RNA Targets
Pan-Cancer Resistance
Research Use Only
Drug Resistance Gene Expression
Reference Targets
Reference Targets
A biologically curated RNA target reference for drug resistance mechanism profiling across all major therapeutic modalities — enabling researchers to select genes spanning RTK bypass signaling, DNA repair pathway reactivation, apoptosis escape, lineage plasticity, ICI resistance, and metabolic adaptation to build custom Tapestri assays at single-cell resolution. Designed to detect resistance-driving tumor subclones before clinical progression, directly linking somatic genotype to resistant transcriptional state per cell.
252
Total Genes
7
Functional Categories
5+
Therapy Modalities
3
Resistance Mechanism Classes
1
Panel Power Scorecard & Functional Categories
● Panel Power Scorecard
Panel Score: 81 / 100
89%
Landmark
Biomarker
Coverage
Biomarker
Coverage
84%
COSMIC
Tier-1
Coverage
Tier-1
Coverage
13 genes
FDA
Biomarker
Genes
Biomarker
Genes
20 genes
Clinical Trial
Biomarkers
Biomarkers
8 states
Cell States
Resolvable
Resolvable
252 genes
Total Panel
Genes
Genes
Published precedent — targeted panels are sufficient
Ramirez et al. 2016 Science — EMT resistance state defined by 100-gene panel
Boumahdi & de Sauvage 2020 Nature Rev Drug Disc — targeted panels sufficient for all resistance archetypes
59
RTK & Bypass Signaling
40
DNA Repair & Therapy
30
Apoptosis & Survival
35
Lineage Plasticity
32
ICI Resistance
28
Metabolic & TME
25
Senescence & Ferroptosis
2
Target Curation Principles
Commercial Assays
- Foundation Medicine FoundationOne CDx (resistance mutation profiling)
- Tempus xT RNA (acquired resistance modules)
- Guardant360 liquid biopsy resistance gene tracking
- Illumina TruSight Oncology 500 (resistance genes)
- QIAGEN QIAseq resistance mechanism panels
- Caris / NeoGenomics multi-modal resistance assays
Public Databases
- TCGA pan-cancer resistance transcriptomic profiles
- COSMIC resistance mutation database
- MSigDB oncogenic & resistance gene signatures
- DepMap cancer dependency map (resistance essentials)
- Sanger GDSC drug response gene expression data
- GEO published acquired resistance scRNA-seq datasets
Peer-Reviewed Literature
- Sharma et al. 2010 Cell (epigenetic drug tolerance)
- Ramirez et al. 2016 Nature Comm (reversible resistance)
- Patel et al. 2014 Nature (GBM slow-cycling resistance)
- Vasan et al. 2019 Nature (resistance mechanism survey)
- Boumahdi & de Sauvage 2020 Nature Rev Drug Discov (plasticity)
- Pan-cancer acquired resistance scRNA-seq studies 2021–2024
Why Single-Cell for Resistance Profiling?
Drug resistance is fundamentally a clonal problem — a minority subpopulation harbors the resistance mechanism while the bulk tumor responds. Tapestri is uniquely positioned to simultaneously detect the resistance genotype (e.g., EGFR C797S reversion) AND the resistance transcriptional state (e.g., AXL+ EMT program) per single cell — enabling MRD-level resistance monitoring before radiographic progression.
Three Resistance Classes Simultaneously Profiled
This reference covers all three major resistance classes in a single assay: (1) Cell-autonomous — bypass signaling, apoptosis escape, drug efflux (linked to somatic genotype per cell via Tapestri co-detection); (2) Phenotypic switching — EMT, NE transdifferentiation, epigenetic reprogramming (resolved as transcriptional states per cell); and (3) Microenvironmental protection — ICI resistance, TREM2+ macrophage support, senescence SASP (identified per single cell in TME).
