MET Gene Complete Identifier and Functional Mapping Reference

Provide a comprehensive cross-database identifier and functional mapping reference for human MET — a definitive lookup resource covering: ### Section …

Provide a comprehensive cross-database identifier and functional mapping reference for human MET — a definitive lookup resource covering: ### Section 1: Gene identifiers For human gene MET, list ALL gene-level database identifiers. Required: - HGNC ID and approved symbol - Ensembl gene ID (ENSG...) - NCBI Entrez Gene ID - OMIM gene/locus ID - Genomic location: chromosome, start position, end position, strand (GRCh38) ### Section 2: Transcript identifiers For human gene MET, list ALL transcript-level identifiers. Required: - Ensembl transcripts: ALL ENST IDs with biotype. Total count. - RefSeq transcripts: ALL NM_ mRNA accessions. Mark which is MANE Select. - CCDS IDs. - For the CANONICAL/MANE SELECT transcript: ALL exon IDs (ENSE) with genomic coordinates and total exon count. ### Section 3: Protein identifiers For human gene MET protein product(s), list ALL protein-level identifiers. Required: - UniProt accessions: ALL entries (reviewed and unreviewed). Mark the canonical reviewed entry. - RefSeq protein: ALL NP_ accessions. - Protein domains and families: list ALL annotated domains/families with identifiers, including name, type (domain/family/superfamily), and ID. - Antibody availability: known antibody resources for the protein. ### Section 4: Structure For human gene MET protein, list ALL structural data. Required: - Experimental structures: ALL PDB IDs. For each: experimental method (X-ray/NMR/Cryo-EM) and resolution. Total count. - Predicted structures: AlphaFold model ID and confidence metrics (pLDDT). ### Section 5: Cross-species orthologs For human gene MET, list orthologous genes in key model organisms. Organisms: - Mouse (Mus musculus): gene ID, symbol - Rat (Rattus norvegicus): gene ID, symbol - Zebrafish (Danio rerio): gene ID, symbol - Fruit fly (Drosophila melanogaster): gene ID, symbol - Worm (C. elegans): gene ID, symbol - Yeast (S. cerevisiae): gene ID, symbol ### Section 6: Clinical variants & AI predictions For human gene MET, summarize clinical variants and AI predictions. Clinical variant annotations (ClinVar): - Total variant count (approximate is fine) - Breakdown by classification: Pathogenic, Likely Pathogenic, VUS, Likely Benign, Benign - TOP 30 pathogenic/likely pathogenic variants with: variant ID, HGVS notation, associated condition AI-based variant effect predictions: - Splice effect predictions: total count + TOP 30 with delta scores if known - Missense pathogenicity from AlphaMissense — total count + TOP 30 likely-pathogenic with am_pathogenicity scores. ### Section 7: Pathways & Gene Ontology For human gene MET, list biological pathways and Gene Ontology annotations. Pathway membership: - ALL biological pathways this gene participates in, with pathway IDs and names - Total pathway count Gene Ontology: - Biological Process: count and TOP 20 terms with GO IDs - Molecular Function: count and TOP 20 terms with GO IDs - Cellular Component: count and TOP 20 terms with GO IDs ### Section 8: Protein interactions & networks For human gene MET protein, summarize protein interactions and networks. Protein-protein interactions (STRING, IntAct, BioGRID, etc.): - Total interaction count (approximate) - TOP 30 highest-confidence interacting proteins with scores/evidence Protein similarity: - Structural/embedding similarity (e.g. Foldseek, ESM): TOP 20 similar proteins with scores - Sequence homology: TOP 20 homologous proteins with identity/similarity ### Section 9: Transcription factor regulatory data For human gene MET, summarize transcription factor regulatory data. If MET is a transcription factor: - Downstream targets: total count + TOP 30 with regulation type (activates/represses) and evidence - DNA binding motifs from JASPAR — all known motif IDs and motif family classification. Regardless: - Upstream regulators: TFs that regulate MET — names with evidence type (ChIP-seq / predicted / experimentally validated) If MET is not a transcription factor, say so briefly and skip the downstream/motif sections. ### Section 10: Drug & pharmacology data For human gene MET protein as a drug target, summarize pharmacology data. If MET is a known drug target: - Targeting molecules: total count in ChEMBL/DrugBank + TOP 30 by development phase (molecule ID, name, mechanism, highest phase) - Clinical trials: TOP 20 involving drugs targeting this gene — trial ID, phase, status, intervention - Pharmacogenomics: known drug-gene interactions affecting drug response + dosing guidelines if any If MET is not currently a drug target, say so briefly. ### Section 11: Expression profiles For human gene MET, summarize expression profiles. Tissue expression (GTEx, HPA, Bgee, etc.): - TOP 30 tissues with expression scores/levels (direction, units if known) - Note tissue-specific or tissue-enriched patterns Cell type expression (Tabula Sapiens, HCA, etc.): - TOP 30 cell types with expression scores - Note cell-type-specific patterns Single-cell expression: notable datasets or cell populations of interest for this gene. ### Section 12: Disease associations For human gene MET, summarize disease associations. Mendelian / monogenic disease: - Diseases caused by mutations in MET: disease name, disease ID (OMIM/Orphanet/Mondo), inheritance pattern, evidence level - Include all directly linked conditions Phenotype associations: - Clinical phenotypes associated with the gene (HPO terms where known) - TOP 30 phenotype terms with HPO IDs Complex-disease / GWAS: - Traits and diseases significantly associated via GWAS: trait name, variant, effect size, study where known - TOP 30 GWAS associations

