Lung cancer remains a major public health challenge as the second most common cancer in both sexes and the leading cause of cancer-related deaths worldwide, accounting for approximately 1.8 million fatalities in 2022. Typically, around 70% of lung cancer patients are diagnosed at an advanced stage, with five-year survival rates dismal at 5 to 15%. Current screening protocols primarily recommend annual low-dose computed tomography (LDCT) for adults aged 50-80 years who have a 20 pack-year history of smoking, as smoking is the predominant risk factor.

However, the incidence of lung cancer in never-smokers has doubled over the past decade, and the reasons behind this shift remain largely unexplained. Additionally, the high incidence of false positives in LDCT screenings, affecting up to 40% of all screened individuals, significantly undermines its efficacy. This highlights the urgent need for robust biomarker-based methods to more accurately identify individuals at high risk who may not normally qualify for screening and to more safely manage screening intervals for lower-risk groups.

This Research Topic aims to explore and validate potential diagnostic biomarkers such as autoantibodies, proteins, miRNA, DNA methylation, and circulating tumor nucleic acids from various sources like blood, nasal epithelia, sputum, and bronchoalveolar lavage. These biomarkers could revolutionize lung cancer screening by improving accuracy and risk stratification.

To gather further insights into the realms of biomarker reliability and utility, we welcome articles addressing, but not limited to, the following themes:
Novel biomarkers for lung cancer risk stratification
Comparative analyses of biomarkers versus LDCT
Advancements in non-invasive sampling techniques
The role of emerging biomarkers in improving diagnostic accuracy
The integration of biomarkers into current clinical workflows

Please note: Submissions should contain empirical validation through independent clinical cohorts or in vivo/in vitro biological studies. Studies based solely on bioinformatic or computational analyses without such validations are not considered for publication in this Research Topic.

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Frontiers in Oncology

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