RNA TargetsHematologic OncologyResearch Use Only
Myeloproliferative Neoplasms (MPN)
Gene Expression Reference Targets
Gene Expression Reference Targets
A biologically curated RNA target reference for myeloproliferative neoplasms spanning JAK2/CALR/MPL driver mutations, inflammatory cytokine fibrosis pathways, myeloid lineage differentiation, and ruxolitinib/fedratinib resistance biology — enabling researchers to configure custom Tapestri assays for MPN disease mechanism, transformation risk, and precision therapy studies.
243
Total Genes
7
Functional Categories
4
MPN Subtypes Covered
6+
Curation Sources
1
Panel Power Scorecard & Functional Categories
● Panel Power Scorecard
Panel Score: 67 / 100
86%
Landmark
Biomarker
Coverage
Biomarker
Coverage
80%
COSMIC
Tier-1
Coverage
Tier-1
Coverage
7 genes
FDA
Biomarker
Genes
Biomarker
Genes
12 genes
Clinical Trial
Biomarkers
Biomarkers
7 states
Cell States
Resolvable
Resolvable
243 genes
Total Panel
Genes
Genes
Published precedent — targeted panels are sufficient
Psaila et al. 2020 Cancer Cell (MPN single-cell atlas)
Verstovsek et al. 2012 NEJM (COMFORT-I ruxolitinib MF)
52
JAK-STAT / Driver
48
Cytokine / Fibrosis
52
HSC / Myeloid
40
Immune / BM
32
Resistance
18
Cell Cycle
20
Epigenetic
2
Background & Curation Principles
Commercial Assays
- FoundationOne Heme
- IDT xGen MPN Panel
- QIAGEN QIAseq Myeloid
- Thermo Oncomine Myeloid
Public Databases
- COSMIC (MPN mutations)
- ELN MPN guidelines
- ClinVar (JAK2/CALR)
- GEO MPN scRNA datasets
- Human Cell Atlas (hematopoietic)
Peer-Reviewed Literature
- JAK2 V617F discovery (James 2005 Nature)
- CALR mutations in MPN (Klampfl 2013 NEJM)
- Myelofibrosis scRNA atlas (Psaila 2020 Cancer Cell)
- Ruxolitinib COMFORT trials (Verstovsek 2012 NEJM)
Why Single-Cell RNA for MPN?
MPN is a clonal HSC disorder where JAK2 V617F-positive and JAK2 wild-type cells coexist in the same patient — and their proportions predict transformation risk. Bulk RNA cannot resolve the transcriptional state of JAK2-mut vs JAK2-WT HSCs. Tapestri co-detects JAK2 V617F mutation alongside inflammatory gene expression per HSC, enabling direct linkage of driver mutation clone size to transcriptional output — the mechanistic underpinning of allele burden-directed therapy decisions.
CALR vs JAK2 — Different Mechanisms, Same Disease
CALR-mutant ET/MF activates MPL signaling via thrombopoietin receptor, while JAK2 V617F directly activates downstream JAK-STAT. These two oncogenic programs have distinct transcriptional signatures: CALR-mut = lower STAT1 activation; JAK2 V617F = higher STAT3/IFN response. Panel enables per-cell subclone identification + transcriptional program characterization that bulk methods cannot achieve.
