Tankyrases modulate the hypoxia response through non-catalytic mechanisms affecting HIF-1α
Bibliographic record
Abstract
BACKGROUND: Adaptation to hypoxia is essential for cancer survival and is linked to poor prognosis and treatment resistance. This adaptation triggers the expression of genes that promote angiogenesis and metabolic reprogramming, collectively enhancing cancer cell survival, tumor growth, migration and metastasis. Consequently, there is an urgent need for innovative strategies to inhibit tumor adaptation to hypoxic conditions. METHODS: The public database cBioPortal was utilized to analyze tankyrase mRNA alteration profiles across various cancer types, and the correlation between TNKS/2 and HIF1A expression was assessed using the GEPIA platform. The effects of TNKS1/2 inhibition or silencing on HIF-1α stabilization and activation were evaluated through western blotting and RT-qPCR analysis of HIF-target genes. To gain a comprehensive understanding of the impact of tankyrase elimination on hypoxia-driven gene expression, RNA-seq was also conducted. The effects on cell fitness and the functional consequences of tankyrase silencing in tumor cell adaptation to hypoxia were examined by measuring glycolysis through ECAR and lactate assays, along with apoptosis, colony formation and migration and invasion assays. To elucidate the molecular mechanisms by which tankyrases influence hypoxic signaling, we employed a range of approaches, including polysome profiling, mRNA half-life assays, reporter luciferase assays to analyze the HIF-1α promoter, and proximity ligation assays to explore the effect of tankyrase elimination on the interaction between HIF-1α and its inhibitory protein FIH-1. RESULTS: In the present study, we investigated the role of TNKS1 and TNKS2 as modulators of the hypoxic response. Notably, we found that tankyrases participate in the regulation of both HIF-1α levels (through fine-tuning HIF1A mRNA expression) and hypoxia-induced gene expression (through alteration of HIF-1α binding to FIH-1). Global RNA-seq revealed a specific impairment of the hypoxia-induced metabolic switch to glycolysis, with consequences for metabolic adaptation and cell fitness following TNKS1/2 silencing. These effects were independent of tankyrase catalytic activity. CONCLUSION: Our findings reveal a novel role for tankyrases in regulating tumor cell adaptation to hypoxia. This new mechanism operates independently of their catalytic activity, underscoring the potential of strategies that target tankyrases interaction with multiple partners through the ankyrin domain and holding promise for the development of new therapeutic advances to counter tumor adaptation to hypoxia.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".