Prognostic and Early Detection Biomarkers for Lung Diseases

Ells Nobles^*
*Correspondence: Ells Nobles, Division of Thoracic Surgery, IRCCS San Raffaele Scientific Institute, Milan, Italy, Email:

Introduction

Lung diseases represent a major global health burden, encompassing a wide range of conditions such as Chronic Obstructive Pulmonary Disease (COPD), Interstitial Lung Disease (ILD), pulmonary fibrosis, asthma and lung cancer. Early detection and accurate prognosis are essential for improving patient outcomes, as many of these diseases progress silently until advanced stages. Traditional diagnostic methods, such as imaging and lung function tests, often detect disease only after significant structural or functional impairment has occurred. In recent years, molecular, genetic and cellular biomarkers have emerged as promising tools for both early detection and prognostic evaluation. These biomarkers provide critical insights into disease pathogenesis, help identify high-risk individuals and support personalized therapeutic strategies [1].

Description

In the realm of lung cancer, biomarkers have played a pivotal role in shifting clinical practice toward precision medicine. Circulating tumor DNA (ctDNA), exosomal microRNAs and specific protein signatures are being investigated as tools for detecting malignancies at early stages. For example, epidermal growth factor receptor (EGFR) mutations and ALK rearrangements not only aid in diagnosis but also predict therapeutic response to targeted agents. Liquid biopsies, which analyze ctDNA or circulating tumor cells from blood samples, offer a minimally invasive approach for disease monitoring and prognostication. These biomarkers are particularly valuable in detecting minimal residual disease and relapse, guiding timely therapeutic interventions. Prognostic markers such as PD-L1 expression further help predict immunotherapy outcomes, enabling tailored treatment plans for patients with lung cancer [2].

In Chronic Obstructive Pulmonary Disease (COPD), biomarkers are increasingly recognized as essential for identifying disease phenotypes and progression risks. Traditional spirometry remains useful but insufficient in capturing the heterogeneity of COPD. Biomarkers such as fibrinogen, C - reactive protein (CRP) and Surfactant Protein D (SP-D) have been linked to systemic inflammation and lung tissue injury. Elevated levels of fibrinogen, for example, are associated with higher mortality and exacerbation frequency, making it a candidate for prognostic evaluation. Blood eosinophil counts have also gained prominence as predictive markers for corticosteroid responsiveness in COPD patients. By integrating such biomarkers into clinical practice, physicians can move beyond generalized treatment approaches and instead employ personalized management strategies aimed at reducing exacerbations and disease progression [3].

Interstitial Lung Diseases (ILDs), particularly Idiopathic Pulmonary Fibrosis (IPF), highlight the urgent need for reliable prognostic and diagnostic biomarkers. Circulating markers such as KL-6, surfactant protein A (SP-A) and SP-D have been studied extensively, with elevated levels correlating with disease activity and progression. Genetic biomarkers, including mutations in the MUC5B promoter and telomerase-related genes, are strongly associated with susceptibility and prognosis in IPF. Imaging-based biomarkers derived from High-Resolution Computed Tomography (HRCT) combined with molecular data further enhance predictive accuracy. These tools enable clinicians to detect disease before significant lung scarring occurs, facilitating early initiation of antifibrotic therapy. Importantly, prognostic biomarkers in ILD also help stratify patients for clinical trials and therapeutic decision-making, ensuring optimal use of available treatments [4].

Beyond individual disease categories, several cross-cutting biomarkers have shown potential across multiple lung conditions. For example, microRNAs (miRNAs) regulate gene expression involved in inflammation, fibrosis and carcinogenesis, making them promising candidates for broad biomarker panels. Circulating extracellular vesicles (EVs) and metabolomic signatures are emerging as innovative biomarkers with the potential to capture the complexity of lung pathophysiology. Proteomic and transcriptomic profiling allows for multi-biomarker signatures that can distinguish between overlapping conditions such as COPD and asthma or between benign and malignant pulmonary nodules. The integration of artificial intelligence and machine learning with biomarker data is also enhancing predictive accuracy, allowing for earlier and more reliable detection. These advances highlight a paradigm shift from single biomarker approaches toward multi-omics strategies for precision lung disease management [5].

Conclusion

Biomarkers for early detection and prognosis in lung diseases hold transformative potential in reshaping clinical care. From ctDNA and PD-L1 expression in lung cancer to KL-6 and MUC5B mutations in pulmonary fibrosis and fibrinogen or eosinophil counts in COPD, these tools provide valuable insights into disease onset, progression and therapeutic responsiveness. As technologies such as liquid biopsy, high-throughput sequencing and multi-omics platforms advance, the accuracy and clinical applicability of biomarkers will continue to expand. Future research should focus on validating biomarker panels in large, diverse populations and integrating them into routine practice to enable earlier diagnosis, better risk stratification and personalized interventions. Ultimately, the development and application of robust prognostic and detection biomarkers represent a crucial step toward reducing morbidity and mortality associated with lung diseases worldwide.

Acknowledgement

None.

Conflict of Interest

None.

References

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