Feasibility of lung cancer screening in developing countries: challenges, opportunities and way forward

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.

Prediction of Interval Growth of Lung Adenocarcinomas Manifesting as Persistent Subsolid Nodules ≤3 cm Based on Radiomic Features

RATIONALES AND OBJECTIVES

To investigate the prognostic value of the radiomic-based prediction model in predicting the interval growth rate of persistent subsolid nodules (SSNs) with an initial size of ≤ 3 cm manifesting as lung adenocarcinomas.

MATERIALS AND METHODS

A total of 133 patients (mean age, 59.02 years; male, 37.6%) with 133 SSNs who underwent a series of CT examinations at our hospital between 2012 and 2022 were included in this study. Forty-one radiomic features were extracted from each volumetric region of interest. Radiomic features combined with conventional clinical and semantic parameters were then selected for radiomic-based model building. To investigate the model performance in terms of substantial SSN growth and stage shift growth, the model performance was compared by the area under the curve (AUC) obtained by receiver operating characteristic analysis.

RESULTS

The mean follow-up period was 3.62 years. For substantial SSN growth, a radiomic-based model (Model 2) based on clinical characteristics, CT semantic features, and radiomic features yielded an AUCs of 0.869 (95% CI: 0.799-0.922). In comparison with Model 1 (clinical characteristics and CT semantic features), Model 2 performed better than Model 1 for substantial SSN growth (AUC model 1:0.793 versus AUC model 2:0.869, p = 0.028). A radiomic-based nomogram combining sex, follow-up period, and three radiomic features was built for substantial SSN growth prediction. For the stage shift growth, a radiomic-based model (Model 4) based on clinical characteristics, CT semantic features, and radiomic features yielded an AUCs of 0.883 (95% CI: 0.815-0.933). Compared with Model 3 (clinical characteristics and CT semantic features), Model 4 performed better than the model 3 for stage shift growth (AUC model 1: 0.769 versus AUC model 2: 0.883, p = 0.006). A radiomic-based nomogram combining the initial nodule size, SSN classification, follow-up period, and three radiomic features was built to predict the stage shift growth.

CONCLUSION

Radiomic-based models have superior utility in estimating the prognostic interval growth of patients with early lung adenocarcinomas (≤ 3 cm) than conventional clinical-semantic models in terms of substantial interval growth and stage shift growth, potentially guiding clinical decision-making with follow-up strategies of SSNs in personalized precision medicine.

microRNAs in exhaled breath condensate for diagnosis of lung cancer in a resource-limited setting: a concise review

Lung cancer is one of the common cancers globally with high mortality and poor prognosis. Most cases of lung cancer are diagnosed at an advanced stage due to limited diagnostic resources. Screening modalities, such as sputum cytology and annual chest radiographs, have not proved sensitive enough to impact mortality. In recent years, annual low-dose computed tomography has emerged as a potential screening tool for early lung cancer detection, but it may not be a feasible option for developing countries. In this context, exhaled breath condensate (EBC) analysis has been evaluated recently as a noninvasive tool for lung cancer diagnosis. The breath biomarkers also have the advantage of differentiating various types and stages of lung cancer. Recent studies have focused more on microRNAs (miRNAs) as they play a key role in tumourigenesis by regulating the cell cycle, metastasis and angiogenesis. In this review, we have consolidated the current published literature suggesting the utility of miRNAs in EBC for the detection of lung cancer.

Lung Cancer Screening in Asia: An Expert Consensus Report

INTRODUCTION

The incidence and mortality of lung cancer are highest in Asia compared with Europe and USA, with the incidence and mortality rates being 34.4 and 28.1 per 100,000 respectively in East Asia. Diagnosing lung cancer at early stages makes the disease amenable to curative treatment and reduces mortality. In some areas in Asia, limited availability of robust diagnostic tools and treatment modalities, along with variations in specific health care investment and policies, make it necessary to have a more specific approach for screening, early detection, diagnosis, and treatment of patients with lung cancer in Asia compared with the West.

METHOD

A group of 19 advisors across different specialties from 11 Asian countries, met on a virtual Steering Committee meeting, to discuss and recommend the most affordable and accessible lung cancer screening modalities and their implementation, for the Asian population.

RESULTS

Significant risk factors identified for lung cancer in smokers in Asia include age 50 to 75 years and smoking history of more than or equal to 20 pack-years. Family history is the most common risk factor for nonsmokers. Low-dose computed tomography screening is recommended once a year for patients with screening-detected abnormality and persistent exposure to risk factors. However, for high-risk heavy smokers and nonsmokers with risk factors, reassessment scans are recommended at an initial interval of 6 to 12 months with subsequent lengthening of reassessment intervals, and it should be stopped in patients more than 80 years of age or are unable or unwilling to undergo curative treatment.

CONCLUSIONS

Asian countries face several challenges in implementing low-dose computed tomography screening, such as economic limitations, lack of efforts for early detection, and lack of specific government programs. Various strategies are suggested to overcome these challenges in Asia.

The global burden of lung cancer: current status and future trends

Lung cancer is the leading cause of cancer-related death worldwide. However, lung cancer incidence and mortality rates differ substantially across the world, reflecting varying patterns of tobacco smoking, exposure to environmental risk factors and genetics. Tobacco smoking is the leading risk factor for lung cancer. Lung cancer incidence largely reflects trends in smoking patterns, which generally vary by sex and economic development. For this reason, tobacco control campaigns are a central part of global strategies designed to reduce lung cancer mortality. Environmental and occupational lung cancer risk factors, such as unprocessed biomass fuels, asbestos, arsenic and radon, can also contribute to lung cancer incidence in certain parts of the world. Over the past decade, large-cohort clinical studies have established that low-dose CT screening reduces lung cancer mortality, largely owing to increased diagnosis and treatment at earlier disease stages. These data have led to recommendations that individuals with a high risk of lung cancer undergo screening in several economically developed countries and increased implementation of screening worldwide. In this Review, we provide an overview of the global epidemiology of lung cancer. Lung cancer risk factors and global risk reduction efforts are also discussed. Finally, we summarize lung cancer screening policies and their implementation worldwide.

Effective lung cancer control: An unaccomplished challenge in cancer research

Lung cancer has always been a burden to the society since its non-effective early detection and poor survival status. Different imaging modalities such as computed tomography scan have been practiced for lung cancer detection. This review focuses on the importance of sputum cytology for early lung cancer detection and biomarkers effective in sputum samples. Published articles were discussed in light of the potential of sputum cytology for lung cancer early detection and risk assessment across high-risk groups. Recent developments in sample processing techniques have documented a clear potential to improve or refine diagnosis beyond that achieved with conventional sputum cytology examination. The diagnostic potential of sputum cytology may be exploited better through the standardization and automation of sputum preparation and analysis for application in routine laboratory practices and clinical trials. The challenging aspects in sputum cytology as well as sputum-based molecular markers are to ensure appropriate standardization and validation of the processing techniques.