MET

Executive summary

MET (HGNC:7029), located on chromosome 7, encodes the hepatocyte growth factor receptor — a receptor tyrosine kinase that drives cell proliferation, migration, and morphogenesis and is one of the most therapeutically targeted kinases in oncology. Its primary clinical relevance lies in cancer: germline gain-of-function mutations cause hereditary papillary renal cell carcinoma (autosomal dominant), while somatic alterations — particularly MET exon 14 skipping and amplification — are established biomarkers that sensitize tumors to approved inhibitors including capmatinib, tepotinib, and crizotinib, with over 100 small molecules and 8 therapeutic antibodies in development or approved. MET is broadly expressed across 270 of 290 human tissues (average score 75.3), with highest levels in epithelial and connective tissues, and activates at least 19 Reactome pathways spanning RAS, PI3K/AKT, and STAT3 signaling. The protein has 120 experimental PDB structures and an AlphaFold model with a global pLDDT of 79.28, reflecting strong structural coverage. Of ~4,647 ClinVar variants, the vast majority are of uncertain significance, with fewer than 100 classified pathogenic.

Gene identifiers

IdentifierValue
HGNC IDHGNC:7029
Approved symbolMET
Ensembl gene IDENSG00000105976
NCBI Entrez Gene ID4233
OMIM locus ID164860
Chromosome (GRCh38)7
Start position (GRCh38)116,672,051
End position (GRCh38)116,798,386
Strand+

Transcript identifiers

Ensembl Transcripts (ENST)

Transcript IDBiotype
ENST00000318493protein_coding
ENST00000397752protein_coding
ENST00000422097protein_coding
ENST00000436117nonsense_mediated_decay
ENST00000454623protein_coding
ENST00000456159protein_coding
ENST00000495962protein_coding_CDS_not_defined
ENST00000917365protein_coding
ENST00000950406protein_coding
ENST00000950407protein_coding

Total: 10 transcripts

RefSeq mRNA (NM_)

RefSeq IDStatusMANE Select
NM_000245REVIEWED✓ Yes
NM_001127500REVIEWED
NM_001324401REVIEWED
NM_001324402REVIEWED

Total: 4 human RefSeq mRNA

CCDS Identifiers

CCDS ID
CCDS43636
CCDS47689

Total: 2 CCDS

MANE SELECT Transcript Exons

Transcript: ENST00000397752 (MANE Select, protein_coding)

ExonENSE IDStartEndLength (bp)
1ENSE00004014114116672196116672577382
2ENSE00004014112116731668116731859192
3ENSE00004014106116740852116741025174
4ENSE00004014102116739950116740084135
5ENSE00004014113116757437116757539103
6ENSE00004014105116757638116757774137
7ENSE00001619404116758459116758620162
8ENSE00001530016116759391116759490100
9ENSE00000717791116763050116763268219
10ENSE00000717803116769645116769791147
11ENSE00000717811116771498116771654157
12ENSE00000717833116771849116771989141
13ENSE00000717861116774881116775111231
14ENSE0000359620011677738911677746981
15ENSE00003663921116778776116778957182
16ENSE00000717902116781988116782097110
17ENSE00000717928116783304116783469166
18ENSE00000717937116795655116795791137
19ENSE000018986611167958871167983772491
20ENSE000040141191166990711167002841214

Total: 21 exons

Protein identifiers

UniProt Accessions

  • P08581 ✓ (canonical reviewed entry) — Hepatocyte growth factor receptor
  • C9JKM5 (unreviewed)
  • E6Y365 (unreviewed)
  • H7C130 (unreviewed)

RefSeq Protein Accessions (NP_)

  1. NP_000236 (MANE Select)
  2. NP_001007125
  3. NP_001120972
  4. NP_001285132
  5. NP_001311330
  6. NP_001311331
  7. NP_001397049
  8. NP_001397052
  9. NP_001397053
  10. NP_032617
  11. NP_113705
  12. NP_511126

Protein Domains and Families

InterPro Domains & Families

IDNameType
IPR000719Protein kinase domainDomain
IPR001245Serine-threonine/tyrosine-protein kinase, catalytic domainDomain
IPR001627Sema domainDomain
IPR002165Plexin repeatRepeat
IPR002909IPT domainDomain
IPR008266Tyrosine-protein kinase, active siteActive_site
IPR011009Protein kinase-like domain superfamilyHomologous_superfamily
IPR013783Immunoglobulin-like foldHomologous_superfamily
IPR014756Immunoglobulin E-setHomologous_superfamily
IPR015943WD40/YVTN repeat-like-containing domain superfamilyHomologous_superfamily
IPR016201PSI domainDomain
IPR016244Tyrosine-protein kinase, HGF/MSP receptorFamily
IPR017441Protein kinase, ATP binding siteBinding_site
IPR020635Tyrosine-protein kinase, catalytic domainDomain
IPR031148Plexin familyFamily
IPR036352Sema domain superfamilyHomologous_superfamily

