RNA TargetsSolid Tumor · GU OncologyResearch Use Only
Prostate Cancer Gene Expression
Reference Targets
Reference Targets
A biologically curated RNA target reference for prostate cancer spanning localized disease through castration-resistant and neuroendocrine stages — enabling researchers to select genes across AR signaling, lineage plasticity, HRD, immune biology, and the bone niche to build custom Tapestri assays. Designed to resolve AR-dependent vs -independent tumor states and NE transdifferentiation at single-cell resolution.
283
Total Genes
7
Functional Categories
4
Disease Stages
6+
Curation Sources
1
Panel Power Scorecard & Functional Categories
● Panel Power Scorecard
Panel Score: 76 / 100
88%
Landmark
Biomarker
Coverage
Biomarker
Coverage
83%
COSMIC
Tier-1
Coverage
Tier-1
Coverage
11 genes
FDA
Biomarker
Genes
Biomarker
Genes
17 genes
Clinical Trial
Biomarkers
Biomarkers
7 states
Cell States
Resolvable
Resolvable
283 genes
Total Panel
Genes
Genes
Published precedent — targeted panels are sufficient
Brady et al. 2021 Cell — targeted panel resolved 5 CRPC transcriptional states
Aggarwal et al. 2018 JCO Precision Oncol — 73-gene panel captured all clinically actionable PCa alterations
61
AR Pathway & Steroidogenesis
41
DNA Damage / HRD
55
Immune Microenvironment
41
Bone Niche / Stroma
33
Proliferation
33
Lipid / Metabolism
36
Cell State / PSMA
2
Target Curation Principles
Commercial Assays
- Foundation Medicine FoundationOne CDx
- Tempus xT RNA (prostate module)
- Decipher Genomics Genomic Classifier
- Oncotype DX Genomic Prostate Score
- Illumina TruSight Oncology 500
- QIAGEN QIAseq Prostate Panel
- Caris MI Transcriptome mRNA assay
Public Databases
- TCGA PRAD dataset
- SU2C/PCF West Coast Dream Team cohort
- COSMIC prostate mutation census
- MSigDB hallmark gene sets
- Human Cell Atlas (prostate)
- GEO mCRPC scRNA-seq datasets
Peer-Reviewed Literature
- PROfound trial (olaparib BRCA/ATM mCRPC)
- VISION trial (Lu-PSMA-617 biomarker data)
- Beltran et al. 2016 Nature Med (CRPC-NE)
- Quigley et al. 2018 Cell (mCRPC landscape)
- EAU/NCCN AR-V7 testing clinical guidelines
- CDK12 biallelic loss IO biomarker literature
Why Single-Cell RNA for Prostate Cancer?
AR-V7 splice variant expression, NE transdifferentiation, and CRPC-NE emergence are subclonal events that bulk RNA masks. Tapestri co-detects each cell’s AR mutation/amplification alongside its NE vs luminal transcriptional state, identifying the AR-independent minority subclone driving resistance.
PSMA Heterogeneity — The Radioligand Therapy Challenge
Lutetium-177 PSMA-617 efficacy is limited by PSMA expression heterogeneity. Tapestri resolves PSMA (FOLH1) expression at single-cell resolution while simultaneously genotyping each cell — revealing which subclone drives PSMA-low resistance.
