Abstract A022: Uncovering CAR-T targets from the cholangiocarcinoma proteome

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Abstract Objective: The project is designed to identify pairs of proteins for CAR-T co-targeting immunotherapy for cholangiocarcinoma (CCA) based on expression of surface proteins in proteomic experiments. Introduction: Cholangiocarcinoma is a rare cancer of the bile duct, with a dismal prognosis. Standard of care in Canada includes chemotherapy, with a 5-year survival rate of just 2%. Alternative approaches are clearly needed, and as with many other indications, immunotherapies are showing promise. Methods: We are performing a three-pronged approach to identify candidate CCA CAR-T targets from proteomic datasets: 1) Proteomic identification of CCA-enriched surface proteins. From 21 FFPE cholangiocarcinoma tumors, we performed mass spectrometry on macrodissected tumor regions, capturing their global proteomes. We obtained the global proteomes of comparator tissues to identify CCA-enriched surface proteins: i) normal liver, pancreas, and gall bladder (3 each, 9 total); ii) a normal cholangiocyte cell line; and iii) a CCA cell line. After informatically filtering the data to those proteins which are found on the cell membrane, we assessed differential abundance between the tumor and normal sample types. 2) A bioinformatic meta-analysis of existing published proteomic datasets. Surface proteins enriched in the proteomic results of the CCA tumors and CCA cell line were compared to a range of healthy tissues across a large age range. Careful reprocessing of raw data was required to be able to compare trends across discrete datasets. 3) Bioinformatic candidate selection. Candidate pairs of proteins would be based on co-occurrence patterns (i.e. pairs of proteins, to be targeted using logic gated CARs), and AlphaFold structure prediction to find sterically-favorable pairs. Criteria would include surface proteins enriched in abundance in CCA tumors, having low abundance in normal comparators, and possessing targetable extra cellular regions. Candidate pairs would be filtered for those NOT having enriched abundance in the SAME normal comparator tissues. Alternatively, candidate pairs seen enriched in the SAME normal comparator could be used in an AND-NOT logic gate. Top-ranked candidates will proceed to validation and CAR-T development in future work. Summary: We have identified many surface enriched candidates, including 3-6 that show promising characteristics; having strong and consistent abundance on CCA tumors, limited detection on a range of normal tissues, and containing extracellular domains where there already exist antibodies that target them. These candidates satisfy the primary logic gate criteria and are undergoing further bioinformatic analyses to confirm pairwise co-occurrence before being validated experimentally for tumor and surface expression on larger CCA tissue microarrays, and copy number evaluation. Conclusion: The combination of proteomic and bioinformatic analysis of tumor and normal tissues to identify tumor associated surface proteins is a promising method to identify novel candidates for logic gated CAR-T immunotherapies. Citation Format: Gregg B. Morin, Scott D. Brown, Tracy S. Lee, Sandra E. Spencer, Gian L. Negri, Sarah Baldry, Naghmeh Khoshgoo, Brian Mooney, Grace SW. Cheng, Robert A. Holt. Uncovering CAR-T targets from the cholangiocarcinoma proteome [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Breaking Barriers in the Fight against Rare Cancers; 2026 Jul 18-20; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(14_Suppl):Abstract nr A022.

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