Recombinant Human Hepatocyte growth factor receptor (MET), partial (Active)

What is the functional significance of c-Met receptor in liver regeneration?

The c-Met receptor plays an indispensable role in liver regeneration and repair processes. After partial hepatectomy (PHx), c-Met activation occurs rapidly, with tyrosine phosphorylation beginning within 5 minutes and peaking at approximately 60 minutes post-surgery . This activation initiates critical signaling cascades that drive hepatocyte proliferation.

Functional studies have demonstrated that mice lacking c-Met experience liver necrosis, jaundice, delayed regeneration, and significantly higher mortality rates compared to wild-type controls . The HGF/c-Met signaling pathway activates multiple downstream pathways essential for regeneration, including JAK/STAT3, PI3K/Akt/NF-κB, and Ras/Raf pathways, which collectively initiate cell proliferation programs .

Researchers investigating liver regeneration should note that c-Met signaling is particularly critical during the initial stages of regeneration, making this receptor an essential component in experimental models of liver repair and regeneration.

How does c-Met receptor activation influence intracellular signaling cascades?

Upon HGF binding, c-Met undergoes tyrosine phosphorylation, triggering multiple downstream signaling pathways that regulate cellular responses. The activation sequence begins with:

• HGF binding and c-Met tyrosine residue phosphorylation

• Induction of Wnt-independent nuclear translocation of β-catenin

• Subsequent internalization and degradation of c-Met via the ubiquitin-proteasome pathway

• Activation of multiple signaling branches

Key pathways activated by HGF/c-Met include:

The Ras pathway is particularly significant, as c-Met activates ERK1/2 (two mitogen-activated protein kinases) to transmit mitotic signals. Research has demonstrated that in c-Met mutant mice, phosphorylation of ERK1/2 is absent, directly correlating with impaired liver regeneration . This indicates that ERK1/2 activation is completely dependent on c-Met signaling during the liver regeneration process.

How can researchers differentiate between active and inactive forms of recombinant c-Met?

Researchers can differentiate between active and inactive forms of recombinant c-Met through several methodological approaches:

Phosphorylation Status Assessment:
The most direct method involves detecting phosphorylated tyrosine residues using phospho-specific antibodies through Western blotting or immunoprecipitation. Active c-Met shows phosphorylation at specific tyrosine residues, particularly in the kinase domain.

Functional Assays:
Measuring downstream pathway activation through ERK1/2 phosphorylation provides an excellent functional readout. Studies have shown that during liver regeneration, ERK1/2 phosphorylation is entirely dependent on c-Met activation . Researchers can use selective inhibitors like SGX523 to confirm c-Met-specific effects, as this compound blocks c-Met phosphorylation and was shown to eliminate enhanced liver regeneration in experimental models .

Structural Analysis:
The partial active form typically refers to a truncated version containing the kinase domain, which can be distinguished from full-length receptor through molecular weight analysis or domain-specific antibodies.

When planning experiments involving recombinant c-Met, researchers should include appropriate controls to verify the activation state and consider the timing of examination, as c-Met is rapidly degraded after activation through the ubiquitin-proteasome pathway .

How do age-related changes affect c-Met expression and function in regenerative models?

Age significantly impacts c-Met expression and function, with important implications for regenerative research. Clinical studies involving 130 patients who underwent hepatectomy revealed that both HGF and c-Met expression levels were substantially lower in older patients compared to younger cohorts .

This age-dependent decline in c-Met expression correlates directly with regenerative capacity. Six months after partial hepatectomy, liver volume increase was significantly greater in younger patients than in elderly individuals . This finding suggests that age is an important variable to control in experimental designs involving c-Met and liver regeneration.

Researchers studying regenerative processes should:

• Stratify experimental groups by age

• Consider age as a covariate in statistical analyses

• Potentially adjust dosing of recombinant HGF in older subjects to account for reduced receptor availability

• Examine age-dependent changes in downstream signaling pathways

These considerations are essential for accurate interpretation of data from regenerative models and may help explain variability in experimental outcomes between different age groups.

What methodological approaches can optimize detection of c-Met activation in complex tissue samples?

