VEGFA Gene Complete Identifier and Functional Mapping Reference

Executive summary

VEGFA (vascular endothelial growth factor A; HGNC:12680, chromosome 6) is the master regulator of angiogenesis and vascular permeability, making it one of the most clinically targeted genes in medicine. Its extraordinary transcript diversity — 26 Ensembl transcripts (20 protein-coding) and 41 RefSeq mRNA isoforms — reflects complex post-transcriptional regulation, while the canonical protein (UniProt P15692) harbors PDGF/VEGF and heparin-binding domains and engages ~160 documented protein partners, most critically VEGFR1 (FLT1) and VEGFR2 (KDR). Expression is ubiquitous across 297 Bgee tissue calls (max score 99.59), driven by upstream regulators including HIF1A, STAT3, and TP53, and the gene carries strong GWAS signals for cytokine levels (p = 7×10⁻³⁰⁶), metabolic traits, and VEGF protein levels themselves (p = 2×10⁻¹⁷¹). Three Phase 4 approved therapeutics — bevacizumab, ranibizumab, and aflibercept — directly neutralize VEGFA protein and underpin thousands of clinical trials spanning oncology and ophthalmology. ClinVar harbors only 2 likely pathogenic variants, underscoring that disease impact arises primarily through expression dysregulation rather than coding mutations.

Gene identifiers

Transcript identifiers

Ensembl Transcripts (26 total)

Protein-coding: 20 | Retained intron: 6

RefSeq Transcripts — mRNA (41 total)

CCDS IDs (17 total)

CCDS4907, CCDS34457, CCDS34458, CCDS47432, CCDS47433, CCDS47434, CCDS47435, CCDS55007, CCDS55008, CCDS55009, CCDS55010, CCDS55011, CCDS55012, CCDS55013, CCDS55014, CCDS55015, CCDS69125

MANE Select Transcript Exons (ENST00000672860 / NM_003376)

8 exons total

Protein identifiers

UniProt Accessions (14 total)

• P15692 ⭐ Canonical reviewed entry — Vascular endothelial growth factor A, long form
• A0A0A0MR43 (unreviewed)
• A0A0A0MRQ4 (unreviewed)
• A0A0A0MSH5 (unreviewed)
• A0A0A0MSH7 (unreviewed)
• A0A0A0MSI7 (unreviewed)
• A0A0A0MTB2 (unreviewed)
• A0A0Y0IMM4 (unreviewed)
• A0A5F9ZH41 (unreviewed)
• A2A2V4 (unreviewed)
• H0YBI8 (unreviewed)
• H0YBZ0 (unreviewed)
• H3BLW8 (unreviewed)
• J3KPA4 (unreviewed)

RefSeq Protein Accessions (NP_) — 31 total

Human (Chromosome 6): NP_001020537, NP_001020538, NP_001020539, NP_001020540, NP_001020541, NP_001028928, NP_001165093, NP_001165094, NP_001165095, NP_001165096, NP_001165097, NP_001165098, NP_001165099, NP_001165100, NP_001165101, NP_001191313, NP_001191314, NP_001273973, NP_001303939, NP_003367

Mouse orthologs (Chromosome 17 & 9): NP_001020421, NP_001020428, NP_001103736, NP_001103737, NP_001103738, NP_001273985, NP_001273986, NP_001273987, NP_001303970, NP_033531, NP_001103803, NP_001103804, NP_001103805, NP_001103806, NP_001274036, NP_001274037, NP_001274039, NP_001274040, NP_001274041, NP_001274042, NP_001274043, NP_001274044, NP_001303972, NP_114024

Protein Domains and Families (6 annotated)

Pfam entries: PF00341, PF14554

Antibody Resources

Human Protein Atlas (HPA) — Primary antibody resource for VEGFA (ENSG00000112715). Access via HPA database or UniProt P15692 links to commercial and research antibody availability.

Structure

Experimental Structures (PDB)

X-RAY DIFFRACTION (52 structures):

SOLUTION NMR (4 structures):

• 1KAT
• 1KMX
• 1VGH
• 2VGH

Total Experimental Structures: 56

Predicted Structures

AlphaFold:

• Model ID: P15692
• pLDDT (Global): 65.32
• pLDDT ≥ 70 (Fraction): 0.29 (29% of residues)

Cross-species orthologs

Clinical variants & AI predictions

ClinVar Variant Summary

Top Pathogenic/Likely Pathogenic ClinVar Variants

Note: Only 2 pathogenic/likely pathogenic variants in ClinVar. Remaining variants are VUS, benign, or likely benign.

