Ari M. Melnick

MALT1 protease inhibition restrains glioblastoma progression by reversing tumor-associated macrophage-dependent immunosuppression

This study shows that inhibiting MALT1 protease in glioblastoma-associated macrophages reduces immunosuppression and tumor growth by reprogramming macrophages to an M1-like phenotype.

Spatial Proteomics Reveals Dual-Compartment Immune Evasion Architecture and Core Lymphomagenic Stromal Niches in Follicular Lymphoma

This study uses spatial proteomics to reveal immune evasion mechanisms in follicular lymphoma, identifying VISTA and CD14-high follicular dendritic cells as therapeutic targets.

Transcriptome sequencing of Hodgkin lymphoma Hodgkin and Reed-Sternberg cells reveals escape from NK cell recognition and an unfolded protein response

This study identifies unique transcriptional features of Hodgkin lymphoma HRS cells, including immune evasion mechanisms and an unfolded protein response, distinguishing them from other B-cell lymphomas.

Enhanced efficacy of a specific HDAC3 inhibitor in combination with 5-Azacitidine against diffuse large B-cell lymphoma

This study shows that combining a HDAC3 inhibitor with 5-Azacitidine enhances anti-tumor effects against DLBCL in vitro and in vivo, with reduced toxicity compared to single agents.

Signaling induced biophysical disruption of repressed chromatin domains drives immune cell fate

The paper identifies H3 serine 28 phosphorylation as a mechanism driving chromatin derepression and immune cell fate transitions by disrupting repressive chromatin domains.

Mutant EZH2 alters the epigenetic network and increases epigenetic heterogeneity in B cell lymphoma

This study investigates how mutant EZH2 affects the epigenetic network in B cell lymphomas, showing it increases epigenetic heterogeneity and dominates over KMT2D mutations.

Deep dynamical models of single-cell multiomic velocities predict loss-of-function and rescue perturbations in B cells

PAIRWISE: Deep Learning-based Prediction of Effective Personalized Drug Combinations in Cancer

PAIRWISE predicts effective personalized drug combinations in cancer using deep learning and transcriptome data, achieving high AUROC scores in validation tests.

ChromaFold predicts the 3D contact map from single-cell chromatin accessibility

ChromaFold predicts 3D chromatin contact maps from scATAC-seq data, outperforming bulk-based methods and enabling cell-type-specific interaction analysis.

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

This study uses rapid diagnostics and metatranscriptomics to analyze SARS-CoV-2 infection, revealing viral evolution, host responses, and drug interactions in NYC samples.

The SEQC2 Epigenomics Quality Control (EpiQC) Study: Comprehensive Characterization of Epigenetic Methods, Reproducibility, and Quantification

The paper evaluates epigenetic methods using reference materials, finding high concordance between assays and differences in performance across platforms.