Benjamin Izar

This study identifies genomic features, particularly copy-number alterations, that predict metastatic progression in melanoma and defines a six-gene signature associated with relapse.

This study uses spatial transcriptomics and lineage tracing to show how tumor subclones drive microenvironmental changes that promote metastasis in a mouse model.

This study maps human natural killer cell development in tonsil using single-cell analysis, showing spatial trajectories and tissue niches that support NK cell differentiation.

This study shows that targeting CD73-A2aR adenosine signaling with radiotherapy and checkpoint inhibitors improves tumor control by overcoming radioresistance and enhancing antitumor immunity.

This study identifies endothelial ICAM-1 as a regulator of T-cell exclusion in melanoma by spatially polarizing its expression, and shows that blocking ICAM-1 enhances T-cell infiltration and immunotherapy efficacy.

This study shows FAK promotes metastasis in BRAF-mutant melanoma through kinase-dependent mechanisms downstream of PTEN, suggesting FAK inhibition could improve treatment outcomes.

This study shows that chromosomal instability in esophageal adenocarcinoma drives an inflammatory tumor microenvironment through a cGAS-chemokine-myeloid axis, with CXCL8 as a key mediator.

This study shows PKMYT1 inhibition causes DNA damage and enhances anti-PD-1 therapy in CCNE1-amplified gastroesophageal adenocarcinoma.

The paper identifies co-expression patterns of chemokine receptors on CD8+ T cells that distinguish anti-tumor efficacy from off-target toxicity in melanoma.

The paper shows that the PBAF complex in melanoma facilitates REST occupancy at repressive chromatin, leading to upregulation of synaptic transcripts when ARID2 is mutated.

This study identifies CNDP1 as a metabolic vulnerability in brain metastasis, showing its inhibition suppresses metastasis and its expression confers metastatic potential.

This study creates a single-nucleus and spatial transcriptomic atlas of the COVID-19 liver, revealing cellular and functional disruptions associated with organ damage.

Echidna quantifies gene dosage effects on phenotypic plasticity by integrating scRNA-seq and WGS data to separate genetic from cell non-autonomous mechanisms.

The paper identifies shared transcriptomic features between melanoma brain metastases and neurodegenerative diseases, highlighting key genes and providing an open-source tool for analysis.

micronuclAI automates micronuclei quantification to assess chromosomal instability, achieving near-human performance on cancer cell line images.

Smoother integrates positional information into non-spatial models for spatial omics data, enabling accurate imputation, deconvolution, and dimensionality reduction in simulated and real datasets.

KINOMO improves the analysis of single-cell RNA-seq data by recovering intra- and inter-tumoral heterogeneity through non-negative matrix factorization, outperforming existing methods in benchmarking.

This study develops a method for single-cell and whole-genome sequencing of frozen clinical specimens, demonstrating its utility in analyzing tumor evolution and rare disease biospecimens.

This study identifies transcriptional states in mCRPC that mediate treatment resistance, including AR splicing heterogeneity, TGF-β signaling, and immune infiltration patterns.

The paper uses Perturb-CITE-Seq to identify novel immune evasion mechanisms in cancer by analyzing multi-modal single-cell data from patient-derived models.

The paper develops a toolbox for scRNA-Seq and snRNA-Seq of fresh and frozen human tumors, testing it across eight tumor types and optimizing protocols for different tissue characteristics.