TRPML1 signaling at lysosomes-mitochondria nexus drives triple-negative breast cancer mitophagy, metabolic reprogramming and chemoresistance
Bibliographic record
Abstract
ABSTRACT Inter-organelle signaling mechanisms, particularly those at the lysosomes-mitochondria interface, are critical for cancer cell metabolism, mitophagy and survival. However, the incomplete understanding of these mechanisms has limited the development of effective therapies, especially for triple-negative breast cancers (TNBC). Here, we demonstrate the lysosomal Ca²⁺-release channel TRPML1 as a master regulator of mitochondrial bioenergetics in TNBC cells. TRPML1 knockdown (ML1-KD) in TNBC cells selectively compromises mitochondrial respiration, reprograms cell metabolism, and induces mitochondrial fragmentation without impacting non-cancerous cells. Mitochondria of ML1-KD TNBC cells sequester around the endoplasmic reticulum (ER), increasing mitochondria-ER contact sites at the expense of mitochondria-lysosomes contacts. Mechanistically, ML1-KD reduces lysosomal acidification, thus hindering autophagic flux and completion of autophagy. ML1-KD inhibits TFEB-mediated mitophagy and oxidative defense mechanisms while causing mitochondrial Ca 2+ overload, further impairing mitochondrial function. These alterations render ML1-KD TNBC cells highly sensitive to doxorubicin and paclitaxel at low doses that are typically ineffective on their own. Together, our findings establish TRPML1 as a critical inter-organelle regulator and highlight its potential as a therapeutic target to exploit the metabolic vulnerabilities of TNBC cells.
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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 | 0.001 |
| 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".