Tom Lesluyes

This study uses single-cell and spatial multi-omics to analyze a malignant peripheral nerve sheath tumor, revealing chromosomal instability drives phenotypic diversity and spatial-temporal evolution.

The paper identifies coordinated neoantigen-specific CD8 T cell responses as key predictors of PD-(L)1 therapy efficacy in non-small cell lung cancer patients.

This study uses whole-exome sequencing and single-cell DNA sequencing to analyze subclonal evolution in breast cancer during aromatase inhibitor treatment, identifying resistance mechanisms and actionable targets.

The paper benchmarks structural variant callers in cancer genomics and recommends a consensus approach combining Delly, GRIDSS, Manta, and SvABA for improved performance.

This paper develops a framework to predict future oncogene amplification or tumour suppressor deletion in cancer using genomic data, achieving an average AUC of 0.87.

This study shows brush biopsies can accurately reflect the genomic profile of oral premalignant lesions and their progression to OSCC, capturing most SNVs and CNAs comparable to tissue biopsies.

The paper develops CliPP to estimate subclonal mutation load (sML) and shows it predicts survival and immunotherapy response in cancers with low to moderate TMB.

This paper introduces GRITIC, a method to time genomic gains in tumors, finding that copy number gains often accumulate after genome duplication.

The paper investigates the evolution of chromosome 4p loss in basal breast cancer, identifying C4orf19 as a novel gene that suppresses proliferation and is part of a kinase module.

The paper presents a genetic model of central chondrosarcoma using genomic and epigenomic data to identify mutations and methylation patterns associated with patient outcomes.

CliPP reconstructs subclonal architecture in cancer DNA sequencing data efficiently and accurately, outperforming existing methods in speed while maintaining high concordance with consensus calls.