MMP1 (24-207) Human

What is the biological significance of the MMP1 (24-207) fragment compared to full-length MMP1?

The MMP1 (24-207) fragment represents a specific region of the human MMP1 protein that contains functional domains critical for its enzymatic activity. Full-length MMP1 is located on chromosome 11q22.3 and belongs to the MMP family responsible for degrading extracellular matrix components . While the full protein is involved in various biological processes including cancer cell development, growth, proliferation, apoptosis, invasion, metastasis, angiogenesis, and immune surveillance , the 24-207 fragment likely contains portions of the catalytic domain without the propeptide domain (which maintains enzyme latency) and the hemopexin-like domain (involved in substrate recognition).

This fragment represents a research tool that allows investigation of structure-function relationships within the MMP1 catalytic region without interference from regulatory domains. When working with this fragment, researchers should note that its catalytic properties may differ from the full-length protein due to the absence of regulatory elements.

How does MMP1 expression regulation differ across tissue types and pathological states?

MMP1 expression is tightly regulated at multiple levels to prevent excessive tissue degradation in normal physiological states. The gene's expression is controlled through several mechanisms:

• Transcriptional regulation: The MMP1 promoter contains multiple polymorphic sites, such as the -1607 G ins/del polymorphism that creates an Ets binding site increasing promoter activity in both fibroblasts and melanoma cells .

• Genetic variations: Seven SNPs in the MMP1 promoter region have been identified (-1607 G ins/del, -839 G>A, -755 T>G, -519 A>G, -422 A>T, -340 A>G, and -320 T>C) that influence expression levels .

• Epigenetic control: DNA methylation at specific sites (e.g., cg25320665, cg14543953) modulates MMP1 expression in hepatocellular carcinoma .

In pathological states, particularly cancer, MMP1 often shows elevated expression and activation. Studies have demonstrated significantly increased MMP1 expression in melanoma, lung cancer, and hepatocellular carcinoma compared to normal tissues . This dysregulation contributes to tumor invasion and metastasis, with higher expression levels correlating with poor prognosis in multiple cancer types .

What experimental controls are essential when working with recombinant MMP1 fragments?

When working with recombinant MMP1 (24-207) Human, implement these essential controls:

• Activity verification: Compare enzymatic activity against well-characterized substrates with full-length MMP1 to understand functional differences.

• Specificity controls: Include specific MMP1 inhibitors to confirm that observed effects are truly MMP1-dependent and not artifacts.

• Expression level normalization: When comparing effects across different experimental conditions, carefully normalize expression levels, especially when examining samples from individuals with different MMP1 polymorphisms .

• Negative controls: Include enzymatically inactive mutants (e.g., catalytic site mutations) to distinguish between proteolytic and non-proteolytic functions.

• Physiological relevance controls: Compare results from the fragment to those from full-length MMP1 to assess whether the findings reflect normal biological processes or are fragment-specific phenomena.

These controls ensure robust and reproducible results when working with this specific MMP1 fragment in research settings.

What are the most effective techniques for quantifying MMP1 expression in clinical samples?

Based on the literature, researchers should consider multiple complementary approaches for comprehensive MMP1 quantification:

• Protein level detection:

  • ELISA: Used successfully for measuring MMP1 concentrations in biological fluids like cerebrospinal fluid

  • Western blotting: Employed for detecting MMP1 protein expression in tissue samples from hepatocellular carcinoma patients

  • Immunohistochemistry: For visualizing spatial distribution within tissues

• Transcript level analysis:

  • RT-qPCR: Implemented for determining MMP1 mRNA expression levels in paired tumor and adjacent tissues

  • Transcriptomic analysis: Utilizing RNA-seq data from databases like TCGA for large-scale expression profiling

• Activity measurement:

  • Zymography: For detecting functional MMP1 activity

  • Fluorogenic substrate assays: For quantitative assessment of enzymatic activity

For clinical applications, researchers should standardize procedures across samples and include appropriate controls. The combined use of protein and transcript measurements is particularly valuable, as post-transcriptional regulation may cause discrepancies between mRNA levels and protein abundance.

How should genotyping experiments be designed to investigate MMP1 polymorphisms and their clinical significance?

