Metastatic castration-resistant prostate cancer (mCRPC) includes a subset of patients with particularly unfavorable prognosis characterized by combined defects in at least two of three tumor suppressor genes: PTEN, RB1, and TP53 as aggressive variant prostate cancer molecular signature (AVPC-MS). We aimed to identify circulating tumor cells (CTC) signatures that could inform treatment decisions of patients with mCRPC with cabazitaxel–carboplatin combination therapy versus cabazitaxel alone. Liquid biopsy samples were collected prospectively from 79 patients for retrospective analysis. CTCs were detected, classified, enumerated through a computational pipeline followed by manual curation, and subjected to single-cell genome-wide copy-number profiling for AVPC-MS detection. On the basis of immunofluorescence intensities, detected rare cells were classified into 8 rare-cell groups. Further morphologic characterization categorized CTC subtypes from 4 cytokeratin-positive rare-cell groups, utilizing presence of mesenchymal features and platelet attachment. Of 79 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 and minimal benefit from combination therapy. In AVPC-MS–negative patients, its presence showed significant survival improvement from combination therapy. Our findings suggest the presence of pc.CTCs as a predictive biomarker to further stratify AVPC subsets with the worst prognosis and the most significant benefit of additional platinum therapy. Implications: HDSCA3.0 can be performed with rare cell detection, categorization, and genomic characterization for pc.CTC identification and AVPC-MS detection as a potential predictive biomarker of mCRPC.

ObjectiveThe standard treatment for cervical cancer in developed countries includes surgery and chemoradiation, with standard of care lagging in developing countries. Even in the former case, treatment frequently yields recalcitrant tumors and women succumb to disease. Here we examine the impact of nelfinavir, an off-patent viral protease inhibitor, which has shown promise as an antineoplastic agent.MethodsWe evaluated the morphological and proliferative effects of the autophagy-stressing drug nelfinavir in normal and cisplatin-resistant cervical cancer cells. Immunofluorescent validation of autophagy markers was performed and the impact of nelfinavir in an in vivo model of tumor growth was determined.ResultsNelfinavir exhibits cytotoxicity against both cisplatin-sensitive and -resistant ME-180 human cervical cancer cells in vitro and in vivo. Immunoblotting and immunofluorescence showed an expression of the autophagy marker LC3-II in response to nelfinavir treatment.ConclusionNelfinavir, now available as an inexpensive generic orally dosed agent (Nelvir), is cytotoxic against cervical cancer cells. It acts by burdening the autophagy pathway to impair tumor cell survival and a modest induction of apoptosis. While further studies are needed to elucidate the optimal method of application of nelfinavir, it may represent an appealing global option for the treatment of cervical cancer.

<p>S1. Platelet confirmation with CD61 staining in the SKBR3-spiked NBD sample S2. Enumeration of CTC subtypes S3. Survival analysis using AVPC-MS-CTC status S4. Survival analysis in patients without pc.CTC S5. Treatment decision tree Table S1. Correlation between CTC and clinical characteristics</p>

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.