Tumor suppressor effects for miR-215 identified through use of miRNA profiling in metastatic renal cell carcinoma.
Bibliographic record
Abstract
392 Background: Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney. Metastatic RCC is difficult to treat. The five-year survival rate for metastatic RCC is <10%. Recently, microRNAs (miRNAs) have been shown to have a role in cancer metastasis and potential as prognostic biomarkers in cancer. Methods: We preformed a miRNA microarray to identify a miRNA signature characteristic of metastatic compared to primary RCC. Results were validated by quantitative real time PCR. Target prediction analysis and gene expression profiling identified many of the dysregulated miRNAs could target genes involved in tumor metastasis. The effect of miR-215 on cellular migration and invasion was shown in a RCC cell line model. Results: We identified 65 miRNAs that were significantly altered in metastatic when compared to primary RCC. Nine (14%) miRNAs had increased expression while 56 (86%) miRNAs showed decreased expression. miR-10b, miR-196a, and miR-27b were the most downregulated while miR-638, miR-1915, and miR-149* were the most upregulated. A non-supervised 2D-cluster analysis showed that a sub-group of the primary tumors clustered under the metastatic arm with a group of miRNAs that follow the same pattern of expression suggesting they have an inherited aggressive signature. We validated our results by examining the expressions of miR-10b, miR-126, miR-196a, miR-204, and miR-215, in two independent cohorts of patients. We also showed that overexpression of miR-215 decreased cellular migration and invasion in a RCC cell line model. In addition, through gene expression profiling, we identified direct and indirect targets of miR-215 that can contribute to tumor metastasis. Conclusions: Our analysis showed that miRNAs are altered in metastatic RCC and can contribute to kidney cancer metastasis through different biological processes. Dysregulated miRNAs represent potential prognostic biomarkers and may have therapeutic applications in kidney cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".