Toward Equitable Precision Oncology: Monitoring Racial and Ethnic Inclusion in Genomics and Clinical Trials.

PURPOSE: Ethnic diversity in cancer research is crucial as race/ethnicity influences cancer incidence, survival, drug response, molecular pathways, and epigenetic phenomena. In 2018, we began a project to examine racial/ethnic diversity in cancer research, with a commitment to review these disparities every 4 years. This report is our second assessment, detailing the present state of racial/ethnic diversity in cancer genomics and clinical trials. METHODS: To study racial/ethnic inclusion in cancer genomics, we extracted ethnic records from all data sets available at cBioPortal (n = 125,128 patients) and cancer-related genome-wide association studies (n = 28,011,282 patients) between 2018 and 2022. Concerning clinical trials, we selected studies related to breast cancer (n = 125,518 patients, 181 studies), lung cancer (n = 34,329 patients, 119 studies), and colorectal cancer (n = 40,808 patients, 105 studies). RESULTS: In cancer genomics (N = 28,136,410), 3% of individuals lack racial/ethnic registries; tumor samples were collected predominantly from White patients (89.14%), followed by Asian (7%), African American (0.55%), and Hispanic (0.21%) patients and other populations (0.1%). In clinical trials (N = 200,655), data on race/ethnicity are missing for 60.14% of the participants; for individuals whose race/ethnicity was recorded, most were characterized as White (28.33%), followed by Asian (7.64%), African (1.79), other ethnicities (1.37), and Hispanic (0.73). Racial/ethnic representation significantly deviates from global ethnic proportions (P ≤ .001) across all data sets, with White patients outnumbering other ethnic groups by a factor of approximately 4-6. CONCLUSION: Our second update on racial/ethnic representation in cancer research highlights the persistent overrepresentation of White populations in cancer genomics and a notable absence of racial/ethnic information across clinical trials. To ensure more equitable and effective precision oncology, future efforts should address the reasons behind the insufficient representation of ethnically diverse populations in cancer research.

Landscape and Saturation Analysis of Mutations Associated With Race in Cancer Genomes by Clinical Sequencing.

Differences in cancer genomes between racial groups may impact tumor biology and health disparities. However, the discovery of race-associated mutations is constrained by the limited representation and sample size of different racial groups in prior genomic studies. We evaluated the influence of race on the frequency of gene mutations using the Genomics, Evidence, Neoplasia, Information, Exchange database, a large genomic dataset aggregated from clinical sequencing. Matched cohort analyses were used to identify histology-specific race-associated mutations including increased TERT promoter mutations in Black and Asian patients with gliomas and bladder cancers, and a decreased frequency of mutations in DNA repair pathway genes and subunits of the SWI/SNF chromatin complex in Asian and Black patients across multiple cancer types. The distribution of actionable mutations in oncogenes was also race-specific, demonstrating how targeted therapies may have a disparate impact on racial groups. Down-sampling analyses indicate that larger sample sizes are likely to discover more race-associated mutations. These results provide a resource to understand differences in cancer genomes between racial groups which may inform the design of clinical studies and patient recruitment strategies in biomarker trials.

Reduction in Breast Cancer Death With Adjuvant Chemotherapy Among US Women According to Race, Ethnicity, and the 21-Gene Recurrence Score.