Development of Debiasing Technique for Lung Nodule Chest X-ray Datasets to Generalize Deep Learning Models

Screening programs for early lung cancer diagnosis are uncommon, primarily due to the challenge of reaching at-risk patients located in rural areas far from medical facilities. To overcome this obstacle, a comprehensive approach is needed that combines mobility, low cost, speed, accuracy, and privacy. One potential solution lies in combining the chest X-ray imaging mode with federated deep learning, ensuring that no single data source can bias the model adversely. This study presents a pre-processing pipeline designed to debias chest X-ray images, thereby enhancing internal classification and external generalization. The pipeline employs a pruning mechanism to train a deep learning model for nodule detection, utilizing the most informative images from a publicly available lung nodule X-ray dataset. Histogram equalization is used to remove systematic differences in image brightness and contrast. Model training is then performed using combinations of lung field segmentation, close cropping, and rib/bone suppression. The resulting deep learning models, generated through this pre-processing pipeline, demonstrate successful generalization on an independent lung nodule dataset. By eliminating confounding variables in chest X-ray images and suppressing signal noise from the bone structures, the proposed deep learning lung nodule detection algorithm achieves an external generalization accuracy of 89%. This approach paves the way for the development of a low-cost and accessible deep learning-based clinical system for lung cancer screening.

Deep Learning-Based Digitally Reconstructed Tomography of the Chest in the Evaluation of Solitary Pulmonary Nodules: A Feasibility Study

RATIONALE AND OBJECTIVES

Computed tomography (CT) is preferred for evaluating solitary pulmonary nodules (SPNs) but access or availability may be lacking, in addition, overlapping anatomy can hinder detection of SPNs on chest radiographs. We developed and evaluated the clinical feasibility of a deep learning algorithm to generate digitally reconstructed tomography (DRT) images of the chest from digitally reconstructed frontal and lateral radiographs (DRRs) and use them to detect SPNs.

METHODS

This single-institution retrospective study included 637 patients with noncontrast helical CT of the chest (mean age 68 years, median age 69 years, standard deviation 11.7 years; 355 women) between 11/2012 and 12/2020, with SPNs measuring 10-30 mm. A deep learning model was trained on 562 patients, validated on 60 patients, and tested on the remaining 15 patients. Diagnostic performance (SPN detection) from planar radiography (DRRs and CT scanograms, PR) alone or with DRT was evaluated by two radiologists in an independent blinded fashion. The quality of the DRT SPN image in terms of nodule size and location, morphology, and opacity was also evaluated, and compared to the ground-truth CT images RESULTS: Diagnostic performance was higher from DRT plus PR than from PR alone (area under the receiver operating characteristic curve 0.95-0.98 versus 0.80-0.85; p < 0.05). DRT plus PR enabled diagnosis of SPNs in 11 more patients than PR alone. Interobserver agreement was 0.82 for DRT plus PR and 0.89 for PR alone; and interobserver agreement for size and location, morphology, and opacity of the DRT SPN was 0.94, 0.68, and 0.38, respectively.

CONCLUSION

For SPN detection, DRT plus PR showed better diagnostic performance than PR alone. Deep learning can be used to generate DRT images and improve detection of SPNs.

MicroRNAs in exhaled breath condensate: A pilot study of biomarker detection for lung cancer

INTRODUCTION

Quantitation of microRNAs secreted by lung cells can provide valuable information regarding lung health. Exhaled breath condensate (EBC) offers a non-invasive way to sample the secreted microRNAs, and could be used as diagnostic tools for lung cancer.

MATERIALS & METHODS

EBC samples from twenty treatment-naïve patients with pathologically confirmed lung cancer and twenty healthy subjects were profiled for miRNAs expression. Selected microRNAs were further validated, using quantitative-PCR, in an independent set of 10 subjects from both groups.

RESULTS

A total of 78 miRNAs were found to be significantly upregulated in the EBC of lung cancer patients compared to the control group. Six of these 78 miRNAs were shortlisted for validation. Of these, miR-31-3p, let7i, and miR-449c were significantly upregulated, exhibited good discriminatory power.

DISCUSSION

Differential expression of miRNAs secreted by lung cells could be quantitated in EBC samples, and could be used as a potential non-invasive tool for early diagnosis of lung cancer.

AI Improves Nodule Detection on Chest Radiographs in a Health Screening Population: A Randomized Controlled Trial

Background The impact of artificial intelligence (AI)-based computer-aided detection (CAD) software has not been prospectively explored in real-world populations. Purpose To investigate whether commercial AI-based CAD software could improve the detection rate of actionable lung nodules on chest radiographs in participants undergoing health checkups. Materials and Methods In this single-center, pragmatic, open-label randomized controlled trial, participants who underwent chest radiography between July 2020 and December 2021 in a health screening center were enrolled and randomized into intervention (AI group) and control (non-AI group) arms. One of three designated radiologists with 13-36 years of experience interpreted each radiograph, referring to the AI-based CAD results for the AI group. The primary outcome was the detection rate, that is, the number of true-positive radiographs divided by the total number of radiographs, of actionable lung nodules confirmed on CT scans obtained within 3 months. Actionable nodules were defined as solid nodules larger than 8 mm or subsolid nodules with a solid portion larger than 6 mm (Lung Imaging Reporting and Data System, or Lung-RADS, category 4). Secondary outcomes included the positive-report rate, sensitivity, false-referral rate, and malignant lung nodule detection rate. Clinical outcomes were compared between the two groups using univariable logistic regression analyses. Results A total of 10 476 participants (median age, 59 years [IQR, 50-66 years]; 5121 men) were randomized to an AI group (n = 5238) or non-AI group (n = 5238). The trial met the predefined primary outcome, demonstrating an improved detection rate of actionable nodules in the AI group compared with the non-AI group (0.59% [31 of 5238 participants] vs 0.25% [13 of 5238 participants], respectively; odds ratio, 2.4; 95% CI: 1.3, 4.7; P = .008). The detection rate for malignant lung nodules was higher in the AI group compared with the non-AI group (0.15% [eight of 5238 participants] vs 0.0% [0 of 5238 participants], respectively; P = .008). The AI and non-AI groups showed similar false-referral rates (45.9% [56 of 122 participants] vs 56.0% [56 of 100 participants], respectively; P = .14) and positive-report rates (2.3% [122 of 5238 participants] vs 1.9% [100 of 5238 participants]; P = .14). Conclusion In health checkup participants, artificial intelligence-based software improved the detection of actionable lung nodules on chest radiographs. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Auffermann in this isssue.

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.

