples were retrospectively obtained in clinics and hospitals of the New York region and the analyses are conducted with collaborators in these institutions. Our dataset is currently composed of 851 tumor-normal WGS and 471 RNASeq, and is progressively being distributed to the scientific community in partnership with ICGC-ARGO. Overall, 75% of the cohort is predominantly of non-European ancestry, as estimated by genetic ancestry analysis using the 1000Genomes continental references.We analyzed the samples with NYGC’s somatic variant calling pipeline and will present results from the 8 cancer types related to germline and somatic variants (single-nucleotide variants, indels, copy-number alterations, complex structural variants) as well as mutational signatures, neoantigen prediction, fusion genes and expression profiles, in relation to genetic ancestry estimation and clinical features of the patients. We anticipate that the dataset will significantly diversify the genetic ancestry of tumor profiles in public databases, and serve to form hypotheses regarding the contribution of ancestry on cancer disparities. The experience of the Polyethnic-1000 project informs our contribution to the Cancer Grand Challenge SAMBAI, which focuses on breast, prostate and pancreatic cancers in the African Diaspora. SAMBAI will further investigate the causes of cancer disparity by combining genomic data with social determinants of health and exposomics information, deeper immune profiling and new genomics technologies such as long reads sequencing and the use of a pangenome reference. Citation Format: Nicolas Robine, Lara Winterkorn, Tim Chu, Zoe Goldstein, Will Hooper, Ali Oku, Heather M. Geiger, Melissa B. Davis, Onyinye Balogun. Polyethnic-1000: Advancing cancer genomics by studying ethnically diverse, underserved patient populations in New York [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C102.

Sleep patterns according to genetically determined ethnicity in the population of São Paulo, Brazil

Sleep is a behavior expressed differently for each individual. However, studies have shown that some ethnic groups express common sleep patterns, which can be observed in different ethnic groups. Previous studies have shown the existence of sleep disparities in populations of different ethnicities. Most of these studies have considered self-reported ethnicity and assessed sleep subjectively. Therefore, the aim of this study was to evaluate sleep disparities in different ethnic groups based on an analysis of genetic ancestry and the use of objective sleep evaluation. To do this, we used data from the São Paulo Epidemiologic Sleep Study (EPISONO), which was undertaken in Brazil, a country that is known for its ethnic/racial diversity. All individuals completed a series of questionnaires, underwent full polysomnography and had their blood collected for DNA extraction. After genotyping and identifying samples with high-quality DNA suitable for genetic analysis, 31 ancestry-informative markers (AIMs) were selected. These markers exhibited substantial allelic frequency differences, enabling the characterization of the three primary founding populations of modern Brazil - Europeans, West-Africans, and Native Americans. Through this analysis, the genetic contribution of each of these ancestral groups was identified in respect of each participant. Based on this, a latent class cluster analysis (LCCA) was performed to define the three clusters that best classified the sample according to ethnic group: African (n = 255), Caucasian (n = 668) and Native American (n = 83). Applying the adjusted model for the confounding variables (age, socio-economic class and sex), statistically significant differences in sleep variables between ethnicities were found. Africans had higher sleep latency compared to the other groups (β = 4.46, CI = 1.18 to 7.74 and β = 7.83, CI = 3.50 to 12.15), while Caucasians had longer total sleep time (β = −16.47, CI = −29.94 to −2.99) and better sleep efficiency (β = −2.19, CI = −4.35 to −0.02) compared to Africans. Regarding the respiratory arousals index (β = −1.11, IC = −2.07 to −0.16) and periodic leg movements index (β = −7.48, CI = −12.08 to −2.88), both were higher among Caucasians compared to Africans. We were able to conclude that genetic ancestry might modulate sleep structure and the occurrence of sleep disorders.

The Genomic Basis of Adaptation to High Elevations in Africanized Honey Bees.

