Lung cancer screening: latest developments and unanswered questions

Weighted Gene Networks Derived from Multi-Omics Reveal Core Cancer Genes in Lung Cancer

Lung cancer remains the leading cause of cancer-related deaths worldwide, driven by its complexity and the heterogeneity of its subtypes, which influence pathogenesis, tumor microenvironment, and genetic alterations. We developed a novel weighted gene regulatory network reconstruction method based on maximum entropy and Markov chain entropy principles, which integrates gene expression and DNA methylation data to generate biologically informed networks. Applied to LUAD and LUSC datasets, we define a network methylation index to determine whether gene methylation acts as oncogenic or tumor-suppressive. By revealing a stable core set of pathogenic genes, we identify not only genes with significant expression changes, such as CD74 and HGF, but also pathogenic genes with stable expression, such as BRAF and KDM6A. Additionally, we uncover potential driver genes, such as CORO2B and C20orf194, associated with disease stage, gender, and smoking status. This method offers a more comprehensive understanding of NSCLC mechanisms, paving the way for improved therapeutic strategies.

Impact on Image Quality and Diagnostic Performance of Dual-Layer Detector Spectral CT for Pulmonary Subsolid Nodules: Comparison With Hybrid and Model-Based Iterative Reconstruction

OBJECTIVE

To evaluate the image quality and diagnostic performance of pulmonary subsolid nodules on conventional iterative algorithms, virtual monoenergetic images (VMIs), and electron density mapping (EDM) using a dual-layer detector spectral CT (DLSCT).

METHODS

This retrospective study recruited 270 patients who underwent DLSCT scan for lung nodule screening or follow-up. All CT examinations with subsolid nodules (pure ground-glass nodules [GGNs] or part-solid nodules) were reconstructed with hybrid and model-based iterative reconstruction, VMI at 40, 70, 100, and 130 keV levels, and EDM. The CT number, objective image noise, signal-to-noise ratio, contrast-to-noise ratio, diameter, and volume of subsolid nodules were measured for quantitative analysis. The overall image quality, image noise, visualization of nodules, artifact, and sharpness were subjectively rated by 2 thoracic radiologists on a 5-point scale (1 = unacceptable, 5 = excellent) in consensus. The objective image quality measurements, diameter, and volume were compared among the 7 groups with a repeated 1-way analysis of variance. The subjective scores were compared with Kruskal-Wallis test.

RESULTS

A total of 198 subsolid nodules, including 179 pure GGNs, and 19 part-solid nodules were identified. Based on the objective analysis, EDM had the highest signal-to-noise ratio (164.71 ± 133.60; P < 0.001) and contrast-to-noise ratio (227.97 ± 161.96; P < 0.001) among all image sets. Furthermore, EDM had a superior mean subjective rating score (4.80 ± 0.42) for visualization of GGNs compared to other reconstructed images (all P < 0.001), although the model-based iterative reconstruction had superior subjective scores of overall image quality. For pure GGNs, the measured diameter and volume did not significantly differ among different reconstructions (both P > 0.05).

CONCLUSIONS

EDM derived from DLSCT enabled improved image quality and lesion conspicuity for the evaluation of lung subsolid nodules compared to conventional iterative reconstruction algorithms and VMIs.

Development and validation of a tumor marker-based model for the prediction of lung cancer: an analysis of a multicenter retrospective study in Shanghai, China

Background

The incidence and mortality rates of cancer are the highest globally. Developing novel methodologies that precisely, safely, and economically differentiate between benign and malignant lung conditions holds immense clinical importance. This research seeks to construct a predictive model utilizing a combination of diverse biomarkers to effectively discriminate between benign and malignant lung diseases.

Methods

This retrospective study included patients admitted to the two general hospitals in Shanghai from 2014 to 2015. This study was developed using five tumor markers: carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), cytokeratin fragment 21-1 (CA211), squamous cell carcinoma antigen (SCC), and neuron specific enolase (NSE). The entire sample was divided into two groups according to the hospital: 1033 cases were included in the development cohort and 300 cases in the validation cohort. Logistic regression analysis was used for univariate analysis to explore individual correlations between each selected clinical variable and lung cancer diagnostic outcome. Diagnostic prediction models were constructed and validated based on independent prognostic factors identified using multifactorial analysis. A nomogram was created using these tumor markers (age and sex were additionally included) and validated using the concordance index and calibration curves. Clinical prediction models were evaluated using decision curve analysis.

Results

Fully adjusted multivariate analysis showed that the risk of lung cancer was 2.38 times higher in men than in women. CEA positivity was associated with an 13.41-fold increased risk in lung cancer. The area under the curve (AUC) values for the development cohort and validation cohort models were 0.907 and 0.954, respectively. In the established nomogram, the AUC for the receiver operating characteristic curve was 0.907 (95% CI, 0.889-0.925). The validation model confirmed the strong discriminative power of the nomogram (AUC = 0.954). The described calibration curves demonstrated good fit predictions and observation probabilities. In addition, decision curve analysis concluded that the newly established nomogram has important implications for clinical decision making.

Conclusions

Combined prediction models based on CEA, CA199, CA211, SCC, and NSE biomarkers could significantly the differentiation between benign and malignant lung diseases, thus facilitating better clinical decision making.

The efficacy of machine learning models in lung cancer risk prediction with explainability

Among many types of cancers, to date, lung cancer remains one of the deadliest cancers around the world. Many researchers, scientists, doctors, and people from other fields continuously contribute to this subject regarding early prediction and diagnosis. One of the significant problems in prediction is the black-box nature of machine learning models. Though the detection rate is comparatively satisfactory, people have yet to learn how a model came to that decision, causing trust issues among patients and healthcare workers. This work uses multiple machine learning models on a numerical dataset of lung cancer-relevant parameters and compares performance and accuracy. After comparison, each model has been explained using different methods. The main contribution of this research is to give logical explanations of why the model reached a particular decision to achieve trust. This research has also been compared with a previous study that worked with a similar dataset and took expert opinions regarding their proposed model. We also showed that our research achieved better results than their proposed model and specialist opinion using hyperparameter tuning, having an improved accuracy of almost 100% in all four models.

Development of an Electronic Health Record Self-Referral Tool for Lung Cancer Screening: One-Group Posttest Study

BACKGROUND

Approximately 14 million individuals in the United States are eligible for lung cancer screening (LCS), but only 5.8% completed screening in 2021. Given the low uptake despite the potential great health benefit of LCS, interventions aimed at increasing uptake are warranted. The use of a patient-facing electronic health record (EHR) patient portal direct messaging tool offers a new opportunity to both engage eligible patients in preventative screening and provide a unique referral pathway for tobacco treatment.

OBJECTIVE

This study sought to develop and pilot an EHR patient-facing self-referral tool for an established LCS program in an academic medical center.

METHODS

Guided by constructs of the Health Belief Model associated with LCS uptake (eg, knowledge and self-efficacy), formative development of an EHR-delivered engagement message, infographic, and self-referring survey was conducted. The survey submits eligible self-reported patient information to a scheduler for the LCS program. The materials were pretested using an interviewer-administered mixed methods survey captured through venue-day-time sampling in 5 network-affiliated pulmonology clinics. Materials were then integrated into the secure patient messaging feature in the EHR system. Next, a one-group posttest quality improvement pilot test was conducted.

RESULTS

A total of 17 individuals presenting for lung screening shared-decision visits completed the pretest survey. More than half were newly referred for LCS (n=10, 60%), and the remaining were returning patients. When asked if they would use a self-referring tool through their EHR messaging portal, 94% (n=16) reported yes. In it, 15 participants provided oral feedback that led to refinement in the tool and infographic prior to pilot-testing. When the initial application of the tool was sent to a convenience sample of 150 random patients, 13% (n=20) opened the self-referring survey. Of the 20 who completed the pilot survey, 45% (n=9) were eligible for LCS based on self-reported smoking data. A total of 3 self-referring individuals scheduled an LCS.

