Abstract A112: A semi-supervised approach to classify atypical BRAF mutations to identify effective targeted therapies in colorectal cancer
Authors: Madduri Abhinav B , Liu Yang , Nelson Bela G , Wang Darren J , Sanders Kaitlin E , Jamal Naadir H , Sahni Nidhi , Shen John Paul 
Published: December 2023

Due to a minority of atypical BRAF alleles being classified as either activating and RAS-independent (class 2) or kinase-impaired and RAS-dependent (class 3), few pre-clinical models of these atypical BRAF mutations exist, limiting efforts to discover effective targeted therapies for these tumors. Here we evaluated the activity of 100 different mutant BRAF alleles (6 Class 2, 10 Class 3, 84 unclassified) using Reverse Phase Protein Array (RPPA) profiles and then used principal component analysis (PCA) and semi-supervised clustering learning methods to classify the 84 unclassified mutations. To identify the protein features that best defined each class of BRAF mutation (Class 1,2,3 and non-activating) pairwise t-tests were performed on the RPPA profiles identifying a total of 43 proteomic features. PCA with K-means clustering was performed; known Class 2 and Class 3 samples separated from each other and non-activating controls. Within the same cluster, previously unclassified mutations were assigned to the same class as mutations with known classification; 8 mutations were classified as Class 1, 42 Class 2, 28 Class 3, and 6 non-activating.Analyzing RPPA profiles across each BRAF class with several markers utilized by Yao and colleagues showed similar patterns in protein expression levels between the putative and Yao classification systems (MAPK_pT202_Y204: p = 0.57, n = 13 for Class 2 and p = 0.62, n = 21 for Class 3; Cyclin-D1: p = 0.83, n = 8 for Class 2 and p = 0.26, n = 17 for Class 3). Cell viability analysis of BRAF-mutant Ba/F3 cells using Student’s t-test yielded no significant differences in mean AUC values between new and old classification systems (class 2: p = 0.53, n = 63, Cohen’s d = 0.22; class 3: p = 0.93, n = 40, Cohen’s d = 0.03), further validating that the newly established classification system is consistent with the Yao classes.Network analysis was also performed to uncover essential oncogenic interactions for each BRAF class. KRAS, NRAS, and PIK3CA were found to have higher CERES scores for class-2 and -3 cells, while atypical BRAF yielded lower CERES scores. This suggests that in cells carrying atypical BRAF mutations, BRAF is less independently important for cell survival and it must partner with other oncogenes to drive tumor growth. Several key genes, including PIK3CA, EGFR, and MEK, were identified as potential drug targets for CRC cell lines with class-3 atypical BRAF mutations. In the cell lines, NCIH508 (Yao class 3) and HT55 (putative class 3), Trametinib (MEK inhibitor) and Afatinib (EGFR inhibitor) yielded IC 50 values below 3 µM (0.1 µM for HT55 with Afatinib and for NCIH508 with Trametinib), while Dactolisib (PIK3CA inhibitor) yielded an IC50 value of 0.1 µM.In conclusion, we extended the previous BRAF-mutant Yao classification system to establish the Yao Classification System Plus, which includes 84 more atypical BRAF mutations. This allows for the development of greater therapeutic options to target tumors carrying these newly characterized mutations and expand care options for many CRC patients.

Citation Format: Abhinav B Madduri, Yang Liu, Bela G Nelson, Darren J Wang, Kaitlin E Sanders, Naadir H Jamal, Nidhi Sahni, John Paul Shen. A semi-supervised approach to classify atypical BRAF mutations to identify effective targeted therapies in colorectal cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A112.