A range of different genetic architectures underpin local adaptation in nature. Honey bees (Apis mellifera) in the Eastern African Mountains harbor high frequencies of two chromosomal inversions that likely govern adaptation to this high-elevation habitat. In the Americas, honey bees are hybrids of European and African ancestries and adaptation to latitudinal variation in climate correlates with the proportion of these ancestries across the genome. It is unknown which, if either, of these forms of genetic variation governs adaptation in honey bees living at high elevations in the Americas. Here, we performed whole-genome sequencing of 29 honey bees from both high- and low-elevation populations in Colombia. Analysis of genetic ancestry indicated that both populations were predominantly of African ancestry, but the East African inversions were not detected. However, individuals in the higher elevation population had significantly higher proportions of European ancestry, likely reflecting local adaptation. Several genomic regions exhibited particularly high differentiation between highland and lowland bees, containing candidate loci for local adaptation. Genes that were highly differentiated between highland and lowland populations were enriched for functions related to reproduction and sperm competition. Furthermore, variation in levels of European ancestry across the genome was correlated between populations of honey bees in the highland population and populations at higher latitudes in South America. The results are consistent with the hypothesis that adaptation to both latitude and elevation in these hybrid honey bees are mediated by variation in ancestry at many loci across the genome.

Abstract 3117: Molecular and clinical correlates of genetic ancestry in a diverse, admixed cancer dataset

Abstract The objective of this study is to determine whether genetic ancestry analysis can provide additional insight into the genetic determinants of cancer disparities distinct from socially constructed variables like self-reported race and ethnicity. The Oncology Research Information Exchange Network (ORIEN) “Avatar” project is a diverse dataset of extensive, longitudinal clinical and molecular data from 18 cancer centers across the U.S.; the ORIEN Intermember Ancestry Project cohort described in this study is a subset of the larger dataset. Using paired tumor/germline whole exome sequencing data from ORIEN, the Genome Aggregation Database (gnomAD) dataset of ancestry reference individuals, and the software tools ADMIXTURE and RFMix, we have estimated genetic ancestry for cancer cases from both ORIEN and The Cancer Genome Atlas (TCGA). The ORIEN dataset has 2.6X greater representation of self-reported Hispanic/Latinos than does TCGA, with Hispanic/Latinos making up 9% of the ORIEN dataset vs. 4% in TCGA. As expected, individuals of Hispanic/Latino ethnicity are heterogeneous in their admixture proportions of Indigenous American, African, and European ancestries. We performed statistical analyses in R to identify molecular and clinical correlations with ancestry. This study highlights the clinical utility of genetic ancestry analysis as an approach to understand the genetic contributions to cancer disparities in diverse, admixed populations. Citation Format: Mackenzie D. Postel, Jamie K. Teer, Steven A. Eschrich, Julie Dutil, Erin M. Siegel, William D. Cress, John D. Carpten, David W. Craig. Molecular and clinical correlates of genetic ancestry in a diverse, admixed cancer dataset [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3117.

Facial and Intraoral Photographic Traits Related to Sleep Apnea in a Clinical Sample with Genetic Ancestry Analysis.

