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

Deciphering resistance mechanisms in cancer: final report of MATCH-R study with a focus on molecular drivers and PDX development

BACKGROUND

Understanding the resistance mechanisms of tumor is crucial for advancing cancer therapies. The prospective MATCH-R trial (NCT02517892), led by Gustave Roussy, aimed to characterize resistance mechanisms to cancer treatments through molecular analysis of fresh tumor biopsies. This report presents the genomic data analysis of the MATCH-R study conducted from 2015 to 2022 and focuses on targeted therapies.

METHODS

The study included resistant metastatic patients (pts) who accepted an image-guided tumor biopsy. After evaluation of tumor content (TC) in frozen tissue biopsies, targeted NGS (10 < TC < 30%) or Whole Exome Sequencing and RNA sequencing (TC > 30%) were performed before and/or after the anticancer therapy. Patient-derived xenografts (PDX) were established by implanting tumor fragments into NOD scid gamma mice and amplified up to five passages.

RESULTS

A total of 1,120 biopsies were collected from 857 pts with the most frequent tumor types being lung (38.8%), digestive (16.3%) and prostate (14.1%) cancer. Molecular targetable driver were identified in 30.9% (n = 265/857) of the patients, with EGFR (41.5%), FGFR2/3 (15.5%), ALK (11.7%), BRAF (6.8%), and KRAS (5.7%) being the most common altered genes. Furthermore, 66.0% (n = 175/265) had a biopsy at progression on targeted therapy. Among resistant cases, 41.1% (n = 72/175) had no identified molecular mechanism, 32.0% (n = 56/175) showed on-target resistance, and 25.1% (n = 44/175) exhibited a by-pass resistance mechanism. Molecular profiling of the 44 patients with by-pass resistance identified 51 variants, with KRAS (13.7%), PIK3CA (11.8%), PTEN (11.8%), NF2 (7.8%), AKT1 (5.9%), and NF1 (5.9%) being the most altered genes. Treatment was tailored for 45% of the patients with a resistance mechanism identified leading to an 11 months median extension of clinical benefit. A total of 341 biopsies were implanted in mice, successfully establishing 136 PDX models achieving a 39.9% success rate. PDX models are available for EGFR (n = 31), FGFR2/3 (n = 26), KRAS (n = 18), ALK (n = 16), BRAF (n = 6) and NTRK (n = 2) driven cancers. These models closely recapitulate the biology of the original tumors in term of molecular alterations and pharmacological status, and served as valuable models to validate overcoming treatment strategies.

CONCLUSION

The MATCH-R study highlights the feasibility of on purpose image guided tumor biopsies and PDX establishment to characterize resistance mechanisms and guide personalized therapies to improve outcomes in pre-treated metastatic patients.

Genomic and transcriptomic features of androgen receptor signaling inhibitor resistance in metastatic castration-resistant prostate cancer

BACKGROUNDAndrogen receptor signaling inhibitors (ARSIs) have improved outcomes for patients with metastatic castration-resistant prostate cancer (mCRPC), but their clinical benefit is limited by treatment resistance.METHODSTo investigate the mechanisms of ARSI resistance, we analyzed the whole-genome (n = 45) and transcriptome (n = 31) sequencing data generated from paired metastatic biopsies obtained before initiation of first-line ARSI therapy for mCRPC and after radiographic disease progression. We investigated the effects of genetic and pharmacologic modulation of SSTR1 in 22Rv1 cells, a representative mCRPC cell line.RESULTSWe confirmed the predominant role of tumor genetic alterations converging on augmenting androgen receptor (AR) signaling and the increased transcriptional heterogeneity and lineage plasticity during the emergence of ARSI resistance. We further identified amplifications involving a putative enhancer downstream of the AR and transcriptional downregulation of SSTR1, encoding somatostatin receptor 1, in ARSI-resistant tumors. We found that patients with SSTR1-low mCRPC tumors derived less benefit from subsequent ARSI therapy in a retrospective cohort. We showed that SSTR1 was antiproliferative in 22Rv1 cells and that the FDA-approved drug pasireotide suppressed 22Rv1 cell proliferation.CONCLUSIONOur findings expand the knowledge of ARSI resistance and point out actionable next steps, exemplified by potentially targeting SSTR1, to improve patient outcomes.FUNDINGNational Cancer Institute (NCI), NIH; Prostate Cancer Foundation; Conquer Cancer, American Society of Clinical Oncology Foundation; UCSF Benioff Initiative for Prostate Cancer Research; Netherlands Cancer Institute.

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.

Intra-individual Dose Escalation of Abiraterone According to Its Plasma Exposure in Patients with Progressive Metastatic Castration-Resistant Prostate Cancer: Results of the OPTIMABI Trial

BACKGROUND AND OBJECTIVE

Trough abiraterone concentration (ABI Cmin) of 8.4 ng/mL has been identified as an appropriate efficacy threshold in patients treated for metastatic castration-resistant prostate cancer (mCRPC). The aim of the phase II OPTIMABI study was to evaluate the efficacy of pharmacokinetics (PK)-guided dose escalation of abiraterone acetate (AA) in underexposed patients with mCRPC with early tumour progression.

METHODS

This multicentre, non-randomised study consisted of two sequential steps. In step 1, all patients started treatment with 1000 mg of AA once daily. Abiraterone Cmin was measured 22-26 h after the last dose intake each month during the first 12 weeks of treatment. In step 2, underexposed patients (Cmin < 8.4 ng/mL) with tumour progression within the first 6 months of treatment were enrolled and received AA 1000 mg twice daily. The primary endpoint was the rate of non-progression at 12 weeks after the dose doubling. During step 1, adherence to ABI treatment was assessed using the Girerd self-reported questionnaire. A post-hoc analysis of pharmacokinetic (PK) data was conducted using Bayesian estimation of Cmin from samples collected outside the sampling guidelines (22-26 h).

RESULTS

In the intention-to-treat analysis (ITT), 81 patients were included in step 1. In all, 21 (26%) patients were underexposed in step 1, and 8 of them (38%) experienced tumour progression within the first 6 months. A total of 71 patients (88%) completed the Girerd self-reported questionnaire. Of the patients, 62% had a score of 0, and 38% had a score of 1 or 2 (minimal compliance failure), without a significant difference in mean ABI Cmin in the two groups. Four patients were enrolled in step 2, and all reached the exposure target (Cmin > 8.4 ng/mL) after doubling the dose, but none met the primary endpoint. In the post-hoc analysis of PK data, 32 patients (39%) were underexposed, and ABI Cmin was independently associated with worse progression-free survival [hazard ratio (HR) 2.50, 95% confidence interval (CI) 1.07-5.81; p = 0.03], in contrast to the ITT analysis.

CONCLUSION

The ITT and per-protocol analyses showed no statistical association between ABI underexposure and an increased risk of early tumour progression in patients with mCRPC, while the Bayesian estimator showed an association. However, other strategies than dose escalation at the time of progression need to be evaluated. Treatment adherence appeared to be uniformly good in the present study. Finally, the use of a Bayesian approach to recover samples collected outside the predefined blood collection time window could benefit the conduct of clinical trials based on drug monitoring. OPTIMABI trial is registered as National Clinical Trial number NCT03458247, with the EudraCT number 2017-000560-15).

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.