Forest M. White

The paper identifies bottlenecks in MHC-I antigen presentation by Mtb, showing that only a small fraction of predicted binders are actually presented, and develops computational models to improve prediction.

The paper identifies E-sensors, HLA-E-restricted CD8+ T cells that recognize increased self-VL9/HLA-E, mediating immunoregulation and antiviral responses in HIV control.

The paper introduces INSIGHT, a platform for phosphoproteomic analysis of rare cell subpopulations, and applies it to study signaling changes in disseminated glioblastoma cells in vivo.

This study identifies persistent interferon signaling and clonal expansion as early events in NDMA-induced liver cancer by analyzing molecular changes in mice.

This study identifies cell-intrinsic phosphotyrosine signaling patterns that limit tyrosine kinase inhibitor efficacy in cancer cell lines.

The paper identifies cross-presented tumor antigens in glioblastoma and shows that targeting these antigens with mRNA vaccines improves anti-tumor immunity.

This study identifies cell competition as a key driver of gliomagenesis by showing that pre-malignant OPCs outcompete wildtype cells, and inhibiting this process reduces tumor growth.

This paper introduces a yeast surface display pipeline to screen for class I peptide MHC binders across multiple alleles and applies it to pathogen proteomes to identify potential T cell antigens.

The paper shows that Mycobacterium tuberculosis uses its ESX-1 secretion system to present antigens on MHC-I, bypassing host pathways like autophagy.

This study evaluates a PTPRJ-targeting peptide agonist's effects on lung cancer cells, revealing broad signaling changes, DNA damage, and growth inhibition.

This study uses a multi-omics approach to analyze early TMZ responses in GBM cells, identifying TMZ-associated peptide antigens and immune-related changes.

This study identifies MHC-II antigens from Mycobacterium tuberculosis using mass spectrometry and evaluates mRNA vaccine immunogens to enhance T cell recognition.

PathMHC improves identification of pathogen-derived MHC peptides for vaccine targets by combining computational analysis with targeted mass spectrometry.

The paper investigates early signaling and transcriptional changes in melanoma cells under BRAF inhibitor treatment, identifying SFK activation as a compensatory mechanism and demonstrating its sensitivity to co-inhibition.

This study shows that CDK9 degradation with KI-CDK9d-32 is more effective than inhibition in disrupting MYC transcriptional networks and causes MYC downregulation and nucleolar destabilization.

The paper identifies and validates tyrosine phosphorylation sites on metabolic enzymes using parallel phosphoproteomics and metabolomics in MCF10A cells.

This study identifies sex-specific metabolic reprogramming in obesity by analyzing phosphorylation sites on metabolic enzymes and their functional impact.

This study shows Src kinase is upregulated and phosphorylated in Alzheimer's disease, interacts with Tau, and may be a therapeutic target.

The paper introduces msiPL, a deep learning model for analyzing MSI data, enabling efficient non-linear visualization and identification of biologically relevant patterns.

This study uses quantitative phosphoproteomics to identify dysregulated kinase networks associated with Alzheimer's disease histopathologies.

The paper quantifies tyrosine phosphorylation in FFPE tissues to reveal patient-specific signaling networks and identifies oncogenic kinases in cancer tumors.

The paper uses phosphoproteomics to identify Siglec-F and Siglec-8 as upregulated in microglia during neurodegeneration, driving inflammatory responses in mouse and human models.