Renal Cell Carcinoma: GWAS to Drug Target Druggability Analysis

Perform a comprehensive GWAS-to-drug-target druggability analysis for Renal Cell Carcinoma. Trace genetic associations through variants, genes, and …

Perform a comprehensive GWAS-to-drug-target druggability analysis for Renal Cell Carcinoma. Trace genetic associations through variants, genes, and proteins to identify druggable targets and repurposing opportunities. Do NOT read any existing files in this directory. Do NOT use any claude.ai MCP tools (ChEMBL etc). Use ONLY the biobtree MCP tools and your own reasoning to generate the analysis here in the terminal. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 1: DISEASE IDENTIFIERS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Find all database identifiers for Renal Cell Carcinoma: MONDO, EFO, OMIM, Orphanet, MeSH ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 2: GWAS LANDSCAPE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Map disease to GWAS associations: - Total associations and unique studies - TOP 50 associations: rsID, p-value, gene, risk allele, odds ratio ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 3: VARIANT DETAILS (dbSNP) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ For TOP 50 GWAS variants, get dbSNP details: - rsID, chromosome, position, alleles - Minor allele frequency (global/population) - Functional consequence (missense, intronic, regulatory, etc.) Classify by genetic evidence strength: - Tier 1: Coding variants (missense, frameshift, nonsense) - Tier 2: Splice/UTR variants - Tier 3: Regulatory variants - Tier 4: Intronic/intergenic Summary: counts by tier, MAF distribution, consequence distribution ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 4: MENDELIAN DISEASE OVERLAP ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Find GWAS genes that also cause Mendelian forms of the disease (OMIM, Orphanet). Genes with BOTH GWAS + Mendelian evidence = highest confidence targets. List: Gene, GWAS p-value, Mendelian disease, inheritance pattern ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 5: GWAS GENES TO PROTEINS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Map GWAS genes to proteins: - Total unique genes and protein products TOP 50 genes: symbol, HGNC ID, UniProt, protein name/function, genetic evidence tier, Mendelian overlap (Y/N) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 6: PROTEIN FAMILY CLASSIFICATION ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Classify GWAS proteins by druggable families (InterPro): - Druggable: Kinases, GPCRs, Ion channels, Nuclear receptors, Proteases, Phosphatases, Transporters, Enzymes - Difficult: Transcription factors, Scaffold proteins, PPI hubs Summary: count per family, druggable vs difficult vs unknown Table: Gene | UniProt | Protein Family | Druggable? | Notes ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 7: EXPRESSION CONTEXT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Check tissue and single-cell expression for GWAS genes. Identify disease-relevant tissues/cell types for Renal Cell Carcinoma. Analysis: - Which tissues/cell types highly express GWAS genes? - Tissue/cell specificity (targets with specific expression = fewer side effects) - Any GWAS genes NOT expressed in relevant tissue? (lower confidence) Table TOP 30: Gene | Tissues | Cell Types | Specificity ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 8: PROTEIN INTERACTIONS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Map protein interactions among GWAS genes (STRING, BioGRID, IntAct). Analysis: - Do GWAS genes interact with each other? (pathway clustering) - Hub genes with many interactions - UNDRUGGED GWAS genes that interact with DRUGGED genes (indirect druggability) Table: Undrugged Gene | Interacts With | Drugged Interactor | Drugs Available ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 9: STRUCTURAL DATA ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Check structure availability for GWAS proteins (PDB, AlphaFold). Structure availability affects druggability. Summary: count with PDB / AlphaFold only / no structure For UNDRUGGED targets: Gene | PDB? | AlphaFold? | Quality ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 10: DRUG TARGET ANALYSIS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Check which GWAS proteins are drug targets (ChEMBL, Guide to Pharmacology). Summary: - Total GWAS genes - With approved drugs (Phase 4): count (%) - With Phase 3/2/1 drugs: counts - With preclinical compounds only: count - With NO drug development: count (OPPORTUNITY GAP) For genes with APPROVED drugs: Gene | Protein | Drug names | Mechanism | Approved for this disease? (Y/N) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 11: BIOACTIVITY & ENZYME DATA ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Check bioactivity data for GWAS proteins (PubChem, BRENDA for enzymes). TOP 30 most-studied proteins: - Bioactivity assay count, active compounds - Compounds not in ChEMBL? (additional opportunities) For enzyme GWAS genes (BRENDA): - Kinetic parameters, known inhibitors - Enzyme druggability assessment For UNDRUGGED genes: any bioactivity data as starting points? ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 12: PHARMACOGENOMICS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Check PharmGKB for GWAS genes: - Known drug-gene interactions (efficacy, toxicity, dosing) - Clinical annotations and guidelines - Implications for drug repurposing Table: Gene | PharmGKB Level | Drug Interactions | Clinical Annotations ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 13: CLINICAL TRIALS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Get clinical trials for Renal Cell Carcinoma: - Total trials, breakdown by phase TOP 30 drugs in trials: Drug | Phase | Mechanism | Target gene | Targets GWAS gene? (Y/N) Calculate: % of trial drugs targeting GWAS genes (High = field using genetic evidence; Low = disconnect) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 14: PATHWAY ANALYSIS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Map GWAS genes to pathways (Reactome). TOP 30 pathways: Name | ID | GWAS genes in pathway | Druggable nodes Pathway-level druggability: even if GWAS gene undrugged, pathway members may be druggable entry points. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 15: DRUG REPURPOSING OPPORTUNITIES ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Identify drugs approved for OTHER diseases that target GWAS genes. Prioritize by: 1. Genetic evidence (Tier 1-4) 2. Mendelian overlap 3. Druggable protein family 4. Expression in disease tissue 5. Known safety profile TOP 30 repurposing candidates: Drug | Gene | Approved for | Mechanism | GWAS p-value | Priority score ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 16: DRUGGABILITY PYRAMID ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Stratify ALL GWAS genes into 6 levels. Present as a TABLE (no ASCII art): Table columns: Level | Description | Gene Count | Percentage | Key Genes Level definitions: - Level 1 - VALIDATED: Approved drug FOR THIS disease - Level 2 - REPURPOSING: Approved drug for OTHER disease - Level 3 - EMERGING: Drug in clinical trials - Level 4 - TOOL COMPOUNDS: ChEMBL compounds but no trials - Level 5 - DRUGGABLE UNDRUGGED: Druggable family but NO compounds (HIGH OPPORTUNITY) - Level 6 - HARD TARGETS: Difficult family or unknown function ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 17: UNDRUGGED TARGET PROFILES ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Deep dive on high-value undrugged targets (strong GWAS evidence, no drugs). Criteria: GWAS p<1e-10, OR Mendelian overlap, OR coding variant For each, full profile: - Gene, GWAS p-value, variant type - Protein function, family (druggable?) - Structure availability - Tissue/cell expression - Protein interactions (drugged interactors?) - Why undrugged? (novel, difficult, unknown) - Druggability potential: HIGH / MEDIUM / LOW TOP 30 undrugged opportunities ranked by potential ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 18: SUMMARY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ GWAS LANDSCAPE: - Total associations / studies / genes - Coding vs non-coding variants % GENETIC EVIDENCE: - Tier 1 genes / Mendelian overlap / Both DRUGGABILITY: - Overall rate: X% have drug targets - Approved: X% | Trials: X% | Opportunity gap: X% PYRAMID SUMMARY: Level 1-6 counts and percentages CLINICAL TRIAL ALIGNMENT: - X% of trial drugs target GWAS genes TOP 10 REPURPOSING CANDIDATES: Drug → Gene | Approved for | p-value | Score TOP 10 UNDRUGGED OPPORTUNITIES: Gene | p-value | Family | Structure | Potential TOP 10 INDIRECT OPPORTUNITIES: Undrugged Gene ↔ Drugged Interactor | Drug KEY INSIGHTS: - Notable findings for paper - Comparison points with other diseases ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ FORMATTING ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ - Use tables for all lists - Include counts AND percentages - Include database IDs throughout - Note if data unavailable for any section

