Signals Controlling Un‐Differentiated States in Embryonic Stem and Cancer Cells: Role of the Phosphatidylinositol 3′ Kinase Pathway
Bibliographic record
Abstract
The capacity of embryonic stem (ES) cells to differentiate into cell lineages comprising the three germ layers makes them powerful tools for studying mammalian early embryonic development in vitro. The human body consists of approximately 210 different somatic cell types, the majority of which have limited proliferative capacity. However, both stem cells and cancer cells bypass this replicative barrier and undergo symmetric division indefinitely when cultured under defined conditions. Several signal transduction pathways play important roles in regulating stem cell development, and aberrant expression of components of these pathways is linked to cancer. Among signaling systems, the critical role of leukemia inhibitory factor (LIF) coupled to the Jak/STAT3 (signal transduction and activation of transcription-3) pathway in maintaining stem cell self-renewal has been extensively reviewed. This pathway additionally plays multiple roles in tumorigenesis. Likewise, the phosphatidylinositide 3-kinase (PI3K)/protein kinase B (PKB/Akt) pathway has been determined to play an important role in both stem cell maintenance and tumor development. This pathway is often induced in cancer with frequent mutational activation of the catalytic subunit of PI3K or loss of a primary PI3K antagonist, phosphatase and tensin homolog deleted on chromosome ten (PTEN). This review focusses on roles of the PI3K signal transduction pathway components, with emphasis on functions in stem cell maintenance and cancer. Since the PI3K pathway impinges on and collaborates with other signaling pathways in regulating stem cell development and/or cancer, aspects of the canonical Wnt, Ras/mitogen-activated protein kinase (MAPK), and TGF-β signaling pathways are also discussed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".