Protein tyrosine phosphatome metabolic screen identifies TC‐PTP as a positive regulator of cancer cell bioenergetics and mitochondrial dynamics
Bibliographic record
Abstract
Metabolic reprogramming occurs in cancer cells and is regulated partly by the opposing actions of tyrosine kinases and tyrosine phosphatases. Several members of the protein tyrosine phosphatase (PTP) superfamily have been linked to cancer as either pro-oncogenic or tumor-suppressive enzymes. In order to investigate which PTPs can modulate the metabolic state of cancer cells, we performed an shRNA screen of PTPs in HCT116 human colorectal cancer cells. Among the 72 PTPs efficiently targeted, 24 were found to regulate mitochondrial respiration, 8 as negative and 16 as positive regulators. Of the latter, we selected TC-PTP (PTPN2) for further characterization since inhibition of this PTP resulted in major functional defects in oxidative metabolism without affecting glycolytic flux. Transmission electron microscopy revealed an increase in the number of damaged mitochondria in TC-PTP-null cells, demonstrating the potential role of this PTP in regulating mitochondrial homeostasis. Downregulation of STAT3 by siRNA-mediated silencing partially rescued the mitochondrial respiration defect observed in TC-PTP-deficient cells, supporting the role of this signaling axis in regulating mitochondrial activity. In addition, mitochondrial stress prevented an increased expression of electron transport chain-related genes in cells with TC-PTP silencing, correlating with decreased ATP production, cellular proliferation, and migration. Our shRNA-based metabolic screen revealed that PTPs can serve as either positive or negative regulators of cancer cell metabolism. Taken together, our findings uncover a new role for TC-PTP as an activator of mitochondrial metabolism, validating this PTP as a key target for cancer therapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".