Abstract LB093: Low IGFBP7 expression identifies a subset of breast cancers with favorable prognosis and sensitivity to IGF-1 receptor targeting with ganitumab: Data from I-SPY2 and SCAN-B
Bibliographic record
Abstract
Abstract Background and Hypothesis: To date, no IGF-1R targeting agent has shown clinical benefit in patients despite promising preclinical data. We hypothesized that Insulin-like growth factor binding protein-7 (IGFBP7) expression predicts response to Insulin-like growth factor-1 receptor (IGF-1R) targeting agents, for which there are no biomarkers predictive of efficacy. High IGFBP7 expression was previously associated with breast cancer progression. Materials and Methods: The predictive value of IGFBP7 expression was interrogated in I-SPY2 (NCT01042379) for pathological complete response (pCR) to neoadjuvant treatment and in SCAN-B (NCT02306096) for clinical outcome. In I-SPY2, IGFBP7 expression was examined as a predictor of pCR to neoadjuvant chemotherapy alone and separately to the combination of chemotherapy plus ganitumab (anti-IGF-1R antibody) and metformin. Odds ratios (OR) and hazard ratios (HR) with 95% confidence interval (CI) were calculated with logistic and Cox regression, respectively. Results: Higher IGFBP7 expression conferred lower odds of achieving pCR in the ganitumab/metformin plus chemotherapy arm, ORadj 0.38 (95% CI 0.17-0.80) but not in the chemotherapy-alone arm, adjusted OR 1.23 (95% CI 0.63-2.45; P interaction=0.016). In the ganitumab/metformin plus chemotherapy arm, 46.9% of patients with tumors in the lowest quartile of IGFBP7 expression achieved pCR compared to compared to only 5.6% in the highest quartile. In SCAN-B, higher IGFBP7 expression was associated with distant metastasis risk HRadj 1.41 (95% CI 1.16-1.73). Conclusion: Low IGFBP7 gene expression identifies a subset of breast cancer patients for whom the addition of ganitumab and metformin to chemotherapy results in a significantly improved pCR rate compared to neoadjuvant chemotherapy alone. Furthermore, we add to prior evidence that high IGFBP7 expression is predictive of poor outcome. Citation Format: Christopher Godina, Michael N. Pollak, Helena Jernström. Low IGFBP7 expression identifies a subset of breast cancers with favorable prognosis and sensitivity to IGF-1 receptor targeting with ganitumab: Data from I-SPY2 and SCAN-B [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB093.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".