Detecting c-Met activation in complex tissue samples requires sophisticated methodological approaches to ensure specificity and sensitivity:

Tissue-Specific Phospho-Profiling:
For heterogeneous tissue samples, researchers should employ phospho-specific antibodies against multiple c-Met tyrosine residues, as different residues may show variable phosphorylation patterns depending on activation context. Post-partial hepatectomy, c-Met phosphorylation follows a specific temporal pattern, beginning within 5 minutes and peaking at 60 minutes .

Multiplexed Analysis:
Combining immunohistochemistry with digital imaging allows spatial mapping of activated c-Met within specific cell populations. This approach is particularly valuable in liver samples where different cell types (hepatocytes, stellate cells, etc.) show differential c-Met expression and activation patterns.

Downstream Signaling Verification:
Confirmation of c-Met activity should include assessment of multiple downstream pathways. During liver regeneration, c-Met activates JAK/STAT3, PI3K/Akt/NF-κB, and Ras/Raf pathways . Examining these multiple readouts provides more robust confirmation of functional c-Met activation.

Temporal Considerations:
Researchers must consider the rapid dynamics of c-Met activation and degradation. After activation, c-Met is promptly internalized and degraded via the ubiquitin-proteasome pathway , necessitating careful timing of sample collection in experimental designs.

When analyzing complex tissue samples, these methodological refinements help overcome common challenges such as cell-type heterogeneity, temporal signaling dynamics, and activation pathway crosstalk.

How do regulatory non-coding RNAs influence c-Met expression and signaling?

Recent research has highlighted the significant role of non-coding RNAs in regulating the HGF/c-Met axis during liver regeneration. These regulatory elements add an important layer of post-transcriptional control that researchers must consider when studying c-Met function.

The research review indicates that non-coding RNAs participate in regulating liver regeneration through the HGF/c-Met pathway, though specific mechanisms were not detailed in the search results . This represents an emerging area of investigation that connects epigenetic regulation with growth factor receptor signaling.

For researchers investigating c-Met regulation, experimental approaches should include:

• Profiling of microRNAs predicted to target c-Met mRNA

• Functional validation using antisense oligonucleotides or CRISPR-based approaches

• Assessment of long non-coding RNAs that may interact with the c-Met promoter region

• Integration of non-coding RNA expression data with c-Met protein levels and activation status

Understanding these regulatory relationships may reveal new opportunities for modulating c-Met signaling in research and therapeutic applications, particularly in contexts where direct receptor targeting has proven challenging.

What are the optimal conditions for studying recombinant human c-Met activity in in vitro models?

Establishing optimal conditions for studying recombinant human c-Met activity in vitro requires careful attention to several experimental parameters:

Activation Conditions:
For studying c-Met activation, researchers should note that HGF binding to c-Met drives phosphorylation of c-Met tyrosine residues, followed by activation of downstream signaling . In experimental designs, both single-chain HGF and two-chain (active form) HGF should be considered, as they exist in different proportions in normal tissue with single-chain being dominant in normal liver .

Temporal Dynamics:
C-Met activation occurs rapidly, with phosphorylation beginning within minutes of stimulation. Studies should include early time points (5-60 minutes) to capture the peak phosphorylation that occurs at approximately 60 minutes post-stimulation . Additionally, researchers should account for the subsequent rapid internalization and degradation of c-Met through the ubiquitin-proteasome pathway .

Environmental Factors:
Research has shown that hypoxic conditions dramatically decrease HGF expression in hepatic stellate cells and c-Met expression in hepatocytes . Therefore, oxygen tension should be carefully controlled and reported in experimental protocols.

Pathway Specificity Controls:
To confirm c-Met-specific effects, selective inhibitors like SGX523 should be employed as controls. This compound blocks c-Met phosphorylation and has been shown to eliminate enhanced effects on liver regeneration in experimental models .

These considerations will help researchers develop robust protocols for studying recombinant human c-Met activity that account for the complex dynamics of receptor activation, signaling, and degradation.

How can researchers effectively evaluate crosstalk between c-Met and other signaling pathways?

