Significance of insulin-like growth factor binding protein-2 in the prognosis of breast cancer and promotion of accelerated growth and chemo-resistance in MDAMB-231 breast cancer model
Bibliographic record
Abstract
542 Background: Insulin like growth factor-1 (IGF1) activity is modulated by a family of IGF binding proteins (IGFBPs). The role of IGFBPs, specifically IGFBP2, in breast cancer (BCa) is poorly defined. We correlate the expression of IGFBP2 and BCa specific survival through a tissue microarray (TMA). Effect of increased IGFBP2 expression was evaluated using gain of- and loss of-function analysis in the MDA-MB231 BCa model. Methods: 348 primary human breast cancers were included in TMA construction and immunostained for IGFBP2. MB231 cells constitutively over-expressing IGFBP2 (231BP2) were generated by lentivirus transfection. IGF1R and IGFBP2 expression and response to exogenous IGF1 was compared between 231BP2 cell line and mock-transfected MB231 cell line (231M). The effect of IGFBP2 over-expression on tumor growth in vivo was determined using nude mice inoculated with either 231BP2 or 231M (n=10) +/- paclitxel (n=10). A potent antisense oligonucleotide against IGFBP2 (OGX-225, OncoGenex, Vancouver), and RNA interference (RNAi) was used to test the effects IGFBP-2 knockdown in vitro and in vivo. Results: TMA analysis show that 20 year disease-specific survival was significantly worse in those BCas highly expressing IGFBP-2 compared to low or moderate expressing tumors (63% vs. 74%, p=0.04). Spearman test demonstrates a correlation between IGFBP2 and tumor size (p=0.006) and node status (p=0.034). BP2 over-expression confers both a growth advantage in media and enhanced resistance to paclitaxel treatment. 231BP2 cells expressed higher IGF1R levels and grew faster after IGF1 treatment compared to 231M cells. In-vivo, 231BP2 tumors grew more rapidly and were more resistant to paclitaxel therapy compared to 231M control. OGX-225 and RNAi treatment inhibited tumor cell growth in vitro and in vivo through increased apoptosis. Conclusions: This study shows a significant association between tumor levels of IGFBP2 and poor survival in BCa. IGFBP2 overexpression in an ER- BCa model confers accelerated growth and chemoresistance that may be induced through increased activation of the IGF1 pathway. Author Disclosure Employment or Leadership Consultant or Advisory Role Stock Ownership Honoraria Research Funding Expert Testimony Other Remuneration Oncogenex Technologies
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".