Abstract LB065: Prostate cancer molecular immunophenotypes in biopsies with high vs average radiation sensitivity as predicted by post-operative radiation therapy outcomes (PORTOS) scores
Bibliographic record
Abstract
Abstract Background: The combination of radiation therapy and immunotherapy has emerged as an exciting field of research with the potential for significant clinical benefit. Using pre-treatment prostate biopsies from two clinical trials we explored the hypothesis that a validated gene expression signature of postoperative radiation therapy outcome score (PORTOS) is associated with differences in tumor molecular immunophenotype. In this study, we compared prostate tumors with high vs average PORTOS scores for expression of 32 molecular immunophenoscores that reflect cancer antigen profiles and the cellular composition of tumor infiltrating lymphocytes. Methods: Gene expression profiles were obtained from microdissected tumor tissue from 242 treatment naïve-prostate biopsy cores obtained from 92 patients enrolled in the University of Miami MAST (NCT02242773) and BLaStM (NCT02307058) clinical trials. For each biopsy the PORTOS score (PMID: 27743920) and 32 tumor molecular immunophenoscores (PMID: 28052254) were determined from Affymetrix Human Exon 1.0 ST microarray data using published methods. Results: 14% of the biopsy cores were predicted by the PORTOS signature to be more responsive to radiation therapy. Compared to the cores with average PORTOS scores, the “high PORTOS” biopsies showed a 2 fold or greater level of the tumor immunoactivation markers Act CD4, Act CD8, EC, HLA DPA1 and Tem CD8 and a 2 fold or lower level of the tumor immunosuppression markers MDSC, SC, TIM3 and T reg (Mann-Whitney P value of <0.0001 for all nine comparisons of medians). Discussion: Preliminary studies suggest that prostate cancers with PORTOS scores that predict greater sensitivity to radiation therapy also have immunophenotype profiles consistent with a higher level of overall immunogenicity. Citation Format: Sandra M. Gaston, Sanoj Punnen, Oleksandr Kryvenko, Alan Pollack, Elai Davicioni, Seagle Liu, Radka Stoyanova. Prostate cancer molecular immunophenotypes in biopsies with high vs average radiation sensitivity as predicted by post-operative radiation therapy outcomes (PORTOS) scores [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB065.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".