40 Canagliflozin, a New Anti-Diabetic Agent Targeting Cellular Metabolism, Suppresses Survival and Enhances the Response of Non-Small Cell Lung Cancer (NSCLC) to Radiotherapy
Bibliographic record
Abstract
CARO-ASM 2019 prostatic adenocarcinomas: most are multi-focal and harbour multiple sub-clonal populations.Herein, we determined the robustness of three validated DNA-based genomic biomarkers to intratumoural heterogeneity, and their association with the respective clinical phenotype. Materials and Methods:After obtaining Institutional approval, we queried a prospective registry including 1,054 patients with high-risk prostate cancer who underwent RP between 2001-2013.A case-control cohort (n=42) risk-matched by clinicopathologic prognostic indices was derived, comprising 21 patients that developed early biochemical recurrence (eBCR; <18 months after RP), and 21 with long-term control (LTC; >48 months after RP).Then, we dissected multiple distinct tumour foci per patient (average 3 foci), leading to a total of 119 samples for genomic profiling.For each focus, three genomic DNA-based biomarker scores were calculated: percentage of genome with a copy number aberration (PGA), a 100-loci biomarker, and an optimized 31-loci biomarker derived from the previous.For each patient and biomarker, we considered three scenarios: sampling of only the lowest-score region, the highest-score region, or sampling of all foci and use the mean score across them. Results:We observed high intra-patient genomic divergence between the least and most altered tumour sample, in average representing 6.15% of the genome (i.e. gain or loss of approximately an entire chromosome).Nevertheless, all three biomarkers successfully distinguished eBCR from LTC in this case-control cohort, regardless of which focus, or way of summarizing foci was used: PGA, 100-and 31-loci scores separated the two clinical phenotypes with an AUC ranging from 0.75-0.80,0.76-0.85and 0.76-0.80respectively.No statistical difference between AUCs was observed.Similarly, on time-to-event analyses (Cox proportional hazards modeling) all three biomarkers were significantly associated with BCR-free survival independent of how different foci were summarized.Conclusions: Genomic heterogeneity within patients is very large, and translates in differences in DNA-biomarker scores.Nonetheless, despite the theoretical impact on prognostication, all three genomic biomarkers evaluated were spatially robust and accurately predicted eBCR.Our study provocatively suggests that individual samples may be adequate in patients with high-risk disease.The validity and implications of this findings in patients with low-and intermediate-risk disease, and other genomic biomarkers warrants further investigation.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".