Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: a correlative MILD trial study

Seven-microRNA panel for lung adenocarcinoma early diagnosis in patients presenting with ground-glass nodules

Background

MicroRNA (miRNA) expression is correlated with tumor histology, differentiation, invasiveness and treatment outcome. We aimed to identify miRNAs whose differential expression might enable early diagnosis of lung adenocarcinoma in patients presenting with ground-glass nodules (GGNs).

Methods

To identify potential miRNAs of interest, we analyzed the miRNA expression profile of tumor and adjacent non-para-tumor tissue in three participants by next-generation sequencing (NGS). We then assessed the expression levels of the miRNAs of interest in 73 lung adenocarcinomas presenting with GGNs with matched adjacent non-tumor tissue by quantitative real-time polymerase chain reaction (qRT-PCR). We also detected the miRNA panel in 66 lung benign diseases and 66 lung adenocarcinomas presenting with GGN lesion tissues by qRT-PCR. Target genes of our selected miRNA panel were predicted using Miranda with default parameters.

Results

Twenty-three miRNAs showed differential expression between tumor and adjacent non-tumor tissue by NGS. Five miRNAs exhibited higher expression in tumor tissue compared to adjacent non-tumor tissue (P<0.05); 18 miRNAs demonstrated lower expression in tumor tissue versus adjacent non-tumor tissue (P<0.05). When qRT-PCR was performed for the 23 miRNAs identified by NGS in the pilot stage, seven were found to have statistically significant expression in tumor versus adjacent non-tumor tissue (P<0.05). The sensitivity and specificity of seven-miRNA panel were 86.4% and 60.6%, respectively.

Conclusion

The predicted targets of our miRNAs of interest are frequently associated with cancer signaling pathways. We developed a miRNA panel that could potentially predict the presence of lung adenocarcinoma in patients presenting with GGNs.

ANK1 Methylation regulates expression of MicroRNA-486-5p and discriminates lung tumors by histology and smoking status

The intragenic tumor-suppressor microRNA miR-486-5p is often down-regulated in non-small cell lung cancer (NSCLC) but the mechanism is unclear. This study investigated epigenetic co-regulation of miR-486-5p and its host gene ANK1. MiR-486-5p expression in lung tumors and cell lines was significantly reduced compared to normal lung (p < 0.001) and is strongly correlated with ANK1 expression. In vitro, siRNA-mediated ANK1 knockdown in NSCLC cells also reduced miR-486-5p while the DNA methylation inhibitor 5-aza-2'-deoxycytidine induced expression of both. ANK1 promoter CpG island was unmethylated in normal lung but methylated in 45% (118/262) lung tumors and 55% (17/31) NSCLC cell lines. After adjustment for tumor histology and smoking, methylation was significantly more prevalent in adenocarcinoma (101/200, 51%) compared to squamous cell carcinoma (17/62, 27%), p < 0.001; HR = 3.513 (CI: 1.818-6.788); and in smokers (73/128, 57%) than never-smokers (28/72, 39%), p = 0.014; HR = 2.086 (CI: 1.157-3.759). These results were independently validated using quantitative methylation data for 809 NSCLC cases from The Cancer Genome Atlas project. Together, our data indicate that aberrant ANK1 methylation is highly prevalent in lung cancer, discriminate tumors by histology and patients' smoking history, and contributes to miR-486-5p repression.

Development of a predictive miRNA signature for breast cancer risk among high-risk women

Significant limitations exist in our ability to predict breast cancer risk at the individual level. Circulating microRNAs (C-miRNAs) have emerged as measurable biomarkers (liquid biopsies) for cancer detection. We evaluated the ability of C-miRNAs to identify women most likely to develop breast cancer by profiling miRNA from serum obtained long before diagnosis. 24 breast cancer cases and controls (matched for risk and age) were identified from women enrolled in the High-Risk Breast Program at the UVM Cancer Center. Isolated RNA from serum was profiled for over 2500 human miRNAs. The miRNA expression data were input into a stepwise linear regression model to discover a multivariable miRNA signature that predicts long-term risk of breast cancer. 25 candidate miRNAs were identified that individually classified cases and controls based on statistical methodologies. A refined 6-miRNA risk-signature was discovered following regression modeling that distinguishes cases and controls (AUC0.896, CI 0.804-0.988) in this cohort. A functional relationship between miRNAs that cluster together when cases are contrasted against controls was suggested and confirmed by pathway analyses. The discovered 6 miRNA risk-signature can discriminate high-risk women who ultimately develop breast cancer from those who remain cancer-free, improving current risk assessment models. Future studies will focus on functional analysis of the miRNAs in this signature and testing in larger cohorts. We propose that the combined signature is highly significant for predicting cancer risk, and worthy of further screening in larger, independent clinical cohorts.

