Baseline computed tomography screening and blood microRNA predict lung cancer risk and define adequate intervals in the BioMILD trial

Current and future therapies for small cell lung carcinoma

Small cell lung cancer (SCLC) is an aggressive malignancy characterized by rapid proliferation and high metastatic potential. It is characterized by universal inactivation of and RB1, overexpression of the MYC family and dysregulation of multiple oncogenic signaling pathways. Among different patients, SCLCs are similar at the genetic level but exhibit significant heterogeneity at the molecular level. The classification of SCLC has evolved from a simple neuroendocrine (NE)/non-neuroendocrine (non-NE) classification system to a transcription factor-based molecular subtype system; lineage plasticity adds further complexity and poses challenges for therapeutic development. While SCLC is initially sensitive to platinum-based chemotherapy, resistance develops rapidly, leading to a dismal prognosis. Various antibodies, including PD-1/PD-L1 inhibitors and antibody‒drug conjugates, have been introduced into clinical practice or are being evaluated in clinical trials. However, their therapeutic benefits for SCLC patients remain limited. This review summarizes SCLC carcinogenic mechanisms, tumor heterogeneity, and the immune microenvironment of SCLC, with a focus on recent advances in metastasis and resistance mechanisms. Additionally, the corresponding clinical progress in tackling these challenges is discussed.

Development of a miRNA-Based Model for Lung Cancer Detection

BACKGROUND

Lung cancer is the leading cause of cancer-related mortality globally, with late-stage diagnoses contributing to poor survival rates. While lung cancer screening with low-dose computed tomography (LDCT) has proven effective in reducing mortality among heavy smokers, its limitations, including high false-positive rates and resource intensiveness, restrict widespread use. Liquid biopsy, particularly using microRNA (miRNA) biomarkers, offers a promising adjunct to current screening strategies. This study aimed to evaluate the predictive power of a panel of serum miRNA biomarkers for lung cancer detection.

PATIENTS AND METHODS

A case-control study was conducted at two tertiary hospitals, enrolling 82 lung cancer cases and 123 controls. We performed an extensive literature review to shortlist 25 candidate miRNAs, of which 16 showed a significant two-fold increase in expression compared to the controls. Machine learning techniques, including Random Forest, K-Nearest Neighbors, Neural Networks, and Support Vector Machines, were employed to identify the top six miRNAs. We then evaluated predictive models, incorporating these biomarkers with lung nodule characteristics on LDCT.

RESULTS

A prediction model utilising six miRNA biomarkers (mir-196a, mir-1268, mir-130b, mir-1290, mir-106b and mir-1246) alone achieved area under the curve (AUC) values ranging from 0.78 to 0.86, with sensitivities of 70-78% and specificities of 73-85%. Incorporating lung nodule size significantly improved model performance, yielding AUC values between 0.96 and 0.99, with sensitivities of 92-98% and specificities of 93-98%.

CONCLUSIONS

A prediction model combining serum miRNA biomarkers and nodule size showed high predictive power for lung cancer. Integration of the prediction model into current lung cancer screening protocols may improve patient outcomes.

Multiplex digital PCR for the simultaneous quantification of a miRNA panel

BACKGROUND

microRNAs (miRNAs) are small non-coding RNAs regulating gene expression. They have attracted significant interest as biomarkers for early diagnosis, prediction and monitoring of treatment response in many diseases. As individual miRNAs often lack the required sensitivity and specificity, miRNA signatures are developed for clinical applications. Digital PCR (dPCR) is a sensitive fluorescent-based quantification method, that can be used to detect the expression of miRNAs in patient samples. Our study presents the first proof-of-concept of a multiplexed dPCR assay for the simultaneous analysis and quantification of multiple miRNAs.

RESULTS

After reverse transcription (RT) using a pool of miRNA-specific stem-loop primers, dPCR was performed with a universal reverse primer and miRNA-specific forward primers along with fluorescently-labelled hydrolysis probes. Multiple experimental parameters were evaluated and strategies for modulating the observed signals were devised. The optimised assay was applied to the analysis of miRNAs from cell lines and biological samples. Although absolute quantification was lost, due to the reverse transcription step, quantification was linear for the dilution series and results were highly reproducible for independent dPCR and RT reactions. Our results confirmed the high sensitivity of dPCR for patient samples.

CONCLUSIONS

We demonstrate the feasibility and reliability of multiplexed detection and quantification of miRNAs by dPCR that can be applied in a clinical setting to evaluate miRNA signatures.

Coronary calcium score and emphysema extent on different CT radiation dose protocols in lung cancer screening

OBJECTIVES

To assess the consistency of automated measurements of coronary artery calcification (CAC) burden and emphysema extent on computed tomography (CT) images acquired with different radiation dose protocols in a lung cancer screening (LCS) population.

MATERIALS AND METHODS

The patient cohort comprised 361 consecutive screenees who underwent a low-dose CT (LDCT) scan and an ultra-low-dose CT (ULDCT) scan at an incident screening round. Exclusion criteria for CAC measurements were software failure and previous history of CVD, including coronary stenting, whereas for emphysema assessment, software failure only. CT images were retrospectively analyzed by a fully automated AI software for CAC scoring, using three predefined Agatston score categories (0-99, 100-399, and ≥ 400), and emphysema quantification, using the percentage of low attenuation areas (%LAA). Demographic and clinical data were obtained from the written questionnaire completed by each participant at the first visit. Agreement for CAC and %LAA categories was measured by the k-Cohen Index with Fleiss-Cohen weights (Kw) and Intraclass Correlation Coefficient (ICC) with 95% Confidence Interval (CI).

RESULTS

An overlap of CAC strata was observed in 275/327 (84%) volunteers, with an almost perfect agreement (Kw = 0.86, 95% CI 0.82-0.90; ICC = 0.86, 95% CI 0.79-0.90), while an overlap of %LAA strata was found in 204/356 (57%) volunteers, with a moderate agreement (Kw = 0.57, 95% CI 0.51-0.63; ICC = 0.57, 95% CI 0.21-0.75).

CONCLUSION

Automated CAC quantification on ULDCT seems feasible, showing similar results to those obtained on LDCT, while the quantification of emphysema tended to be overestimated on ULDCT images.

KEY POINTS

Question Evidence demonstrating that coronary artery calcification and emphysema can be automatedly quantified on ultra-low-dose chest CT is still awaited. Findings Coronary artery calcification and emphysema measurements were similar among different CT radiation dose protocols; their automated quantification is feasible on ultra-low-dose CT. Clinical relevance Ultra-low-dose CT-based LCS might offer an opportunity to improve the secondary prevention of cardiovascular and respiratory diseases through automated quantification of both CAC burden and emphysema extent.