The Effect of Body Mass Index on Survival in Lung Cancer

The prognostic significance of body mass index in lung cancer and the direction of this relationship are not yet clear. This study aimed to evaluate the relationship between BMI and overall survival time of advanced-stage lung cancer patients treated in a center in Turkey, a developing country. In this study, the data of 225 patients diagnosed with stage III or stage IV lung cancer between 2016 and 2020 were analyzed. The effects of BMI and other variables on survival were examined by Cox regression analysis for NSCLC and SCLC. For NSCLC and SCLC, being underweight compared to the normal group, being diagnosed at a more advanced stage, and having a worse performance score were associated with a significantly higher risk of death. Other variables significantly associated with survival were gender, type of radiotherapy for NSCLC, age group, and family history for SCLC. This study showed that being underweight relative to the normal group was associated with worse survival for NSCLC and SCLC but did not support the obesity paradox. Studies that are representative of all BMI categories and free of bias are needed to understand the BMI-lung cancer survival relationship clearly.

Lung Cancer in Non-Smokers: Clinicopathological and Survival Differences from Smokers

Background Lung cancer in non-smokers is a clinically distinct entity based on unique epidemiology, clinicopathology, genetics, treatment response, and outcome. Data from Indian centres are scarce. The objective of this study was to compare the frequency, clinical characteristics, driver mutations, and survival of non-smoking and smoking lung cancer patients treated at a tertiary cancer centre in North India. Methodology Two years of data on 724 consecutive lung cancer patients were assessed. Clinical, demographics, smoking history, and EGFR and ALK mutation test results were collected. Descriptive and inferential statistics were applied. Survival analysis was performed using the Kaplan-Meier method. Results Non-smokers comprised 40.9% of the study sample. Non-smokers were more likely than smokers to experience disease onset at a younger age (P = 0.004) and metastasis (P < 0.001). The tumor histology showed significant differences (P < 0.001), with non-smokers more likely to be diagnosed with adenocarcinoma (77.4%), while squamous and small cell histologies were commonly found among smokers (37.6% and 13.8%, respectively). The EGFR mutation and ALK rearrangement rates in the cohort were 23.3% and 10.1%, respectively, and were more frequent in non-smoking patients. Overall, 10-year survival was 7%, with a significantly better survival rate of non-smokers than smokers (median survival time of 15.13 vs 10.17 months; P = 0.012). Conclusions About four out of 10 patients diagnosed with lung cancer at our centre were non-smokers. They were more often young, diagnosed at an advanced stage, with predominantly adenocarcinoma histology, and had a threefold higher frequency of EGFR mutations than smokers. In our cohort, non-smokers appear to be a targetable group with better survival than smokers.

Microbial dysbiosis and epigenetics modulation in cancer development - A chemopreventive approach

An overwhelming number of research articles have reported a strong relationship of the microbiome with cancer. Microbes have been observed more commonly in the body fluids like urine, stool, mucus of people with cancer compared to the healthy controls. The microbiota is responsible for both progression and suppression activities of various diseases. Thus, to maintain healthy human physiology, host and microbiota relationship should be in a balanced state. Any disturbance in this equilibrium, referred as microbiome dysbiosis becomes a prime cause for the human body to become more prone to immunodeficiency and cancer. It is well established that some of these microbes are the causative agents, whereas others may encourage the formation of tumours, but very little is known about how these microbial communications causing change at gene and epigenome level and trigger as well as encourage the tumour growth. Various studies have reported that microbes in the gut influence DNA methylation, DNA repair and DNA damage. The genes and pathways that are altered by gut microbes are also associated with cancer advancement, predominantly those implicated in cell growth and cell signalling pathways. This study exhaustively reviews the current research advancements in understanding of dysbiosis linked with colon, lung, ovarian, breast cancers and insights into the potential molecular targets of the microbiome promoting carcinogenesis, the epigenetic alterations of various potential targets by altered microbiota, as well as the role of various chemopreventive agents for timely prevention and customized treatment against various types of cancers.

Challenges and Suggestions in Management of Lung and Liver Cancer in Uzbekistan: The Second Report of the Uzbekistan-Korea Oncology Consortium

The health burden of cancer increases in Uzbekistan as the country develops and the life expectancy increases. Management of such a burden requires efficient screening, treatment optimization, and investigation of the causes of cancer. The Ministry of Health of Uzbekistan formed an advisory consortium, including clinical oncology and healthcare management experts from Uzbekistan and South Korea, to design a strategy for cancer management. Our consortium has analyzed six cancer types with high morbidity and mortality in Uzbekistan by classifying them into three categories (breast, cervical (gynecologic cancers), lung, liver (cancer common in men), stomach, and colorectal cancers (gastrointestinal cancers)). Lung and liver cancers are common causes of death in men after middle age-they can yield a serious health burden on the country and ruin the livelihood of families. In this review, we will analyze the oncologic literature and suggest practical recommendations for the treatment and prevention of lung and liver cancer in Uzbekistan. Data from South Korea, which has conducted nationwide screening for two decades and made progress in improving prognosis, will be discussed as a comparative control.

Radiology for Thoracic Conditions in Low- and Middle-Income Countries

With a disproportionately high burden of global morbidity and mortality caused by chronic respiratory diseases (CRDs) in low and middle-income countries (LMICs), access to radiological services is of critical importance for screening, diagnosis, and treatment guidance.

Lung Cancer Management in Low and Middle-Income Countries

Lung cancer is an increasing problem in the developing world due to rising trends in smoking, high incidence of air pollution, lack of awareness and screening, delayed presentation, and diagnosis at the advanced stage. Even after diagnosis, there are disparities in access to health care facilities and inequitable distribution of resources and treatment options. In addition, the shortage of trained personnel and infrastructure adds to the challenges faced by patients with lung cancer in these regions. A multi-pronged effort targeting tobacco cessation, health promotion and awareness, capacity building, and value-based care are the need of the hour.

Role of low dose computed tomography on lung cancer detection and mortality - an updated systematic review and meta-analysis

Chest low dose computed tomography (LDCT) is reported to be a sensitive tool for the detection of lung cancer at asymptomatic stage, thus reducing mortality. The review assesses the effect of LDCT screening on all-cause mortality, lung cancer mortality and incidence rates. We conducted literature searches of PubMed, SCOPUS, and the Cochrane Library from inception through January 2020 to identify relevant studies assessing the diagnostic accuracy of LDCT for lung cancer. We used Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for reporting this meta-analysis and review. The inclusion criteria were a) Randomized control trials, b) Comparing LDCT to any other form of screening or standard of care, and (c) Primary outcome studied: all-cause mortality, lung cancer-specific mortality, rate of early detection of lung cancer. A total of 11 studies encompassing 97,248 patients were included. When compared with controls (no screening or CXR), LDCT screening was associated with statistically significant reduction in lung cancer mortality (pooled RR 0.86; 95% CI 0.75-0.98); low heterogeneity was observed (I2= 27.86). However, LDCT screening was not associated with statistically significant reduction in all-cause mortality (RR =0.96; 95% CI: 0.92 -1.01). Notably, the LDCT screening was associated with statistically significant increase in lung cancer detection (RR =1.76; 95% CI: 1.14-2.72). LDCT screening has the potential to reduce mortality due to lung cancer among high-risk individuals. LDCT could be considered as a screening modality after careful assessment of other factors like prevalence of TB, proportion of high-risk population, cost, access and availability of LDCT.

