HGF Human

What is Human Hepatocyte Growth Factor and what is its molecular structure?

Human Hepatocyte Growth Factor (HGF) is a paracrine hormone that plays an important role in epithelial-mesenchymal transition and functions as a potent mitogen for mature parenchymal hepatocytes in primary culture . Structurally, HGF has a relative molecular mass of 82,000 Da and exists as a heterodimer composed of a large α-subunit of 69,000 Da and a small β-subunit of 34,000 Da .

Both chains originate from a single open reading frame coding for a pre-pro precursor protein of 728 amino acids, which undergoes post-translational processing to form the mature protein . This unique structure allows HGF to interact with its receptor, MET, and trigger various cellular responses including motogenesis, mitogenesis, and morphogenesis .

How does human HGF differ from other species' HGF variants?

Human HGF (hHGF) differs significantly from mouse HGF (mHGF) in terms of cross-species activity, despite structural similarities. A critical research consideration is that while mHGF binds to human MET with high affinity, it does not stimulate the proliferation of human cells or human tumor xenografts . This species-specific functionality has important implications for experimental design.

This limitation has prompted the development of hHGF transgenic and knock-in mice to enable more comprehensive preclinical studies that fully encompass the spectrum of pathway involvement in human cancers . Understanding these species differences is crucial when designing experiments and interpreting results, especially in preclinical studies involving animal models.

What are the primary physiological roles of human HGF?

Human HGF serves multiple essential physiological functions across various tissue types:

• Liver regeneration: HGF acts as a hepatotrophic factor that triggers liver regeneration after partial hepatectomy and liver injury .

• Vascular repair: HGF is released by stressed human vascular cells and promotes vascular cell repair responses in both autocrine and paracrine ways, contributing to endothelial integrity maintenance .

• Developmental processes: HGF plays an important role in cell motility, proliferation, and stimulation of branching morphogenesis in the fetal lung .

• Hair regeneration: HGF is secreted by dermal papilla cells (DPCs) and exerts biological effects on various epithelial cells, though its specific role in hair regeneration requires further investigation .

• Cellular homeostasis: HGF drives mitogenesis, motogenesis, and morphogenesis in a wide spectrum of target cell types across embryologic, developmental, and homeostatic contexts .

What are the key considerations for designing experiments to study human HGF function?

When designing experiments to study human HGF function, researchers should follow systematic experimental design principles while addressing HGF-specific considerations:

• Define clear variables and relationships: Consider your independent variable (HGF treatment/concentration), dependent variables (cellular responses), and control for potential confounding variables .

• Formulate a specific, testable hypothesis: For example, "Increased HGF concentration leads to enhanced cell motility in epithelial cells" .

• Select appropriate experimental treatments: Determine how widely and finely to vary HGF concentration to establish dose-response relationships .

• Use appropriate randomization: Apply either completely randomized design or randomized block design based on your experimental system .

• Consider species-specific effects: Since mouse HGF does not stimulate human cell proliferation despite binding to human MET with high affinity, ensure proper species matching in your experimental system .

• Include proper controls: Implement both negative controls (no HGF treatment) and positive controls (known HGF effects) to validate experimental outcomes .

• Measure multiple endpoints: HGF affects multiple cellular processes, so consider measuring mitogenesis, motogenesis, and morphogenesis parameters to comprehensively assess its effects .

How should researchers approach the selection of appropriate cell models for human HGF studies?

Selecting appropriate cell models for human HGF research requires careful consideration of several factors:

• Expression of MET receptor: Ensure your chosen cell model expresses the MET receptor, as this is essential for HGF signaling. Verify receptor expression through techniques like Western blotting or flow cytometry.

• Response to HGF stimulation: Validate that your selected cell model responds to human HGF with expected biological outcomes such as proliferation, migration, or morphological changes .

• Relevance to research question: Select cell types that are relevant to your specific research question. For liver regeneration studies, hepatocytes would be appropriate; for vascular repair research, endothelial cells and smooth muscle cells are suitable .

• Consider autocrine vs. paracrine models: Determine whether your research question pertains to autocrine or paracrine HGF signaling, and design your cell model accordingly. For paracrine studies, co-culture systems may be necessary .

• Primary cells vs. cell lines: Primary cells better reflect physiological conditions but have limited lifespan and higher variability. Cell lines offer consistency but may have altered signaling pathways. The choice depends on your specific research goals .

What methodological approaches are recommended for measuring human HGF expression and activity?

