PS1 - 158 The Role of LIN28A in Neoplastic Transformation of Human Embryonic Stem Cells (hESCs)
Bibliographic record
Abstract
Human embryonic stem cells (hESCs) are known for their indefinite self-renewal ability and pluripotent nature. However, during long-term culture, normal hESCs can undergo neoplastic transformation and acquire enhanced self-renewal ability and aberrant differentiation potential. These transformed-hESCs (trans-hESCs) exhibit high expression of the pluripotent gene, LIN28A. LIN28A, an RNA binding protein, is known: for its role in self-renewal of hESCs, as a reprogramming factor for generating induced-pluripotent stem cells and as a potent oncogene in several poorly differentiated, highly malignant human cancers. Despite its multiple functions, how LIN28A contributes to neoplastic transformation of normal hESCs is poorly understood. Our preliminary data demonstrate that following LIN28A knockdown, trans-hESCs display normal hESCs morphology consisting of both pluripotent colony cells surrounded by more differentiated fibroblast-like cells. Neural precursors derived from LIN28A knockdown trans-hESCs also revert back to a state of normal cell morphology and growth. Further analyses revealed that the expression levels of stage-specific embryonic antigen (SSEA3), OCT3/4 and NANOG decreases and are comparable to that observed in normal hESCs following LIN28A downregulation. Expression of miRNA targets of LIN28A such as let7i and mir125b was increased to levels seen in normal hESCs. These preliminary results indicate that LIN28A is a major contributing factor to neoplastic transformation of hESCs and that this process can be reversed by cellular “reprogramming”. This study will enhance our understanding of role of LIN28A in the transformation process in various human cancers thus, underscoring the value of hESCs and their neoplastic-derivatives as cellular and molecular model for studying tumor progression.
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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) | 0.003 | 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".