Antagonists of the serotonin receptor 5A target human breast tumor initiating cells
Bibliographic record
Abstract
Abstract Background Breast tumor initiating cells (BTIC) are stem-like cells that initiate and sustain tumor growth, and drive disease recurrence. Identifying therapies targeting BTIC has been hindered due primarily to their scarcity in tumors. We previously reported that BTIC frequency ranges between 15% and 50% in multiple mammary tumors of 3 different transgenic mouse models of breast cancer and that this frequency is maintained in tumor cell populations cultured in serum-free, chemically defined media as non-adherent tumorspheres. The latter enabled high-throughput screening of small molecules for their capacity to affect BTIC survival. Antagonists of several serotonin receptors (5-HTRs) were among the hit compounds. The most potent compound we identified, SB-699551, selectively binds to 5-HT5A, a Gαi/o protein coupled receptor (GPCR). Methods We evaluated the activity of structurally unrelated selective 5-HT5A antagonists using multiple orthogonal assays of BTIC frequency. Thereafter we used a phosphoproteomic approach to uncover the mechanism of action of SB-699551. To validate the molecular target of the antagonists, we used the CRISPR-Cas9 gene editing technology to conditionally knockout HTR5A in a breast tumor cell line. Results We found that selective antagonists of 5-HT5A reduced the frequency of tumorsphere initiating cells residing in breast tumor cell lines and those of patient-derived xenografts (PDXs) that we established. The most potent compound among those tested, SB-699551, reduced the frequency of BTIC in ex vivo assays and acted in concert with chemotherapy to shrink human breast tumor xenografts in vivo. Our phosphoproteomic experiments established that exposure of breast tumor cells to SB-699551 elicited signaling changes in the canonical Gαi/o-coupled pathway and the phosphoinositide 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) axis. Moreover, conditional mutation of the HTR5A gene resulted in the loss of tumorsphere initiating cells and BTIC thus mimicking the effect of SB-699551. Conclusions Our data provide genetic, pharmacological and phosphoproteomic evidence consistent with the on-target activity of SB-699551. The use of such agents in combination with cytotoxic chemotherapy provides a novel therapeutic approach to treat breast 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 | 0.000 |
| 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".