Precise targeting of transcriptional co-activators YAP/TAZ annihilates chemoresistant brCSCs by alteration of their mitochondrial homeostasis
Bibliographic record
Abstract
Abstract Persistence of drug-resistant breast cancer stem cells (brCSCs) after a chemotherapeutic regime correlates with disease recurrence and elevated mortality. Therefore, deciphering mechanisms that dictate their drug-resistant phenotype is imperative for designing targeted and more effective therapeutic strategies. The transcription factor SOX2 has been recognized as a protagonist in brCSC maintenance, and previous studies have confirmed that inhibition of SOX2 purportedly eliminated these brCSCs. However, pharmacological targeting of transcription factors like SOX2 is challenging due to their structural incongruities and intrinsic disorders in their binding interfaces. Therefore, transcriptional co-activators may serve as a feasible alternative for effectively targeting the brCSCs. Incidentally, transcriptional co-activators YAP/TAZ were found to be upregulated in CD44+/CD24-/ALDH+ cells isolated from patient breast tumors and CSC-enriched mammospheres. Interestingly, it was observed that YAP/TAZ exhibited direct physical interaction with SOX2 and silencing YAP/TAZ attenuated SOX2 expression in mammospheres, leading to significantly reduced sphere forming efficiency and cell viability. YAP/TAZ additionally manipulated redox homeostasis and regulated mitochondrial dynamics by restraining the expression of the mitochondrial fission marker, DRP1. Furthermore, YAP/TAZ inhibition induced DRP1 expression and impaired OXPHOS, consequently inducing apoptosis in mammospheres. In order to enhance clinical relevance of the study, an FDA-approved drug verteporfin (VP), was used for pharmacological inhibition of YAP/TAZ. Surprisingly, VP administration was found to reduce tumor-initiating capacity of the mammospheres, concomitant with disrupted mitochondrial homeostasis and significantly reduced brCSC population. Therefore, VP holds immense potential for repurposing and decisively eliminating the chemoresistant brCSCs, offering a potent strategy for managing tumor recurrence effectively.
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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".