Calls to action on lung cancer management and research

Lung cancer, the leading cause of cancer-related deaths globally, remains a pressing health issue despite significant medical advances. The New York Lung Cancer Foundation brought together experts from academia, the pharmaceutical and biotech industries as well as organizational leaders and patient advocates, to thoroughly examine the current state of lung cancer diagnosis, treatment, and research. The goal was to identify areas where our understanding is incomplete and to develop collaborative public health and scientific strategies to generate better patient outcomes, as highlighted in our "Calls to Action." The consortium prioritized 8 different calls to action. These include (1) develop strategies to cure more patients with early-stage lung cancer, (2) investigate carcinogenesis leading to lung cancers in patients without a history of smoking, (3) harness precision medicine for disease interception and prevention, (4) implement solutions to deliver prevention measures and effective therapies to individuals in under-resourced countries, (5) facilitate collaborations with industry to collect and share data and samples, (6) create and maintain open access to big data repositories, (7) develop new immunotherapeutic agents for lung cancer treatment and prevention, and (8) invest in research in both the academic and community settings. These calls to action provide guidance to representatives from academia, the pharmaceutical and biotech industries, organizational and regulatory leaders, and patient advocates to guide ongoing and planned initiatives.

Lung cancer screening in India: Preparing for the future using smart tools & biomarkers to identify highest risk individuals

There is a growing burden of lung cancer cases in India, incidence projected to increase from 63,708 cases (2015) to 81,219 cases (2025). The increasing numbers are attributed to smoking (India currently has nearly 100 million adult smokers) and environmental pollution. Most patients present with advanced disease (80-85% are incurable), causing nearly 60,000 annual deaths from lung cancer. Early detection through lung cancer screening (LCS) can result in curative therapies for earlier stages of lung cancer and improved survival. Annual low-dose computerized tomography (LDCT) is the standard method for LCS. Usually, high-risk populations (age>50 yr and >20 pack-years of smoking) are considered for LCS, but even such focused screening may be challenging in resource-limited countries like India. However, developing a smart LCS programme with high yield may be possible by leveraging demographic and genomic data, use of smart tools, and judicious use of blood-based biomarkers. Developing this model over the next several years will facilitate a structured cancer screening programme for populations at the highest risk of lung cancer. In this paper, we discuss the demographics of lung cancer in India and its relation to smoking patterns. Further, we elaborate on the potential applications and challenges of bringing a smart approach to LCS in high-risk populations in India.

The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence

In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and explore the contributions of artificial intelligence (AI), in overcoming them. We focus on evaluating the initial (baseline) LDCT examination, which provides a wealth of information relevant to the screening participant's health. This includes the detection of large-size prevalent LC and small-size malignant nodules that are typically diagnosed as LCs upon growth in subsequent annual LDCT scans. Additionally, the baseline LDCT examination provides valuable information about smoking-related comorbidities, including cardiovascular disease, chronic obstructive pulmonary disease, and interstitial lung disease (ILD), by identifying relevant markers. Notably, these comorbidities, despite the slow progression of their markers, collectively exceed LC as ultimate causes of death at follow-up in LC screening participants. Computer-assisted diagnosis tools currently improve the reproducibility of radiologic readings and reduce the false negative rate of LDCT. Deep learning (DL) tools that analyze the radiomic features of lung nodules are being developed to distinguish between benign and malignant nodules. Furthermore, AI tools can predict the risk of LC in the years following a baseline LDCT. AI tools that analyze baseline LDCT examinations can also compute the risk of cardiovascular disease or death, paving the way for personalized screening interventions. Additionally, DL tools are available for assessing osteoporosis and ILD, which helps refine the individual's current and future health profile. The primary obstacles to AI integration into the LDCT screening pathway are the generalizability of performance and the explainability.

Dumbbell probe initiated multi-rolling circle amplification assisted CRISPR/Cas12a for highly sensitive detection of clinical microRNA

A novel miRNA detection technique named Dumbbell probe initiated multi-Rolling Circle Amplification assisted CRISPR/Cas12a (DBmRCA) was developed relying on the ligation-free dumbbell probe and the high-sensitivity CRISPR/Cas12a signal out strategy. This DBmRCA assay streamlines miRNA quantification within a mere 30-min timeframe and with exceptional analytical precision. The efficacy of this method was validated by assessing miRNA levels in clinical samples, revealing distinct expression panel of miR-200a and miR-126 in lung cancer/adjacent/normal tissue specimens. Moreover, a predictive model was established to classify benign and malignant tumor. Due to its time efficiency, enhanced sensitivity, and streamlined workflow, this assay would be a reliable tool for miRNA analysis in clinical settings, offering potential guidance for early diagnosis and treatment of lung cancer.

Blood microRNA testing in participants with suspicious low-dose CT findings: follow-up of the BioMILD lung cancer screening trial

Background

The proper management of suspicious radiologic findings is crucial to optimize the effectiveness of low-dose computed tomography (LDCT) lung cancer screening trials. In the BioMILD study, we evaluated the utility of combining a plasma 24-microRNA signature classifier (MSC) and LDCT to define the individual risk and personalize screening strategies. Here we aim to assess the utility of repeated MSC testing during annual screening rounds in 1024 participants with suspicious LDCT findings.

Methods

The primary outcome was two-year lung cancer incidence in relation to MSC test results, reported as relative risk (RR) with 95% confidence interval (CI). Lung cancer incidence and mortality were estimated using extended Cox models for time-dependent covariates, yielding the respective hazard ratios (HR). Clinicaltrials.gov ID: NCT02247453.

Findings

With a median follow-up of 8.5 years, the full study set included 1403 indeterminate LDCT (CTind) and 584 positive LDCT (CT+) results. A lung cancer RR increase in MSC+ compared to MSC- participants was observed in both the CTind (RR: 2.5; 95% CI: 1.4-4.32) and CT+ (RR: 2.6; 95% CI: 1.81-3.74) groups and was maintained when considering stage I or resectable tumors only. A 98% negative predictive value in CTind/MSC- and a 30% positive predictive value in CT+/MSC+ lesions were recorded. At seven years' follow-up, MSC+ participants had a cumulative HR of 4.4 (95% CI: 3.0-6.4) for lung cancer incidence and of 8.1 (95% CI: 2.7-24.5) for lung cancer mortality.

Interpretation

Our study shows that MSC can be reliably performed during LDCT screening rounds to increase the accuracy of lung cancer risk and mortality prediction and supports its clinical utility in the management of LDCT findings of uncertain malignancy.

Funding

Italian Association for Cancer Research; Italian Ministry of Health; Horizon2020; National Cancer Institute (NCI); Gensignia LifeScience.