Lung Cancer Screening Considerations During Respiratory Infection Outbreaks, Epidemics or Pandemics: An International Association for the Study of Lung Cancer Early Detection and Screening Committee Report

After the results of two large, randomized trials, the global implementation of lung cancer screening is of utmost importance. However, coronavirus disease 2019 infections occurring at heightened levels during the current global pandemic and also other respiratory infections can influence scan interpretation and screening safety and uptake. Several respiratory infections can lead to lesions that mimic malignant nodules and other imaging changes suggesting malignancy, leading to an increased level of follow-up procedures or even invasive diagnostic procedures. In periods of increased rates of respiratory infections from severe acute respiratory syndrome coronavirus 2 and others, there is also a risk of transmission of these infections to the health care providers, the screenees, and patients. This became evident with the severe acute respiratory syndrome coronavirus 2 pandemic that led to a temporary global stoppage of lung cancer and other cancer screening programs. Data on the optimal management of these situations are not available. The pandemic is still ongoing and further periods of increased respiratory infections will come, in which practical guidance would be helpful. The aims of this report were: (1) to summarize the data available for possible false-positive results owing to respiratory infections; (2) to evaluate the safety concerns for screening during times of increased respiratory infections, especially during a regional outbreak or an epidemic or pandemic event; (3) to provide guidance on these situations; and (4) to stimulate research and discussions about these scenarios.

Artificial intelligence for early diagnosis of lung cancer through incidental nodule detection in low- and middle-income countries-acceleration during the COVID-19 pandemic but here to stay

Although the coronavirus disease of 2019 (COVID-19) pandemic had profound pernicious effects, it revealed deficiencies in health systems, particularly among low- and middle-income countries (LMICs). With increasing uncertainty in healthcare, existing unmet needs such as poor outcomes of lung cancer (LC) patients in LMICs, mainly due to late stages at diagnosis, have been challenging-necessitating a shift in focus for judicious health resource utilization. Leveraging artificial intelligence (AI) for screening large volumes of pulmonary images performed for noncancerous reasons, such as health checks, immigration, tuberculosis screening, or other lung conditions, including but not limited to COVID-19, can facilitate easy and early identification of incidental pulmonary nodules (IPNs), which otherwise could have been missed. AI can review every chest X-ray or computed tomography scan through a trained pair of eyes, thus strengthening the infrastructure and enhancing capabilities of manpower for interpreting images in LMICs for streamlining accurate and early identification of IPNs. AI can be a catalyst for driving LC screening with enhanced efficiency, particularly in primary care settings, for timely referral and adequate management of coincidental IPN. AI can facilitate shift in the stage of LC diagnosis for improving survival, thus fostering optimal health-resource utilization and sustainable healthcare systems resilient to crisis. This article highlights the challenges for organized LC screening in LMICs and describes unique opportunities for leveraging AI. We present pilot initiatives from Asia, Latin America, and Russia illustrating AI-supported IPN identification from routine imaging to facilitate early diagnosis of LC at a potentially curable stage.

Discovery of bletillain, an unusual benzyl polymer with significant autophagy-inducing effects in A549 lung cancer cells through the Akt/GSK-3β/β-catenin signaling pathway

Lung cancer is one of the most malignant tumors with the highest mortality and morbidity. The tubers of Bletilla striata are known as "an excellent medicine for lung diseases" in traditional Chinese medicine. This study performed a targeted study to explore compounds with anti-lung cancer activity and the molecular mechanisms using A549 cells. Eighteen bibenzyl derivatives, including four new compounds (13, 14, 16, and 18), were isolated from the tubers of B. striata. Analysis of the structure-activity relationship indicated that the cytotoxicity of the bibenzyls against A549 cells increased gradually as the number of the benzyl groups in the structures increased. Bletillain (18), an unusual benzyl polymer, was found to be the most active compound. Further flow cytometric analysis, dual-luciferase assays, real-time PCR assays, and western blot assays revealed that bletillain induced autophagy in A549 cells by regulating the Akt/GSK-3β/β-catenin signaling pathway. Beclin 1, LC3, and p62 are downstream autophagy factors of Akt, and Beclin 1 was the key autophagy factor. These results suggested that bibenzyls of B. striata play important roles in the treatment of lung cancer and provided scientific evidence illustrating why the tubers of B. striata are a suitable medicine for the treatment of lung cancer in traditional Chinese medicine.

LDCT Screening in Smokers in India-A Pilot, Proof-of-Concept Study

Aim The aim of the study is to assess the effectiveness of low dose CT scan (LDCT) to pick up nodules and carcinomas in smokers in India.

Methods A retrospective study of 350 smokers scanned with LDCT was performed in a private practice center in Mumbai, India. Their demographic profile, smoking history in pack-years, lung nodules, and associated findings/superimposed complications were recorded and analyzed. The nodules were assigned the appropriate Lung-RADS category and results of the patients undergoing biopsy were recorded.

Results Of the 350 smokers, 15 (4%) were women . The mean age was 61 years (32–90 years) with a mean smoking history of 22 pack-years (1–160 pack-years). Lung nodules were found in 335 (93%) smokers, with Lung-RADS category 1 nodules seen in 117 (36%), category 2 in 133 (41%), category 3 in 29 (9%), and category 4 in 46 (14%) of positive scans. Seven of the category 4 patients who underwent biopsy showed carcinoma, with a mean smoking history of 30 pack years. Superimposed interstitial lung disease, airways diseases, and infections were also seen in the scans and recorded.

Discussion It has been proven in the Western world that screening for lung cancer with LDCT saves lives with early pick-up of malignant nodules. This pilot study from India, shows that even in a tuberculosis endemic country, LDCT picks up malignant lung nodules early and saves lives.

Conclusion Smokers with a more than 20 pack years history have a higher incidence of lung nodules, which may represent carcinoma, in a tuberculosis endemic country like India, as has been proven in other countries in the Western world. Larger studies and trials may be performed to elaborate further on this proof-of-concept study.

Metastatic patterns and prognosis of young lung cancer patients: a population-based study by age

Background

We aimed to examine the different metastatic patterns and corresponding survival outcomes between all ages of young (aged <60 years) and elderly lung cancer patients.

Methods

Lung cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 were divided into a young and elderly group. The young group was subdivided into four consecutive subgroups. Baseline characteristics were analyzed by the Chi-square test. Survival differences were evaluated by Kaplan-Meier curves and Cox proportional hazards models.