Based on successful approaches in the literature, a comprehensive MMP1 genotyping study should include:

• Study design considerations:

  • Hospital-based case-control design with appropriate matching for age, sex, and ethnicity

  • Sufficient sample size calculation based on expected effect sizes

  • Collection of comprehensive demographic and risk factor data for covariate adjustment

• SNP selection criteria:

  • Focus on common variants with minor allele frequency ≥5% in the study population

  • Include functionally relevant polymorphisms like the -1607 G ins/del (rs1799750)

  • Consider haplotype tagging SNPs to efficiently capture genetic variation

• Methodological verification:

  • Test for Hardy-Weinberg equilibrium in control populations to validate genotyping quality

  • Perform linkage disequilibrium analysis to understand relationships between SNPs

  • Consider both individual SNP and haplotype analyses for comprehensive assessment

• Statistical analysis approaches:

  • Conduct stratification analyses to identify effect modification by relevant risk factors

  • Examine gene-environment interactions, particularly with known risk factors (e.g., smoking in lung cancer studies)

  • Analyze gene dosage effects, as demonstrated by the dose-response relationship observed between number of risk alleles and melanoma risk (P trend = 0.0002)

This structured approach will maximize the reliability and clinical relevance of MMP1 polymorphism studies.

What cellular models best recapitulate MMP1 functional dynamics for in vitro studies?

When selecting cellular models for MMP1 research, consider these evidence-based recommendations:

• Cancer models with documented MMP1 relevance:

  • Melanoma cell lines: Demonstrated elevated MMP1 expression and association with invasiveness

  • Lung cancer cells: Showed MMP1 overexpression with relevance to early-onset disease

  • Hepatocellular carcinoma lines: Used successfully for experimental validation of MMP1 expression studies

• Model selection considerations:

  • Baseline MMP1 expression levels: Verify detectable expression through preliminary assays

  • Genetic background: Consider models with different MMP1 polymorphism profiles to study genetic effects

  • Microenvironmental context: 3D culture systems better recapitulate extracellular matrix interactions relevant to MMP1 function

• Experimental manipulation approaches:

  • Genetic modification: CRISPR/Cas9 editing for knockout/knockin studies

  • Pharmacological modulation: MMP inhibitors at various selectivity levels

  • Expression modulation: Inducible systems for controlled MMP1 expression

• Validation approaches:

  • Compare in vitro findings with patient-derived samples

  • Verify with multiple cell lines to ensure findings aren't cell-line specific

  • Correlate with clinical data when possible

These considerations ensure that cellular models provide physiologically relevant insights into MMP1 biology and pathological roles.

How does MMP1 mechanistically contribute to cancer progression and metastasis?

MMP1 facilitates multiple aspects of cancer progression through diverse mechanisms:

• Extracellular matrix degradation:

  • As an interstitial collagenase, MMP1 degrades fibrillar collagens in the extracellular matrix

  • This degradation creates pathways for tumor cell invasion and migration

  • Studies in melanoma have linked MMP1 expression with deep invasiveness

• Signaling pathway modulation:

  • MMP1 activates protease-activated receptors (PARs)

  • This activation triggers pro-growth and pro-survival signaling cascades

  • Contributes to cancer cell proliferation and resistance to apoptosis

• Tumor microenvironment remodeling:

  • Facilitates angiogenesis by liberating matrix-bound growth factors

  • Modulates immune surveillance by affecting immune cell recruitment and function

  • Contributes to formation of pre-metastatic niches

• Gene expression effects:

  • Polymorphisms in the MMP1 promoter, particularly the -1607 G ins/del, create an Ets binding site that increases transcription in melanoma cells

  • The variant -422TT and -320CC genotypes were associated with significantly increased melanoma risk (OR = 1.50 and OR = 1.72, respectively)

  • In lung cancer, MMP1 SNPs rs1938901, rs193008, and rs996999 showed significant associations with early-onset disease

These multifaceted roles make MMP1 a central player in cancer progression across multiple tumor types.

What is the prognostic value of MMP1 expression in different cancer types?

MMP1 expression has demonstrated significant prognostic relevance across multiple cancer types:

These findings support MMP1's utility as a prognostic biomarker, though standardized assessment methods are needed for clinical implementation.

How does MMP1 interact with the tumor immune microenvironment?

The relationship between MMP1 and the tumor immune microenvironment represents an important frontier in cancer research:

• Immune surveillance modulation:

  • MMP1 influences immune surveillance mechanisms as evidenced by its multifunctional roles in cancer progression

  • By degrading extracellular matrix components, MMP1 can affect immune cell infiltration and function within the tumor microenvironment

• Research methodologies:

  • The TIMER database has been employed to systematically evaluate differential gene correlation and tumor-immune infiltrate analysis across cancer types

  • This approach enables examination of MMP1's relationships with specific immune cell populations

• Hepatocellular carcinoma findings:

  • Comprehensive bioinformatic analysis of MMP1 in hepatocellular carcinoma specifically focused on the tumor-immune microenvironment

  • This research explored how MMP1 expression correlates with infiltration of various immune cell types

• Therapeutic implications:

  • Understanding MMP1's immune-related functions opens avenues for combination therapies

  • Potential exists for combining MMP1 inhibitors with immunotherapeutic approaches

  • MMP inhibitors showed improved outcomes in experimental models of infection , suggesting potential immune-modulating properties

These interactions highlight the complex role of MMP1 beyond matrix degradation and suggest potential for targeting MMP1 in immunomodulatory therapeutic strategies.