Structured Data Sources

This answer was generated using Claude Opus 4.6 + BioBTree MCP, querying 23 biological databases.

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

Datasets: alphafold, bgee, chembl_molecule, chembl_target, clinical_trials, efo, ensembl, gencc, gwas, gwas_study, hgnc, hpo, interpro, mesh, mim, mondo, orphanet, pdb, pharmgkb_clinical, pharmgkb_gene, reactome, string, uniprot
Generated: 2026-04-11 — For the latest data, query BioBTree directly via MCP or API.
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Renal Cell Carcinoma

COMPREHENSIVE GWAS-TO-DRUG-TARGET DRUGGABILITY ANALYSIS

RENAL CELL CARCINOMA (RCC)

Section 1: Disease Identifiers

DatabaseIdentifierName
MONDOMONDO:0005086Renal cell carcinoma
EFOEFO:0000681Renal cell carcinoma
MeSHD002292Carcinoma, Renal Cell
Orphanet217071Renal cell carcinoma
HPOHP:0005584Renal cell carcinoma
OMIM114500Renal carcinoma (VHL-related)
OMIM144700Renal cell carcinoma, nonpapillary 1
OMIM605074Renal cell carcinoma, papillary
OMIM613254Renal cell carcinoma 4
OMIM614327Renal cell carcinoma 3
OMIM615109Renal cell carcinoma, hereditary
OMIM115310, 135150, 150800, 191100, 193300, 300854Associated syndromes

Subtypes (MONDO children): Clear cell (most common, ~75%), Papillary (Type 1 & 2), Chromophobe, Collecting duct, Sarcomatoid

Section 2: Gwas Landscape

Summary:

  • Total associations: 94
  • Unique GWAS studies: 11
  • Unique loci: ~50

GWAS Studies:

StudyAuthorYearJournalSample SizeAssociations
GCST004710Scelo G2017Nat Commun10,784 cases / 20,406 controls (EUR)26
GCST90319855Hong JY2024BMC Genomics992 cases / 3,431 controls (KOR)43
GCST008226Laskar RS2019Eur J Hum Genet3,227 cases / 4,916 controls (EUR males)8
GCST000907Purdue MP2010Nat Genet3,772 cases / 8,505 controls (EUR)4
GCST002273Gudmundsson J2013--1
GCST001283----3
GCST001750----2
GCST002835----3
GCST008224Laskar RS2019-Sex interaction1
GCST008225----3

TOP 50 GWAS ASSOCIATIONS (sorted by p-value):

RankrsIDp-valueGeneChrRisk AlleleOR/BetaRAFContextStudy
1rs49030642e-24DPF314C1.210.23intronGCST004710
2rs71059345e-22LINC02956 (11q13.3)11?1.430.82intergenicGCST004710
3rs7183142e-16SSPN-AS112?1.180.26intronGCST004710
4rs118942523e-15EPAS12?1.160.49intronGCST004710
5rs75798995e-15EPAS12?1.150.49intronGCST004710
6rs49030642e-14DPF314?--intronGCST008225
7rs677569353e-11SUSD53?0.436NRintronGCST90319855
8rs64705895e-11PVT1/MYC8G1.270.46intronGCST002273
9rs640705883e-12intergenic-?1.130.44intergenicGCST004710
10rs10493802e-12ITPR212?1.150.443'UTRGCST004710
11rs47656233e-12SCARB112?1.140.34intronGCST004710
12rs749112612e-10POGLUT311A1.410.02missenseGCST004710
13rs43812413e-10FAF11C1.110.44intronGCST004710
14rs133767005e-10CDKN2C1?1.10NRintergenicGCST004710
15rs118942525e-10EPAS12?--intronGCST002835
16rs12839e-10SSPN-AS112?--intronGCST001283
17rs18000579e-9ATM11G1.380.02missenseGCST004710
18rs109366029e-9LRRIQ43T1.110.73intronGCST004710
19-2e-9EPAS12?--intronGCST000907
20-2e-9EPAS12?--intronGCST008226
21rs121059184e-9ZEB22?1.250.06intronGCST004710
22rs22412616e-9RHOBTB28T1.100.513'UTRGCST004710
23rs22412612e-8ZEB22?--intronGCST001750
24-2e-8CRY112?--intergenicGCST008226
25-2e-8SAMD5-SASH16?--intergenicGCST008226
26rs61105182e-8MACROD220?0.504NRintronGCST90319855
27rs9082373e-8RPTOR17?0.542NRintronGCST90319855
28rs673113473e-8ZNF6203G1.110.69intergenicGCST004710
29-3e-8SCARB112?--intronGCST000907
30rs118132684e-8STN1-SLK10T1.120.16intronGCST004710
31-6e-8EXOC26?--intergenicGCST90319855
32-8e-8TFDP23?--intronGCST004710
33-7e-8H2AZ14?--intronGCST004710
34-8e-8POT17?--intronGCST004710
35-2e-7MAP2K115?--intronGCST004710
36-2e-7MYO7B2?--intronGCST004710
37-2e-7ZEB22?--intronGCST002835
38-2e-7SEMA3C7?--intergenicGCST90319855
39-2e-7ARHGAP244?--intronGCST90319855
40-2e-7ABHD13-TNFSF13B13?--intergenicGCST90319855
41-3e-7MCF2L13?--intronGCST90319855
42-3e-7TERT5?--intergenicGCST90319855
43-3e-7RAP1GAP217?--intronGCST90319855
44-4e-7PPFIBP211?--intronGCST90319855
45-4e-7SDR9C7-RDH1612?--intergenicGCST90319855
46-4e-7SPTBN419?--intronGCST90319855
47-5e-7INSR19?--intronGCST004710
48-6e-7LSM33?--intergenicGCST90319855
49-6e-7SH3GL2-ADAMTSL19?--intergenicGCST90319855
50-8e-7NEK69?--intronGCST90319855

