In Vitro and Ex Vivo Inhibition of Human Telomerase by Anti-HIV Nucleoside Reverse Transcriptase Inhibitors (NRTIs) but Not by Non-NRTIs
Bibliographic record
Abstract
Telomerase is a specialized reverse transcriptase responsible for the de novo synthesis of telomeric DNA repeats. In addition to its established reverse transcriptase and terminal transferase activities, recent reports have revealed unexpected cellular activities of telomerase, including RNA-dependent RNA polymerization. This telomerase characteristic, distinct from other reverse transcriptases, indicates that clinically relevant reverse transcriptase inhibitors might have unexpected telomerase inhibition profiles. This is particularly important for the newer generation of RT inhibitors designed for anti-HIV therapy, which have reported higher safety margins than older agents. Using an in vitro primer extension assay, we tested the effects of clinically relevant HIV reverse transcriptase inhibitors on cellular telomerase activity. We observed that all commonly used nucleoside reverse transcriptase inhibitors (NRTIs), including zidovudine, stavudine, tenofovir, didanosine and abacavir, inhibit telomerase effectively in vitro. Truncated telomere synthesis was consistent with the expected mode of inhibition by all tested NRTIs. Through dose-response experiments, we established relative inhibitory potencies of NRTIs on in vitro telomerase activity as compared to the inhibitory potencies of the corresponding dideoxynucleotide triphosphates. In contrast to NRTIs, the non-nucleoside reverse transcriptase inhibitors (NNRTIs) nevirapine and efavirenz did not inhibit the primer extension activity of telomerase, even at millimolar concentrations. Long-term, continuous treatment of human HT29 cells with select NRTIs resulted in an accelerated loss of telomere repeats. All tested NRTIs exhibited the same rank order of inhibitory potencies on telomerase and HIV RT, which, according to published data, were orders-of-magnitude more sensitive than other DNA polymerases, including the susceptible mitochondria-specific DNA polymerase gamma. We concluded that telomerase activity could be inhibited by common NRTIs, including currently recommended RTI agents tenofovir and abacavir, which warrants large-scale clinical and epidemiological investigation of the off-target effects of long-term highly active antiretroviral therapy (HAART) with these agents.
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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 | 0.001 | 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".