Abstract 4035: MicroRNA-221 levels correlate with aggressive and clinically recurrent prostate cancers
Bibliographic record
Abstract
Abstract One of the most important challenges in prostate cancer research is to identify biomarkers that are predictive of cancer aggressiveness and future tumor recurrence following radical prostatectomy. Recent studies have shown that altered expression of microRNAs (miRs) is involved in the development of prostate cancer, and among the differentially expressed miRNAs, miR-221 may be critical in metastatic induction/regulation. While the precise role of this miRNA in facilitating malignant progression remains unclear, expression of miR-221 in prostate cancer may correlate with disease state/status and serve as a surrogate biomarker for tumor recurrence and/or aggressiveness. In the present study, we sought to investigate whether miR-221 is differentially regulated in patients with aggressive and non-aggressive tumors relative to control normal prostate cell line RWPE-1 and, more specifically, whether this miRNA can be used as biomarker for disease recurrence. To address this question, we initially chose to assess the relative expression of miR-221 in a series of aggressive (n=69) and non-aggressive (n=45) primary carcinoma tissues derived from clinically resected prostates by quantitative real-time PCR. Aggressive tumors were categorized based on clinicopathological parameters such as Gleason score of 8 or higher, high PSA levels, presence of metastasis, invasion to the seminal vesicles, and recurrence after radical prostatectomy. Relative expression of mature miR-221 in tumors was quantified in comparison to control prostate epithelial cell line, RWPE-1, which was set to be 1x. Levels of miR-221 expression were found to be variable. Among all aggressive and non-aggressive cancer patients, expression of miR-221 transcript levels was differentially expressed relative to control sample. However, when we divided this group of patients on the basis of miR-221 expression levels, 72% of the patients with aggressive tumors had miR-221 less than 5-fold the RWPE-1 levels and only 28% of the patients had miR-221 expression equal to or more than 5-fold RWPE-1 levels. On the other hand, 53% of the patients with non-aggressive tumors had miR-221 less than 5-fold the RWPE-1 levels compared to 47% of the patients with miR-221 equal to or more than 5-fold RWPE-1 levels. Our results show that miR-221 is lower in majority of aggressive prostate cancer and differential expression may have utility as a biomarker for disease recurrence. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. 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 4035.
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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".