A. Tsirigos

Connecting Chromatin Structures to Gene Regulation Using Dynamic Polymer Simulations

The paper uses polymer simulations to model chromatin dynamics and shows that productive interactions depend on contact frequency, capture radius, and duration, not just average contact matrices.

The expression profile and tumorigenic mechanisms of CD97 (ADGRE5) in glioblastoma render it a targetable vulnerability

This study identifies CD97 as a targetable vulnerability in glioblastoma through its role in tumor metabolism and signaling, supported by transcriptomic, proteomic, and functional analyses.

MetFinder: a neural network-based tool for automated quantitation of metastatic burden in histological sections from animal models

MetFinder uses a deep neural network to automate metastasis burden quantification in histological sections from mouse models, improving throughput and resolution compared to current methods.

Tumor-intrinsic LKB1-LIF signaling axis establishes a myeloid niche to promote immune evasion and tumor growth

This study identifies a LKB1-LIF signaling axis in tumors that promotes immune evasion by reprogramming myeloid cells, and shows that inhibiting LIF signaling reduces tumor growth.

MethNet: a robust approach to identify regulatory hubs and their distal targets in cancer

MethNet identifies regulatory hubs and their distal targets in cancer by integrating DNA methylation and gene expression data to uncover cis regulatory elements linked to patient survival.

Glutamine antagonist DRP-104 suppresses tumor growth and enhances response to checkpoint blockade in KEAP1 mutant lung cancer

This study shows that DRP-104, a glutamine antagonist, suppresses KEAP1 mutant lung tumor growth and enhances response to checkpoint blockade by inhibiting glutamine metabolism and improving T cell function.

Single-Cell RNA Sequencing Reveals the Effects of Chemotherapy on Human Pancreatic Adenocarcinoma and its Tumor Microenvironment

This study uses single-cell RNA sequencing to analyze how chemotherapy affects PDAC tumor cells and their microenvironment, finding limited transcriptional shifts and reduced TIGIT-mediated immune checkpoint activity.

Genome-wide analysis of dendritic cell differentiation

This study uses a genome-wide CRISPR/Cas9 screen to identify regulators of dendritic cell differentiation in a Flt3L-dependent murine progenitor cell line.

NSD2 E1099K drives relapse in pediatric acute lymphoblastic leukemia by disrupting 3D chromatin organization

This study shows NSD2 E1099K mutation disrupts 3D chromatin organization in B-ALL, leading to drug resistance and clonal evolution through compartmentalization changes.

KEAP1 mutation in lung adenocarcinoma promotes immune evasion and immunotherapy resistance

This study shows KEAP1 mutations in lung adenocarcinoma lead to immune evasion by reducing dendritic cell and T cell responses, contributing to immunotherapy resistance.

Ontogeny and Vulnerabilities of Drug-Tolerant Persisters in HER2+ Breast Cancer

This study identifies drug-tolerant persisters (DTPs) in HER2+ breast cancer and reveals their origins and vulnerabilities to TKI resistance.

A CRISPR Screen Identifies Myc-associated Zinc Finger Protein (MAZ) as an Insulator Functioning at CTCF boundaries in Hox Clusters

The paper identifies MAZ as an insulator functioning at CTCF boundaries in Hox clusters, contributing to genomic architecture during differentiation.

A Deep Learning Approach for Rapid Mutational Screening in Melanoma

This paper develops a deep learning model to detect BRAF mutations in melanoma histopathology images using whole slide images from 256 patients, achieving AUC scores of 0.96 and 0.72.

Dynamic 3D chromosomal landscapes in acute leukemia

The paper examines 3D chromatin changes in T-ALL, identifies TAD fusion events linked to oncogene activation, and shows drug treatments can restore some interactions.

Efficient pan-cancer whole-slide image classification and outlier detection using convolutional neural networks

This paper introduces a simplified CNN architecture for efficient pan-cancer whole-slide image classification and outlier detection.

Classification and Mutation Prediction from Non-Small Cell Lung Cancer Histopathology Images using Deep Learning

This study uses deep learning to classify lung cancer subtypes and predict gene mutations from histopathology images, achieving high accuracy and outperforming human pathologists.