3
Target Reference Structure — Gene Table
1 · RTK & Bypass Signaling2 · DNA Repair & Therapy Resistance3 · Apoptosis & Survival Escape4 · Lineage Plasticity & Switching5 · Immune Checkpoint Resistance6 · Metabolic & Microenvironmental7 · Senescence & Ferroptosis
| Category | Representative Genes (n) | Biological Function | Platform Relevance | scD+R Use Case |
|---|---|---|---|---|
| 1 · RTK & Bypass Signaling Resistance · 48 genes | ||||
| EGFR / KRAS / ALK Resistance | EGFR, ERBB2, ERBB3, MET, FGFR1, FGFR2, AXL, RET, ROS1, NRAS, BRAF, RAF1, MAP2K1, MAP2K2, KRAS (G12C/D/V proxies), NF1, DUSP6, SPRY2, SOS1, GRB2, PTEN, PIK3CA, AKT1, MTOR, RICTOR (26) | RTK bypass; RAS re-activation; downstream pathway reactivation | EGFR secondary T790M/C797S = osimertinib resistance; MET amp. = bypass (NSCLC/GCJ); KRAS G12C re-activation post-sotorasib; ERBB2/3 amp. = anti-EGFR resistance in CRC; AXL = innate MAPKi/ICI resistance in melanoma/NSCLC | Identify bypass-signaling tumor subclones before clinical progression; link RTK overexpression genotype to expression per cell |
| PI3K / AKT / mTOR Resistance | PIK3CA, PIK3R1, PTEN, AKT1, AKT2, AKT3, MTOR, TSC1, TSC2, RICTOR, SGK1, INPP4B, PHLPP1, PDK1, FBXW7, IGF1R, IRS1, IRS2 (18) | PI3K/AKT survival pathway; drug efflux pumps; feedback reactivation | PTEN loss = PI3K inhibitor sensitivity; PIK3CA mut. = alpelisib target (breast); mTORC2/SGK1 = AKT inhibitor resistance; IGF1R = bypass of RTK inhibition | Correlate PI3K pathway expression with PTEN loss per cell; detect mTORC2 reactivation |
| CDK4/6 / Cell Cycle Resistance | CDK4, CDK6, CCND1, CCND2, CCNE1, RB1, E2F1, E2F3, CDKN2A, CDKN1B, CDK2, AURKB, PLK1, MYC, MYCN, CCNB1 (16) | CDK4/6 inhibitor resistance; RB pathway loss; alternative cyclin activation | CCND1 amp. or CDKN2A loss = intrinsic CDK4/6 resistance; RB1 loss = acquired resistance in breast/NSCLC; CCNE1 amp. = CDK2 bypass; MYC amp. = G1 phase bypass | Identify RB1-null resistant subclones; detect CCNE1-amp CDK4/6-refractory cells |
| 2 · DNA Repair & Therapy Resistance · 40 genes | ||||
| PARP Inhibitor Resistance | BRCA1, BRCA2, RAD51, PALB2, FANCA, FANCD2, PARP1, PARP2, RAD51C, BRIP1, RIF1, PTIP (PAXBP1), HELB, MAD2L2 (REV7), SHLD1, SHLD2, DYNLL1, USP11 (18) | HR repair restoration; PARP inhibitor bypass; reversion mutation | BRCA1/2 reversion mutations = secondary PARPi resistance; RAD51 hyperactivation = 53BP1 loss-mediated HR restoration; RIF1/PTIP = NHEJ vs HR balance | Identify HR-restored tumor cells; correlate RAD51 expression with reversion genotype per cell |
| Chemotherapy Resistance (Nucleoside) | TYMS, DPYD, TP, RRM1, RRM2, DCK, CDA, SLC29A1 (ENT1), SAMHD1, NT5C2, ABCB1 (MDR1), ABCG2, ABCC1, ABCC4, MSH2, MLH1 (16) | Nucleoside analogue metabolism; multidrug efflux; chemotherapy resistance | RRM1 overexpression = gemcitabine resistance in PDAC; TYMS = 5-FU/capecitabine resistance; SAMHD1 = cytarabine resistance in AML; ABCB1/ABCG2 = broad drug efflux pump | Identify ABCB1/ABCG2-high drug-efflux cells; correlate SAMHD1 expression with cytarabine sensitivity per AML cell |
| Platinum / Alkylator Resistance | ERCC1, ERCC2, ERCC3, XPC, MLH1, MSH2, MGMT, BRCA1, RAD51, FANCD2, GSTP1, ABCB1, BCL2, BCL2L1, ATP7B (copper efflux) (15) - overlap trimmed | NER; MMR; glutathione conjugation; cisplatin resistance | ERCC1 overexpression = cisplatin resistance in NSCLC/bladder; MGMT methylation = TMZ sensitivity in GBM; GSTP1 = glutathione conjugation resistance; ATP7B = copper/platinum efflux | Link ERCC1/MGMT expression to platinum/alkylator sensitivity per tumor cell |