Evaluating crosstalk between c-Met and other signaling pathways requires sophisticated experimental approaches that can distinguish direct c-Met effects from secondary pathway interactions:

Sequential Inhibition Strategy:
Researchers should employ selective inhibitors in sequence to delineate pathway hierarchies. For example, studies have demonstrated that PPARγ regulates liver regeneration by influencing the HGF/c-Met/ERK1/2 pathway. The PPARγ antagonist GW9662 was shown to accelerate liver regeneration, but this effect was eliminated when c-Met phosphorylation was blocked by SGX523 . This sequential inhibition approach helps establish causality in signaling networks.

Pathway Convergence Analysis:
Several pathways interact with c-Met signaling. For instance, the bone morphogenetic protein (BMP)9 and HGF/c-Met signaling axes establish a signal crossover through ALK1 by modulating SMAD1 (pro-survival) and p38MAPK (pro-apoptotic) pathways . Researchers should design experiments that can track multiple pathway components simultaneously through techniques like multiplexed phospho-flow cytometry or mass cytometry.

Transcription Factor Activity Mapping:
Downstream effects of pathway crosstalk can be evaluated through transcription factor activity assays. Research has shown that the cellular transcription factor late SV40 factor (LSF) regulates osteopontin, which then activates c-Met through interaction with CD44 . Monitoring transcription factor activity provides insight into the functional outcomes of pathway interactions.

These methodological approaches enable researchers to construct more complete models of how c-Met integrates with broader cellular signaling networks, particularly in complex biological processes like liver regeneration and response to injury.

What considerations are important when translating c-Met research from rodent models to human applications?

Translating c-Met research from rodent models to human applications requires careful attention to several key considerations:

Species-Specific Differences:
While the HGF/c-Met signaling pathway is conserved across mammals, there are important species-specific differences in expression patterns, regulatory mechanisms, and downstream effectors. In the PHx model, liver regeneration in rodents shows complete recovery in volume and mass within one week , but this timeline differs in humans.

Age-Dependent Variation:
Clinical studies have demonstrated significant age-related differences in HGF and c-Met expression. In a study of 130 patients undergoing hepatectomy, older patients showed substantially lower expression of both HGF and c-Met compared to younger patients, correlating with reduced regenerative capacity . Age stratification is therefore critical when designing translational studies.

Therapeutic Formulation Considerations:
Engineered forms of HGF have shown promise in translational research. For example, 1K1, a synthetic small molecule derived from the naturally occurring HGF fragment NK1, demonstrates anti-fibrotic properties and promotes liver regeneration in rodents with better stability and easier production characteristics than native HGF . Such engineered variants may bridge the gap between basic research and clinical application.

Activation and Delivery Methods:
The method of delivering recombinant proteins affects outcomes. Studies showed that administering recombinant human HGF-activator via the portal vein significantly increased liver regeneration rates compared to control groups . Administration route and activation state of recombinant proteins should be carefully considered in translational design.

By addressing these translational considerations, researchers can develop more effective strategies for applying c-Met research findings from rodent models to human therapeutic applications in liver diseases and regenerative medicine.

How should researchers interpret contradictory data regarding c-Met activation in different experimental models?

Interpreting contradictory data regarding c-Met activation across experimental models requires systematic analysis of several key variables:

Model-Specific Activation Context:
Different experimental models may represent distinct physiological or pathological states that influence c-Met activation. For example, c-Met signaling in liver regeneration after partial hepatectomy may differ from that observed in models of acute liver injury or chronic fibrosis. The research shows that HGF/c-Met plays critical roles in liver fibrosis, post-inflammatory hepatocyte regeneration, and post-transplantation liver regeneration , suggesting context-dependent functions.

Pathway Component Assessment:
Comprehensive analysis of multiple pathway components can help resolve contradictions. For instance, in cases where direct c-Met activation measurements conflict, examining downstream effectors like ERK1/2 phosphorylation, which is completely dependent on c-Met during liver regeneration , can provide clarification.

Biological Variable Stratification:
Age-related differences can explain contradictory findings. Clinical studies demonstrate that HGF and c-Met expression levels are significantly lower in older patients compared to younger patients . Stratifying data by age or other biological variables may resolve apparent contradictions.