Strengthening lung cancer screening in Europe: fostering participation, improving outcomes, and addressing health inequalities through collaborative initiatives in the SOLACE consortium

The Strengthening the Screening of Lung Cancer in Europe (SOLACE) initiative, supported by Europe's Beating Cancer Plan, is dedicated to advancing lung cancer screening. This initiative brings together the most extensive pan-European network of respiratory and radiology experts, involving 37 partners from 15 countries. SOLACE aims to enhance equitable access to lung cancer screening by developing targeted recruitment strategies for underrepresented and high-risk populations. Through comprehensive work packages, SOLACE integrates scientific research, pilot studies, and sustainability efforts to bolster regional and national screening efforts across EU member states. CRITICAL RELEVANCE STATEMENT: The SOLACE project aims to facilitate the optimization and implementation of equitable lung cancer screening programs across the heterogeneous healthcare landscape in EU member states. KEY POINTS: The effectiveness of lung cancer screening is supported by both scientific evidence and now increasing legislative support. SOLACE aims to develop, test, and disseminate tools to facilitate the realization of lung cancer screening at both a national and regional level. Previously underrepresented populations in lung cancer screening will be targeted by tailored recruitment strategies. SOLACE forms the first pan-European network of experts poised to drive real-world implementation of lung cancer screening.

CRISPR for companion diagnostics in low-resource settings

New point-of-care tests (POCTs), which are especially useful in low-resource settings, are needed to expand screening capacity for diseases that cause significant mortality: tuberculosis, multiple cancers, and emerging infectious diseases. Recently, clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostic (CRISPR-Dx) assays have emerged as powerful and versatile alternatives to traditional nucleic acid tests, revealing a strong potential to meet this need for new POCTs. In this review, we discuss CRISPR-Dx assay techniques that have been or could be applied to develop POCTs, including techniques for sample processing, target amplification, multiplex assay design, and signal readout. This review also describes current and potential applications for POCTs in disease diagnosis and includes future opportunities and challenges for such tests. These tests need to advance beyond initial assay development efforts to broadly meet criteria for use in low-resource settings.

Lung cancer screening in never smokers

PURPOSE OF REVIEW

Low-dose computed tomography (LDCT) lung cancer screening has been established in smokers, but its role in never smokers remains unclear. The differences in lung cancer biology between smokers and nonsmokers highlight the importance of a discriminated approach. This overview focuses on the emerging data and implementation challenges for LDCT screening in nonsmokers.

RECENT FINDINGS

The first LDCT screening study in nonsmokers enriched with risk factors demonstrated a lung cancer detection rate double that of the phase 3 trials in smokers. The relative risk of lung cancer detected by LDCT has also been found to be similar amongst female never smokers and male ever smokers in Asia. Majority of lung cancers detected through LDCT screening are stage 0/1, leading to concerns of overdiagnosis. Risk prediction models to enhance individual selection and nodule management could be useful to enhance the utility of LDCT screening in never smokers.

SUMMARY

With appropriate risk stratification, LDCT screening in never smokers may attain similar efficacy as compared to smokers. A global effort is needed to generate evidence surrounding optimal screening strategies, as well as health and economic benefits to determine the suitability of widespread implementation.

The Impact of Model Assumptions on Personalized Lung Cancer Screening Recommendations

BACKGROUND

Recommendations regarding personalized lung cancer screening are being informed by natural-history modeling. Therefore, understanding how differences in model assumptions affect model-based personalized screening recommendations is essential.

DESIGN

Five Cancer Intervention and Surveillance Modeling Network (CISNET) models were evaluated. Lung cancer incidence, mortality, and stage distributions were compared across 4 theoretical scenarios to assess model assumptions regarding 1) sojourn times, 2) stage-specific sensitivities, and 3) screening-induced lung cancer mortality reductions. Analyses were stratified by sex and smoking behavior.

RESULTS

Most cancers had sojourn times <5 y (model range [MR]; lowest to highest value across models: 83.5%-98.7% of cancers). However, cancer aggressiveness still varied across models, as demonstrated by differences in proportions of cancers with sojourn times <2 y (MR: 42.5%-64.6%) and 2 to 4 y (MR: 28.8%-43.6%). Stage-specific sensitivity varied, particularly for stage I (MR: 31.3%-91.5%). Screening reduced stage IV incidence in most models for 1 y postscreening; increased sensitivity prolonged this period to 2 to 5 y. Screening-induced lung cancer mortality reductions among lung cancers detected at screening ranged widely (MR: 14.6%-48.9%), demonstrating variations in modeled treatment effectiveness of screen-detected cases. All models assumed longer sojourn times and greater screening-induced lung cancer mortality reductions for women. Models assuming differences in cancer epidemiology by smoking behaviors assumed shorter sojourn times and lower screening-induced lung cancer mortality reductions for heavy smokers.

CONCLUSIONS

Model-based personalized screening recommendations are primarily driven by assumptions regarding sojourn times (favoring longer intervals for groups more likely to develop less aggressive cancers), sensitivity (higher sensitivities favoring longer intervals), and screening-induced mortality reductions (greater reductions favoring shorter intervals).

IMPLICATIONS

Models suggest longer screening intervals may be feasible and benefits may be greater for women and light smokers.

HIGHLIGHTS

Natural-history models are increasingly used to inform lung cancer screening, but causes for variations between models are difficult to assess.This is the first evaluation of these causes and their impact on personalized screening recommendations through easily interpretable metrics.Models vary regarding sojourn times, stage-specific sensitivities, and screening-induced lung cancer mortality reductions.Model outcomes were similar in predicting greater screening benefits for women and potentially light smokers. Longer screening intervals may be feasible for women and light smokers.

Lung cancer screening: where do we stand?

Lung cancer screening (LCS) programmes have emerged over recent years around the world. LCS programmes present differences in delivery, inclusion criteria and resource allocation. On a national scale, only a few LCS programmes have been fully established, but more are anticipated to follow. Evidence has shown that, in combination with a low-dose chest computed tomography scan, smoking cessation should be offered as part of a LCS programme for improved patient outcomes. Promising tools in LCS include further refined risk prediction models, the use of biomarkers, artificial intelligence and radiomics. However, these tools require further study and clinical validation is required prior to routine implementation.

Perspective on Management of Low-Dose Computed Tomography Findings on Low-Dose Computed Tomography Examinations for Lung Cancer Screening. From the International Association for the Study of Lung Cancer Early Detection and Screening Committee

Lung cancer screening using low-dose computed tomography (LDCT) carefully implemented has been found to reduce deaths from lung cancer. Optimal management starts with selection of eligibility criteria, counseling of screenees, smoking cessation, selection of the regimen of screening which specifies the imaging protocol, and workup of LDCT findings. Coordination of clinical, radiologic, and interventional teams and ultimately treatment of diagnosed lung cancers under screening determine the benefit of LDCT screening. Ethical considerations of who should be eligible for LDCT screening programs are important to provide the benefit to as many people at risk of lung cancer as possible. Unanticipated diseases identified on LDCT may offer important benefits through early detection of leading global causes of death, such as cardiovascular diseases and chronic obstructive pulmonary disease, as the latter may result from conditions such as emphysema and bronchiectasis, which can be identified early on LDCT. This report identifies the key components of the regimen of LDCT screening for lung cancer which include the need for a management system to provide data for continuous updating of the regimen and provides quality assurance assessment of actual screenings. Multidisciplinary clinical management is needed to maximize the benefit of early detection, diagnosis, and treatment of lung cancer. Different regimens have been evolving throughout the world as the resources and needs may be different, for countries with limited resources. Sharing of results, further knowledge, and incorporation of technologic advances will continue to accelerate worldwide improvements in the diagnostic and treatment approaches.

Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging

Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation. In the last decade, a number of countries have adopted population-based LCS as a public health recommendation. Albeit still incipient, discussion on this topic in Brazil is becoming increasingly broad and necessary. With the aim of increasing knowledge and stimulating debate on LCS, the Brazilian Society of Thoracic Surgery, the Brazilian Thoracic Association, and the Brazilian College of Radiology and Diagnostic Imaging convened a panel of experts to prepare recommendations for LCS in Brazil. The recommendations presented here were based on a narrative review of the literature, with an emphasis on large population-based studies, systematic reviews, and the recommendations of international guidelines, and were developed after extensive discussion by the panel of experts. The following topics were reviewed: reasons for screening; general considerations about smoking; epidemiology of LC; eligibility criteria; incidental findings; granulomatous lesions; probabilistic models; minimum requirements for LDCT; volumetric acquisition; risks of screening; minimum structure and role of the multidisciplinary team; practice according to the Lung CT Screening Reporting and Data System; costs versus benefits of screening; and future perspectives for LCS.

Study rationale and design of the PEOPLHE trial

PURPOSE

Lung cancer screening (LCS) by low-dose computed tomography (LDCT) demonstrated a 20-40% reduction in lung cancer mortality. National stakeholders and international scientific societies are increasingly endorsing LCS programs, but translating their benefits into practice is rather challenging. The "Model for Optimized Implementation of Early Lung Cancer Detection: Prospective Evaluation Of Preventive Lung HEalth" (PEOPLHE) is an Italian multicentric LCS program aiming at testing LCS feasibility and implementation within the national healthcare system. PEOPLHE is intended to assess (i) strategies to optimize LCS workflow, (ii) radiological quality assurance, and (iii) the need for dedicated resources, including smoking cessation facilities.

METHODS

PEOPLHE aims to recruit 1.500 high-risk individuals across three tertiary general hospitals in three different Italian regions that provide comprehensive services to large populations to explore geographic, demographic, and socioeconomic diversities. Screening by LDCT will target current or former (quitting < 10 years) smokers (> 15 cigarettes/day for > 25 years, or > 10 cigarettes/day for > 30 years) aged 50-75 years. Lung nodules will be volumetric measured and classified by a modified PEOPLHE Lung-RADS 1.1 system. Current smokers will be offered smoking cessation support.

CONCLUSION

The PEOPLHE program will provide information on strategies for screening enrollment and smoking cessation interventions; administrative, organizational, and radiological needs for performing a state-of-the-art LCS; collateral and incidental findings (both pulmonary and extrapulmonary), contributing to the LCS implementation within national healthcare systems.

Non-coding RNAs in disease: from mechanisms to therapeutics

Non-coding RNAs (ncRNAs) are a heterogeneous group of transcripts that, by definition, are not translated into proteins. Since their discovery, ncRNAs have emerged as important regulators of multiple biological functions across a range of cell types and tissues, and their dysregulation has been implicated in disease. Notably, much research has focused on the link between microRNAs (miRNAs) and human cancers, although other ncRNAs, such as long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), are also emerging as relevant contributors to human disease. In this Review, we summarize our current understanding of the roles of miRNAs, lncRNAs and circRNAs in cancer and other major human diseases, notably cardiovascular, neurological and infectious diseases. Further, we discuss the potential use of ncRNAs as biomarkers of disease and as therapeutic targets.

miR-Blood - a small RNA atlas of human blood components

miR-Blood is a high-quality, small RNA expression atlas for the major components of human peripheral blood (plasma, erythrocytes, thrombocytes, monocytes, neutrophils, eosinophils, basophils, natural killer cells, CD4+ T cells, CD8+ T cells, and B cells). Based on the purified blood components from 52 individuals, the dataset provides a comprehensive repository for the expression of 4971 small RNAs from eight non-coding RNA classes.

Emerging Strategies in Lung Cancer Screening: Blood and Beyond

BACKGROUND

Although low dose computed tomography (LDCT)-based lung cancer screening (LCS) can decrease lung cancer-related mortality among high-risk individuals, it remains an imperfect and substantially underutilized process. LDCT-based LCS may result in false-positive findings, which can lead to invasive procedures and potential morbidity. Conversely, current guidelines may fail to capture at-risk individuals, particularly those from under-represented minority populations. To address these limitations, numerous biomarkers have emerged to complement LDCT and improve early lung cancer detection.

CONTENT

This review focuses primarily on blood-based biomarkers, including protein, microRNAs, circulating DNA, and methylated DNA panels, in current clinical development for LCS. We also examine other emerging biomarkers-utilizing airway epithelia, exhaled breath, sputum, and urine-under investigation. We highlight challenges and limitations of biomarker testing, as well as recent strategies to integrate molecular strategies with imaging technologies.

SUMMARY

Multiple biomarkers are under active investigation for LCS, either to improve risk-stratification after nodule detection or to optimize risk-based patient selection for LDCT-based screening. Results from ongoing and future clinical trials will elucidate the clinical utility of biomarkers in the LCS paradigm.

Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities

Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.

Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer

Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting.

ERS International Congress 2023: highlights from the Thoracic Oncology Assembly

Lung cancer is the leading cause of cancer mortality in the world. It greatly affects the patients' quality of life, and is thus a challenge for the daily practice in respiratory medicine. Advances in the genetic knowledge of thoracic tumours' mutational landscape, and the development of targeted therapies and immune checkpoint inhibitors, have led to a paradigm shift in the treatment of lung cancer and pleural mesothelioma. During the 2023 European Respiratory Society Congress in Milan, Italy, experts from all over the world presented their high-quality research and reviewed best clinical practices. Lung cancer screening, management of early stages of lung cancer, application of artificial intelligence and biomarkers were discussed and they will be summarised here.

