Macrophage Inflammatory Protein (MIP)-1alpha (CCL3) Is a Downstream Target of FGFR3 and RAS Signaling in Multiple Myeloma.
Bibliographic record
Abstract
Abstract The identification of the t(4;14) translocation in Multiple Myeloma (MM) provided the first indication that fibroblast growth factor 3 (FGFR3) could act as an oncogene. Several studies have assessed the potential of FGFR3 as a drug target and have shown that inhibition of FGFRs using tyrosine kinase inhibitors induces cell death of FGFR3 expressing MM cells. To clarify the signaling pathways implicated in FGFR3 dependent myeloma, we assessed gene expression changes associated with treatment of MM cell lines with three known small molecule FGFR inhibitors, PD173074, SU5402 and a third novel compound using Human U133_Plus2 arrays. In addition to describing the unique pharmacogenomic signals of each drug in myeloma, 845 differentially expressed genes, common to all three FGFR3 inhibitors, were identified. Cell cycle, DNA replication and ATP binding proteins were the most common (47%) functional classes of genes effected. Further validation and refinement of this gene list was conducted using FGFR3 siRNA inhibition and FGF ligand induction. 120 genes were altered between FGFR3 RNAi and scrambled control and 892 were induced by FGF ligand. Ten genes were commonly identified as significantly regulated by all 4 FGFR3 inhibitors and induced in the opposing direction by ligand. Of these macrophage inflammatory protein (MIP)-1alpha, and dual specific phosphatase 6 (DUSP6) were positively regulative while ANXA9, CR2, AL531683, ZNF589, AW274468, FRMD3, LTB and WDR42A were negatively regulated by FGFR3 signaling. Validating our findings, a feedback loop between FGFR/ERK/MAP kinase activation and DUSP6 has previously been described in the literature. MIP-1alpha however was the most significantly altered (12 fold) on array, and MIP-1alpha regulation in response to FGFR3 pathway stimulation was confirmed by flow cytometry and Western blot. Mining of publicly available array datasets on 174 MM patients significantly associated MIP1-alpha with FGFR3 expression (p=0.01). Of note down-regulation of MIP-1alpha was not observed following FGFR3 inhibition in MM cells with RAS mutations. Based on these, and previous findings, we hypothesized that MIP-1alpha was regulated by the FGFR3/ERK/MAP kinase pathway. Indeed, inhibition of ERK in FGFR inhibitor resistant cells with RAS mutations also led to down regulation of MIP-1alpha. Because of the recognized role of MIP1-alpha (CCL3) in survival and proliferation of MM cells and in MM bone disease, our observations raise the possibility that pharmacological inhibition of MIP-1 alpha may hold therapeutic promise in t(4;14) MM and may serve as a biomarker for successful FGFR3 or RAS signaling inhibition.
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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".