Abstract Background: DNA methylation (Me) is known to vary by race and ethnicity; cell-free DNA-based MCED tests must detect cancer-specific Me in the presence of this variation to be useful as a screening tool. Clinical study cohorts, however, often do not reflect the screening population. Additionally, underserved populations who may benefit most from improved cancer screening are often underrepresented. We sought to evaluate the robustness of an MCED test to detect cancer-specific Me patterns across self-reported ethnicity (SRE) in the training (N = 4487) and validation (N = 5309) datasets from the 15254-participant (pts) Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study. Methods: To understand MCED test performance across SRE, we assessed concordance between ancestry and SRE by genotype in CCGA. We then conducted two in silico experiments to assess the robustness of the MCED test to differences in SRE. First, MCED test classifier scores from 1254 non-cancer pts from the validation cohort were regressed against covariates of sex and SRE, with smoking status and age included as potential confounders. Two SRE groups were considered for the analysis: White, non-Hispanic (W; 996 pts) and all other non-White SRE (NW; 258 pts). Second, to evaluate classifier generalization across SRE, two experimental MCED test classifiers (single SRE, S; multiple SRE, M) were trained similarly to the MCED test with intentionally skewed SRE compositions: S with 100% W pts and M with all available NW pts (20% NW). The training sets for both classifiers further included pts from STRIVE (NCT03085888) and matched on demographics (age, sex, smoking status), number of pts, samples, cancer type and stage. Sensitivity (at 99.4% specificity) and accuracy of cancer signal origin (CSO) prediction for the two classifiers were assessed in a separate held out population of 507 NW cancer pts. Results: Ancestry and SRE by genotype were in good agreement with >95% concordance in CCGA study pts. Neither sex, smoking status, nor SRE were significantly correlated with MCED classifier scores; age was weakly (r2 < 0.01) associated. In the classifier training experiment, both S and M performed nearly identically for sensitivity (S: 57% [95% CI: 53-62], 290/507 vs M: 57% [52-61], 288/507; McNemar test, P > 0.5) and CSO prediction accuracy (S: 90% [86-93] 262/290 vs M: 91% [88-94] 263/288) in a diverse population of NW cancer pts, despite the relatively large difference in SRE training composition. Neither analysis detected a significant contribution from Me patterns associated with SRE on classifier performance. Conclusions: Though DNA Me differences are known to occur across SRE, MCED classifier scores were comparable across non-cancer pts in SRE groups. Similarly, cancer signal detection in a NW population was comparable regardless of classifier training exposure. These findings indicate that detection of invasive cancer by the MCED test is not strongly influenced by SRE. Ongoing interventional studies of the MCED test are targeting enrollment of population-representative SRE. Citation Format: Oliver Venn, Joerg Bredno, Alexis Thornton, Earl Hubbell, Kathryn Kurtzman, John Beausang, Charles Swanton. The robustness of a targeted methylation-based multi-cancer early detection (MCED) test to population differences in self-reported ethnicity [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C139.