The biomarker-based diagnosis of Alzheimer's disease. 2-lessons from oncology

Biomarkers for the diagnosis of Alzheimer's disease (AD) are not yet validated for use in clinical settings. We aim to provide a methodological framework for their systematic validation, by reference to that developed for oncology biomarkers. As for this discipline, the steps for the systematic validation of AD biomarkers need to target analytical validity, clinical validity, and clinical utility. However, the premises are different from oncology: the nature of disease (neurodegeneration vs. cancer), the purpose (improve diagnosis in clinically affected vs. screening preclinical individuals), and the target population (mild cognitive impairment patients referring to memory clinics vs. general population) lead to important differences, influencing both the design of validation studies and the use of selected biomarkers. This framework is applied within a wider initiative to assess the current available evidence on the clinical validity of biomarkers for AD, for the final aim to identify gaps and research priorities, and to inform coordinated research efforts boosting AD biomarkers research.

Current and Prospective Protein Biomarkers of Lung Cancer

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

Translating cancer epigenomics into the clinic: focus on lung cancer

Epigenetic deregulation is increasingly being recognized as a hallmark of cancer. Recent studies have identified many new epigenetic biomarkers, some of which are being introduced into clinical practice for diagnosis, molecular classification, prognosis or prediction of response to therapies. O-6-methylguanine-DNA methyltransferase gene is the most clinically advanced epigenetic biomarker as it predicts the response to temozolomide and carmustine in gliomas. Therefore, epigenomics may represent a novel and promising tool for precision medicine, and in particular, the detection of epigenomic biomarkers in liquid biopsies will be of great interest for monitoring diseases in patients. Of particular relevance is the identification of epigenetic biomarkers in lung cancer, one of the most prevalent and deadly types of cancer. DNA methylation of SHOX2 and RASSF1A could be used as diagnostic markers to differentiate between normal and tumor samples. MicroRNA and long noncoding RNA signatures associated with lung cancer development or tobacco smoke have also been identified. In addition to the field of biomarkers, therapeutic approaches using DNA methylation and histone deacetylation inhibitors are being tested in clinical trials for several cancer types. Moreover, new DNA editing techniques based on zinc finger and CRISPR/Cas9 technologies allow specific modification of aberrant methylation found in oncogenes or tumor suppressor genes. We envision that epigenomics will translate into the clinical field and will have an impact on lung cancer diagnosis/prognosis and treatment.

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening

The development of a minimally invasive test, such as liquid biopsy, for early lung cancer detection in its preclinical phase is crucial to improve the outcome of this deadly disease. MicroRNAs (miRNAs) are tissue specific, small, non-coding RNAs regulating gene expression, which may act as extracellular messengers of biological signals derived from the cross-talk between the tumor and its surrounding microenvironment. They could thus represent ideal candidates for early detection of lung cancer. In this work, a methodological workflow for the prospective validation of a circulating miRNA test using custom made microfluidic cards and quantitative Real-Time PCR in plasma samples of volunteers enrolled in a lung cancer screening trial is proposed. In addition, since the release of hemolysis-related miRNAs and more general technical issues may affect the analysis, the quality control steps included in the standard operating procedures are also presented. The protocol is reproducible and gives reliable quantitative results; however, when using large clinical series, both pre-analytical and analytical features should be cautiously evaluated.

Lung cancer screening

PURPOSE OF REVIEW

Lung cancer screening with low-dose chest computed tomography is now recommended for high-risk individuals by the US Preventive Services Task Force. This recommendation was informed by several randomized controlled trials, the largest of which, the National Lung Screening Trial, demonstrated a 20% relative reduction in lung cancer mortality with annual low-dose chest computed tomography compared with chest radiography.

RECENT FINDINGS

The benefit of lung cancer screening must be balanced against potential harms, including a high false-positive rate with consequent further evaluative studies and invasive testing. It is critical that harms be minimized as screening generalizes to the broad community. Informed decision making between providers and patients should include individualized risk assessment, a discussion of both potential benefit and harm, and tobacco treatment. Given the multiple components required for high quality, screening should ideally occur in the context of a multidisciplinary program.

SUMMARY

We are in the early days of lung cancer screening, still with much to learn. Ongoing studies are necessary to refine the definition of a positive screen and develop better methods of distinguishing between true positive and false-positive results. Novel approaches, including the development of multicomponent lung cancer biomarkers, will likely inform and improve our future screening practice.