Which MMP1 genetic variants demonstrate the strongest disease associations?

Comprehensive genetic analyses have identified several MMP1 variants with significant disease associations:

• Promoter polymorphisms in melanoma:

  • The -1607 G ins/del (rs1799750) creates an Ets binding site that increases transcription in melanoma cells

  • Variant -422TT genotype associated with significantly increased melanoma risk (OR = 1.50, 95% CI = 1.11-2.03)

  • Variant -320CC genotype associated with significantly increased melanoma risk (OR = 1.72, 95% CI = 1.05-2.81)

  • The number of risk alleles across multiple polymorphisms showed a dose-response relationship with melanoma risk (P trend = 0.0002)

• Early-onset lung cancer associations:

  • rs1938901 showed significant association (P = 0.0089)

  • rs193008 demonstrated significant effect (P = 0.0108)

  • rs996999 showed association (P = 0.0459), though significance vanished after correction for multiple testing

  • For these SNPs, the major allele was associated with increased risk with ORs between 1.2 and 1.3

• Haplotype effects:

  • The haplotypes Gdel-A-G-A-T-G-T and G-G-G-A-T-A-T were associated with significantly increased melanoma risk (ORs = 1.56 and 2.13, 95% CIs = 1.02-2.38 and 1.22-3.70, respectively)

  • Haplotype analysis in lung cancer supported individual SNP findings, especially in subgroups with high smoking intensity

• Environmental interactions:

  • The associations between MMP1 polymorphisms and melanoma risk were modified by sun-exposure related risk factors

  • Smoking intensity modified genetic effects in lung cancer studies

These findings highlight the complex genetic architecture of MMP1-related disease risk and the importance of considering both individual variants and their combinations.

How do epigenetic mechanisms regulate MMP1 expression in healthy and disease states?

Epigenetic regulation represents an important layer of MMP1 expression control:

• DNA methylation analysis:

  • The MEXPRESS tool has been employed to visualize DNA methylation patterns between MMP1 gene at various probes (e.g., cg25320665, cg14543953) and hepatocellular carcinoma

  • These analyses revealed relationships between methylation status and gene expression

• Methylation-expression correlations:

  • Specific CpG sites show differential methylation between tumor and normal tissues

  • The methylation status correlates with MMP1 expression levels, providing mechanistic insight into expression dysregulation in cancer

• Cancer-specific patterns:

  • In hepatocellular carcinoma, comprehensive bioinformatic analysis revealed distinct methylation profiles associated with MMP1 expression

  • These patterns may contribute to the aberrant expression observed in tumor tissues

• Methodological approaches:

  • Combined analysis of expression data with methylation profiles

  • Statistical assessment using Pearson correlation coefficient and Benjamini–Hochberg methods for multiple testing correction

  • Integration with clinical outcomes to understand prognostic relevance

Understanding these epigenetic mechanisms provides opportunities for developing novel biomarkers and potentially therapeutic approaches targeting epigenetic modifiers to normalize MMP1 expression in disease states.

What molecular pathways interact with MMP1 in disease pathogenesis?

MMP1 functions within complex molecular networks that drive disease processes:

• Protein-protein interaction networks:

  • The STRING database has been used to construct MMP1-related protein-protein interaction networks

  • These networks reveal functional protein associations relevant to MMP1 biology

• Pathway enrichment analyses:

  • Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses identify biological processes associated with MMP1-related genes

  • These analyses encompass biological process (BP), cellular component (CC), and molecular function (MF) categories

• Differential gene expression:

  • DESeq2 platform has been employed to identify MMP1-related/similar genes in hepatocellular carcinoma

  • Genes with log2FoldChange > 2/< -2 and p-value < 0.05 were selected for further analysis

• Functional categorization:

  • Identified pathways can be visualized using tools like "ggplot2", "clusterProfiler", and "Goplot" packages in R

  • These visualizations help contextualize MMP1's role in broader biological processes

Understanding these pathway interactions provides a systems-level view of MMP1 biology and identifies potential points for therapeutic intervention beyond direct MMP1 targeting.

What novel therapeutic strategies target MMP1 in cancer and inflammatory diseases?

