Integrative <scp>miRNOMe</scp> profiling reveals the <scp>miR</scp> ‐195‐5p– <scp>CHEK1</scp> axis and its impact on luminal breast cancer outcomes
Bibliographic record
Abstract
The luminal subtype (estrogen receptor-positive, ER+) is the most common and the most heterogeneous type of breast carcinoma (BC) in women. During our study, we determined expression levels of all microRNAs (miRNome) in 101 ER+ BC samples and identified 25 miRNAs being associated with proliferative markers. Using comprehensive in silico analyses we prioritized CHEK1, CDC25A, and CCNE1 as candidate genes affecting the proliferation of ER+ BC, with two microRNAs from the miR-497∼195 cluster identified as their potential regulators. In a cohort of 217 patients, we found a significant association between high expression of CHEK1 and shorter relapse-free survival (RFS) in luminal BC patients treated with adjuvant chemotherapy, especially in patients with luminal A subtype. In patients treated with neoadjuvant therapy, the opposite role for RFS was observed for hsa-miR-195-5p. Subsequently, we confirmed the potency of hsa-miR-195-5p to inhibit the expression of CHEK1 in vitro. Moreover, the specific Chk1 inhibitor rabusertib (LY2603618) significantly enhanced the efficacy of doxorubicin in both ER+ and ER- cell lines. In summary, we have identified the association of a specific miRNA profile with highly proliferative luminal BCs and demonstrated the ability of hsa-miR-195-5p to inhibit CHEK1 expression in BC in vitro, underlining the importance of CHEK1 expression and its inhibition for prognosis and treatment of patients with luminal BCs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".