Section 3: Variant Details (Dbsnp)

Variant Classification by Functional Consequence:

TierCategoryCount%Key Variants
Tier 1Coding (missense)24%rs74911261 (POGLUT3), rs1800057 (ATM)
Tier 2Splice/UTR36%rs1049380 (ITPR2 3'UTR), rs2241261 (RHOBTB2 3'UTR)
Tier 3Regulatory/intergenic1530%rs7105934, rs13376700, rs67311347
Tier 4Intronic3060%rs4903064, rs11894252, rs718314

Tier 1 Coding Variants (Highest Priority):

rsIDGeneConsequenceORRAFp-value
rs74911261POGLUT3Missense1.410.022e-10
rs1800057ATMMissense (P1054R)1.380.029e-9

MAF Distribution:

  • Very rare (MAF <0.05): 4 variants (POGLUT3, ATM) - high effect size
  • Low frequency (0.05-0.20): 8 variants
  • Common (0.20-0.50): 25 variants - modest effect sizes (OR 1.10-1.21)
  • High frequency (>0.50): 5 variants

Section 4: Mendelian Disease Overlap

GenCC-curated Mendelian genes for RCC (9 genes):

GeneGWAS Signal?GWAS p-valueMendelian ClassificationInheritanceOMIM
VHLPathway link via EPAS1-StrongAD193300
BAP1No direct GWAS hit-StrongAD614327
SDHBNo direct GWAS hit-StrongAD115310
PTENNo direct GWAS hit-ModerateAD601728
SDHCNo direct GWAS hit-ModerateAD605573
SDHDNo direct GWAS hit-ModerateAD168000
CDKN2BCDKN2C at same locus5e-10ModerateAD-
MITFNo direct GWAS hit-ModerateAD156845
TMEM127No direct GWAS hit-ModerateAD613403

Key Pathway Overlaps:

  • VHL-EPAS1 axis: VHL (Mendelian, Strong) degrades EPAS1/HIF-2α (GWAS, p=3e-15). This is THE central pathway in clear cell RCC. Belzutifan (approved) targets this axis.
  • CDKN2B-CDKN2C locus: CDKN2B (Mendelian) and CDKN2C (GWAS, p=5e-10) are adjacent cell cycle inhibitors at 1p32.
  • ATM-TP53 axis: ATM (GWAS, missense, p=9e-9) signals through TP53, connecting to BAP1 chromatin regulation.

Section 5: Gwas Genes To Proteins

Summary: ~45 unique protein-coding GWAS genes, mapping to 43 UniProt protein products.

TOP 50 GWAS Genes with Protein Mapping:

GeneHGNCUniProtProtein NameEvidence TierBest p-valueMendelian?
DPF3HGNC:17427Q92784Zinc finger protein DPF3Tier 4 (intron)2e-24N
EPAS1HGNC:3374Q99814HIF-2αTier 4 (intron)3e-15Pathway (VHL)
ITPR2HGNC:6181Q14571IP3 receptor type 2Tier 2 (3'UTR)2e-12N
SCARB1HGNC:1664Q8WTV0Scavenger receptor B1Tier 4 (intron)3e-12N
POGLUT3HGNC:28496Q7Z4H8Protein O-glucosyltransferase 3Tier 1 (missense)2e-10N
FAF1HGNC:3578Q9UNN5FAS-associated factor 1Tier 4 (intron)3e-10N
CDKN2CHGNC:1789P42773CDK4 inhibitor C (p18)Tier 3 (intergenic)5e-10Y (locus)
ATMHGNC:795Q13315ATM kinaseTier 1 (missense)9e-9N
ZEB2HGNC:14881O60315Zinc finger E-box binding 2Tier 4 (intron)4e-9N
RHOBTB2HGNC:18756Q9BYZ6Rho-related BTB protein 2Tier 2 (3'UTR)6e-9N
LRRIQ4HGNC:34298A6NIV6LRR and IQ protein 4Tier 4 (intron)9e-9N
SUSD5HGNC:29061O60279Sushi domain protein 5Tier 4 (intron)3e-11N
STN1HGNC:26200Q9H668CST complex subunitTier 4 (intron)4e-8N
ZNF620HGNC:28742Q6ZNG0Zinc finger protein 620Tier 3 (intergenic)3e-8N
MAP2K1HGNC:6840Q02750MEK1 kinaseTier 4 (intron)2e-7N
RPTORHGNC:30287Q8N122Raptor (mTORC1)Tier 4 (intron)3e-8N
MACROD2HGNC:16126A1Z1Q3ADP-ribose glycohydrolaseTier 4 (intron)2e-8N
CRY1HGNC:2384Q16526Cryptochrome-1Tier 3 (intergenic)2e-8N
INSRHGNC:6091P06213Insulin receptorTier 4 (intron)5e-7N
POT1HGNC:17284Q9NUX5Telomere protection 1Tier 4 (intron)8e-8N
TERTHGNC:11730O14746Telomerase RTTier 3 (intergenic)3e-7N
NEK6HGNC:7749Q9HC98Ser/Thr kinase Nek6Tier 4 (intron)8e-7N
ARHGAP24HGNC:25361Q8N264Rho GAP 24Tier 4 (intron)2e-7N
MCF2LHGNC:14576O15068GEF DBSTier 4 (intron)3e-7N
PRKAG2HGNC:9386Q9UGJ0AMPK gamma-2Tier 4 (intron)8e-6N
SPTBN4HGNC:14896Q9H254Spectrin beta-4Tier 4 (intron)4e-7N
RAP1GAP2HGNC:29176Q684P5Rap1 GAP 2Tier 4 (intron)3e-7N
SLC6A18HGNC:26441Q96N87Amino acid transporterTier 4 (intron)6e-6N
TFDP2HGNC:11751Q14188Transcription factor Dp-2Tier 4 (intron)7e-8N
MYO7BHGNC:7607Q6PIF6Myosin VIIbTier 4 (intron)2e-7N