Rationale: Craniofacial and pharyngeal morphology influences risk for obstructive sleep apnea (OSA). Quantitative photography provides phenotypic information about these anatomical factors and is feasible in large samples. However, whether associations between morphology and OSA severity differ among populations is unknown. Objectives: The aim of this study was to examine this question in a large sample encompassing people from different ancestral backgrounds. Methods: Participants in SAGIC (Sleep Apnea Global Interdisciplinary Consortium) with genotyping data were included (N = 2,393). Associations between photography-based measures and OSA severity were assessed using linear regression, controlling for age, sex, body mass index, and genetic ancestry. Subgroups (on the basis of 1000 Genomes reference populations) were identified: European (EUR), East Asian, American, South Asian, and African (AFR). Interaction tests were used to assess if genetically determined ancestry group modified these relationships. Results: Cluster analysis of genetic ancestry proportions identified four ancestrally defined groups: East Asia (48.3%), EUR (33.6%), admixed (11.7%; 46% EUR, 27% Americas, and 22% AFR), and AFR (6.4%). Multiple anatomical traits were associated with more severe OSA independent of ancestry, including larger cervicomental angle (standardized β [95% confidence interval (CI)] = 0.11 [0.06-0.16]; P < 0.001), mandibular width (standardized β [95% CI] = 0.15 [0.10-0.20]; P < 0.001), and tongue thickness (standardized β [95% CI] = 0.06 [0.02-0.10]; P = 0.001) and smaller airway width (standardized β [95% CI] = -0.08 [-0.15 to -0.002]; P = 0.043). Other traits, including maxillary and mandibular depth angles and lower face height, demonstrated different associations with OSA severity on the basis of ancestrally defined subgroups. Conclusions: We confirm that multiple facial and intraoral photographic measurements are associated with OSA severity independent of ancestral background, whereas others differ in their associations among the ancestrally defined subgroups.

Analysis of Genetic Ancestry from NGS Data Using EthSEQ

Next-generation sequencing (NGS) is widely utilized both in translational cancer genomics studies and in the setting of precision medicine. Identification and stratification of an individual's ancestry is fundamental for the correct interpretation of genetic and genomic profiling. EthSEQ provides an easy and effective computational workflow to determine the ancestry of individuals, exploiting single nucleotide polymorphism genotypes computed from NGS data of whole-exome and targeted sequencing experiments. Genotypes are determined by EthSEQ from sequencing alignment files (BAM files) or can be provided as input in Variant Call Format (VCF) or CoreArray Genomic Data Structure (GDS) format. Ancestry is determined and assigned to individuals by EthSEQ exploiting a reference model and a standard or multi-step refinement approach based on Principal Component Analysis (PCA). A complete and detailed set of textual and graphical output files are generated by EthSEQ as result. EthSEQ is easy to use and can be integrated into any NGS-based processing pipeline also exploiting multi-core capabilities. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Perform ancestry analysis using a pre-computed reference model Alternate Protocol: Perform ancestry analysis using a user-specified GDS file as reference model Basic Protocol 2: Perform ancestry analysis using multi-step refinement Support Protocol 1: Create a reference model from multiple VCF genotype data files Support Protocol 2: Create VCF genotype data files from a BAM file.

P593: Genetic ancestry analysis using 46 AIM-InDel in three population groups of Colombia: Amerindian, African-descent and European-admix populations

P593: Genetic ancestry analysis using 46 AIM-InDel in three population groups of Colombia: Amerindian, African-descent and European-admix populations

Abstract A006: Increased germline mutational burden in individuals of African ancestry: Implications for interpretation of tumor mutation burden