CONCLUSIONS

Pretest and initial application data suggest this tool is a positive stimulus to trigger the decision-making process to engage in a self-referral process to LCS among eligible patients. This self-referral tool may increase the number of patients engaging in LCS and could also be used to aid in self-referral to other preventative health screenings. This tool has implications for clinical practice. Tobacco treatment clinical services or health care systems should consider using EHR messaging for LCS self-referral. This approach may be cost-effective to improve LCS engagement and uptake. Additional referral pathways could be built into this EHR tool to not only refer patients who currently smoke to LCS but also simultaneously trigger a referral to clinical tobacco treatment.

Absolute ground truth-based validation of computer-aided nodule detection and volumetry in low-dose CT imaging

PURPOSE

To validate the performance of computer-aided detection (CAD) and volumetry software using an anthropomorphic phantom with a ground truth (GT) set of 3D-printed nodules.

METHODS

The Kyoto Kaguku Lungman phantom, containing 3D-printed solid nodules including six diameters (4 to 9 mm) and three morphologies (smooth, lobulated, spiculated), was scanned at varying CTDIvol levels (6.04, 1.54 and 0.20 mGy). Combinations of reconstruction algorithms (iterative and deep learning image reconstruction) and kernels (soft and hard) were applied. Detection, volumetry and density results recorded by a commercially available AI-based algorithm (AVIEW LCS + ) were compared to the absolute GT, which was determined through µCT scanning at 50 µm resolution. The associations between image acquisition parameters or nodule characteristics and accuracy of nodule detection and characterization were analyzed with chi square tests and multiple linear regression.

RESULTS

High levels of detection sensitivity and precision (minimal 83 % and 91 % respectively) were observed across all acquisitions. Neither reconstruction algorithm nor radiation dose showed significant associations with detection. Nodule diameter however showed a highly significant association with detection (p < 0.0001). Volumetric measurements for nodules > 6 mm were accurate within 10 % absolute range from volumeGT, regardless of dose and reconstruction. Nodule diameter and morphology are major determinants of volumetric accuracy (p < 0.001). Density assignment was not significantly influenced by any parameters.

CONCLUSIONS

Our study confirms the software's accurate performance in nodule volumetry, detection and density characterization with robustness for variations in CT imaging protocols. This study suggests the incorporation of similar phantom setups in quality assurance of CAD tools.

Projected effectiveness of lung cancer screening and concurrent smoking cessation support in the Netherlands

Background

The NELSON trial demonstrated a 24% intention-to-screen reduction in lung cancer mortality from regular screening with low-dose computed tomography. Implementation efforts in Europe are ongoing, but still await country-specific and NELSON-adapted estimates of the benefits and harms of screening.

Methods

We use the MISCAN-Lung microsimulation model, calibrated to individual-level outcomes from the NELSON trial, to estimate the effectiveness under 100% compliance of biennial lung cancer screening with concomitant smoking cessation support for Dutch cohorts 1942-1961. The model simulates smoking behaviour, lung cancer incidence and the effects of screening and smoking cessation on lung- and other-cause mortality.

Findings

We find biennial screening with eligibility criteria equal to those of the 4-IN-THE-LUNG-RUN implementation trial to reduce lung cancer mortality by 16.9% among the eligible population, equivalent to 1076 LC deaths prevented per year in the next two decades. Eligible individuals constitute 21.5% of the cohorts studied, and stand to face 61% of the projected lung cancer mortality burden in the absence of screening. 10.3 life-years are gained per prevented LC death, for 14.9 screens per life year gained. Concomitant smoking cessation interventions may increase the expected gains in life years from screening by up to 20%.

Interpretation

Policy makers should imminently consider the implementation of lung cancer screening in Europe, paired with effective smoking cessation interventions. Smoking cessation interventions on their own are not estimated to yield a gain in remaining life expectancy of the magnitude offered by even a single CT screen.

Funding

European UnionHorizon 2020 grant 848294: 4-IN-THE-LUNG-RUN.

Knowledge, Attitudes, and Practice Patterns of Lung Cancer Screening Among Physicians in Saudi Arabia

BACKGROUND

Lung cancer remains the primary cause of death connected to cancer on a worldwide scale. Obtaining a deep understanding of the knowledge, attitudes, and behavior patterns of doctors is essential for developing successful strategies to improve lung cancer screening. This study aims to identify the attitudes, beliefs, referral practices, and knowledge of lung cancer screening among physicians in Saudi Arabia.

METHODS

An online survey was conducted from July to December 2023 to investigate the attitudes, beliefs, referral practices, and knowledge of lung cancer screening, and adherence to lung cancer screening recommendations among physicians in Saudi Arabia. Internal medicine, family medicine, and pulmonology physicians of all levels (consultants, senior registrars, and residents) who are currently practicing medicine in Saudi Arabia formed the study population. This study employed a previously developed questionnaire. Binary logistic regression analysis was employed to identify factors that indicate a better degree of knowledge and a positive attitude toward lung cancer screening.

RESULTS

This study involved a total of 96 physicians. The study participants demonstrated a significant degree of understanding regarding lung cancer screening, with an average knowledge score of 5.8 (SD: 1.7) out of 8, equivalent to 72.5% of the highest possible score. The accuracy rate for knowledge items varied from 44.8% to 91.7%. The study participants had a moderately favorable attitude toward lung cancer screening, as shown by a mean attitude score of 14.4 (SD: 3.7) out of a maximum possible score of 30, which corresponds to 48.0% of the highest achievable score. Around 36.5% of the survey participants reported engaging in the practice of discussing the results of lung cancer screening with patients. The primary obstacles frequently cited were challenges in patient scheduling, insufficient time to discuss lung cancer screening during clinic appointments, and patient refusal, constituting 59.4%, 53.1%, and 53.1% of the identified barriers, respectively. Physicians in Saudi Arabia, particularly those employed in private hospitals, demonstrated a higher level of knowledge of lung cancer screening compared to others (p < 0.05). In contrast, individuals with 11-15 years of experience were shown to have a 78.0% lower likelihood of being educated about lung cancer screening compared to their counterparts (p < 0.05).

CONCLUSION

The study's results indicate that there is a need for the development of specialized educational initiatives aimed at Saudi Arabian physicians, particularly those with 11 to 15 years of experience who exhibit a limited understanding of lung cancer screening. Utilizing programs that provide continuing medical education would aid in their education. There is a need to facilitate communication between physicians and patients. It is critical to address the identified issues, such as streamlining the appointment scheduling process and ensuring patients have sufficient time during clinic visits. Furthermore, it is critical for the success of nationwide screening initiatives to foster collaboration between the public and private healthcare sectors.

Quantification of diffuse parenchymal lung disease in non-small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis

BACKGROUND

We sought to quantify diffuse parenchymal lung disease (DPLD) extent using quantitative computed tomography (CT) analysis and to investigate its association with radiation pneumonitis (RP) development in non-small cell lung cancer (NSCLC) patients receiving definitive concurrent chemoradiation therapy (CCRT).

METHODS

A total of 82 NSCLC patients undergoing definitive CCRT were included in this prospective cohort study. Pretreatment CT scans were analyzed using quantitative CT analysis software. Low-attenuation area (LAA) features based on lung density and texture features reflecting interstitial lung disease (ILD) were extracted from the whole lung. Clinical and dosimetric factors were also evaluated. RP development was assessed using the Common Terminology Criteria for Adverse Events version 5.0. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors for grade ≥3 (≥GR3) RP.

RESULTS

RP was identified in 68 patients (73.9%), with nine patients (10.9%) experiencing ≥GR3 RP. Univariable logistic regression analysis identified excess kurtosis and high-attenuation area (HAA)_volume (cc) as significantly associated with ≥GR3 RP. Multivariable logistic regression analysis showed that the combined use of imaging features and clinical factors (forced expiratory volume in 1 second [FEV1], forced vital capacity [FVC], and CHEMO regimen) demonstrated the best performance (area under the receiver operating characteristic curve = 0.924) in predicting ≥GR3 RP.

CONCLUSION

Quantified imaging features of DPLD obtained from pretreatment CT scans would predict the occurrence of RP in NSCLC patients undergoing definitive CCRT. Combining imaging features with clinical factors could improve the accuracy of the predictive model for severe RP.

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.

