Lung cancer is the leading cause of cancer-related death worldwide, largely due to late detection, when treatment options are limited. Detecting the disease earlier and tailoring treatments more precisely are essential to improve survival and quality of life for patients.
In a new thesis from Karolinska Institutet, Weiwei Bian , PhD student at the Department of Medical Epidemiology and Biostatistics , attempts to advance precision oncology in lung cancer by integrating epidemiological risk identification with cutting-edge molecular diagnostics.
What are the most important results in your thesis?
"My thesis includes studies on the development of new sequencing technologies and computational algorithms that markedly improve the sensitivity of ctDNA detection (i.e., circulating tumor DNA), enabling earlier diagnosis and more reliable monitoring of minimal residual disease and relapse. We have also quantified how interstitial lung disease (ILD) elevates subsequent lung-cancer risk and outlined strategies to identify and monitor high-risk individuals. Taken together, we show that combining risk prediction, ultra-sensitive detection, and biomarker-guided therapy may help reduce the burden of lung cancer eventually."
Why did you become interested in this topic?
"Because lung cancer is a paradox: it's the most diagnosed and deadliest cancer (when combined gender) globally, yet it has one of the best-documented biomarker landscapes. That contrast - high burden but clear molecular clues - convinced me that better technology and research could shift clinical outcomes: detecting disease earlier with ctDNA, resolving cryptic fusions that shape heterogeneity, and turning real-world findings from Swedish registers into a continuous feedback loop for clinical care. In short, it's the area where methodological advances can rapidly translate into earlier diagnoses and more precisely guided treatments."
What do you think should be done in future research?
"I think we should continue combining the innovation of molecular diagnostic techniques with the power of large-scale Swedish registers, by enabling the ultra-sensitive mutation detection and fusion profiling for cancer patients to early detection and individualized therapy. Adopting this integrated approach will be critical to saving more lives and improving the long-term outlook for patients."