When confronted with contradictory data, researchers should systematically evaluate these factors and consider integrating findings through computational modeling to generate testable hypotheses that may reconcile disparate observations.

What statistical approaches are most appropriate for analyzing c-Met phosphorylation dynamics in time-course experiments?

Time-course experiments investigating c-Met phosphorylation dynamics require specialized statistical approaches to properly capture the complex temporal patterns:

Mixed-Effects Modeling:
Given the rapid changes in c-Met phosphorylation status (beginning within 5 minutes and peaking at 60 minutes post-stimulation ), mixed-effects models that account for both fixed (treatment, time) and random (subject-specific) effects are optimal for analyzing longitudinal data with potential missing timepoints.

Functional Data Analysis:
The continuous nature of phosphorylation dynamics is better captured by functional data analysis approaches that model the entire phosphorylation curve rather than discrete timepoints. This is particularly important for c-Met, which undergoes rapid activation followed by ubiquitin-proteasome-mediated degradation .

Pathway-Informed Bayesian Methods:
Incorporating prior knowledge about the HGF/c-Met signaling pathway into Bayesian models can improve estimation of phosphorylation parameters. For instance, knowing that HGF binding triggers c-Met phosphorylation followed by β-catenin translocation provides temporal constraints that can inform statistical models.

Sample Size Considerations:
For detecting meaningful differences in c-Met phosphorylation, researchers should conduct power analyses that account for:

• The expected effect size (often large for phosphorylation events)

• Biological variability between samples

• Technical variability in phospho-protein detection

• Multiple testing correction for pathway analysis

These statistical approaches help researchers extract meaningful patterns from time-course phosphorylation data while accounting for the complex dynamics of c-Met activation, signaling, and degradation observed in biological systems.

How can researchers distinguish between direct and indirect effects on c-Met signaling in complex biological systems?

Distinguishing between direct and indirect effects on c-Met signaling in complex biological systems requires sophisticated experimental designs and analytical approaches:

Selective Inhibition Strategy:
Using highly selective c-Met inhibitors like SGX523 provides a direct way to isolate c-Met-specific effects. Research has demonstrated that SGX523 eliminates enhanced liver regeneration effects of PPARγ antagonist GW9662, confirming that PPARγ inhibits liver growth and hepatocyte proliferation specifically through the HGF/c-Met/ERK1/2 pathway .

Temporal Sequence Mapping:
Direct c-Met effects typically occur rapidly, with phosphorylation beginning within minutes of stimulation . By establishing detailed temporal sequences of signaling events, researchers can distinguish primary (direct) from secondary (indirect) effects based on their kinetics.

Genetic Rescue Experiments:
Complementing pharmacological approaches with genetic rescue experiments can provide definitive evidence of direct c-Met involvement. In c-Met mutant mice, liver regeneration is impaired and ERK1/2 phosphorylation is absent , demonstrating direct dependence of this pathway on c-Met.

Pathway Crossover Analysis:
Research has identified specific crossover points between signaling pathways. For example, BMP9 and HGF/c-Met signaling establish a signal crossover through ALK1 by modulating SMAD1 and p38MAPK . Targeted analysis of these nodes helps delineate where pathways directly interact versus where they operate independently.

These methodological approaches provide researchers with a framework for distinguishing direct c-Met-mediated effects from indirect influences or pathway crosstalk, enabling more precise understanding of c-Met's role in complex biological processes such as liver regeneration.

What are the most promising approaches for targeting c-Met in regenerative medicine applications?

Several promising approaches for targeting c-Met in regenerative medicine applications have emerged from recent research:

Recombinant HGF Administration:
Direct administration of recombinant human HGF (rh-HGF) has shown significant therapeutic potential. Studies demonstrate that rh-HGF can inhibit hepatocyte death and stabilize structural and vascular integrity in mice with acute liver failure . The method of administration matters significantly - injection of HGF into the portal vein has been shown to cause hepatocyte proliferation and hepatomegaly in normal rats and mice .

HGF Activator Therapy:
Recombinant human HGF-activator (rh-HGF-activator) administered via the portal vein significantly increases liver regeneration rates compared to control groups . This approach leverages the body's existing HGF while enhancing its activation state.