BACKGROUND: We previously showed the 21-gene breast recurrence score (RS) has lower prognostic accuracy for non-Hispanic Black (NHB) compared with non-Hispanic White (NHW) women with estrogen receptor (ER)-positive/HER2-negative breast cancer. The purpose of this study was to determine the clinical validity of the RS for predicting chemotherapy benefit as recommended in the current NCCN Guidelines for Breast Cancer among women from diverse racial/ethnic groups. METHODS: Using the SEER Oncotype database, we estimated propensity score-weighted hazard ratios (HRs) and 95% confidence intervals for breast cancer death with chemotherapy for women with ER-positive/HER2-negative, AJCC stages I-II, axillary node-negative, invasive breast cancer according to race/ethnicity. RESULTS: We included 6,033 (8.2%) Asian/Pacific Islander (API), 5,697 (7.8%) NHB, 6,688 (9.1%) Hispanic, and 54,945 (74.9%) NHW women. Breast cancer death was reduced with chemotherapy for NHB (HR, 0.48, 95% CI, 0.28-0.81), Hispanic (HR, 0.48; 95% CI, 0.25-0.94), and NHW (HR, 0.80; 95% CI, 0.65-0.99) women with an RS of 26 to 100. There was a nonsignificant reduction for API women (HR, 0.59; 95% CI, 0.28-1.24). For women with an RS of 11 to 25, there was no reduction in death for any racial/ethnic group. Among women aged ≤50 years, the reduction in breast cancer death with chemotherapy differed according to race (NHB: HR, 0.37 [95% CI, 0.20-0.67]; NHW: HR, 0.56 [95% CI, 0.44-0.74]; Pinteraction for chemotherapy * race <.0499). An exploratory subgroup analysis found that young NHB women may benefit from chemotherapy at a lower RS cutoff than other women. CONCLUSIONS: The RS was clinically validated as a predictive biomarker for NHB, Hispanic, and NHW women with ER-positive, axillary node-negative breast cancer, but it may underestimate the benefit of chemotherapy for young NHB women. If this finding is confirmed, the RS cutoff for recommending adjuvant chemotherapy for young NHB women with ER-positive, axillary node-negative breast cancer may need to be lower than for other women.

Genetic Testing for Cancer Risk and Perceived Importance of Genetic Information Among US Population by Race and Ethnicity: a Cross-sectional Study.

BACKGROUND: Genetic testing can help determine the risk of many cancers and guide cancer prevention and treatment plans. Despite increasing concern about disparities in precision cancer medicine, public knowledge and cancer genetic testing by race and ethnicity have not been well investigated. METHODS: We analyzed data from the 2020 Health Information National Trends Survey in 2022. Self-reported cancer genetic testing (e.g., Lynch syndrome, BRCA1/2) knowledge and utilization were compared by race and ethnicity. Perceived importance of genetic information for cancer care (prevention, detection, and treatment) was also examined in relation to the uptake of cancer genetic testing. Multivariable logistic regression models were employed to examine factors associated with knowledge and genetic testing to calculate predicted probability of undergoing genetic testing by race and ethnicity. RESULTS: Of 3551 study participants, 37.8% reported having heard of genetic testing for cancer risk and 3.9% stated that they underwent cancer genetic testing. Being non-Hispanic Black (OR=0.47, 95% CI=0.30-0.75) or Hispanic (OR=0.56, CI=0.35-0.90) was associated with lower odds of genetic testing knowledge. Although Hispanic or non-Hispanic Black respondents were more likely to perceive higher importance of genetic information versus non-Hispanic Whites, they had a lower predicted probability of cancer genetic testing. CONCLUSION: Non-Hispanic Black and Hispanic adults had lower knowledge and were less likely to undergo cancer genetic testing than non-Hispanic Whites. Further research is needed on sources of genetic testing information for racial and ethnic minorities and the barriers to accessing genetic testing to inform the development of effective cancer risk genetic testing promotion.

A Systems Biology Approach to Understand the Racial Disparities in Colorectal Cancer.

Racial disparities between Black/African Americans (AA) and White patients in colorectal cancer are an ever-growing area of concern. Black/AA show the highest incidence and have the highest mortality among major U.S. racial groups. There is no definite cause other than possible sociodemographic, socioeconomic, education, nutrition, delivery of healthcare, screening, and cultural factors. A primary limitation in this field is the lack of and small sample size of Black/AA studies. Thus, this study aimed to investigate whether differences in gene expression contribute to this ongoing unanswered racial disparity issue. In this study, we examined transcriptomic data of Black/AA and White patient cohorts using a bioinformatic and systems biology approach. We performed a Kaplan-Meier overall survival analysis between both patient cohorts across critical colorectal cancer signal transduction networks (STN), to determine the differences in significant genes across each cohort. Other bioinformatic analyses performed included PROGENy (pathway responsive genes for activity inference), RNA sequencing differential expression using DESeq2, multivariable-adjusted regression, and other associated Kaplan-Meier analyses. These analyses identified novel prognostic genes independent from each cohort, 176 differentially expressed genes, and specific patient cohort STN survival associations. Despite the overarching limitation, the results revealed several novel differences in gene expression between the colorectal cancer Black/AA and White patient cohorts, which allows one to dive deeper into and understand the behavior on a systems level of what could be driving this racial difference across colorectal cancer. Concretely, this information can guide precision medicine approaches tailored specifically for colorectal cancer racial disparities. SIGNIFICANCE: The purpose of this work is to investigate the racial disparities in colorectal cancer between Black/AA and White patient cohorts using a systems biology and bioinformatic approach. Our study investigates the underlying biology of each patient cohort. Concretely, the findings of this study include disparity-associated genes and pathways, which provide a tangible starting point to guide precision medicine approaches tailored specifically for colorectal cancer racial disparities.

