Abstract 2023: Potential importance of micro-RNA-193b in human head and neck squamous cell carcinoma
Bibliographic record
Abstract
Abstract INTRODUCTION Head and neck squamous cell carcinoma (HNSCC) is the fifth most common cancer worldwide, half of these patients presenting with locally advanced disease, which despite aggressive multi-modality treatments, achieves five-year survival rates of only 50%, underscoring a need to better understand the biological bases of this disease. One approach would be examining HNSCC through the lens of micro-RNAs (miRs), which are endogenous non-coding RNAs that could post-transcriptionally regulate up to 1/3 of all human genes. EXPERIMENTAL DESIGN Global miR profilings were conducted on 54 primary human HNSCC samples, and three HNSCC cell lines (FaDu, UTSCC42a, UTSCC8), compared to normal laryngeal tissues, and a normal oral epithelial cell line, using the Taqman Low-Density Array (Applied Biosystems). The most deregulated miRs were then selected for further evaluation by knocking down the over-expressed miRs using LNAs (locked nucleic acids), and cellular effects were then determined using MTS, clonogenic, and flow cytometry assays. Micro-RNA-193b was selected for more detailed examination; mRNA candidate targets were determined by combining three different approaches described below. Binding of miR-193b with candidate mRNA was determined using a luciferase assay after co-transfection of a luciferase vector containing the 3′UTR of the mRNA target, with LNA miR-193b. RESULTS Based on the predictive power (relapse vs. non-relapse) from the clinical samples, and biological relevance in cell line studies (tumour vs. normal), six top dysregulated (over-expressed) miRs; miR-15b, miR-106b, miR-130a, miR-193b, miR-205, and miR-423, were selected for further evaluation. Only miR-106b, miR-193b and miR-205 were able to reduce cell proliferation in all three cell lines after LNA, assessed using both the MTS and clonogenic assays, with miR-193b also increasing the proportion of cells in the sub-G1 phase of the cell cycle. Candidate mRNA targets of miR-193b were elucidated by integrating in silico prediction algorithms with in vitro experimental mRNA expression profilings, and publically-available clinical mRNA expression data. A set of 11 potential mRNA targets of miR-193b were selected; 6 of which were over-expressed after miR-193b LNA knockdown. One target, Neurofibromatosis 1 (NF1), was demonstrated to directly interact with miR-193b using the luciferase vector carrying the 3′UTR of NF1. CONCLUSION Global miR profiling of HNSCC tissues and cell lines, demonstrated a trend toward over-expressed miRs. MiR-193b appears to be an important over-expressed miR in HNSCC, which targets NF1, a RAS-GTPase which hydrolyzes active RAS-GTP into inactive RAS-GDP. This failure to inactivate RAS might therefore be a potential mechanism by which several downstream oncogenic pathways of MAPK, STAT, and PI(3)K are activated, signaling continued cellular proliferation, and anti-apoptosis, hallmarks of aggressive HNSCC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2023.
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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) | 0.003 | 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".