Increased expression of individual genes in whole blood is associated with late-stage lung cancer at and close to diagnosis

Lung cancer (LC) mortality rates are still increasing globally. As survival is linked to stage, there is a need to identify markers for earlier LC diagnosis and individualized treatment. The whole blood transcriptome of LC patients represents a source of potential LC biomarkers. We compared expression of > 60,000 genes in whole blood specimens taken from LC cases at diagnosis (n = 128) and controls (n = 62) using genome-wide RNA sequencing, and identified 14 candidate genes associated with LC. High expression of ANXA3, ARG1 and HP was strongly associated with lower survival in late-stage LC cases (hazard ratios (HRs) = 2.81, 2.16 and 2.54, respectively). We validated these markers in two independent population-based studies with pre-diagnostic whole blood specimens taken up to eight years prior to LC diagnosis (n = 163 cases, 184 matched controls). ANXA3 and ARG1 expression was strongly associated with LC in these specimens, especially with late-stage LC within two years of diagnosis (odds ratios (ORs) = 3.47 and 5.00, respectively). Additionally, blood CD4 T cells, NK cells and neutrophils were associated with LC at diagnosis and improved LC discriminative ability beyond candidate genes. Our results indicate that in whole blood, increased expression levels of ANXA3, ARG1 and HP are diagnostic and prognostic markers of late-stage LC.

Early Detection of Lung Cancer Using Small RNAs

INTRODUCTION

Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting.

METHODS

We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin.

RESULTS

We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling.

CONCLUSIONS

These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.

Long-term outcomes of lung cancer screening in males and females

BACKGROUND

This study explored female and male overall mortality and lung cancer (LC) survival in two LC screening (LCS) populations, focusing on the predictive value of coronary artery calcification (CAC) at baseline low-dose computed tomography (LDCT).

METHODS

This retrospective study analysed data of 6495 heavy smokers enrolled in the MILD and BioMILD LCS trials between 2005 and 2016. The primary objective of the study was to assess sex differences in all-cause mortality and LC survival. CAC scores were automatically calculated on LDCT images by a validated artificial intelligence (AI) software. Sex differences in 12-year cause-specific mortality rates were stratified by age, pack-years and CAC score.

RESULTS

The study included 2368 females and 4127 males. The 12-year all-cause mortality rates were 4.1 % in females and 7.7 % in males (p < 0.0001), and median CAC score was 8.7 vs. 41 respectively (p < 0.0001). All-cause mortality increased with rising CAC scores (log-rank test, p < 0.0001) for both sexes. Although LC incidence was not different between the two sexes, females had lower rates of 12-year LC mortality (1.0 % vs. 1.9 %, p = 0.0052), and better LC survival from diagnosis (72.3 % vs. 51.7 %; p = 0.0005), with a similar proportion of stage I (58.1 % vs. 51.2 %, p = 0.2782).

CONCLUSIONS

Our findings demonstrate that female LCS participants had lower rates of all-cause mortality at 12 years and better LC survival than their male counterparts, with similar LC incidence rates and stage at diagnosis. The lower CAC burden observed in women at all ages might contribute to explain their lower rates of all-cause mortality and better LC survival.

Liquid Biopsy as an Adjunct to Lung Screening Imaging

Current lung cancer screening protocols use low-dose computed tomography scans in selected high-risk individuals. Unfortunately, utilization is low, and the rate of false-positive screens is high. Peripheral biomarkers carry meaningful promise in diagnosing and monitoring cancer with added potential advantages reducing invasive procedures and improving turnaround time. Herein, the use of such blood-based assays is considered as an adjunct to further utilization and accuracy of lung cancer screening.

Lung Cancer Screening: The European Perspective

Several randomized and observational studies on lung cancer screening held in Europe significantly contributed to the knowledge on low-dose computed tomography screening targets in high-risk individuals with smoking history and older than 50 years. In particular, steps forward have been made in the field of risk modeling, screening interval, diagnostic protocol with volumetry, optimization, overdiagnosis estimation, oncological outcome, oncological risk due to radiation exposure, recruitment, and communication strategy.

Extracellular vesicles from subjects with COPD modulate cancer initiating cells phenotype through HIF-1α shuttling

Chronic obstructive pulmonary disease (COPD) is a risk factor for lung cancer development. COPD induces activation of hypoxia-induced signaling, causing remodeling of surrounding microenvironmental cells also modulating the release and cargo of their extracellular vesicles (EVs). We aimed to evaluate the potential role of circulating EVs from COPD subjects in lung cancer onset. Plasma-EVs were isolated by ultracentrifugation from heavy smoker volunteers with (COPD-EVs) or without (heavy smoker-EVs, HS-EV) COPD and characterized following MISEV guidelines. Immortalized human bronchial epithelial cells (CDK4, hTERT-HBEC3-KT), genetically modified with different oncogenic alterations commonly found in lung cancer (sh-p53, KRASV12), were used to test plasma-EVs pro-tumorigenic activity in vitro. COPD-EVs mainly derived from immune and endothelial cells. COPD-EVs selectively increased the subset of CD133+CXCR4+ metastasis initiating cells (MICs) in HBEC-sh-p53-KRASV12high cells and stimulated 3D growth, migration/invasion, and acquisition of mesenchymal traits. These effects were not observed in HBEC cells bearing single oncogenic mutation (sh-p53 or KRASV12). Mechanistically, hypoxia-inducible factor 1-alpha (HIF-1α) transferred from COPD-EVs triggers CXCR4 pathway activation that in turn mediates MICs expansion and acquisition of pro-tumorigenic effects. Indeed, HIF-1α inhibition or CXCR4 silencing prevented the acquisition of malignant traits induced by COPD-EVs alone. Hypoxia recapitulates the effects observed with COPD-EVs in HBEC-sh-p53-KRASV12high cells. Notably, higher levels of HIF-1α were observed in EVs from COPD subjects who subsequently developed cancer compared to those who remained cancer-free. Our findings support a role of COPD-EVs to promote the expansion of MICs in premalignant epithelial cells through HIF-1α-CXCR4 axis activation thereby potentially sustaining lung cancer progression.

Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review

Lung cancer represent the leading cause of cancer mortality, so several efforts have been focused on the development of a screening program. To address the issue of high overdiagnosis and false positive rates associated to LDCT-based screening, there is a need for new diagnostic biomarkers, with liquid biopsy ncRNAs detection emerging as a promising approach. In this scenario, this work provides an updated summary of the literature evidence about the role of non-coding RNAs in lung cancer screening. A literature search on PubMed was performed including studies which investigated liquid biopsy non-coding RNAs biomarker lung cancer patients and a control cohort. Micro RNAs were the most widely studied biomarkers in this setting but some preliminary evidence was found also for other non-coding RNAs, suggesting that a multi-biomarker based liquid biopsy approach could enhance their efficacy in the screening context. However, further studies are needed in order to optimize detection techniques as well as diagnostic accuracy before introducing novel biomarkers in the early diagnosis setting.

