Knockdown of HSF1 sensitizes resistant prostate cancer cell line to chemotherapy
Bibliographic record
Abstract
The treatment of prostate cancer patients usually starts with androgen ablation and followed by chemotherapy; however, in some cases the tumor develops resistant phenotype.Combination therapy is currently regarded as a cornerstone in cancer therapy to overcome the drug resistance.Herein, we investigated the combinatory effect of Docetaxel and Trastuzumab with a novel nanomedicine, BCc1.Also, we knocked down the expression of Heat shock factor-1, HSF1, in resistant Prostate Cancer cell line 3, PC3, using RNA interference, RNAi, to sensitize the cancer cells to the drug treatment.We observed down-regulation of Erb-B2 Receptor Tyrosine Kinase 3, ERBB3, B-Cell Leukemia/Lymphoma 2, BCL2, and Heat Shock Protein 90, HSP90, in HSF1 knockdown PC3 cells.Knockdown of HSF1 made PC3 cells more susceptible to Docetaxel treatment.Additionally, BCc1 nanomedicine was tested on prostate cancer cell line PC3 for the first time.It resulted in reduced metabolic activity in these cells.We propose that a combination of the gene therapy and the chemotherapy gives more favorable results in the treatment of refractory prostate cancer.
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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".