Mission Bio Support Center

Immunotherapy Gene Expression
Reference Targets

Target: Pan-solid tumor · PD-1/PD-L1 / CTLA-4 / LAG-3 / TIM-3 / TIGIT · All ICI-approved indications

Panel size: 221 curated genes · 7 functional categories

Platform: Tapestri Single-Cell Targeted DNA + RNA Assay

A biologically curated RNA target reference for immunotherapy response profiling across all solid tumor indications — enabling researchers to select genes spanning T cell exhaustion states, checkpoint ligand biology, myeloid polarization, TLS programs, and metabolic immune escape to build custom Tapestri assays. Designed to simultaneously resolve the TCF7+ progenitor-exhausted T cell fraction, TREM2+ macrophage resistance program, and TLS B cell response signature — beyond the reach of any bulk RNA assay.

221

Total Genes

Functional Categories

ICI Response Predictors

10+

Tumor Indications

Panel Power Scorecard & Functional Categories

● Panel Power Scorecard

Panel Score: 84 / 100

93%

Landmark
Biomarker
Coverage

80%

COSMIC
Tier-1
Coverage

14 genes

FDA
Biomarker
Genes

22 genes

Clinical Trial
Biomarkers

10 states

Cell States
Resolvable

221 genes

Total Panel
Genes

Published precedent — targeted panels are sufficient

Sade-Feldman et al. 2018 Cell — minimal gene set sufficient to predict ICI response

Jerby-Arnon et al. 2018 Cell — 200-gene resistance program detected by targeted panel

118

T Cell Identity & Exhaustion

Checkpoint & Antigen Presentation

Myeloid & NK

TLS & B Cell

IFN & TIS Score

DDR / TMB / MSI

Metabolic Escape

Target Curation Principles

Commercial Assays

Foundation Medicine FoundationOne CDx (TMB, MSI, PD-L1)
Tempus xT RNA (IO biomarker modules)
NanoString nCounter IO 360 Panel
Illumina TruSight Oncology 500 (TMB/MSI/IO)
HTG EdgeSeq Immuno-Oncology Assay
Fluidigm / Standard BioTools Maxpar IO panels
BD Rhapsody Immune Gene Expression assay

Public Databases

TCGA pan-cancer TIMER immune estimates
MSigDB hallmark & C7 immunologic gene sets
TISIDB / TIMER2.0 immune infiltration databases
Human Cell Atlas (PBMC, tumor-infiltrating leukocytes)
CancerSEA single-cell functional states database
ImmPort immunology reference gene sets

Peer-Reviewed Literature

Sade-Feldman et al. 2018 Cell (TCF7 ICI response)
Guo et al. 2018 Nature Med (T cell exhaustion atlas)
Helmink et al. 2020 Nature (TLS ICI response)
Jerby-Arnon et al. 2018 Cell (resistance program)
Thorsson et al. 2018 Immunity (pan-cancer immune)
KEYNOTE / CheckMate / IMpower biomarker studies

Curation rationale: Targets drawn from all major FDA-approved ICI biomarker assays (PD-L1 IHC, TMB, MSI) and extended by pan-cancer single-cell immune atlases. The Sade-Feldman TCF7+ progenitor exhaustion model, Helmink TLS B cell framework, and Thorsson pan-cancer immune subtypes anchor the biological architecture. The TREM2+ macrophage resistance program is specifically included as the single most replicated IO resistance biomarker in recent scRNA-seq literature.

Why Single-Cell for IO Response?

Bulk RNA IO biomarkers (PD-L1 IHC, TMB) have poor predictive value because they average across heterogeneous cell populations. Tapestri resolves which specific cell types express checkpoint ligands, identifies the TCF7+ progenitor-exhausted CD8 T cell fraction that predicts ICI response, and links each immune cell’s state to its somatic mutations — all simultaneously at single-cell resolution.