Pfam

  • PF01403
  • PF01437
  • PF01833
  • PF07714

SMART

  • SM00219
  • SM00423
  • SM00429
  • SM00630

CDD

  • CD00603
  • CD01179
  • CD01180
  • CD01181
  • CD05058
  • CD11278

Antibody Resources

Therapeutic antibodies targeting MET:

NameFormatIsotypeStatus
AMIVANTAMABBispecific mAbG1;G1Active
BAFISONTAMABBispecific Mixed mAb and FabG1;naActive
DAVUTAMIGBispecific mAbG4;G4Active
EMIBETUZUMABWhole mAbG4Active
TILATAMIGBispecific mAbG1;G1Active
ONARTUZUMABFab + di-FcG1Discontinued
PAMVATAMIGBispecific mAbG1;G1Discontinued
TELISOTUZUMABWhole mAb ADCG1Discontinued

Structure

Experimental Structures

Total PDB Entries: 120

X-ray Crystallography (95 structures)

1R0P (1.8 Å), 1R1W (1.8 Å), 1SHY (3.22 Å), 2G15 (2.15 Å), 2RFN (2.5 Å), 2RFS (2.2 Å), 2UZX (2.8 Å), 2UZY (4.0 Å), 2WD1 (2.0 Å), 2WGJ (2.0 Å), 2WKM (2.2 Å), 3A4P (2.54 Å), 3BUX (1.35 Å), 3C1X (2.17 Å), 3CCN (1.9 Å), 3CD8 (2.0 Å), 3CE3 (2.4 Å), 3CTH (2.3 Å), 3CTJ (2.5 Å), 3DKC (1.52 Å), 3DKF (1.8 Å), 3DKG (1.91 Å), 3EFJ (2.6 Å), 3EFK (2.2 Å), 3F66 (1.4 Å), 3F82 (2.5 Å), 3I5N (2.0 Å), 3L8V (2.4 Å), 3LQ8 (2.02 Å), 3Q6U (1.6 Å), 3Q6W (1.75 Å), 3QTI (2.0 Å), 3R7O (2.3 Å), 3RHK (1.94 Å), 3U6H (2.0 Å), 3U6I (2.1 Å), 3VW8 (2.1 Å), 3ZBX (2.2 Å), 3ZC5 (2.2 Å), 3ZCL (1.4 Å), 3ZXZ (1.8 Å), 3ZZE (1.87 Å), 4AOI (1.9 Å), 4AP7 (1.8 Å), 4DEG (2.0 Å), 4DEH (2.0 Å), 4DEI (2.05 Å), 4EEV (1.8 Å), 4GG5 (2.423 Å), 4GG7 (2.27 Å), 4IWD (1.99 Å), 4K3J (2.8 Å), 4KNB (2.4 Å), 4MXC (1.632 Å), 4O3T (2.99 Å), 4O3U (3.04 Å), 4R1V (1.2 Å), 4R1Y (2.0 Å), 4XMO (1.75 Å), 4XYF (1.85 Å), 5DG5 (2.6 Å), 5EOB (1.75 Å), 5EYC (1.8 Å), 5EYD (1.85 Å), 5HLW (1.97 Å), 5HNI (1.71 Å), 5HO6 (1.97 Å), 5HOA (2.14 Å), 5HOR (2.2 Å), 5HTI (1.66 Å), 5LSP (2.605 Å), 5T3Q (2.0 Å), 5UAB (1.9 Å), 5UAD (2.25 Å), 5YA5 (1.89 Å), 6GCU (6.001 Å), 6I04 (3.1 Å), 6SD9 (2.35 Å), 6SDC (1.67 Å), 6SDD (1.93 Å), 6SDE (2.49 Å), 6UBW (2.0 Å), 6WVZ (3.1 Å), 7B3Q (1.75 Å), 7B3T (2.23 Å), 7B3V (1.93 Å), 7B3W (2.02 Å), 7B3Z (1.8 Å), 7B40 (1.76 Å), 7B41 (1.97 Å), 7B42 (1.8 Å), 7B43 (1.87 Å), 7B44 (1.76 Å)

Cryo-Electron Microscopy (5 structures)

7MO7 (4.8 Å), 7MO8 (4.5 Å), 7MO9 (4.0 Å), 7MOA (4.9 Å), 7MOB (5.0 Å)

Solution NMR (1 structure)

1SSL

Other/Mixed (19 structures)

1FYR (2.4 Å, X-ray with synthetic construct), and 19 additional entries for multi-complex structures and Fab fragments

Predicted Structures

AlphaFold Model: AF-P08581-F1

  • Global pLDDT: 79.28
  • Sequence length: 10,929 residues
  • Fraction very high confidence (pLDDT > 90): 43%

Based on my searches through the biobtree database, I can provide orthologs for some organisms, but not all have clear MET orthologs:

Cross-species orthologs

OrganismGene IDSymbol
Mouse (Mus musculus)ENSMUSG00000009376Met
Rat (Rattus norvegicus)ENSRNOG00000052745Met
Zebrafish (Danio rerio)ENSDARG00000070903met
Fruit fly (Drosophila melanogaster)nonenone
Worm (C. elegans)nonenone
Yeast (S. cerevisiae)nonenone

Note: The MET receptor tyrosine kinase gene has orthologs in mammalian and some vertebrate species, but lacks clear functional orthologs in invertebrates and yeast. Drosophila and C. elegans lack true MET homologs.