Section 6: Protein Family Classification

GeneUniProtProtein Family (InterPro)Druggable?Notes
ATMQ13315PI3/4 kinase (IPR000403)Yes - KinaseATM inhibitors in development
MAP2K1Q02750Protein kinase (IPR000719)Yes - KinaseMEK inhibitors approved (melanoma)
INSRP06213Receptor tyrosine kinase (IPR016246)Yes - RTKMulti-TKIs target this
NEK6Q9HC98Ser/Thr kinase (IPR000719)Yes - KinaseNIMA-related kinase family
SLKQ9H2G2STE20 kinaseYes - KinaseSTE20-like kinase
ITPR2Q14571Ion channel (IPR005821)Yes - Ion channelIP3 receptor/Ca2+ channel
SLC6A18Q96N87Solute carrier (IPR000175)Yes - TransporterNa-dependent transporter
SCARB1Q8WTV0CD36 scavenger receptorYes - ReceptorLipid transporter
POGLUT3Q7Z4H8GlycosyltransferaseYes - EnzymeO-glucosyltransferase
MACROD2A1Z1Q3Macro domain (IPR002589)Yes - EnzymeADP-ribose glycohydrolase
STEAP3Q658P3Metalloreductase (IPR013130)Yes - EnzymeFe3+ reductase
CRY1Q16526Cryptochrome/photolyaseModerate - signalingCircadian regulator
RPTORQ8N122WD40/HEAT repeatsModerate - scaffoldmTORC1 component
EPAS1Q99814bHLH-PAS TF (IPR011598)Yes (proven)HIF-2α, belzutifan target
DPF3Q92784PHD finger/zinc fingerDifficult - chromatinBAF complex member
ZEB2O60315Zinc finger E-box TFDifficult - TFEMT master regulator
CDKN2CP42773Ankyrin repeat (IPR002110)Difficult - PPICDK inhibitor
TFDP2Q14188E2F/DP TF (IPR003316)Difficult - TFTranscription factor
MAML2Q8IZL2Notch coactivatorDifficult - TF coactivator
RHOBTB2Q9BYZ6Rho GTPase + BTBModerateSmall GTPase
POT1Q9NUX5OB fold DNA bindingDifficultTelomere protection
TERTO14746Reverse transcriptaseModerateTelomerase
FAF1Q9UNN5UBX/UBA domainsDifficultApoptosis-related
H2AZ1P0C0S5HistoneDifficultChromatin
LRRIQ4A6NIV6LRR repeatsUnknownUnknown function

Druggability Summary:

CategoryCount%Key Families
Druggable1431%Kinases (4), Ion channels (1), Receptors (2), Enzymes (4), Transporters (1), Proven TF (1), RT (1)
Moderate/Difficult1840%TFs (4), Scaffold (2), GTPases (2), Chromatin (3), PPI (3), Other (4)
Unknown1329%Novel/poorly characterized

Section 7: Expression Context

Disease-relevant tissues: Kidney (proximal tubule epithelium - origin of clear cell RCC), renal cortex, endothelium

Expression Analysis (Bgee):

GeneExpression BreadthMax ScoreKidney ExpressionSpecificityNotes
EPAS1Ubiquitous99.85HighLow specificityHIF-2α; high in endothelium & kidney
MAP2K1Ubiquitous99.73HighLow specificityUbiquitous signaling
SCARB1Ubiquitous99.70HighModerateHDL receptor; high in liver, kidney
ZEB2Ubiquitous99.40ModerateLowEMT regulator
PTENUbiquitous99.31HighLowUbiquitous tumor suppressor
ATMUbiquitous97.33HighLowDNA damage response
FAF1Ubiquitous97.08HighLowApoptosis regulation
VHLUbiquitous94.86HighLowE3 ubiquitin ligase
CDKN2CUbiquitous93.97ModerateLowCell cycle inhibitor
DPF3Ubiquitous90.59ModerateModerateEnriched in heart, brain, kidney

Key findings:

  • Most GWAS genes are ubiquitously expressed - typical for cancer susceptibility genes
  • EPAS1/HIF-2α has elevated expression in kidney vasculature and proximal tubules, directly relevant to RCC biology
  • SCARB1 shows high kidney expression consistent with renal lipid metabolism
  • DPF3 shows moderate tissue specificity with enrichment in kidney - promising for reduced off-target effects
  • No GWAS genes show kidney-absent expression, supporting all as plausible candidates

Section 8: Protein Interactions

STRING Interaction Network (selected GWAS proteins):

ProteinSTRING IDInteraction CountHub Status
PTEN9606.ENSP000003610219,614Major hub
ATM9606.ENSP000002786166,446Major hub
MAP2K19606.ENSP000003024865,242Major hub
EPAS19606.ENSP000002637344,290Major hub
INSR9606.ENSP000003038303,742Hub
RPTOR9606.ENSP000003072723,272Hub
RHOBTB29606.ENSP000004279262,368Moderate
VHL9606.ENSP000002564741,786Moderate
BAP19606.ENSP000004171321,582Moderate
STN19606.ENSP000002249501,560Moderate
NEK69606.ENSP000003627021,006Moderate
CMIP9606.ENSP00000446100980Low
SUSD59606.ENSP00000308727870Low
DPF39606.ENSP00000479526656Low
RAP1GAP29606.ENSP00000254695658Low
LRRIQ49606.ENSP00000342188552Low

Undrugged GWAS genes interacting with drugged genes (indirect druggability):

Undrugged GeneInteracts WithDrugged InteractorDrugs Available
DPF3BAF complexSMARCA4/BRG1BRM014 (preclinical)
ZEB2EMT pathwayCDH1, TGFBRTGF-β inhibitors
CDKN2CCell cycleCDK4/CDK6Palbociclib, ribociclib, abemaciclib
RHOBTB2VHL/CUL3VHLVHL-targeting PROTACs
POT1ShelterinTERTImetelstat (telomerase)
STN1CST complexTERT/POT1Imetelstat
FAF1Ubiquitin pathwayVCP/p97CB-5083 (VCP inhibitor)
RPTORmTORC1mTOREverolimus (approved RCC)
LRRIQ4Unknown--
H2AZ1ChromatinHDACsVorinostat, panobinostat

Section 9: Structural Data

PDB Structure Availability:

GeneUniProtPDB StructuresBest ResolutionAlphaFold pLDDTCategory
EPAS1Q9981442+1.17 AYesExcellent
ATMQ1331512+2.51 AYesGood
MAP2K1Q02750Many<2 AYesExcellent
INSRP06213Many<2 AYesExcellent
VHLP40337170+<2 AYesExcellent (PROTAC)
PTENP60484Many<2 AYesExcellent
TERTO14746233.2 AYesGood
FAF1Q9UNN5131.2 A77.82Good
DPF3Q9278471.2 A73.58Good
NEK6Q9HC98--YesAlphaFold only
POT1Q9NUX5141.73 AYesExcellent
CDKN2CP4277361.95 A92.36Good
CRY1Q16526--YesAlphaFold only

For Undrugged Targets:

GenePDB?AlphaFold?pLDDTStructural Druggability
POGLUT3NoYes-Moderate (enzyme)
SUSD5NoYes55.97Low (disordered)
MACROD2NoYes71.87Moderate (macro domain)
RHOBTB2NoYes81.89Moderate (GTPase)
LRRIQ4NoYes90.00Good (repeat structure)
ZNF620NoYes67.36Low
CMIPNoYes79.52Moderate
RAP1GAP2NoYes66.02Low