Systematic Review of Lung Cancer Screening: Advancements and Strategies for Implementation

Lung cancer is the leading cause of cancer-related deaths in Europe, with low survival rates primarily due to late-stage diagnosis. Early detection can significantly improve survival rates, but lung cancer screening is not currently implemented in Italy. Many countries have implemented lung cancer screening programs for high-risk populations, with studies showing a reduction in mortality. This review aimed to identify key areas for establishing a lung cancer screening program in Italy. A literature search was conducted in October 2022, using the PubMed and Scopus databases. Items of interest included updated evidence, approaches used in other countries, enrollment and eligibility criteria, models, cost-effectiveness studies, and smoking cessation programs. A literature search yielded 61 scientific papers, highlighting the effectiveness of low-dose computed tomography (LDCT) screening in reducing mortality among high-risk populations. The National Lung Screening Trial (NLST) in the United States demonstrated a 20% reduction in lung cancer mortality with LDCT, and other trials confirmed its potential to reduce mortality by up to 39% and detect early-stage cancers. However, false-positive results and associated harm were concerns. Economic evaluations generally supported the cost-effectiveness of LDCT screening, especially when combined with smoking cessation interventions for individuals aged 55 to 75 with a significant smoking history. Implementing a screening program in Italy requires the careful consideration of optimal strategies, population selection, result management, and the integration of smoking cessation. Resource limitations and tailored interventions for subpopulations with low-risk perception and non-adherence rates should be addressed with multidisciplinary expertise.

Developing a pan-European technical standard for a comprehensive high-quality lung cancer computed tomography screening programme: an ERS technical standard

BACKGROUND

Screening for lung cancer with low radiation dose computed tomography (LDCT) has a strong evidence base. The European Council adopted a recommendation in November 2022 that lung cancer screening (LCS) be implemented using a stepwise approach. The imperative now is to ensure that implementation follows an evidence-based process that delivers clinical and cost-effectiveness. This European Respiratory Society (ERS) Task Force was formed to provide a technical standard for a high-quality LCS programme.

METHOD

A collaborative group was convened to include members of multiple European societies. Topics were identified during a scoping review and a systematic review of the literature was conducted. Full text was provided to members of the group for each topic. The final document was approved by all members and the ERS Scientific Advisory Committee.

RESULTS

Topics were identified representing key components of a screening programme. The actions on findings from the LDCT were not included as they are addressed by separate international guidelines (nodule management and clinical management of lung cancer) and by a linked ERS Task Force (incidental findings). Other than smoking cessation, other interventions that are not part of the core screening process were not included (e.g. pulmonary function measurement). 56 statements were produced and areas for further research identified.

CONCLUSIONS

This European collaborative group has produced a technical standard that is a timely contribution to implementation of LCS. It will serve as a standard that can be used, as recommended by the European Council, to ensure a high-quality and effective programme.

The Journey for Lung Cancer Screening where we Stand Today

BACKGROUND

Lung cancer remains a leading cause of cancer mortality worldwide with many patients presenting with advanced disease.

OBJECTIVE

We reviewed the available literature for lung cancer screening using low dose computed tomography (LDCT). We reviewed the National Lung Screening Trial (NLST), Early Lung Cancer Action Program (ELCAP) and the (Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) trials. We also look at different lung cancer risk prediction models that may aid in identifying target populations and also discuss the cost-effectiveness of LDCT screening in different groups of smokers and ex-smokers. Lastly, we discuss recent guideline changes that have occurred in line with new and emerging evidence on lung cancer screening.

CONCLUSION

LDCT has been shown reduce lung cancer mortality in certain groups of current and former smokers and should be considered to help in the early diagnosis of lung cancer.

Early diagnosis of breast cancer lung metastasis by nanoprobe-based luminescence imaging of the pre-metastatic niche

BACKGROUND

Early detection of breast cancer lung metastasis remains highly challenging, due to few metastatic cancer cells at an early stage. Herein we propose a new strategy for early diagnosis of lung metastasis of breast cancer by luminescence imaging of pulmonary neutrophil infiltration via self-illuminating nanoprobes.

METHODS

Luminescent nanoparticles (LAD NPs) were engineered using a biocompatible, neutrophil-responsive self-illuminating cyclodextrin material and an aggregation-induced emission agent. The chemiluminescence resonance energy transfer (CRET) effect and luminescence properties of LAD NPs were fully characterized. Using mouse peritoneal neutrophils, in vitro luminescence properties of LAD NPs were thoroughly examined. In vivo luminescence imaging and correlation analyses were performed in mice inoculated with 4T1 cancer cells. Moreover, an active targeting nanoprobe was developed by surface decoration of LAD NPs with a neutrophil-targeting peptide, which was also systemically evaluated by in vitro and in vivo studies.

RESULTS

LAD NPs can generate long-wavelength and persistent luminescence due to the CRET effect. In a mouse model of 4T1 breast cancer lung metastasis, we found desirable correlation between neutrophils and tumor cells in the lungs, demonstrating the effectiveness of early imaging of the pre-metastatic niche by the newly developed LAD NPs. The active targeting nanoprobe showed further enhanced luminescence imaging capability for early detection of pulmonary metastasis. Notably, the targeting nanoprobe-based luminescence imaging strategy remarkably outperformed PET/CT imaging modalities in the examined mouse model. Also, preliminary tests demonstrated good safety of LAD NPs.

CONCLUSIONS

The neutrophil-targeting imaging strategy based on newly developed luminescence nanoparticles can serve as a promising modality for early diagnosis of lung metastasis of breast cancers.

Results of the cancer screening feasibility study in China: a multicentered randomized controlled trial of lung and colorectal cancer screening

Background

To provide an understanding of important aspects of the participant recruitment and data collection, become aware of any potential problems, and obtain necessary information in order to design a large-scale randomized controlled trial (RCT) for lung cancer and colorectal cancer (CRC) screening in China.

Methods

This feasibility study was a multicentered, open-label, pilot randomized trial. A total of 2696 participants who were at high risk of lung cancer were recruited from three screening centers and randomly allocated to arm 1 (n = 894), annual low-dose computed tomography (LDCT) plus a baseline colonoscopy; arm 2 (n = 902), biennial LDCT plus annual fecal immunochemical test (FIT) with OC-Sensor (OC-FIT); and arm 3 (n = 900), annual Insure-FIT plus Septin 9 blood test. Information on randomization, compliance, positivity rate, cancer case detection, and contamination with screening for lung cancer and CRC were collected.

Results

Participant characteristics were similar across study arms. The compliance rate of annual LDCT screening in arm 1 was 86.4% (95% CI: 83.9%, 88.5%) at baseline (T0), and 69.0% (95% CI: 65.8%, 72.0%) and 70.7% (95% CI: 67.6%, 73.7%) at the following two rounds (T1 and T2). The compliance rates of biennial LDCT screening in arm 2 were similar to those in arm 1 in the corresponding rounds. The compliance rate was 55.5% (95% CI: 52.2%, 58.8%) for colonoscopy in arm 1, while the compliance rates of OC-FIT, Insure-FIT, and the Septin 9 test in arms 2 and 3 were all approximately 90% at T0, decreasing to 65%-80% at T1 and T2. The positivity rate, cancer case detection rate, and contamination rate of screening for lung cancer and CRC were also reported.

Conclusion

In this pilot study, the feasibility of an RCT in China of lung cancer and CRC screening was demonstrated.

Establishing a Cohort and a Biorepository to Identify Biomarkers for Early Detection of Lung Cancer: The Nashville Lung Cancer Screening Trial Cohort

Rationale: A prospective longitudinal cohort of individuals at high risk of developing lung cancer was established to build a biorepository of carefully annotated biological specimens and low-dose computed tomography (LDCT) chest images for derivation and validation of candidate biomarkers for early detection of lung cancer.Objectives: The goal of this study is to characterize individuals with high risk for lung cancer, accumulating valuable biospecimens and LDCT chest scans longitudinally over 5 years.Methods: Participants 55-80 years of age with a 5-year estimated risk of developing lung cancer >1.5% were recruited and enrolled from clinics at the Vanderbilt University Medical Center, Veteran Affairs Medical Center, and Meharry Medical Center. Individual demographic characteristics were assessed via questionnaire at baseline. Participants underwent an LDCT scan, spirometry, sputum cytology, and research bronchoscopy at the time of enrollment. Participants will be followed yearly for 5 years. Positive LDCT scans are followed-up according to standard of care. The clinical, imaging, and biospecimen data are collected prospectively and stored in a biorepository. Participants are offered smoking cessation counseling at each study visit.Results: A total of 480 participants were enrolled at study baseline and consented to sharing their data and biospecimens for research. Participants are followed with yearly clinic visits to collect imaging data and biospecimens. To date, a total of 19 cancers (13 adenocarcinomas, four squamous cell carcinomas, one large cell neuroendocrine, and one small-cell lung cancer) have been identified.Conclusions: We established a unique prospective cohort of individuals at high risk for lung cancer, enrolled at three institutions, for whom full clinical data, well-annotated LDCT scans, and biospecimens are being collected longitudinally. This repository will allow for the derivation and independent validation of clinical, imaging, and molecular biomarkers of risk for diagnosis of lung cancer.Clinical trial registered with ClinicalTrials.gov (NCT01475500).

