TAp73 Modifies Metabolism and Positively Regulates Growth of Cancer Stem–Like Cells in a Redox-Sensitive Manner
Bibliographic record
Abstract
Abstract Purpose: Stem-like cancer cells, with characteristic self-renewal abilities, remain highly refractory to various clinical interventions. As such, stemness-inhibiting entities, such as tumor suppressor p53, are therapeutically pursued for their anticancer activities. Interestingly, similar implications for tumor suppressor TAp73 in regulating stemness features within stem-like cancer cells remain unknown. Experimental Design: This study utilizes various in vitro molecular biology techniques, including immunoblotting, qRT-PCR, and mass spectrometry–based proteomics, and metabolomics approaches to study the role of TAp73 in human and murine embryonal carcinoma stem-like cells (ECSLC) as well as human breast cancer stem-like cells (BCSLC). These findings were confirmed using patient-derived brain tumor–initiating cells (BTIC) and in vivo xenograft models. Results: TAp73 inhibition decreases the expression of stem cell transcription factors Oct4, Nanog, and Sox-2, as well as tumorsphere formation capacity in ECSLCs. In vivo, TAp73-deficient ECSLCs and BCSLCs demonstrate decreased tumorigenic potential when xenografted in mice. Mechanistically, TAp73 modifies the proline regulatory axis through regulation of enzymes GLS, OAT, and PYCR1 involved in the interconversion of proline–glutamine–ornithine. Further, TAp73 deficiency exacerbates glutamine dependency, enhances accumulation of reactive oxygen species through reduced superoxide dismutase 1 (SOD1) expression, and promotes differentiation by arresting cell cycle and elevating autophagy. Most importantly, the knockdown of TAp73 in CD133HI BTICs, separated from three different glioblastoma patients, strongly decreases the expression of prosurvival factors Sox-2, BMI-1, and SOD1, and profoundly decreases their self-renewal capacity as evidenced through their reduced tumorsphere formation ability. Conclusions: Collectively, we reveal a clinically relevant aspect of cancer cell growth and stemness regulation through TAp73-mediated redox-sensitive metabolic reprogramming.
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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".