Genetic determinants and clinical significance of circulating and tumor-specific levels of insulin-like growth factor binding protein 7 (IGFBP7) in a Swedish breast cancer cohort
Bibliographic record
Abstract
Previous research indicates that insulin-like growth factor binding protein 7 (IGFBP7) protein levels in breast cancer tissue and blood are prognostic. However, genetic determinants of IGFBP7 in breast cancer remain largely unexplored. We examined IGFBP7 in a cohort of 1701 patients with first breast cancer from Sweden, enrolled prior to surgery 2002-16 and followed for up to 15 years. Genotyping was performed on blood samples using OncoArray. Tumor-specific protein levels of IGFBP7, insulin receptor (InsR), and IGF-I receptor (IGFIR) were assessed on tumor tissue microarrays in 964 patients. Furthermore, 275 patients had plasma IGFBP7 levels measured. A genetic proxy marker for circulating IGFBP7 levels was constructed from five candidate single-nucleotide polymorphisms (SNPs) (rs6852762, rs1714014, rs9992658, rs10004910, and rs4865180) based on number of recessive genotypes. Age-adjusted linear regression was used to evaluate SNPs and tumor-specific IGFBP7 levels in relation to circulating IGFBP7 levels. Cox regression adjusted for age, tumor characteristics, and adjuvant treatments was used to assess associations with clinical outcomes. Circulating and tumor-specific IGFBP7 levels were significantly positively correlated. High circulating and genetically predicted IGFBP7 levels were associated with increased risk for distant metastasis and all-cause mortality. A significant interaction between high tumor-specific IGFBP7 levels and membrane-bound InsR resulted in a four-fold increased risk of breast cancer events and distant metastases. Both measured and genetically predicted IGFBP7 levels were independent prognostic biomarkers in breast cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".