Overuse of follow-up chest computed tomography in patients with incidentally identified nodules suspicious for lung cancer

PURPOSE

Although professional societies agreed that CT screening inconsistent with recommendation leads to radiation-related cancer and unexpected cost, many patients still undergo unnecessary Chest CT before treatment. The goal of this study was to assess the overuse of Chest CT in different type of patients.

METHODS

Data on 1853 patients who underwent pulmonary resection from May 2019 to May 2020 were retrospectively analyzed. Data collected include age, sex, follow-up period, density and size of nodules and frequency of undergoing Chest CT. Pearson χ² test and logistic regression were conducted to compare the receipt of CT screening.

RESULTS

Among 1853 patients in the study, 689 (37.2%) overused Chest CT during follow-up of the pulmonary nodules. This rate was 16.2% among patients with solid nodules, 57.5% among patients with pure ground glass opacity (pGGO), and 41.4% among patients with mixed ground glass opacity (mGGO) (P < 0.001). 50.7% in the "age ≤ 40" group, 39.8% in the "41 ≤ age ≤ 50" group, 38.7% in the "51 ≤ age ≤ 60" group, 32.3% in the "61 ≤ age ≤ 70" group, 27.8% in the " > 70" group underwent unnecessary CT (P < 0.001). Female got more unnecessary CT than male (40.6% vs 32.8%, P < 0.001). Factors associated with a greater likelihood of overusing Chest CT was the density of nodules [odds ratios (ORs) of 0.53 for mGGO; 0.15 for solid nodule, P < 0.0001, vs patients with pGGO].

CONCLUSION

Roughly 37% patients with pulmonary nodules received Chest CT too frequently despite national recommendations against the practice. Closer adherence to clinical guidelines is likely to result in more cost-effective care.

ARHGAP10 inhibits the epithelial-mesenchymal transition of non-small cell lung cancer by inactivating PI3K/Akt/GSK3β signaling pathway

Background

Rho GTPase activating protein 10 (ARHGAP10) has been implicated as an essential element in multiple cellular process, including cell migration, adhesion and actin cytoskeleton dynamic reorganization. However, the correlation of ARHGAP10 expression with epithelial–mesenchymal transition (EMT) in lung cancer cells is unclear and remains to be elucidated. Herein, we investigated the relationship between the trait of ARHGAP10 and non-small cell lung cancer (NSCLC) pathological process.

Methods

Immunohistochemistry was conducted to evaluate the expression of ARHGAP10 in NSCLC tissues. CCK-8 assays, Transwell assays, scratch assays were applied to assess cell proliferation, invasion and migration. The expression levels of EMT biomarkers and active molecules involved in PI3K/Akt/GSK3β signaling pathway were examined through immunofluorescence and Western blot.

Results

ARHGAP10 was detected to be lower expression in NSCLC tissues compared with normal tissues from individuals. Moreover, overexpression of ARHGAP10 inhibited migratory and invasive potentials of A549 and NCI-H1299 cells. In addition, ARHGAP10 directly mediated the process of EMT via PI3K/Akt/GSK3β pathway. Meanwhile, activation of the signaling pathway of insulin-like growth factors-1 (IGF-1) reversed ARHGAP10 overexpression regulated EMT in NSCLC cells.

Conclusion

ARHGAP10 inhibits the epithelial–mesenchymal transition in NSCLC via PI3K/Akt/GSK3β signaling pathway, suggesting agonist of ARHGAP10 may be an optional remedy for NSCLC patients than traditional opioids.

Spi-B Promotes the Recruitment of Tumor-Associated Macrophages via Enhancing CCL4 Expression in Lung Cancer

Tumor immune escape plays a critical role in malignant tumor progression and leads to the failure of anticancer immunotherapy. Spi-B, a lymphocyte lineage-specific Ets transcription factor, participates in mesenchymal invasion and favors metastasis in human lung cancer. However, the mechanism through which Spi-B regulates the tumor immune environment has not been elucidated. In this study, we demonstrated that Spi-B enhanced the infiltration of tumor-associated macrophages (TAMs) in the tumor microenvironment using subcutaneous mouse models and clinical samples of human lung cancer. Spi-B overexpression increased the expression of TAM polarization- and recruitment-related genes, including CCL4. Moreover, deleting CCL4 inhibited the ability of Spi-B promoting macrophage infiltration. These data suggest that Spi-B promotes the recruitment of TAMs to the tumor microenvironment via upregulating CCL4 expression, which contributes to the progression of lung cancer.

Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges

Randomised clinical trials have shown the efficacy of computed tomography lung cancer screening, initiating discussions on whether and how to implement population‐based screening programs. Due to smoking behaviour being the primary risk‐factor for lung cancer and part of the criteria for determining screening eligibility, lung cancer screening is inherently risk‐based. In fact, the selection of high‐risk individuals has been shown to be essential in implementing lung cancer screening in a cost‐effective manner. Furthermore, studies have shown that further risk‐stratification may improve screening efficiency, allow personalisation of the screening interval and reduce health disparities. However, implementing risk‐based lung cancer screening programs also requires overcoming a number of challenges. There are indications that risk‐based approaches can negatively influence the trade‐off between individual benefits and harms if not applied thoughtfully. Large‐scale implementation of targeted, risk‐based screening programs has been limited thus far. Consequently, questions remain on how to efficiently identify and invite high‐risk individuals from the general population. Finally, while risk‐based approaches may increase screening program efficiency, efficiency should be balanced with the overall impact of the screening program. In this review, we will address the opportunities and challenges in applying risk‐stratification in different aspects of lung cancer screening programs, as well as the balance between screening program efficiency and impact.

Screen-detected solid nodules: from detection of nodule to structured reporting

Lung cancer screening (LCS) is gaining some interest worldwide after positive results from International trials. Unlike other screening practices, LCS is performed by an extremely sensitive test, namely low-dose computed tomography (LDCT) that can detect the smallest nodules in lung parenchyma. Up-to-date detection approaches, such as computer aided detection systems, have been increasingly employed for lung nodule automatic identification and are largely used in most LCS programs as a complementary tool to visual reading. Solid nodules of any size are represented in the vast majority of subjects undergoing LDCT. However, less than 1% of solid nodules will be diagnosed lung cancer. This fact calls for specific characterization of nodules to avoid false positives, overinvestigation, and reduce the risks associated with nodule work up. Recent research has been exploring the potential of artificial intelligence, including deep learning techniques, to enhance the accuracy of both detection and characterisation of lung nodule. Computer aided detection and diagnosis algorithms based on artificial intelligence approaches have demonstrated the ability to accurately detect and characterize parenchymal nodules, reducing the number of false positives, and to outperform some of the currently used risk models for prediction of lung cancer risk, potentially reducing the proportion of surveillance CT scans. These forthcoming approaches will eventually integrate a new reasoning for development of future guidelines, which are expected to evolve into precision and personalized stratification of lung cancer risk stratification by continuous fashion, as opposed to the current format with a limited number of risk classes within fixed thresholds of nodule size. This review aims to detail the standard of reference for optimal management of solid nodules by low-dose computed and its projection into the fine selection of candidates for work up.

Lung cancer screening with low-dose computed tomography at a tertiary hospital in Anhui, China and secondary analysis of trial data

OBJECTIVE

Lung cancer screening with low-dose computed tomography (LDCT) partly reduces cancer-specific mortality. However, few data have described this specific population for screening in mainland China. Here, we conducted a population-based screening program in Anhui, China.