Results

Of the total 200,362 lung cancer patients, 155,348 were elderly patients and 45,014 were young patients, including 3,461 aged <45 years, 5,697 aged 45–49 years, 13,645 aged 50–54 years, and 22,211 aged 55–59 years. Compared with elderly lung cancer patients, extrathoracic metastases were significantly more frequent in each younger group, irrespective of the site and number of extrathoracic metastatic organs. Regardless of metastasis patterns, young ages were independent prognostic factors of lung cancer-specific survival (LCSS) [<45 years: hazard ratio (HR): 0.70; 45–49 years: HR: 0.87; 50–54 years: HR: 0.90; 55–59 years: HR: 0.93, all P values were <0.001]. In each age subgroup, patients with multi-organ extrathoracic metastasis had the worst LCSS.

Conclusions

Young lung cancer patients across all ages were at increased risk of extrathoracic metastasis, especially multi-organ patterns, but had a reduced risk of lung cancer-related death compared to elderly patients. Regular and meticulous monitoring of potential metastasized organs is required in young lung cancer patients throughout the follow-up period.

DNA repair genes are associated with tumor tissue differentiation and immune environment in lung adenocarcinoma: a bioinformatics analysis based on big data

Background

Lung adenocarcinoma (LUAD) is the most common type of lung cancer. DNA repair genes (DRGs) is important in lung cancer. The relationship between the immune environment and the expression levels of DRGs in LUAD remains unclear. The purpose of this study is to assess the relationship between DRGs and the immune environment and clinical characteristics of LUAD.

Methods

Data of 169 LUAD cases were obtained from cbioportal. The RNA-seq data came from the The Cancer Genome Atlas (TCGA) database. We collected DRGs from the Reactom database (KW0037, Reactom.org). The 302 genes expressed in each sample were analyzed by hierarchical clustering and grouped using the Gene Cluster 3.0 program. The Java Treeview program was used to generate heat maps of cluster indications and tumor staging patterns. GraphPad Prism 8 was used to draw survival curves and compare overall survival (OS). For single genes, an OS difference analysis between low and high expression populations was performed in GraphPad Prism 8.

Results

Matrix clustering showed no difference in the prognosis of the two clusters. The comparison of subgroups showed that Subcluster 1 (SC1) had the best prognosis, and Subcluster 2 (SC2) had the worst. There was a significant difference in tumor grades between Cluster 1 and Cluster 2 (P=0.01). There were significant differences in smoking status, histological grade and adenocarcinoma subtype among subgroups. In Subcluster 3 (SC3), the proportion of poorly differentiated cases was highest. Immunological index analysis showed that there were significant differences between Cluster 1 and Cluster 2 in interferon, macrophages, monocytes, neutrophils, natural killer (NK) cells, and T cells. Tumor purity, interferon, macrophages, monocytes, neutrophils, NK cells, T cells, translation, and proliferation all showed significant differences between subgroups. In SC2, the proliferation index increased (0.082 vs. 0.070); the protein translation index decreased (0.134 vs. 0.137); and the interferon level increased (0.099 vs. 0.097). In SC3, the proliferation index decreased (0.076 vs. 0.071); the protein translation index decreased (0.140 vs. 0.136); and the level of neutrophils increased (0.083 vs. 0.086).

Conclusions

The differences of DRGs in LUAD are related to tissue differentiation and immune indicators but not to prognosis.

A model based on the quantification of complement C4c, CYFRA 21-1 and CRP exhibits high specificity for the early diagnosis of lung cancer

Lung cancer screening detects early-stage cancers, but also a large number of benign nodules. Molecular markers can help in the lung cancer screening process by refining inclusion criteria or guiding the management of indeterminate pulmonary nodules. In this study, we developed a diagnostic model based on the quantification in plasma of complement-derived fragment C4c, cytokeratin fragment 21-1 (CYFRA 21-1) and C-reactive protein (CRP). The model was first validated in two independent cohorts, and showed a good diagnostic performance across a range of lung tumor types, emphasizing its high specificity and positive predictive value. We next tested its utility in two clinically relevant contexts: assessment of lung cancer risk and nodule malignancy. The scores derived from the model were associated with a significantly higher risk of having lung cancer in asymptomatic individuals enrolled in a computed tomography (CT)-screening program (OR = 1.89; 95% CI = 1.20-2.97). Our model also served to discriminate between benign and malignant pulmonary nodules (AUC: 0.86; 95% CI = 0.80-0.92) with very good specificity (92%). Moreover, the model performed better in combination with clinical factors, and may be used to reclassify patients with intermediate-risk indeterminate pulmonary nodules into patients who require a more aggressive work-up. In conclusion, we propose a new diagnostic biomarker panel that may dictate which incidental or screening-detected pulmonary nodules require a more active work-up.

Relevance of PD-L1 Non-Coding Polymorphisms on the Prognosis of a Genetically Admixed NSCLC Cohort

Purpose

Although non-small cell lung cancer (NSCLC) remains a deadly disease, new predictive biomarkers have emerged to assist in managing the disease, of which one of the most promising is the programmed death‐ligand 1 (PD-L1). Each, PD-L1 variant seem to modulate the function of immune checkpoints differently and affect response to adjuvant treatment and outcome in NSCLC patients. We thus investigated the influence of these PD-L1 genetic variations in genetically admixed NSCLC tissue samples, and correlated these values with clinicopathological characteristics, including prognosis.

Materials and Methods

We evaluated PD-L1 non-coding genetic variants and protein expression in lung adenocarcinomas (ADC), squamous cell carcinomas (SqCC), and large cell carcinomas (LCC) in silico. Microarray paraffin blocks from 70 samples of ADC (N=33), SqCC (N=24), and LCC (N=13) were used to create PD-L1 multiplex immunofluorescence assays with a Cell Signaling E1L3N clone. Fifteen polymorphisms of the PD-L1 gene were investigated by targeted sequencing and evaluated in silico using dedicated tools.

Results

Although PD-L1 polymorphisms seemed not to interfere with protein expression, PD-L1 expression varied among different histological subtypes, as did clinical outcomes, with the rs4742098A>G, rs4143815G>C, and rs7041009G>A variants being associated with relapse (P=0.01; P=0.05; P=0.02, respectively). The rs7041009 GG genotype showed a significant correlation with younger and alive patients compared to carriers of the A allele (P=0.02 and P<0.01, respectively). The Cox regression model showed that the rs7041009 GG genotype may influence OS (P<0.01) as a co-dependent factor associated with radiotherapy and recurrence in NSCLC patients. Furthermore, the Kaplan–Meier survival curves showed that rs7041009 and rs4742098 might impact PPS in relapsed patients. In silico approaches identified the variants as benign.

Conclusion

PD-L1 non-coding variants play an important role in modulating immune checkpoint function and may be explored as immunotherapy biomarkers. We highlight the rs7041009 variant, which impacts OS and PPS in NSCLC patients.

Feasibility of implementing a national lung cancer screening program: Interim results from the Korean Lung Cancer Screening Project (K-LUCAS)

Background

Lung cancer screening conducted in high-risk group using low-dose computer tomography (LDCT) has been reported as an effective method to reduce lung cancer mortality in two large randomized-control trials. However, the effectiveness is uncertain when lung cancer screening is expanded to a nationwide population-based program.