Several methodological approaches can be employed to effectively measure human HGF expression and activity:

Expression Analysis Methods:

• qRT-PCR: For quantifying HGF mRNA expression levels in cells or tissues

• Western blotting: For detecting HGF protein expression and processing

• ELISA: For quantifying secreted HGF in culture media or biological fluids

• Immunohistochemistry/immunofluorescence: For localizing HGF expression in tissues

Activity Assessment Methods:

• Proliferation assays: MTT or BrdU incorporation to measure mitogenic effects

• Migration assays: Wound healing or Boyden chamber assays to assess motogenic effects

• 3D culture morphogenesis: To evaluate branching morphogenesis in response to HGF

• MET phosphorylation: Western blotting for phospho-MET to assess receptor activation

• Downstream signaling analysis: Evaluation of pathway activation through phosphorylation of ERK, Akt, and other downstream targets

Expression Array Analysis:
For comprehensive assessment of the HGF-induced gene expression program, expression array profiling followed by pathway analysis can identify canonical pathways associated with enhanced cell motility and invasiveness . This approach has successfully identified non-canonical networks linked to cancer and inflammation, and gene sets associated with decreased disease-free survival in cancer patients .

How can researchers effectively study the role of human HGF in vascular repair mechanisms?

To effectively study human HGF in vascular repair mechanisms, researchers should implement the following methodological approaches:

• In vitro stress models: Develop models that simulate vascular stress conditions (oxidative stress, mechanical strain, hypoxia) to study HGF release from vascular cells .

• Co-culture systems: Establish co-culture systems of endothelial cells and smooth muscle cells to investigate paracrine and autocrine effects of HGF in the vascular environment .

• Biomarker analysis: Measure circulating HGF levels in subjects with vascular stress to correlate with cardiovascular risk. Research has shown that subjects with a low capacity to express HGF in response to systemic stress have increased cardiovascular risk .

• Plaque stability assessment: Analyze HGF content in atherosclerotic plaques to assess correlation with plaque stability. Studies have demonstrated that human atherosclerotic plaques with a low content of HGF have a more unstable phenotype .

• Response to metabolic stress: Evaluate the ability of subjects to express HGF in response to metabolic stress, as this has been linked to risk of myocardial infarction and stroke .

• Endothelial integrity measures: Implement techniques to assess endothelial integrity and repair in response to HGF, as maintaining endothelial integrity is critical for prevention of acute cardiovascular events .

What techniques are most effective for studying human HGF in cancer progression?

Studying human HGF in cancer progression requires sophisticated techniques that address both molecular mechanisms and translational implications:

• Humanized mouse models: Utilize hHGF transgenic or knock-in mice for preclinical studies, as murine HGF (mHGF) fails to stimulate the growth of human tumor xenografts .

• Pathway activation analysis: Implement expression array profiling and pathway analysis to characterize the HGF invasive program. This approach has successfully identified canonical pathways associated with enhanced cell motility and tumor cell invasiveness .

• Patient-derived xenografts (PDXs): Establish PDX models in hHGF transgenic mice to better recapitulate the human tumor microenvironment and HGF signaling.

• 3D organoid cultures: Develop tumor organoid cultures that better represent tissue architecture and cell-cell interactions for studying HGF's role in invasion and metastasis.

• Multi-omics integration: Combine transcriptomics, proteomics, and metabolomics to comprehensively characterize HGF-induced changes in cancer cells.

• TCGA data correlation: Compare experimental findings with The Cancer Genome Atlas (TCGA) data to identify clinically relevant gene signatures associated with HGF activity and patient outcomes .

The table below summarizes key analytical approaches for studying HGF in cancer:

How can researchers address the challenges of translating in vitro HGF findings to in vivo systems?

Translating in vitro HGF findings to in vivo systems presents several challenges that can be addressed through the following methodological approaches:

• Species specificity considerations: Due to the critical finding that murine HGF does not stimulate human cell proliferation despite binding to human MET with high affinity, researchers should use humanized mouse models (hHGF transgenic or knock-in mice) for translational studies .

• Physiological concentration ranges: In vitro studies often use HGF concentrations that exceed physiological levels. Researchers should determine physiological HGF concentrations in relevant tissues and use dose-response experiments that include this range.

• Complex microenvironment simulation: Develop more complex in vitro systems that better mimic the in vivo microenvironment, such as:

  • 3D culture systems

  • Co-culture with multiple cell types

  • Extracellular matrix components

  • Mechanical forces/stress conditions

• Validation across multiple models: Confirm findings using multiple complementary approaches:

  • Primary cells and established cell lines

  • 2D and 3D culture systems

  • Multiple animal models

  • Patient-derived samples

• Functional redundancy analysis: Consider that some HGF effects may be redundant with other growth factors. The search results mention that MET-selective competitive antagonist NK1 and mouse HGF share functional redundancy in some contexts, which can be leveraged for pathway analysis .