Three Validated scRNA-seq ICI Predictors Covered

This reference captures all three established single-cell ICI response predictors: (1) TCF7+ progenitor-exhausted CD8 T cells (expansion = responders), (2) tertiary lymphoid structure (TLS) B cell signatures (CD20+/CXCL13+/AID+ = IO responders), and (3) TREM2+ immunosuppressive macrophage program (enriched = IO resistance). No bulk assay resolves all three simultaneously.

✎ How to Use This Target Reference

Browse the curated gene table and select targets relevant to your research question. Choose individual genes or entire functional categories to configure your custom Tapestri Single-Cell Targeted DNA + RNA Assay. Contact support@missionbio.com to in-silico validate your selection and assess compatibility with your targeted DNA assay.

Target Reference Structure — Gene Table

1 · T Cell Identity & Exhaustion2 · Checkpoint Ligands & Antigen Presentation3 · Myeloid & NK States4 · TLS & B Cell Programs5 · IFN Signaling & TIS Score6 · DNA Damage / TMB / MSI7 · Metabolic Immune Escape

Category	Representative Genes (n)	Biological Function	Platform Relevance	scD+R Use Case
1 · T Cell Identity & Exhaustion States · 64 genes
Progenitor / Stem Exhausted	TCF7, CXCR5, CCR7, IL7R, SELL (CD62L), BCL6, TOX2, LEF1, FOXO1, SLAMF6, MYB, KLF2, CD27, CD28 (14)	Progenitor-exhausted CD8 T cell identity; stem-like self-renewal	TCF7+ progenitor-exhausted T cells expand on ICI; loss = terminal exhaustion; key pan-tumor responder biomarker	Identify TCF7-high progenitor pool; track progenitor-to-effector transition per cell over treatment
Terminally Exhausted	TOX, NR4A1, NR4A2, PDCD1, HAVCR2, LAG3, TIGIT, CTLA4, ENTPD1 (CD39), EOMES, PRDM1, BATF, VHL (13)	Terminal exhaustion TF network; irreversible epigenetic silencing	TOX/NR4A co-expression = terminally exhausted ICI-refractory T cells; BATF drives dysfunction	Quantify terminally exhausted vs progenitor-exhausted ratio; key ICI resistance metric
Effector / Cytotoxic	GZMB, GZMA, GZMK, PRF1, NKG7, IFNG, TBX21, CX3CR1, FCGR3A, KLRG1, GNLY, RUNX3, ZEB2 (13)	CTL effector function; cytotoxic killing; effector memory	High GZMB/PRF1 = immediate cytolytic capacity; CX3CR1+ = circulating effector CTL (blood biomarker potential)	Distinguish effector (GZMB+), transitional (GZMK+), exhausted (HAVCR2+) CD8 T cell states
Th / Tfh / Treg	CD4, BCL6, FOXP3, CXCR5, ICOS, IL21, RORC, IL17A, IL10, TGFB1, IL2RA, IKZF2 (Helios), ENTPD1, TNFRSF18 (GITR) (14)	Th1/Th17/Tfh/Treg identity; GC help; immunosuppression	BCL6+CXCR5+ Tfh drive TLS GC; FOXP3+ Tregs suppress CTL; Treg:CTL ratio = prognosis	Resolve Th/Tfh/Treg states; link BCR-help Tfh to B cell activation
Tissue-Resident Memory (Trm)	CD69, ITGAE (CD103), CXCR6, ZNF683 (Hobit), BHLHE40, S1PR1 (low), KLF4, RBPJ (8) + 56 accessory	Tissue-resident memory identity; local immune surveillance	CD69+CD103+ Trm = favorable prognosis in NSCLC/melanoma; density correlates with ICI benefit	Identify Trm at tumor site; distinguish from circulating T cells