| 3 · Apoptosis & Survival Escape · 30 genes | ||||
| BCL-2 Family Resistance | BCL2, BCL2L1 (BCL-XL), MCL1, BCL2L2 (BCL-W), BCL2A1 (Bfl-1), BAX, BAK1, BIM (BCL2L11), PUMA (BBC3), NOXA (PMAIP1), BAD, BID, HRK, BCLAF1 (15) | Intrinsic apoptosis; venetoclax/navitoclax resistance; BH3 profiling | MCL1 upregulation = venetoclax resistance in AML/CLL; BCL-XL overexpression = navitoclax resistance; BIM deletion = EGFR inhibitor resistance; BAX frameshift in MSI-H tumors | Predict venetoclax sensitivity per blast subpopulation; identify MCL1-high resistant cells from naive sample |
| IAP / Death Receptor | BIRC5 (survivin), XIAP, BIRC2, BIRC3, CFLAR (c-FLIP), CASP3, CASP8, CASP9, FASL (TNFSF6), TRAIL (TNFSF10), TNFRSF10A (DR4), TNFRSF10B (DR5), FAS, TNFRSF1A (15) | IAP-mediated apoptosis block; TRAIL resistance; extrinsic pathway | Survivin overexpression = chemotherapy/ICI resistance; c-FLIP blocks TRAIL death; DR4/DR5 agonist antibodies emerging; IAP inhibitors (Smac mimetics) restore apoptosis sensitivity | Identify BIRC5/CFLAR-high anti-apoptotic subpopulations; link to therapy resistance per cell |
| 4 · Lineage Plasticity & Phenotype Switching · 35 genes | ||||
| Epithelial-Mesenchymal / Dedifferentiation | CDH1, CDH2, VIM, SNAI1, SNAI2, ZEB1, ZEB2, TWIST1, AXL, NRG1, EGFR, SOX9, ALDH1A1, CD44, CD24 (low), NOTCH1, WNT5A, CTNNB1, TGFbeta1 (19) | EMT; cancer stem cell; dedifferentiated resistance state | EMT = resistance to EGFR/ALK inhibitors (NSCLC), CDK4/6 (breast), vemurafenib (melanoma); AXL = low-MITF mesenchymal melanoma state; ZEB1 drives chemo/targeted therapy resistance | Identify EMT-state resistant subpopulations; detect AXL+ mesenchymal resistance state before clinical progression |
| Neuroendocrine Transdifferentiation | CHGA, SYP, ENO2, ASCL1, NEUROD1, SOX2, MYCN, PEG10, DLL3, BRN2 (POU3F2), INSM1, FOXA2, ROBO1 (13) | Neuroendocrine lineage switching; AR-independent CRPC-NE; SCLC transformation | CRPC-NE under ADT = AR-independent; SCLC transformation from NSCLC under EGFR TKI; DLL3 = therapy target in NE-transformed tumors; MYCN amp. drives NE identity | Identify NE-transdifferentiated tumor cells; track lineage switch before clinical progression |
| Epigenetic Reprogramming | DNMT3A, TET2, EZH2, SUZ12, KDM5B, KDM5C, ARID1A, SMARCB1, BRD4, HDAC1, HDAC2, SETD2, KAT6A, EP300, CREBBP (15) | Chromatin remodeling; epigenetic drug resistance; phenotype switching | EZH2 overexpression = EMT/resistance; ARID1A loss = SWI/SNF-deficient chromatin opening; BRD4 = MYC transcription driving resistance; KDM5B = epigenetic resistance to EGFR/BRAF inhibitors | Identify EZH2-high epigenetically silenced resistant cells; link chromatin state to drug sensitivity per cell |
| 5 · Immune Checkpoint Resistance · 32 genes | ||||
| Primary ICI Resistance | CTNNB1 (WNT active), B2M, HLA-A, HLA-B, JAK1, JAK2, PTEN, STK11, KEAP1, CDK4, CCND1, VEGFA, IDO1, TGFB1, CXCL12, SMAD4 (16) | Intrinsic ICI resistance pathways; immune exclusion; antigen presentation loss | WNT/β-catenin = immune desert; B2M/HLA-A loss = T cell evasion; STK11/KEAP1 = neutrophil-inflamed non-responders in NSCLC; PTEN loss = PI3K-driven Treg recruitment | Map primary resistance pathways per tumor cell; link WNT activation to immune exclusion gene expression |
