Abstract 2: Addressing treatment resistance in models of lethal prostate cancer

Abstract

Abstract Prostate cancer (PC) is the malignancy with the highest incidence worldwide in males. Although localized disease can be effectively treated and usually has a favorable prognosis, progression to metastasis results in high mortality rates as current treatment modalities are not yet curative. The standard of care for advanced PC is hormonal therapy, termed Androgen Deprivation Therapy (ADT). Unfortunately, ADT typically elicits the emergence of a lethal phenotype, termed Castration Resistant PC (CRPC), which is treatment-resistant and frequently gives rise to a highly aggressive variant with features of neuroendocrine differentiation, known as Neuroendocrine PC (NEPC). We used Genetically-Engineered Mouse Models (GEMMs) of CRPC to perform a forward genetic screening using the Sleeping Beauty (SB) transposon system. Specifically, we selected a GEMM with loss of function of both Pten and Trp53, since we previously demonstrated that this model is able to transdifferentiate to NEPC tumors under ADT pressure. Then, we generated a mouse strain in which the SB transposase expression is under the control of a tamoxifen-inducible Cre allele driven by the prostate-specific Nkx3.1 promoter. SB activation generated tumors with an accelerated growth phenotype, when compared to non-activated controls, that present histological features of NEPC. To elucidate these tumors' regulatory program, we harvested SB-barcoded DNA-Seq and RNA-Seq and performed an integrative analysis that links genomic alterations to downstream regulatory programs. Specifically, we used DNA data to recover genes in the proximity of integration patterns generated by SB-transposase random insertions, candidate to be initiator events that fostered the accelerated phenotype and the acquisition of NEPC features. We used RNA-Seq data to identify Master Regulator (MR) proteins responsible of NEPC cell identity. Next, we analyzed molecular data from cohorts of CRPC patients to reverse-engineer both regulatory network of Transcription Factors (TFs) and regulatory dependencies between signaling proteins and TFs activity. This analysis resulted in an NEPC regulatory network of candidate MR proteins and their upstream genomic events, that are likely to be responsible for this treatment-resistant phenotype. Notably, top hits from this analysis are known to be involved in the DNA repair machinery and the WNT pathway, but are not yet associated with lethal prostate cancer. Cross-species computational analysis of patient-specific MRs activity conservation between patients and our mice cohorts, aligned NEPC patients to mice tumors with NE differentiation features, corroborating our study's clinical relevance. In summary, we used in vivo models of prostate cancer to elucidate molecular drivers of NEPC, a lethal variant that is treatment-resistant. We are in the process of validating these results in vitro using the latest CRISPR technology. Citation Format: Alessandro Vasciaveo, Francisca Nunes de Almeida, Min Zou, Matteo Di Bernardo, Andrea Califano, Cory Abate-Shen. Addressing treatment resistance in models of lethal prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2.