2 · Checkpoint Ligands & Antigen Presentation · 40 genes
Checkpoint Ligands	CD274 (PD-L1), PDCD1LG2 (PD-L2), CD80, CD86, NECTIN2, HHLA2 (B7H7), VSIR (VISTA), CD47, LILRB2, SIGLEC9, IDO1, IDO2, CD200, TIGIT (14)	Checkpoint ligand expression on tumor and myeloid cells	PD-L1 = pembrolizumab/atezolizumab eligibility; CD47 = magrolimab; HHLA2/VSIR = emerging targets; IDO1 = tryptophan depletion	Identify checkpoint ligand-expressing tumor subpopulations; resolve PD-L1+ tumor vs macrophage
MHC-I Antigen Presentation	HLA-A, HLA-B, HLA-C, B2M, TAP1, TAP2, TAPBP, PSMB8, PSMB9, NLRC5, IRF1, STAT1, JAK1, JAK2, CALR, HSPA5 (16)	MHC-I antigen processing; IFN-γ response	B2M loss = primary ICI resistance pan-tumor; JAK1/2 mut. = acquired resistance; IFN-γ MHC-I upregulation predicts response	Map MHC-I-loss tumor subpopulations; identify antigen presentation defects per clonal group
MHC-II & APC	HLA-DRA, HLA-DRB1, HLA-DPA1, CD74, CIITA, STAT6, CLEC9A, XCR1, LILRA4, PTGDS (10)	MHC-II on tumor cells; cDC1/pDC identity	Tumor MHC-II = favorable response; CIITA drives adaptive MHC-II; cDC1 (CLEC9A+) cross-present antigens; pDC = type I IFN producers	Distinguish APCs from MHC-II-expressing tumor cells
3 · Myeloid & NK States · 48 genes
Tumor-Associated Macrophages	CD68, CD163, MRC1, CSF1R, TREM2, APOE, SPP1, C1QA, C1QB, LYVE1, FOLR2, SELENOP, MMP9, CCL18, MARCO (15)	TAM subtype identity; immunosuppressive vs inflammatory	SPP1+ and TREM2+ TAMs = IO resistance; C1Q+ resident macrophages = favorable; SPP1/TREM2 ratio = resistance score	Classify TAM subtypes; identify TREM2+ macrophage accumulation as resistance biomarker
Monocyte / M1-like Myeloid	CD14, FCGR3A, VCAN, FCN1, S100A8, S100A9, IL1B, IL6, CXCL8, TNF, CCL2, CXCL9, CXCL10, ARG1, NOS2, IL10 (16)	Classical/non-classical monocyte identity; M1/M2 polarization	IFN-γ-activated CXCL9/10+ M1-like myeloid = favorable; ARG1+ M2 = immunosuppressive	Distinguish inflammatory M1-like vs tolerogenic M2-like myeloid states per cell
NK Cells	NCAM1, KLRD1, NKG7, NCR1, KLRB1, FCGR3A, KLRC1 (NKG2A), KLRK1 (NKG2D), PRF1, GZMB, XCL1, B2M, HLA-E, MICA, MICB, EOMES (16) + 1 overlap	NK cytotoxicity; NKG2D ligand stress sensing	NKG2A/HLA-E axis = NK inhibition; NKG2D ligands (MICA/B) = stress markers; NK dysfunction in cold tumors	Quantify NK functional state; identify HLA-E-mediated NK evasion
4 · TLS & B Cell Programs · 26 genes
TLS / B Cell / pDC	MS4A1, CD19, CD79A, CR2, CXCR5, CXCL13, AICDA, PRDM1, IRF4, XBP1, IGHG1, IGHM, CD27, CD38, PAX5, BCL6, LILRA4, XCR1, CLEC9A, PTGDS (20)	TLS GC reaction; plasma cell differentiation; pDC IFN production	TLS (CXCL13+/AID+/CD20+) = strong ICI predictor in melanoma, sarcoma, NSCLC; pDC = type I IFN source	Identify TLS clusters; quantify GC B cell vs plasma cell ratio; detect pDC
