Abstract 6962: Shed Trop2 drives prostate cancer progression and Trop2 is a novel tissue prognostic biomarker and a candidate urinary marker for prostate cancer
Bibliographic record
Abstract
Abstract Distinguishing indolent from clinically significant localized prostate cancer and treatment of metastatic prostate cancer are two major clinical challenges in prostate cancer. The development of novel predictive biomarkers will help with risk stratification, and influence clinical decision-making between treatment and active surveillance, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2, an oncogenic transmembrane surface protein, is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that higher Trop2 expression is correlated with worse clinical features and elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detected shed Trop2 in urine from men with clinically significant prostate cancer. We further define the functional role of shed Trop2 on metastasis in prostate cancer and identify that shed Trop2 increases cell migration, invasion, metastatic colonization, and spontaneous metastasis in vitro and in vivo. Proteomic profiling reveals that shed Trop2 modulates a set of proteins associated with invasion, migration, mTOR signaling, and epithelial-to-mesenchymal transition. shed Trop2 binds to EGFR and results in the activation of the EGFR-PI3K-AKT-mTOR pathway in prostate cancer. Our study reveals the new function of shed Trop2 in driving prostate cancer progression and identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer that could be used to optimize treatment decision-making. Citation Format: Shiqin Liu, Sarah Hawley, Christian Kunder, En-Chi Hsu, Michelle Shen, Merve Aslan, Fernando J. Marques, Chung S. Lee, Abel Bermudez, Lennart Westphalen, Heidi Auman, Lisa F. Newcomb, Daniel W. Lin, Peter S. Nelson, Ziding Feng, Maria S. Tretiakova, Lawrence D. True, Funda Vakar-Lopez, Peter R. Carroll, Jeffry Simko, Martin E. Gleave, Dean A. Troyer, Jesse K. McKenney, Donna Peehl, Sharon J. Pitteri, James D. Brooks, Michael A. Liss, Tanya Stoyanova. Shed Trop2 drives prostate cancer progression and Trop2 is a novel tissue prognostic biomarker and a candidate urinary marker for prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6962.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".