The chemosensory bitter taste receptors (T2Rs) are involved in proliferation and migration of breast cancer
Bibliographic record
Abstract
Background and Objective Breast cancer is a very complex disease and involves interactions between many proteins. The human bitter taste receptors (T2Rs) are a group of 25 chemosensory proteins that belong to the G protein‐coupled receptor family. T2Rs mediate signal transduction in response to stimulation by a wide variety of bitter compounds. Earlier studies showed that bitter agonists such as quinidine and chloroquine triggered apoptosis in MCF‐7 breast cancer cells, and bitter melon extract inhibited breast cancer cell proliferation by modulating cell cycle regulatory genes and promoting apoptosis. However, the cell surface receptor (T2R) targets for these bitter compounds, and their expression and characterization in the cancer cells is not yet elucidated. Methods To delineate the expression profile of T2Rs in breast cancer MDA‐MB‐231 and MCF‐7 cells and non‐cancerous MCF‐10A cell line, quantitative PCR (qPCR) and flow cytometry analysis was done. Next, analysis of T2R4 and T2R49 in human breast cancer tissue panel was performed using qPCR array (Origene Inc.). Calcium mobilization experiment was pursued to analyze the functional response after stimulation of these cells using bitter compounds. Cell proliferation was pursued using MTT assay and migration analysis by RTCA xCELLigence cell system after stimulating the cells with T2R ligands. Results Our results suggest differential expression of T2Rs is breast cancer cells. Stimulation of endogenous T2Rs with bitter agonists leads to increase in intracellular calcium release. Breast cancer cells treated with T2R4 agonist show decrease in cell proliferation and migration compared to non‐cancerous cells. This effect was reversed upon T2R4 antagonist treatment. Furthermore, knockdown and/or overexpression studies of T2R4 in these cells suggest its role in inhibition of cell proliferation and migration of breast cancer cells. Conclusions Our results suggest that T2Rs are involved in decrease of breast cancer cell proliferation and migration. Investigating the mechanistic role of these chemosensory T2Rs in breast cancer would aid in developing strategies to prevent and/or treat breast cancer. Support or Funding Information The Natural Sciences and Engineering Research Council of Canada (NSERC)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".