MétaCan
Menu
Back to cohort

Abstract PR-02: Loss of tumor-intrinsic type I IFN facilitates and predicts bone-metastatic progression in advanced prostate cancer and drives radiotherapeutic resistance

2025· article· en· W4414465977 on OpenAlexaboutno aff
Katie L. Owen, Linden J. Gearing, Christopher M. Hovens, Shahneen Sandhu, Michael S. Hofman, Belinda S. Parker, Luc Furic

Bibliographic record

VenueCancer Immunology Research · 2025
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsProstate cancerBone metastasisMetastasisImmunotherapyTumor microenvironmentLymph nodeCancer

Abstract

fetched live from OpenAlex

Abstract Background: Bone metastases occur in up to 90% of men with castration-resistant prostate cancer (CRPC) and are invariably fatal. A "cold" tumor microenvironment has been implicated in the failure of conventional and targeted therapies to improve long-term survival in metastatic disease. Yet, studies interrogating the bone metastatic niche for candidate drivers of therapeutic resistance are lacking, as are real-world strategies to advance precision approaches that reduce patient mortality. Here we define explicit and previously undisclosed features of the tumor-immune landscape that shape CRPC progression to bone and reveal key predictors of resistance to radioligand therapy (RLT). Methods: We performed in-depth single cell and digital spatial profiling linked to transcriptomic analysis of >230 prostate cancer patients from 6 independent cohorts spanning >100 tissues and PDX from adenocarcinomas (non-metastatic and metastatic) to lymph node (LN) and bone metastases, with >32 matched tumors. Results: Bone metastases show a significant site-specific loss of type I interferon (IFN-I) signaling and antigen presentation markers (HLA-I) compared to LN and primary tumors. Tumor-intrinsic (TI) IFN-I signaling is predictive of bone metastasis (HR=0.92, p=0.04) while tumor cell HLA-I is predictive of bone metastasis-free survival (HR=0.97, p=0.03) and biochemical recurrence (HR=0.97, p=0.009). Bone metastasis is correlated with robust suppression of both TI IFN-I signaling and HLA-I (r=0.79, p<0.0001) compared to metastatic and non-metastatic primaries. Metastasis is associated with increased Treg, while tumor-excluded memory T cells are only predictive of better bone metastasis-free survival when active TI IFN-I is intact. A bone-specific enrichment of tumor-infiltrating M2 macrophages is observed yet is not prognostic. Similarly, a bone-specific loss of HLA-II and dendritic cell activation is evidenced yet holds no predictive value. Notably, we identified a bone-specific loss of >15 IFN-I regulated druggable targets compared to matched adenocarcinomas concurrent to a bone-specific TI increase in B7-H3, validated in PDX and 3 independent cohorts. Systemic immune analysis in men receiving PSMA-targeted RLT reveal that radiographic progression in CRPC can be predicted by IFN-I driven antigen presentation markers in novel immune subsets as early as cycle 2 of treatment. Conclusion: We reveal the first in-depth profiling of the bone metastatic landscape in CRPC and identify TI IFN-I biomarkers as superior to the quantitation and characterization of tumor infiltrating immune cells to predict risk of bone metastasis. Our findings suggest the loss of tumor immunogenicity in CRPC is a critical mediator of bone-specific progression, drives therapeutic resistance and underpins response to targeted RLT. Here, we highlight the utility of TI IFN-I markers to predict CRPC progression to bone and discuss novel points of intervention to limit autoimmune responses to RLT and IFN-activating therapies that may improve survival for men with a lethal stage of disease. Citation Format: Katie L. Owen, Linden J. Gearing, Chris Hovens, Shahneen Sandhu, Michael Hofman, Belinda S. Parker, Luc Furic. Loss of tumor-intrinsic type I IFN facilitates and predicts bone-metastatic progression in advanced prostate cancer and drives radiotherapeutic resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr PR-02.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.409
Teacher spread0.374 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCancer Immunology ResearchSame topicProstate Cancer Treatment and ResearchFrench-language works237,207