METHODS

9084 individuals were participating in the screening program for lung cancer in Anhui province from 1 June 2014 to 31 May 2017. LDCT was offered to all participants who joined the program.

RESULTS

Of 9084 individuals undergoing LDCT, we detected 54 lung cancers (0.594%). The age with the highest rate was 61-65 years (up to 1.016%), followed by 56-60 (0.784%). Most patients (98.1%, 53/54) were in stage I-II (early stage), and only one was in stage III (advanced stage). Adenocarcinoma, squamous cell carcinoma and small cell lung cancer accounted for 57.4% (31/54), 37% (20/54) and 5.6% (3/54) of the individuals, respectively. Notably, There were 4,102 never smokers in our study. The median age was 63 years. Males and females accounted for 53.4 and 46.6%, respectively. Among the 4102 never smokers, 96 participants had a positive family cancer history. Additionally, we detected 20 lung cancers (0.488%), slightly lower than the whole rate 0.594%. Finally, our data showed that age, smoking, family cancer history and features of nodules were risk factors for lung cancer.

CONCLUSION

Our study qualified the efficiency of LDCT to detect early-stage lung cancers in Anhui, China. Further establishment of appropriate lung cancer screening methods specifically for individuals in China is warranted.

ADVANCES IN KNOWLEDGE

We evaluated the performance of lung cancer screening for asymptomatic populations using LDCT in Anhui, an eastern inland province of China. Our study qualified the efficiency of LDCT to detect early-stage lung cancers in Anhui, China.

The hepatic microenvironment promotes lung adenocarcinoma cell proliferation, metastasis, and epithelial-mesenchymal transition via METTL3-mediated N6-methyladenosine modification of YAP1

The inflammatory microenvironment plays an important role in the onset and progression of lung adenocarcinoma (LUAD), and the liver is a suitable site of metastasis for LUAD cells. However, whether the inflammatory microenvironment of the liver is conducive to the proliferation, invasion, and metastasis of LUAD cells remains unclear. In this study, we confirmed that the hepatic inflammatory microenvironment stimulated by IL-6 promoted the proliferation, migration, invasion, and epithelial–mesenchymal transition of LUAD cells, increased the m6A methylation of total RNA, and transcriptionally activated METTL3 expression. Additionally, METTL3 activated the YAP1/TEAD signaling pathway by increasing the m6A modification and expression of YAP1 mRNA. These results indicate that the hepatic inflammatory microenvironment plays a role in regulating the biological functions of LUAD cells. Further, our study identifies a molecular mechanism that may provide a new strategy for the early diagnosis, treatment, and prognosis of liver metastasis in LUAD patients.

Lung cancer screening strategy for non-high-risk individuals: a narrative review

Lung cancer is the deadliest malignancy worldwide, accounting for almost 20% of all cancer deaths. Clinical trials, such as NLST and NELSON, have proved the survival benefit of lung cancer screening using low-dose computed tomography (LDCT), and most of the lung cancer screening guidelines recommended annual lung cancer screening by LDCT for high-risk individuals. However, a relatively high proportion of lung cancer patients do not have risk factors, and it is questionable whether non-high-risk individuals should receive LDCT screening. In this review, we reviewed risk factors of lung cancer and summarized the benefits and potential harms of LDCT screening. After clarifying the differences between China and western countries in lung cancer screening, we recommended that non-high-risk individuals should receive LDCT screening with an interval of five to ten years. To better balance benefits and harms from LDCT screening, we also proposed a flexible screening strategy using LDCT based on lung cancer risk. Hopefully, it may help reduce unnecessary radiation exposure from CT scans while decreasing mortality of lung cancer.

DNA Methylation Markers in Lung Cancer

Lung cancer is the most common cancer and the leading cause of cancer-related morbidity and mortality worldwide. As early symptoms of lung cancer are minimal and non-specific, many patients are diagnosed at an advanced stage. Despite a concerted effort to diagnose lung cancer early, no biomarkers that can be used for lung cancer screening and prognosis prediction have been established so far. As global DNA demethylation and gene-specific promoter DNA methylation are present in lung cancer, DNA methylation biomarkers have become a major area of research as potential alternative diagnostic methods to detect lung cancer at an early stage. This review summarizes the emerging DNA methylation changes in lung cancer tumorigenesis, focusing on biomarkers for early detection and their potential clinical applications in lung cancer.

Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives

In the past decade, the introduction of molecularly targeted agents and immune-checkpoint inhibitors has led to improved survival outcomes for patients with advanced-stage lung cancer; however, this disease remains the leading cause of cancer-related mortality worldwide. Two large randomized controlled trials of low-dose CT (LDCT)-based lung cancer screening in high-risk populations - the US National Lung Screening Trial (NLST) and NELSON - have provided evidence of a statistically significant mortality reduction in patients. LDCT-based screening programmes for individuals at a high risk of lung cancer have already been implemented in the USA. Furthermore, implementation programmes are currently underway in the UK following the success of the UK Lung Cancer Screening (UKLS) trial, which included the Liverpool Health Lung Project, Manchester Lung Health Check, the Lung Screen Uptake Trial, the West London Lung Cancer Screening pilot and the Yorkshire Lung Screening trial. In this Review, we focus on the current evidence on LDCT-based lung cancer screening and discuss the clinical developments in high-risk populations worldwide; additionally, we address aspects such as cost-effectiveness. We present a framework to define the scope of future implementation research on lung cancer screening programmes referred to as Screening Planning and Implementation RAtionale for Lung cancer (SPIRAL).

A comprehensive algorithm to distinguish between MPLC and IPM in multiple lung tumors patients

Background

Diagnosis of multiple lung nodules has become convenient and frequent due to the improvement of computed tomography (CT) scans. However, to distinguish intrapulmonary metastasis (IPM) from multiple primary lung cancer (MPLC) remains challenging. Herein, for the accurate optimization of therapeutic options, we propose a comprehensive algorithm for multiple lung carcinomas based on a multidisciplinary approach, and investigate the prognosis of patients who underwent surgical resection.

Methods

Patients with multiple lung carcinomas who were treated at West China Hospital of Sichuan University from April, 2009 to December, 2017, were retrospectively identified. A comprehensive algorithm combining histologic assessment, molecular analysis, and imaging information was used to classify nodules as IPM or MPLC. The Kaplan-Meier method was used to estimate survival rates, and the relevant factors were evaluated using the log-rank test or Cox proportional hazards model.

Results

The study included 576 patients with 1,295 lung tumors in total. Significant differences were observed between the clinical features of 171 patients with IPM and 405 patients with MPLC. The final classification consistency was 0.65 and 0.72 compared with the criteria of Martini and Melamed (MM) and the American College of Chest Physicians (ACCP), respectively. Patients with independent primary tumors had better overall survival (OS) than patients with intra-pulmonary metastasis (HR =3.99, 95% CI: 2.86–5.57; P<0.001). Nodal involvement and radiotherapy were independent prognostic factors.

Conclusions

The comprehensive algorithm was a relevant tool for classifying multifocal lung tumors as MPLC or IPM, and could help doctors with precise decision-making in routine clinical practice. Patients with multiple lesions without lymph node metastasis or without radiotherapy tended to have a better prognosis.

