LncRNA LINC01315 silencing modulates cancer stem cell properties and epithelial-to-mesenchymal transition in colorectal cancer via miR-484/DLK1 axis
Bibliographic record
Abstract
Long non-coding RNA long intergenic non-protein coding RNA 01315 (LncRNA LINC01315) has been found to be implicated in various cancers, but its role and functions in colorectal cancer (CRC) remain to be addressed. Data on LINC01315 expression in CRC were gathered using bioinformatics analysis, and cancer stem cells (CSCs) were sorted by aldehyde dehydrogenase (ALDH) assay and flow cytometry. Migration, invasion, and stemness of CSCs isolated from CRC cells after transfection were determined by scratch, Transwell, and sphere-formation assays, respectively. Tumor xenograft model was constructed. Target genes and potential-binding sites were predicted using online databases and further confirmed via dual-luciferase reporter assay. Relative factors expressions were determined via quantitative real-time polymerase-chain reaction and Western blot as needed. LINC01315 was high-expressed in CRC and ALDH+ cells. LINC01315 silencing suppressed the migration, invasion, and sphere formation of CRC cells and tumor growth, and downregulated expressions of CSC molecules (ALDH, cluster of difference 44 (CD44), Prominin, and sex determining region Y-box 2 (SOX2)), Zinc Finger E-Box Binding Homeobox 1 (ZEB1) and Vimentin but upregulated E-Cadherin expression. MiR-484 could competitively bind with LINC01315, and LINC01315 silencing promoted miR-484 expression. The level of Delta Like Non-Canonical Notch Ligand 1 (DLK1), the target gene of miR-484, was enhanced by overexpressed LINC01315 yet was suppressed by LINC01315 silencing. Also, DLK1 silencing reversed the effects of downregulated miR-484 on migration, invasion, sphere formation, and CSC molecules expressions in CRC cells. LINC01315 silencing modulated CSC properties and epithelial-to-mesenchymal transition via miR-484/DLK1 axis.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".