A New Twist in Cellular Resistance to the Anticancer Drug Bleomycin-A5
Bibliographic record
Abstract
Bleomycin is a potent chemotherapeutic agent that can mediate cell killing by attacking the DNA. It is used in combination with other antineoplastic agents to effectively treat lymphomas, testicular carcinomas and squamous cell carcinomas of the cervix, head and neck. However, resistance to bleomycin remains a persistent limitation in exploiting the full therapeutic benefit of the drug for other types of cancers. Herein, we review recent findings from both yeast and human cells showing that uptake of bleomycin-A5 is a key mechanism that limits toxicity of the drug. We also discuss how the mammalian transporter hCT2 (SLC22A16) could be used to predict the outcome of tumor responses towards bleomycin therapy, and highlight the importance of further exploring this permease with respect to its regulation and pharmacological substrates for treating a wide range of cancers. Keywords: Bleomycin, cancer cells, drug resistance, substrates, therapy, transport, Anticancer Drug, mammalian transporter hCT2, Streptomyces verticillis, guanine base, apurinic/apyrimidinic, antineoplastic agents, Saccharomyces cerevisiae, bleomycin hydrolase (BLH1), thiol protease specific inhibitor, Agp2, L-carnitine, fatty acid β-oxidation, acetyl-CoA, L-carnitine transporters, hCT2, OCTN2, RT-PCR, N1-acetylspermine, Jurkat cells, adriamycin, OCTN1, SLC22A4, SLC22A5, OCTN3, SLC22A21, OCT1, SLC22A1, OCT2, SLC22A2
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".