EVALUATING THE RELATIONSHIPS BETWEEN GENETIC ANCESTRY AND THE CLINICAL PHENOME.

There is a desire in research to move away from the concept of race as a clinical factor because it is a societal construct used as an imprecise proxy for geographic ancestry. In this study, we leverage the biobank from Vanderbilt University Medical Center, BioVU, to investigate relationships between genetic ancestry proportion and the clinical phenome. For all samples in BioVU, we calculated six ancestry proportions based on 1000 Genomes references: eastern African (EAFR), western African (WAFR), northern European (NEUR), southern European (SEUR), eastern Asian (EAS), and southern Asian (SAS). From PheWAS, we found phecode categories significantly enriched neoplasms for EAFR, WAFR, and SEUR, and pregnancy complication in SEUR, NEUR, SAS, and EAS (p < 0.003). We then selected phenotypes hypertension (HTN) and atrial fibrillation (AFib) to further investigate the relationships between these phenotypes and EAFR, WAFR, SEUR, and NEUR using logistic regression modeling and non-linear restricted cubic spline modeling (RCS). For EAS and SAS, we chose renal failure (RF) for further modeling. The relationships between HTN and AFib and the ancestries EAFR, WAFR, and SEUR were best fit by the linear model (beta p < 1x10-4 for all) while the relationships with NEUR were best fit with RCS (HTN ANOVA p = 0.001, AFib ANOVA p < 1x10-4). For RF, the relationship with SAS was best fit with a linear model (beta p < 1x10-4) while RCS model was a better fit for EAS (ANOVA p < 1x10-4). In this study, we identify relationships between genetic ancestry and phenotypes that are best fit with non-linear modeling techniques. The assumption of linearity for regression modeling is integral for proper fitting of a model and there is no knowing a priori to modeling if the relationship is truly linear.

Imputation of race and ethnicity categories using genetic ancestry from real-world genomic testing data.

The incompleteness of race and ethnicity information in real-world data (RWD) hampers its utility in promoting healthcare equity. This study introduces two methods-one heuristic and the other machine learning-based-to impute race and ethnicity from genetic ancestry using tumor profiling data. Analyzing de-identified data from over 100,000 cancer patients sequenced with the Tempus xT panel, we demonstrate that both methods outperform existing geolocation and surname-based methods, with the machine learning approach achieving high recall (range: 0.859-0.993) and precision (range: 0.932-0.981) across four mutually exclusive race and ethnicity categories. This work presents a novel pathway to enhance RWD utility in studying racial disparities in healthcare.

[Prevalence of the GA risk haplotype of the rs1554483 and rs4864548 polymorphisms of the CLOCK gene associated with obesity and overweight in 26 populations]. / Prevalencia del haplotipo de riesgo GA de los polimorfismos rs1554483 y rs4864548 del gen CLOCK asociados a la obesidad y el sobrepeso en 26 poblaciones.

Introduction: Introduction: the GA haplotype of polymorphisms rs1554483 and rs4864548 has been associated with components of the metabolic syndrome such as high blood pressure and triglyceride levels; its carriers have a risk of obesity, 1.5 times higher than the rest of the population. Methodology: SNP rs1554483 and rs4864548 were obtained from 2504 individuals from the "1000genomes phase 3" database. Data were grouped into five macro populations (Africa, East Asia, South Asia, Europe and Latin America) covering a total of 26 populations. Differences in haplotype frequency between macro populations and populations were analyzed, for which Fisher's F statistic was used. Results: the macro population of Africa presented the lowest frequency (17.9 %) and that of East Asia the highest (57.4 %). Within the populations there is a relative homogeneity in the frequencies, except in the case of those that make up the macro population of Latin America where the Peruvian population of Lima and the Puerto Rican population present much higher frequencies than the rest. Conclusions: the GA haplotype presents heterogeneity between macro populations, which suggests highly differentiated micro evolutionary processes between continents. We propose to study the association of the GA haplotype with other polymorphisms such as rs3749474, rs11932595 and rs6859524 that have also been associated with risk of obesity and factors associated with metabolic syndrome.

