Lymphoma Diagnosis and Treatment

This paper uses machine learning to classify B cell lymphomas based on BCR repertoire sequencing, achieving high accuracy in distinguishing between subtypes.

This study uses Deep Visual Proteomics to analyze proteomic profiles in composite Hodgkin and small lymphocytic lymphomas, identifying subtype-specific treatment strategies.

This study shows CD20 stabilizes CD37 on B-cell lymphoma cells, affecting anti-CD37 therapy efficacy, but not CAR-T cell effectiveness.

This study identifies sex-specific genetic variants associated with lymphoma subtypes and oestrogen levels, revealing shared biological pathways influenced by oestrogen.

The paper analyzes sequencing data from gastric MALT lymphoma patients to identify genetic mutations, gene fusions, and microbiome changes associated with H. pylori infection and disease progression.

This study identifies mutations in the IgG heavy chain in follicular lymphoma and EZB DLBCL that enhance BCR signalling and oncogenicity by disrupting the IgG intracellular tail.

The paper models BCR signaling in B cell lymphoma cells to identify conserved network structures and crosstalk mechanisms.

This study shows that targeting PSGL-1 with an antibody induces apoptosis in lymphoma cells and inhibits tumorigenesis in some models.

This study identifies HERV-K as a therapeutic target in DLBCL, develops a humanized nanobody with anti-lymphoma activity, and shows its potential through antibody-dependent cytotoxicity.

The paper reanalyzes Reddy et al.'s 2017 DLBCL study, revealing discrepancies in mutation detection and outcome associations that render their findings non-replicable.

This study uses ultra-deep exome sequencing to identify recurrent mutations in classical Hodgkin lymphoma HRS cells, demonstrating its utility for analyzing genomic variants in large patient cohorts.

The paper uses single-cell sequencing to study the evolution of follicular lymphoma and its microenvironment during transformation, finding gene programs and TME changes associated with progression.

This study identifies subtype-specific and co-occurring genetic alterations across major B-NHL subtypes using targeted sequencing of 380 genes in 685 tumors.

The paper constructs an IPI-based immune prognostic model for DLBCL using gene expression data, showing high-risk patients have shorter survival and higher potential response to ICB therapy.

This study identifies genetic and pathologic features of t(14;18)-negative diffuse follicular lymphoma, showing recurrent 16p13 and 1p36 deletions, CREBBP and STAT6 mutations, and co-mutations.

This study identifies genetic drivers of mantle cell lymphoma through exome and genome sequencing, revealing novel mutations in genes involved in RNA splicing and regulation.

This study uses whole genome sequencing to identify potential familial Hodgkin lymphoma predisposing genes in three families, finding a novel DICER1 variant in one family.

This study uses ctDNA analysis to identify genetic mutations and monitor residual disease in NK/T lymphoma patients, finding KMT2D mutations correlate with poor prognosis and treatment response.

The paper identifies TCF4 overexpression driven by 18q21.2 gains as a mechanism promoting IgM expression in ABC-like DLBCL and shows BET inhibitors can suppress it.

This study investigates the relationship between c-MYC gene SNPs and Burkitt’s lymphoma formation using bioinformatics analysis of 286 SNPs, identifying eight potentially disease-causing variants.

This study identifies somatic coding and regulatory variants in DLBCL, revealing novel mechanisms of oncogene deregulation and potential therapeutic targets.

The paper identifies molecular overlaps between malaria and Burkitt’s lymphoma and links artemisinin derivatives to shared pathways that could inform their anticancer potential.