Kinesin family member 11 is a potential therapeutic target and is suppressed by microRNA‐30a in breast cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Kinesin family member 11 (KIF11) is a plus end-directed kinesin indispensable for the formation of the bipolar spindle in metaphase, where it objects to the action of minus end-directed molecular motors. Here, we hypothesize that KIF11 might be a therapeutic target of breast cancer and regulated by miR-30a. Cell Counting Kit 8 assays were used to investigate cell proliferation. Invasion assays were used to survey the motility of cells. Kaplan-Meier and Cox proportional analyses were employed for this outcome study. The prognostic significance and performance of KIF11 were validated on 17 worldwide independent microarray datasets and two The Cancer Genome Atlas-Breast Invasive Carcinoma sets. microRNA was predicted targeting KIF11 through sequence alignment in microRNA.org and confirmed by coexpression analysis in human breast cancer samples. Dual-luciferase reporter assays were employed to validate the interaction between miR-30a and KIF11 further. Higher KIF11 mRNA levels and lower miR-30a were significantly associated with poor survival of breast cancer patients. Inhibition of KIF11 by small-hairpin RNA significantly reduced the proliferation and invasion capabilities of the breast cancer cells. Meanwhile, downregulation of KIF11 could enhance the cytotoxicity of adriamycin in breast cancer cell lines MCF-7 and MDA-MB-231. A population study also validated that chemotherapy and radiotherapy significantly improved survival in early-stage breast cancer patients with low KIF11 expression levels. Further bioinformatics analysis demonstrated that miR-30a could interact with KIF11 and validated by dual-luciferase reporter assays. Therefore, KIF11 is a potential therapeutic target of breast cancer. miR-30a could specifically interact with KIF11 and suppress its expression in breast cancer.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it