Epidemiological studies are important to understand the aetiology of disease-causative and associated factors that influence disease incidence and progression, which require large international cohorts and collection of detailed personal data and outcomes. The Roy Castle Lung Cancer Research Programme, through the Liverpool Lung Project, contributes to studies run under the umbrella of the International Lung Cancer Consortium (ILCCO: https://ilcco.iarc.fr/ ) and the International Association for Research on Cancer (IACR), e.g. the SYNERGY project, a pooled analysis of case-control studies on the joint effects of occupational carcinogens in the development of lung cancer. We also continue to utilise the LLP epidemiology data to generate new risk models or examine factors associated with lung cancer incidence.
Genetic Risk Factors
Similarly, when looking at genetic risk factors (variations in a person’s DNA that influence disease) we work with the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium. For example, we contributed to major Genome Wide Association Studies (GWAS) that identified novel genetic variants contributing to an increased risk of lung cancer. More recently, we are part to the OncoArray project looking at genetic risk in the largest cross-cancer genetic analysis to date (McKay et al., Nature Genetics 2017, 49(7):1126-1132 ).
As part of the CURELUNG project and the Clinical Lung Cancer Genome Project, Next Generation Sequencing (NGS) has revealed the mutational profiles of cancers collected as part of LLP and these have been used to help generate new histo-molecular classifications for different types of lung cancer (Fernandez-Cuesta et al., Nature Communications 2014, 5:3518 , Clinical Lung Cancer Genome Project & Network Genomic Medicine, Science Translational Medicine 2013, 5(209):209ra153 ).
NGS mutational profiling has also been applied to FFPE tumour samples and to circulating tumour DNA in blood plasma.
Epigenetic changes associated with lung cancer [e.g. DNA methylation, microRNAs (miRNA) and long non-coding RNA (lncRNA)] are a rich source of biomarkers for lung cancer detection, diagnosis and prognosis. For example:
· A panel of DNA methylation biomarkers has been shown to improve the accuracy lung cancer diagnosis based on bronchial lavage cytology (Nikolaidis et al., Cancer Research 2012, 72(22):5692-5701 ).
· A microRNA signature, detectable in small quantities of biopsy material can differentiate between tumour and normal tissue to help identify NSCLC (Bediaga et al., British Journal of Cancer 2013, 109(9):2404-2411 ).
· A prognostic DNA methylation signature was identified for stage I Non-Small Cell Lung Cancer (Sandoval et al., Journal of Clinical Oncology 2013, 31(32):4140-4147 )
· A study of lncRNA in lung cancer indicated frequent dysregulationin Non-small Cell Lung Cancer (Acha-Sagredo et al., British Journal of Cancer 2020, 122(7):1050-1058