Abstract 5736: In silico analysis shows that PTEN loss and AR overexpression are associated with increased CD8+ T-cell and Treg density and earlier disease recurrence in prostate cancer
Bibliographic record
Abstract
Abstract PTEN loss occurs in 20-30% prostate cancers (PCa), is associated with worse outcome, and regulates the type I interferon response through the interferon regulatory factor 3 (IRF3). Both PTEN loss and the overexpression of the androgen receptor (AR) promote castrate-resistant PCa leading to a more aggressive disease. To characterize the associations between PTEN loss and AR expression in immune cell infiltration in the tumor microenvironment (TME), we conducted an in silico analysis in two PCa cohorts. RNAseq and gene expression array data were imputed in CIBERSORT to evaluate the relative frequency of 22 immune infiltrating cells in the TME. PTEN was lost in 19.7% (97/491) and 19.8% (26/131) in the TCGA and MSKCC cohorts, respectively. AR was overexpressed in 56% (279/491) and 54% (71/131) of the TCGA and MSKCC cohorts, respectively. Remarkably, AR overexpression was associated with decreased CD8+ T-cells infiltration in both the TCGA (p<0.0001) and MSKCC (p=0.001) cohorts. In addition we found that PTEN loss was associated with increased Treg infiltration in both the TCGA (p=0.002) and MSKCC (p<0.0001) cohorts. PTEN loss was also associated with low plasma cell infiltration in both the TCGA and MSKCC cohorts (p=0.001 and p=0.002, respectively). More detailed analysis of the MSKCC cohort showed that PTEN loss correlated with increased CD8+ T-cell density in the TME (p<0.0001). When we compared the immune cell infiltration profile from the primary and metastatic tumors in the MSKCC cohort, we found an increased infiltration of memory B-cell, Treg, and active dendritic cells (p<0.0001, p=0.005, and p=0.002, respectively) in the metastatic tumors. We then investigated the association between PTEN and AR expression with the most common immunotherapeutic targets. We found that PTEN loss was associated with increased PD-1 expression in MSKCC cohort (p<0.0001) and with reduced PD-L1 expression in the TCGA cohort (p=0.006). Increased AR expression correlated with reduced PD-1 expression in both TCGA and MSKCC cohorts (p<0.0001) and with reduced CTLA-4 expression in TCGA cohort (p=0.009). There was a positive association between PD-1 and CTLA-4 expression with CD8+ T-cell and Treg infiltration in both cohorts. Log-rank analysis showed that PTEN loss and high Treg infiltration predicted earlier disease recurrence in both the TCGA and MSKCC cohorts (p=0.021 and p=0.027, respectively). In addition, combined PTEN loss and increased CD8+ T-cell infiltration promotes earlier disease recurrence in both the TCGA and MSKCC cohorts (p=0.05 and p=0.029, respectively). These findings imply that the immune cell profile in the TME can be influenced by changes in the expression of PTEN and AR, suggesting that novel immunotherapies may promote better responses in castrate-resistant PCa. Citation Format: Thiago Vidotto, Madhuri Koti, Jeremy A. Squire. In silico analysis shows that PTEN loss and AR overexpression are associated with increased CD8+ T-cell and Treg density and earlier disease recurrence in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5736.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.007 | 0.001 |
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".