Abstract 3689: Identification of candidate therapeutic targets in BCG unresponsive bladder cancer- inflammatory subtypes of BCG unresponsive bladder cancer
Bibliographic record
Abstract
Abstract Intravesical immunotherapy with Bacillus Calmette-Guérin (BCG) is used for the first line treatment of high risk non-muscle invasive bladder cancer. Despite high initial response rates (70%), recurrence is a major problem and many patients develop BCG unresponsive disease, for which the primary treatment option is definitive surgery (cystectomy). In order to define the biological properties of BCG unresponsive disease, we performed whole transcriptome RNAseq on 29 matched tumors obtained from patients before and after the development of BCG resistance. Unsupervised cluster analysis revealed the presence of two clusters - BCG cluster 1, containing 8 pre- and 19-post BCG treatment tumors, and BCG cluster 2, containing 21 pre- and 10- post BCG tumors (Fisher's exact test, p<0.01). To characterize the biological properties of the two clusters, we extracted the significantly differentially expressed genes and analyzed them by Ingenuity Pathway Analysis (Sigma). Interestingly, multiple immune response pathways (T cell receptor signaling, IL8 signaling, IL12-mediated signaling, IFN-gamma pathways, immune cell trafficking, etc) were significantly enriched (p<0.01) in the BCG cluster 1 that was enriched for BCG unresponsive tumors. To determine the potential relationship between BCG clusters 1 and 2 and the previously defined basal and luminal molecular subtypes, we generated a batch-corrected bladder cancer meta-dataset combining two publically available datasets (GSE48075 and GSE32894) consisting of mixtures of non-muscle invasive and muscle-invasive tumors. We performed consensus cluster analysis using the meta-data and identified 3 distinct molecular clusters. The results indicated that the gene expression signature that characterized BCG cluster 1 was also present in tumors assigned to the basal/SCC-like and p53-like/infiltrated tumors defined previously. Together, the results indicate that the tumors in BCG cluster 1 may be enriched with T cells and therefore may have increased sensitivity to immune checkpoint blockade. However, it is likely that alternative therapeutic targets will need to be identified for BCG unresponsive tumors that display the ‘immune desert' phenotype characteristic of BCG cluster 2. Citation Format: Woonyoung Choi, Roger Li, Chinedu Mmeje, I-ling Lee, Shanna Pretzsch, Jolanta Bondaruk, Max Kates, Trinity Bivalacqua, Bogdan Czerniak, Ashish M. Kamat, Colin Dinney, Peter Black, David J. McConkey. Identification of candidate therapeutic targets in BCG unresponsive bladder cancer- inflammatory subtypes of BCG unresponsive bladder 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 3689.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".