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Record W4281784436 · doi:10.1016/j.ijrobp.2022.05.037

Tumor-Derived Extracellular Vesicles Predict Clinical Outcomes in Oligometastatic Prostate Cancer and Suppress Antitumor Immunity

2022· article· en· W4281784436 on OpenAlexfundno aff
Fabrice Lucien, Yohan Kim, Jing Qian, Jacob J. Orme, Henan Zhang, Ali Arafa, Feven Abraha, Ishwor Thapa, E. Tryggestad, William S. Harmsen, Jorgena Kosti, Hesham Ali, Val J. Lowe, Geoffrey B. Johnson, Eugene D. Kwon, Haidong Dong, Sean S. Park

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsnot available
FundersNational Cancer InstituteFonds de Recherche du Québec - SantéAdvanced Accelerator ApplicationsNovartis
KeywordsSABR volatility modelProstate cancerMedicineOncologyInternal medicineCancerProstateUrology

Abstract

fetched live from OpenAlex

Purpose SABR has demonstrated clinical benefit in oligometastatic prostate cancer. However, the risk of developing new distant metastatic lesions remains high, and only a minority of patients experience durable progression-free response. Therefore, there is a critical need to identify which patients will benefit from SABR alone versus combination SABR and systemic agents. Herein we provide, to our knowledge, the first proof-of-concept of circulating prostate cancer-specific extracellular vesicles (PCEVs) as a noninvasive predictor of outcomes in oligometastatic castration-resistant prostate cancer (omCRPC) treated with SABR. Methods and Materials We analyzed the levels and kinetics of PCEVs in the peripheral blood of 79 patients with omCRPC at baseline and days 1, 7, and 14 after SABR using nanoscale flow cytometry and compared with baseline values from cohorts with localized and widely metastatic prostate cancer. The association of omCRPC PCEV levels with oncological outcomes was determined with Cox regression models. Results Levels of PCEVs were highest in mCRPC followed by omCRPC and were lowest in localized prostate cancer. High PCEV levels at baseline predicted a shorter median time to distant recurrence (3.5 vs 6.6 months; P = .0087). After SABR, PCEV levels peaked on day 7, and median overall survival was significantly longer in patients with elevated PCEV levels (32.7 vs 27.6 months; P = .003). This suggests that pretreatment PCEV levels reflect tumor burden, whereas early changes in PCEV levels after treatment predict response to SABR. In contrast, radiomic features of 11 C-choline positron emission tomography and computed tomography before and after SABR were not predictive of clinical outcomes. Interestingly, PCEV levels and peripheral tumor-reactive CD8 T cells (T TR ; CD8 + CD11a high ) were correlated. Conclusions This original study demonstrates that circulating PCEVs can serve as prognostic and predictive markers to SABR to identify patients with "true" omCRPC. In addition, it provides novel insights into the global crosstalk, mediated by PCEVs, between tumors and immune cells that leads to systemic suppression of immunity against CRPC. This work lays the foundation for future studies to investigate the underpinnings of metastatic progression and provide new therapeutic targets (eg, PCEVs) to improve SABR efficacy and clinical outcomes in treatment-resistant CRPC.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.342
Teacher spread0.322 · 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 source (direct Gemma or distilled Codex), 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

Citations23
Published2022
Admission routes1
Has abstractno

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