The clinical use of circulating microRNAs as non-invasive diagnostic biomarkers for lung cancers

Many studies have investigated the diagnostic role of circulating microRNAs (miRNAs) in patients with lung cancer; however, the results still remain inconclusive. An updated system review and meta-analysis was necessary to give a comprehensive evaluation of diagnostic role of circulating miRNAs in lung cancer. Eligible studies were searched in electronical databases. The sensitivity and specificity were used to plot the summary receiver operator characteristic (SROC) curve and calculate the area under the curve (AUC). The between-study heterogeneity was evaluated by Q test and I² statistics. Subgroup analyses and meta-regression were further performed to explore the potential sources of heterogeneity. A total of 134 studies from 65 articles (6,919 patients with lung cancer and 7,064 controls) were included for analysis. Overall analysis showed that circulating miRNAs had a good diagnostic performance in lung cancers, with a sensitivity of 0.83, a specificity of 0.84, and an AUC of 0.90. Subgroup analysis suggested that combined miRNAs and Caucasian populations may yield relatively higher diagnostic performance. In addition, we found serum might serve as an ideal material to detecting miRNA as good diagnostic performance. We also found the diagnostic role of miRNAs in early stage lung cancer was still relatively high (the sensitivity, specificity and an AUC of stage I/II was 0.81, 0.82 and 0.88; and for stage I, it was 0.80, 0.81, and 0.88). We also identified a panel of miRNAs such as miR-21-5p, miR-223-3p, miR-155-5p and miR-126-3p might serve as potential biomarkers for lung cancer. As a result, circulating miRNAs, particularly the combination of multiple miRNAs, may serve as promising biomarkers for the diagnosis of lung cancer.

Serum Monitoring and Phenotype Identification of Stage I Non-Small Cell Lung Cancer Patients

A stage I non-small cell lung cancer (NSCLC) serum profiling platform is presented which is highly efficient and accurate. Test sensitivity (0.95) for stage I NSCLC is the highest reported so far. Test metrics are reported for discriminating stage I adenocarcinoma vs squamous cell carcinoma subtypes. Blinded analysis identified 23 out of 24 stage I NSCLC and control serum samples. Group-discriminating mass peaks were targeted for tandem mass spectrometry peptide/protein identification, and yielded a lung cancer phenotype. Bioinformatic analysis revealed a novel lymphocyte adhesion pathway involved with early-stage lung cancer.

Smoking and Lung Cancer: A Geo-Regional Perspective

Lung cancer is the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) represents the most frequently diagnosed subtype of this morbid malignancy. NSCLC is causally linked to tobacco consumption with more than 500 million smokers worldwide at high risk for this fatal malignancy. We are currently lagging in our knowledge of the early molecular (e.g., genomic) effects of smoking in NSCLC pathogenesis that would constitute ideal markers for early detection. This limitation is further amplified when considering the variable etiologic factors in NSCLC pathogenesis among different regions around the globe. In this review, we present our current knowledge of genomic alterations arising during early stages of smoking-induced lung cancer initiation and progression, including discussing the premalignant airway field of injury induced by smoking. The review also underscores the wider spectra and higher age-adjusted rates of tobacco (e.g., water-pipe smoke) consumption, along with elevated environmental carcinogenic exposures and relatively poorer socioeconomic status, in low-middle income countries (LMICs), with Lebanon as an exemplar. This “cocktail” of carcinogenic exposures warrants the pressing need to understand the complex etiology of lung malignancies developing in LMICs such as Lebanon.

Progress and prospects of early detection in lung cancer

Lung cancer is the leading cause of cancer-related death in the world. It is broadly divided into small cell (SCLC, approx. 15% cases) and non-small cell lung cancer (NSCLC, approx. 85% cases). The main histological subtypes of NSCLC are adenocarcinoma and squamous cell carcinoma, with the presence of specific DNA mutations allowing further molecular stratification. If identified at an early stage, surgical resection of NSCLC offers a favourable prognosis, with published case series reporting 5-year survival rates of up to 70% for small, localized tumours (stage I). However, most patients (approx. 75%) have advanced disease at the time of diagnosis (stage III/IV) and despite significant developments in the oncological management of late stage lung cancer over recent years, survival remains poor. In 2014, the UK Office for National Statistics reported that patients diagnosed with distant metastatic disease (stage IV) had a 1-year survival rate of just 15-19% compared with 81-85% for stage I.

Genomic approaches to accelerate cancer interception

Although major advances have been reported in the last decade in the treatment of late-stage cancer with targeted and immune-based therapies, there is a crucial unmet need to develop new approaches to improve the prevention and early detection of cancer. Advances in genomics and computational biology offer unprecedented opportunities to understand the earliest molecular events associated with carcinogenesis, enabling novel strategies to intercept the development of invasive cancers. This Series paper will highlight emerging big data genomic approaches with the potential to accelerate advances in cancer prevention, screening, and early detection across various tumour types, and the challenges inherent in the development of these tools for clinical use. Through coordinated multicentre consortia, these genomic approaches are likely to transform the landscape of cancer interception in the coming years.

