Bone morphogenetic protein 2 (BMP2) induces growth suppression and enhances chemosensitivity of human colon cancer cells
Bibliographic record
Abstract
BACKGROUND: Molecular profiling of colorectal cancer (CRC) based on global gene expression has revealed multiple dysregulated signalling pathways associated with drug resistance and poor prognosis. However, the role of BMP2 signaling in CRC is not fully characterised. METHODS: Bioinformatics data analysis were conducted on the GSE21510 dataset. Leniviral technology was utilized to stably express BMP2 in the HCT116 CRC model. Gene expression profiling was conducted using Agilent microarray platform while data normalization and bioinformatics were conducted using GeneSpring software. Changes in gene expression were assessed using qRT-PCR. AlamarBlue assay was used to assess cell viability in vitro. In vivo experiments were conducted using SCID mice. RESULTS: Our data revealed frequent downregulation of BMP2 in primary CRC tissues. Additionally, interrogation of publically available gene expression datasets revealed significant downregulation of BMP2 in metastatic recurrent compared to non-metastatic cancer (p = 0.02). Global gene expression analysis in CRC cells over-expressing BMP2 revealed multiple dysregulated pathways mostly affecting cell cycle and DNA damage response. Concordantly, lentiviral-mediated re-expression of BMP2 inhibited HCT116 CRC growth, sphere formation, clonogenic potential, cell migration, and sensitized CRC cells to 5-fluorouracil (5-FU) in vitro. Additionally, BMP2 inhibited CRC tumor formation in SCID mice. CONCLUSIONS: Our data revealed an inhibitory role for BMP2 in CRC, suggesting that restoration of BMP2 expression could be a potential therapeutic strategy for CRC.
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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 | 0.000 | 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".