Submitted:
03 March 2025
Posted:
04 March 2025
You are already at the latest version
Abstract
Metastatic prostate cancer (mPCa) remains a significant global health concern and cause of cancer-related mortality in men. Advances in molecular profiling have illuminated the critical drivers of disease progression and therapeutic resistance, notably within the androgen receptor (AR) axis, DNA damage repair (DDR) pathways, and PI3K/AKT/mTOR network. Despite the established benefits of hormone therapy, chemotherapy, and bone-targeting agents, mPCa commonly evolves into a treatment-resistant state, typified by intrapatient heterogeneity and clonal evolution. Recent breakthroughs have highlighted the importance of identifying actionable genetic alterations such as BRCA2 or ATM defects that render tumors sensitive to poly-ADP ribose polymerase (PARP) inhibitors. Parallel efforts have refined imaging—particularly prostate-specific membrane antigen (PSMA) PET-CT—to detect and localize metastatic lesions with high sensitivity, thereby guiding patient selection for PSMA-targeted radioligand therapies (177Lu-PSMA, 225Ac-PSMA). Multi-omics innovations, including liquid biopsy technologies, enable real-time tracking of emergent AR splice variants (e.g., AR-V7) or reversion mutations, supporting adaptive therapy paradigms. Nonetheless, the complexity of mPCa necessitates combination strategies—for example, pairing AR inhibition with PI3K/AKT blockade or PARP inhibitors—to intercept tumor plasticity. Immuno-oncology approaches remain challenging in unselected patients; however, subsets with mismatch repair deficiency (MSI-high) or neuroendocrine phenotypes may benefit from immune checkpoint blockade or targeted epigenetic interventions. We present these pivotal advances and discuss how biomarker-guided integrative treatments can improve the management of mPCa.
Keywords:
1. Introduction
2. Molecular Pathophysiology of Metastatic Prostate Cancer
2.1. Centrality of the Androgen Receptor (AR) Axis
2.1.1. Historical Underpinnings and Core AR Functions
2.1.2. Routes to AR Reactivation Under Therapeutic Pressure
2.2. PARP Inhibitors and the Synthetic Lethality Paradigm (Molecular Pathophysiology Focus)
2.2.1. Historical Context and Foundational Insights
2.2.2. Core Molecular Mechanisms in Prostate Cancer
2.2.3. Adaptive and Resistance Mechanisms
2.2.4. Research Methodologies and Knowledge Gaps
2.2.5. Forward-Looking Perspectives in Molecular Pathophysiology
2.3. TMPRSS2-ERG Fusions and Oncogenic Transcription Factors (Molecular Pathophysiology Focus)
2.3.1. Historical to Current Understanding
2.3.2. Mechanistic Insights
2.3.3. Methodological Limitations
2.3.4. Clinical or Scientific Significance
2.3.5. Comparisons, Divergent Findings, and Future Outlook
2.4. PTEN Loss, PI3K/AKT/mTOR Hyperactivation, and Crosstalk with AR (Molecular Pathophysiology Focus)
2.4.1. Historical to Current Perspective
2.4.2. Mechanistic Insights
2.4.3. Methodological Constraints
2.4.4. Clinical or Scientific Significance
2.4.5. Contrasting Evidence and Future Directions
2.5. Tumor Heterogeneity, Clonal Evolution, and Lineage Plasticity
2.5.1. Historical to Current Understanding
2.5.2. Mechanistic Insights on Clonal Dynamics


2.5.3. Methodological Constraints
2.5.4. Clinical or Scientific Significance
2.5.5. Comparisons and Divergent Data
2.5.6. Future Outlook
2.6. Tumor Microenvironment (TME) and Immune Dynamics (Molecular Pathophysiology Focus)
2.6.1. Historical to Current Understanding
2.6.2. Mechanistic Insights
2.6.3. Methodological Constraints
2.6.4. Clinical or Scientific Significance
2.6.5. Comparisons and Divergent Data
2.6.6. Future Outlook
3. Molecular Stratification and Diagnostic Advances
3.1. High-Resolution Molecular Profiling
3.2. Companion Diagnostics and Gene Panels
3.2.1. DDR-Focused Panels for PARP Inhibitor Selection
3.2.2. AR Variant Detection and PTEN/PI3K Panels
3.3. Advanced Imaging: PSMA PET-CT and Beyond
3.4. Liquid Biopsies in Metastatic Prostate Cancer
3.4.1. Historical Context and Technological Evolution
3.4.2. Methodological Approaches and Clinical Relevance