Knockdown of lncRNA ZFAS1-suppressed non-small cell lung cancer progression via targeting the miR-150-5p/HMGA2 signaling

Non-small cell lung cancer (NSCLC) is the main type of lung malignancy. Early diagnosis and treatments for NSCLC are far from satisfactory due to the limited knowledge of the molecular mechanisms regarding NSCLC progression. Long noncoding RNA (lncRNA) ZNFX1 antisense RNA1 (ZFAS1) has been implicated for its functional role in the progression of malignant tumors. This study aimed to determine the ZFAS1 expression from lung cancer clinical samples and to explore the molecular mechanisms underlying ZFAS1-modulated NSCLC progression. Experimental assays revealed that clinical samples and cell lines of lung malignant tumors showed an upregulation of ZFSA1. ZFAS1 expression was markedly upregulated in the lung tissues from patients with advanced stage of this malignancy. The loss-of-function assays showed that knockdown of ZFAS1-suppressed NSCLC cell proliferative, as well as invasive potentials, increased NSCLC cell apoptotic rates in vitro and also attenuated tumor growth of NSCLC cells in the nude mice. Further experimental evidence showed that ZFAS1 inversely affected miR-150-5p expression and positively affected high-mobility group AT-hook 2 (HMGA2) expression in NSCLC cell lines. MiR-150-5p inhibition or HMGA2 overexpression counteracted the effects of ZFAS1 knockdown on NSCLC cell proliferative, invasive potentials and apoptotic rates. In light of examining the clinical lung cancer samples, miR-150-5p expression was downregulated and the HMGA2 expression was highly expressed in the lung cancer tissues compared with normal ones; the ZFAS1 expression showed a negative correlation with miR-150-5p expression but a positive correlation with HMGA2 expression in lung cancer tissues. To summarize, we, for the first time, demonstrated the inhibitory effects of ZFAS1 knockdown on NSCLC cell progression, and the results from mechanistic studies indicated that ZFAS1-mediated NSCLC progression cells via targeting miR-150-5p/HMGA2 signaling.

Examining the effect of underlying individual preferences for present over future on lung cancer screening participation: a cross-sectional analysis of a Korean National Cancer Screening Survey

OBJECTIVES

This study aimed to examine the effect of underlying individual preferences for the present over that for the future on lung cancer screening participation.

SETTING

We analysed the data from the Korean National Cancer Screening Survey in 2018.

PARTICIPANTS

4500 adults aged 20-74 years old participated in the study.

DESIGN

In this cross-sectional survey, multivariate logistic regression analysis was carried out to examine the association between subjects' intention to participate in lung cancer screening and individual preferences. The underlying individual preferences were measured on the basis of the self-reported general willingness to spend money now in order to save money in the future and general preferences with regard to financial planning.

PRIMARY OUTCOME MEASURE

Intention to participate in lung cancer screening.

RESULTS

Individuals eligible for lung cancer screening who place less value on their future were around four times less likely to report an intention to participate in lung cancer screening than were those who valued their future (OR 3.86, 95% CI 1.89 to 7.90). A present-biassed individual (one with a tendency for immediate gratification) was also about four times less likely to report an intention to participate in screening than an individual with no present bias (OR 0.26, 95% CI 0.12 to 0.57).

CONCLUSIONS

Underlying individual preferences regarding the present and future significantly affect individuals' intention to participate in lung cancer screening. Hence, provision of incentives may be necessary to encourage the targeted heavy smokers who may have a strong preferences for the present over future.

Identification of Candidates for Longer Lung Cancer Screening Intervals Following a Negative Low-Dose Computed Tomography Result

Lengthening the annual low-dose computed tomography (CT) screening interval for individuals at lowest risk of lung cancer could reduce harms and improve efficiency. We analyzed 23 328 participants in the National Lung Screening Trial who had a negative CT screen (no ≥4-mm nodules) to develop an individualized model for lung cancer risk after a negative CT. The Lung Cancer Risk Assessment Tool + CT (LCRAT+CT) updates "prescreening risk" (calculated using traditional risk factors) with selected CT features. At the next annual screen following a negative CT, risk of cancer detection was reduced among the 70% of participants with neither CT-detected emphysema nor consolidation (median risk = 0.2%, interquartile range [IQR] = 0.1%-0.3%). However, risk increased for the 30% with CT emphysema (median risk = 0.5%, IQR = 0.3%-0.8%) and the 0.6% with consolidation (median = 1.6%, IQR = 1.0%-2.5%). As one example, a threshold of next-screen risk lower than 0.3% would lengthen the interval for 57.8% of screen-negatives, thus averting 49.8% of next-screen false-positives among screen-negatives but delaying diagnosis for 23.9% of cancers. Our results support that many, but not all, screen-negatives might reasonably lengthen their CT screening interval.

Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms

Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in several aspects. Identifying their differentially expressed genes and different gene expression patterns can deepen our understanding of these two subtypes at the transcriptomic level. In this work, we used several machine learning algorithms to investigate the gene expression profiles of lung AC and lung SCC samples retrieved from Gene Expression Omnibus. First, the profiles were analyzed by using a powerful feature selection method, namely, Monte Carlo feature selection. A feature list, ranking all features according to their importance, and some informative features were obtained. Then, the feature list was used in the incremental feature selection method to extract optimal features, which can allow the support vector machine (SVM) to yield the best performance for classifying lung AC and lung SCC samples. Some top genes (CSTA, TP63, SERPINB13, CLCA2, BICD2, PERP, FAT2, BNC1, ATP11B, FAM83B, KRT5, PARD6G, PKP1) were extensively analyzed to prove that they can be differentially expressed genes between lung AC and lung SCC. Meanwhile, a rule learning procedure was applied on informative features to construct the classification rules. These rules provide a clear procedure of classification and show some different gene expression patterns between lung AC and lung SCC.

Serum TNFRII: A promising biomarker for predicting the risk of subcentimetre lung adenocarcinoma

Early diagnosis of lung adenocarcinoma requires effective risk predictors. TNFRII was reported to be related to tumorigenesis, but remained unclear in lung cancer. This research set out to investigate the relationship between the sTNFRII (serum TNFRII) level and the risk of lung adenocarcinoma less than 1 cm in diameter. Seventy‐one pairs of subcentimetre lung adenocarcinoma patients and healthy controls were analysed through multiplex bead‐based Luminex assay and found a significantly lower expression of sTNFRII in patients with subcentimetre lung adenocarcinoma than that in the healthy controls (P < .001), which was further verified through ONCOMINE database analysis. Increased levels of sTNFRII reduced the risk of subcentimetre lung adenocarcinoma by 89% (P < .001). Patients with a higher level of BLC had a 2.70‐fold (P < .01) higher risk of subcentimetre adenocarcinoma. Furthermore, a higher BLC/TNFRII ratio was related to a 35‐fold higher risk of subcentimetre adenocarcinoma. TNFRII showed good specificity, sensitivity and accuracy (0.72, 0.75 and 0.73, respectively), with an AUC of 0.73 (P < .001). In conclusion, the present study assessed the value of sTNFRII as a potential biomarker to predict the risk of subcentimetre lung adenocarcinoma and provided evidence for the further use of TNFRII as an auxiliary marker in the diagnosis of subcentimetre lung adenocarcinoma.

Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial

BACKGROUND

There are limited data from randomized trials regarding whether volume-based, low-dose computed tomographic (CT) screening can reduce lung-cancer mortality among male former and current smokers.

METHODS

A total of 13,195 men (primary analysis) and 2594 women (subgroup analyses) between the ages of 50 and 74 were randomly assigned to undergo CT screening at T0 (baseline), year 1, year 3, and year 5.5 or no screening. We obtained data on cancer diagnosis and the date and cause of death through linkages with national registries in the Netherlands and Belgium, and a review committee confirmed lung cancer as the cause of death when possible. A minimum follow-up of 10 years until December 31, 2015, was completed for all participants.

RESULTS

Among men, the average adherence to CT screening was 90.0%. On average, 9.2% of the screened participants underwent at least one additional CT scan (initially indeterminate). The overall referral rate for suspicious nodules was 2.1%. At 10 years of follow-up, the incidence of lung cancer was 5.58 cases per 1000 person-years in the screening group and 4.91 cases per 1000 person-years in the control group; lung-cancer mortality was 2.50 deaths per 1000 person-years and 3.30 deaths per 1000 person-years, respectively. The cumulative rate ratio for death from lung cancer at 10 years was 0.76 (95% confidence interval [CI], 0.61 to 0.94; P = 0.01) in the screening group as compared with the control group, similar to the values at years 8 and 9. Among women, the rate ratio was 0.67 (95% CI, 0.38 to 1.14) at 10 years of follow-up, with values of 0.41 to 0.52 in years 7 through 9.

CONCLUSIONS

In this trial involving high-risk persons, lung-cancer mortality was significantly lower among those who underwent volume CT screening than among those who underwent no screening. There were low rates of follow-up procedures for results suggestive of lung cancer. (Funded by the Netherlands Organization of Health Research and Development and others; NELSON Netherlands Trial Register number, NL580.).

