Cold-inducible RNA-binding protein is associated with subtype-specific breast cancer patient outcomes
Bibliographic record
Abstract
BACKGROUND: Cold-inducible RNA-binding protein (CIRBP) is a stress-induced mRNA-binding protein associated with clinical outcomes in a variety of human disease states. The role of CIRBP as a role as a prognostic biomarker in breast cancer (BC) has yet to be established. FINDINGS: We describe a clinically annotated tissue micro-array cohort of 1406 hormone receptor positive (HR +) and 281 triple negative primary breast cancers (TNBC) stained by immunohistochemistry (IHC) for CIRBP. Statistical analyses were performed with the Kaplan-Meier estimator, as well as univariate and multivariate Cox proportional-hazards models. Multivariate models incorporated tumor size, lymph node status, grade and CIRBP expression levels. Co-primary endpoints were overall survival (OS) and progression-free survival (PFS). In N = 281 primary TNBCs, high levels of CIRBP expression by IHC was associated with poor prognosis in multivariate analysis (OS: adjusted hazard ratio (aHR) 2.05, 95% confidence interval (CI) 1.24-3.41, P = 0.005. PFS: aHR 2.46, 95% CI 1.33-4.57, P = 0.004). However, in N = 1406 HR + primary BC, CIRBP expression was correlated with favorable prognosis (OS: aHR 0.927, 95% CI 0.88-0.98, P = 0.005. PFS: aHR 0.904, 95% CI 0.85-0.96, P = 0.002). CONCLUSIONS: CIRBP expression is associated with poor prognosis in TNBC but not HR + BC patients. This finding highlights the prognostic significance of CIRBP in TNBC and suggests differential underlying mRNA targets bound and modulated by CIRBP in TNBC and HR + BC, respectively.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".