Introducción: Introducción: el haplotipo GA de los polimorfismos rs1554483 y rs4864548 se ha asociado con componentes del síndrome metabólico como la hipertensión arterial y los niveles de triglicéridos. Sus portadores presentan un riesgo de obesidad 1,5 veces mayor que el resto de la población. Metodología: se obtuvieron los SNP rs1554483 y rs4864548 de 2504 individuos desde la base de datos "1000genomes phase 3". Los datos se agruparon en cinco macropoblaciones (África, Asia Oriental, Asia Meridional, Europa y Latinoamérica) cubriendo un total de 26 poblaciones. Se analizaron las diferencias en la frecuencia del haplotipo entre las macropoblaciones y las poblaciones, para lo cual se utilizó el estadístico F de Fisher. Resultados: la macropoblación de África presentó la menor frecuencia (17,9 %) y la del Este de Asia la mayor (57,4 %). Dentro de las poblaciones existe una relativa homogeneidad en las frecuencias, excepto en el caso de las que componen la macropoblación de Latinoamérica, donde la población peruana de Lima y la puertorriqueña presentan frecuencias mucho mayores que el resto. Conclusiones: el haplotipo GA presenta heterogeneidad entre las macropoblaciones, lo que sugiere procesos microevolutivos altamente diferenciados entre los continentes. Se propone estudiar la asociación del haplotipo GA con otros polimorfismos, como rs3749474, rs11932595 y rs6859524, que también se han asociado con el riesgo de obesidad y factores asociados al síndrome metabólico.

Understanding how genetic ancestry may influence cancer development.

Of the multifactorial determinants that lead to cancer health disparities among race groups, quantified genetic ancestry has begun to expand our knowledge beyond self-reported race. However, it is essential to study these biological determinants in the context of social determinants to truly improve clinical tools and achieve equitable survival outcomes.

Continental-scale genomic analysis suggests shared post-admixture adaptation in the Americas.

American populations are one of the most interesting examples of recently admixed groups, where ancestral components from three major continental human groups (Africans, Eurasians and Native Americans) have admixed within the last 15 generations. Recently, several genetic surveys focusing on thousands of individuals shed light on the geography, chronology and relevance of these events. However, even though gene flow could drive adaptive evolution, it is unclear whether and how natural selection acted on the resulting genetic variation in the Americas. In this study, we analysed the patterns of local ancestry of genomic fragments in genome-wide data for ~ 6000 admixed individuals from 10 American countries. In doing so, we identified regions characterized by a divergent ancestry profile (DAP), in which a significant over or under ancestral representation is evident. Our results highlighted a series of genomic regions with DAPs associated with immune system response and relevant medical traits, with the longest DAP region encompassing the human leukocyte antigen locus. Furthermore, we found that DAP regions are enriched in genes linked to cancer-related traits and autoimmune diseases. Then, analysing the biological impact of these regions, we showed that natural selection could have acted preferentially towards variants located in coding and non-coding transcripts and characterized by a high deleteriousness score. Taken together, our analyses suggest that shared patterns of post admixture adaptation occurred at a continental scale in the Americas, affecting more often functional and impactful genomic variants.

A review of the racial heterogeneity of breast cancer stem cells.

