Bibliographic record
Abstract
Background & Aims: Tumor-initiating stem-like cells (TICs) are defective in maintaining asymmetric cell division and responsible for tumor recurrence. Stem cell markers such as Nanog have been implicated in various cancer, but whether they are functionally contributing to cancer pathogenesis has remained unclear. Novel NOTCH/NUMB-interacting protein, TBC1D15, is overexpressed and contributes to p53 degradation in TICs. Aims are to identify NANOG- or TBC1D15-mediated oncogenic mechanisms and to test tumorigenic roles. \n \nMethods: We determined novel targets of NANOG in tumor-initiating cells (TICs) from patient and mouse-models of hepatocellular carcinoma (HCC) using genome-wide NANOG-binding site analysis (ChIP-seq) and how Nanog is regulated at the transcriptional to promote oncogenesis and self-renewal in TICs. TBC1D15 interacting proteins were searched by large-scale immunoaffinity purification and LC-MS analysis. We examined HCC development in alcohol Western diet (AWD)-fed HCV NS5A Tg mice with hepatocyte-specific TBC1D15 deficiency or hepatocyte-specific expression of non-phosphorylatable NUMB mutations (non-p-NUMB). \n \nResults: Silencing NANOG inhibits tumor development in HCC mouse-models and genesis of TICs. NANOG binds genes of oxidative phosphorylation and b-oxidation in mitochondria. Silencing \nNANOG promotes oxidative phosphorylation and b-oxidation, indicating that NANOG is a suppressor of mitochondria-mediated energy production. We identified NuMA1, RANGAP1 and NOTCH1-4 as TBC1D15-interacting proteins. TBC1D15-NuMA1 association impaired NuMA1-LAN interaction which is essential for an asymmetric division machinery, thereby promoting TIC self-renewal. TBC1D15-NOTCH1 interaction activated and stabilized NOTCH1 and NOTCH1 Intracellular Domain (N1ICD) which in turn upregulated transcription of Nanog essential for TICs. \n \nConclusions: These results suggest that NANOG-mediated metabolic reprogramming through suppression of mitochondria function in both experimental and clinical HCC downstream of TLR4/ \nNANOG generates TICs and drives liver tumorigenesis. TBC1D15 and p-NUMB are required for liver tumor development in vivo.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.787 | 0.585 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".