Abstract Introduction: Tumor mutation burden (TMB), defined as the number of somatic gene mutations per megabase in a tumor genome, is used clinically to identify cancer patients that may respond to immune checkpoint inhibitors. Recent studies suggest that patient ancestry can influence TMB, where individuals of African ancestry were found to have elevated TMB values based on tumor-only sequencing analysis. However, the impact of patient ancestry on germline mutational burden and implications for interpretation of tumor-only mutational burden data is largely unexplored. Methods: We examined the influence of patient ancestry on germline and tumor mutation burden using tumor-normal whole exome sequencing (WES) data from a pan-cancer cohort of 1228 individuals from a single institution. Genetic ancestry was estimated from constitutional WES data using single nucleotide polymorphism weights from external reference panels. Variant calling was performed using constitutional, tumor-only, and paired tumor-normal workflows. Total and loss-of-function burden scores were calculated for each participant from each workflow based on the total number of mutations detected in each sample and the total number of predicted loss-of-function mutations, based on snpEff annotations, respectively. Results: Genetic ancestry analysis found that one-third of this pan-cancer cohort was of non-European ancestry. 9.4% of individuals were of Eastern Asian ancestry, 5.3% of African ancestry, 1.0% of South Asian ancestry, 0.2% of Native American ancestry, and 17.1% of admixed ancestry, predominantly European and Native American admixed ancestry (15.6%). Total and loss-of-function germline burden scores varied across ancestral groups, with individuals of African ancestry showing significantly increased germline burden scores compared to other ancestral groups (p&amp;lt;0.0001). Tumor-only analysis also showed increased mutation burden for individuals of African ancestry. However, when private and rare germline variation was taken into account using paired tumor-normal analysis, tumor mutation burden did not differ based on patient ancestry, suggesting the differences seen in tumor-only analysis are due to germline variation rather than differences in true somatic mutation burden. Conclusion: Our study reveals that the paucity of knowledge of ancestry-specific reference genomes leads to unacceptable health disparities in cancer, specifically in patients with African ancestry. We show that germline mutational burden varies by ancestral background, with individuals of African ancestry displaying increased genetic variation compared to other ancestral populations. These results suggest that patient ancestry should be considered when interpreting tumor mutational burden values, particularly from tumor-only analysis. Approaches utilizing paired tumor-normal analysis or ancestry-specific reference genomes can aid in more accurate assessment of TMB, thereby avoiding futile treatments targeted at presumed high mutational burden tumors specifically in African American populations. Citation Format: Janith Don, Sara A. Byron, Guangfa Zhang, Tyler Izatt, Jiaming Zhang, Bethany Davis, Bryce Turner, Jonathan J. Keats, Jeffrey M. Trent, Lorna Rodriguez-Rodriguez, Nicholas J. Schork. Increased germline mutational burden in individuals of African ancestry: Implications for interpretation of tumor mutation burden [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A006.

Genetic Variations of the DPYD Gene and Its Relationship with Ancestry Proportions in Different Ecuadorian Trihybrid Populations.

Dihydropyrimidine dehydrogenase is one of the main pharmacological metabolizers of fluoropyrimidines, a group of drugs widely used in clinical oncology. Around 20 to 30% of patients treated with fluoropyrimidines experience severe toxicity caused by a partial or total decrease in enzymatic activity. This decrease is due to molecular variants in the DPYD gene. Their prevalence and allelic frequencies vary considerably worldwide, so their description in heterogeneous groups such as the Ecuadorian population will allow for the description of pharmacogenetic variants and proper characterization of this population. Thus, we genotyped all the molecular variants with a predictive value for DPYD in a total of 410 Ecuadorian individuals belonging to Mestizo, Afro-Ecuadorian, and Indigenous ethnic groups. Moreover, we developed a genetic ancestry analysis using 46 autosomal ancestry informative markers. We determined 20 genetic variations in 5 amplified regions, including 3 novel single nucleotide variants. The allele frequencies for DPYD variants c.1627G>A (*5, rs1801159), c.1129-15T>C (rs56293913), c.1218G>A (rs61622928), rs1337752, rs141050810, rs2786783, rs2811178, and g.97450142G>A (chr1, GRCh38.p13) are significantly related to Native American and African ancestry proportions. In addition, the FST calculated from these variants demonstrates the closeness between Indigenous and Mestizo populations, and evidences genetic divergence between Afro-Ecuadorian groups when compared with Mestizo and Indigenous ethnic groups. In conclusion, the genetic variability in the DPYD gene is related to the genetic component of ancestral populations in different Ecuadorian ethnic groups. The absence and low frequency of variants with predictive value for fluoropyrimidine toxicity such as DPYD *2A, HapB3, and c.2846A>T (prevalent in populations with European ancestry) is consistent with the genetic background found.

Ancestry-based differences in gene alterations in non–small cell lung cancer: Real-world data using genetic ancestry analysis.

