Genetic Screen Identifies Insulin-like Growth Factor Binding Protein 5 as a Modulator of Tamoxifen Resistance in Breast Cancer
Bibliographic record
Abstract
Tamoxifen resistance is one of the overarching challenges in the treatment of patients with estrogen receptor (ER)-positive breast cancer. Through a genome-wide RNA interference screen to discover genes responsible for tamoxifen resistance in vitro, we identified insulin-like growth factor binding protein 5 (IGFBP5) as a determinant of drug sensitivity. Specific knockdown of IGFBP5 by retroviral infection with short hairpin RNA-expressing cassette in MCF7 human breast cancer cells (pRS-shIGFBP5) conferred tamoxifen resistance in vitro due to concomitant loss of ERalpha expression and signaling. IGFBP5 expression was also reduced in MCF7 cells selected for tamoxifen resistance in culture (TAMR). Both tamoxifen-resistant MCF7-TAMR and MCF7-pRS-shIGFBP5 cells could be resensitized to drug by treatment with exogenous recombinant IGFBP5 (rIGFBP5) protein. Treatment with rIGFBP5 protein in mouse tumor xenografts reversed the in vivo tamoxifen resistance of MCF7-pRS-shIGFBP5 cell-derived tumors by reducing tumor cell proliferation. IGFBP5 immunohistochemical staining in a cohort of 153 breast cancer patients showed that low IGFBP5 expression was associated with shorter overall survival after tamoxifen therapy. Thus, IGFBP5 warrants investigation as an agent to reverse tamoxifen resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".