Riccardin D, a Macrocyclic Bisbibenzy, Inhibits Human Breast Cancer Growth through the Suppression of Telomerase Activity
Bibliographic record
Abstract
Riccardin D, a liverwort-derived naturally occurring macrocyclic bisbibenzyl, has been found to exert anticancer effects in multiple cancer cell types. In this study, we investigated the effect and mechanism of Riccardin D on human breast cancer. Experiments were performed on human breast cancer MCF-7 and MDA-MB-231 cells. The antitumour effects of Riccardin D were assessed by the 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay and human breast cancer xenografts mice model. TRAPeze(®) XL Telomerase Detection assay was used for the detection of telomerase activity. γ-H2 AX foci formation was tested for the induction of DNA damage response. Cell cycle distribution was analysed by flow cytometry, and cell apoptosis was determined by annexin V-FITC/PI staining, terminal deoxynucleotidyl transferase-mediated dUTP nick end labelling (TUNEL) assay and Western blotting. Riccardin D effectively inhibited the growth of MCF-7 and MDA-MB-231 cells in vitro. And Riccardin D also effectively delayed the growth of MCF-7 and MDA-MB-231-luc-D3H2LN xenografts without significant loss of body-weight. Further analysis suggested that Riccardin D's effects may arise from its suppression of telomerase activity, which led to telomere dysfunction. Telomerase inhibition and telomere dysfunction could activate the canonical ataxia telangiectasia-mutated (ATM) kinase-mediated DNA damage response, as shown by elevated expression of γ-H2 AX, p-ATM and p-Chk2. This is finally followed by the induction of cell cycle arrest and apoptosis, as shown by the increase of TUNEL-stained cells, caspase activation, PARP cleavage and the increase of bax/bcl-2 ratio. Moreover, Riccardin D induced p53-proficient MCF-7 cells to arrest in G1 phase and p53-deficient MDA-MB-231 cells to arrest in G2/M phase. Overall, these results demonstrate that Riccardin D may inhibit human breast cancer growth through suppression of telomerase activity.
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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) | 0.001 | 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".