9125 Background: Racial differences in morbidity and mortality of non-small cell lung cancer (NSCLC) have been demonstrated and some genomic alterations (e.g. EGFR) in NSCLC are known to differ according to race. However, studies have been limited in sample size and hence, limited in their capacity to detect discrepancies in less frequently altered genes. Here, we investigated alteration prevalence in a large real-world NSCLC cohort, stratified by genetic ancestry. Methods: 75,362 NSCLC patients from the United States, were profiled with comprehensive genomic profiling (CGP) of tissue biopsy, as part of routine clinical care (Foundation Medicine Inc., FMI; Frampton GM, et al. Nat Biotechnol 2013). 296 genes targeted across all assays were examined for known/likely pathogenic alterations of all classes. Predominant genetic ancestry was inferred using a SNP-based approach (Newberg J, et al. AACR 2019), and patients were categorized into European (EUR), African (AFR), East Asian (EAS), Admixed American (AMR), and South Asian (SAS) ancestry groups. Patients were additionally stratified by histological type, age (≥40/ &lt; 40), and sex. The prevalence of high tumor mutational burden (TMB-High), defined as ≥ 10 mutations/mb (Chalmers ZR, et al. Genome Med 2017), and microsatellite instability status (Trabucco, et al. J Mol Diagn 2019) was also calculated. Results: In this NSCLC cohort, ancestry was split 82.2% for EUR, 10.0% for AFR, 4.4% for EAS, 2.7% for AMR, and 0.8% for SAS. 50.4% were female (n = 37,972) and 49.6% male (n = 37,360). The most prevalent alterations in the overall cohort included TP53 (67.5%), KRAS (30.6%), CDKN2A (29.2%), CDKN2B (17.2%), STK11 (16.1%), and EGFR (15.3%). The prevalence of TMB-High status in the overall cohort was 34.6%. Stratified by ancestry, the prevalence of EGFR alterations was significantly enriched in EAS vs. other ancestry groups ( p &lt; 0.001). KRAS and STK11 were enriched in EUR and AFR vs. other groups ( p &lt; 0.001). TMB-High status was significantly enriched in AFR vs. all other groups ( p &lt; 0.001). In EAS and SAS, TMB-High was typically reduced vs. other ancestry groups (TMB-High AFR 41.6%, AMR 20.1%, EAS 14.1%, EUR 35.5%, SAS 11.7%). A similar analysis based on sex revealed differences in prevalence of 80 gene alterations and TMB-High with sex-specific enrichments (e.g., EGFR 19.0% female vs. 11.5% male; KRAS 34.6% vs. 26.6%). With respect to age, the prevalence of 41 gene alterations and TMB-High were significantly different between samples from patients age &lt; 40 and age ≥ 40 (e.g., ALK 21.1% age &lt; 40 vs. 2.7% age ≥ 40; KRAS 13.0% vs. 30.8%; TMB-High 14.4% vs. 34.8%). Conclusions: Comprehensive analysis of this real-world dataset, which includes the largest NSCLC patient cohort, revealed ancestry-associated differences in genomic alterations in NSCLC. Age and sex were also associated with differences in genomic alteration and TMB-High prevalence.

Role of genetic ancestry in endometrial cancers: Understanding disparities in black women.

