Genomic ancestry in kidney cancer: Correlations with clinical and molecular features Journal Article


Authors: Kotecha, R. R.; Knezevic, A.; Arora, K.; Bandlamudi, C.; Kuo, F.; Carlo, M. I.; Fitzgerald, K. N.; Feldman, D. R.; Shah, N. J.; Reznik, E.; Hakimi, A. A.; Carrot-Zhang, J.; Mandelker, D.; Berger, M.; Lee, C. H.; Motzer, R. J.; Voss, M. H.
Article Title: Genomic ancestry in kidney cancer: Correlations with clinical and molecular features
Abstract: Introduction: Genetic ancestry (GA) refers to population hereditary patterns that contribute to phenotypic differences seen among race/ethnicity groups, and differences among GA groups may highlight unique biological determinants that add to our understanding of health care disparities. Methods: A retrospective review of patients with renal cell carcinoma (RCC) was performed and correlated GA with clinicopathologic, somatic, and germline molecular data. All patients underwent next-generation sequencing of normal and tumor DNA using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets, and contribution of African (AFR), East Asian (EAS), European (EUR), Native American, and South Asian (SAS) ancestry was inferred through supervised ADMIXTURE. Molecular data was compared across GA groups by Fisher exact test and Kruskal–Wallis test. Results: In 953 patients with RCC, the GA distribution was: EUR (78%), AFR (4.9%), EAS (2.5%), SAS (2%), Native American (0.2%), and Admixed (12.2%). GA distribution varied by tumor histology and international metastatic RCC database consortium disease risk status (intermediate-poor: EUR 58%, AFR 88%, EAS 74%, and SAS 73%). Pathogenic/likely pathogenic germline variants in cancer-predisposition genes varied (16% EUR, 23% AFR, 8% EAS, and 0% SAS), and most occurred in CHEK2 in EUR (3.1%) and FH in AFR (15.4%). In patients with clear cell RCC, somatic alteration incidence varied with significant enrichment in BAP1 alterations (EUR 17%, AFR 50%, SAS 29%; p =.01). Comparing AFR and EUR groups within The Cancer Genome Atlas, significant differences were identified in angiogenesis and inflammatory pathways. Conclusion: Differences in clinical and molecular data by GA highlight population-specific variations in patients with RCC. Exploration of both genetic and nongenetic variables remains critical to optimize efforts to overcome health-related disparities. © 2023 American Cancer Society.
Keywords: adult; cancer survival; controlled study; human tissue; aged; major clinical study; overall survival; somatic mutation; genetics; clinical feature; cancer risk; gene; cancer susceptibility; incidence; inflammation; cohort analysis; angiogenesis; genetics, population; retrospective study; histology; renal cell carcinoma; kidney neoplasms; self report; kidney tumor; carcinoma, renal cell; mammalian target of rapamycin; genomics; checkpoint kinase 2; kidney cancer; molecular biology; glycolysis; oxidative phosphorylation; ethnicity; hla antigen; american indian; african; genetic correlation; clear cell renal cell carcinoma; bap1 gene; population genetics; european; tumor metabolism; chek2 gene; high throughput sequencing; east asian; south asian; humans; human; male; female; article; molecular feature; genomic ancestry; fh gene; people of mixed ancestry; population genomics
Journal Title: Cancer
Volume: 130
Issue: 5
ISSN: 0008-543X
Publisher: Wiley Blackwell  
Date Published: 2024-03-01
Start Page: 692
End Page: 701
Language: English
DOI: 10.1002/cncr.35074
PUBMED: 37864521
PROVIDER: scopus
PMCID: PMC11220722
DOI/URL:
Notes: Article -- Source: Scopus
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MSK Authors
  1. Robert Motzer
    1243 Motzer
  2. Darren Richard Feldman
    341 Feldman
  3. Martin Henner Voss
    288 Voss
  4. Michael Forman Berger
    765 Berger
  5. Abraham Ari Hakimi
    324 Hakimi
  6. Maria Isabel Carlo
    162 Carlo
  7. Eduard Reznik
    103 Reznik
  8. Chung-Han   Lee
    157 Lee
  9. Diana Lauren Mandelker
    178 Mandelker
  10. Fengshen Kuo
    81 Kuo
  11. Andrea Knezevic
    106 Knezevic
  12. Ritesh Rajesh Kotecha
    92 Kotecha
  13. Neil Jayendra Shah
    85 Shah
  14. Kanika Suresh Arora
    27 Arora