Martin L. Miller

This study identifies immunogenomic drivers of acquired resistance to immunotherapy across multiple cancer types using a large-scale clinicogenomic dataset.

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

The paper analyzes whole-genome sequencing data from melanoma metastases to show that branched evolution is common and that subclonal heterogeneity is prevalent in metastatic melanoma.

This study benchmarks six cell estimation tools and introduces ConsensusTME, which performs consistently well across multiple cancer-related benchmarks.

This study develops CT-based texture analysis to quantify intra- and inter-site tumor heterogeneity in HGSOC and shows it correlates with progression-free survival.

The paper identifies copy number aberrations that alter kinase signaling and highlights potential therapeutic targets by integrating genomic and proteomic data across cancer samples.

The paper quantifies neoantigen depletion in cancer genomes and finds negligible depletion signals, suggesting weak or absent immunogenic negative selection.

This paper introduces nTEP barcoding to spatially resolve tumour clones and their interactions with the microenvironment using multiplexed antibody imaging.