Liquid biopsy for early detection of lung cancer

PURPOSE OF REVIEW

The possibility of complete recovery for a lung cancer patient depends on very early diagnosis, as it allows total surgical resection. Screening for this cancer in a high-risk population can be performed using a radiological approach, but this holds a certain number of limitations. Liquid biopsy could become an alternative and complementary screening approach to chest imaging for early diagnosis of lung cancer.

RECENT FINDINGS

Several circulating biomarkers indicative of lung cancer can be investigated in blood, such as circulating tumor cells, circulating free nucleic acids (RNA and DNA) and proteins. However, none of these biomarkers have yet been adopted in routine clinical practice and studies are ongoing to confirm or not the usefulness and practical interest in routine early diagnosis and screening for lung cancers.

SUMMARY

Several potential circulating biomarkers for the early detection of lung cancer exist. When coupled to thoracic imaging, these biomarkers must give diagnosis of a totally resectable lung cancer and potentially provide new recommendations for surveillance by imagery of high-risk populations without a detectable nodule. Optimization of the specificity and sensitivity of the detection methods as well as standardization of the techniques is essential before considering for daily practice a liquid biopsy as an early diagnostic tool, or possibly as a predictive test, of lung cancer.

MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact

MicroRNAs are well-known strong RNA regulators modulating whole functional units in complex signaling networks. Regarding clinical application, they have potential as biomarkers for prognosis, diagnosis, and therapy. In this review, we focus on two microRNAs centrally involved in lung cancer progression. MicroRNA-21 promotes and microRNA-34 inhibits cancer progression. We elucidate here involved pathways and imbed these antagonistic microRNAs in a network of interactions, stressing their cancer microRNA biology, followed by experimental and bioinformatics analysis of such microRNAs and their targets. This background is then illuminated from a clinical perspective on microRNA-21 and microRNA-34 as general examples for the complex microRNA biology in lung cancer and its diagnostic value. Moreover, we discuss the immense potential that microRNAs such as microRNA-21 and microRNA-34 imply by their broad regulatory effects. These should be explored for novel therapeutic strategies in the clinic.

Analysis of primary-miRNA-3662 and its mature form may improve detection of the lung adenocarcinoma

INTRODUCTION

Because of the alarming data concerning lung cancer morbidity and mortality, investigation of new molecular markers allowing early cancer detection is desirable. In the present study, we investigated the potential role of miRNA-3662 precursor (pri-miRNA-3662) as potential novel diagnostic marker of lung adenocarcinoma (AC).

MATERIALS AND METHODS

Expression of miRNA-3662 and pri-miRNA-3662 was analyzed in 56 fresh-frozen tissues of non-small cell lung cancer and corresponding adjacent non-cancerous tissues using (NCT) qRT-PCR. Using receiver operating curves (ROC) analysis, the diagnostic accuracy of both studied markers for AC detection was assessed.

RESULTS

miRNA-3662 and its precursor were significantly overexpressed in AC compared to squamous-cell carcinoma (SCC) and NCT. Combined analysis of pri-miRNA-3662 and mature miRNA-3662 allowed to distinguish AC tissue from SCC with sensitivity of 96% and specificity of 85.7% (AUC = 0.963), and SCC from non-cancerous tissue with 92% sensitivity and 92% specificity (AUC = 0.979).

CONCLUSIONS

miRNA-3662 and its precursor are potentially involved in AC development. pri-miRNA seem to be novel interesting group of potential cancer biomarkers, because they demonstrate high diagnostic accuracy for tumor detection.

Circulating cell-free microRNAs as clinical cancer biomarkers

MicroRNAs (miRNAs) are non-coding small RNAs that are master regulators of genic expression and consequently of many cellular processes. But their expression is often deregulated in human tumors leading to cancer development. Recently miRNAs were discovered in body fluids (serum, plasma and others) and their levels have often been reported to be altered in patients. Circulating miRNAs became one of the most promising biomarkers in oncology for early diagnosis, prognosis and therapeutic response prediction. Here we describe the origins and roles of miRNAs, and summarize the most recent studies focusing on their usefulness as cancer biomarkers in lung, breast, colon, prostate, ovary cancers and melanoma. Lastly, we describe the main methodologies related to miRNA detection, which should be standardized for their use in clinical practice.

