CI lead: Professor Shyamali Dharmage, Allergy and Lung Function Unit, Melbourne School of Population and Global Health

Team members: Dr Jennifer Perret, A/Professor Shuai Li, Professor Melissa Southey, Dr Don Vicendese, Dr Jingwen Zhang

Awarded: $100,000 in GERA’s Grant Round 1 (2025)

About the project: Lung cancer remains the leading cause of cancer death globally and is the primary cause of death among all Australian aged 65-74.¹ The disease is broadly categorized into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), with adenocarcinoma, a subtype of NSCLC, accounting for 40% of cases and showing an increasing trend.² Early-onset lung cancer is a devastating diagnosis that strikes individuals during their most productive years, typically resulting in premature death due to late-stage detection when treatments are largely ineffective.

In response to the high mortality rate, Australia has recently commenced the National Lung Cancer Screening Program, offering targeted screening to high-risk individuals aged 50-70 who undertake a risk assessment using the PLCOm2012 model.³ However, due to this arbitrary cut-off at 50 years, younger individuals at high-risk for early-onset lung cancer are not captured.

Genome-wide association studies (GWAS) have identified 46 susceptibility loci, with 23 of these occurring across all lung cancer subtypes.⁴  Polygenic risk scores (PRS) may enhance lung cancer (LC) risk assessment beyond clinical risk factors,^5,6 with the best published LC-PRS derived using UK Biobank (UKB) data.⁶ A recent meta-PRS for incident LC using UKB data similarly showed independent discriminatory ability (C-index 0.58) ⁷ with PRSs of non-genetic LC-risk factors incorporating sentinel variants from the largest GWASs in Europeans to date.⁸ Functional post-GWAS studies have provided insights into the biological implications of several LC-associated loci, from smoking behaviour to DNA repair.⁴ An exploratory GWAS in Chinese adults identified 4 SNPs, associated with early-onset LC.⁹ However, a comprehensive risk model integrating genetic and clinical factors for predicting early-onset lung cancer is still lacking.

This project will leverage the familial Tasmanian Longitudinal Health Study (TAHS) initiated in 1968, comprising ~8500 probands, ~17,000 siblings, and ~22,000 parents of northern European ancestry; >55% being smokers. This project will apply the best published LC-PRS ⁶ to the whole exome sequencing and genome-wide SNP array data of TAHS probands. The new risk model for predicting early-onset LC will be developed using UKB data, tested in TAHS, to investigate genetics/familial history, host and environmental predictors and their interactions.

Aim 1: To link the familial Tasmanian Longitudinal Health Study (TAHS) cohort to the Australian Institute of Health and Welfare’s Australian Cancer Database to derive all cancer outcomes, focusing on ‘early-onset’ lung cancer (diagnosed before age 60).

Aim 2: To leverage TAHS’s unique seven-decade follow-up data on probands, siblings, and parents to describe the genomic, host, and environmental features of early-onset lung cancer.

Aim 3: Using UK Biobank data, to develop a novel risk prediction model for “young” individuals aged 40-55 years, validated in TAHS, that could potentially extend the eligibility age criteria of the National Lung Cancer Screening Program (NLCSP).

References:

1. Australian Institute of Health and Welfare (AIHW). Deaths in Australia. Last updated Apr 9, 2025. https://wwwaihwgovau/reports/life-expectancy-deaths/deaths-in-australia/contents/leading-causes-of-death.
2. Zappa C, Mousa SA. Non-small cell lung cancer: current treatment and future advances. Transl Lung Cancer Res 2016; 5(3): 288-300.
3. Tammemagi MC, Katki HA, Hocking WG, et al. Selection criteria for lung-cancer screening. N Engl J Med 2013; 368(8): 728-36.
4. Long E, Patel H, Byun J, Amos CI, Choi J. Functional studies of lung cancer GWAS beyond association. Hum Mol Genet 2022; 31(R1): R22-R36.
5. Lebrett MB, Smith MJ, Crosbie EJ, et al. Validation of lung cancer polygenic risk scores in a high-risk case-control cohort. Genet Med 2023; 25(8): 100882.
6. Jia G, Lu Y, Wen W, et al. Evaluating the Utility of Polygenic Risk Scores in Identifying High-Risk Individuals for Eight Common Cancers. JNCI Cancer Spectr 2020; 4(3): pkaa021.
7. Ma Z, Zhu Z, Pang G, et al. Development and validation of a lung cancer polygenic risk score incorporating susceptibility variants for risk factors. Int J Cancer 2025; 156(5): 953-63.
8. McKay JD, Hung RJ, Han Y, et al. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes. Nat Genet 2017; 49(7): 1126-32.
9. Fan J, Hong T, Zhao X, et al. A two-stage genome-wide association study identified four potential early-onset nonsmall cell lung cancer risk loci based on 26,652 participants in Chinese population. Mol Carcinog 2023; 62(9): 1263-70.

---

Go back to: