HAEM5:Primary cutaneous gamma/delta T-cell lymphoma
Primary Author(s)*
Mahzad Azimpouran, MD; Sumire Kitahara, MD; Cedars-Sinai, Los Angeles, CA
WHO Classification of Disease
| Structure | Disease |
|---|---|
| Book | Haematolymphoid Tumours (5th ed.) |
| Category | T-cell and NK-cell lymphoid proliferations and lymphomas |
| Family | Mature T-cell and NK-cell neoplasms |
| Type | Primary cutaneous T-cell lymphoid proliferations and lymphomas |
| Subtype(s) | Primary cutaneous gamma/delta T-cell lymphoma |
Related Terminology
| Acceptable | N/A |
| Not Recommended | N/A |
Gene Rearrangements
| Driver Gene | Fusion(s) and Common Partner Genes | Molecular Pathogenesis | Typical Chromosomal Alteration(s) | Prevalence -Common >20%, Recurrent 5-20% or Rare <5% (Disease) | Diagnostic, Prognostic, and Therapeutic Significance - D, P, T | Established Clinical Significance Per Guidelines - Yes or No (Source) | Clinical Relevance Details/Other Notes |
|---|---|---|---|---|---|---|---|
| Arm‑level chromosomal alterations (e.g., 9p, 18q deletions; 1q, 7q,15q gains) | — | Copy number loss or gain → altered gene dosage of tumour suppressors/oncogenes | Other / chromosomal alteration | Recurrent (5‑20%) (9p del ~22%, 18q del ~22%; 1q/7q/15q gains ~33‑39%) | D / P | No | These structural changes suggest genomic instability and aggressive biology; may help risk stratification though not diagnostic per se[1] |
| Fusion: FYN :: (probable partner TRAF3IP2) | TRAF3IP2 | Structural alteration – deletion/exon8 deletion → (in other T‑cell lymphomas) FYN::TRAF3IP2 fusion leading to SRC‑family kinase activation; in this PCGDTCL case FYN exon8 deletion noted | Oncogene / Other | Rare (<5%) (single case reported) | T | No | Very recently described; may represent novel driver/target; further cases needed[2] |
| Fusion: PCM1 :: JAK2 | PCM1 | Fusion → juxtaposition of dimerization domain of PCM1 with kinase domain of JAK2 → constitutive JAK2 activation | Oncogene | Rare (<5%) (single documented PCGDTCL case) | T | No | Known in other T‑cell and myeloid neoplasms; in PCGDTCL this double‐hit case had PCM1::JAK2 + TBL1XR1::TP63 fusion; patient refractory to JAK inhibitor[3] |
| Fusion: TBL1XR1 :: TP63 | TBL1XR1 | Fusion → truncation/overexpression of ΔNp63 form → oncogenic p63 signalling | Oncogene / Other | Rare (<5%) (same single case) ( | P / T | No | Associated with aggressive behaviour in T‑cell lymphomas; in the reported PCGDTCL case contributed to aggressive course and JAK inhibitor resistance[3] |
Individual Region Genomic Gain/Loss/LOH
| Chr # | Gain, Loss, Amp, LOH | Minimal Region Cytoband and/or Genomic Coordinates [Genome Build; Size] | Relevant Gene(s) | Diagnostic, Prognostic, and Therapeutic Significance - D, P, T | Established Clinical Significance Per Guidelines - Yes or No (Source) | Clinical Relevance Details/Other Notes |
|---|---|---|---|---|---|---|
| 1p | Loss | 1p36.11 | ARID1A | P | No | Deleted in ~28% of cases. Indicates epigenetic/chromatin modifier pathway involvement[1] |
| 1q | Gain (arm‐level amplification) | 1q (approx chr1:144,000,000‑249,000,000) | Multiple genes on 1q (unspecified) | P / T | No | Amplification in ~33% of cases. Potential gene dosage effect; specific driver gene not yet defined[1] |
| 2q | Loss | 2q37.3 | PDCD1 | P | No | Deletion in ~22% of cases. Immune checkpoint gene loss; potential therapeutic‑escape mechanism[1] |
| 7q | Gain (arm‐level) | 7q (approx chr7:100,000,000‑159,000,000) | Multiple genes on 7q (unspecified) | P | No | Amplification in ~39% of cases. Suggests MAPK/other pathway involvement but specific gene not yet defined. |
