GREM1 Human
Description
BMP Antagonism
GREM1 binds BMPs (e.g., BMP2, BMP4), blocking their interaction with receptors and downstream Smad1/5/8 signaling. This antagonism modulates:
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Fibrosis: Promotes extracellular matrix deposition via TGF-β activation in renal and intestinal tissues .
Role in Cancer
GREM1 is overexpressed in multiple cancers, driving:
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Epithelial-to-Mesenchymal Transition (EMT): Enhances metastasis via TGF-β/SMAD signaling .
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Immunosuppression: Recruits Tregs, MDSCs, and M2 macrophages into tumor microenvironments .
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Angiogenesis: Supports tumor vascularization through VEGF/VEGFR2 pathways .
4. Research Findings in Disease
GREM1’s clinical significance spans cancer, fibrosis, and regenerative medicine:
Cancer Biomarker and Prognosis
Fibrosis and Tissue Damage
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Intestinal Fibrosis: Drives fibroblast proliferation via fatty acid oxidation (FAO) and MAPK activation .
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Intervertebral Disc Degeneration: Increased expression correlates with nucleus pulposus apoptosis and ECM remodeling .
Regenerative Applications
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Cartilage Engineering: Suppresses hypertrophy (e.g., collagen X, MMP13) in BMSC-derived constructs, enhancing matrix retention .
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Cardiac Progenitor Cells: Overexpression improves survival via ERK/NRF2 antioxidant signaling .
5. Therapeutic Implications
GREM1 targeting offers potential strategies:
Product Specs
Q&A
What is the functional role of GREM1 in human biology?
GREM1 functions as a secreted protein involved in extracellular matrix (ECM) organization, cell adhesion, and collagen metabolism. Research indicates that GREM1 regulates cellular activities including migration, differentiation, and proliferation through the ECM-receptor interaction pathway . Mechanistically, GREM1 can bind to growth factors, with studies showing it can regulate cancer cell lineage plasticity by binding to receptors such as FGFR1 . In normal tissues, GREM1 primarily acts in the extracellular environment, facilitating cell-to-cell communication and modulating the external cellular environment .
How is GREM1 expression typically detected in experimental settings?
Multiple complementary techniques are employed to quantify GREM1 expression:
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Transcriptomic analysis: RNA-seq data from public databases (TCGA, GEO) can be analyzed using the "limma" R package for differential expression
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Protein detection: Immunohistochemistry (IHC) with scoring systems (scores <2 considered low expression, ≥2 considered high expression)
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Serum quantification: ELISA for measuring circulating GREM1 levels in patient serum samples
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Cell line studies: Western blot analysis to confirm GREM1 overexpression or knockdown in experimental models
For rigorous validation, paired analysis of tumor tissues and adjacent non-tumor tissues is recommended to establish baseline expression levels .
What evidence exists for GREM1 as a prognostic indicator in different cancer types?
GREM1 demonstrates consistent prognostic value across multiple cancer types:
Pancreatic Ductal Adenocarcinoma (PDAC):
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High serum GREM1 (>1,117.8 pg/ml) associated with significantly shorter postoperative survival (p=0.0394)
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Mean survival time: 554.0 days in high-GREM1 group vs. 877.0 days in low-GREM1 group
Similar prognostic patterns have been observed in ER-negative breast cancer, colorectal cancer, and prostate cancer .
How does GREM1 expression correlate with clinicopathological features?
GREM1 expression shows strong associations with aggressive disease characteristics:
In Bladder Cancer:
In PDAC:
These correlations are consistent across multiple independent datasets (TCGA, GSE31684, GSE32894) and validation cohorts .
What is the diagnostic potential of GREM1 in cancer detection?