e17631 Background: Endometrial cancer is the most common gynecological malignancy in the United States. Endometrial cancer disproportionately affects black women in terms of incidence and survival despite advancement in treatment, and preventive strategies. Identifying distinct tumor markers in patients with African ancestry will help distinguish biological determinants underlying the disparities in endometrial cancer. In this study, we investigated the genetic alterations in endometrial cancer in individuals of African (AFR) ancestry using The Cancer Genome Atlas (TCGA). Methods: The genomic and clinical data of TCGA PanCancer Atlas uterine corpus endometrial carcinoma (UCEC) were explored using CBioportal (http://www.cbioportal.org/). We utilized The Cancer Genome Ancestry Atlas (TCGAA) and LAMP for estimates of genetic ancestry and quantitative ancestral composition. This dataset contains 529 patients, including 357 self-reported whites and 107 blacks. For each case the proportion of European, West African, East Asian, Native American ancestry was estimated. The dominant ancestry was defined as ≥50% of admixture from one reference population. Differences in gene mutation frequency were analyzed based on AFR ancestry proportion. The Kaplan-Meier curves were generated, and Cox regression analyses were performed. Results: Global genetic ancestry analysis identified 115 AFR ancestry cases with mean ancestry of 80.4%. The dominant AFR ancestry subject matched the self-reported race with 94% accuracy. We identified 23 subjects with ≥90% AFR ancestry, 43 subjects with 80-90% AFR ancestry, 34 subjects with 70-80% AFR ancestry, and 15 subjects with 50-70% AFR ancestry. TP53 was the most frequently mutated gene in patients with AFR ancestry(49.5%). ≥90% AFR ancestry had the highest rate of TP53 mutations (52.2%) compared with 80-90% AFR ancestry (51.2%), 70-80% AFR ancestry (43.8%), and 50-70% AFR ancestry (41.7%). PTEN was less commonly mutated in patients with higher proportion of AFR ancestry (47.8% in ≥90% AFR ancestry, 39.0% in 80-90% AFR ancestry, 59.4% in 70-80% AFR ancestry, and 66.7% in 50-70% AFR ancestry). PIK3CA mutation frequency was almost identical in all AFR ancestry groups studied. No significant differences in overall survival was observed between AFR ancestry groups. Conclusions: We aimed to investigate the etiology of endometrial cancer disparities by analyzing the effect of ancestry on genetic alterations in endometrial cancer. This study demonstrated differences in the mutation frequency among patients with AFR ancestry. We have shown that TP53 mutations were seen more frequently in patients with higher AFR ancestry, which may confer a poorer prognosis. Nonetheless, to validate the findings of this study, future studies should be conducted with larger sample sizes and more diverse ancestral groups to explore how genetic ancestry impacts tumorigenesis and cancer progression.

Integrated Clinico-Genomic Analysis of Genetic Ancestry in 1,614 Patients With Cancer Treated With Immune Checkpoint Inhibitors

Integrated Clinico-Genomic Analysis of Genetic Ancestry in 1,614 Patients With Cancer Treated With Immune Checkpoint Inhibitors

P70.02 Clinicopathological and Genetic Ancestry Impact of TP53 Mutations in Brazilian Lung Adenocarcinoma Patients

TP53 is the most mutated gene in lung adenocarcinoma tumors. TP53 gene plays a crucial role in maintaining genome stability, and the presence of alterations in this gene may lead to uncontrolled cell proliferation and cancer. However, the frequency of TP53 mutation and its clinical impact in admixture lung adenocarcinoma populations, such as the Brazilian population, is unclear. Aim: To describe the frequency of TP53 mutations and their association with clinicopathological and genetic ancestry background data in lung adenocarcinoma patients in Brazil. We evaluated a retrospective FFPE series of lung adenocarcinoma (n=363) diagnosed at Barretos Cancer Hospital, Barretos, Brazil, between 2018 and 2020. TP53 mutational status was assessed by NGS (TruSight Tumor 15, Illumina). The genetic ancestry analysis was assessed on tumor DNA by a specific panel of 46 ancestry informative markers, and the ancestry proportions for Asian, African, European, and Native American was calculated. In accordance with the AJCC 7thedition, the following disease stage was present at diagnosis: I/II (n=51); III (n=43), and IV (n=245). We observed the presence of TP53 mutations in 59% (n=215) of cases. About 71.0% of mutations were missense variants and the majority were located in the DNA-binding domain of the TP53 gene (Figure1). Furthermore, the codon Arg273 was the most mutated (n=13), and the R337H variant (founder-effect in Brazil) was identified in 10 cases (4.65%). TP53 mutations were associated with younger age at diagnosis(p=0.006) quitter and current smokers(p=0.006 and p=0.001), and intermedium and high African genetic ancestry(p=0.012 and p<0.0001). TP53 mutated patients presented a significantly worse overall survival (14 months) compared to wild-type patients (22months) (p=0.024). The adjusted cox regression model showed TP53 mutational status(TP53m HR=1.15, p=0.386) was not independently associated with worse outcomes. Apart from, EGFR mutational status(EGFRm HR=0.44, p<0.0001), advanced disease at diagnosis(HR=15.78, p<0.0001), and PS ECOG at diagnosis(PS1 HR=2.25, p=0.032; PS2 HR=3.71, p=0.01; PS3/4 HR=5.91, p<0.0001) were independently associated with worse outcomes regardless of disease course. TP53 mutations are present in 59.0% in Brazilian lung adenocarcinoma patients. TP53 mutations are associated with younger patients, quitter and current smokers, patients with African genetic ancestry background.

