Dissecting CTC phenotypic heterogeneity for predictive biomarker identification and its association with clonal lineage through single-cell multi-omic profiling

Abstract Background: The mutation, selection, and adaptation of tumor cells along disease progression exhibits a spectrum of phenotypic and genotypic heterogeneity. The importance of distinguishing phenotypic states of CTC in addition to genomic alterations has been addressed for identifying predictive biomarkers and understanding CTC biology. Current liquid biopsy usually relies on only one phenotypic state of CTCs without further genomic validation of cancer cell identity. Here, we developed HDSCA3.0, a multi-omic platform, which could distinguish various phenotypic states of CTCs followed by genomic characterization. Methods: Paired peripheral blood (PB) and bone marrow aspirate (BMA) samples were collected prospectively from 80 metastatic castrate resistant prostate cancer (mCRPC) patients for retrospective analysis. Seventy-nine of them were part of Cabazitaxel With or Without Carboplatin Trial (NCT01505868) and one independent index patient was included with aggressive disease and unfavorable prognosis. CTCs were detected, classified, enumerated through a four-channel immunostaining assay (DAPI|Cytokeratin|Vimentin|CD45/CD31) and a computational pipeline followed by manual curation, and subjected to single-cell copy-number profiling for clonality analysis and aggressive variant prostate cancer molecular signature (AVPC-MS) detection i.e. 2+ defects in PTEN, RB1, and TP53 genes. Results: CTC subtypes were categorized from Cytokeratin-positive rare cell groups based on the presence of mesenchymal features and platelet attachment. Of 79 trial cases, 77 (97.5%) had CTCs, 24 (30.4%) were positive for platelet-coated CTCs (pc.CTCs) and 25 (38.5%) of 65 sequenced patients exhibited AVPC-MS in CTCs. Survival analysis indicated that the presence of pc.CTCs identified the subset of patients who were AVPC-MS-positive with the worst prognosis. In AVPC-MS-negative patients, its presence showed significant survival improvement from combination therapy. In index patient, we uniquely identified genetically clonal mesenchymal-like CTCs (mes.CTCs) and their presence was significantly associated with one subclone emerged along clonal lineage. Meanwhile, differences of CTC abundance and phenotypic diversity were observed between paired PB and BMA as well as genomic variations. Conclusion: Our findings suggest pc.CTCs and AVPC-MS in CTCs as a multi-omic predictive biomarker to stratify mCRPC subpopulations with the worst prognosis and the most significant benefit of additional platinum therapy and illustrate a robust approach to analyze intra-patient CTC genotypic and phenotypic heterogeneity and association. Citation Format: Shoujie Chai, Nicholas Matsumoto, Ryan Storgard, Chen-Ching Peng, Ana Aparicio, Benjamin Ormseth, Kate Rappard, Cunningham Kate, Anand Kolatkar, Rafael Nevarez, Kai Han Tu, Ching-Ju Hsu, Amin Naghdloo, Paymaneh Malihi, Liya Xu, Paul Corn, Amado Zurita-Saavedra, James Hicks, Carmen Ruiz-Velasco, Peter Kuhn. Dissecting CTC phenotypic heterogeneity for predictive biomarker identification and its association with clonal lineage through single-cell multi-omic profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1957.