Resistance to androgen-deprivation therapies leads to metastatic castration-resistant prostate cancer (mCRPC) of adenocarcinoma (AdCa) origin that can transform into emergent aggressive variant prostate cancer (AVPC), which has neuroendocrine (NE)-like features. In this work, we used LuCaP patient-derived xenograft (PDX) tumors, clinically relevant models that reflect and retain key features of the tumor from advanced prostate cancer patients. Here we performed proteome and phosphoproteome characterization of 48 LuCaP PDX tumors and identified over 94,000 peptides and 9,700 phosphopeptides corresponding to 7,738 proteins. We compared 15 NE versus 33 AdCa samples, which included six different PDX tumors for each group in biological replicates, and identified 309 unique proteins and 476 unique phosphopeptides that were significantly altered and corresponded to proteins that are known to distinguish these two phenotypes. Assessment of concordance from PDX tumor-matched protein and mRNA revealed increased dissonance in transcriptionally regulated proteins in NE and metabolite interconversion enzymes in AdCa. Implications: Overall, our study highlights the importance of protein-based identification when compared with RNA and provides a rich resource of new and feasible targets for clinical assay development and in understanding the underlying biology of these tumors.

Metastases to the brain are rare in prostate cancer. Here, we describe a patient with two treatment-emergent metastatic lesions, one to the brain with neuroendocrine prostate cancer (NEPC) histology and one to the dural membrane of adenocarcinoma histology. We performed genomic, transcriptomic, and proteomic characterization of these lesions and the primary tumor to investigate molecular features promoting these metastases. The two metastatic lesions had high genomic similarity, including TP53 mutation and PTEN deletion, with the most striking difference being the additional loss of RB1 in the NEPC lesion. Interestingly, the dural lesion expressed both androgen receptor and neuroendocrine markers, suggesting amphicrine carcinoma (AMPC). When analyzing pioneer transcription factors, the AMPC lesion exhibited elevated FOXA1 activity while the brain NEPC lesion showed elevated HOXC10, NFYB, and OTX2 expression suggesting novel roles in NEPC formation or brain tropism. Our results highlight the utility of performing multi-omic characterization, especially in rare cancer subtypes.

Introduction: Prostate cancer treatment has been revolutionized by targeted therapies, including PARP inhibitors, checkpoint immunotherapies, and PSMA-targeted radiotherapies. Despite such advancements, accurate patient stratification remains a challenge, with current methods relying on genomic markers, tissue staining, and imaging. Extracellular vesicle (EV)-derived proteins offer a novel non-invasive alternative for biomarker discovery, holding promise for improving treatment precision. However, the characterization of plasma-derived EVs in prostate cancer patients remains largely unexplored. Methods: We conducted proteomic analyses on EVs isolated from plasma in 27 metastatic castration-resistant prostate cancer (mCRPC) patients. EVs were purified using ultracentrifugation and analyzed via mass spectrometry. Proteomic data were correlated with clinical markers such as serum prostate-specific antigen (PSA) and bone lesion counts. Statistical significance was assessed using Mann–Whitney t-tests and Spearman correlation. Results: The median age of patients was 74 (range: 44–94) years. At the time of blood collection, the median PSA level was 70 (range: 0.5–1000) ng/mL. All patients had bone metastasis. A total of 5213 proteins were detected, including EV-related proteins (CD9, CD81, CD63, FLOT1, TSG101) and cancer-related proteins (PSMA, B7-H3, PD-L1). Proteomic profiling of plasma EVs revealed a significant correlation between specific EV-derived proteins and clinical prognostic markers. B7-H3, LAT1, and SLC29A1 showed a strong association with serum PSA levels and number of bone lesions, indicating potential for these proteins to serve as biomarkers of disease burden and therapy response. Conclusions: Our findings demonstrate the potential of EV-based proteomics for identifying biomarkers in mCRPC patients. Proteins such as B7-H3 and LAT1 could guide precision oncology approaches, improving patient stratification. Future research incorporating outcomes data and EV subpopulation analysis is needed to establish clinical relevance.