• Ingenuity Pathway Analysis (IPA): For a more comprehensive analysis, implement IPA of expression array data and compare to databases like TCGA to identify clinically relevant signatures .

What are the key downstream pathways activated by human HGF/MET signaling?

Human HGF activates various downstream pathways through binding to its receptor MET, leading to diverse cellular responses. The key downstream pathways include:

• MAPK/ERK Pathway: Activation of the Ras-Raf-MEK-ERK cascade leads to cell proliferation and is particularly important for the mitogenic effects of HGF. This pathway is central to HGF's role as "the most potent mitogen for mature parenchymal hepatocytes in primary culture" .

• PI3K/Akt Pathway: This pathway mediates cell survival and anti-apoptotic responses, contributing to HGF's protective effects in various tissues, including its role in vascular repair responses .

• STAT Pathway: Signal Transducers and Activators of Transcription (particularly STAT3) activation contributes to cell proliferation and differentiation effects.

• Rac/PAK Pathway: This pathway mediates cytoskeletal reorganization and is crucial for the motogenic (cell movement) effects of HGF, which are central to its role in epithelial-mesenchymal transition .

• β-catenin Pathway: HGF can activate β-catenin signaling, contributing to morphogenic responses and epithelial tubulogenesis.

• NF-κB Pathway: This pathway mediates inflammatory responses and can contribute to HGF's role in tissue repair and regeneration.

The integration of these signaling pathways allows HGF to drive "mitogenesis, motogenesis and morphogenesis in a wide spectrum of target cell types and embryologic, developmental and homeostatic contexts" .

How can researchers effectively analyze gene expression changes induced by human HGF?

To effectively analyze gene expression changes induced by human HGF, researchers should implement a systematic approach:

• Experimental design for expression analysis:

  • Include appropriate time points (early, intermediate, and late responses)

  • Use dose-response relationships to identify concentration-dependent effects

  • Include appropriate controls (untreated, vehicle, and positive controls)

  • Consider the use of pathway inhibitors to dissect specific signaling branches

• High-throughput methods:

  • RNA sequencing for comprehensive transcriptome analysis

  • Microarray analysis for targeted gene expression profiling

  • Proteomics to correlate transcriptional changes with protein expression

  • Single-cell RNA sequencing to identify cell population-specific responses

• Bioinformatic analysis approaches:

  • Use tools like Ingenuity Pathway Analysis (IPA) to identify activated canonical pathways

  • Perform Gene Ontology (GO) enrichment analysis to identify biological processes

  • Conduct gene set enrichment analysis (GSEA) to identify coordinated changes

  • Compare findings with public datasets such as The Cancer Genome Atlas (TCGA)

• Validation strategies:

  • Confirm key findings with qRT-PCR

  • Validate protein expression changes with Western blotting

  • Use ChIP-seq to identify transcription factor binding

  • Implement functional assays to confirm biological relevance

According to the search results, a comprehensive approach used for HGF research included analyzing "520 probes with ≥2-fold change over untreated control cells (FDR < 0.05) representing the union of hHGF, mHGF and hNK2 treatments" which were then processed by IPA Core Analysis . This approach successfully identified canonical pathways associated with enhanced cell motility and tumor cell invasiveness, as well as non-canonical networks linked to cancer and inflammation .

What methodological approaches can help differentiate between canonical and non-canonical HGF signaling?

Differentiating between canonical and non-canonical HGF signaling requires specialized methodological approaches:

• Receptor mutant studies: Use cells expressing MET receptor variants with mutations in specific docking sites to identify which downstream pathways are activated by which binding sites.

• Specific pathway inhibitors: Employ selective inhibitors of canonical pathways (e.g., MEK inhibitors for MAPK pathway, PI3K inhibitors for Akt pathway) to identify responses that persist despite canonical pathway blockade.

• Phosphoproteomic analysis: Implement mass spectrometry-based phosphoproteomics to comprehensively map phosphorylation events following HGF stimulation, identifying both known and novel signaling nodes.

• CRISPR/Cas9 screens: Perform genome-wide or targeted CRISPR screens to identify genes essential for specific HGF-induced phenotypes, which may reveal non-canonical mediators.

• Network analysis approaches: As demonstrated in the search results, pathway analysis identified "non-canonical networks linked to cancer and inflammation" in response to HGF stimulation . Use sophisticated network analysis tools to distinguish canonical pathway components from emerging non-canonical connections.

• Time-course analysis: Canonical pathways often activate rapidly, while non-canonical responses may emerge later. Implement detailed time-course studies to distinguish temporal patterns of pathway activation.