Polymorphisms in the CYP2A6 and ABCC4 genes are associated with a protective effect on chronic myeloid leukemia in the Brazilian Amazon population.

BackgroundSusceptibility to Chronic Myeloid Leukemia (CML) may be modulated by genetic variables. However, the majority of previous investigations have focused on genetically homogeneous populations, resulting in a lack of evidence on how genetic factors may influence the development of CML in miscegenated populations. We analyzed 30 polymorphisms in genes related to DNA repair, folate metabolism, transmembrane transport, xenobiotic metabolism, and pyrimidine synthesis in relation to their potential role in the susceptibility of the individual to CML.MethodsThis case‐control study included 126 healthy individuals and 143 patients diagnosed with CML from the admixed population of the Brazilian Amazon. The samples were genotyped by real‐time PCR and the genetic ancestry analysis was based on a panel of 61 ancestry informative markers.ResultsThe results indicated a protective effect against the development of CML in carriers of the C allele of the rs28399433 (CYP2A6) gene and the CC genotype of the rs3742106 (ABCC4) gene.ConclusionOur findings suggest that the rs3742106 (ABCC4) and rs28399433 (CYP2A6) polymorphisms may modulate susceptibility to CML in a population of the Brazilian Amazon region.

Genetic ancestry analysis on >93,000 individuals undergoing expanded carrier screening reveals limitations of ethnicity-based medical guidelines

PurposeCarrier status associates strongly with genetic ancestry, yet current carrier screening guidelines recommend testing for a limited set of conditions based on a patient’s self-reported ethnicity. Ethnicity, which can reflect both genetic ancestry and cultural factors (e.g., religion), may be imperfectly known or communicated by patients. We sought to quantitatively assess the efficacy and equity with which ethnicity-based carrier screening captures recessive disease risk. MethodsFor 93,419 individuals undergoing a 96-gene expanded carrier screen (ECS), correspondence was assessed among carrier status, self-reported ethnicity, and a dual-component genetic ancestry (e.g., 75% African/25% European) calculated from sequencing data. ResultsSelf-reported ethnicity was an imperfect indicator of genetic ancestry, with 9% of individuals having >50% genetic ancestry from a lineage inconsistent with self-reported ethnicity. Limitations of self-reported ethnicity led to missed carriers in at-risk populations: for 10 ECS conditions, patients with intermediate genetic ancestry backgrounds—who did not self-report the associated ethnicity—had significantly elevated carrier risk. Finally, for 7 of the 16 conditions included in current screening guidelines, most carriers were not from the population the guideline aimed to serve. ConclusionSubstantial and disproportionate risk for recessive disease is not detected when carrier screening is based on ethnicity, leading to inequitable reproductive care.

