Screening for lung cancer using low-dose computed tomography: concerns about the application in low-risk individuals

An Artificial Intelligence (AI)-Integrated Approach to Enhance Early Detection and Personalized Treatment Strategies in Lung Cancer Among Smokers: A Literature Review

Lung cancer (LC) is a significant global health issue, particularly among smokers, and is characterized by high rates of incidence and mortality. This comprehensive review offers detailed insights into the potential of artificial intelligence (AI) to revolutionize early detection and personalized treatment strategies for LC. By critically evaluating the limitations of conventional methodologies, we emphasize the innovative potential of AI-driven risk prediction models and imaging analyses to enhance diagnostic precision and improve patient outcomes. Our in-depth analysis of the current state of AI integration in LC care highlights the achievements and challenges encountered in real-world applications, thereby shedding light on practical implementation. Furthermore, we examined the profound implications of AI on treatment response, survival rates, and patient satisfaction, addressing ethical considerations to ensure responsible deployment. In the future, we will outline emerging technologies, anticipate potential barriers to their adoption, and identify areas for further research, emphasizing the importance of collaborative efforts to fully harness the transformative potential of AI in reshaping LC therapy. Ultimately, this review underscores the transformative impact of AI on LC care and advocates for a collective commitment to innovation, collaboration, and ethical stewardship in healthcare.

Risk Assessment of Early Lung Cancer with LDCT and Health Examinations

Early detection of lung cancer has a higher likelihood of curative treatment and thus improves survival rate. Low-dose computed tomography (LDCT) screening has been shown to be effective for high-risk individuals in several clinical trials, but has high false positive rates. To evaluate the risk of stage I lung cancer in the general population not limited to smokers, a retrospective study of 133 subjects was conducted in a medical center in Taiwan. Regularized regression was used to build the risk prediction model by using LDCT and health examinations. The proposed model selected seven variables related to nodule morphology, counts and location, and ten variables related to blood tests and medical history, achieving an area under the curve (AUC) value of 0.93. The higher the age, white blood cell count (WBC), blood urea nitrogen (BUN), diabetes, gout, chronic obstructive pulmonary disease (COPD), other cancers, and the presence of spiculation, ground-glass opacity (GGO), and part solid nodules, the higher the risk of lung cancer. Subjects with calcification, solid nodules, nodules in the middle lobes, more nodules, and diseases related to thyroid, liver, and digestive systems were at a lower risk. The selected variables did not indicate causation.

Diagnosis of pulmonary nodules by DNA methylation analysis in bronchoalveolar lavage fluids

BACKGROUND

Lung cancer is the leading cause of cancer-related mortality. The alteration of DNA methylation plays a major role in the development of lung cancer. Methylation biomarkers become a possible method for lung cancer diagnosis.

RESULTS

We identified eleven lung cancer-specific methylation markers (CDO1, GSHR, HOXA11, HOXB4-1, HOXB4-2, HOXB4-3, HOXB4-4, LHX9, MIR196A1, PTGER4-1, and PTGER4-2), which could differentiate benign and malignant pulmonary nodules. The methylation levels of these markers are significantly higher in malignant tissues. In bronchoalveolar lavage fluid (BALF) samples, the methylation signals maintain the same differential trend as in tissues. An optimal 5-marker model for pulmonary nodule diagnosis (malignant vs. benign) was developed from all possible combinations of the eleven markers. In the test set (57 tissue and 71 BALF samples), the area under curve (AUC) value achieves 0.93, and the overall sensitivity is 82% at the specificity of 91%. In an independent validation set (111 BALF samples), the AUC is 0.82 with a specificity of 82% and a sensitivity of 70%.

CONCLUSIONS

This model can differentiate pulmonary adenocarcinoma and squamous carcinoma from benign diseases, especially for infection, inflammation, and tuberculosis. The model's performance is not affected by gender, age, smoking history, or the solid components of nodules.

The Current Understanding Of Asbestos-Induced Epigenetic Changes Associated With Lung Cancer

Asbestos is a naturally occurring mineral consisting of extremely fine fibres that can become trapped in the lungs after inhalation. Occupational and environmental exposures to asbestos are linked to development of lung cancer and malignant mesothelioma, a cancer of the lining surrounding the lung. This review discusses the factors that are making asbestos-induced lung cancer a continuing problem, including the extensive historic use of asbestos and decades long latency between exposure and disease development. Genomic mutations of DNA nucleotides and gene rearrangements driving lung cancer are well-studied, with biomarkers and targeted therapies already in clinical use for some of these mutations. The genes involved in these mutation biomarkers and targeted therapies are also involved in epigenetic mechanisms and are discussed in this review as it is hoped that identification of epigenetic aberrations in these genes will enable the same gene biomarkers and targeted therapies to be used. Currently, understanding of how asbestos fibres trapped in the lungs leads to epigenetic changes and lung cancer is incomplete. It has been shown that oxidoreduction reactions on fibre surfaces generate reactive oxygen species (ROS) which in turn damage DNA, leading to genetic and epigenetic alterations that reduce the activity of tumour suppressor genes. Epigenetic DNA methylation changes associated with lung cancer are summarised in this review, and some of these changes will be due to asbestos exposure. So far, little research has been carried out to separate the asbestos driven epigenetic changes from those due to non-asbestos causes of lung cancer. Asbestos-associated lung cancers exhibit less methylation variability than lung cancers in general, and in a large proportion of samples variability has been found to be restricted to promoter regions. Epigenetic aberrations in cancer are proving to be promising biomarkers for diagnosing cancers. It is hoped that further understanding of epigenetic changes in lung cancer can result in useful asbestos-associated lung cancer biomarkers to guide treatment. Research is ongoing into the detection of lung cancer epigenetic alterations using non-invasive samples of blood and sputum. These efforts hold the promise of non-invasive cancer diagnosis in the future. Efforts to reverse epigenetic aberrations in lung cancer by epigenetic therapies are ongoing but have not yet yielded success.

