Racial/ethnic representation and disparities in preclinical cancer models.
Authors: Jonathan M. Loree, Arvind Dasari, Jason Willis, Himanish Gothwal, Mena Shaheed, Kulwinder Singh, Hewad Shaheed, Riya Mangal, Shivek Gothwal, Anya Pant, Michael J. Overman, Scott Kopetz, Kanwal Pratap Singh Raghav
Journal: Journal of Clinical Oncology (2024)

1601 Background: Patient-derived xenograft models (PDXs) recapitulate tumor characteristics credibly and have become a standard for preclinical inquiries that form the basis of clinical trials of novel therapies in oncology. While ample evidence reveals racial/ethnic disparities in cancer care delivery and clinical research, limited data exists regarding racial composition of available PDXs. We sought to define the extent of racial/ethnic representation and disparities among existing PDXs. Methods: Data regarding available PDXs was gathered from the publicly accessible CancerModels.org website ( https://www.cancermodels.org/overview ). Seven members of the research team were involved in data extraction. Information on race/ethnicity (White, Black, Hispanic, Asian), sex, age, and cancer type were recorded. The primary objective was to determine the racial/ethnic composition of PDX models and compare this to racial/ethnic demographics of cancer patients, for which we used US population-based cancer estimates calculated using National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER Incidence Data, 11/2022 Submission (1975 - 2020), SEER 22 registries). Descriptive statistics were used. Proportions were compared using Fischer’s exact test or Chi-squared tests with Yates' correction (odds-ratio [OR] and 95% confidence intervals [95%CI] or Woolf logit interval) were reported. Results: We reviewed 4597 unique PDXs across 33 SEER cancer sites spanning 11 oncology sub-specialties. Of these, 55% models were derived from males and age groups were (years): &lt; 20: 6%; 20-70: 69% and ≥ 70: 25%. Most common cancer sites represented were colorectal (26%), lung (12%), breast (9%), melanoma (9%) and leukemia (7%). Race/ethnicity was not reported in 3395 (73.9%) cases. Racial/ethnic composition of the remaining models was Whites (80.9%), Blacks (7.3%), Hispanics (6.4%) and Asians (5.4%). Compared with their respective proportion of US cancer incidence (69.9%, 10.9%, 13.2% and 5.9%, respectively), these models were over-representative for Whites (OR: 1.82, 95%CI: 1.6-2.1, P &lt; 0.001) and under-represented Blacks (OR: 0.64, 95%CI: 0.5-0.8, P &lt; 0.001) and Hispanics (OR: 0.45, 95%CI: 0.4-0.6, P &lt; 0.001) but not Asians (OR: 0.89, 95%CI: 0.7-1.2, P = 0.43). Similar trends were seen in subgroups focused by cancer site. Among colorectal (N = 1201) models, race/ethnicity was reported for 17.2% of cases and Blacks (OR: 0.52; 55.7% of expected; P = 0.014) and Hispanics (OR: 0.57; 60.8% of expected; P = 0.015) were underrepresented compared to Whites (OR: 1.82; 116% of expected; P &lt; 0.001). Conclusions: Race/ethnicity are infrequently reported for PDX models. Minority races/ethnicities (Blacks and Hispanics) are underrepresented in preclinical models compared to their burden of cancer incidence. There is a need to develop a diverse repertoire of preclinical models to ensure inclusivity and guide equitable research.