Purpose: Germline alterations in homologous recombination repair (gHRR) genes affect the pathogenesis, treatment options, and survival of patients with cancer. However, distinct gHRR gene alterations may differentially affect treatment response and oncogenic signaling. In this study, we interrogated genomic and transcriptomic data and assessed clinical outcomes of patients with gHRR mutations across four BRCA-associated cancers (breast, ovarian, pancreatic, and prostate cancers) to identify therapeutic vulnerabilities. Experimental Design: We assessed 24,309 patients undergoing matched tumor/normal next-generation DNA and RNA sequencing. Annotated gHRR gene variants [germline BRCA1, germline BRCA2, germline PALB2, germline ATM (gATM), and germline CHEK2] were analyzed. HRs were used to assess survival outcomes comparing germline versus sporadic groups. Somatic alterations and their frequencies were compared across gHRR-altered groups. Differential gene expression and gene set enrichment analysis were used to compare transcriptomic profiles. Results: Somatic TP53 mutations were depleted in gATM carriers (P < 0.05) across all four BRCA-associated cancers by up to 2.5-fold. Tumors with germline BRCA1/2 mutations were associated with improved survival in patients with ovarian cancer and had consistent enrichment of TP53 mutations in all four cancers. gATM mutations displayed elevated p53 transcriptional activity in all four cancers, with significance reached in breast and prostate cancers (P < 0.01). In breast, ovarian, and prostate cancers, gATM tumors demonstrated significantly increased inflammatory pathways (P < 0.001). Finally, using gene dependency data, we found that cell lines that were highly dependent on ATM were co-dependent on canonical p53 function. Conclusions: gATM-associated cancers seem to require intact p53 activity and this synthetic essentiality may be used to guide targeted therapies that perturb canonical TP53 function.

Prostate cancer is the most common non‐cutaneous cancer among men in the United States. Most prostate cancers are driven by androgen receptor (AR) signalling, but there are an increasing number of cases that lose AR and gain neuroendocrine (NE) features (AR−/NE+) or lack both (AR−/NE−). These latter subtypes are particularly aggressive and lethal. Extracellular vesicles (EVs) have shown great potential as biomarkers for non‐invasive liquid biopsy assays, as EVs contain biomolecules from their cells of origin. Here, we used a shotgun proteomics approach with mass spectrometry to interrogate the global proteome of EVs isolated from prostate cancer cell lines reflecting diverse clinical subtypes, including AR−/NE+ and AR−/NE− models. We identified 3952 EV proteins, which clustered largely by tumour subtype and provided enough proteomic coverage to derive classic gene signatures of AR or NE identity that are of high relevance for prostate cancer prognostication. EVs isolated from AR+ cells displayed high levels of proteins regulated by AR and mTOR signalling. EVs isolated from AR−/NE+ cells contained known NE markers such as SYP and CHGA, whereas EVs from AR−/NE− models were enriched in basal cell markers and proteins that regulate epithelial‐to‐mesenchymal transition (EMT). We integrated our cell line data with recently published EV proteomics data from 27 advanced prostate cancer patients and found 2733 overlapping proteins, including cell surface markers relevant to prostate cancer, AR activity indicators, and proteins enriched in specific subtypes (AR+, AR−/NE−, AR−/NE+). This approach may be useful for rare cancer subtypes, such as prostate cancers that lose AR‐related features and gain NE features, to optimise the use of these liquid biopsy samples for clinical decision making.

Prostate cancer is the most common non-cutaneous cancer among men in the United States. Most prostate cancers are driven by androgen receptor (AR) signaling, but there are an increasing number of cases that lose AR and gain neuroendocrine (NE) features (AR−/NE+) or lack both (AR−/NE−). These latter subtypes are particularly aggressive and lethal. Extracellular vesicles (EVs) have shown great potential as biomarkers for noninvasive liquid biopsy assays, as EVs contain biomolecules from their cells of origin. Here, we used a shotgun proteomics approach with mass spectrometry to interrogate the global proteome of EVs isolated from prostate cancer cell lines reflecting diverse clinical subtypes, including AR−/NE+ and AR−/NE−models. We identified 3,952 EV proteins, which clustered largely by tumor subtype and provided enough proteomic coverage to derive classic gene signatures of AR or NE identity that are of high relevance for prostate cancer prognostication. EVs isolated from AR+ cells displayed high levels of proteins regulated by AR and mTOR signaling. EVs isolated from AR−/NE+ cells contained known NE markers such as SYP and CHGA, whereas EVs from AR−/NE−models were enriched in basal cell markers and proteins that regulate epithelial-to-mesenchymal transition (EMT). We integrated our cell line data with recently published EV proteomics data from 27 advanced prostate cancer patients and found 2,733 overlapping proteins including cell surface markers relevant to prostate cancer, AR activity indicators, and proteins enriched in specific subtypes (AR+, AR−/NE−, AR−/NE+). This approach is especially promising for rare cancer subtypes, such as prostate cancers that lose AR− related features and gain NE features, so as to optimize the use of these liquid biopsy samples for clinical decision making.