Artificial Intelligence in Lung Cancer Screening: The Future Is Now

Lung cancer has one of the worst morbidity and fatality rates of any malignant tumour. Most lung cancers are discovered in the middle and late stages of the disease, when treatment choices are limited, and patients' survival rate is low. The aim of lung cancer screening is the identification of lung malignancies in the early stage of the disease, when more options for effective treatments are available, to improve the patients' outcomes. The desire to improve the efficacy and efficiency of clinical care continues to drive multiple innovations into practice for better patient management, and in this context, artificial intelligence (AI) plays a key role. AI may have a role in each process of the lung cancer screening workflow. First, in the acquisition of low-dose computed tomography for screening programs, AI-based reconstruction allows a further dose reduction, while still maintaining an optimal image quality. AI can help the personalization of screening programs through risk stratification based on the collection and analysis of a huge amount of imaging and clinical data. A computer-aided detection (CAD) system provides automatic detection of potential lung nodules with high sensitivity, working as a concurrent or second reader and reducing the time needed for image interpretation. Once a nodule has been detected, it should be characterized as benign or malignant. Two AI-based approaches are available to perform this task: the first one is represented by automatic segmentation with a consequent assessment of the lesion size, volume, and densitometric features; the second consists of segmentation first, followed by radiomic features extraction to characterize the whole abnormalities providing the so-called "virtual biopsy". This narrative review aims to provide an overview of all possible AI applications in lung cancer screening.

The new world of RNA diagnostics and therapeutics

The 5th Workshop IRE on Translational Oncology was held in Rome (Italy) on 27-28 March at the IRCCS Regina Elena National Cancer Institute. This meeting entitled "The New World of RNA diagnostics and therapeutics" highlightes the significant progress in the RNA field made over the last years. Research moved from pure discovery towards the development of diagnostic biomarkers or RNA-base targeted therapies seeking validation in several clinical trials. Non-coding RNAs in particular have been the focus of this workshop due to their unique properties that make them attractive tools for the diagnosis and therapy of cancer.This report collected the presentations of many scientists from different institutions that discussed recent oncology research providing an excellent overview and representative examples for each possible application of RNA as biomarker, for therapy or to increase the number of patients that can benefit from precision oncology treatment.In particular, the meeting specifically emphasized two key features of RNA applications: RNA diagnostic (Blandino, Palcau, Sestito, Díaz Méndez, Cappelletto, Pulito, Monteonofrio, Calin, Sozzi, Cheong) and RNA therapeutics (Dinami, Marcia, Anastasiadou, Ryan, Fattore, Regazzo, Loria, Aharonov).

Automated Coronary Artery Calcium and Quantitative Emphysema in Lung Cancer Screening: Association With Mortality, Lung Cancer Incidence, and Airflow Obstruction

PURPOSE

To assess automated coronary artery calcium (CAC) and quantitative emphysema (percentage of low attenuation areas [%LAA]) for predicting mortality and lung cancer (LC) incidence in LC screening. To explore correlations between %LAA, CAC, and forced expiratory value in 1 second (FEV 1 ) and the discriminative ability of %LAA for airflow obstruction.

MATERIALS AND METHODS

Baseline low-dose computed tomography scans of the BioMILD trial were analyzed using an artificial intelligence software. Univariate and multivariate analyses were performed to estimate the predictive value of %LAA and CAC. Harrell C -statistic and time-dependent area under the curve (AUC) were reported for 3 nested models (Model survey : age, sex, pack-years; Model survey-LDCT : Model survey plus %LAA plus CAC; Model final : Model survey-LDCT plus selected confounders). The correlations between %LAA, CAC, and FEV 1 and the discriminative ability of %LAA for airflow obstruction were tested using the Pearson correlation coefficient and AUC-receiver operating characteristic curve, respectively.

RESULTS

A total of 4098 volunteers were enrolled. %LAA and CAC independently predicted 6-year all-cause (Model final hazard ratio [HR], 1.14 per %LAA interquartile range [IQR] increase [95% CI, 1.05-1.23], 2.13 for CAC ≥400 [95% CI, 1.36-3.28]), noncancer (Model final HR, 1.25 per %LAA IQR increase [95% CI, 1.11-1.37], 3.22 for CAC ≥400 [95%CI, 1.62-6.39]), and cardiovascular (Model final HR, 1.25 per %LAA IQR increase [95% CI, 1.00-1.46], 4.66 for CAC ≥400, [95% CI, 1.80-12.58]) mortality, with an increase in concordance probability in Model survey-LDCT compared with Model survey ( P <0.05). No significant association with LC incidence was found after adjustments. Both biomarkers negatively correlated with FEV 1 ( P <0.01). %LAA identified airflow obstruction with a moderate discriminative ability (AUC, 0.738).

CONCLUSIONS

Automated CAC and %LAA added prognostic information to age, sex, and pack-years for predicting mortality but not LC incidence in an LC screening setting. Both biomarkers negatively correlated with FEV 1 , with %LAA enabling the identification of airflow obstruction with moderate discriminative ability.

ERS International Congress 2022: highlights from the Thoracic Oncology Assembly

Thoracic malignancies are associated with a substantial public health burden. Lung cancer is the leading cause of cancer-related mortality worldwide, with significant impact on patients' quality of life. Following 2 years of virtual European Respiratory Society (ERS) Congresses due to the COVID-19 pandemic, the 2022 hybrid ERS Congress in Barcelona, Spain allowed peers from all over the world to meet again and present their work. Thoracic oncology experts presented best practices and latest developments in lung cancer screening, lung cancer diagnosis and management. Early lung cancer diagnosis, subsequent pros and cons of aggressive management, identification and management of systemic treatments' side-effects, and the application of artificial intelligence and biomarkers across all aspects of the thoracic oncology pathway were among the areas that triggered specific interest and will be summarised here.

Lung Cancer Screening with Low-Dose CT: What We Have Learned in Two Decades of ITALUNG and What Is Yet to Be Addressed

The ITALUNG trial started in 2004 and compared lung cancer (LC) and other-causes mortality in 55-69 years-aged smokers and ex-smokers who were randomized to four annual chest low-dose CT (LDCT) or usual care. ITALUNG showed a lower LC and cardiovascular mortality in the screened subjects after 13 years of follow-up, especially in women, and produced many ancillary studies. They included recruitment results of a population-based mimicking approach, development of software for computer-aided diagnosis (CAD) and lung nodules volumetry, LDCT assessment of pulmonary emphysema and coronary artery calcifications (CAC) and their relevance to long-term mortality, results of a smoking-cessation intervention, assessment of the radiations dose associated with screening LDCT, and the results of biomarkers assays. Moreover, ITALUNG data indicated that screen-detected LCs are mostly already present at baseline LDCT, can present as lung cancer associated with cystic airspaces, and can be multiple. However, several issues of LC screening are still unaddressed. They include the annual vs. biennial pace of LDCT, choice between opportunistic or population-based recruitment. and between uni or multi-centre screening, implementation of CAD-assisted reading, containment of false positive and negative LDCT results, incorporation of emphysema. and CAC quantification in models of personalized LC and mortality risk, validation of ultra-LDCT acquisitions, optimization of the smoking-cessation intervention. and prospective validation of the biomarkers.