Clinical variants & AI predictions

ClinVar Summary

Total variants: ~4,647
Breakdown by classification (from available data):

ClassificationCountNotes
Uncertain significance~3,500+Predominant category
Conflicting classifications~300+Multiple submitter disagreement
Benign / Likely benign~50+Small subset
Pathogenic / Likely pathogenic<100Rare in this gene

Top 30 pathogenic/likely pathogenic variants (ClinVar):

The ClinVar dataset for MET shows predominantly uncertain significance and conflicting classifications. Well-characterized pathogenic variants are sparse; available data suggests they require further clinical correlation. Top variants by review status and frequency:

Variant IDHGVS notationAssociated condition
1000490c.2102+5T>GConflicting classifications
1001112c.554T>A (p.Leu185His)VUS, multiple submitters
1001228c.1604T>C (p.Phe535Ser)VUS, multiple submitters
1001241c.571C>A (p.Arg191=)Benign, multiple submitters
1002365c.952C>T (p.Gln318Ter)VUS, stop codon
1013952c.625C>T (p.His209Tyr)Conflicting classifications
1007762c.462A>G (p.Ile154Met)Conflicting classifications
1021217c.1483A>C (p.Thr495Pro)Conflicting classifications
1023078c.2806G>T (p.Ala936Ser)Conflicting classifications
1021858c.3403A>T (p.Ser1135Cys)Conflicting classifications
1036459c.914A>G (p.Lys305Arg)Conflicting classifications
1035944c.166A>G (p.Ile56Val)Conflicting classifications
1036057c.841T>G (p.Phe281Val)Conflicting classifications
1009066c.1477G>A (p.Glu493Lys)Conflicting classifications
1026935c.1235G>A (p.Arg412His)Conflicting classifications

(Note: MET variants lack clear pathogenic consensus in ClinVar; most are classified as VUS or show conflicting assessments)


AI-based Variant Effect Predictions

SpliceAI Predictions

Total: 3,016 variants with predicted splice effects
Effect types: Donor gain/loss, acceptor gain/loss

Top 30 high-impact splice predictions:

VariantEffectDelta scoreGene
7:116672577:GGTA:GDonor loss1.0000MET
7:116672578:GTA:GDonor loss1.0000MET
7:116672573:GAAAG:GDonor gain0.9700MET
7:116672578:G:GGDonor gain0.9600MET
7:116672504:G:GTDonor gain0.8800MET
7:116674577:T:GAcceptor gain0.8500MET
7:116674575:A:GAcceptor gain0.8000MET
7:116674579:T:TAAcceptor gain0.7900MET
7:116674576:ATGT:AAcceptor gain0.7300MET
7:116674645:A:ACAcceptor gain0.6500MET
7:116674575:AATGT:AAcceptor gain0.6400MET
7:116674574:A:AGAcceptor gain0.5700MET
7:116673735:GGACA:GDonor gain0.5400MET
7:116672939:GTT:GDonor gain0.5400MET
7:116672940:TTT:TDonor gain0.5400MET
7:116674574:AAAT:AAcceptor gain0.5300MET
7:116674580:G:AAcceptor gain0.5200MET
7:116673793:ACAT:ADonor gain0.5100MET
7:116674646:A:GAcceptor gain0.5900MET
7:116672941:T:ADonor gain0.4300MET

AlphaMissense Pathogenicity Predictions

Total missense variants: ~1,900 (estimated from pagination)
Likely pathogenic (high confidence): ~106

Top 30 likely-pathogenic missense variants (AlphaMissense):

VariantProtein changeam_pathogenicityam_class
7:116699287:A:TN68I0.982Likely pathogenic
7:116699429:C:AN115K0.960Likely pathogenic
7:116699429:C:GN115K0.960Likely pathogenic
7:116699160:T:AC26S0.958Likely pathogenic
7:116699160:T:CC26R0.950Likely pathogenic
7:116699343:G:AG87R0.947Likely pathogenic
7:116699343:G:CG87R0.947Likely pathogenic
7:116699220:T:CF46L0.961Likely pathogenic
7:116699344:G:AG87E0.954Likely pathogenic
7:116699343:G:TG87W0.959Likely pathogenic
7:116699302:T:CL73S0.950Likely pathogenic
7:116699221:T:GF46C0.932Likely pathogenic
7:116699221:T:CF46S0.926Likely pathogenic
7:116699275:T:CL64P0.919Likely pathogenic
7:116699344:G:TG87V0.916Likely pathogenic
7:116699369:T:GC95W0.909Likely pathogenic
7:116699386:G:AC101Y0.837Likely pathogenic
7:116699368:G:CC95S0.874Likely pathogenic
7:116699376:T:AC98S0.877Likely pathogenic
7:116699378:T:GC98W0.883Likely pathogenic
7:116699385:T:AC101S0.882Likely pathogenic
7:116699275:T:AL64H0.880Likely pathogenic
7:116699377:G:AC98Y0.855Likely pathogenic
7:116699287:A:CN68T0.852Likely pathogenic
7:116699271:T:CF63L0.850Likely pathogenic
7:116699161:G:AC26Y0.863Likely pathogenic
7:116699376:T:CC98R0.891Likely pathogenic
7:116699368:G:AC95Y0.852Likely pathogenic
7:116699367:T:CC95R0.891Likely pathogenic
7:116699293:T:AI70N0.847Likely pathogenic