GREM1 shows promise as a diagnostic biomarker, particularly in PDAC:
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Serum GREM1 levels are significantly higher in PDAC patients compared to healthy controls (p<0.001)
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As a standalone marker, GREM1 demonstrates good diagnostic value (AUC=0.718, p<0.001)
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When combined with CA199, diagnostic efficacy substantially improves (AUC=0.914, p<0.001) compared to CA199 alone
This supports investigating GREM1 in multi-marker diagnostic panels rather than as a single biomarker.
Through which signaling pathways does GREM1 influence cancer progression?
Functional genomics analyses reveal GREM1 operates through multiple pathways:
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Extracellular matrix interactions: GO analysis shows GREM1 strongly associates with extracellular matrix organization, cell adhesion, and collagen catabolic processes
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Growth factor signaling: GREM1 participates in growth factor binding networks
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BMP antagonism: Functions through BMP-related pathways to influence tumor development
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Metabolism-related pathways: Demonstrated through KEGG enrichment analysis
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Immune regulation: GREM1 expression correlates with immunosuppressive microenvironment formation
These pathways collectively contribute to GREM1's role in tumor growth, invasion, and metastasis.
What is GREM1's role in the tumor microenvironment?
GREM1 appears to be a critical modulator of the tumor microenvironment:
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Stromal formation: High GREM1 expression correlates with increased stromal score in multiple cancers
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Immunosuppressive effects: Recruits immunosuppressive cells including T regulatory cells (Tregs), M2 macrophages, and myeloid-derived suppressor cells (MDSCs)
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T cell exhaustion: Associated with increased exhausted T cell populations in the tumor microenvironment
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Extracellular matrix remodeling: Functions primarily in exocellular environment, influencing matrix composition and organization
These findings suggest GREM1 creates a favorable microenvironment for tumor growth while suppressing anti-tumor immunity.
How does epithelial-mesenchymal transition (EMT) relate to GREM1 expression?
EMT appears to be a key mechanism through which GREM1 promotes cancer progression:
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EMT induced by GREM1 may contribute to aggressive clinical features in high-GREM1 patients
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This process likely facilitates tumor cell invasion and metastasis
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The blocking of matrix degeneration by GREM1-promoted stromal construction may contribute to EMT-related phenotypes
Further mechanistic studies are needed to fully characterize the GREM1-EMT axis in different cancer types.
What are the recommended bioinformatic methods for analyzing GREM1's biological functions?
Multiple computational approaches are used to characterize GREM1's functional role:
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Gene Ontology (GO) enrichment analysis: Identifies biological processes, molecular functions, and cellular components associated with GREM1
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KEGG pathway analysis: Reveals signaling pathways influenced by GREM1 expression
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Gene Set Enrichment Analysis (GSEA): Utilized to enrich REACTOME pathways (selection criteria: p<0.05 and FDR<25%)
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Correlation network analysis: Identifies genes positively and negatively correlated with GREM1 expression
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Immune infiltration analysis: Tools like TIMER 2.0 and CIBERSORT quantify immune cell populations correlated with GREM1 expression
For comprehensive understanding, researchers should employ multiple analytical approaches and validate findings across independent datasets.
What experimental models are suitable for studying GREM1 function?
Based on the reviewed literature, several experimental systems are appropriate:
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Cell lines: A549 and H1650 lung cancer cell lines and HBE (normal) cells have been used to study GREM1 overexpression and knockdown effects
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Patient-derived samples: Fresh tissue samples from surgical resections provide clinically relevant material for expression analysis
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Paired tumor/normal tissue analysis: Essential for establishing disease-specific expression patterns
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Serum analysis: For investigating GREM1 as a circulating biomarker in liquid biopsies
Western blot confirmation of GREM1 manipulation is critical when performing overexpression or knockdown studies in cellular models .
What statistical approaches should be used when analyzing GREM1 in clinical cohorts?