| 9p | Loss (deletion) | 9p21.3 (~ chr9:21,900,000‑22,200,000) | CDKN2A, CDKN2B | P | No | High‐frequency homozygous or biallelic deletion (~61% of cases; 45% biallelic) in PCGDTCL. (PMC) Suggests aggressive biology, prognostic marker candidate[1] |
| 10q | Loss | 10q24.1 | FAS | P | No | Deletion in ~22% of cases. Loss of apoptosis regulator; may contribute to immune‑escape[1] |
| 15q | Gain (arm‐level) | 15q (approx chr15:30,000,000‑102,000,000) | Multiple genes on 15q (unspecified) | P | No | Amplification in ~33% of cases. Likely reflects tumour evolution rather than diagnostic biomarker[1] |
| 18q | Loss | 18q (arm level; no precise minimal region specified) | Putative tumour suppressors (unspecified) | P | No | Recurrent deletion ~22% in PCGDTCL cohort. May reflect genomic instability and poor outcome[1] |
Characteristic Chromosomal or Other Global Mutational Patterns
| Chromosomal Pattern | Molecular Pathogenesis | Prevalence -
Common >20%, Recurrent 5-20% or Rare <5% (Disease) |
Diagnostic, Prognostic, and Therapeutic Significance - D, P, T | Established Clinical Significance Per Guidelines - Yes or No (Source) | Clinical Relevance Details/Other Notes |
|---|---|---|---|---|---|
| Arm‑level somatic copy‑number variation (SCNV) (average ~4 arm‑level events per case; median ~166.5 SCNVs per sample)[1] | Reflects genomic instability; multiple gains and losses of whole chromosome arms likely contribute to oncogenesis and progression by altering gene dosage of multiple oncogenes/tumour suppressors simultaneously. (PMC) | Common (>20%) — nearly all cases show multiple arm‑level events (median 4 per sample) (PMC) | P | No | High genomic complexity may explain aggressive behaviour and poor response to therapy. Could impact prognosis or treatment resistance but not yet in guidelines. |
| High burden of somatic copy‑number variants (SCNVs) relative to single‐nucleotide variants (SNVs) (e.g., median ~166.5 SCNVs per sample) [1] | Suggests that structural genomic alterations dominate the mutational landscape, perhaps more so than classical hotspot SNVs, indicating a biology driven by large‑scale genomic disruption rather than just point mutations. | Common (>20%) | P | No | Recognising this pattern may guide expectation of complexity, but this is not currently used clinically for diagnosis or treatment. |
| Distinct cell‑of‑origin signature: Vδ1 vs Vδ2 subtype (epidermal/dermal Vδ1 vs panniculitic Vδ2) [1] | Different tissue compartments (epidermis/dermis vs subcutaneous) correspond to distinct γδ T‑cell subsets (Vδ1 vs Vδ2). The cell‑of‑origin influences mutational signatures (eg UV signature in Vδ1) and clinical phenotype (Vδ2 more aggressive)[1] | Recurrent (5‑20%) — this pattern applies in a subset of cases defined by tissue involvement and TCR subtype. | D / P | No | This dichotomy may help stratify patients clinically (Vδ2 subtype worse prognosis) but is not currently part of formal diagnostic or therapeutic guidelines. |
| Ultraviolet (UV) mutational signature in Vδ1 subtype [1] | The epidermal/dermal Vδ1 γδ T‑cell lymphomas exhibit a UV signature in their mutation spectrum, likely reflecting skin localization and UV exposure contributing to oncogenesis. | Recurrent (5‑20%) — seen in Vδ1 cases but not all. | P | No | Could suggest etiology and may influence prognosis; though not yet used for therapy selection. |