• Motif analysis: Analyze promoter regions of HGF-responsive genes to identify enriched transcription factor binding motifs, which may reveal non-canonical transcriptional regulators.

How can human HGF be used as a biomarker for cardiovascular risk assessment?

Human HGF shows significant promise as a biomarker for cardiovascular risk assessment, as supported by recent research findings:

• Stress response marker: Circulating HGF reflects activation of vascular repair in response to stress. Research has shown that "subjects with a low capacity to express HGF in response to systemic stress have an increased cardiovascular risk" .

• Plaque stability indicator: Human atherosclerotic plaques with low HGF content demonstrate "a more unstable phenotype," suggesting that HGF levels in plaques could serve as an indicator of vulnerability to rupture .

• Cardiovascular event predictor: Studies have demonstrated that "subjects with a low ability to express HGF in response to metabolic stress have an increased risk to suffer myocardial infarction and stroke" .

• Endothelial integrity assessment: Since "maintaining endothelial integrity is critical for prevention of acute cardiovascular events," HGF's role in promoting vascular cell repair responses makes it a potential marker for endothelial health .

To implement HGF as a cardiovascular biomarker, researchers should consider:

• Standardizing measurement protocols for circulating HGF

• Establishing reference ranges in different populations

• Determining the optimal timing for sampling relative to stress events

• Integrating HGF measurements with other established cardiovascular risk markers

• Developing point-of-care testing methods for clinical applications

What methodological considerations are important when studying human HGF in liver regeneration?

When studying human HGF in liver regeneration, researchers should address these key methodological considerations:

• Model selection: Choose appropriate models based on research objectives:

  • Partial hepatectomy models (most physiologically relevant)

  • Toxic injury models (CCl₄, acetaminophen, etc.)

  • Cell culture systems (primary hepatocytes, liver organoids)

  • Human liver samples (from resection or transplantation)

• Temporal dynamics: HGF acts as "a trigger for liver regeneration after partial hepatectomy and liver injury" , so establish detailed time courses to capture:

  • Immediate early response (minutes to hours)

  • Proliferative phase (hours to days)

  • Termination phase (days to weeks)

• Source identification: Determine the cellular sources of HGF in different contexts, as HGF may be produced by:

  • Stellate cells

  • Sinusoidal endothelial cells

  • Kupffer cells

  • Distant organs (e.g., platelets)

• Pathway analysis: Implement comprehensive pathway analysis to understand how HGF integrates with other regenerative factors:

  • Use techniques like Ingenuity Pathway Analysis (IPA)

  • Consider early vs. late gene expression programs

  • Identify feedback mechanisms that terminate the regenerative response

• Functional endpoints: Measure multiple endpoints to comprehensively assess regeneration:

  • Liver mass restoration

  • Hepatocyte proliferation indices

  • Functional restoration (synthetic and metabolic functions)

  • Vascular and biliary reconstruction

• Species considerations: Account for species differences when translating findings:

  • Consider using humanized models for preclinical studies

  • Validate findings in human samples whenever possible

How can researchers effectively study the therapeutic potential of human HGF in tissue engineering?

To effectively study the therapeutic potential of human HGF in tissue engineering, researchers should implement these methodological approaches:

• Controlled delivery systems: Develop and characterize systems for controlled release of HGF:

  • Encapsulation in biodegradable polymers

  • Integration with scaffold materials

  • Binding to extracellular matrix components

  • Gene therapy approaches for sustained expression

• Dose optimization studies: Establish optimal dosing regimens:

  • Determine minimum effective concentration

  • Identify potential dose-dependent adverse effects

  • Evaluate single versus repeated administration

  • Consider synergistic effects with other growth factors

• Functional assessment: Implement comprehensive assessment of engineered tissue function:

  • Tissue-specific functional assays

  • Mechanical property testing

  • Vascularization evaluation

  • Integration with host tissue

• Genetic engineering approaches: Consider genetic modification strategies:

  • Transfection with HGF-expressing plasmids

  • As demonstrated in the search results, researchers have "constructed a plasmid containing hHGF gene (pTARGET-hHGF) and then transfected it into human fibroblasts"

  • Viral vector delivery of HGF genes

  • CRISPR-based enhancement of endogenous HGF expression

• In vivo validation: Systematically evaluate engineered constructs in vivo:

  • Initial assessment in immunodeficient models

  • Progression to immunocompetent models when appropriate

  • Evaluation in disease-specific models

  • Long-term studies to assess durability and safety

• Translational considerations: Address factors critical for clinical translation:

  • Scale-up of production processes

  • Stability studies under storage and handling conditions

  • Development of quality control measures

  • Regulatory considerations for clinical applications