Plasma miR-30a-5p as an early novel noninvasive diagnostic and prognostic biomarker for lung cancer

Aim: Circulation miRNAs have become increasingly appreciated in the diagnosis and prognosis of lung cancer. This study aims to identify and evaluate plasma miRNA-30a-5p as an early noninvasive biomarker for the diagnosis and prognosis of lung cancer. Pateints & methods: Expression levels of plasma miRNA 30a-5p were measured by quantitative real-time PCR. Receiver operating characteristic analysis and area under the curve were used to differentiate malignant from benign tumors and from healthy controls. Kaplan-Meier curves and Cox regression were used to determine survival and prognosis. Results: Our results suggest that the level of miRNA-30a-5p in plasma might be a considerable early novel noninvasive diagnostic and prognostic biomarker for lung cancer. Conclusion: Prospective studies must be performed to confirm this new early novel noninvasive diagnostic and prognostic biomarker for lung cancer.

Serous IFNA3 predicts unfavorable prognosis in lung cancer via abnormal activation of AKT signaling

This study addresses the demand through datamining The Cancer Genome Atlas (TCGA) database and elucidates mechanistic involvements of interferon alpha 8 (IFNA8) in lung cancer. The overall survival and disease-free survival of lung cancer patients in respect to IFNA8 expression level were analyzed. IFNA8 expression levels in both serum and tumor tissue were determined by real-time polymerase chain reaction. The diagnostic value of serous IFNA8 in lung cancer was assessed by receiver operating characteristic (ROC) curve analysis. Cell viability and proliferation were measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and Cell Counting Kit-8 assays. in vivo pro-tumor effect of IFNA8 was evaluated using xenograft tumor model. The metastasis-prone behaviors were determined by Transwell chamber assay and tail vein-injection in mice. Protein levels of p-AKT, total AKT, and endogenous reference actin were analyzed by western blot. We uncovered high IFNA8 associated with unfavorable overall survival and disease-free survival in lung cancer patients from TCGA. We further characterized the aberrant over-expression of IFNA8 in both peripheral blood and solid tumor from our clinical patient panel, and ROC analysis suggested its potential diagnostic value. Ectopic over-expression of IFNA8 promoted viability and proliferation in both A549 and H1299 cells in vitro and accelerated xenograft tumor growth in vivo. Furthermore, IFNA8 facilitated migration, invasion, and metastasis of A549 cells in vivo. Mechanistically, we disclosed the over-activation of AKT signaling in IFNA8-proficient A549 cells, inhibition of which completely abolished the pro-tumor effects of IFNA8. We have identified IFNA8 as a novel biomarker for either diagnostic or prognostic purpose in lung cancer, which is mechanistically associated with abnormal activation of AKT signaling.

Ten-year results of the Multicentric Italian Lung Detection trial demonstrate the safety and efficacy of biennial lung cancer screening

BACKGROUND

The Multicentric Italian Lung Detection (MILD) trial demonstrated that prolonged low-dose computed tomography (LDCT) screening could achieve a 39% reduction in lung cancer (LC) mortality. We have here evaluated the long-term results of annual vs. biennial LDCT and the impact of screening intensity on overall and LC-specific mortality at 10 years.

PATIENTS AND METHODS

Between 2005 and 2018, the MILD trial prospectively randomised the 2376 screening arm participants to annual (n = 1190) or biennial (n = 1186) LDCT, for a median screening period of 6.2 years and 23,083 person-years of follow-up. The primary outcomes were 10-year overall and LC-specific mortality, and the secondary end-points were the frequency of advanced-stage and interval LCs.

RESULTS

The biennial LDCT arm showed a similar overall mortality (hazard ratio [HR] 0.80, 95% confidence interval [CI] 0.57-1.12) and LC-specific mortality at 10 years (HR 1.10, 95% CI 0.59-2.05), as compared with the annual LDCT arm. Biennial screening saved 44% of follow-up LDCTs in subjects with negative baseline LDCT, and 38% of LDCTs in all participants, with no increase in the occurrence of stage II-IV or interval LCs.

CONCLUSIONS

The MILD trial provides original evidence that prolonged screening beyond five years with biennial LDCT can achieve an LC mortality reduction comparable to annual LDCT, in subjects with a negative baseline examination.

Screening baseline characteristics of early lung cancer on low-dose computed tomography with computer-aided detection in a Chinese population

OBJECTIVES

This study investigated appropriate baseline characteristics for screening a Chinese population at high risk of early lung cancer, assisted by low-dose computed tomography (LDCT) with computer-aided detection (CAD). Included is a discussion of the viability of using LDCT in the screening guideline and optimizing the guideline.

METHODS

In 2014, 1016 individuals from Sichuan Province were enrolled who satisfied the criteria for high risk according to the 2013 National Comprehensive Cancer Network (NCCN) Guidelines for Non-Small Cell Lung Cancer. From 2014 to 2018, each subject was followed using LDCT with CAD, and pathologically confirmed lung cancers and baseline nodule characteristics (size and density) were recorded. Positive risk was considered a non-calcified solid or part-solid nodule on LDCT with diameter ≥5 mm and ground-glass nodule ≥8 mm, as newly recommended by the China National Lung Cancer Screening Guideline.

RESULTS

From 2014-2018, 13 cases of lung cancer were detected; 5 of these were early stage (38.5%). According to the NCCN criteria, 54 women were included and one of these (1.8%) developed lung cancer. The prevalence of lung cancer was 0.7% at baseline. For the entire population (excluding subjects with a tumor mass at baseline, n = 4), the rate of positivity was 20.4% at baseline; applying the Chinese criteria, the false positive rate was 19.5% (197/1012).

CONCLUSIONS

Further studies are warranted to establish appropriate eligible criteria and management strategies for Chinese populations.

Prolonged lung cancer screening reduced 10-year mortality in the MILD trial: new confirmation of lung cancer screening efficacy

BACKGROUND

The National Lung Screening Trial showed that lung cancer (LC) screening by three annual rounds of low-dose computed tomography (LDCT) reduces LC mortality. We evaluated the benefit of prolonged LDCT screening beyond 5 years, and its impact on overall and LC specific mortality at 10 years.

DESIGN

The Multicentric Italian Lung Detection (MILD) trial prospectively randomized 4099 participants, to a screening arm (n = 2376), with further randomization to annual (n = 1190) or biennial (n = 1186) LDCT for a median period of 6 years, or control arm (n = 1723) without intervention. Between 2005 and 2018, 39 293 person-years of follow-up were accumulated. The primary outcomes were 10-year overall and LC specific mortality. Landmark analysis was used to test the long-term effect of LC screening, beyond 5 years by exclusion of LCs and deaths that occurred in the first 5 years.

RESULTS

The LDCT arm showed a 39% reduced risk of LC mortality at 10 years [hazard ratio (HR) 0.61; 95% confidence interval (CI) 0.39-0.95], compared with control arm, and a 20% reduction of overall mortality (HR 0.80; 95% CI 0.62-1.03). LDCT benefit improved beyond the 5th year of screening, with a 58% reduced risk of LC mortality (HR 0.42; 95% CI 0.22-0.79), and 32% reduction of overall mortality (HR 0.68; 95% CI 0.49-0.94).

CONCLUSIONS

The MILD trial provides additional evidence that prolonged screening beyond 5 years can enhance the benefit of early detection and achieve a greater overall and LC mortality reduction compared with NLST trial.

CLINICALTRIALS.GOV IDENTIFIER

NCT02837809.

HLA-DQB1 expression on tumor cells is a novel favorable prognostic factor for relapse in early-stage lung adenocarcinoma

Background: Postoperative recurrence is the main cause of a poor prognosis in early-stage lung adenocarcinoma (LUAD). Factors that can predict recurrence risk are critically needed.

Materials and methods: In this study, we designed a screening procedure based on gene profile data and performed validation using TCGA and Daping hospital’s cohorts. Differentially expressed genes (DEGs) between patients with recurrence-free survival (RFS) <1 year and RFS >3 years were identified, overlapping genes among these DEGs were selected as candidate biomarkers. A Cox proportional hazards model, immunohistochemistry and Kaplan-Meier survival analysis were performed to validate these biomarkers in two distinct validation sets.