| Frequent deletions of 9p21.3 (CDKN2A region) (part of the SCNV pattern) [1] | Loss of CDKN2A/p14^ARF leads to cell‑cycle deregulation, loss of tumour suppressor control: a hallmark of many aggressive lymphomas | Common (>20%) (approx 61% of cases) | P | No | Among the most prevalent genomic events in PCGDTCL — potential prognostic marker though not yet guideline‑endorsed. |
| Multiple gains of oncogenic arms (e.g., 1q, 7q, 15q) and corresponding losses (eg 18q) [1] | Gains may increase dosage of oncogenes; losses may reduce tumour suppressor dosage—together contributing to malignant phenotype | Recurrent (5‑20%) for specific arm‑level changes (e.g., 1q gain ~33%, 7q ~39%, 15q ~33%) | P | No | These arm‑level events indicate complexity; may correlate with poorer prognosis; not yet actionable in therapy. |
| TCR chain repertoire restriction / non‑random Vγ or Vδ usage (eg Vγ3Vδ2 in panniculitic cases) [1] | Suggests antigen‑driven or tissue‐resident γδ T‑cell proliferation; highlights non‑random selection of malignant clones | Recurrent (5‑20%) in defined subtypes | D | No | Might help refine subclassification of PCGDTCL; not currently used in routine diagnostic algorithms. |
Gene Mutations (SNV/INDEL)
| Gene | Genetic Alteration | Tumor Suppressor Gene, Oncogene, Other | Prevalence -
Common >20%, Recurrent 5-20% or Rare <5% (Disease) |
Diagnostic, Prognostic, and Therapeutic Significance - D, P, T | Established Clinical Significance Per Guidelines - Yes or No (Source) | Clinical Relevance Details/Other Notes |
|---|---|---|---|---|---|---|
| STAT5B | Activating missense (e.g., p.N642H) → constitutive downstream STAT5 signalling | Oncogene | Recurrent (~5‑20 %) — e.g., in the 2020 genomic study: JAK/STAT mutations ~21 % of cases[1] | T / P: Therapeutic potential (JAK/STAT inhibition); Prognostic implication (pathway addiction/resistance) | No | Mutant STAT5B (especially N642H) shown to induce T‑cell neoplasia in models; in PCGDTCL JAK/STAT addiction shown clinically [4][5] |
| STAT3 | Activating missense (SH2 domain) → constitutive STAT3 signalling | Oncogene | Rare (<5 %) to Recurrent (≈5‑10 %) (in NK/γδ‑T lymphomas earlier) | T / P | No | Less frequent than STAT5B in PCGDTCL; part of JAK/STAT pathway involvement[1][4] |
| JAK3 | Activating mutation (e.g., p.R657W) → JAK3 tyrosine kinase activation | Oncogene | Rare (<5 %) (noted in the Daniels et al. cohort) | T | No | Supports JAK/STAT involvement; one case report showed response to JAK inhibition[5] |
| KRAS | Activating hotspot mutations (e.g., G12D, Q61H, D119N) → RAS/MAPK activation | Oncogene | Recurrent (~5‑20 %) — “KRAS was the most frequently mutated oncogene” [1] | T / P | No | MAPK pathway appears relevant; patients with MAPK‑pathway driver mutations had worse survival in the cohort[1] |
| NRAS | Activating hotspot mutation → RAS/MAPK activation | Oncogene | Rare (<5 %) to Recurrent (~5‑10 %) | T / P | No | Part of the same RAS/MAPK pathway as KRAS; less common. |
| MAPK1 | Activating mutation → MAPK1 signalling activation | Oncogene | Rare (<5 %) | T | No | Also in MAPK pathway; limited data in PCGDTCL[1][4] |
| MYC | Activating missense mutation (e.g., p.P74L) → MYC pathway up‑regulation | Oncogene | Rare (<5 %) | P / T | No | MYC pathway involvement may contribute to the aggressive phenotype; direct targeting not yet established[1] |
| MYCN | Activating mutation (e.g., p.G34R) → MYCN pathway activation | Oncogene | Rare (<5 %) | P / T | No | Highlights involvement of MYC‑family beyond MYC itself in this disease[1] |
Note: A more extensive list of mutations can be found in cBioportal, COSMIC, and/or other databases. When applicable, gene-specific pages within the CCGA site directly link to pertinent external content.