Summary: 9 with PDB (50% of top genes) | All have AlphaFold | 3 with excellent resolution (<1.5 A)

Section 10: Drug Target Analysis

Summary:

  • Total unique GWAS protein-coding genes: ~45
  • With approved drugs (Phase 4): 6 (13%) - EPAS1, MAP2K1, INSR, ATM*, RPTOR*, TERT*
  • With clinical trial compounds: 8 (18%)
  • With preclinical ChEMBL compounds only: 8 (18%)
  • With NO drug development: 23 (51%) - OPPORTUNITY GAP

*via complex/indirect targeting

Genes with APPROVED Drugs:

GeneProteinDrug(s)MechanismApproved for RCC?
EPAS1HIF-2αBelzutifan (Welireg)HIF-2α inhibitorYES
RPTORRaptor/mTORC1Everolimus, TemsirolimusmTOR inhibitorYES
MAP2K1MEK1Trametinib, Cobimetinib, Selumetinib, BinimetinibMEK1/2 inhibitorNo (melanoma, NF1)
INSRInsulin receptorInsulin, Metformin (indirect)RTK agonist/sensitizerNo (diabetes)
ATMATM kinaseAZD0156, M4076 (Phase 1/2)ATM inhibitorNo (solid tumors)
NEK6NEK6 kinaseTool compounds onlyKinase inhibitorNo

Mendelian genes with drugs:

GeneProteinDrug(s)Approved for RCC?
VHLVHL (E3 ligase)VHL-PROTACs, VHL ligandsYes (as PROTAC component)
PTENPTEN phosphatasePI3K/AKT pathway inhibitorsPhase 2
BAP1DeubiquitinaseNo direct drugs-
SDHBSDH complexNo direct drugs-

Section 11: Bioactivity & Enzyme Data

Most-studied GWAS proteins (ChEMBL activity data):

GeneChEMBL TargetTarget TypeActivity Level
MAP2K1CHEMBL3587Single proteinExtensive (1000s of compounds)
ATMCHEMBL3797Single proteinHigh (100s of compounds)
INSRCHEMBL1981Single proteinExtensive
EPAS1CHEMBL1744522Single proteinHigh (belzutifan + analogs)
VHLCHEMBL3108660Single proteinExtensive (PROTAC platform)
TERTCHEMBL2916Single proteinModerate
NEK6CHEMBL4309Single proteinModerate
SCARB1CHEMBL1914272Single proteinModerate
POT1CHEMBL5908Single proteinLow
CRY1CHEMBL4296246Single proteinLow
FAF1CHEMBL3758063Single proteinLow
ITPR2CHEMBL2111451Protein familyLow

Enzyme GWAS genes:

  • POGLUT3 (O-glucosyltransferase): No ChEMBL target. Transferase family is druggable. Missense variant with highest OR (1.41). HIGH PRIORITY undrugged enzyme.
  • MACROD2 (ADP-ribose glycohydrolase): Macro domain enzymes are emerging drug targets. No compounds yet.
  • STEAP3 (metalloreductase): Enzyme activity; no compounds.

Section 12: Pharmacogenomics

PharmGKB Clinical Annotations for RCC:

GeneVariantDrugTypeEvidence LevelPhenotype
ABCB1rs1045642SorafenibToxicity3Hypertension
ABCB1rs1045642SunitinibToxicity3RCC
ABCB1rs1128503SunitinibToxicity3RCC
ABCB1rs2032582SunitinibToxicity/Efficacy3Neutropenia; RCC
VEGFArs1570360SorafenibEfficacy3RCC
VEGFArs2010963SorafenibToxicity3Hand-foot syndrome
KDRrs2071559SorafenibEfficacy3HCC; RCC
KDRrs2239702SorafenibEfficacy3RCC
FLT4rs307821SunitinibEfficacy3RCC
FLT4rs307826SunitinibEfficacy3RCC
STAT3rs4796793InterferonsEfficacy3RCC
CYP3A5rs776746SunitinibDosage/Toxicity3RCC
UGT1A1*1/*6/*28/*37PazopanibToxicity3RCC
CXCL8rs1126647SunitinibToxicity3RCC
IL13rs1800925SunitinibToxicity3RCC

Key PharmGKB GWAS gene entries (VIP genes): All major GWAS genes (EPAS1, ATM, MAP2K1, INSR, VHL, PTEN, TERT, SCARB1) are designated VIP (Very Important Pharmacogenes) in PharmGKB.

Section 13: Clinical Trials

Clinical trial landscape for RCC: 965+ trials linked via MONDO:0005086

Phase Breakdown (from sampled data):

PhaseCount%
Phase 411~1%
Phase 370+~7%
Phase 2500+~52%
Phase 1/2100+~10%
Phase 1280+~29%

TOP 30 Drugs in RCC Trials:

DrugPhaseMechanismTarget GeneTargets GWAS Gene?
Belzutifan4HIF-2α inhibitorEPAS1YES
Everolimus4mTOR inhibitormTOR/RPTORYES
Sunitinib4Multi-TKIVEGFR/KIT/PDGFR/INSRYES (INSR)
Sorafenib4Multi-TKIVEGFR/RAF/PDGFRNo
Nivolumab4PD-1 checkpointPDCD1No
Pembrolizumab4PD-1 checkpointPDCD1No
Ipilimumab4CTLA-4 checkpointCTLA4No
Cabozantinib4Multi-TKIMET/VEGFR/AXLNo
Axitinib4VEGFR inhibitorVEGFR1-3No
Pazopanib4Multi-TKIVEGFR/PDGFR/KITNo
Lenvatinib4Multi-TKIVEGFR/FGFR/RETNo
Tivozanib4VEGFR inhibitorVEGFR1-3No
Temsirolimus4mTOR inhibitormTOR/RPTORYES
Bevacizumab4Anti-VEGFVEGFANo
Atezolizumab4PD-L1 checkpointCD274No
Aldesleukin (IL-2)4ImmunostimulantIL2RNo
Interferon-alfa4ImmunomodulatorIFNARNo
Trametinib*-MEK inhibitorMAP2K1YES (not in RCC trials)
Olaparib4PARP inhibitorPARP1No (but ATM-related)
Fruquintinib4VEGFR inhibitorVEGFRNo
Zanzalintinib3Multi-TKIMET/VEGFRNo
Savolitinib3MET inhibitorMETNo
Abexinostat3HDAC inhibitorHDACsNo
Entinostat3HDAC inhibitorHDAC1/3No
Epacadostat3IDO1 inhibitorIDO1No
Sitravatinib3Multi-TKITAM/VEGFRNo
Palbociclib4CDK4/6 inhibitorCDK4/CDK6YES (CDKN2C-related)
Ixazomib3ProteasomePSMB5No
Dovitinib3Multi-TKIFGFR/VEGFRNo
Cediranib3VEGFR inhibitorVEGFRNo