Methods

The Korean Lung Cancer Screening Project (K-LUCAS) is a single-arm cohort study that was conducted from February 2017 to evaluate the feasibility of implementing an organized national lung cancer screening program in Korea. High-risk population aged 55–74 years with more than a 30-pack-year smoking history was recruited. Smoking history was obtained from administering questionnaires at national health screening programs or public smoking cessation programs which are already established programs in Korea. The screening results were reported using the Lung Imaging Reporting and Data System (Lung-RADS), suggested by the American College of Radiology. K-LUCAS was performed by a network-based diagnosis supporting system using a computer-aided detection (CAD) program to maintain screening quality. Current smokers were provided with mandatory smoking counseling.

Results

Among 71,829 participants aged 50 years or older in the national health screening program, 5,975 (8.3%) were eligible for lung cancer screening. Among them, 1,062 (17.8%) refused to participate in K-LUCAS. Additionally, 779 participants were recruited in the smoking cessation program. Thus, a total of 5,692 eligible high-risk participants were recruited in this study. Among them, 865 (15.2%) had positive screening results, which requires a further examination; 529 (9.3%) had Lung-RADS category 3 (indeterminate), and 336 (5.9%) had category 4 (suspicious of lung cancer); 42 (0.7%) had confirmed lung cancer. Approximately 66.7% had early-stage lung cancer: 24 (57.1%), stage I and 4 (9.5%), stage II. Six (1.1%) patients developed complications at the time of diagnosis, including one death. The anxiety level related to cancer screening was low. Participation in screening encouraged motivation to quit smoking.

Conclusions

K-LUCAS provided promising evidence supporting the implementation of a national lung cancer screening program to detect early stage lung cancer and promote smoking cessation for participants in Asian population.

Assessment of lung cancer risk factors and mortality in Qatar: A case series study

BACKGROUND

The global burden of cancer has exponentially increased over the last few years. In 2018 alone, approximately more than half of the 18.1 million individuals who had cancer succumbed to it. Lung cancer cases and fatalities are particularly on the rise. Therefore, exploring the factors surrounding lung cancer mortality is of utmost importance.

AIMS

We investigate the clinicopathological and epidemiological characteristics of patients with lung cancer undergoing treatments, and their 5-year survival rates from a case series study in Qatar.

METHODS AND RESULTS

All patients' data (between January 2010 and December 2014) in this case series study were retrieved from Al-Amal Hospital database. Kaplan-Meier survival plots, life tables and Cox regression were utilized for the statistical analysis. A total of 229 lung cancer patients were included in this study; of which 23.6% are Qatari (40 males and 14 females) and 76.4% non-Qatari (133 males and 42 females). Approximately 57.6% of our patients received at least one type of treatment. We observe a 5-year survival rate of 9.4% in our patient cohort. We also observe other predictive factors, such as distant metastasis (adjusted hazards ratio, HR = 2.414, 95% CI: 1.035-5.632), smoking status (adjusted HR = 3.909, 95% CI: 1.664-9.180) and the treatment history (adjusted HR = 0.432, 95% CI: 0.270-0.691), to be significant.

CONCLUSION

Lung cancer is a prevalent health condition in Qatar, particularly owing to the rising use of tobacco in the country. The survival rate for lung cancer patients in this country is lower, compared to the global average. Moreover, several factors such as distant metastasis, smoking status, and treatment history are associated with lung cancer survival in Qatar.

Reduced expression of circRNA novel_circ_0005280 and its clinical value in the diagnosis of non-small cell lung cancer

Background

Circular RNAs (circRNAs) are a class of novel RNAs with important biologic functions. The aberrant expression of circRNAs has been implicated in human diseases; however, the clinical significance of circRNAs in non-small cell lung cancer (NSCLC) is still unclear. The aim of the present study was to evaluate the expression and clinical implications of novel_circ_0005280 in patients with NSCLC.

Methods

We evaluated differential circRNA expression in cancer and adjacent normal tissues from 3 patients with NSCLC via RNA sequencing. Among these circRNAs, 17 and 64 circRNAs showed higher and lower expressions, respectively. Novel_circ_0005280 expression in cancer tissues (n=41) was examined using quantitative real-time polymerase chain reaction, and the results are presented in the form of paired graph and scatter graph and its correlation with clinicopathological features and patient prognosis was analyzed by drawing receiver-operating characteristic (ROC) curve and Kaplan-Meier survival analysis.

Results

Novel_circ_0005280 expression was significantly decreased in NSCLC tumor tissues (n=41, obtained via biopsies), compared with adjacent normal tissues (n=27). Novel_circ_0005280 expression was correlated with tumor diameter and age. The area under the receiver-operating characteristic curve, cutoff, sensitivity, and specificity of novel_circ_0005280 were 0.944, 10.23, 85.2%, and 95.1%, respectively. Low novel_circ_0005280 expression was associated with a worse prognosis.

Conclusions

Novel_circ_0005280 may be a useful biomarker for the diagnosis and prognosis of NSCLC.

Estimating rotation angle from asymmetric projection of chest

BACKGROUND

Manual or machine-based analysis of chest radiographs needs the images acquired with technical adequacy. Currently, the equidistance between the medial end of clavicles and the center of spinous processes serves as the only criterion to assess whether a frontal PA chest radiograph is taken with any rotation. However, this measurement is normally difficult to implement because there exists overlapping of anatomies within the region. Moreover, there is no way available to predict exact rotating angles even the distances were correctly measured from PA chest radiographs.

OBJECTIVE

To quantitatively assess positioning adequacy of PA chest examination, this study proposes and investigates a new method to estimate rotation angles from asymmetric projection of thoracic cage on radiographs.

METHOD

By looking into the process of radiographic projection, generalized expressions have been established to correlate rotating angles of thorax with projection difference of left and right sides of thoracic cage. A trunk phantom with different positioning angles is employed to acquire radiographs as standard reference to verify the theoretical expressions.

RESULTS

The angles estimated from asymmetric projections of thoracic cage yield good agreement with those actual rotated angles, and an approximate linear relationship exists between rotation angle and asymmetric projection of thoracic cage. Under the experimental projection settings, every degree of rotation corresponds to the width difference of two sides of thoracic cage around 13-14 pixels.

CONCLUSION

The proposed new method may be used to quantify rotating angles of chest and assess image quality for thoracic radiographic examination.

