Table_1_Overexpression of IGF2BP3 as a Potential Oncogene in Ovarian Clear Cell Carcinoma.XLSX
Bibliographic record
Abstract
<p>Ovarian Clear Cell Carcinoma (OCCC) displays distinctive clinical and molecular characteristics and confers the worst prognosis among all ovarian carcinoma histotypes when diagnosed at advanced stage, because of the lack of effective therapy. IGF2BP3 is an RNA binding protein that modulates gene expression by post-transcriptional action. In this study, we investigated the roles of IGF2BP3 in the progression of OCCC. We used 328 OCCCs from the AOVT (the Alberta Ovarian Tumor Type study) and the COEUR (the Canadian Ovarian Experimental Unified Resource) cohorts to elucidate the associations between IGF2BP3 expression and clinicopathological parameters, with positive IGF2BP3 expression defined as diffuse block staining, being more frequently observed at stage III (P = 0.0056) and significantly associated with unfavorable overall survival (HR = 1.59, 95% CI 1.09–2.33) in multivariate analysis. IGF2BP3 mRNA gene expression was markedly increased in OCCC cell lines compared to normal tissues such as ovarian surface epithelium. We chose two IGF2BP3-overexpressing cell lines ES2 and OVMANA for in vitro and in vivo knockdown experiments. The proliferation and viability of both cell lines were significantly inhibited by two IGF2BP3 siRNAs and similar suppression was observed in cell migration and invasion by Wound Healing and Transwell assays. The percentage of apoptotic cancer cells was enhanced by both IGF2BP3 siRNAs. In vivo experiments showed significantly reduced sizes of tumors when treated with IGF2BP3 siRNA compared to controls. Furthermore, cancer metastasis-indicators MMP2 and MMP9 proteins were down-regulated. In conclusion, our study shows that IGF2BP3 expression is a promising biomarker for prognostication of women diagnosed with OCCC with multiple effects on key cell functions, supporting its role as an important cellular regulator with potential oncogenic activity, and as a potential target for future intervention strategies.</p>
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.413 | 0.023 |
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; both teacher heads agree on what is shown here.
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".