The LCS6 polymorphism in the binding site of let-7 microRNA to the KRAS 3′-untranslated region
Bibliographic record
Abstract
OBJECTIVE: Although KRAS mutation status has been identified as a strong predictor of response to anti-epidermal growth factor receptor (EGFR) therapies, not all wild-type patients respond. The lethal-7 (let-7) family of microRNAs regulates KRAS activity. A functional polymorphism (rs61764370) has been described in the let-7 complementary site (LCS6). We hypothesized a possible association between this KRAS let-7 LCS6 polymorphism and the response to anti-EGFR treatments in KRAS and BRAF wild-type metastatic colorectal cancer patients (mCRC). MATERIALS AND METHODS: We studied the association of the KRAS let-7 LCS6 polymorphism with the response in 100 refractory mCRC patients treated with anti-EGFR antibodies. To assess the real effect of this polymorphism in relation to the treatment administered, we also studied this association in an independent cohort of patients treated exclusively with chemotherapy. The KRAS let-7 LCS6 polymorphism was genotyped using the BioMark system in blood and tumor DNA samples. The BRAF V600E mutation was analyzed in tumor samples. RESULTS: The KRAS let-7 LCS6 G-allele showed a statistically significant association with nonresponse to anti-EGFR-based treatment: 31.9% of patients with the T/T genotype presented a complete or a partial response versus no patients with T/G or G/G genotypes (P=0.004). No statistically significant differences were observed in the patients who received chemotherapy only. CONCLUSION: These data support the pharmacogenetic role of the KRAS let-7 LCS6 polymorphism in predicting the efficacy of anti-EGFR-based therapy in mCRC patients with the KRAS and the BRAF wild-type genotype.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".