While traditional MMP inhibitors have shown limited clinical success due to broad specificity, emerging approaches offer new potential:

• Domain-specific targeting:

  • The MMP1 (24-207) fragment contains key functional regions that could be selectively targeted

  • Structure-based drug design focusing on unique binding pockets within this region may yield more selective inhibitors

  • Peptide-based inhibitors designed to compete with specific MMP1 substrates relevant to pathogenesis

• Genetic approaches:

  • Antisense oligonucleotides or siRNAs targeting MMP1 mRNA

  • CRISPR-based approaches to modulate MMP1 expression

  • Targeting specific MMP1 polymorphisms associated with increased disease risk

• Indirect modulation strategies:

  • Targeting upstream regulators of MMP1 expression

  • Modifying epigenetic control mechanisms identified through methylation studies

  • Inhibiting specific MMP1-protein interactions identified through protein-protein interaction networks

• Combination therapies:

  • MMP inhibitors showed improved outcomes in experimental models of infection

  • Combining MMP1-targeted approaches with immunotherapies based on MMP1's role in the tumor-immune microenvironment

  • Stratifying patients based on MMP1 genetic profiles for personalized treatment approaches

These strategies represent promising avenues for overcoming limitations of previous MMP-targeting approaches.

How can systems biology approaches enhance our understanding of MMP1 in complex diseases?

Systems biology offers powerful frameworks for understanding MMP1's multifaceted roles:

• Multi-omics integration:

  • Combining genomic data on MMP1 polymorphisms with transcriptomic, proteomic, and epigenomic data

  • Integrating clinical outcomes to create comprehensive disease models

  • Correlating MMP1 expression with immune cell infiltration data from resources like TIMER

• Network analysis approaches:

  • Protein-protein interaction networks constructed using databases like STRING

  • Pathway enrichment analyses using GO and KEGG frameworks

  • Identification of key nodes and potential therapeutic targets within MMP1-centered networks

• Computational modeling:

  • Predicting functional impacts of genetic variants through in silico approaches

  • Modeling MMP1's contribution to dynamic processes like cancer progression

  • Simulating effects of potential therapeutic interventions

• Data visualization and interpretation:

  • Tools like "ggplot2", "clusterProfiler", and "Goplot" packages in R enable effective visualization of complex relationships

  • These visualizations help identify patterns and generate hypotheses for experimental validation

By integrating diverse data types, systems biology approaches can reveal emergent properties and unexpected relationships in MMP1 biology that may not be apparent from reductionist approaches.

What are the most promising biomarker applications for MMP1 in precision medicine?

MMP1 holds significant potential as a biomarker across multiple clinical contexts:

• Risk stratification:

  • Genotyping MMP1 polymorphisms for cancer risk assessment, particularly the -1607 G ins/del, -422 A>T, and -320 T>C variants in melanoma

  • The rs1938901, rs193008, and rs996999 variants for early-onset lung cancer risk

  • Haplotype analysis for improved risk prediction beyond single variants

• Diagnostic applications:

  • Differential MMP1 expression between tumor and adjacent normal tissues in hepatocellular carcinoma and other cancers

  • CSF MMP1 levels in central nervous system infections

• Prognostic indicators:

  • Expression levels as predictors of survival outcomes (OS, DSS, PFI, PFS) in hepatocellular carcinoma

  • Cancer patients with tumors expressing higher levels of MMP1 consistently show poor prognosis

• Treatment response prediction:

  • Potential for predicting response to MMP inhibitors or other targeted therapies

  • Correlation with immune infiltration patterns may predict immunotherapy response

• Monitoring applications:

  • Serial measurements of MMP1 levels to track disease progression or treatment response

  • Liquid biopsy approaches for non-invasive monitoring

The combined use of genetic, expression, and activity-based MMP1 biomarkers could significantly enhance precision medicine approaches across multiple disease contexts.

What are the key unresolved questions in MMP1 research?

Despite significant advances, several critical questions remain in MMP1 research:

• Structure-function relationships:

  • How do specific domains within MMP1, including the 24-207 region, contribute to its diverse biological functions?

  • What structural features determine substrate specificity and inhibitor binding?

• Regulatory mechanisms:

  • How do genetic, epigenetic, and environmental factors interact to regulate MMP1 expression in different contexts?

  • What are the feedback mechanisms that control MMP1 activity in normal physiology?

• Disease specificity:

  • Why does MMP1 show differential associations with various cancer types and other diseases?

  • How do tissue-specific microenvironments influence MMP1's pathological roles?

• Therapeutic targeting:

  • How can we develop selective MMP1 inhibitors without the side effects seen with broad-spectrum MMP inhibitors?

  • What patient populations might benefit most from MMP1-targeted therapies?

Addressing these questions will require innovative approaches combining structural biology, systems biology, genetic epidemiology, and translational research methodologies.