3.4.3. Critical Assessment and Significance
3.4.4. Methodological Challenges
3.4.5. Future Outlook
4. Targeted Therapeutic Approaches
4.1. AR Axis–Centric Treatments
4.2. DDR-Defect–Based Therapies: PARP Inhibitors and Beyond
4.3. Targeting PI3K/AKT/mTOR and WNT Pathways
4.4. Immuno-Oncology Approaches
4.5. PSMA-Targeted Radioligand Therapy
5. Conclusion and Future Perspectives
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
| mPCa | metastatic prostate cancer |
| AR | androgen receptor |
| DDR | DNA damage repair |
| PARP | poly-ADP ribose polymerase |
| PSMA | prostate-specific membrane antigen |
| PCa | prostate cancer |
| mCRPC | metastatic castration-resistant prostate cancer |
| TME | tumor microenvironment |
| NGS | next-generation sequencing |
| ADT | androgen deprivation therapy |
| DHT | testosterone–dihydrotestosterone |
| NTD | N-terminal transactivation domain |
| DBD | DNA-binding domain |
| LBD | ligand-binding domain |
| ARE | androgen response element |
| CRISPR | clustered regularly interspaced short palindromic repeats |
| PROTAC | proteolysis-targeting chimera |
| CAR-T | chimeric antigen receptor T |
| HR | homologous recombination |
| DSB | double-strand break |
| NHEJ | non-homologous end joining |
| EMT | epithelial–mesenchymal transition |
| PIP3 | phosphatidylinositol (3,4,5)-trisphosphate |
| t-NEPC | treatment-induced neuroendocrine prostate cancer |
| ctDNA | circulating tumor DNA |
| MDSC | myeloid-derived suppressor cell |
| TAM | tumor-associated macrophage |
| Treg | regulatory T cell |
| WES/WGS | whole-exome/genome sequencing |
| FAP | fibroblast activation protein |
| CTC | circulating tumor cell |
| cfDNA | cell-free DNA |
| t-NEPC | treatment-emergent neuroendocrine prostate cancer |
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| Molecular Target or Genetic Alteration | Key Mechanism/Function | Clinical Features | Clinical Utility |
| AR Amplification / AR Splice Variants (e.g., AR-V7) | Sustained AR signaling under low-androgen conditions; ligand-independent activation | Poor response or resistance to AR-targeted therapies; commonly seen in mCRPC | Predicts resistance to enzalutamide or abiraterone; potential biomarker for treatment selection |
| PTEN Loss | Hyperactivation of the PI3K/AKT/mTOR pathway; cross-talk with AR signaling | Associated with high-grade tumors and aggressive clinical course | May guide PI3K/AKT/mTOR inhibitor-based combination trials; potential prognostic indicator |
| DDR Defects (e.g., BRCA2, ATM) | Impaired DNA repair and increased genomic instability; vulnerability to PARP inhibition | More aggressive behavior if untreated; better response to PARP inhibitors | Companion diagnostics for PARP inhibitors; synthetic lethality-based therapy targeting |
| TMPRSS2-ERG Fusion | ETS transcription factor (ERG) overexpression; promotes invasion, EMT, and genomic instability | High prevalence in localized prostate cancer; variable association with outcomes in mPCa | Potential prognostic marker in combination with other alterations (e.g., PTEN) |
| PI3K/AKT/mTOR Mutations | Aberrant cell proliferation and survival; metabolic reprogramming | Often co-occurs with AR pathway alterations; contributes to therapeutic resistance | Under investigation in clinical trials targeting AKT and mTOR; potential combination strategy with AR inhibitors |
| TP53 / RB1 Co-mutations | Disruption of cell-cycle checkpoints; may facilitate lineage plasticity or neuroendocrine differentiation | Common in advanced mPCa; associated with poor prognosis | Emerging biomarker for early switch to chemotherapy or combination therapies |
| Diagnostic Panel/Biomarker | Testing Method | Clinical Significance | Limitations/Considerations |
| DDR-Focused Panel (BRCA1/2, ATM, etc.) | - Targeted NGS or expanded gene panels - Germline vs. somatic testing |
- Identifies candidates for PARP inhibitors and platinum-based therapies - May inform familial genetic risk |
- Cost and limited access in some regions - May miss epigenetic alterations |
| AR Splice Variants (e.g., AR-V7) | - RT-PCR or ddPCR on CTCs - Tissue-based RNA assays |