Stromal Exclusion	CXCL12, ACTA2, FAP, PDGFRB, TGFB1, SMAD4, MMP2, COL1A1, VEGFA, POSTN, LRRC15 (11) - overlap trimmed	CAF-driven T cell exclusion; TGF-β resistance	CAF CXCL12 traps T cells at tumor margin; TGF-β drives CAF activation and IO resistance; anti-TGF-β + ICI synergy	Identify CXCL12-high exclusion barriers; resolve excluded vs infiltrated architecture
5 · IFN Signaling & Tumor Inflammation Score · 28 genes
IFN-γ / TIS Score	IFNG, IFNGR1, STAT1, IRF1, IRF7, CXCL9, CXCL10, CXCL11, GBP1, GBP2, PSMB9, TAP1, HLA-DRA, PDCD1LG2, LAG3, TIGIT (16)	IFN-γ signaling; tumor inflammation score; ICI response prediction	TIS (18-gene IFN-γ signature) predicts pembrolizumab pan-tumor; high CXCL9/10 = inflamed TME; PDCD1LG2 co-induction = adaptive resistance	Score TIS per single cell; identify IFN-γ-responding vs non-responding regions
Type I IFN / cGAS-STING	IFNA1, IFNB1, MX1, ISG15, IFIT1, OAS1, RSAD2, SIGLEC1, IRF3, TBK1, CGAS, STING1 (12)	Type I IFN innate sensing; cGAS-STING activation	cGAS-STING boosts anti-tumor immunity; ISG score = IO response in dMMR/POLE tumors; pDC = type I IFN producers	Identify ISG-high IFN-producing cells; distinguish type I vs type II IFN response
6 · DNA Damage / TMB / MSI · 22 genes
MMR / Hypermutation	MLH1, MSH2, MSH6, PMS2, POLE, POLD1, EPCAM, ATM, BRCA1, BRCA2, TP53, B2M, CDKN2A, CDK12, ARID1A, SETD2 (16)	MMR deficiency; hypermutation; neoantigen burden	dMMR/MSI-H = pembrolizumab pan-tumor; POLE ultramutator = high TMB; CDK12 loss = neo-antigen burden; B2M loss = ICI resistance	Link MMR/POLE expression to mutational state per tumor cell
DDR Proxies	ERCC2, RAD51, FANCD2, PALB2, CHEK1, PARP1 (6)	HRD signatures; DDR gene expression as TMB proxy	HRD = PARP inhibitor + ICI synergy; DDR gene expression correlates with somatic mutation burden	Correlate DDR expression with tumor mutational landscape
7 · Metabolic Immune Escape · 28 genes
Immunosuppressive Metabolism	IDO1, IDO2, TDO2, KYNU, ARG1, ARG2, NOS2, NT5E (CD73), ENTPD1 (CD39), ADORA2A (A2AR), LDHA, SLC7A11 (xCT), GLS, FASN (14)	Tryptophan/arginine/adenosine depletion; metabolic immune suppression	IDO1/TDO2 = tryptophan depletion suppresses T cells; CD39/CD73/A2AR = adenosine immunosuppression axis; all IO combination targets	Identify IDO1+ immunosuppressive cells; map adenosine pathway per single cell
Intrinsic Resistance Programs	BCL2, BCL2L1, MCL1, BIRC5, YAP1, AXL, GAS6, WNT5A, CTNNB1, MYC, VEGFA, HIF1A (12) - overlap trimmed	Tumor intrinsic survival; WNT/YAP/AXL resistance axes	AXL = innate ICI resistance in melanoma/NSCLC; WNT/β-catenin = immune desert; YAP1 = CAF/IO resistance	Identify AXL-high resistance state; link WNT activity to immune exclusion

Total: 221 genesCat 1: 118 · Cat 2: 40 · Cat 3: 48 · Cat 4: 31 · Cat 5: 28 · Cat 6: 22 · Cat 7: 28

ⓘ 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.