Liquid Biopsy in NSCLC: An Investigation with Multiple Clinical Implications

Tissue biopsy is essential for NSCLC diagnosis and treatment management. Over the past decades, liquid biopsy has proven to be a powerful tool in clinical oncology, isolating tumor-derived entities from the blood. Liquid biopsy permits several advantages over tissue biopsy: it is non-invasive, and it should provide a better view of tumor heterogeneity, gene alterations, and clonal evolution. Consequentially, liquid biopsy has gained attention as a cancer biomarker tool, with growing clinical applications in NSCLC. In the era of precision medicine based on molecular typing, non-invasive genotyping methods became increasingly important due to the great number of oncogene drivers and the small tissue specimen often available. In our work, we comprehensively reviewed established and emerging applications of liquid biopsy in NSCLC. We made an excursus on laboratory analysis methods and the applications of liquid biopsy either in early or metastatic NSCLC disease settings. We deeply reviewed current data and future perspectives regarding screening, minimal residual disease, micrometastasis detection, and their implication in adjuvant and neoadjuvant therapy management. Moreover, we reviewed liquid biopsy diagnostic utility in the absence of tissue biopsy and its role in monitoring treatment response and emerging resistance in metastatic NSCLC treated with target therapy and immuno-therapy.

Plasma protein biomarkers for early prediction of lung cancer

BACKGROUND

Individual plasma proteins have been identified as minimally invasive biomarkers for lung cancer diagnosis with potential utility in early detection. Plasma proteomes provide insight into contributing biological factors; we investigated their potential for future lung cancer prediction.

METHODS

The Olink® Explore-3072 platform quantitated 2941 proteins in 496 Liverpool Lung Project plasma samples, including 131 cases taken 1-10 years prior to diagnosis, 237 controls, and 90 subjects at multiple times. 1112 proteins significantly associated with haemolysis were excluded. Feature selection with bootstrapping identified differentially expressed proteins, subsequently modelled for lung cancer prediction and validated in UK Biobank data.

FINDINGS

For samples 1-3 years pre-diagnosis, 240 proteins were significantly different in cases; for 1-5 year samples, 117 of these and 150 further proteins were identified, mapping to significantly different pathways. Four machine learning algorithms gave median AUCs of 0.76-0.90 and 0.73-0.83 for the 1-3 year and 1-5 year proteins respectively. External validation gave AUCs of 0.75 (1-3 year) and 0.69 (1-5 year), with AUC 0.7 up to 12 years prior to diagnosis. The models were independent of age, smoking duration, cancer histology and the presence of COPD.

INTERPRETATION

The plasma proteome provides biomarkers which may be used to identify those at greatest risk of lung cancer. The proteins and the pathways are different when lung cancer is more imminent, indicating that both biomarkers of inherent risk and biomarkers associated with presence of early lung cancer may be identified.

FUNDING

Janssen Pharmaceuticals Research Collaboration Award; Roy Castle Lung Cancer Foundation.

China lung cancer screening (CLUS) version 2.0 with new techniques implemented: Artificial intelligence, circulating molecular biomarkers and autofluorescence bronchoscopy

OBJECTIVE

The present study, CLUS version 2.0, was conducted to evaluate the performance of new techniques in improving the implementation of lung cancer screening and to validate the efficacy of LDCT in reducing lung cancer-specific mortality in a high-risk Chinese population.

METHODS

From July 2018 to February 2019, high-risk participants from six screening centers in Shanghai were enrolled in our study. Artificial intelligence, circulating molecular biomarkers and autofluorescencebronchoscopy were applied during screening.

RESULTS

A total of 5087 eligible high-risk participants were enrolled in the study; 4490 individuals were invited, and 4395 participants (97.9%) finally underwent LDCT detection. Positive screening results were observed in 857 (19.5%) participants. Solid nodules represented 53.6% of all positive results, while multiple nodules were the most common location type (26.8%). Up to December 2020, 77 participants received lung resection or biopsy, including 70 lung cancers, 2 mediastinal tumors, 1 tracheobronchial tumor, 1 malignant pleural mesothelioma and 3 benign nodules. Lung cancer patients accounted for 1.6% of all the screened participants, and 91.4% were in the early stage (stage 0-1).

CONCLUSIONS

LDCT screening can detect a high proportion of early-stage lung cancer patients in a Chinese high-risk population. The utilization of new techniques would be conducive to improving the implementation of LDCT screening.

Important steps towards a big change for lung health: a joint approach by the European Respiratory Society, the European Society of Radiology and their partners to facilitate implementation of the European Union's new recommendations on lung cancer screening

Enormous progress has been made on the epic journey towards implementation of lung cancer screening in Europe. A breakthrough for lung health has been achieved with the EU proposal for a Council recommendation on cancer screening. https://bit.ly/3J4O0Jb.

Role of circulating-tumor DNA in the early-stage non-small cell lung carcinoma as a predictive biomarker

Lung cancer is one of the most common solid malignancies. Tissue biopsy is the standard method for accurately diagnosing lung and many other malignancies over decades. However, molecular profiling of tumors leads to establishing a new horizon in the field of precision medicine, which has now entered the mainstream in clinical practice. In this context, a minimally invasive complementary method has been proposed as a liquid biopsy (LB) which is a blood-based test that is gaining popularity as it provides the opportunity to test genotypes in a unique, less invasive manner. Circulating tumor cells (CTC) captivating the Circulating-tumor DNA (Ct-DNA) are often present in the blood of lung cancer patients and are the fundamental concept behind LB. There are multiple clinical uses of Ct-DNA, including its role in prognostic and therapeutic purposes. The treatment of lung cancer has drastically evolved over time. Therefore, this review article mainly focuses on the current literature on circulating tumor DNA and its clinical implications and future goals in non-small cell lung cancer.

Ultra-low dose computed tomography protocols using spectral shaping for lung cancer screening: Comparison with low-dose for volumetric LungRADS classification

PURPOSE

To compare Low-Dose Computed Tomography (LDCT) with four different Ultra-Low-Dose Computed Tomography (ULDCT) protocols for PN classification according to the Lung Reporting and Data System (LungRADS).