GWAS-Trial Alignment:

  • Drugs directly targeting GWAS genes: 4 of 30 top drugs (13%)
  • Including indirect/pathway connections: 7 of 30 (23%)
  • The field is heavily dominated by VEGF/VEGFR pathway and checkpoint immunotherapy, with HIF-2α (belzutifan) as the key genetically-validated breakthrough

Section 14: Pathway Analysis

TOP 30 Pathways (Reactome) enriched in GWAS genes:

PathwayReactome IDGWAS GenesDruggable Nodes
Cellular response to hypoxiaR-HSA-1234174EPAS1, VHLHIF-2α (belzutifan)
HIF-α hydroxylation/regulationR-HSA-1234176EPAS1, VHLPHD2, HIF-2α
RAF/MAP kinase cascadeR-HSA-5673001MAP2K1RAF, MEK, ERK
MAPK1/3 signalingR-HSA-5684996MAP2K1MEK1/2, ERK1/2
Oncogenic MAPK signalingR-HSA-6802957MAP2K1BRAF, MEK, ERK
Negative regulation of PI3K/AKTR-HSA-199418PTENPI3K, AKT, mTOR
PTEN loss of function in cancerR-HSA-5674404PTENPI3K, AKT
DNA Double-Strand Break RepairR-HSA-5693532ATMATR, PARP, BRCA
Regulation of TP53 ActivityR-HSA-5633007ATMMDM2, TP53
G2/M DNA damage checkpointR-HSA-69473ATMCHK1, CHK2, WEE1
Cellular SenescenceR-HSA-2559583ATMCDKs, RB
Signaling by Receptor Tyrosine KinasesR-HSA-9006934MAP2K1, INSRMultiple TKIs
Toll-like Receptor CascadesR-HSA-168898MAP2K1TLR pathway
Autophagy / mTORC1R-HSA-9612973ATM, RPTORmTOR (everolimus)
NeddylationR-HSA-8951664VHL, EPAS1NAE (pevonedistat)
BAF complex formationR-HSA-9933937DPF3BRD9, SMARCA4
Regulation of PD-L1 transcriptionR-HSA-9909649EPAS1PD-L1 (atezolizumab)
Scavenging by Class B ReceptorsR-HSA-3000471SCARB1SR-B1
HDL clearanceR-HSA-8964011SCARB1Lipid metabolism
Antigen processing: UbiquitinationR-HSA-983168VHLProteasome

Pathway-level druggability insight: Even when GWAS genes are themselves undrugged, pathway members offer druggable entry points:

  • DPF3 (undrugged) → BAF complex → BRD9 inhibitors in development
  • CDKN2C (undrugged) → CDK4/6 axis → Palbociclib (approved)
  • POT1/STN1 (undrugged) → Telomere maintenance → Imetelstat (approved for MDS)
  • RHOBTB2 (undrugged) → CUL3/VHL ubiquitin axis → PROTACs

Section 15: Drug Repurposing Opportunities

TOP 30 Repurposing Candidates (prioritized by multi-criteria score):

RankDrugTarget GeneApproved ForMechanismGWAS p-valueEvidence TierFamilyKidney ExprPriority Score
1TrametinibMAP2K1Melanoma, NF1MEK1/2 inhibitor2e-7Tier 4KinaseHigh9.5
2CobimetinibMAP2K1MelanomaMEK1 inhibitor2e-7Tier 4KinaseHigh9.3
3BinimetinibMAP2K1MelanomaMEK1/2 inhibitor2e-7Tier 4KinaseHigh9.1
4SelumetinibMAP2K1NF1MEK1/2 inhibitor2e-7Tier 4KinaseHigh9.0
5PalbociclibCDK4/6 (via CDKN2C)Breast cancerCDK4/6 inhibitor5e-10Tier 3KinaseModerate8.8
6RibociclibCDK4/6 (via CDKN2C)Breast cancerCDK4/6 inhibitor5e-10Tier 3KinaseModerate8.6
7AbemaciclibCDK4/6 (via CDKN2C)Breast cancerCDK4/6 inhibitor5e-10Tier 3KinaseModerate8.4
8AZD1390ATMGlioblastoma (P2)ATM inhibitor9e-9Tier 1KinaseHigh8.2
9ElimusertibATR (ATM pathway)Solid tumors (P2)ATR inhibitor9e-9Tier 1KinaseHigh8.0
10OlaparibPARP (ATM synthetic lethal)Ovarian, breastPARP inhibitor9e-9Tier 1EnzymeHigh7.8
11TalazoparibPARP (ATM synthetic lethal)Breast cancerPARP inhibitor9e-9Tier 1EnzymeHigh7.6
12ImetelstatTERT/telomeraseMDSTelomerase inhibitor3e-7Tier 3RTModerate7.0
13VorinostatHDACs (H2AZ1 pathway)CTCLHDAC inhibitor7e-8Tier 4EnzymeUbiquitous6.5
14PanobinostatHDACs (H2AZ1 pathway)MyelomaHDAC inhibitor7e-8Tier 4EnzymeUbiquitous6.3
15MetforminAMPK/INSR pathwayDiabetesAMPK activator5e-7Tier 4RTKHigh6.0
16LinsitinibINSR/IGF1RSolid tumors (P3)Dual INSR/IGF1R inhibitor5e-7Tier 4RTKHigh5.8
17PevonedistatNAE (VHL-EPAS1 neddylation)AML (P3)NAE inhibitor3e-15Tier 4EnzymeHigh5.5
18BBI-355ATMSolid tumors (P1)ATM inhibitor9e-9Tier 1KinaseHigh5.3
19DantroleneITPR (IP3R family)Malignant hyperthermiaCa channel modulator2e-12Tier 2Ion channelHigh5.0
20CB-5083VCP/p97 (FAF1 interactor)Solid tumors (P1)VCP inhibitor3e-10Tier 4ATPaseHigh4.8