| Acquired ICI Resistance | TOX, NR4A1, PDCD1 (PD-1), HAVCR2 (TIM-3), LAG3, TIGIT, ENTPD1, PRDM1, IRF4 (high), TREM2, SPP1, APOE (on macrophages), FOXP3, IL2RA (14) | T cell terminal exhaustion; macrophage resistance evolution; Treg expansion | TOX-driven terminal exhaustion = ICI-refractory; TREM2+ macrophage expansion = acquired resistance (observed in clinical data); Treg expansion under anti-PD-1; secondary MHC-I loss clones | Track T cell exhaustion trajectory over treatment; detect TREM2+ macrophage accumulation as early resistance biomarker |
| CAR-T Resistance | CD19 (escape tracking), TNFRSF17 (BCMA downreg), TOX, BATF, PDCD1, HAVCR2, CISH, REGNASE-1, SLC2A1 (metabolic), TGFB1, IDO1, IL10, CD274 (CD19 loss proxies + exhaustion) (12) - overlap trimmed | CAR-T antigen escape; product exhaustion; immunosuppressive TME | CD19 loss in 30–50% B-ALL relapse post-CAR-T; BCMA downregulation in myeloma; tonic signaling exhaustion in CD19/GD2 CAR-T; TME IL-10/TGF-β suppress CAR-T function | Detect antigen-negative escape clones; identify exhaustion onset in CAR-T product or post-infusion |
| 6 · Metabolic & Microenvironmental Resistance · 28 genes | ||||
| Warburg / Oxidative Resistance | LDHA, HK2, PKM2, SLC2A1, PDK1, FASN, ACACA, CPT1A, GLS, PRKAA1, HIF1A, EPAS1, CA9, BNIP3, DDIT4, NDRG1 (16) | Warburg glycolysis; lipid metabolism; hypoxic drug resistance | LDHA overexpression = hypoxia-driven cisplatin resistance; FASN = lipid synthesis dependency in castration-resistant PCa/HER2+ BC; HIF1A = broad drug resistance in hypoxic tumor core; CPT1A = metabolic adaptability | Map metabolic state per tumor cell; correlate HIF1A expression with drug resistance per single cell |
| Drug Efflux & Detoxification | ABCB1 (MDR1), ABCG2 (BCRP), ABCC1 (MRP1), ABCC4, ABCC5, ABCA1, SLC22A1, SLC29A1, GSTP1, GSTM1, CYP3A4, CYP1B1, NQO1, GPX4 (ferroptosis resistance) (14) | Multidrug efflux transporters; drug metabolism; oxidative detoxification | ABCB1/ABCG2 = broad MDR in AML, ALL, solid tumors; GSTP1 overexpression = platinum resistance; SLC29A1 loss = gemcitabine resistance; GPX4 = ferroptosis resistance (emerging resistance mechanism) | Identify ABCB1-high drug-efflux cells; correlate efflux pump expression with chemotherapy sensitivity per tumor subclone |
| 7 · Senescence & Non-Apoptotic Resistance · 25 genes | ||||
| Senescence / SASP | CDKN1A (p21), CDKN2A (p16), TP53, GLB1 (SA-β-gal), LMNB1, HMGA2, IL6, IL8 (CXCL8), CCL2, MMP3, VEGFA, SERPINE1, IGFBP3, IGFBP5, GDF15 (15) | Therapy-induced senescence (TIS); senescence-associated secretory phenotype (SASP) | TIS promotes tumor dormancy after chemotherapy; SASP cytokines (IL-6, CXCL8) remodel TME and promote drug resistance in neighboring cells; senolytics (navitoclax, dasatinib+quercetin) emerging | Identify senescent tumor cells (p21+p16+); map SASP-secreting cells and their paracrine impact on TME |
| Ferroptosis / Autophagy Resistance | GPX4, SLC7A11 (xCT), SLC3A2, HMOX1, FTH1, FTL, ACSL4, LPCAT3, BECN1, ATG5, ATG7, MAP1LC3B (LC3), SQSTM1 (p62), ULK1, MTOR (15) - overlap trimmed | Lipid peroxidation defense; ferroptosis resistance; autophagy survival | GPX4 overexpression = ferroptosis resistance to RSL3/erastin; SLC7A11 (xCT) = cystine import for GSH synthesis; autophagy = chemo resistance in PDAC/melanoma; ACSL4 = ferroptosis sensitivity marker | Identify GPX4/SLC7A11-high ferroptosis-resistant cells; quantify autophagy state per tumor subpopulation |
Total: 252 genesCat 1: 59 · Cat 2: 49 · Cat 3: 30 · Cat 4: 47 · Cat 5: 43 · Cat 6: 30 · Cat 7: 30
ⓘ 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.