LIN28B promotes the development of neuroendocrine prostate cancer
Bibliographic record
Abstract
Therapy-induced neuroendocrine prostate cancer (t-NEPC) is a highly aggressive subtype of prostate cancer with poor patient survival. Emerging evidence indicates that t-NEPC can develop when prostate adenocarcinoma cells acquire cancer stem-like cell signaling in the presence of androgen receptor inhibition, followed by redifferentiation toward neuroendocrine lineage and subsequent t-NEPC progression. Whether the stem-like signaling is controlled by the core pluripotency stem cell genes (e.g., LIN28 and SOX2) remains unknown. Here, we report that the transcription of the LIN28B isoform and SOX2 were co-upregulated in t-NEPC patient tumors, patient-derived xenografts, transgenic mice, and cell models. Immunohistochemistry validated that LIN28B and SOX2 protein expression were elevated in t-NEPC patient biopsies. Using prostate adenocarcinoma and t-NEPC cell models, we demonstrated that LIN28B induced a stem-like gene network, neuroendocrine biomarkers, and neuroendocrine cell morphology. LIN28B depletion by CRISPR inhibited t-NEPC tumorigenesis and xenograft growth. These LIN28B functions were mediated mainly through the suppression of let-7 miRNA expression, resulting in de-repression of the transcription factor HMGA2 and HMGA2-mediated SOX2 expression. This study revealed a mechanism by which t-NEPC can develop through the LIN28B/let-7/SOX2 axis that regulates a cancer cell stem-like gene network, highlighting LIN28B as a potential therapeutic target in t-NEPC.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".