The Interplay between Cancer Biology and the Endocannabinoid System-Significance for Cancer Risk, Prognosis and Response to Treatment

The various components of the endocannabinoid system (ECS), such as the cannabinoid receptors (CBRs), cannabinoid ligands, and the signalling network behind it, are implicated in several tumour-related states, both as favourable and unfavourable factors. This review analyses the ECS's complex involvement in the susceptibility to cancer, prognosis, and response to treatment, focusing on its relationship with cancer biology in selected solid cancers (breast, gastrointestinal, gynaecological, prostate cancer, thoracic, thyroid, CNS tumours, and melanoma). Changes in the expression and activation of CBRs, as well as their ability to form distinct functional heteromers affect the cell's tumourigenic potential and their signalling properties, leading to pharmacologically different outcomes. Thus, the same ECS component can exert both protective and pathogenic effects in different tumour subtypes, which are often pathologically driven by different biological factors. The use of endogenous and exogenous cannabinoids as anti-cancer agents, and the range of effects they might induce (cell death, regulation of angiogenesis, and invasion or anticancer immunity), depend in great deal on the tumour type and the specific ECS component that they target. Although an attractive target, the use of ECS components in anti-cancer treatment is still interlinked with many legal and ethical issues that need to be considered.

Evaluating the diagnostic accuracy of a ctDNA methylation classifier for incidental lung nodules: protocol for a prospective, observational, and multicenter clinical trial of 10,560 cases

Background

Lung nodules are a diagnostic challenge. Current clinical management of lung nodule patients is inefficient and therefore causes patient misclassification, which increases healthcare expenses. However, a precise and robust lung nodule classifier to minimize discomfort for patients and healthcare costs is still lacking. The aim of the present protocol is to evaluate the effectiveness of using a liquid biopsy classifier to diagnose nodules compared to physician estimates and whether the classifier can reduce the number of unnecessary biopsies in benign cases.

Methods

A prospective cohort of 10,560 patients enrolled at 23 clinical centers in China with non-calcified pulmonary nodules, ranging from 0.5 to 3 cm in diameter, indicated by LDCT or CT will be included. After signed consent forms, the participants’ pulmonary nodules will be assessed using three evaluation tools: (I) physician cancer probability estimates (II) validated lung nodule risk models, including Mayo Clinic and Veteran’s Affairs models (III) ctDNA methylation classifier previously established. Each patient will undergo LDCT/CT follow-ups for 2 to 3 years and their information and one blood sample will be collected at baseline, 3, 6, 12, 24 and 36 months. The primary study outcomes will be the diagnostic accuracy of the methylation classifier in the cohort. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) will be used to compare the diagnostic value of each testing tool in differentiating benign and malignant pulmonary nodules.

Discussion

We are conducting an observational study to explore the accuracy of using a ctDNA methylation classifier for incidental lung nodules diagnosis

Trial registration

Clinicaltrials.gov NCT03651986.

Lung cancer awareness and palliative care interventions implemented in low-and middle-income countries: a scoping review

BACKGROUND

Lung cancer is the most diagnosed cancer worldwide. In low- and middle-income countries (LMICs), lung cancer is often diagnosed at a late stage due to poor knowledge and awareness of its signs and symptoms. Increasing lung cancer awareness is likely to reduce the diagnosis and treatment delays. The implementation of early palliative care has also been reported to improve a patient's quality of life, and even survival. The aim of this scoping review was to map evidence on lung cancer awareness and palliative care interventions implemented in sub-Saharan Africa (SSA) and other LMICs.

METHODS

This scoping review was guided by Arksey and O'Malley's framework. Databases such as the EBSCOhost, PubMed, Science Direct, Google Scholar, World Health Organization (WHO) library and grey literature were used to perform systematic searches of relevant articles. The methodological quality assessment of included primary studies was assessed using the Mixed Method Appraisal Tool (MMAT). NVivo version 10 software was used to perform the thematic content analysis of the included studies.

RESULTS

A total number of screened articles was 2886, with 236 meeting the eligibility criteria and 167 further excluded following abstract screening. Sixty-nine (69) articles qualified for full-article screening and 9 were selected for detailed data extraction and methodological quality assessment. Of the included nine studies, eight described at least one lung cancer warning signs and symptoms, while one described the effectiveness of palliative care for lung cancer. Eight articles recognized the level of lung cancer knowledge, risk factors awareness of warning signs and symptoms in LMICs, mostly Africa and Asia.

CONCLUSIONS

Most of the participants were aware of tobacco use as the major risk factor for lung cancer but lacked knowledge on the other pre-disposing risk factors. Evidence on palliative care is scarce, therefore, awareness interventions packaged with evidence on the value of timely access to palliative care services in improving the quality of life of the lung cancer patients and their families, are required.

Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population

Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on chest radiographs in a health screening population. Materials and Methods Out-of-sample testing of a deep learning algorithm was retrospectively performed using chest radiographs from individuals undergoing a comprehensive medical check-up between July 2008 and December 2008 (validation test). To evaluate the algorithm performance for visible lung cancer detection, the area under the receiver operating characteristic curve (AUC) and diagnostic measures, including sensitivity and false-positive rate (FPR), were calculated. The algorithm performance was compared with that of radiologists using the McNemar test and the Moskowitz method. Additionally, the deep learning algorithm was applied to a screening cohort undergoing chest radiography between January 2008 and December 2012, and its performances were calculated. Results In a validation test comprising 10 285 radiographs from 10 202 individuals (mean age, 54 years ± 11 [standard deviation]; 5857 men) with 10 radiographs of visible lung cancers, the algorithm's AUC was 0.99 (95% confidence interval: 0.97, 1), and it showed comparable sensitivity (90% [nine of 10 radiographs]) to that of the radiologists (60% [six of 10 radiographs]; P = .25) with a higher FPR (3.1% [319 of 10 275 radiographs] vs 0.3% [26 of 10 275 radiographs]; P < .001). In the screening cohort of 100 525 chest radiographs from 50 070 individuals (mean age, 53 years ± 11; 28 090 men) with 47 radiographs of visible lung cancers, the algorithm's AUC was 0.97 (95% confidence interval: 0.95, 0.99), and its sensitivity and FPR were 83% (39 of 47 radiographs) and 3% (2999 of 100 478 radiographs), respectively. Conclusion A deep learning algorithm detected lung cancers on chest radiographs with a performance comparable to that of radiologists, which will be helpful for radiologists in healthy populations with a low prevalence of lung cancer. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Armato in this issue.

Microbiota dysbiosis in lung cancer: evidence of association and potential mechanisms

Over the past decade, revolution in microbial research has provided valuable insights into the function of microbes that inhabit human body. This complex community of microbes, collectively named as microbiota, displays tremendous interaction with a host to maintain homeostasis of the local environment. Lungs were even previously regarded as sterile for a long time. With the development of high-throughput next-generation sequencing technology, a low-density, diversified microbial ecosystem is found in bronchoalveolar lavage fluid, sputum, and lung tissues. Current research confirms that, compared with healthy people, patients with lung cancer show changes in the relative abundance of multiple genera. Emerging evidence has suggested that dysbiosis of the lung microbiota may play a critical role in lung carcinogenesis by affecting metabolic, inflammatory pathways and immune response. We briefly summarize the relationship between lung microbiome and lung cancer and discuss the potential mechanisms mediating lung microbiota and lung cancer. Thus, we provide innovative strategies for early prevention and personalized treatment of lung cancer.

