Comprehensive identification of hub mRNAs and lncRNAs in colorectal cancer using galaxy: an in silico transcriptome analysis
Why this work is in the frame
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Bibliographic record
Abstract
Colorectal cancer (CRC) is the second leading cause of cancer-related mortality. Using the Galaxy platform, the present study aimed to assess the differentially expressed genes (DEGs) in CRC patients. The expression data was obtained from the Gene Expression Omnibus database (GSE137327). DEGs were analyzed using Gene Ontology (GO) and GeneMANIA databases to detect the most critical biological pathways and processes. Protein-Protein Interaction Studies (PPIS) identified four hub genes (CCN1, CCL2, FLNC, MYH11). This article presents findings on three mRNAs (CEMIP, MMP7, and DPEP1) and also two notable lncRNAs, EVADR and DLX6-AS1, that have an impact on CRC pathogenesis and play a role in the epithelial-mesenchymal transition in tumor cells. The identified genes and lncRNAs are putative therapeutic targets and diagnostic markers. For instance, CRISPR/Cas9 editing systems can be designed in order to modulate expression of these genes, or edit them for the purpose of inducing sensitivity to conventional therapies. Besides, these genes can be incorporated into clinical prognostic models, offering panels of genes to choose appropriate personalized methods of treatment. Together, these genes represent novel markers and possible therapeutic targets for CRC.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it