IGF1R signalling in testicular germ cell tumour cells impacts on cell survival and acquired cisplatin resistance
Bibliographic record
Abstract
Testicular germ cell tumours (TGCTs) are the most frequent malignancy and cause of death from solid tumours in the 20- to 40-year age group. Although most cases show sensitivity to cis-platinum-based chemotherapy, this is associated with long-term toxicities and chemo-resistance. Roles for receptor tyrosine kinases other than KIT are largely unknown in TGCT. We therefore conducted a phosphoproteomic screen and identified the insulin growth factor receptor-1 (IGF1R) as both highly expressed and activated in TGCT cell lines representing the nonseminomatous subtype. IGF1R was also frequently expressed in tumour samples from patients with nonseminomas. Functional analysis of cell line models showed that long-term shRNA-mediated IGF1R silencing leads to apoptosis and complete ablation of nonseminoma cells with active IGF1R signalling. Cell lines with high levels of IGF1R activity also showed reduced AKT signalling in response to decreased IGF1R expression as well as sensitivity to the small-molecule IGF1R inhibitor NVP-AEW541. These results were in contrast to those in the seminoma cell line TCAM2 that lacked IGF1R signalling via AKT and was one of the two cell lines least sensitive to the IGF1R inhibitor. The dependence on IGF1R activity in the majority of nonseminomas parallels the known role of IGF signalling in the proliferation, migration, and survival of primordial germ cells, the putative cell of origin for TGCT. Upregulation of IGF1R expression and signalling was also found to contribute to acquired cisplatin resistance in an in vitro nonseminoma model, providing a rationale for targeting IGF1R in cisplatin-resistant disease. © 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
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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 | 0.000 |
| 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".