Sherlock-lung

Sherlock-Lung is a comprehensive study, set to include 2,000 never-smoking lung cancer samples, that aims to trace the etiology of the disease in never smokers by analyzing genomic data in tumour and surrounding lung tissue. Whole genome sequencing, whole transcriptome, genome-wide methylation, and microbiome data are being analyzed to characterize the genomic landscape of lung cancer in never smokers (LCINS) and to identify exogenous and endogenous processes involved in lung tumourigenesis. Analysis of the tumour cells of origin, normal-to-tumour evolution, and tumour microenvironment will be conducted in a subgroup of the cases also using single/oligo cell sequencing approaches. The molecular landscape will be integrated with histological and radiological features to develop a more refined classification of LCINS and provide insights into prognosis and treatment strategies.

The Wedge group’s contributions to the project include tumour evolution analysis and artificially intelligent sample clustering.

To date, publications related to the Sherlock-lung project include:

Genomic and evolutionary classification of lung cancer in never smokers - Zhang et al. https://doi.org/10.1038/s41588-021-00920-0

Tracing Lung Cancer Risk Factors Through Mutational Signatures in Never-Smokers : The Sherlock-Lung Study - Landi et al. https://doi.org/10.1093/aje/kwaa234

Chris Wirth
Chris Wirth
Postdoctoral Research Associate / Computational Biologist
Nurnadiah Zamri
Nurnadiah Zamri
Visiting Postdoctoral Researcher
David Wedge
David Wedge
Professor of Cancer Genomics and Data Science

My research interests include cancer genomics, tumour evolution, data science and machine learning.

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