Lung cancer screening with low-dose spiral computed tomography: evidence from a pooled analysis of two Italian randomized trials

The benefits and harms of lung cancer (LC) screening with low-dose computed tomography (LDCT) are debatable. Positive results from the US National Lung Screening Trial were not evident in the European trials, possibly due to their smaller sample sizes. To address this issue, we conducted a patient-level pooled analysis of two Italian randomized controlled trials. Data from DANTE and MILD trials were combined for a total of 3640 individuals in the LDCT arm and 2909 in the control arm. LC and overall mortality were analyzed using multivariate hazard ratios (HRs) and log-rank tests stratified by study. The median follow-up was 8.2 years, with a total of 30 480 person-years in the LDCT arm and 22 157 in the control arm. A total of 192 patients developed LC in the LDCT arm and 105 in the control arm. Half of the LC cases in the LDCT arm had stage IA or IB cancer, as compared with 21% in the control arm. Overall mortality rates/100 000 person-years were 925 in the LDCT arm and 1074 in the control arm, and LC mortality rates were 299 and 357, respectively. The multivariate pooled overall mortality HR was 0.89 (95% confidence interval: 0.74-1.06) and the LC mortality HR was 0.83 (95% confidence interval: 0.61-1.12) for the LDCT arm as compared with the control arm. The present pooled analysis shows a nonsignificant 11% reduction in overall mortality in individuals undergoing LDCT screening as compared with the control arm. A pooled analysis of all European trials would be a useful contribution to assess the real benefit of LDCT screening.

Association of Smoking with Metabolic Volatile Organic Compounds in Exhaled Breath

Lung cancer (LC) screening will be more efficient if it is applied to a well-defined high-risk population. Characteristics including metabolic byproducts may be taken into account to access LC risk more precisely. Breath examination provides a non-invasive method to monitor metabolic byproducts. However, the association between volatile organic compounds (VOCs) in exhaled breath and LC risk or LC risk factors is not studied. Exhaled breath samples from 122 healthy persons, who were given routine annual exam from December 2015 to December 2016, were analyzed using thermal desorption coupled with gas chromatography mass spectrometry (TD-GC-MS). Smoking characteristics, air quality, and other risk factors for lung cancer were collected. Univariate and multivariate analyses were used to evaluate the relationship between VOCs and LC risk factors. 7, 7, 11, and 27 VOCs were correlated with smoking status, smoking intensity, years of smoking, and depth of inhalation, respectively. Exhaled VOCs are related to smoking and might have a potential to evaluate LC risk more precisely. Both an assessment of temporal stability and testing in a prospective study are needed to establish the performance of VOCs such as 2,5-dimethylfuranm and 4-methyloctane as lung cancer risk biomarkers.

DNA Methylation as a Noninvasive Epigenetic Biomarker for the Detection of Cancer

In light of the high incidence and mortality rates of cancer, early and accurate diagnosis is an important priority for assigning optimal treatment for each individual with suspected illness. Biomarkers are crucial in the screening of patients with a high risk of developing cancer, diagnosing patients with suspicious tumours at the earliest possible stage, establishing an accurate prognosis, and predicting and monitoring the response to specific therapies. Epigenetic alterations are innovative biomarkers for cancer, due to their stability, frequency, and noninvasive accessibility in bodily fluids. Epigenetic modifications are also reversible and potentially useful as therapeutic targets. Despite this, there is still a lack of accurate biomarkers for the conclusive diagnosis of most cancer types; thus, there is a strong need for continued investigation to expand this area of research. In this review, we summarise current knowledge on methylated DNA and its implications in cancer to explore its potential as an epigenetic biomarker to be translated for clinical application. We propose that the identification of biomarkers with higher accuracy and more effective detection methods will enable improved clinical management of patients and the intervention at early-stage disease.

Necessity of organized low-dose computed tomography screening for lung cancer: From epidemiologic comparisons between China and the Western nations

OBJECTIVES

To compare the proportion of stage I lung cancer and population mortality in China to those in U.S. and Europe where lung cancer screening by low-dose computed tomography (LDCT) has been already well practiced.

METHODS

The proportions of stage I lung cancer in LDCT screening population in U.S. and Europe were retrieved from NLST and NELSON trials. The general proportion of stage I lung cancer in China was retrieved from a rapid meta-analysis, based on a literature search in the China National Knowledge Infrastructure database. The lung cancer mortality and prevalence of China, U.S. and Europe was retrieved from Globocan 2012 fact sheet. Mortality-to-prevalence ratio (MPR) was applied to compare the population survival outcome of lung cancer.

RESULTS

The estimated proportion of stage I lung cancer in China is merely 20.8% among hospital-based cross-sectional population, with relative ratios (RRs) being 2.40 (95% CI 2.18-2.65) and 2.98 (95% CI 2.62-3.38) compared by LDCT-screening population in U.S. and Europe trials, respectively. MPR of lung cancer is as high as 58.9% in China, with RRs being 0.46 (95% CI 0.31-0.67) and 0.58 (95% CI 0.39-0.85) compared by U.S. and Europe, respectively.

CONCLUSIONS

By the epidemiological inference, the LDCT mass screening might be associated with increasing stage I lung cancer and therefore improving population survival outcome. How to translate the experiences of lung cancer screening by LDCT from developed counties to China in a cost-effective manner needs to be further investigated.