ERCC1 Isoform Expression and DNA Repair in Non–Small-Cell Lung Cancer
Bibliographic record
Abstract
BACKGROUND: The excision repair cross-complementation group 1 (ERCC1) protein is a potential prognostic biomarker of the efficacy of cisplatin-based chemotherapy in non-small-cell lung cancer (NSCLC). Although several ongoing trials are evaluating the level of expression of ERCC1, no consensus has been reached regarding a method for evaluation. METHODS: We used the 8F1 antibody to measure the level of expression of ERCC1 protein by means of immunohistochemical analysis in a validation set of samples obtained from 494 patients in two independent phase 3 trials (the National Cancer Institute of Canada Clinical Trials Group JBR.10 and the Cancer and Leukemia Group B 9633 trial from the Lung Adjuvant Cisplatin Evaluation Biology project). We compared the results of repeated staining of the entire original set of samples obtained from 589 patients in the International Adjuvant Lung Cancer Trial Biology study, which had led to the initial correlation between the absence of ERCC1 expression and platinum response, with our previous results in the same tumors. We mapped the epitope recognized by 16 commercially available ERCC1 antibodies and investigated the capacity of the different ERCC1 isoforms to repair platinum-induced DNA damage. RESULTS: We were unable to validate the predictive effect of immunostaining for ERCC1 protein. The discordance in the results of staining for ERCC1 suggested a change in the performance of the 8F1 antibody since 2006. We found that none of the 16 antibodies could distinguish among the four ERCC1 protein isoforms, whereas only one isoform produced a protein that had full capacities for nucleotide excision repair and cisplatin resistance. CONCLUSIONS: Immunohistochemical analysis with the use of currently available ERCC1 antibodies did not specifically detect the unique functional ERCC1 isoform. As a result, its usefulness in guiding therapeutic decision making is limited. (Funded by Eli Lilly and others.).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".