Abstract 4260: Understanding genomic and social determinants of cancer immunotherapy outcome across ancestry
Authors: Fong Christopher J. , Waters Michele , Pichotta Karl , Jee Justin , Jutagir Devika R. , Ma David , Perea-Chamblee Tomin , Kim Susie , Arora Kanika , Mastrogiacomo Brooke , Tran Thinh , Maron Steven , Altoe Mirella , Luthra Anisha , Kholodenko Joseph , Patha Arfath , Rose Doori , Berger Michael F. , Riely Gregory J. , Schultz Nikolaus , Goyert Sanna , Schoenfeld Adam , Gany Francesca , Carrot-Zhang Jian 
Published: April 2023

Abstract
Compared with previous standards of care, the use of immune checkpoint inhibitors (ICI) has brought significant improvements in survival and quality of life for lung cancer patients. However, only a small proportion of these patients respond durably. People with different ancestries differ probabilistically in genetic factors, environmental exposures, and socio-economic conditions. Whether patients of different ancestry benefit equally from ICIs remains unclear.
We studied the impact of genomic ancestry, tumor genomics, and social determinants of health (SDH) factors and factors that are impacted from SDH including recorded race/ethnicity, inferred low-income status from patient zip codes, exposure to smoking, and BMI on ICI response, defined by cancer progression-free survival (PFS, minimum 6 months FU), for non-small cell lung cancer (NSCLC) patients with MSK-IMPACT targeted panel sequencing. This FDA approved assay includes matched tumor-white blood cell sequencing to distinguish germline from somatic variants and has been applied to 1,802 NSCLC patients who received ICI treatment, including 81 and 117 patients with at least 80% of African (AFR) and East Asian (EAS) ancestry, respectively. Moreover, 173 samples were derived from admixed patients with more than one major ancestry.
We first used a natural language processing (NLP) model to obtain PFS from free-text clinical notes. A multivariable cox proportional hazard model was then used to associate PFS with ancestry, race, smoking status, ICI drug regimen, PD-L1 status, disease stage, tumor mutational burden (TMB), inferred income, and BMI. Neither genetic ancestry nor self-reported race/ethnicity was associated with the PFS. Moreover, ICI drug regimen types, low-income status, and BMI were not associated with PFS in our cohort. TMB-high was associated with longer PFS across all ancestries, although TMB was lower in patients with EAS ancestry (Median 7.9 vs. 5.3 mut/Mb, p&lt;0.001).
These results suggest that the benefits of ICI extend across ancestry, race, and income lines in a single institution, arguing for more equitable patient access to these medications. We also show that TMB is a generalizable biomarker for ICI outcome across ancestries. However, more diverse patient populations are needed to understand whether there is ancestry-specificity in other ICI outcome biomarkers.
Citation Format: Christopher J. Fong, Michele Waters, Karl Pichotta, Justin Jee, Devika R. Jutagir, David Ma, Tomin Perea-Chamblee, Susie Kim, Kanika Arora, Brooke Mastrogiacomo, Thinh Tran, Steven Maron, Mirella Altoe, Anisha Luthra, Joseph Kholodenko, Arfath Patha, Doori Rose, Michael F. Berger, Gregory J. Riely, Nikolaus Schultz, Sanna Goyert, Adam Schoenfeld, Francesca Gany, Jian Carrot-Zhang. Understanding genomic and social determinants of cancer immunotherapy outcome across ancestry. [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 4260.