Abstract Background: Recent studies support that high levels of tumor-infiltrating lymphocytes (TILs) were associated with better prognosis in HPV(+) oropharyngeal squamous cell carcinoma (OPSCC). While these studies provide a potential role for TILs as a prognostic biomarker, the analyses were relied on manual quantification performed by pathologists, resulting in inter-observer variability. Deep Learning (DL)-based whole slide hematoxylin and eosin (H&E) image analyses may overcome these challenges. However, this analysis only provides the presence of cell types without consideration for the functional roles of each cell within the tumor immune microenvironment (TME). In this work, we develop a computational pipeline to integrate paired H&E and immunohistochemistry (IHC) images to functionally characterize TILs and investigate their prognostic utility. Methods: We analyzed 88 patients: 42 stage I, 39 stage II, and 7 stage III. Our data contain both H&E and IHCs examining FoxP3, CD3, PD-L1, CD20, etc. on serial sections of the tissue. In-house DL-based H&E analysis used to identify TILs, tumors, and stroma in each tumor, then performed registration between adjacent H&E and IHC images from the same tissue. The patients were then classified into three basic immune phenotypes: immune inflamed (IN; high TILs in the tumor region), immune excluded (EX; TILs are mostly localized in stroma), and immune desert (ID; few/no TILs) based on TIL enrichment in the TME. To functionally characterize TILs, we quantified protein expression from the adjacent IHCs. For example, we further classified each patient into different subtypes based on enriched protein expression (e.g., FoxP3 high IN, FoxP3 low IN). We used the Kaplan-Meier method and multivariate Cox analysis to evaluate the prognostic value of different subtypes enriched with different proteins to predict disease-free survival (DFS). Results: The IN group with 43 patients was significantly associated with good prognosis. Interestingly, further stratification of the IN subgroup based on Foxp3 quantification on TIL regions (i.e., high FoxP3 IN and low FoxP3 IN) showed that high protein expression of FoxP3 in TILs in the IN subgroup is significantly associated with a better prognosis compared to other immune subgroups (HR, 0.16; p-value, 0.003). Multivariate analysis, including other clinical covariates showed that the immune subtypes associated with high FoxP3 are independently associated with DFS. These results demonstrate that DL-based integrative IHC and H&E image analysis could be used to identify subgroups with distinct clinical outcomes. Furthermore, our results reveal unknown roles for Foxp3 expression in the TILs in HPV(+) OPSCC as a prognostic biomarker, a finding which should be evaluated in a larger cohort. Citation Format: Sumanth Reddy Nakkireddy, Inyeop Jang, Minji Kim, Linda X. Yin, Michael Rivera, Joaquin J. Garcia MD, Kathleen R. Bartemes, David M. Routman, Eric J. Moore, Daniel J. Ma, Kathryn M. Van Abel, Tae Hyun Hwang. Integrative spatial analysis of paired IHC and H&E images identifies Foxp3 enriched tumor-infiltrating lymphocytes associated with disease-free survival in human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma. [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 4638.
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