Breast Cancer Stem Cells has become the toast of many breast cancer investigators in the past two decades owing to their crucial roles in tumourigenesis, progression, differentiation, survival and chemoresistance. Despite the growing list of research data in this field, racial or ethnic comparison studies on these stem cells remain scanty. This study is a comparative racial analysis of putative breast cancer stem cells. Research articles on the clinicopathological significance of breast cancer stem cells within a period of 17 years (2003-2020) were reviewed across 5 major races (African/Black American, Asian, Caucasian/White, Hispanic/Latino, and American). The associations between the stem cells markers (CD44+/CD24-/low, BMI1, ALDH1, CD133, and GD2) and clinicopathological and clinical outcomes were analysed. A total of 40 studies were included in this study with 50% Asian, 25% Caucasian, 10% African, 5% American and 2.5% Hispanic/Latino, and 7.5% other mixed races. CD44+/CD24-/low has been associated with TNBC/Basal like phenotype across all races. It is generally associated with poor clinicopathological features such as age, tumour size, lymph node metastasis and lymphovascular invasion. In Asians, CD44+/CD24-/low was associated with DFS and OS but not in Caucasians. ALDH1 was the most studied breast CSC marker (40% of all studies on breast cancer stem cell markers) also associated with poor clinicopathological features including size, age, stage, lymph node metastasis and Nottingham Prognostic Index. ALDH1 was also associated with DFS and OS in Asians but not Caucasians. Racial variations exist in breast cancer stem cell pattern and functions but ill-defined due to multiple factors. Further research is required to better understand the role of breast CSC.

Mapping the human genetic architecture of COVID-19.

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3-7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.

Racial/ancestral diversity in 174 toxicity-related radiogenomic studies: A systematic review.

PURPOSE: This study systematically reviews the distribution of racial/ancestral features and their inclusion as covariates in genetic-toxicity association studies following radiation therapy. MATERIALS AND METHODS: Original research studies associating genetic features and normal tissue complications following radiation therapy were identified from PubMed. The distribution of radiogenomic studies was determined by mining the statement of country of origin and racial/ancestrial distribution and the inclusion in analyses. Descriptive analyses were performed to determine the distribution of studies across races/ancestries, countries, and continents and the inclusion in analyses. RESULTS: Among 174 studies, only 23 with a population of more one race/ancestry which were predominantly conducted in the United States. Across the continents, most studies were performed in Europe (77 studies averaging at 30.6 patients/million population [pt/mil]), North America (46 studies, 20.8 pt/mil), Asia (46 studies, 2.4 pt/mil), South America (3 studies, 0.4 pt/mil), Oceania (2 studies, 2.1 pt/mil), and none from Africa. All 23 studies with more than one race/ancestry considered race/ancestry as a covariate, and three studies showed race/ancestry to be significantly associated with endpoints. CONCLUSION: Most toxicity-related radiogenomic studies involved a single race/ancestry. Individual Participant Data meta-analyses or multinational studies need to be encouraged.

Epigenome-wide association study of kidney function identifies trans-ethnic and ethnic-specific loci.

BACKGROUND: DNA methylation (DNAm) is associated with gene regulation and estimated glomerular filtration rate (eGFR), a measure of kidney function. Decreased eGFR is more common among US Hispanics and African Americans. The causes for this are poorly understood. We aimed to identify trans-ethnic and ethnic-specific differentially methylated positions (DMPs) associated with eGFR using an agnostic, genome-wide approach. METHODS: The study included up to 5428 participants from multi-ethnic studies for discovery and 8109 participants for replication. We tested the associations between whole blood DNAm and eGFR using beta values from Illumina 450K or EPIC arrays. Ethnicity-stratified analyses were performed using linear mixed models adjusting for age, sex, smoking, and study-specific and technical variables. Summary results were meta-analyzed within and across ethnicities. Findings were assessed using integrative epigenomics methods and pathway analyses. RESULTS: We identified 93 DMPs associated with eGFR at an FDR of 0.05 and replicated 13 and 1 DMPs across independent samples in trans-ethnic and African American meta-analyses, respectively. The study also validated 6 previously published DMPs. Identified DMPs showed significant overlap enrichment with DNase I hypersensitive sites in kidney tissue, sites associated with the expression of proximal genes, and transcription factor motifs and pathways associated with kidney tissue and kidney development. CONCLUSIONS: We uncovered trans-ethnic and ethnic-specific DMPs associated with eGFR, including DMPs enriched in regulatory elements in kidney tissue and pathways related to kidney development. These findings shed light on epigenetic mechanisms associated with kidney function, bridging the gap between population-specific eGFR-associated DNAm and tissue-specific regulatory context.

