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March 4, 2026Journal of Clinical Oncology0 citations

Multi-omics profiling of residual cancer burden after neoadjuvant hormonal therapy guides subtype-directed treatment in high-risk and locally advanced prostate cancer.

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YCYi CaiGTGuyu TangXGXiaomei Gao

Key Points

  • The study aims to identify molecular subtypes of residual cancer after hormonal therapy and to create a treatment framework for high-risk prostate cancer.
  • Integrated profiling of genomic, transcriptomic, proteomic, and N-glycoproteomic data from 138 cases.
  • Development of a molecular classification model using ssGSEA.
  • Creation of an IHC-based stratification scheme for clinical application.
  • Establishment of patient-derived organoids for each molecular subtype and validation of drug sensitivity against these subtypes.
  • Three molecular subtypes (C1, C2, C3) were identified with differing prognoses and pathways involved.
  • Key biomarkers were identified for each subtype (e.g., CANT1 and MRE11 for C1).
  • A consistent IHC-based classification was validated with high Cohen's Kappa values.
  • Therapeutic potentials were established for BET inhibitors targeting C1 and JAK inhibitors targeting C2.

Abstract

245 Background: Residual cancer burden (RCB) in patients failing to achieve pathological complete response (non-pCR) after neoadjuvant hormonal therapy (NHT) are a major cause of recurrence for high-risk localized and locally advanced prostate cancer (HRLPC). This study aimed to identify molecular subtypes of residual cancer and develop a precision framework to guide treatment of HRLPC. Methods: We performed integrated genomic, transcriptomic, proteomic, and N-glycoproteomic profiling of residual cancers from 138 HRLPC cases treated 3-6 months of ADT+ARPIs NHT. A molecular ssGSEA classification model was developed and translated into a clinically applicable immunohistochemistry (IHC)-based stratification scheme. Patient-derived organoids (PDOs) representing each molecular subtype were established and characterized, followed by drug sensitivity assays to validate potential therapeutic targets. Results: Three subtypes were characterized: C1 (AR and MYC signaling activation, poorest prognosis), C2 (upregulation of JAK-STAT pathway and high sialylation), and C3 (intermediate). A proteomic molecular classification model based on ssGSEA was constructed. Key biomarkers (CANT1, MRE11 for C1; CD8A, GSDME for C2) were identified, and developed an IHC-based classification strategy. The consistency between the ssGSEA and IHC model was validated (retrospective: Cohen’s Kappa = 0.719; prospective: Cohen’s Kappa = 0.747). PDOs representing C1–C3 subtypes were established for target prediction and drug validation, revealing the therapeutic potential of BETi for C1 and JAKi for C2. Conclusions: This study comprehensively elucidated the molecular characteristics of RCB in HRLPC after NHT, established a clinically translatable classification system, and proposed subtype-guided precision therapeutic strategies.

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Cite This Study

Cai et al. (2026) studied this question.

synapsesocial.com/papers/69a7cd8cd48f933b5eeda085https://doi.org/10.1200/jco.2026.44.7_suppl.245
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