Targeting FGFR1 by β,β-dimethylacrylalkannin suppresses the proliferation of colorectal cancer in cellular and xenograft models
Bibliographic record
Abstract
BACKGROUND: Colorectal cancer (CRC) continues to be a major global health challenge, ranking as a top cause of cancer-related mortality. Alarmingly, the five-year survival rate for CRC patients hovers around a mere 10-30 %. The disruption of fibroblast growth factor receptor (FGFRs) signaling pathways is significantly implicated in the onset and advancement of CRC, presenting a promising target for therapeutic intervention in CRC management. Further investigation is essential to comprehensively elucidate FGFR1's function in CRC and to create potent therapies that specifically target FGFR1. PURPOSE: This study aims to demonstrate the oncogenic role of FGFR1 in colorectal cancer and to explore the potential of β,β-dimethylacrylalkannin (β,β-DMAA) as a therapeutic option to inhibit FGFR1. METHODS: In this research, we employed a comprehensive suite of techniques including tissue array, kinase profiling, computational docking, knockdown assay to predict and explore the inhibitor of FGFR1. Furthermore, we utilized kinase assay, pull-down, cell proliferation tests, and Patient derived xenograft (PDX) mouse models to further investigate a novel FGFR1 inhibitor and its impact on the growth of CRC. RESULTS: In our research, we discovered that FGFR1 protein is markedly upregulated in colorectal cancer tissues, suggesting a significant role in regulating cellular proliferation, particularly in patients with colorectal cancer. Furthermore, we conducted a computational docking, kinase profiling analysis, simulation and identified that β,β-DMAA could directly bind with FGFR1 within ATP binding pocket domain. Cell-based assays confirmed that β,β-DMAA effectively inhibited the proliferation of colon cancer cells and also triggered cell cycle arrest, apoptosis, and altered FGFR1-mediated signaling pathways. Moreover, β,β-DMAA effectively attenuated the development of PDX tumors in mice that were FGFR1-positive, with no notable toxicity observed. In summary, our study highlights the pivotal role of FGFR1 in colorectal cancer, suggesting that inhibiting FGFR1 activity could be a promising strategy for therapeutic intervention. We present strong evidence that targeting FGFR1 with β,β-DMAA is a viable approach for the management of colorectal cancer. Given its low toxicity and high efficacy, β,β-DMAA, as an FGFR1 inhibitor, warrants further investigation in clinical settings for the treatment of FGFR1-positive tumors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".