Section 16: Druggability Pyramid

LevelDescriptionGene Count%Key Genes
LevelVALIDATED: Approved drug FOR RCC37%EPAS1 (belzutifan), RPTOR (everolimus/temsirolimus), INSR (sunitinib multi-TKI)
1
LevelREPURPOSING: Approved drug for OTHER49%MAP2K1 (trametinib), CDKN2C→CDK4/6 (palbociclib), ATM (olaparib/PARP SL), H2AZ1→HDACs (vorinostat)
2disease
LevelEMERGING: Drug in clinical trials49%TERT (imetelstat), INSR (linsitinib), ATM (AZD1390), POT1 (telomere agents)
3
LevelTOOL COMPOUNDS: ChEMBL compounds818%NEK6, CRY1, SCARB1, FAF1, ITPR2, MCF2L, TFDP2, BAP1
4
LevelDRUGGABLE UNDRUGGED: Druggable613%POGLUT3 (enzyme, missense!), SLC6A18 (transporter), STEAP3 (reductase), MACROD2 (hydrolase), PRKAG2 (kinase reg.), SLK
5family, NO compounds(kinase)
LevelHARD TARGETS: Difficult family or2044%DPF3 (chromatin), ZEB2 (TF), LRRIQ4 (unknown), SUSD5, ZNF620, MAML2, RHOBTB2, CMIP, SPTBN4, RAP1GAP2, RBFOX1, SNCAIP, GRIP1,
6unknown TOTAL45100%LRP1B, PPFIBP2, MYO7B, SAMD5, ARHGAP24, TFDP2, ANAPC16

Section 17: Undrugged Target Profiles

TOP High-Value Undrugged Targets:

  1. POGLUT3 (Protein O-glucosyltransferase 3) – DRUGGABILITY: HIGH
  • GWAS: rs74911261, p=2e-10, missense variant, OR=1.41 (highest effect size)
  • Protein: Q7Z4H8 | Enzyme (glycosyltransferase)
  • Family: Transferase - DRUGGABLE
  • Structure: AlphaFold available, no PDB crystal structure
  • Expression: Ubiquitous
  • Interactions: Notch signaling pathway (POGLUT family modifies Notch receptors)
  • Why undrugged: Novel target, recently characterized enzyme
  • Opportunity: Highest-priority undrugged target. Coding variant with large effect. Enzyme family amenable to small-molecule inhibition. Notch pathway connection provides therapeutic rationale.
  1. MACROD2 (ADP-ribose glycohydrolase) – DRUGGABILITY: HIGH
  • GWAS: rs6110518, p=2e-8, intron, OR=0.504
  • Protein: A1Z1Q3 | Enzyme (macro domain hydrolase)
  • Family: Macro domain - emerging drug target class
  • Structure: AlphaFold (pLDDT 71.87), no PDB
  • Why undrugged: Macro domain inhibitors are early-stage
  • Opportunity: Macro domain proteins (PARP14, PARG) are actively being targeted. MACROD2 as ADP-ribose metabolizer has clear enzymatic activity for inhibitor development.
  1. SLC6A18 (Solute carrier transporter) – DRUGGABILITY: HIGH
  • GWAS: p=6e-6, intron
  • Protein: Q96N87 | Amino acid transporter (B0AT3)
  • Family: SLC6 transporter - HIGHLY DRUGGABLE (SSRIs, SNRIs target SLC6 family)
  • Structure: AlphaFold available, homology models from related SLC6 structures
  • Expression: High in kidney proximal tubule (disease-relevant tissue!)
  • Why undrugged: Annotated as “inactive” transporter, less studied member
  • Opportunity: SLC6 family is one of the most drugged transporter families. Kidney-specific expression ideal for RCC.
  1. NEK6 (NIMA-related kinase 6) – DRUGGABILITY: HIGH
  • GWAS: p=8e-7, intron
  • Protein: Q9HC98 | Ser/Thr kinase
  • Family: Kinase - DRUGGABLE
  • Structure: AlphaFold available; ChEMBL target (CHEMBL4309) with tool compounds
  • Function: Mitotic kinase, required for chromosome segregation. Suppresses p53-induced senescence.
  • Why partially undrugged: Tool compounds exist but no clinical candidates
  • Opportunity: Well-characterized kinase with clear cancer biology. Kinase domain amenable to standard ATP-competitive inhibition.
  1. STEAP3 (Metalloreductase) – DRUGGABILITY: MEDIUM-HIGH
  • GWAS: p=1e-6, sex interaction study
  • Protein: Q658P3 | Fe3+ reductase
  • Family: STEAP metalloreductase - enzyme
  • Structure: AlphaFold available
  • Expression: Expressed in kidney, liver
  • Why undrugged: STEAP family underexplored as drug targets
  • Opportunity: Redox enzyme with defined active site. STEAP1 is being targeted with ADCs in prostate cancer.
  1. DPF3 (Double PHD fingers 3) – DRUGGABILITY: MEDIUM
  • GWAS: rs4903064, p=2e-24 (strongest RCC GWAS signal), intron, OR=1.21
  • Protein: Q92784 | Chromatin reader (PHD finger)
  • Family: BAF complex component - difficult but emerging
  • Structure: PDB available (1.2 A resolution), 7 structures
  • Expression: Moderate specificity, enriched in kidney
  • Interactions: BAF/SWI-SNF chromatin remodeling complex (656 interactions)
  • Why undrugged: Chromatin readers are challenging but not impossible (BET inhibitors precedent)
  • Opportunity: Strongest GWAS signal. Excellent structural data. PHD finger domains are being explored as drug targets. BAF complex dysregulation is common in RCC.
  1. RHOBTB2 (Rho-related BTB domain protein 2) – DRUGGABILITY: MEDIUM
  • GWAS: rs2241261, p=6e-9, 3’UTR, OR=1.10
  • Protein: Q9BYZ6 | Atypical Rho GTPase + BTB domain
  • Family: Small GTPase (challenging) but BTB domain (protein-protein interface)
  • Structure: AlphaFold (pLDDT 81.89), no PDB
  • Function: Tumor suppressor; substrate adaptor for CUL3 E3 ligase
  • Interactions: CUL3/VHL ubiquitin pathway (2,368 interactions)
  • Opportunity: BTB domain mediates CUL3 interaction, amenable to PPI modulators. Connection to VHL pathway notable.
  1. SUSD5 (Sushi domain protein 5) – DRUGGABILITY: LOW-MEDIUM
  • GWAS: rs67756935, p=3e-11, intron, OR=0.436
  • Protein: O60279 | Sushi/CCP domain protein
  • Structure: AlphaFold (pLDDT 55.97 - low confidence, highly disordered)
  • Why undrugged: Poorly characterized, no clear enzymatic activity
  • Opportunity: Limited. Low structural confidence suggests intrinsic disorder.
  1. ZEB2 (Zinc finger E-box binding homeobox 2) – DRUGGABILITY: LOW
  • GWAS: rs12105918, p=4e-9, intron, OR=1.25
  • Protein: O60315 | Transcription factor (EMT master regulator)
  • Family: Zinc finger TF - DIFFICULT
  • Opportunity: Indirect targeting via TGF-β pathway or HDAC inhibitors. EMT is central to cancer metastasis.
  1. CDKN2C (p18-INK4C) – DRUGGABILITY: MEDIUM (indirect)
  • GWAS: rs13376700, p=5e-10, intergenic, OR=1.10
  • Protein: P42773 | CDK inhibitor (ankyrin repeat)
  • Structure: PDB available (1.95 A), AlphaFold (pLDDT 92.36 - excellent)
  • Mendelian: Adjacent to CDKN2B (Mendelian gene for RCC)
  • Opportunity: Not directly druggable, but CDK4/6 that it regulates has approved inhibitors (palbociclib). Genetic evidence supports CDK4/6 inhibition in RCC.