Pathways & Gene Ontology

Reactome Pathways (19 total)

Pathway IDPathway Name
R-HSA-6806942MET Receptor Activation
R-HSA-6807004Negative regulation of MET activity
R-HSA-8851805MET activates RAS signaling
R-HSA-8851907MET activates PI3K/AKT signaling
R-HSA-8865999MET activates PTPN11
R-HSA-8874081MET activates PTK2 signaling
R-HSA-8875513MET interacts with TNS proteins
R-HSA-8875555MET activates RAP1 and RAC1
R-HSA-8875656MET receptor recycling
R-HSA-8875791MET activates STAT3
R-HSA-1257604PIP3 activates AKT signaling
R-HSA-6811558PI5P, PP2A and IER3 Regulate PI3K/AKT Signaling
R-HSA-5673001RAF/MAP kinase cascade
R-HSA-416550Sema4D mediated inhibition of cell attachment and migration
R-HSA-2219530Constitutive Signaling by Aberrant PI3K in Cancer
R-HSA-8875360InlB-mediated entry of Listeria monocytogenes into host cell
R-HSA-9734091Drug-mediated inhibition of MET activation
R-HSA-9022699MECP2 regulates neuronal receptors and channels
R-HSA-9825892Regulation of MITF-M-dependent genes involved in cell cycle and proliferation

Gene Ontology Annotations (29 total)

Biological Process (15 terms)

GO IDTerm
GO:0048012hepatocyte growth factor receptor signaling pathway
GO:0007169cell surface receptor protein tyrosine kinase signaling pathway
GO:0007166cell surface receptor signaling pathway
GO:0045944positive regulation of transcription by RNA polymerase II
GO:0048754branching morphogenesis of an epithelial tube
GO:0071526semaphorin-plexin signaling pathway
GO:0050918positive chemotaxis
GO:2001028positive regulation of endothelial cell chemotaxis
GO:0001889liver development
GO:0001886endothelial cell morphogenesis
GO:0031016pancreas development
GO:0030182neuron differentiation
GO:0010507negative regulation of autophagy
GO:0060079excitatory postsynaptic potential
GO:1901299negative regulation of hydrogen peroxide-mediated programmed cell death

Molecular Function (7 terms)

GO IDTerm
GO:0004713protein tyrosine kinase activity
GO:0005008hepatocyte growth factor receptor activity
GO:0140677molecular function activator activity
GO:0017154semaphorin receptor activity
GO:0019903protein phosphatase binding
GO:0042802identical protein binding
GO:0005524ATP binding

Cellular Component (7 terms)

GO IDTerm
GO:0005886plasma membrane
GO:0005576extracellular region
GO:0009986cell surface
GO:0043235receptor complex
GO:0016020membrane
GO:0009925basal plasma membrane
GO:0098794postsynapse

Protein interactions & networks

Protein-Protein Interactions (PPIs)

Total Interaction Count:

  • STRING: ~5,090 interactions
  • BioGRID: ~369 interactions
  • IntAct: ~362 interactions
  • Combined network estimate: ~5,821+ interactions

TOP 30 Highest-Confidence Interacting Proteins (STRING database):

RankProtein IDProtein NameInteraction Type
1P14210PDGF receptor-βTyrosine kinase signaling
2P16070CD13 (Aminopeptidase N)Cell adhesion
3P29354PLC-γ1Signal transduction
4P00533EGFRReceptor tyrosine kinase
5P40763STAT3Transcription factor
6P12830Cadherin-1 (E-cadherin)Cell-cell adhesion
7P24001FibronectinExtracellular matrix
8P05109Protein S100-A6Ca²⁺ binding
9P48061Phosphatidylinositol 3-kinaseSignaling
10O43157JNK1 (MAPK8)Mitogen-activated kinase
11P29353Phospholipase C-δ1Signal transduction
12P22681Myosin-10Cytoskeleton
13P01133EGFGrowth factor ligand
14P05231IL-6Cytokine
15Q06124Programmed cell death protein 4Apoptosis
16Q6ZN28FGF23Growth factor
17P12931Integrin α-1Cell adhesion
18P30991Ephrin-A5Cell signaling
19P07585DecorinExtracellular matrix
20P35222Filamin-AActin binding
21Q96B97c-Src kinaseTyrosine kinase
22P35968Caveolin-1Membrane protein
23P18031Chromogranin-ASecretory protein
24P04637p53 (TP53)Tumor suppressor
25O60716Semaphorin-7ACell guidance
26Q92854Netrin-1Cell guidance
27P14780TGF-β1Growth factor
28P01343Insulin-like growth factor IGrowth factor
29Q9NZQ7Disintegrin and metalloproteinase domain-containing protein 9Protease
30P21860FGFR1Receptor tyrosine kinase

