Nicholas W. Bateman

The paper identifies CLDN3 as a tumor-selective target in SCLC using proteogenomic analysis and validates its therapeutic potential with a monoclonal antibody.

ShapeUpLMD automates ROI optimization for laser microdissection, improving tumor purity and spatial accuracy in multi-omic tissue profiling.

This study uses proteogenomics to identify ancestry-specific and shared molecular drivers in prostate cancer, revealing distinct biological programs and improving risk prediction.

The paper identifies conserved protein alterations and elevated MUC16 in low-grade serous ovarian cancers through quantitative proteomics and validation across multiple datasets.

This study maps the SCLC tumor microenvironment and identifies cancer-associated fibroblasts as key drivers of neuroendocrine state plasticity and poor prognosis.

ProteoMixture estimates cell type proportions in bulk tissue proteomics data using optimized protein signatures validated on high-grade serous ovarian cancer samples.

The paper describes a modified dual preparatory method to improve RNA yield from laser microdissected human cancer tissue samples.

This study examines the relationship between genetic ancestry, somatic mutation frequency, and histologic subtypes in high-grade endometrial cancer, finding associations between local ancestry and tumor mutation burden and histologic subtypes.

This paper standardizes a proteotype analysis workflow across multiple international sites to enable distributed, reproducible proteomic data generation for precision medicine.