Integration of multiple "OMIC" biomarkers: A precision medicine strategy for lung cancer

More than half of all new lung cancer diagnoses are made in patients with locally advanced or metastatic disease, at which point therapeutic options are scarce. It is anticipated, however, that the widespread use of Low-Dose Computed Tomography (LDCT) screening, will lead to a greater proportion of lung cancers being diagnosed at an early, operable, stage. Still, the overall rate of recurrence for surgically treated Stage I lung cancer patients is up to 30% within 5 years of diagnosis. Thus, the identification and clinical application of biomarkers of early stage lung cancer are a pressing medical need. The integrative analysis of "omic," clinical and epidemiological data for single patients is a core principle of precision medicine. Through rigorous bioinformatics and statistical analyses we have identified biomarkers of early-stage lung cancer based on DNA methylation, expression of mRNA and miRNA, inflammatory cytokines, and urinary metabolites. Beyond a more comprehensive understanding of the molecular taxonomy of lung cancer, these biomarkers can have very practical implications in the context of unmet clinical needs of early stage lung cancer patients: First, current guidelines for LDCT screening broadly include individuals based on age and history of heavy smoking. Tumor-derived circulating biomarkers in the blood and urine associated with lung cancer risk could narrow and prioritize individuals for LDCT screening. Second, a high number of nodules are identified by LDCT, of which fewer than 5% are finally diagnosed as lung cancer. Biomarkers may help discriminate malignant nodules from benign or indolent lesions. Third, the expected rise in the numbers of lung cancer patients diagnosed at an early stage will necessitate new treatment options. Circulating, urinary and tissue-based biomarkers that molecularly categorize Stage I patients after tumor resection can help identify high-risk patients who may benefit from adjuvant chemotherapy or innovative immunotherapy regimens.

Multimodal lung cancer screening using the ITALUNG biomarker panel and low dose computed tomography. Results of the ITALUNG biomarker study

Asymptomatic high-risk subjects, randomized in the intervention arm of the ITALUNG trial (1,406 screened for lung cancer), were enrolled for the ITALUNG biomarker study (n = 1,356), in which samples of blood and sputum were analyzed for plasma DNA quantification (cut off 5 ng/ml), loss of heterozygosity and microsatellite instability. The ITALUNG biomarker panel (IBP) was considered positive if at least one of the two biomarkers included in the panel was positive. Subjects with and without lung cancer diagnosis at the end of the screening cycle with LDCT (n = 517) were evaluated. Out of 18 baseline screen detected lung cancer cases, 17 were IBP positive (94%). Repeat screen-detected lung cancer cases were 18 and 12 of them positive at baseline IBP test (66%). Interval cancer cases (2-years) and biomarker tests after a suspect Non Calcific Nodule follow-up were investigated. The single test versus multimodal screening measures of accuracy were compared in a simulation within the screened ITALUNG intervention arm, considering screen-detected and interval cancer cases. Sensitivity was 90% at baseline screening. Specificity was 71 and 61% for LDCT and IBP as baseline single test, and improved at 89% with multimodal, combined screening. The positive predictive value was 4.3% for LDCT at baseline and 10.6% for multimodal screening. Multimodal screening could improve the screening efficiency at baseline and strategies for future implementation are discussed. If IBP was used as primary screening test, the LDCT burden might decrease of about 60%.

A prediction model for distinguishing lung squamous cell carcinoma from adenocarcinoma

Accurate classification of squamous cell carcinoma (SCC) from adenocarcinoma (AC) of non–small cell lung cancer (NSCLC) can lead to personalized treatments of lung cancer. We aimed to develop a miRNA-based prediction model for differentiating SCC from AC in surgical resected tissues and bronchoalveolar lavage (BAL) samples. Expression levels of seven histological subtype-associated miRNAs were determined in 128 snap-frozen surgical lung tumor specimens by using reverse transcription-polymerase chain reaction (RT-PCR) to develop an optimal panel of miRNAs for acutely distinguishing SCC from AC. The biomarkers were validated in an independent cohort of 112 FFPE lung tumor tissues, and a cohort of 127 BAL specimens by using droplet digital PCR for differentiating SCC from AC. A prediction model with two miRNAs (miRs-205-5p and 944) was developed that had 0.988 area under the curve (AUC) with 96.55% sensitivity and 96.43% specificity for differentiating SCC from AC in frozen tissues, and 0.997 AUC with 96.43% sensitivity and 96.43% specificity in FFPE specimens. The diagnostic performance of the prediction model was reproducibly validated in BAL specimens for distinguishing SCC from AC with a higher accuracy compared with cytology (95.69 vs. 68.10%; P < 0.05). The prediction model might have a clinical value for accurately discriminating SCC from AC in both surgical lung tumor tissues and liquid cytological specimens.

