Abstract B071: Monitoring the evolution of treatment resistance by transcriptional profiling of circulating tumor cells with RNAseq

Abstract Background: Treatment with androgen receptor (AR) -targeted therapy, chemotherapy and 177Lu-PSMA-617 radioligand therapy have improved patient outcomes for patients with metastatic prostate cancer (PCa). However, development of treatment resistance remains universal, occurring through AR dependent mechanisms driving constitutive AR signaling, or lineage state transitions that bypass AR signaling and culminate in highly proliferative tumors, including those with luminal B (LumB) and neuroendocrine phenotypes. We recently described two distinct luminal phenotypes with high luminal and AR signaling gene expression but distinguished by high (LumB) or low (luminal A (LumA) ) proliferation signature scores, with the LumB phenotype associated with shorter survival compared to the LumA phenotype. We also identified a low proliferation phenotype characterized by low AR/luminal signature and low proliferation, and a neuroendocrine phenotype characterized by high neuroendocrine and proliferation signature scores. Evolution of tumor biology has been difficult to monitor due to challenges in collecting serial tissue biopsies. Blood-based liquid biopsy is non-invasive and well suited for repeat sampling. RNA sequencing of circulating tumor cells (CTCs) provides an accessible means to perform longitudinal transcriptional profiling to track mechanisms of resistance over time. Methods: CTCs were isolated from patients with PCa during standard of care treatments including baseline and progression timepoints with automated microfluidic technology integrating negative and positive selection. CTCs and RNA were captured immunomagnetically. RNAseq data was assessed for CTC RNAseq phenotype, signature scores including CCP-31, signatures of tumor suppressor loss (p53, RB1, PTEN) and MYC signatures and genes previously identified as expressed in AR+ PCa or NEPC. Results: We analyzed longitudinal samples including 27 sets of matched baseline and post-treatment samples from 22 patients with metastatic PCa during treatment with AR targeted therapies, chemotherapy and 177Lu-PSMA-617. In 30% (8/27) of these patients, we observed a switch of CTC phenotype at treatment progression from pretreatment baseline sample. The most common switch (n=5) was from the LumA phenotype to LumB phenotype, which was associated with increased RB1 loss signature score (p=0. 016). We observed a patient transitioning from a LumB phenotype to neuroendocrine at progression on 177Lu-PSMA-617 radioligand therapy. In this patient, coinciding with the phenotype shift, we detected decreased expression of KLK3 and FOLH1 (PSMA) and increased expression of ASCL1, INSM1 and SYP consistent with a shift from a luminal adenocarcinoma to a neuroendocrine phenotype. Conclusions: To better understand tumor evolution, it is essential to monitor molecular changes during treatment. RNAseq of CTCs enables longitudinal tracking of lineage phenotype transitions. Ongoing studies are investigating mechanisms that drive resistance and plasticity in larger, uniformly treated patient cohorts. Citation Format: Jamie M. Sperger, Marina N. Sharifi, Amy K. Taylor, Krisitin L. Rosche, David Gallo, Viridiana Carreno, Alex H. Chang, Emily Abella, Kaitlin Durnen, Muhammad Dar, Charlotte Linebarger, William M. Stump, Kendra Marr, Kyle T. Helzer, Grace C. Blitzer, John Floberg, David Kosoff, Rana R. McKay, Xiao X. Wei, Shuang G. Zhao, Joshua M. Lang. Monitoring the evolution of treatment resistance by transcriptional profiling of circulating tumor cells with RNAseq abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86 (2Suppl): Abstract nr B071.