Abstract B073: Estimating genetic ancestry of commonly used cancer cell lines

Abstract Given the scarcity of human cell lines from under-represented populations available for study, it is crucial that these cell lines be accurately characterized regarding their genetic ancestry so findings can be properly contextualized. Mischaracterization of a cell line's race/ethnicity can lead to wasted time and resources and potentially publication retractions. Here we calculated genetic ancestry proportions for 22 commercially available cell lines to test the accuracy of the “race/ethnicity” categorization assigned to these cells and to provide previously unknown genetic ancestry estimates to the scientific community. To determine cellular genetic ancestry proportions, DNA was extracted from the cell lines and genotyped for ancestry informative markers using the Agena MassARRAY platform with iPLEX chemistry. Genotypes for each cell line were analyzed with STRUCTURE software using settings of 30,000 for burn-in length, 70,000 replications, and K = 3 ancestral populations, representing West African (WA), Native American (NA), and European (EA) input genotype data. Commercially available cell lines designated as “Caucasian” in ethnicity were accurately described with mean European ancestry proportions of 97% (range 92-99%). Recently, using a much smaller panel of markers, the 22Rv1 cell line was found to have 41% WA ancestry. Our genetic ancestry analysis found the 22Rv1 cell line to have mostly EA ancestry, 91% EA, while also containing a non-negligible proportion of WA ancestry (8%). Three of the commercially available cell lines ascribed “Black” race appear to be accurate (HeLa, MDA-MB-PCa2, MDA-MB-468), although two of the three, HeLa and MDA-MBPCa2, fall far below the mean of ~80% WA ancestry for US-born African Americans with 60% and 66% WA ancestry, respectively. Interestingly, the MDA-MB-468 “Black” cell line had an appreciable amount of NA ancestry, 23% NA and 77% WA ancestry, which could suggest possible Afro-Caribbean ethnicity. Most notably, the E006 cell line, designated as “Black,” is as European as the previously mentioned cell lines ascribed Caucasian ethnicity with &amp;gt; 92% EA genetic ancestry. Cell lines with unassigned ethnicity varied widely in genetic ancestry with ranges of WA, NA, and EA ancestry proportions of 1%-92%, 0%-30%, and 2%-96%, respectively. Our results suggest predominantly European ancestry for the Caucasian-designated cell lines and high variance in genetic ancestry proportions for the Black-designated cell lines. However, the E006 cell line is an example of extreme misclassification, which has led to erroneous findings in the disparities literature and leave open the possibility of mischaracterization of other unanalyzed cell lines. Genetic ancestry estimates add more advanced and detailed ancestral characterization to these cell lines and allow for better contextualization of comparisons, applicability, and significant findings. We suggest robust genetic ancestry estimates as a requirement for all current and novel cell lines used in research. Citation Format: Stanley E. Hooker Jr., Madhavi Bathina, Stacy Lloyd, Priyatham Gorjala, Ranjana Mitra, Kevin S. Kimbro, Rick A. Kittles. Estimating genetic ancestry of commonly used cancer cell lines [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr B073.

Impact of Genetic Ancestry on Treatment Toxicity and Racial Disparities in Breast Cancer

Racial disparities in breast cancer are multifactorial and include inferior outcomes and increased rates of serious toxicity in African Americans. The purpose of this review is to evaluate the contribution of race, genetic ancestry, and genomic biomarkers to treatment toxicity and to demonstrate the impact of toxicity on racial disparities. Taxane-induced peripheral neuropathy (TIPN) and congestive heart failure (CHF) are potentially irreversible and life-altering toxicities of curative chemotherapy for breast cancer. Analysis of genetic ancestry, rather than self-reported race, in a large cooperative group adjuvant clinical trial discovered significantly higher rates of both TIPN and CHF in women of African descent compared with European Americans. Importantly, TIPN resulted in more dose reductions of chemotherapy in African Americans, which resulted in worse disease-free survival. Beyond race, significant individual variations in toxicity exist, which may be explained by validated genotypic predictors of TIPN and CHF, reviewed here. Race, in particular genetic ancestry, impacts both tumor and host biology, contributing to toxicity that drives disparities in quality of life and survival. Translating these data into clinical decision-making will benefit from engagement of the African American community to perform clinical trials and develop datasets focused specifically in this population to validate biomarkers and best understand patient preferences.

Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer

We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.