Associations of microRNA single nucleotide polymorphisms and disease risk and pathophysiology

Single nucleotide polymorphisms (SNPs) are genetic variations that contribute to human phenotypes associated with various diseases. SNPs are involved in the regulation of a broad range of physiological and pathological processes, such as cellular senescence, apoptosis, inflammation, and immune response, by upregulating the expression of classical inflammation markers. Recent studies have suggested that SNPs located in gene-encoding microRNAs (miRNAs) affect various aspects of diseases by regulating the expression or activity of miRNAs. In the last few years, miRNA polymorphisms that increase and/or reduce the risk of developing many diseases, such as cancers, autoimmune diseases, and cardiovascular diseases, have attracted increasing attention not only because of their involvement in the pathophysiology of diseases but also because they can be used as prognostic biomarkers for a variety of diseases. In this review, we summarize the relationships between miRNA SNPs and the pathophysiology and risk of diseases.

Mutational Profile from Targeted NGS Predicts Survival in LDCT Screening-Detected Lung Cancers

Background:

The issue of overdiagnosis in low-dose computed tomography (LDCT) screening trials could be addressed by the development of complementary bio-markers able to improve detection of aggressive disease. The mutation profile of LDCT screening–detected lung tumors is currently unknown.

Methods:

Targeted next-generation sequencing was performed on 94 LDCT screening–detected lung tumors. Associations with clinicopathologic features, survival, and the risk profile of a plasma microRNA signature classifier were analyzed.

Results:

The mutational spectrum and frequency observed in screening series was similar to that reported in public data sets, although a larger number of tumors without mutations in driver genes was detected. The 5-year overall survival (OS) rates of patients with and without mutations in the tumors were 66% and 100%, respectively (p = 0.015). By combining the mutational status with the microRNA signature classifier risk profile, patients were stratified into three groups with 5-year OS rates ranging from 42% to 97% (p < 0.0001) and the prognostic value was significant after controlling for stage (p = 0.02).

Conclusion:

Tumor mutational status along with a microRNA-based liquid biopsy can provide additional information in planning clinical follow-up in lung cancer LDCT screening programs.

C-Met/miR-130b axis as novel mechanism and biomarker for castration resistance state acquisition

Although a significant subset of prostate tumors remain indolent during the entire life, the advanced forms are still one of the leading cause of cancer-related death. There are not reliable markers distinguishing indolent from aggressive forms. Here we highlighted a new molecular circuitry involving microRNA and coding genes promoting cancer progression and castration resistance. Our preclinical and clinical data demonstrated that c-Met activation increases miR-130b levels, inhibits androgen receptor expression, promotes cancer spreading and resistance to hormone ablation therapy. The relevance of these findings was confirmed on patients' samples and by in silico analysis on an independent patient cohort from Taylor's platform. Data suggest c-Met/miR-130b axis as a new prognostic marker for patients' risk assessment and as an indicator of therapy resistance. Our results propose new biomarkers for therapy decision-making in all phases of the pathology. Data may help identify high-risk patients to be treated with adjuvant therapy together with alternative cure for castration-resistant forms while facilitating the identification of possible patients candidates for anti-Met therapy. In addition, we demonstrated that it is possible to evaluate Met/miR-130b axis expression in exosomes isolated from peripheral blood of surgery candidates and advanced patients offering a new non-invasive tool for active surveillance and therapy monitoring.

Blood-Based Nucleic Acid Biomarkers as a Potential Tool to Determine Radiation Therapy Response in Non-Small Cell Lung Cancer

Lung cancer is the leading cause of cancer deaths worldwide, with smoking as the main risk factor. The use of low-dose computed tomography (LDCT) as a screening method has shown a 20% lung cancer specific mortality benefit; however, widespread implementation is estimated to add $1.3-$2.0 billion in annual national health care expenditures. Blood-based microRNAs (miRNAs) have been investigated in detail and found to be potentially useful biomarkers indicating the presence of lung cancer, especially when used as a companion test to LDCT. Testing for miRNAs and circulating tumor DNA (ct-DNA) in the blood are anticipated to become more affordable in the near future, and therefore these potentially sensitive methods could serve as first-line screening modalities prior to obtaining LDCT and definitive diagnostic tests for lung cancer. Furthermore, miRNAs may shed light not only on the tumor burden, but also perhaps on tumor aggressiveness, histology, treatment response and the patient's overall survival. In the near future, analysis of ct-DNA may reveal somatic mutations beyond EGFR, tumor burden and the presence of occult progression of disease. In theory, these biomarkers may also help oncologists to elucidate the tumor response to radiotherapy, and in the future, may assist the radiation oncologist in making data-driven treatment decisions and providing patients with quantitative information regarding their treatment response.