AlphaMissense Missense Pathogenicity (TOP 30 Likely-Pathogenic)

AlphaMissense Total: ~100+ likely-pathogenic missense predictions identified

SpliceAI Predictions Summary

TOP 30 SpliceAI High-Confidence Splice Effects (score ≥0.90)

Now let me compile the complete data into the requested format.

Pathways & Gene Ontology

Reactome Pathways (10 total)

MSigDB Gene Sets (1,086 total)

Representative examples include VEGF signaling pathways, GO-based gene sets (vascular development, endothelial cell processes, hypoxia response), transcription factor motifs, and disease-associated gene sets.

Gene Ontology Annotations

Total GO Terms: 144

• Biological Process: 116 terms
• Molecular Function: 15 terms
• Cellular Component: 13 terms

Biological Process (TOP 20)

Molecular Function (TOP 15)

Cellular Component (TOP 13)

Protein interactions & networks

Human VEGFA (UniProt: P15692)

Protein-protein interactions

Total interaction count: ~160 interactions documented (113 from BioGRID, 53 from IntAct, 18 from SIGNOR)

TOP 30 highest-confidence interacting proteins:

Protein similarity

Structural/embedding similarity (ESM2): TOP 15 similar proteins

Sequence homology (DIAMOND): TOP 20 homologous proteins

Transcription factor regulatory data

VEGFA is not a transcription factor. VEGFA (vascular endothelial growth factor A, P15692) is a secreted signaling protein that acts through cell-surface receptors (VEGFR1/VEGFR2), not a DNA-binding transcription factor. No DNA binding motifs are found in JASPAR.

Upstream regulators of VEGFA

VEGFA expression is regulated by 164 transcription factors (from collectri database):

Key activators (high-confidence): AR, ATF4, CTNNB1, DLX4, DNMT1, E2F8, EGR1, EPAS1, ESR1, FOXO1, GATA4, GLI1, HDGF, HIF1A, ID1, MITF, MTA1, MYC, MYOD1, NFKB, PPARA, PPARD, PPARG, RUNX2, SALL1, SMAD1, SMAD2, SP1, STAT3, TEAD1, TFAP2A, TFE3, TP53, WT1, YY1

Key repressors (high-confidence): AHR, AP1, BHLHE40, E2F1, FOXP3, HHEX, JUN, NFE2L2, NR1H2, NR2E1, NR2F2, PAX6, RARA, RUNX1, SMAD4, SOX9, SREBF1, TEAD4, ZNF24

Note on evidence: Regulatory relationships include experimentally validated (ChIP-seq, reporter assays), computationally predicted, or literature-curated interactions. Confidence levels range from high (curated multi-evidence) to low/unknown (predicted or limited evidence). The most robust regulators include HIF1A (hypoxia pathway), STAT3 (JAK-STAT signaling), TP53 (p53-mediated response), and multiple nuclear receptors (PPARA/D/G, ESR1) reflecting VEGFA’s role in angiogenesis, immune response, and metabolic regulation.

Based on my search of BioDBtree, VEGFA is a well-established and extensively targeted drug target with major clinical significance, particularly for oncology and ophthalmology indications.

Drug & pharmacology data

Targeting Molecules

Total count: 100+ small molecules and biologics targeting VEGFA in ChEMBL (with continued discovery indicated by pagination). The three major approved anti-VEGF therapeutics are:

TOP APPROVED DRUGS (Phase 4)

Clinical Trials

Top 20 trials involving VEGFA-targeting drugs (selection from 2,257+ bevacizumab, 449+ ranibizumab, 359+ aflibercept trials):

Oncology (recent/active):

1. NCT05185505 – Atezolizumab + Bevacizumab for hepatocellular carcinoma (RECRUITING)
2. NCT05525767 – Chemotherapy + Bevacizumab for HER2-negative breast cancer (RECRUITING)
3. NCT06121401 – Olaparib + Bevacizumab for HRD-positive cancers (ACTIVE)
4. NCT06843954 – VEGFA polymorphisms & bevacizumab efficacy in colorectal cancer (COMPLETED)

Ophthalmology (major Phase 3/4): 5. NCT01127360 – LUCAS: Lucentis vs. Avastin for AMD (COMPLETED) 6. NCT00682539 – Anti-VEGF vs. triamcinolone in diabetic macular edema (COMPLETED) 7. NCT01957918 – Ranibizumab PRN vs. aflibercept bimonthly in wet AMD (COMPLETED) 8. NCT02130024 – Ranibizumab vs. aflibercept for geographic atrophy development (COMPLETED) 9. NCT03148132 – Bevacizumab vs. ranibizumab for retinopathy of prematurity (COMPLETED) 10. NCT01969708 – SCORE2: Comparative treatments for retinal vein occlusion (COMPLETED, Phase 3)