Lung Cancer Mortality and the Availability of Chest Computerized Tomography: A Longitudinal Nationwide Study

Lung-cancer screening with chest computerized tomography (CT) is not easy to introduce in low-medium resource countries due to cost issues. We investigated whether the increasing availability of chest CT exams in Brazil, in spite of no lung-cancer screening protocol, was associated with lung-cancer death rate along 10-year follow-up. We performed regressions to estimate the rate ratio between chest CT exams and lung-cancer deaths per 10⁵ inhabitants. We stratified data per municipality. Regressions were adjusted for physicians and hospital beds per 10⁵ inhabitants and per capita gross domestic product. Increasing availability of chest CT exams predicted decreasing lung-cancer death rate.

Attitudes toward tobacco cessation and lung cancer screening in two South African communities

Among men in South Africa, the prevalence of tobacco smoking is as high as 33%. Although smoking is responsible for most lung cancer in South Africa, occupational and environmental exposures contribute greatly to risk. We conducted a tobacco and lung cancer screening needs assessment and administered surveys to adults who smoked >100 cigarettes in their lifetime in Johannesburg (urban) and Kimberley (rural). We compared tobacco use, risk exposure, attitudes toward and knowledge of, and receptivity to cessation and screening, by site. Of 324 smokers, nearly 85% of current smokers had a <30 pack-year history of smoking; 58.7% had tried to stop smoking ≥1 time, and 78.9% wanted to quit. Kimberley smokers more often reported being advised by a healthcare provider to stop smoking (56.5% vs. 37.3%, p=0.001) than smokers in Johannesburg but smokers in Johannesburg were more willing to stop smoking if advised by their doctor (72.9% vs. 41.7%, p<0.001). Findings indicate that tobacco smokers in two geographic areas of South Africa are motivated to stop smoking but receive no healthcare support to do so. Developing high risk criteria for lung cancer screening and creating tobacco cessation infrastructure may reduce tobacco use and decrease lung cancer mortality in South Africa.

Epidemiology of lung cancer in Northern Greece: An 18-year hospital-based cohort study focused on the differences between smokers and non-smokers

INTRODUCTION

Lung cancer remains a leading cause of cancer incidence, yet, in Greece, country-level registry-based data are limited. We have thus investigated the epidemiology of lung cancer and its trends in the George Papanikolaou Hospital, Northern Greece over 18 years (2000–2018).

METHODS

We analyzed all the cases reported in the Bronchoscopy Unit of the Hospital for the period 2000–2018. In total, 15131 subjects (12300 males and 2831 females) that presented with a mass in the imaging, were submitted to bronchoscopy. Characteristics of patients such as age, sex, smoking history and occupation were collected. Statistical analysis was performed with SPSS 21.0 software package.

RESULTS

Among all subjects, a total of 5628 (37.2%; mean age: 65.85 ± 9.6 years) cases of primary lung cancer were identified with a male to female ratio of 2:1 (41.1% to 20.4%) (p<0.001). Squamous cell lung cancer was the most common type of lung cancer identified in this population (44%) with a higher proportion in males compared to females (p<0.001). Furthermore, adenocarcinoma was mostly observed in female non-smokers compared to males (p<0.001). The majority of lung cancer cases were identified in patients occupied with agriculture and livestock breeding (41.1%). The mean age at lung cancer diagnosis was 66.13 ± 9.19 years for the whole study population. Lung cancer cases observed with a higher mean of 43.93 ± 10.84 years of smoking compared to cancer-free patients with 39.64 ± 13.23 years of smoking (p<0.001).

CONCLUSIONS

Apart from smoking, demographic characteristics including age, sex and occupation appear to have an impact on lung cancer development in this population. Smoking history alone could not predict the development of lung cancer in the studied northern Greek population.

Matrix metalloproteinase family gene polymorphisms and lung cancer susceptibility: an updated meta-analysis

Background

Many studies have investigated the association between matrix metalloproteinase polymorphisms and lung cancer susceptibility. However, the results are still controversial. To clarify these associations, we conducted a meta-analysis.

Methods

A systematic search of studies was conducted in PubMed, Embase, and China National Knowledge Infrastructure. Overall and subgroup analysis stratified by ethnicity was conducted. OR with 95% CI was used to assess the strength of the association. Furthermore, false-positive report probability (FPRP) tests were also performed for associations obtained in this meta-analysis.

Results

Twenty-four studies, including 10,099 cases and 9,395 controls, were analyzed. Nine polymorphisms were reported. For MMP1 -1607 1G/2G and MMP7 -181 A/G, increased lung cancer risk was found in Asians. For MMP2 -1306 C/T and MMP2 -735 C/T, decreased lung cancer risk was found in both “diverse populations” and Asians. For MMP9 -1562, C/T decreased lung cancer risk was found in both “diverse populations” and Caucasians. For MMP13 -77A/G, the A/G genotype decreased lung cancer risk in Asians. However, only associations between MMP1 -1607 1G/2G, MMP2 -1306 C/T, MMP2 -735 C/T, and MMP7 -181 A/G and lung cancer risk were considered noteworthy according to FPRP tests. There was no association between MMP3 -1171 5A/6A, MMP9 R279Q, and MMP12 -82A/G and lung cancer risk.

Conclusions

Our meta-analysis suggested that MMP1 -1607 1G/2G and MMP7 -181 A/G were risk factors for lung cancer, while MMP2 -1306 C/T, MMP2 -735 C/T, MMP9 -1562 C/T, and MMP13 -77A/G might be protective factors. However, results for MMP9 -1562 C/T and MMP13 -77A/G should be interpreted with caution due to the probability of false-positive reports.

The barriers to initiating lung cancer care in low-and middle-income countries

Lung cancer in low-and middle-income countries is the leading and the second leading cause of cancer deaths in males and females, respectively. This, in part, is due to late presentation of patients in health facilities and late diagnosis, thereby compromising the effectiveness of treatment and resulting in poor treatment outcomes. Investigating patients’ late presentation to health facilities and late diagnosis, as barriers to achieving good treatment outcomes, is an important step towards improving the existing pathways of care. Therefore, the aim of this paper is to critically review the published and unpublished literature, including government reports on lung cancer care, with regards to the barriers to patient access, referral, diagnosis and treatment in low-and middle-income countries. The emphasis is on access point and the primary care continuum. This review has been packaged into themes in order to efficiently inform researchers and cancer health professionals, on the existing gaps necessary for developing appropriate intervention strategies and policy guidelines. This review has revealed that the timeous and correct diagnosis of lung cancer enables lung specialists to engage on options for improved patient care. Currently, there are variations in lung cancer management in low-and middle-income countries. Many of the factors impacting on health care outcomes are a function of patient circumstances and/or understanding, leading to delays in presentation to health facilities. Factors pertaining to individual patient circumstances are further compounded by inefficiencies within the health care system. Therefore, limited health system capacities and competing health priorities in these settings require action.