3
Target Reference Structure — Gene Table
1 · AR Pathway & Steroidogenesis2 · DNA Damage / HRD3 · Immune Microenvironment4 · Bone Niche / Stroma5 · Proliferation / Cell Cycle6 · Lipid / Metabolism7 · Cell State / PSMA
| Category | Representative Genes (n) | Biological Function | Disease Relevance | scD+R Use Case |
|---|---|---|---|---|
| 1 · AR Pathway & Steroidogenesis · 61 genes | ||||
| AR / CRPC / NE | AR, FOXA1, HOXB13, KLK3 (PSA), KLK2, TMPRSS2, ERG, ETS2, NKX3-1, SRD5A1, SRD5A2, CYP17A1, HSD3B1, AKR1C3, CHGA, SYP, ENO2, ASCL1, NEUROD1, SOX2, MYCN, PEG10, DLL3, BRN2, INSM1, FOXA2 (26) + 35 accessory | AR signaling; steroidogenesis; NE differentiation | AR-V7 = enzalutamide/abiraterone resistance; TMPRSS2-ERG in 50%; CYP17A1 = abiraterone; CRPC-NE: ASCL1/NEUROD1/MYCN; DLL3 = NE therapy target | Identify AR-V7 cells; track NE lineage switch per cell |
| 2 · DNA Damage / HRD · 41 genes | ||||
| HRD / DDR | BRCA1, BRCA2, ATM, CDK12, PALB2, RAD51C, RAD51D, BRIP1, FANCA, CHEK2, PARP1, MLH1, MSH2, MSH6, PMS2, POLE (16) + 25 accessory | HR repair; CDK12; MMR | BRCA1/2 = olaparib (PROfound); CDK12 = neoantigen burden/IO; ATM = DDR target | Link DDR expression to HRD genotype per cell |
| 3 · Immune Microenvironment · 55 genes | ||||
| T Cell / Myeloid / Checkpoint | CD3E, CD8A, CD4, GZMB, IFNG, TOX, PDCD1, LAG3, HAVCR2, TIGIT, CD274, FOXP3, CD68, CD163, CSF1R, SPP1, TREM2, ARG1, IDO1, CXCL9, CXCL10, CXCL12, B2M, HLA-A, NCAM1, NKG7, MS4A1 (27) + 28 accessory | T cell exhaustion; myeloid polarization; immune desert | PCa = immune-cold; PSMA-targeted + ICI; ARG1+ TAMs suppress T cells; CDK12-loss = IO-responsive | Identify T cell exclusion; classify immunosuppressive myeloid states |
| 4 · Bone Niche / Stroma · 41 genes | ||||
| Bone Niche / CAF | ACTA2, FAP, PDGFRA, PDGFRB, CXCL12, CXCR4, TNFSF11 (RANKL), TNFRSF11B (OPG), PTHLH (PTHrP), BMP2, BMP4, VEGFA, KDR, COL1A1, MMP2, FN1, SPARC (17) + 24 accessory | CAF; bone niche; osteoblastic signaling | CXCL12/CXCR4 = bone homing; RANKL = denosumab; PTHrP drives osteoblastic mets | Resolve bone niche stroma; identify RANKL+ osteoclast-activating cells |
| 5 · Proliferation · 33 genes | ||||
| Proliferation | MKI67, TOP2A, AURKA, CDK2, CCNB1, E2F1, FOXM1, TYMS, MCM2, PLK1, BUB1, CDC20 (12) + 21 accessory | Proliferative index | Ki-67 = Gleason grade; AURKA = alisertib; TOP2A = docetaxel | Score proliferating vs quiescent tumor cells |
| 6 · Lipid / Metabolism · 33 genes | ||||
| Lipid / Metabolism | FASN, ACACA, SCD1, LDLR, HMGCR, CPT1A, SLC2A1, LDHA, CA9, HIF1A, PRKAA1 (11) + 22 accessory | Fatty acid synthesis; cholesterol; Warburg | FASN overexpression = lipid dependency; HMGCR = statin target; HIF1A = hypoxic bone mets | Identify FASN-high lipid-dependent tumor cells |
| 7 · Cell State / PSMA Expression · 36 genes | ||||
| Luminal/Basal/PSMA | NKX3-1, FOXA1, KRT8, KRT18, KRT5, KRT14, CD44, TROP2, FOLH1 (PSMA), SLC45A3, HOXB13, ALDH1A1, TP63, SOX2, EPCAM, CDH1 (16) + 20 accessory | Luminal vs basal identity; PSMA expression | PSMA = Lu-177 target; TROP2 = sacituzumab; KRT5+ basal = stem-like; PSMA heterogeneity limits radioligand | Resolve luminal/basal/NE states; map PSMA heterogeneity |
Total: 283 genesCat 1: 61 · Cat 2: 41 · Cat 3: 55 · Cat 4: 41 · Cat 5: 33 · Cat 6: 33 · Cat 7: 36
ⓘ Select genes appear in more than one functional category reflecting their multi-role biology. The total above counts unique genes; per-category counts include all category-relevant entries.