Other conditions: 11. NCT02389959 – Intranasal bevacizumab for HHT epistaxis (COMPLETED) 12. NCT07014280 – Bevacizumab vs. triamcinolone for keloids (ACTIVE)

Pharmacogenomics

Known genetic interactions affecting response:

1. VEGF Polymorphisms – Genetic variants in the VEGFA gene (e.g., -2578C>A, -1154G>A, +405G>C) are associated with variable anti-VEGF drug response and bevacizumab efficacy in colorectal cancer (NCT06843954). Patients with specific VEGF genotypes show differential plasma VEGF levels and treatment outcomes.

2. Metabolism/Clearance genes – Anti-VEGF monoclonal antibodies (bevacizumab, ranibizumab, aflibercept) are metabolized via standard antibody catabolism; no major pharmacokinetic drug-gene interactions documented.

3. Response biomarkers – Baseline serum VEGF levels, aqueous humor cytokine profiles, and genetic variation in VEGFR2 have been studied as predictors of treatment response in AMD and diabetic macular edema, but no standardized pharmacogenomic guidelines are established.

Dosing: Bevacizumab (5–15 mg/kg IV), ranibizumab (0.5–2.0 mg intravitreal), and aflibercept (2–8 mg intravitreal) are dosed empirically. No gene-based dose adjustments are standard; dosing is primarily based on indication and clinical response.

Contraindications: No pharmacogenomic-driven contraindications; safety monitoring focuses on proteinuria, hypertension, and thrombotic events across all patients.

I can provide high-level tissue and cell type expression summaries based on the biobtree data available, but detailed tissue-by-tissue scoring and cell-type-by-cell-type tables from GTEx, HPA, Tabula Sapiens, and other major expression repositories would require access to those databases directly. Here’s what I can compile from the available biobtree data:

Expression profiles

Tissue Expression Summary

From Bgee (Benign Gene Expression): VEGFA shows ubiquitous expression across tissues with:

• Expression breadth: Ubiquitous (expressed in multiple tissues/organs)
• Total present calls: 297
• Max expression score: 99.59

Known major VEGFA expression tissues (based on biological literature integration):

• Vascular tissues (endothelial cells, smooth muscle) - very high
• Hypoxic tissues (kidneys, brain) - elevated
• Reproductive tissues (ovaries, placenta, uterus) - high
• Gastrointestinal tissues - moderate to high
• Bone marrow - elevated
• Adipose tissue - moderate

Single-Cell/Tissue Expression Datasets

Expression Atlas (SCXA) integration identifies 11 datasets with VEGFA data:

Known Cell Type Expression Patterns

Based on VEGFA biology:

• Endothelial cells - primary VEGFA responders and some production
• Fibroblasts - moderate producers under hypoxia
• Macrophages/immune cells - hypoxia-inducible VEGFA expression
• Smooth muscle cells - responsive cells
• Cancer-associated fibroblasts - high VEGFA production
• Tumor cells - hypoxia-driven expression

Note: For comprehensive tissue expression ranking (top 30) with GTEx/HPA quantitative scores and detailed cell-type expression tables from Tabula Sapiens/Human Cell Atlas, you would need direct access to those integrated expression databases (GTEx v8, HPA v22, Tabula Sapiens, HCA). These biobtree mappings provide connective data but not the full expression score matrices.

Disease associations

Mendelian / Monogenic Disease

OMIM Entry: 192240 (VEGFA gene)

ClinVar-linked Diseases:

Evidence: ClinVar variants in VEGFA include mostly benign or uncertain significance classifications, with one likely pathogenic deletion (NM_003376.6(VEGFA):c.576_589del). Most variants are classified as uncertain significance or likely benign, indicating limited evidence for severe monogenic diseases directly caused by VEGFA mutations.

Phenotype Associations

No direct HPO (Human Phenotype Ontology) term associations found in curated databases. VEGFA mutations are primarily associated with disease states and complex trait variation rather than discrete phenotypic features.

Complex-Disease / GWAS

VEGFA shows significant associations with metabolic and vascular phenotypes. Top 30 GWAS associations (by p-value significance):

Key findings: VEGFA variants are predominantly associated with metabolic traits (waist-to-hip ratio, BMI-adjusted measurements, lipid levels), hematologic traits (hemoglobin, red blood cell count, reticulocyte parameters), renal function (GFR, creatinine), and vascular/inflammatory markers (VEGF levels itself, cytokines, coronary artery disease). These associations reflect VEGFA’s established roles in angiogenesis, metabolic regulation, and vascular homeostasis.