Utilising "Omics" Technologies
TRACKER will, for the first time, provide the critical sample numbers and clinical follow-up necessary for extensive multidisciplinary biological investigations. This will result in significant advancements in knowledge of lung cancer biology and treatment.
Why "Omics"
New high-throughput technologies have enabled a vast number of molecular measurements to be able to be captured within tissue or cells. Applying multiple technologies simultaneously (multi-omics) to our lung cancer biospecimens and linking them with clinical follow-up data will provide a comprehensive view of the underlying biology at an unprecedented resolution.
Key multi-omic methods used in TRACKER include:
Flow Cytometry
Identifies and analyses multiple physical and biological characteristics of cells. It will be used to assess the abundance of various immune cells, identify novel targets for combination therapies, and detect markers of drug resistance.
Single-Cell Sequencing
Enables the simultaneous quantification of cell surface proteins and RNA gene expression within a single-cell readout. Using EBUS samples, changes in cell composition between immunotherapy responders and non-responders will be identified.
Metagenomics
A comprehensive DNA-based approach to profile microbial diversity and interactions. Sequencing bronchoalveolar fluid from lung cancer patients will identify microbial communities associated with therapy resistance.
Circulating Tumour DNA Analysis
Identifies genomic regions with DNA methylation, which can silence genes. Longitudinally collected blood samples from lung cancer patients will be used to detect methylation patterns associated with treatment resistance.
Metabolomics
The study of chemical processes involving metabolites—the substrates, intermediates, and products of cell metabolism. Bronchoalveolar fluid will be analysed to assess bacterial metabolic activity and its impact on treatment response.
Whole Exome Sequencing
Using next-generation sequencing, this analysis will characterise mutations in protein-coding regions, focusing on treatment resistance and clinically actionable alterations in EBUS lung cancer tissue samples.