Lung cancer screening with low-dose CT in Europe: strength and weakness of diverse independent screening trials

A North American trial reported a significant reduction of lung cancer mortality and overall mortality as a result of annual screening using low-dose computed tomography (LDCT). European trials prospectively tested a variety of possible screening strategies. The main topics of current discussion regarding the optimal screening strategy are pre-test selection of the high-risk population, interval length of LDCT rounds, definition of positive finding, and post-test apportioning of lung cancer risk based on LDCT findings. Despite the current lack of statistical evidence regarding mortality reduction, the European independent diverse strategies offer a multi-perspective view on screening complexity, with remarkable indications for improvements in cost-effectiveness and harm-benefit balance. The UKLS trial reported the advantage of a comprehensive and simple risk model for selection of patients with 5% risk of lung cancer in 5 years. Subjective risk prediction by biological sampling is under investigation. The MILD trial reported equal efficiency for biennial and annual screening rounds, with a significant reduction in the total number of LDCT examinations. The NELSON trial introduced volumetric quantification of nodules at baseline and volume-doubling time (VDT) for assessment of progression. Post-test risk refinement based on LDCT findings (qualitative or quantitative) is under investigation. Smoking cessation remains the most appropriate strategy for mortality reduction, and it must therefore remain an integral component of any lung cancer screening programme.

[Lung screening]

The NLST study found in more than 53,000 (former-) heavy smokers that annual screening with low-dose CT-scan (LDCT) reduced lung cancer mortality and overall mortality by 20% and 6.7% respectively. However, several potential harms of such screening strategy were underlined: over-diagnosis bias, irradiation risk, and the high rate of false-positive results that could lead to futile invasive (and potentially harmful) exams, to impact quality of life, to increase patient's anxiety and costs. All these concerns were largely debated in several recent publications. Most of them concluded in a risk/benefit ratio favoring screening strategy by LDCT. Conversely, most of American academic societies currently recommend LDCT-based lung cancer screening. In France, a taskforce edited a common statement recommending screening smokers or ex-smokers, from 55 to 75years old who have smoked at least 30packs/year. The taskforce also underlined the need for clinical trials aiming to translate screening strategy to the French setting. However, the French Health Authority recently claimed that lung cancer screening was not relevant in the current setting.

Circulating and tissue biomarkers in early-stage non-small cell lung cancer

OBJECTIVE

We sought to characterise circulating and tissue tumour biomarkers of patients who developed early-stage non-small cell lung cancer (NSCLC) during long-term follow-up of a chemoprevention trial (NCT00321893).

MATERIALS AND METHODS

Blood and sputum samples were collected from 202 high-risk asymptomatic individuals with CT-detected stable lung nodules. Real-time PCR was performed on plasma to quantify free circulating DNA. Baseline serum was investigated with a previously validated test based on 13 circulating miRNAs (miR-Test). Promoter methylation status of p16, RASSF1a and RARβ2 and telomerase activity were assessed in sputum samples. DNA was extracted from each tumour developed during follow-up and subjected to a mutation survey using the LungCarta panel on the Sequenom MassARRAY platform.

RESULTS

During follow-up (9 years) six individuals underwent surgery for stage I NSCLC with a median time of disease onset of 20.5 months. MiR-Test scores were positive (range: 0.14-7.24) in four out of six baseline pre-disease onset sera. No association was identified between free circulating DNA or sputum biomarkers and disease onset. All tumours harboured at least one somatic mutation in well-known cancer genes, including KRAS (n = 4), BRAF (n = 1), and TP53 (n = 3).

CONCLUSION

Circulating miRNA tests may represent valuable tools to detect clinically-silent tumours. Early-stage lung adenocarcinomas harbour recurrent genetic events similar to those described in advanced-stage NSCLCs.

[The microRNAs as biomarkers: What prospects?]

MicroRNAs are nucleic acids of about twenty nucleotides that regulate about a third of the genome at the post-transcriptional level. Thanks to their different forms of transport, microRNAs are stable and can be detected in biological fluids such as blood, urine, cerebrospinal fluid, or saliva. In addition, the profile of circulating microRNAs is a specific part of the cells in which it is secreted and is modified according to the physiological or pathological conditions of these cells. MicroRNAs therefore appear as biomarkers of interest for many diseases. However, these applications face several challenges because there are currently considerable differences between the sample processing procedures, assay methods, and especially the result standardization strategies. This literature review aims to take stock of the current use of microRNAs as biomarkers mainly in biological fluids and address the perspectives that emerge from the fact that their vesicular circulating forms could be used to assess the state of the cells and the tissues that produce them.

Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools

Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs.