Robust statistical methodology is essential for GREM1 research:
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Survival analysis: Kaplan-Meier curves with log-rank tests for assessing prognostic value
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Cutoff determination: Receiver operating characteristic (ROC) analysis or X-tile program to establish clinically relevant expression thresholds
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Correlation analysis: Spearman or Pearson correlation for associations with clinical parameters
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Multiple testing correction: Benjamini-Hochberg False Discovery Rate (FDR) correction should be applied when analyzing differentially expressed genes and pathway enrichment
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Multivariate analysis: Logistic regression to identify independent associations between GREM1 and clinical features
Statistical significance is typically defined as a two-tailed p-value <0.05 .
How might GREM1 be exploited as a therapeutic target?
While direct therapeutic targeting strategies are still emerging, several approaches show promise:
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Combination therapy: GREM1 can predict responses to immunotherapy and chemotherapy in bladder cancer, suggesting potential synergistic targeting approaches
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Stromal targeting: Given GREM1's role in stromal formation, strategies disrupting GREM1-mediated stromal development could inhibit tumor growth
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Immune modulation: Counteracting GREM1's immunosuppressive effects could enhance anti-tumor immunity
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Growth factor pathway inhibition: Targeting GREM1's interaction with growth factor receptors like FGFR1
The secreted nature of GREM1 makes it potentially accessible for therapeutic targeting without requiring intracellular delivery systems.
What are the challenges in establishing GREM1 as a clinical biomarker?
Several challenges must be addressed before clinical implementation:
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Standardization: Establishing standardized cutoff values for "high" vs "low" GREM1 expression across different detection platforms
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Cancer-type specificity: GREM1's significance may vary between cancer types, requiring cancer-specific validation
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Sample size limitations: Current studies have relatively small cohorts (e.g., 82 PDAC patients with radical resection surgery)
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Methodological consistency: Different analytical techniques (IHC, serum analysis, mRNA expression) may yield different results
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Confounding factors: Some studies show inconsistent correlations with clinical parameters like age, sex, and smoking history
Larger, multi-center validation studies are needed to establish GREM1's clinical utility.
How does GREM1 interact with other established cancer biomarkers?
Emerging evidence suggests important interactions with other biomarkers:
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CA199 synergy: In PDAC, GREM1 combined with CA199 shows significantly improved diagnostic performance compared to either marker alone
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Tumor mutation burden (TMB): Analysis of correlation between GREM1 expression and TMB may provide insights into tumor biology
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Microsatellite instability (MSI): Relationship between GREM1 and MSI status is being investigated using the "maftools" package
Investigating these interactions may lead to more sophisticated multi-marker panels with improved clinical utility.
Product Science Overview
GREM1 is a secreted protein that binds directly to BMP dimers, preventing them from interacting with their receptors (BMPRII and BMPRI) and thus inhibiting BMP signaling . This inhibition is crucial for maintaining a balance in BMP signaling, which is necessary for proper organogenesis, tissue differentiation, and kidney development . In fact, Grem1 knockout mice exhibit severe developmental defects, including renal agenesis and limb malformations .
GREM1 has been implicated in various cancers, acting both as a tumor promoter and suppressor depending on the context . In breast cancer, for example, GREM1 is overexpressed in cancer-associated fibroblasts (CAFs), where it promotes cancer cell invasion and metastasis by inhibiting BMP signaling and activating other pathways such as EGFR and VEGFR . Conversely, in pancreatic cancer, GREM1 has been shown to promote an epithelial state, thereby inhibiting tumor growth and metastasis .
Human recombinant GREM1 is produced using recombinant DNA technology, which involves inserting the GREM1 gene into an expression vector and introducing it into a host cell, such as E. coli or mammalian cells. The host cells then produce the GREM1 protein, which can be purified and used for various research and therapeutic applications. Recombinant GREM1 is particularly useful for studying its role in BMP signaling and its implications in diseases like cancer .
Given its dual role in cancer, GREM1 is a potential target for therapeutic interventions. Inhibiting GREM1 in cancers where it acts as a tumor promoter could help in reducing cancer cell invasion and metastasis. Conversely, enhancing GREM1 activity in cancers where it acts as a tumor suppressor could inhibit tumor growth .
