The PI3K/AKT/c-MYC Axis Promotes the Acquisition of Cancer Stem-Like Features in Esophageal Squamous Cell Carcinoma
Bibliographic record
Abstract
The importance of intratumoral heterogeneity has been highlighted by the identification and characterization of cancer stem cells (CSCs). Based on the differential responsiveness to a Sox2 reporter, SRR2, we had found a novel dichotomy in esophageal squamous cell carcinoma (ESCC) cells, with reporter-responsive (RR) cells showing more CSC-like features than reporter-unresponsive (RU) cells. Specifically, RR cells exhibited significantly higher tumorsphere formation capacity, proportions of CD44(High) cells, chemoresistance to cisplatin, and tumorigenic potential in vivo. H2 O2 , a potent inducer of oxidative stress and reactive oxygen species, was found to induce a conversion from RU to RR cells; importantly, converted RR cells acquired CSC-like features. The PI3K/AKT/c-MYC signalling axis is important in this context, since pharmacologic blockade of PI3K-AKT or siRNA knockdown of c-MYC effectively inhibited the RR phenotype and its associated CSC-like features, as well as the H2 O2 -induced RU/RR conversion. In a cohort of 188 ESCC patient samples, we found a significant correlation between strong c-MYC expression and a short overall survival (p = .009). In conclusion, we have described a novel intratumoral heterogeneity in ESCC. The identification of the PI3K/AKT/c-MYC axis as a driver of CSC-like features carries therapeutic implications. Stem Cells 2016;34:2040-2051.
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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".