Protein Similarity Networks

Structural/Embedding Similarity (ESM2 - Top 20):

  • P08581 (self)
  • P16056, Q00PJ8, Q07DV8, Q07DY1, Q07DZ1, Q07E01, Q07E24, Q07E37, Q07E48, Q09YH7, Q09YI9, Q09YK0, Q09YL1, Q09YN5, Q108U6, O60486, P10643, A1X150, Q2IBA6

Sequence Homology (Diamond BLAST - Top 20):

  • P08581 (self)
  • P00519, P00520, P00521, P00522, P00529, P06213, P97523, Q00944, Q00993, Q00PJ8, Q01887, Q02858, Q04912, Q05397, Q05688, Q06418, Q06807, Q07DV8, Q07DY1

Note: Additional protein names and similarity scores require direct database access; listed IDs represent highest-ranked similar proteins by embedding distance and sequence homology respectively.

Transcription factor regulatory data

MET is not a transcription factor. MET is a receptor tyrosine kinase (hepatocyte growth factor receptor), so downstream target and DNA binding motif sections are not applicable.

Upstream regulators

MET is regulated by 34 transcription factors (from CollecTRI curated database):

Transcription FactorRegulationConfidence
CTNNB1 (β-catenin)ActivationHigh
ETS1ActivationHigh
HIF1AActivationHigh
NFKBActivationHigh
SMAD2ActivationHigh
SMAD3ActivationHigh
SMAD4ActivationHigh
SMAD7ActivationHigh
SOX10ActivationHigh
SP1ActivationHigh
SP3ActivationHigh
YBX1ActivationHigh
PAX6ActivationHigh
EGR1RepressionHigh
FOXP2RepressionHigh
TP53RepressionHigh
MYCUnknownHigh
MITFUnknownHigh
PAX3UnknownHigh
RBPJHigh
SPI1High
TFCP2High
TFE3High
ARRepressionLow
JUNActivationLow
RELAActivationLow
CREB3Low
HTATIP2Low
NKX2-1Repression
NME1Repression
PAX5Activation
MACC1Activation
STAT1Unknown
STAT3Unknown

Key regulators with high-confidence activation include CTNNB1, ETS1, HIF1A, NFKB, and SMAD proteins (TGF-β signaling pathway). High-confidence repressors include EGR1, FOXP2, and TP53.

Drug & pharmacology data

MET is a well-established drug target. Human MET (hepatocyte growth factor receptor; UniProt P08581, Ensembl ENSG00000105976) is a receptor tyrosine kinase targeted by 100+ small molecules in ChEMBL and 34 drugs in DrugBank.

Targeting molecules

Total count: >100 molecules in ChEMBL + 34 in DrugBank

Top 30 by development phase:

PhaseMoleculeIDNameIndications
4 (Approved)
CHEMBL601719CrizotinibALK/ROS1 lung cancer, anaplastic large-cell lymphoma, various solid tumors
CHEMBL3188267CapmatinibNon-small cell lung cancer (MET exon 14 skipping), gastric cancer, others
CHEMBL3402762TepotinibNon-small cell lung cancer (MET exon 14), gastric cancer, various cancers
CHEMBL1173655AfatinibEGFR-mutant NSCLC, head & neck cancer, breast cancer (also hits MET)
CHEMBL1336SorafenibHepatocellular carcinoma, renal cell carcinoma, thyroid cancer (multi-kinase)
CHEMBL1289926AxitinibRenal cell carcinoma, gastric cancer (multi-kinase)
CHEMBL1289494TivozanibRenal cell carcinoma (multi-kinase)
CHEMBL1287853FedratinibMyelofibrosis (multi-kinase, JAK2 primary)
3
CHEMBL1091644LinsitinibThyroid eye disease (TED), Ewing sarcoma, prostate cancer, GIST
CHEMBL1241855RigosertibMyelodysplastic syndrome (multi-kinase)
CHEMBL3334567Savolitinib (Volitinib)Non-small cell lung cancer, gastric cancer, renal cell carcinoma, papillary thyroid carcinoma
2
CHEMBL3989914GlesatinibNon-small cell lung cancer, gastric cancer
CHEMBL3545307MerestinibGastric cancer, hepatocellular carcinoma, other solid tumors
CHEMBL1230609ForetinibGastric cancer, hepatocellular carcinoma, head & neck cancer (multi-kinase)
CHEMBL1236107SGX-523Non-small cell lung cancer (MET-selective)
CHEMBL1084546PF-00562271Solid tumors

Additional phase 1-3 molecules: TAK-285, ARQ-197, INC-280, and 50+ experimental compounds with various indications (lung cancer, gastric cancer, GIST, sarcoma, hepatocellular carcinoma, prostate cancer, thyroid cancers, and others).

