Abstract 1056: Development of a B-cell epitope classifier for early detection of renal cell carcinoma
Authors: Campbell Thomas W. , Hoerner Christian R. , Alli Elizabeth , Leppert John T. , Shon John C. , Fan Alice C. 
Published: March 2024

Abstract
A blood biomarker for early detection of renal cell carcinoma (RCC) would help decrease the burden of 15,000 deaths annually in the U.S. (1). Antibodies against tumor (neo)antigens are thought to arise early in cancer development and might serve as a more sensitive biomarker for RCC than tumor-derived biomolecules. Serum Epitope Repertoire Analysis (SERA) of human serum/plasma uses a random bacterial peptide display library and next generation sequencing to allow for unbiased highly multiplexed profiling of B cell epitopes. In combination with bioinformatic methods and machine learning, a classifier was trained to predict the presence of RCC using a cohort of 163 treatment-naïve patients (median age 62, stage: I 35%, II 5%, III 20%, IV 40%) with clear cell RCC (ccRCC) and 438 age-matched healthy controls (median age 61). Classifier performance was evaluated by sensitivity, specificity, and receiver operator curve (ROC) area under the curve (AUC) analysis in an independent validation cohort of 43 treatment-naïve patients with ccRCC (age 22-86, median 63, stage: I 33%, II 2%, III 26%, IV 39%) and 1,759 healthy controls (age 18-89, median 40). A total of 1,465 individual B cell epitope features were discovered and enriched in ccRCC vs. controls and included in a random forest model. In the validation cohort, the ROC-AUC was 0.65, and sensitivities of 9%, 16%, 30%, and 36% were achieved at specificities of 99%, 98%, 95%, and 90%, respectively. Performance was better in both early stage ccRCC and low tumor grade (grade 1 or 2). For stage I, the ROC-AUC was 0.88, and sensitivities of 7%, 14%, 36%, and 57% were achieved at specificities of 99%, 98%, 95%, and 90%, respectively. For low tumor grade, the ROC-AUC was 0.86, and sensitivities of 10%, 20%, 50%, and 60% of were achieved at specificities of 99%, 98%, 95%, and 90%, respectively. The classifier did not miscategorize benign renal lesions as ccRCC (Mann-Whitney p-value 0.52, ROC-AUC 0.54) in a separate cohort of 23 patients with benign renal tumors vs. the 1,759 healthy controls. This preliminary performance for a B cell epitope-based classifier is promising: the better performance in early stage ccRCC suggests that B cell epitope biomarkers may complement the lower sensitivity of cell-free DNA for detecting early-stage cancer (2). Future work will further validate these results in larger multi-institutional cohorts to improve classification performance and explore if B cell epitope biomarkers can be combined with existing assays to develop an early detection composite biomarker for RCC and tumor grade.
(1)Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023 Jan;73(1):17-48.(2)Francini, E.; Fanelli, G.N.; Pederzoli, F.; Spisak, S.; Minonne, E.; Raffo, M.; Pakula, H.; Tisza, V.; Scatena, C.; Naccarato, A.G.; et al. Circulating Cell-Free DNA in Renal Cell Carcinoma: The New Era of Precision Medicine. Cancers 2022, 14, 4359.
Citation Format: Thomas W. Campbell, Christian R. Hoerner, Elizabeth Alli, John T. Leppert, John C. Shon, Alice C. Fan. Development of a B-cell epitope classifier for early detection of renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1056.