Profiling Neoadjuvant Therapy Response in Rectal Cancer Using Publicly Available Transcriptomic RNA-seq Datasets
Bibliographic record
Abstract
ABSTRACT Neoadjuvant chemoradiotherapy followed by total mesorectal excision is standard for locally advanced rectal cancer, but response varies and current markers are insufficient. This study integrates public bulk RNAseq data to identify predictive features of response. TRIM54 and PABPC4 were up-regulated in the responder group, while ADSS1 and MGAT1 were up-regulated in non-responder group. ARMC2 was identified as a predictive biomarker up-regulated in pathological complete response. Responder group showed enrichment of NK cells and CD4+ lymphocytes, while immune precursors were linked to poor outcome. Transcription factor analysis revealed SP1 and NFKB activations in the non-responder group and TCF15 in responder group. SMAD3 and RDXANK were associated with complete regression, while MYC was dominant in incomplete regression. These findings provided insight into mechanisms underlying therapy response. To our knowledge, this is the first meta-analysis using high-throughput sequencing data, providing a valuable starting point for future rectal cancer research.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".