Results:SFTPB, SFTPD, SFTA1P, HLA-DQB1, ITGB8, ANLN, and LRRN1 were overlapped both in TCGA and Daping discovery sets. The Cox proportional hazards model analysis of the TCGA validation set showed that HLA-DQB1 was an independent prognostic factor for RFS (HR=0.686, 95% CI, 0.542–0.868). Immunohistochemistry and Kaplan-Meier analysis in Daping validation sets confirmed HLA-DQB1 expression on tumor cells (not interstitial cells) to be an effective predictor of postoperative recurrence. Further examination revealed that the level of HLA-DQB1 expression on tumor cells was positively correlated with CD4- and CD8-positive lymphocyte infiltration into the tumor.

Conclusion: All results indicate that high expression of HLA-DQB1 on tumor cells is a good prognostic marker in early-stage LUAD, and the mechanism may be related to anti-tumor immune activity.

LUCSO-1-French pilot study of LUng Cancer Screening with low-dose computed tomography in a smokers population exposed to Occupational lung carcinogens: study protocol

INTRODUCTION

Guidelines concerning the follow-up of subjects occupationally exposed to lung carcinogens, published in France in 2015, recommended the setting up of a trial of low-dose chest CT lung cancer screening in subjects at high risk of lung cancer.

OBJECTIVE

To evaluate the organisation of low-dose chest CT lung cancer screening in subjects occupationally exposed to lung carcinogens and at high risk of lung cancer.

METHODS AND ANALYSIS

This trial will be conducted in eight French departments by six specialised reference centres (SRCs) in occupational health. In view of the exploratory nature of this trial, it is proposed to test initially the feasibility and acceptability over the first 2 years in only two SRCs then in four other SRCs to evaluate the organisation. The target population is current or former smokers with more than 30 pack-years (who have quit smoking for less than 15 years), currently or previously exposed to International Agency for Research on Cancer group 1 lung carcinogens, and between the ages of 55 and 74 years. The trial will be conducted in the following steps: (1) identification of subjects by a screening invitation letter; (2) evaluation of occupational exposure to lung carcinogens; (3) evaluation of the lung cancer risk level and verification of eligibility; (4) screening procedure: annual chest CT scans performed by specialised centres and (5) follow-up of CT scan abnormalities.

ETHICS AND DISSEMINATION

This protocol study has been approved by the French Committee for the Protection of Persons. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings.

TRIAL REGISTRATION NUMBER

NCT03562052; Pre-results.

Lung cancer screening: Practice guidelines and insurance coverage are not enough

BACKGROUND AND PURPOSE

Low-dose computed tomography (LDCT) is expected to increase early detection of lung cancer and improve survival. The growth in the number of advanced nurse practitioners (NPs) in primary care settings increases the likelihood that an NP will serve as a patient's provider. This study's purpose was to examine knowledge, attitudes, and practices regarding LDCT among NPs who work in primary care settings.

METHODS

An explanatory, sequential, mixed-method design used a 32-item questionnaire, followed by a semi-structured telephone interview. The development of the survey and interview questions were guided by a conceptual framework representing a temporal sequence for behavior change and potential barriers to guideline adherence.

CONCLUSIONS

Nurse practitioners believe that shared decision making with their high-risk patients about LDCT is within their scope of their practice. Working in time-constrained primary care settings, NPs have limited abilities to improve the uptake of LDCT. Substantial patient barriers exist that deter follow through on providers' recommendation. Disseminating guidelines and authorizing health insurance reimbursement is insufficient.

IMPLICATIONS FOR PRACTICE

Research is needed that investigates the screening process so that barriers can be closely studied. Culture change is needed where early detection has greater value for insurers, providers, and patients.

Persisting new nodules in incidence rounds of the NELSON CT lung cancer screening study

BACKGROUND

The US guidelines recommend low-dose CT (LDCT) lung cancer screening for high-risk individuals. New solid nodules after baseline screening are common and have a high lung cancer probability. Currently, no evidence exists concerning the risk stratification of non-resolving new solid nodules at first LDCT screening after initial detection.

METHODS

In the Dutch-Belgian Randomized Lung Cancer Screening (NELSON) trial, 7295 participants underwent the second and 6922 participants the third screening round. We included participants with solid nodules that were registered as new or <15 mm³ (study detection limit) at previous screens and received additional screening after initial detection, thereby excluding high-risk nodules according to the NELSON management protocol (nodules ≥500 mm³).

RESULTS

Overall, 680 participants with 1020 low-risk and intermediate-risk new solid nodules were included. A total of 562 (55%) new solid nodules were resolving, leaving 356 (52%) participants with a non-resolving new solid nodule, of whom 25 (7%) were diagnosed with lung cancer. At first screening after initial detection, volume doubling time (VDT), volume, and VDT combined with a predefined ≥200 mm³ volume cut-off had high discrimination for lung cancer (VDT, area under the curve (AUC): 0.913; volume, AUC: 0.875; VDT and ≥200 mm³ combination, AUC: 0.939). Classifying a new solid nodule with either ≤590 days VDT or ≥200 mm³ volume positive provided 100% sensitivity, 84% specificity and 27% positive predictive value for lung cancer.

CONCLUSIONS

More than half of new low-risk and intermediate-risk solid nodules in LDCT lung cancer screening resolve. At follow-up, growth assessment potentially combined with a volume limit can be used for risk stratification.

TRIAL REGISTRATION NUMBER

ISRCTN63545820; pre-results.

Identification of Serial DNA Methylation Changes in the Blood Samples of Patients with Lung Cancer

Background

The development of lung cancer results from the interaction between genetic mutations and dynamic epigenetic alterations, although the exact mechanisms are not completely understood. Changes in DNA methylation may be a promising biomarker for early detection and prognosis of lung cancer. We evaluated the serial changes in genome-wide DNA methylation patterns in blood samples of lung cancer patients.

Methods

Blood samples were obtained for three consecutive years from three patients (2 years before, 1 year before, and after lung cancer detection) and from three control subjects (without lung cancer). We used the MethylationEPIC BeadChip method, which covers the 850,000 bp cytosine-phosphate-guanine (CpG) site, to conduct an epigenome-wide analysis. Significant differentially methylated regions (DMRs) were identified using p-values <0.05 in a correlation test identifying serial methylation changes and serial increase or decrease in β value above 0.1 for three consecutive years.

Results

We found three significant CpG sites with differentially methylated β values and 7,105 CpG sites with significant correlation from control patients without lung cancer. However, there were no significant DMRs. In contrast, we found 11 significant CpG sites with differentially methylated β values and 10,562 CpG sites with significant correlation from patients with lung cancer. There were two significant DMRs: cg21126229 (RNF212) and cg27098574 (BCAR1).

Conclusion

This study revealed DNA methylation changes that might be implicated in lung cancer development. The DNA methylation changes may be the possible candidate target regions for the early detection and prevention of lung cancer.

LncRNA ATB promotes the proliferation and metastasis of lung cancer via activation of the p38 signaling pathway

Long non-coding RNA (lncRNA) activated by TGF-β (ATB) has been reported to be widely expressed in different types of cancer; however, the function of ATB in lung cancer remains unclear. In order to elucidate the role of ATB in lung cancer, reverse transcription-quantitative polymerase chain reaction was used to detect the expression of ATB in tumor tissues and corresponding non-tumor lung tissues from 32 patients with lung cancer. Furthermore, the association between the expression of ATB and clinical characteristics was investigated. Cell proliferation was assessed using a cell counting kit-8 assay and cell migration was assessed using a wound healing assays. Epithelial-mesenchymal-transition and mitogen-activated protein kinase signaling pathway activity was examined using western blotting. It was demonstrated that ATB was highly expressed in lung cancer tissues compared with noncancerous tissues, and associated with tumor size and metastasis. It was also demonstrated that ATB was highly expressed in the lung cancer cell lines, A549 and HCC827, compared with the HBE-1 cell line. Suppression of ATB significantly inhibited the proliferation and migratory rate of lung cancer cells. The protein expression levels of p38, E-cadherin and N-cadherin were altered by suppression of ATB expression. Overall, the present study demonstrated that ATB may promote the development of lung cancer.