Compendium of Cancer Genome Aberrations

Primary cutaneous gamma/delta T-cell lymphoma

Revision as of 22:17, 6 January 2026 by Sumire.Kitahara (talk | contribs) (→Gene Rearrangements)


Haematolymphoid Tumours (WHO Classification, 5th ed.)

(General Instructions – The focus of these pages is the clinically significant genetic alterations in each disease type. This is based on up-to-date knowledge from multiple resources such as PubMed and the WHO classification books. The CCGA is meant to be a supplemental resource to the WHO classification books; the CCGA captures in a continually updated wiki-stye manner the current genetics/genomics knowledge of each disease, which evolves more rapidly than books can be revised and published. If the same disease is described in multiple WHO classification books, the genetics-related information for that disease will be consolidated into a single main page that has this template (other pages would only contain a link to this main page). Use HUGO-approved gene names and symbols (italicized when appropriate), HGVS-based nomenclature for variants, as well as generic names of drugs and testing platforms or assays if applicable. Please complete tables whenever possible and do not delete them (add N/A if not applicable in the table and delete the examples); to add (or move) a row or column in a table, click nearby within the table and select the > symbol that appears. Please do not delete or alter the section headings. The use of bullet points alongside short blocks of text rather than only large paragraphs is encouraged. Additional instructions below in italicized blue text should not be included in the final page content. Please also see Author_Instructions and FAQs as well as contact your Associate Editor or Technical Support.)

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

Put your text here and fill in the table (Instructions: Includes aberrations not involving gene rearrangements. Details on clinical significance such as prognosis and other important information can be provided in the notes section. Can refer to CGC workgroup tables as linked on the homepage if applicable. Please include references throughout the table. Do not delete the table.)

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
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]
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]
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]
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]
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.
Focal deletion: ARID1A Loss unspecified (del/trunc) ARID1A P No Deleted in ~28% of cases. Indicates epigenetic/chromatin modifier pathway involvement[1]
Focal deletion: FAS Loss unspecified (biallelic) FAS P No Deletion in ~22% of cases. Loss of apoptosis regulator; may contribute to immune‑escape[1]
Focal deletion: PDCD1 Loss unspecified PDCD1 P No Deletion in ~22% of cases. Immune checkpoint gene loss; potential therapeutic‑escape mechanism[1]

Characteristic Chromosomal or Other Global Mutational Patterns

Put your text here and fill in the table (Instructions: Included in this category are alterations such as hyperdiploid; gain of odd number chromosomes including typically chromosome 1, 3, 5, 7, 11, and 17; co-deletion of 1p and 19q; complex karyotypes without characteristic genetic findings; chromothripsis; microsatellite instability; homologous recombination deficiency; mutational signature pattern; etc. Details on clinical significance such as prognosis and other important information can be provided in the notes section. Please include references throughout the table. Do not delete the table.)

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)

Put your text here and fill in the table (Instructions: This table is not meant to be an exhaustive list; please include only genes/alterations that are recurrent or common as well either disease defining and/or clinically significant. If a gene has multiple mechanisms depending on the type or site of the alteration, add multiple entries in the table. For clinical significance, denote associations with FDA-approved therapy (not an extensive list of applicable drugs) and NCCN or other national guidelines if applicable; Can also refer to CGC workgroup tables as linked on the homepage if applicable as well as any high impact papers or reviews of gene mutations in this entity. Details on clinical significance such as prognosis and other important information such as concomitant and mutually exclusive mutations can be provided in the notes section. Please include references throughout the table. Do not delete the table.)

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

Put your text here

Genes and Main Pathways Involved

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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

Put your text here (Instructions: Include recommended testing type(s) to identify the clinically significant genetic alterations.)

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

NA

Links

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References

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Notes

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Prior Author(s):


*Citation of this Page: “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.

  1. ↑ 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).
  2. ↑ 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. ↑ 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. ↑ 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. ↑ 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. ↑ 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. ↑ 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)
  8. ↑ 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).
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