RBM5 reduces small cell lung cancer growth, increases cisplatin sensitivity and regulates key transformation-associated pathways
Bibliographic record
Abstract
Small cell lung cancer (SCLC) is the most aggressive type of lung cancer, with almost 95% of patients succumbing to the disease. Although RBM5 , a tumor suppressor gene, is downregulated in the majority of lung cancers, its role in SCLC is unknown. Using the GLC20 SCLC cell line, which has a homozygous deletion encompassing the RBM5 gene locus, we established stable RBM5 expressing sublines and investigated the effects of RBM5 re-expression. Transcriptome and target identification studies determined that RBM5 directly regulates the cell cycle and apoptosis in SCLC cells, as well as significantly downregulates other important transformation-associated pathways such as angiogenesis and cell adhesion. RNA sequencing of paired non-tumor and tumor SCLC patient specimens showed decreased RBM5 expression in the tumors, and expression alterations in the majority of the same pathways that were altered in the GLC20 cells and sublines. Functional studies confirmed RBM5 expression slows SCLC cell line growth, and increases sensitivity to the chemotherapy drug cisplatin. Overall, our work demonstrates the importance of RBM5 expression to the non-transformed state of lung cells and the consequences of its deletion to SCLC development and 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".