<i>KIF14</i> mRNA expression is a predictor of grade and outcome in breast cancer
Bibliographic record
Abstract
Gain of chromosome 1q is a hallmark of breast cancer, and likely reflects oncogene amplification. We previously identified mitotic kinesin KIF14 (kinesin family member 14) as an overexpressed candidate oncogene in the 1q31.3-1q32.1 minimal region of genomic gain in breast cancer cell lines. KIF14 also showed high expression in other cancers, notably an association with survival in lung tumors. We now report KIF14 expression in 99 primary breast tumors and 10 normal breast controls. Measured by real-time RT-PCR, KIF14 was overexpressed 10-fold on average in tumors relative to normals (t test p = 0.000054); expression increased with grade (ANOVA p = 0.000006). Infiltrating ductal carcinomas had higher KIF14 levels than lobular (p = 0.017), and estrogen receptor (ER) negative tumors had higher KIF14 levels than ER positive tumors (t test p = 0.030). KIF14 expression correlated positively with Ki-67 mRNA level (Spearman r = 0.692, p = 0.000001), fraction of positive nodes (r = 0.227, p = 0.024) and percent invasive cells (r = 0.360, p = 0.0002), and negatively with percent fatty stroma (r = -0.258, p = 0.010) and percent normal epithelium (r = -0.291, p = 0.003). KIF14 expression is thus tumor-specific and increased in more aggressive tumors. Indeed, KIF14 expression predicted overall survival (univariate Cox p = 0.010), with an odds ratio of 3.60 (1.37-9.48), in 50 tumors with available outcome data. KIF14 overexpression also predicted decreased disease-free survival (log-rank p = 0.049). These findings are the first evidence of association between expression of a mitotic kinesin and prognostic variables in breast cancer.
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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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".