- Predicts resistance to enzalutamide or abiraterone - Can guide switch to chemotherapy or other targeted agents |
- Variable sensitivity depending on assay - Not yet universally available or standardized |
| PTEN / PI3K / AKT | - IHC, FISH - Targeted sequencing for hotspot mutations |
- Potential biomarker for AKT/mTOR inhibitors - May correlate with disease aggressiveness |
- Limited predictive validation in some trials - Reimbursement issues in certain regions |
| TP53 / RB1 | - Targeted NGS or WES/WGS - IHC for protein loss |
- Associated with poor prognosis - May indicate early progression toward neuroendocrine differentiation |
- Rarely used in routine practice - Data interpretation can be complex (co-occurring events) |
| TMPRSS2-ERG Fusion | - FISH, RT-PCR, or RNA-seq | - Possible prognostic marker when combined with other aberrations (e.g., PTEN) | - Prognostic impact remains debated - May not be actionable with current therapies |
| Modality | Specimen Characteristics | Analytical Techniques | Clinical Applications | Advantages | Limitations |
| ctDNA | - Cell-free DNA fragments shed by tumor cells - Detected in plasma or serum |
- Targeted/Whole-Exome NGS - ddPCR |
- Real-time monitoring of tumor burden - Detection of actionable mutations (e.g., BRCA2) |
- Minimally invasive - Repeat sampling feasible - Reflects genomic heterogeneity |
- Low abundance in early disease - Sensitivity depends on tumor fraction - Assay costs and standardization issues |
| CTCs | - Intact, viable tumor cells in the bloodstream - May be enriched via immunomagnetic or size-based separation methods |
- Immunophenotyping - Single-cell genomics/transcriptomics |
- Prognostic biomarker (CTC count) - AR-V7 status for therapy guidance - Potential ex vivo drug testing |
- Allows morphological and molecular analyses - Provides insight into specific cell populations |
- Rare cells, labor-intensive- Limited sensitivity in low-volume disease - Heterogeneity among different CTC populations |
| Exosomes and Extracellular Vesicles | - Nano-scale vesicles containing proteins, RNA, and DNA - Released by tumor and stromal cells into bodily fluids |
- RNA-seq, proteomics - Nanoparticle tracking - Advanced mass spectrometry |
- May reveal early resistance signatures - Potential biomarkers for immune- and stromal interactions |
- Reflects active secretory pathways - Can capture tumor–stromal communication |
- Isolation protocols not standardized - Complexity of vesicle subtypes - Data interpretation is challenging |
| Treatment or Combination | Primary Target/Mechanism | Trial Phase | Patient Population | Key Outcomes | Current Status | Reference |
| Olaparib vs. Abiraterone/Enzalutamide (PROfound) | PARP inhibition (DDR deficiency) | Phase III | mCRPC with HRR gene alterations (e.g., BRCA1/2) | Improved radiographic PFS and OS in biomarker-selected patients | Approved for HRR-mutated mCRPC | [171] |
| Ipatasertib + Abiraterone (IPATential150) | AKT inhibitor + AR axis blockade | Phase III | mCRPC, particularly with PTEN loss | Prolonged PFS in the PTEN-loss subgroup | Ongoing or completed; subset analyses continuing | [148] |
| 177Lu-PSMA-617 + Standard of Care (VISION) | PSMA-targeted radioligand therapy | Phase III | Heavily pretreated mCRPC | Improved OS and PFS vs. standard care | Approved in multiple regions | [172] |
| Nivolumab + Ipilimumab (CheckMate 650) | Dual immune checkpoint blockade (PD-1, CTLA-4) | Phase II | mCRPC, previously treated | Moderate objective response; significant immune-related toxicity | Further refinement of combination strategies needed | [173] |
| Pembrolizumab (KEYNOTE-199) | PD-1 immune checkpoint blockade | Phase II | mCRPC with prior treatments | Modest response rates; better outcomes in MSI-H or DNA repair defects | Investigational in selected biomarker-defined subgroups | [174] |
| Apalutamide (SPARTAN) | Next-generation AR antagonist | Phase III | nmCRPC (non-metastatic CRPC) | Significantly improved metastasis-free survival (MFS) | Approved for nmCRPC | [175] |
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