Epigenomic Alterations
N/A
Genes and Main Pathways Involved
| Gene; Genetic Alteration | Pathway | Pathophysiologic Outcome |
|---|---|---|
| DNMT3A (DNA methyltransferase) | Loss‑of‑function mutations or deletions → reduced de novo DNA methylation; “epigenetic writer” defect (DNA methylation pathway)[6] | Deregulation of gene silencing; tumour suppressor genes may remain unmethylated or aberrantly methylated → genomic instability, aberrant T‑cell differentiation/activation |
| TET2 (methylcytosine dioxygenase) | Loss‑of‑function mutations → failure of DNA 5‑mC → 5‑hmC demethylation (“epigenetic eraser” defect)[6] | Aberrant hypermethylation or demethylation patterns; influences T‑cell development and malignant transformation (e.g., in T‑fh lymphomas) |
| IDH2 (metabolic enzyme altering epigenome) | Gain‑of‑function mutation (e.g., R172) → produces 2‑hydroxyglutarate → inhibits TET family → epigenetic dysregulation[6] | Oncometabolite‑driven methylation changes, impaired differentiation, proliferation of malignant T cells |
| ARID1A (SWI/SNF chromatin‑remodeller) | Loss‑of‑function mutation/deletion → impaired nucleosome remodelling, altered chromatin accessibility (“chromatin remodeller”)[6] | Reduced tumour‑suppressor gene expression due to chromatin compaction; may influence immune microenvironment and genomic instability |
| KMT2D / KMT2A (H3K4 methyltransferases) | Loss‑of‑function mutations (“histone‑writer” defect) → decreased H3K4 methylation (activating mark)[7] | Impaired activation of gene expression programs (differentiation, apoptosis) → contributes to malignant transformation |
| KDM6A (H3K27 demethylase) | Loss‑of‑function → accumulation of H3K27me3 (repressive histone mark) (“histone‑eraser” defect)[7] | Further chromatin repression of tumour‑suppressor genes; may enhance survival of malignant T cells |
| EZH2 (PRC2 complex methyltransferase) | Overexpression/gain of function → increased H3K27me3 (“histone‑writer” overactivity) [6] | Enhanced silencing of differentiation/apoptosis genes; contributes to aggressive lymphoma phenotypes |
| CREBBP / EP300 (histone acetyl‑transferases) | Loss‑of‑function mutations (“histone‑writer” defect) → reduced histone acetylation and gene activation[7] | Diminished transcriptional activation of tumour‑suppressor/immune genes; may drive malignant progression |
| DNA methylation of specific tumour‑suppressor loci (e.g., CDKN2A promoter; FAS promoter) | Hypermethylation of promoter CpG islands → silencing of tumor suppressor / apoptosis‑initiator genes[8] | Loss of cell‑cycle control or apoptosis leads to malignant T‑cell survival/proliferation |
Genetic Diagnostic Testing Methods
| Method | Description | Type of Alteration Detected | Advantages | Limitations | Clinical Use in PCGDTCL |
| Next-Generation Sequencing (NGS) | High-throughput sequencing of targeted gene panels, whole-exome, or whole-genome sequencing | SNVs, INDELs, copy number variants (CNVs), some fusions (if RNA-seq included) | Comprehensive mutation detection; scalable; can detect multiple variants simultaneously | Requires high-quality DNA/RNA; bioinformatics expertise needed; cost-intensive | Main tool for mutational profiling in PCGDTCL; used in research and increasingly in clinical labs |
| Targeted Gene Panels (amplicon or hybrid capture-based) | Sequencing of a defined set of genes known to be relevant | SNVs, INDELs, limited CNVs, hotspot fusions (if included) | Faster, cheaper than WES/WGS; focused on clinically relevant genes | May miss novel or unexpected mutations; limited to panel content | Often used clinically to screen for mutations in JAK/STAT, RAS pathways in PCGDTCL |
| Fluorescence In Situ Hybridization (FISH) | DNA probes hybridize to metaphase or interphase chromosomes | Structural chromosomal alterations, gene fusions, amplifications, deletions | Visualizes gene rearrangements and copy number changes; established clinical use | Limited to known targets; low resolution; labor-intensive | Used to detect known translocations or gene amplifications (e.g., MYC) in lymphoma diagnosis |
| Array Comparative Genomic Hybridization (aCGH) / SNP Arrays | Genome-wide detection of copy number alterations and LOH | Copy number gains, losses, LOH (Loss of heterozygosity) | Genome-wide coverage; detects submicroscopic CNVs | Cannot detect balanced translocations or point mutations; resolution depends on array density | Useful for detecting large chromosomal alterations in lymphoma samples |
| RNA Sequencing (RNA-Seq) | Sequencing of transcriptome | Gene fusions, splice variants, expression levels | Detects novel and known fusions; measures gene expression; alternative splicing | RNA quality sensitive; bioinformatics expertise needed | Research use for identifying novel fusion partners or expression signatures in PCGDTCL |
| Sanger Sequencing | Chain termination sequencing of PCR-amplified regions | SNVs and small indels | Gold standard for validation; high accuracy | Low throughput; not suitable for large panels | Used to confirm NGS-identified mutations |
| Digital Droplet PCR (ddPCR) / qPCR | Highly sensitive quantification of known mutations or gene rearrangements | Known point mutations, copy number changes | Very sensitive, quantitative; fast turnaround | Limited to known mutations; not comprehensive | Useful for monitoring known mutations (e.g., STAT5B N642H) in minimal residual disease (MRD) or treatment response |
| Immunohistochemistry (IHC) (surrogate genetic marker) | Antibody staining of protein expression | Protein expression reflecting genetic alterations (e.g., pSTAT5B, MYC) | Widely available; easy to implement | Indirect; may not perfectly correlate with mutation status | Supportive role in diagnosis and prognosis, not definitive genetic test |
Familial Forms
There are currently no well-established familial or hereditary forms described in the literature.