METHODS

Three hundred sixty-one participants of an ongoing lung cancer screening (LCS) underwent single-breath-hold double chest Computed Tomography (CT), including LDCT (120kVp, 25mAs; CTDIvol 1,62 mGy) and one ULDCT among: fully automated exposure control ("ULDCT₁"); fixed tube-voltage and current according to patient size ("ULDCT₂"); hybrid approach with fixed tube-voltage ("ULDCT₃") and tube current automated exposure control ("ULDCT₄"). Two radiologists (R1, R2) assessed LungRADS 2022 categories on LDCT, and then after 2 weeks on ULDCT using two different kernels (R1: Qr49_{ADMIRE 4}; R2: Br49_{ADMIRE 3}). Intra-subject agreement for LungRADS categories between LDCT and ULDCT was measured by the k-Cohen Index with Fleiss-Cohen weights.

RESULTS

LDCT-dominant PNs were detected in ULDCT in 87 % of cases on Qr49_{ADMIRE 4} and 88 % on Br49_{ADMIRE 3}. The intra-subject agreement was: κULDCT₁ = 0.89 [95 %CI 0.82-0.96]; κULDCT₂ = 0.90 [0.81-0.98]; κULDCT₃ = 0.91 [0.84-0.99]; κULDCT₄ = 0.88 [0.78-0.97] on Qr49_{ADMIRE 4}, and κULDCT₁ = 0.88 [0.80-0.95]; κULDCT₂ = 0.91 [0.86-0.96]; κULDCT₃ = 0.87 [0.78-0.95]; and κULDCT₄ = 0.88 [0.82-0.94] on Br49_{ADMIRE 3}. LDCT classified as LungRADS 4B were correctly identified as LungRADS 4B at ULDCT₃, with the lowest radiation exposure among the tested protocols (median effective doses were 0.31, 0.36, 0.27 and 0.37 mSv for ULDCT₁, ULDCT₂, ULDCT₃, and ULDCT₄, respectively).

CONCLUSIONS

ULDCT by spectral shaping allows the detection and characterization of PNs with an excellent agreement with LDCT and can be proposed as a feasible approach in LCS.

Design of a printed electrochemical strip towards miRNA-21 detection in urine samples: optimization of the experimental procedures for real sample application

MicroRNAs (miRNAs) are clinical biomarkers for various human diseases, including cancer. They have been found in liquid biopsy samples, including various bodily fluids. They often play an important role in the early diagnosis and prognosis of cancer, and the development of simple and effective analytical methods would be of pivotal importance for the entire community. The determination of these targets may be affected by the different physicochemical parameters of the specimen of interest. In this work, an electrochemical detection platform for miRNA based on a screen-printed gold electrode was developed. In the present study, miRNA-21 was selected as a model sequence, due to its role in prostate, breast, colon, pancreatic, and liver cancers. A DNA sequence modified with methylene blue (MB) was covalently bound to the electrochemical strip and used to detect the selected target miRNA-21. After optimization of selected parameters in standard solutions, including the study of the effect of pH, the presence of interferent species, and NaCl salt concentration in the background, the application of square-wave voltammetry (SWV) technique allowed the detection of miRNA-21 down to a limit in the order of 2 nM. The developed device was then applied to several urine samples. In this case too, the device showed high selectivity in the presence of the complex matrix, satisfactory repeatability, and a limit of detection in the order of magnitude of nM, similarly as what observed in standard solutions.

Secondary prevention and treatment innovation of early stage non-small cell lung cancer: Impact on diagnostic-therapeutic pathway from a multidisciplinary perspective

Lung cancer (LC) is the leading cause of cancer-related death worldwide, mostly because the lack of a screening program so far. Although smoking cessation has a central role in LC primary prevention, several trials on LC screening through low-dose computed tomography (LDCT) in a high risk population showed a significant reduction of LC related mortality. Most trials showed heterogeneity in terms of selection criteria, comparator arm, detection nodule method, timing and intervals of screening and duration of the follow-up. LC screening programs currently active in Europe as well as around the world will lead to a higher number of early-stage Non Small Cell Lung Cancer (NSCLC) at the diagnosis. Innovative drugs have been recently transposed from the metastatic to the perioperative setting, leading to improvements in terms of resection rates and pathological responses after induction chemoimmunotherapy, and disease free survival with targeted agents and immune checkpoint inhibitors. The present review summarizes available evidence about LC screening, highlighting potential pitfalls and benefits and underlining the impact on the diagnostic therapeutic pathway of NSCLC from a multidisciplinary perspective. Future perspectives in terms of circulating biomarkers under evaluation for patients' risk stratification as well as a focus on recent clinical trials results and ongoing studies in the perioperative setting will be also presented.

Clinical Scores, Biomarkers and IT Tools in Lung Cancer Screening-Can an Integrated Approach Overcome Current Challenges?

As most lung cancer (LC) cases are still detected at advanced and incurable stages, there are increasing efforts to foster detection at earlier stages by low dose computed tomography (LDCT) based LC screening. In this scoping review, we describe current advances in candidate selection for screening (selection phase), technical aspects (screening), and probability evaluation of malignancy of CT-detected pulmonary nodules (PN management). Literature was non-systematically assessed and reviewed for suitability by the authors. For the selection phase, we describe current eligibility criteria for screening, along with their limitations and potential refinements through advanced clinical scores and biomarker assessments. For LC screening, we discuss how the accuracy of computerized tomography (CT) scan reading might be augmented by IT tools, helping radiologists to cope with increasing workloads. For PN management, we evaluate the precision of follow-up scans by semi-automatic volume measurements of CT-detected PN. Moreover, we present an integrative approach to evaluate the probability of PN malignancy to enable safe decisions on further management. As a clear limitation, additional validation studies are required for most innovative diagnostic approaches presented in this article, but the integration of clinical risk models, current imaging techniques, and advancing biomarker research has the potential to improve the LC screening performance generally.

Lung cancer screening

Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.

Increased levels of microRNA-320 in blood serum and plasma is associated with imminent and advanced lung cancer

Lung cancer (LC) incidence is increasing globally and altered levels of microRNAs (miRNAs) in blood may contribute to identification of individuals with LC. We identified miRNAs differentially expressed in peripheral blood at LC diagnosis and evaluated, in pre-diagnostic blood specimens, how long before diagnosis expression changes in such candidate miRNAs could be detected. We identified upregulated candidate miRNAs in plasma specimens from a hospital-based study sample of 128 patients with confirmed LC and 62 individuals with suspected but confirmed negative LC (FalsePos). We then evaluated the expression of candidate miRNAs in pre-diagnostic plasma or serum specimens of 360 future LC cases and 375 matched controls. There were 1663 miRNAs detected in diagnostic specimens, nine of which met our criteria for candidate miRNAs. Higher expression of three candidates, miR-320b, 320c, and 320d, was associated with poor survival, independent of LC stage and subtype. Moreover, miR-320c and miR-320d expression was higher in pre-diagnostic specimens collected within 2 years of LC diagnosis. Our results indicated that elevated levels of miR-320c and miR-320d may be early indications of imminent and advanced LC.

Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.