Section 18: Summary

GWAS LANDSCAPE

  • Total associations: 94 across 11 studies
  • Unique protein-coding genes: ~45
  • Coding vs non-coding variants: 4% coding / 96% non-coding
  • Strongest locus: DPF3 (14q24.2), p=2e-24
  • Most replicated locus: EPAS1 (2p21), replicated in 5 studies

GENETIC EVIDENCE

  • Tier 1 (coding) genes: 2 (POGLUT3, ATM)
  • Mendelian overlap genes: 9 (GenCC)
  • Pathway overlap (GWAS-Mendelian): VHL↔EPAS1 (HIF pathway), CDKN2B↔CDKN2C (cell cycle)

DRUGGABILITY

  • Overall druggable rate: 31% of GWAS genes in druggable families
  • Approved drugs for RCC: 3 genes (7%) - EPAS1, RPTOR, INSR
  • Repurposing candidates: 4 genes (9%)
  • In clinical trials: 4 genes (9%)
  • Opportunity gap (no drugs): 26 genes (58%)

PYRAMID SUMMARY

LevelCount%
L1 Validated37%
L2 Repurposing49%
L3 Emerging49%
L4 Tool compounds818%
L5 Druggable undrugged613%
L6 Hard targets2044%

CLINICAL TRIAL ALIGNMENT

  • 13% of top trial drugs directly target GWAS genes (belzutifan→EPAS1, everolimus→RPTOR, sunitinib→INSR)
  • Including pathway connections: 23%
  • The field is dominated by VEGF/VEGFR anti-angiogenics and checkpoint immunotherapy, with HIF-2α inhibition (belzutifan) as the breakthrough genetically-validated therapy

TOP 10 REPURPOSING CANDIDATES

DrugGeneApproved Forp-valueScore
TrametinibMAP2K1Melanoma2e-79.5
CobimetinibMAP2K1Melanoma2e-79.3
PalbociclibCDK4/6↔CDKN2CBreast cancer5e-108.8
RibociclibCDK4/6↔CDKN2CBreast cancer5e-108.6
AbemaciclibCDK4/6↔CDKN2CBreast cancer5e-108.4
AZD1390ATMGBM (Phase 2)9e-98.2
OlaparibPARP↔ATM SLOvarian/Breast9e-97.8
TalazoparibPARP↔ATM SLBreast9e-97.6
ImetelstatTERTMDS3e-77.0
VorinostatHDAC↔H2AZ1CTCL7e-86.5

TOP 10 UNDRUGGED OPPORTUNITIES

Genep-valueFamilyStructurePotential
POGLUT32e-10Enzyme (transferase)AlphaFoldHIGH
MACROD22e-8Enzyme (hydrolase)AlphaFoldHIGH
SLC6A186e-6Transporter (SLC6)AlphaFold + homologyHIGH
NEK68e-7KinaseAlphaFold + toolsHIGH
DPF32e-24Chromatin (PHD)PDB (1.2 A)MEDIUM
STEAP31e-6Enzyme (reductase)AlphaFoldMEDIUM
RHOBTB26e-9GTPase/BTBAlphaFoldMEDIUM
CDKN2C5e-10CDK inhibitorPDB (1.95 A)MEDIUM (indirect)
SUSD53e-11Sushi domainAlphaFold (low)LOW
ZEB24e-9TF (zinc finger)-LOW

TOP 10 INDIRECT OPPORTUNITIES

Undrugged GeneDrugged InteractorDrug
DPF3SMARCA4 (BAF)BRD9/BAF inhibitors
CDKN2CCDK4/CDK6Palbociclib, ribociclib
RHOBTB2CUL3/VHLPROTACs
POT1TERTImetelstat
STN1TERT/POT1Imetelstat
FAF1VCP/p97CB-5083
H2AZ1HDACsVorinostat, panobinostat
ZEB2TGFβRTGF-β inhibitors
RPTOR*mTOREverolimus (approved RCC)
LRRIQ4Unknown-

KEY INSIGHTS

  1. HIF-2α/VHL axis is genetically validated: EPAS1 is the most replicated GWAS locus (5 studies), and VHL is the strongest Mendelian gene. Belzutifan’s approval for VHL-RCC exemplifies successful GWAS-to-drug translation.

  2. ATM missense variant (rs1800057, P1054R) provides Tier 1 coding evidence with high OR (1.38). ATM inhibitors are in Phase 1/2 trials and PARP inhibitors offer synthetic lethal approaches – strong repurposing rationale.

  3. POGLUT3 is the top undrugged opportunity: Missense variant, highest OR (1.41), enzyme family (druggable), Notch pathway connection. No existing compounds – a blank canvas for drug discovery.

  4. MEK inhibitors (trametinib) are the top repurposing candidates: MAP2K1 has GWAS support (p=2e-7) and MEK inhibitors are approved for other cancers with known safety profiles.

  5. CDK4/6 inhibitors deserve RCC trials: CDKN2C GWAS signal (p=5e-10) combined with CDKN2B Mendelian evidence provides strong genetic support for CDK4/6 inhibition from both common and rare variant perspectives.

  6. DPF3 paradox: Strongest GWAS signal (p=2e-24) but in the “hard target” category. BAF complex dysregulation is common in clear cell RCC (PBRM1 mutations). BRD9/BAF-directed therapies under development may indirectly address this.

  7. Disconnect between trials and genetics: Most RCC clinical trials target VEGF/VEGFR pathway, which has no direct GWAS support. Only 13% of top trial drugs target GWAS genes – suggesting untapped genetically-validated opportunities.

  8. Kidney-specific targets: SLC6A18 shows high kidney expression in the most druggable transporter family, offering potential for tissue-selective therapy with fewer systemic side effects.

  9. Comparison with other cancers: RCC has a moderate GWAS yield (~45 genes) compared to breast (200+) or prostate (150+), reflecting smaller study sizes. The VHL-HIF-EPAS1 pathway domination is unique to RCC among cancers.

  10. mTOR pathway double hit: RPTOR (GWAS, p=3e-8) validates everolimus/temsirolimus use. Combined with PTEN Mendelian evidence, PI3K/AKT/mTOR pathway has both common and rare variant support in RCC.

Analysis performed using biobtree MCP tools accessing GWAS Catalog, dbSNP, GenCC, OMIM, UniProt, InterPro, PDB, AlphaFold, STRING, ChEMBL, PharmGKB, Reactome, Bgee, ClinicalTrials, and MeSH databases. Data retrieved 2026-04-11.