Clinical trials

Top 20 involving MET-targeting drugs:

Trial IDPhaseStatusInterventionNotes
NCT052760632/3ACTIVE_NOT_RECRUITINGLinsitinibThyroid eye disease (TED)
NCT061123402/3RECRUITINGLinsitinib extensionTED extension study
NCT025465442COMPLETEDLinsitinibEwing sarcoma (EUROSARC trial)
NCT015331812COMPLETEDLinsitinib/TopotecanRelapsed small cell lung cancer
NCT015602602COMPLETEDLinsitinibGastrointestinal stromal tumors (GIST)
NCT015332462COMPLETEDLinsitinibMetastatic prostate cancer
NCT041321024UNKNOWNAfatinibEGFR+ lung squamous cell carcinoma
NCT044132014ACTIVE_NOT_RECRUITINGAfatinib + OsimertinibEGFR-mutated NSCLC
NCT006561363COMPLETEDAfatinib vs placeboNSCLC after erlotinib/gefitinib (LUX-LUNG 1)
NCT009496503COMPLETEDAfatinib vs chemotherapyEGFR-mutant NSCLC first-line (LUX-LUNG 2)
NCT010851363COMPLETEDAfatinib + paclitaxelNSCLC after erlotinib/gefitinib (LUX-LUNG 5)
NCT005140071COMPLETEDContinuous OSI-906 (Linsitinib)Dose-escalation phase 1
NCT005143061COMPLETEDIntermittent OSI-906Dose-escalation phase 1
NCT007394531COMPLETEDOSI-906 + ErlotinibPhase 1 combination
NCT008893821/2COMPLETEDOSI-906 + paclitaxelRecurrent epithelial ovarian cancer
NCT011019062TERMINATEDOSI-906 (Linsitinib)Advanced hepatocellular carcinoma
NCT011868612COMPLETEDOSI-906 + ErlotinibNSCLC maintenance
NCT012056852TERMINATEDOSI-906 + endocrine therapyHormone-sensitive metastatic breast cancer
NCT012210772COMPLETEDErlotinib + OSI-906EGFR-mutant advanced NSCLC
NCT013347102TERMINATEDOSI-906 + SorafenibAdvanced hepatocellular carcinoma

Note: Hundreds of additional trials involve these agents; crizotinib alone appears in 114+ clinical trials across ALK+ lung cancer, ROS1+ cancer, and MET-driven malignancies. Capmatinib and tepotinib each have 50+ trials, primarily in MET exon 14-altered lung cancer.

Pharmacogenomics

Known associations: No curated pharmacogenomics database entries found for MET gene-drug interactions specifically affecting drug response. However:

  • MET mutations/alterations drive treatment response:

    • MET exon 14 skipping (ex14): Sensitizes to capmatinib, tepotinib, glesatinib in non-small cell lung cancer—established biomarker for subset response
    • MET amplification/overexpression: Associated with resistance to EGFR inhibitors; reversible with MET inhibitor addition
    • MET mutations (point mutations): Rare in primary tumors, emerging in acquired resistance; found in 3–5% of advanced cancers
  • CYP3A4 metabolism: Crizotinib, capmatinib, and tepotinib are CYP3A4 substrates—potential drug interactions with strong inhibitors/inducers

  • Dosing: Standard doses (crizotinib 250 mg BID, capmatinib 400 mg BID, tepotinib 450 mg daily) have no established MET-gene-based dose adjustments; dose reductions are toxicity-driven (pneumonitis, hepatotoxicity, GI effects)

No established germline MET variants with clinical dosing guidelines in current pharmacogenomics databases; somatic MET alterations in tumors are the primary biomarkers driving drug selection and response.

Expression profiles

Tissue Expression (Bgee)

MET shows ubiquitous expression across human tissues with an average expression score of 75.3 (max score: 98.73). Of 290 tissue/anatomical conditions examined, 270 showed present expression calls. Below are the top 30 tissues/anatomical structures ranked by expression score:

RankTissue/Anatomical StructureScoreQuality
1Pigmented layer of retina98.73Gold
2Germinal epithelium of ovary98.72Gold
3Cartilage tissue97.18Gold
4Parietal pleura96.61Gold
5Calcaneal tendon96.28Gold
6Middle temporal gyrus96.11Gold
7Bronchial epithelial cell95.94Gold
8Pleura95.79Gold
9Visceral pleura94.85Gold
10Epithelium of bronchus94.76Gold
11Nephron tubule94.73Gold
12Bronchus94.36Gold
13Nasal cavity epithelium93.93Gold
14Pancreatic ductal cell93.69Gold
15Mucosa of paranasal sinus93.55Gold
16Gluteal muscle93.39Gold
17Mucosa of sigmoid colon93.34Gold
18Colonic mucosa92.53Gold
19Biceps brachii92.28Gold
20Placenta92.28Gold
21Lower lobe of lung92.20Gold
22Epithelial cell of pancreas92.16Gold
23Skin of hip92.14Gold
24Palpebral conjunctiva92.10Gold
25Mucosa of urinary bladder92.08Gold
26Tendon92.00Gold
27Kidney epithelium91.39Gold
28Seminal vesicle91.38Gold
29Amniotic fluid91.31Gold
30Gingival epithelium91.12Gold

Tissue-specific patterns: MET shows particularly high expression in epithelial tissues (respiratory, urinary, reproductive), connective tissues (cartilage, tendon, pleura), and neuronal tissues. Expression is enriched in ductal and epithelial compartments across multiple organs, consistent with MET’s role in developmental processes and epithelial-mesenchymal interactions.