Additional Information
N/A
Links
N/A
References
- ↑ 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 1.16 1.17 1.18 1.19 1.20 1.21 1.22 Daniels, Jay; et al. (2020-04-14). "Cellular origins and genetic landscape of cutaneous gamma delta T cell lymphomas". Nature Communications. 11 (1): 1806. doi:10.1038/s41467-020-15572-7. ISSN 2041-1723. PMC 7156460 Check
|pmc=value (help). PMID 32286303 Check|pmid=value (help). - ↑ Azimpouran, Mahzad; et al. (2024-12-01). "Rapidly Progressive Primary Cutaneous Gamma Delta T-Cell Lymphoma With FYN Gene Alteration". The American Journal of Dermatopathology. 46 (12): e120–e123. doi:10.1097/DAD.0000000000002856. ISSN 1533-0311. PMID 39412302 Check
|pmid=value (help). - ↑ 3.0 3.1 Fadl, Amr; et al. (2023-09). "Primary cutaneous gamma/delta T-cell lymphoma with simultaneous JAK2 and TP63 rearrangements: a new double-hit?". Histopathology. 83 (3): 492–495. doi:10.1111/his.14973. ISSN 1365-2559. PMC 10524708 Check
|pmc=value (help). PMID 37308177 Check|pmid=value (help). Check date values in:|date=(help) - ↑ 4.0 4.1 4.2 Küçük, Can; et al. (2015-01-14). "Activating mutations of STAT5B and STAT3 in lymphomas derived from γδ-T or NK cells". Nature Communications. 6: 6025. doi:10.1038/ncomms7025. ISSN 2041-1723. PMC 7743911 Check
|pmc=value (help). PMID 25586472. - ↑ 5.0 5.1 Zhang, Yue; et al. (2025-04-15). "Addiction of primary cutaneous γδ T cell lymphomas to JAK/STAT signaling". The Journal of Clinical Investigation. 135 (8): e180417. doi:10.1172/JCI180417. ISSN 1558-8238. PMC 11996904 Check
|pmc=value (help). PMID 40231467 Check|pmid=value (help). - ↑ 6.0 6.1 6.2 6.3 6.4 Zhang, Ping; et al. (2020-11-07). "Epigenetic alterations and advancement of treatment in peripheral T-cell lymphoma". Clinical Epigenetics. 12 (1): 169. doi:10.1186/s13148-020-00962-x. ISSN 1868-7083. PMC 7648940 Check
|pmc=value (help). PMID 33160401 Check|pmid=value (help). - ↑ 7.0 7.1 7.2 Ahmed, Nada; et al. (2020-02). "Targeting epigenetic regulators in the treatment of T-cell lymphoma". Expert Review of Hematology. 13 (2): 127–139. doi:10.1080/17474086.2020.1711732. ISSN 1747-4094. PMC 7110907 Check
|pmc=value (help). PMID 31903826. Check date values in:|date=(help) - ↑ Hara, Natsumi; et al. (2022-03-24). "Epigenetics of Cutaneous T-Cell Lymphomas". International Journal of Molecular Sciences. 23 (7): 3538. doi:10.3390/ijms23073538. ISSN 1422-0067. PMC 8998216 Check
|pmc=value (help). PMID 35408897 Check|pmid=value (help).
Notes
*Citation of this Page: Azimpouran M, Kitahara S. “Primary cutaneous gamma/delta T-cell lymphoma”. Compendium of Cancer Genome Aberrations (CCGA), Cancer Genomics Consortium (CGC), updated 01/6/2026, https://ccga.io/index.php/HAEM5:Primary_cutaneous_gamma/delta_T-cell_lymphoma.
*Primary authors will typically be those that initially create and complete the content of a page. If a subsequent user modifies the content and feels the effort put forth is of high enough significance to warrant listing in the authorship section, please contact the Associate Editor or other CCGA representative. When pages have a major update, the new author will be acknowledged at the beginning of the page, and those who contributed previously will be acknowledged below as a prior author.
Prior Author(s): N/A