Abstract 6414: Ultra-sensitive structural biomarker discovery for TNBC and pancreatic cancer using a deep VHH repertoire (IBMET): A translational platform for tissue-agnostic target identification

Abstract Background: In cancers with substantial unmet medical need (UMN), the limited availability of reliable and tumor-selective surface biomarkers continues to hinder therapeutic development. This challenge is particularly evident in triple-negative breast cancer (TNBC) and pancreatic ductal adenocarcinoma (PDAC), where currently available targets often show insufficient specificity or restricted applicability across patient subgroups. Methods: We established the Inverse Biomarker Exploration Technology (IBMET), a systematic framework designed to detect pathological structural alterations on tumor cells. IBMET utilizes a large alpaca-derived VHH antibody repertoire as highly sensitive structural probes. Alpacas were immunized with multiple tumor cell lines, and the resulting VHH library was analyzed using phage display and next-generation sequencing. Candidate antibodies were selected based on statistical enrichment and evaluated by IHC/IF across an extensive panel of tumor and normal tissues. Antigen identification was performed by cross-linking immunoprecipitation, SDS-PAGE, and LC-MS/MS. Clinical relevance was examined using a breast cancer biopsy cohort (n = 106). Results: IBMET identified several structural biomarker candidates relevant to TNBC and PDAC. The lead antibody, VHH89, selectively recognized a previously uncharacterized low-molecular-weight isoform of ALCAM (approximately 70 kDa; designated ALCAM70). VHH89 showed lesion-selective staining in tumor tissues with minimal reactivity in normal organs, indicating a high degree of tumor specificity. In clinical breast cancer specimens, VHH89 demonstrated positivity in more than 20% of TNBC cases. In addition, subsets of pancreatic cancer and cholangiocarcinoma specimens also showed VHH89 positivity, suggesting that this isoform may represent a structurally altered antigen present across multiple tumor types. Conclusion: IBMET offers a reproducible and scalable approach for identifying structurally defined biomarkers that may not be detectable using genomic or transcriptomic analyses alone. By systematically excluding antibodies that react with normal tissues and enriching for tumor-associated conformational epitopes, IBMET broadens the spectrum of actionable targets for aggressive cancers. These findings support the potential integration of IBMET-derived antibodies into the development of next-generation antibody-drug conjugates, radioligand therapies, and companion diagnostics. To facilitate broader validation, COGNANO will make eight PDAC-selective VHH antibodies available for research use at AACR 2026. Citation Format: Akihiro Imura, Ryota Maeda, Hiroyuki Yamazaki, Tsuyoshi Inoue, Sadako Aakashi-Tanaka, Hiroko Tsukada. Ultra-sensitive structural biomarker discovery for TNBC and pancreatic cancer using a deep VHH repertoire (IBMET): A translational platform for tissue-agnostic target identification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6414.