Genomic Profiling of Metastatic Castration-Resistant Prostate Cancer Samples Resistant to Androgen Receptor Pathway Inhibitors

Reproducible preclinical models of androgen receptor driven human prostate cancer bone metastasis

BACKGROUND

Preclinical models recapitulating the metastatic phenotypes are essential for developing the next-generation therapies for metastatic prostate cancer (mPC). We aimed to establish a cohort of clinically relevant mPC models, particularly androgen receptor positive (AR+) bone metastasis models, from LuCaP patient-derived xenografts (PDX) that reflect the heterogeneity and complexity of mPC.

METHODS

PDX tumors were dissociated into single cells, modified to express luciferase, and were inoculated into NSG mice via intracardiac injection. The progression of metastases was monitored by bioluminescent imaging. Histological phenotypes of metastases were characterized by immunohistochemistry and immunofluorescence staining. Castration responses were further investigated in two AR-positive models.

RESULTS

Our PDX-derived metastasis (PDM) model collection comprises three AR+ adenocarcinomas (ARPC) and one AR- neuroendocrine carcinoma (NEPC). All ARPC models developed bone metastases with either an osteoblastic, osteolytic, or mixed phenotype, while the NEPC model mainly developed brain metastasis. Different mechanisms of castration resistance were observed in two AR+ PDM models with distinct genotypes, such as combined loss of TP53 and RB1 in one model and expression of AR splice variant 7 (AR-V7) expression in another model. Intriguingly, the castration-resistant tumors displayed inter- and intra-tumor as well as organ-specific heterogeneity in lineage specification.

CONCLUSION

Genetically diverse PDM models provide a clinically relevant system for biomarker identification and personalized medicine in metastatic castration-resistant prostate cancer.

The interplay between autophagy and ferroptosis presents a novel conceptual therapeutic framework for neuroendocrine prostate cancer

In American men, the incidence of prostate cancer (PC) is the highest among all types of cancer, making it the second leading cause of mortality associated with cancer. For advanced or metastatic PC, antiandrogen therapies are standard treatment options. The administration of these treatments unfortunately carries the potential risk of inducing neuroendocrine prostate cancer (NEPC). Neuroendocrine differentiation (NED) serves as a crucial indicator of prostate cancer development, encompassing various factors such as phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR), Yes-associated protein 1 (YAP1), AMP-activated protein kinase (AMPK), miRNA. The processes of autophagy and ferroptosis (an iron-dependent form of programmed cell death) play pivotal roles in the regulation of various types of cancers. Clinical trials and preclinical investigations have been conducted on many signaling pathways during the development of NEPC, with the deepening of research, autophagy and ferroptosis appear to be the potential target for regulating NEPC. Due to the dual nature of autophagy and ferroptosis in cancer, gaining a deeper understanding of the developmental programs associated with achieving autophagy and ferroptosis may enhance risk stratification and treatment efficacy for patients with NEPC.

Identification of Molecular Markers Associated with Prostate Cancer Subtypes: An Integrative Bioinformatics Approach

Prostate cancer (PCa) is characterised by androgen dependency. Unfortunately, under anti-androgen treatment pressure, castration-resistant prostate cancer (CRPC) emerges, characterised by heterogeneous cell populations that, over time, lead to the development of different androgen-dependent or -independent phenotypes. Despite important advances in therapeutic strategies, CRPC remains incurable. Context-specific essential genes represent valuable candidates for targeted anti-cancer therapies. Through the investigation of gene and protein annotations and the integration of published transcriptomic data, we identified two consensus lists to stratify PCa patients' risk and discriminate CRPC phenotypes based on androgen receptor activity. ROC and Kaplan-Meier survival analyses were used for gene set validation in independent datasets. We further evaluated these genes for their association with cancer dependency. The deregulated expression of the PCa-related genes was associated with overall and disease-specific survival, metastasis and/or high recurrence risk, while the CRPC-related genes clearly discriminated between adeno and neuroendocrine phenotypes. Some of the genes showed context-specific essentiality. We further identified candidate drugs through a computational repositioning approach for targeting these genes and treating lethal variants of PCa. This work provides a proof-of-concept for the use of an integrative approach to identify candidate biomarkers involved in PCa progression and CRPC pathogenesis within the goal of precision medicine.

Genomic Portraits: Reflections into a Tumor's Response to Therapy

Well-annotated matched tissue specimens both before and after initiation of androgen receptor signaling inhibitors (ARSI) have revealed activation of unique signaling pathways and genomic signatures that identify a profile to guide therapy. A recent study represents the largest prospective biospecimen banking protocol to study mechanisms of resistance to ARSIs. See related article by Menssouri et al., p. 4504.