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Updated: May 7, 2026

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VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
Published on: December 28, 2015
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Single Cell Resolution Tracking of Cutaneous T-Cell Lymphoma Reveals Clonal Evolution in Disease Progression
Biorxiv : the Preprint Server for Biology
|February 24, 2025
Summary
This study reveals key molecular changes driving cutaneous T-cell lymphoma (CTCL) progression, identifying mutations in CCR4, PI3K, PD-1, and STAT3 pathways. These findings offer new targets for treating this challenging cancer.
Area of Science:
- Oncology
- Genomics
- Immunology
Background:
- Cutaneous T-cell lymphoma (CTCL) is a heterogeneous, therapy-resistant cancer with relentless progression.
- Multi-omics technologies offer precise insights into disease dynamics and treatment response.
Purpose of the Study:
- To comprehensively map the clonal evolution of CTCL using multi-omics data.
- To identify molecular underpinnings of CTCL progression at single-cell resolution.
- To discover novel biomarkers and therapeutic targets for CTCL.
Main Methods:
- Integrated analysis of exome, whole genome, epigenome, bulk, and single-cell (sc) VDJ/RNA sequencing from 114 patient samples.
- Single-cell resolution analysis of CTCL clonal evolution.
- CUT&RUN-seq to investigate STAT3 mutation effects on gene regulation.
Main Results:
- Identified recurrent genomic alterations associated with CTCL progression, including mutations in CCR4, PI3K signaling, and PD-1 checkpoint pathways.
- Discovered a STAT3 (D661Y) gain-of-function mutation enhancing Rho GTPase pathway gene binding.
- Found significant mutations in chromatin methylation modifiers (e.g., EZH2), suggesting EZH1/2 inhibition as a potential therapy.
Conclusions:
- CTCL progression involves complex clonal evolution driven by specific genomic alterations and pathway dysregulation.
- Rho GTPase pathway dysregulation and chromatin modifier mutations play critical roles in CTCL advancement.
- These molecular insights can guide improved disease monitoring, clinical trial design, and therapeutic strategies for CTCL.