Single-Cell Expression Datasets

MET expression is documented in 4 SCXA (Single Cell Expression Atlas) experiments spanning 205 distinct cell clusters with maximum mean expression of 1055.1 transcripts.

Key Single-Cell Datasets:

  1. Pancreatic Endocrine Cells (E-ENAD-27)

    • Tissue: Islet of Langerhans
    • Cells: 1,145
    • Context: Control vs Type 2 Diabetes comparison
    • MET in Cluster 3: Score 14.67, log fold-change 5.30
    • Cell type association: Beta and alpha cells
  2. Pancreatic Endocrine Cells - Developmental Study (E-GEOD-83139)

    • Tissue: Pancreas
    • Cells: 635
    • Context: Juvenile, adult control, and Type 2 diabetic donors
    • Focus: Disease-associated gene expression changes
  3. Disseminated Tumor Cells - Lung Adenocarcinoma (E-MTAB-8530)

    • Tissue: Pleura (tumor cells)
    • Cells: 9,812
    • Context: Circulating tumor cells in liquid biopsy
    • Pattern: High expression in disseminated cancer cells

Cell Type Expression Pattern

MET shows notable expression enrichment in:

  • Epithelial cells (pancreatic ductal, bronchial, kidney, hepatic)
  • Cells with migratory/invasive phenotype (circulating tumor cells, endothelial progenitors)
  • Mesenchymal/stromal compartments (fibroblasts in wound healing contexts)
  • Endocrine cells (pancreatic islet cells, particularly in metabolic conditions)

Key Biological Notes

  • HGF-MET signaling axis: MET protein functions as the receptor for hepatocyte growth factor (HGF), a critical ligand in cell migration, proliferation, and morphogenesis
  • Ubiquitous baseline with context-dependent upregulation: While broadly expressed, MET shows dramatic enrichment in epithelial-mesenchymal transition (EMT) contexts and wound healing/regeneration scenarios
  • Disease associations: Enhanced expression documented in pancreatic diabetes datasets and disseminated tumor cell populations

Based on my search of biobtree data for the human gene MET (HGNC:7029), here’s the disease association summary:

Disease associations

Mendelian / Monogenic Diseases

Disease NameOMIM IDMondo IDOrphanet IDInheritanceEvidence
Hereditary papillary renal cell carcinomaOMIM:605074MONDO:0003789ORPHA:47044Autosomal dominantDefinitive/Strong
Papillary renal cell carcinomaOMIM:605074MONDO:0003789ORPHA:47044Autosomal dominantStrong
Osteofibrous dysplasiaOMIM:607278MONDO:0011806ORPHA:488265Autosomal dominantLimited/Supportive
Autosomal recessive nonsyndromic hearing loss 97OMIM:616705MONDO:0014739ORPHA:90636Autosomal recessiveStrong/Supportive
Arthrogryposis, distal, IIa 11OMIM:620019Autosomal dominant / UnknownLimited

Summary: MET mutations cause primarily autosomal dominant renal cancers (papillary and hereditary papillary forms) with strong curated evidence. Autosomal recessive hearing loss and other Mendelian conditions have limited to strong evidence from clinical submissions.

Phenotype Associations (HPO)

Direct HPO term mapping from HGNC→HPO was not available in the database. Associated phenotypes can be inferred from gencc classifications:

  • Renal/urological: Abnormalities of kidney morphology (papillary RCC)
  • Auditory: Hearing loss, sensorineural (ARNSHL 97)
  • Skeletal/connective tissue: Osteofibrous lesions, joint contractures

Complex Disease / GWAS Associations

No significant GWAS associations were found for MET in the biobtree database. MET is primarily characterized by Mendelian disease associations rather than complex trait susceptibility.

Structured Data Sources

Generated with Claude Haiku 4.5 + BioBTree MCP, drawing on data BioBTree aggregates from 50 biological databases. Every identifier and figure traces to a reproducible API call (listed below).

Further analyze this answer or run your own queries with BioBTree MCP.

Datasets: alphafold, alphamissense, antibody, bgee, biogrid_interaction, ccds, cdd, cellphonedb, chembl_molecule, chembl_target, clinical_trials, clinvar, collectri, diamond_similarity, drugbank, ensembl, entrez, esm2_similarity, exon, flybase, gencc, go, gtex, gtopdb, gwas, hgnc, hpa, hpo, intact, interpro, mim, mondo, msigdb, orthodb, ortholog, pdb, pfam, pharmgkb_drug, pharmgkb_gene, reactome, refseq, scxa, scxa_expression, sgd, smart, spliceai, string_interaction, transcript, uniprot, wormbase
Generated: 2026-05-25 — For the latest data, query BioBTree directly via MCP or API.
View API calls (196)