Engineered HGF Fragments:
Synthetic small molecules based on natural HGF fragments show promise. The engineered molecule 1K1, derived from the naturally occurring HGF fragment NK1, demonstrates anti-fibrotic properties and promotes liver regeneration in rodents with improved stability and production characteristics . Such engineered variants may overcome the pharmacokinetic and production challenges of full-length HGF.

Natural Compound Modulators:
Several natural compounds have shown efficacy in modulating HGF/c-Met signaling. Schisandra Chinensis and Resina Draconis significantly increase HGF expression levels, promoting liver function recovery and ameliorating acute liver injury by enhancing cell proliferation . These natural compounds may offer complementary approaches with potentially favorable safety profiles.

These diverse approaches highlight the therapeutic potential of targeting the HGF/c-Met axis in regenerative medicine, particularly for liver diseases where restoration of tissue function is critical.

How can researchers monitor potential off-target effects when modulating c-Met signaling in experimental models?

Monitoring potential off-target effects when modulating c-Met signaling requires comprehensive assessment strategies:

Broad Pathway Profiling:
Since c-Met activates multiple downstream pathways including JAK/STAT3, PI3K/Akt/NF-κB, and Ras/Raf , researchers should employ phospho-proteomic approaches to evaluate changes across these and other pathways simultaneously. This broad profiling can identify unexpected pathway activation or inhibition that may indicate off-target effects.

Tissue-Specific Analysis:
The effects of c-Met modulation may vary across tissues. Research has shown that HGF/c-Met signaling is essential for liver regeneration , but it also plays roles in other tissues. Multi-tissue analysis can identify off-target effects that may be restricted to specific organ systems.

Cell-Type Specificity Assessment:
Within tissues, different cell types may respond differently to c-Met modulation. For example, under hypoxic conditions, HGF expression in hepatic stellate cells and c-Met expression in hepatocytes both decrease dramatically . Single-cell analysis techniques can resolve cell-type-specific responses that might be missed in bulk tissue analysis.

Developmental Timing Considerations:
The biological functions of HGF/c-Met are extensive and diverse, particularly during embryonic development. Targeted destruction of HGF or c-Met leads to embryonic lethality in mice with specific damage to liver and placental development . Age-appropriate models should be used to avoid misinterpreting developmental effects as off-target effects.

By implementing these monitoring strategies, researchers can better differentiate between intended on-target effects and potential off-target consequences of c-Met modulation, enhancing both the safety and specificity of experimental interventions targeting this pathway.

What biomarkers most accurately reflect c-Met activation status in clinical samples?

Accurate assessment of c-Met activation status in clinical samples requires a multi-biomarker approach that reflects the complex dynamics of receptor activation:

Phosphorylated c-Met Residues:
The primary direct biomarkers are phosphorylated tyrosine residues on the c-Met receptor itself. After partial hepatectomy, c-Met tyrosine phosphorylation begins within 5 minutes and peaks at 60 minutes . Phospho-specific antibodies against these residues provide the most direct measurement of activation status.

ERK1/2 Phosphorylation:
Research has established that ERK1/2 activation is completely dependent on c-Met during liver regeneration . Therefore, phospho-ERK1/2 serves as a reliable downstream biomarker that reflects functional c-Met signaling, particularly in liver tissue samples.

Nuclear β-catenin Localization:
HGF binding to c-Met induces Wnt-independent nuclear translocation of β-catenin . Immunohistochemical assessment of nuclear β-catenin localization provides an additional readout of functional c-Met activation.

Age-Adjusted Reference Ranges:
Clinical studies have demonstrated that HGF and c-Met expression levels are significantly lower in older patients compared to younger patients . Biomarker interpretation therefore requires age-appropriate reference ranges to accurately assess activation status relative to biological norm.

These biomarkers, when assessed in combination, provide a comprehensive picture of c-Met activation status in clinical samples. This multi-parameter approach is particularly important given the rapid dynamics of c-Met activation and degradation, which might lead to false negatives if relying on a single biomarker at a single timepoint.