3
Target Reference Structure — Gene Table
1 · JAK-STAT / Driver2 · Cytokine / Fibrosis3 · HSC / Myeloid Differentiation4 · Immune / Inflammation5 · Resistance / BCL-26 · Cell Cycle7 · Epigenetic / CHIP
| Category | Representative Genes (n) | Biological Function | Disease Relevance | scD+R Use Case |
|---|---|---|---|---|
| 1 · JAK-STAT / Driver Signaling · 52 genes | ||||
| Driver | JAK2, CALR, MPL, JAK1, JAK3, STAT1, STAT3, STAT5A, STAT5B, SOCS1, SOCS3, LNK (SH2B3), CBL, KRAS, NRAS, RAS, FLT3, KIT, CSF3R, EPOR, THPO, CISH (22) + 30 accessory | JAK-STAT pathway; TPO/EPO receptor signaling; RAS activation | JAK2 V617F = ruxolitinib/fedratinib/pacritinib target; CALR = luspatercept context; CSF3R = CNL (ruxolitinib); MPL = eltrombopag target | Co-detect JAK2 mutation + STAT3/5 activation state per HSC/progenitor |
| 2 · Cytokine / Fibrosis / BM Stroma · 48 genes | ||||
| Stromal | TGFB1, TGFB2, TGFBR1, TGFBR2, IL6, IL6R, TNF, CXCL8, IL1B, IL1A, CXCL4 (PF4), CXCL10, CCL2, CCL5, VEGFA, PDGFRA, PDGFRB, ACTA2, COL1A1, FN1, CTGF (21) + 27 accessory | Inflammatory cytokine storm; TGFβ-driven fibrosis; megakaryocyte-derived profibrotic factors | TGFβ1 = MF fibrosis driver (released by megakaryocytes); PF4 = MF megakaryocyte; IL6 = constitutional symptoms; CXCL8 = BM niche retention | Identify TGFβ1-producing megakaryocyte subclones driving fibrosis |
| 3 · HSC / Myeloid Progenitor Differentiation · 52 genes | ||||
| Lineage | CD34, CD38, CD117 (KIT), CD133 (PROM1), GATA1, GATA2, KLF1, TAL1, FLI1, ETV6, RUNX1, CEBPA, SPI1, IRF8, GFI1, IKAROS (IKZF1), MPO, ELANE, CD71 (TFRC), GYPA, ITGA2B (GP2B) (21) + 31 accessory | HSC/MPP identity; erythroid/megakaryocyte/myeloid lineage commitment | GATA1 = erythro-megakaryocyte fate; RUNX1 = HSC self-renewal; MPO = granulocyte commitment; ITGA2B = megakaryocyte identity | Reconstruct myeloid differentiation hierarchy; identify blocked maturation in blast-phase transformation |
| 4 · Immune / Inflammatory TME · 40 genes | ||||
| Immune | CD3E, CD8A, CD4, GZMB, PDCD1, LAG3, CD274, FOXP3, IL2RA, TREM2, SPP1, CD68, CSF1R, IL10, TNF, IFNG, NK cells (NKG7, KLRD1), NCAM1 (18) + 21 accessory | Immune suppression in BM; NK exhaustion; inflammatory monocytes | T cell exhaustion in MF = impaired NK/T surveillance; IL10 = immunosuppressive; TNF = constitutionally symptomatic | Map BM immune cell states; identify exhausted NK subpopulations that fail to clear JAK2+ clones |
| 5 · Resistance / BCL-2 / Apoptosis · 32 genes | ||||
| Resistance | BCL2, MCL1, BCL2L1, BCL2L11, BAX, BIRC5, JAK2, STAT3, AURKB, CCND1, CDK6, RB1, MDM2, TP53, CDKN2A (15) + 17 accessory | JAK inhibitor resistance; apoptosis evasion; venetoclax combination | MCL1/BCL2 = ruxolitinib resistance (venetoclax combination rationale); AURKB = transformation marker; TP53 mut = blast-phase transformation | Identify anti-apoptotic subclones resistant to ruxolitinib; assess venetoclax eligibility |
| 6 · Cell Cycle / Proliferation · 18 genes | ||||
| Cell Cycle | MKI67, TOP2A, CCNB1, CDK2, E2F1, MCM2, PLK1, CDC20, BUB1 (9) + 9 accessory | Proliferative index; transformation risk | MKI67 = blast-phase transformation risk; PLK1 = volasertib target in MPN-BP | Score proliferating progenitor fraction; track blast-phase transformation |
| 7 · Epigenetic / CHIP Mutations · 20 genes | ||||
| Epigenetic | DNMT3A, TET2, ASXL1, EZH2, IDH1, IDH2, SRSF2, SF3B1, U2AF1, ZRSR2, PHF6, BCOR, KDM6A (13) + 7 accessory | CHIP-driver co-mutations; epigenetic progression; transformation | ASXL1/SRSF2 co-mutation = high transformation risk (MIPSS70); TET2/DNMT3A = early clonal events; IDH1/2 = blast-phase (enasidenib) | Identify co-mutation landscape per HSC clone; stratify transformation risk by epigenetic mutation profile |
Total: 243 genesCat 1: 52 · Cat 2: 48 · Cat 3: 52 · Cat 4: 40 · Cat 5: 32 · Cat 6: 18 · Cat 7: 20
ⓘ 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.