Sex and Race-Related DNA Methylation Changes in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the sixth most common cancer and fourth leading cause of cancer-related death worldwide. The number of HCC cases continues to rise despite advances in screening and therapeutic inventions. More importantly, HCC poses two major health disparity issues. First, HCC occurs more commonly in men than women. Second, with the global increase in non-alcoholic fatty liver diseases (NAFLD), it has also become evident that HCC is more prevalent in some races and/or ethnic groups compared to others, depending on its predisposing etiology. Most studies on HCC in the past have been focused on genetic factors as the driving force for HCC development, and the results revealed that genetic mutations associated with HCC are often heterogeneous and involve multiple pathogenic pathways. An emerging new research field is epigenetics, in which gene expression is modified without altering DNA sequences. In this article, we focus on reviewing current knowledge on HCC-related DNA methylation changes that show disparities among different sexes or different racial/ethnic groups, in an effort to establish a point of departure for resolving the broader issue of health disparities in gastrointestinal malignancies using cutting-edge epigenetic approaches.

GENETICS IN ENDOCRINOLOGY: Impact of race and sex on genetic causes of aldosterone-producing adenomas.

Primary aldosteronism (PA) is a common cause of secondary hypertension. Recent technological advances in genetic analysis have provided a better understanding of the molecular pathogenesis of this disease. The application of next-generation sequencing has resulted in the identification of somatic mutations in aldosterone-producing adenoma (APA), a major subtype of PA. Based on the recent findings using a sequencing method that selectively targets the tumor region where aldosterone synthase (CYP11B2) is expressed, the vast majority of APAs appear to harbor a somatic mutation in one of the aldosterone-driver genes, including KCNJ5, ATP1A1, ATP2B3, CACNA1D, CACNA1H, and CLCN2. Mutations in these genes alter intracellular ion homeostasis and enhance aldosterone production. In a small subset of APAs, somatic activating mutations in the CTNNB1 gene, which encodes ß-catenin, have also been detected. Accumulating evidence suggests that race and sex impact the somatic mutation spectrum of APA. Specifically, somatic mutations in the KCNJ5 gene, encoding an inwardly rectifying K+ channel, are common in APAs from Asian populations as well as women regardless of race. Associations between APA histology, genotype, and patient clinical characteristics have also been proposed, suggesting a potential need to consider race and sex for the management of PA patients. Herein, we review recent findings regarding somatic mutations in APA and discuss potential roles of race and sex on the pathophysiology of APA as well as possible clinical implications.

A transdisciplinary approach to understand the epigenetic basis of race/ethnicity health disparities.

Health disparities correspond to differences in disease burden and mortality among socially defined population groups. Such disparities may emerge according to race/ethnicity, socioeconomic status and a variety of other social contexts, and are documented for a wide range of diseases. Here, we provide a transdisciplinary perspective on the contribution of epigenetics to the understanding of health disparities, with a special emphasis on disparities across socially defined racial/ethnic groups. Scientists in the fields of biological anthropology, bioinformatics and molecular epidemiology provide a summary of theoretical, statistical and practical considerations for conducting epigenetic health disparities research, and provide examples of successful applications from cancer research using this approach.

Maternal ancestry and hematological cancer risk: case-control study in an Argentinean population.

Aim: We investigated the role of maternal ancestry in neoplastic hematological malignancies (HMs) risk in a population from Central Argentina. Materials & methods: We analyzed 125 cases with HMs and 310 controls from a public hospital, and a set of 202 colorectal, breast, lung, and hematologic cancer patients from a private hospital. Results: A decreased risk for HMs was associated with the Native American haplogroup B2 (odds ratio = 0.49; 95% CI: 0.25-0.92; p = 0.02). The sub-Saharan African parahaplogroup L was associated with higher susceptibility for disease (odds ratio = 3.10; 95% CI: 1.04-9.31; p = 0.043). Although the mean ancestral proportions in the total studied population was as published (61.7% Native American, 34.6% European and 3.7% African), an unequal distribution was observed between hospitals. Conclusion: We confirmed the tri-hybrid nature of the Argentinean population, with proportions varying within the country. Our finding supports the notion that associated haplogroup is population and cancer specific.