Noncoding RNA Profiles in Tobacco- and Alcohol-Associated Diseases

Tobacco and alcohol are the leading environmental risk factors in the development of human diseases, such as cancer, cardiovascular disease, and liver injury. Despite the copious amount of research on this topic, by 2030, 8.3 million deaths are projected to occur worldwide due to tobacco use. The expression of noncoding RNAs, primarily microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), is modulated by tobacco and alcohol consumption. Drinking alcohol and smoking cigarettes can modulate the expression of miRNAs and lncRNAs through various signaling pathways, such as apoptosis, angiogenesis, and inflammatory pathways—primarily interleukin 6 (IL-6)/signal transducer and activator of transcription 3 (STAT3), which seems to play a major role in the development of diseases associated with these risk factors. Since they may be predictive and prognostic biomarkers, they can be used both as predictors of the response to therapy and as a targeted therapy. Further, circulating miRNAs might be valuable noninvasive tools that can be used to examine diseases that are related to the use of tobacco and alcohol. This review discusses the function of noncoding RNAs in cancer and other human tobacco- and alcohol-associated diseases.

Predicting Malignant Nodules from Screening CT Scans

OBJECTIVES

The aim of this study was to determine whether quantitative analyses ("radiomics") of low-dose computed tomography lung cancer screening images at baseline can predict subsequent emergence of cancer.

METHODS

Public data from the National Lung Screening Trial (ACRIN 6684) were assembled into two cohorts of 104 and 92 patients with screen-detected lung cancer and then matched with cohorts of 208 and 196 screening subjects with benign pulmonary nodules. Image features were extracted from each nodule and used to predict the subsequent emergence of cancer.

RESULTS

The best models used 23 stable features in a random forests classifier and could predict nodules that would become cancerous 1 and 2 years hence with accuracies of 80% (area under the curve 0.83) and 79% (area under the curve 0.75), respectively. Radiomics outperformed the Lung Imaging Reporting and Data System and volume-only approaches. The performance of the McWilliams risk assessment model was commensurate.

CONCLUSIONS

The radiomics of lung cancer screening computed tomography scans at baseline can be used to assess risk for development of cancer.

A methodological procedure for evaluating the impact of hemolysis on circulating microRNAs

Circulating microRNAs (miRNAs) are promising non-invasive biomarkers whose expression may be affected by confounding factors, including hemolysis, that should be considered in studies of miRNA discovery. The present study proposes a methodology for evaluating the impact of hemolysis on the expression of miRNAs. An experiment of in vitro controlled hemolysis was designed for assessing if changes in the expression of eight miRNAs observed to be circulating in plasma may be associated with hemolysis, and also to estimate the level of red blood cell (RBC) contamination in plasma samples where the expression of these miRNAs will be measured. It was confirmed that four miRNAs, miR-16, miR-92a, miR-451 and miR-486, known to be present in blood cells, were influenced by contamination of RBCs. Furthermore, it was demonstrated that miR-378 and miR-30c are hemolysis-independent and that the expression of miR-320 and miR-324-3p was associated with the level of RBC contamination. This procedure is proposed as a tool for the evaluation of the influence of hemolysis on candidate circulating miRNA biomarkers prior to their analysis in plasma samples.

Plasma vesicle miRNAs for therapy response monitoring in Hodgkin lymphoma patients

BACKGROUND. Cell-free circulating nucleic acids, including 22-nt microRNAs (miRNAs), represent noninvasive biomarkers for treatment response monitoring of cancer patients. While the majority of plasma miRNA is bound to proteins, a smaller, less well-characterized pool is associated with extracellular vesicles (EVs). Here, we addressed whether EV-associated miRNAs reflect metabolic disease in classical Hodgkin lymphoma (cHL) patients.

METHODS. With standardized size-exclusion chromatography (SEC), we isolated EV-associated extracellular RNA (exRNA) fractions and protein-bound miRNA from plasma of cHL patients and healthy subjects. We performed a comprehensive small RNA sequencing analysis and validation by TaqMan qRT-PCR for candidate discovery. Fluorodeoxyglucose-PET (FDG-PET) status before treatment, directly after treatment, and during long-term follow-up was compared directly with EV miRNA levels.

RESULTS. The plasma EV miRNA repertoire was more extensive compared with protein-bound miRNA that was heavily dominated by a few abundant miRNA species and was less informative of disease status. Purified EV fractions of untreated cHL patients and tumor EVs had enriched levels of miR24-3p, miR127-3p, miR21-5p, miR155-5p, and let7a-5p compared with EV fractions from healthy subjects and disease controls. Serial monitoring of EV miRNA levels in patients before treatment, directly after treatment, and during long-term follow-up revealed robust, stable decreases in miRNA levels matching a complete metabolic response, as observed with FDG-PET. Importantly, EV miRNA levels rose again in relapse patients.

CONCLUSION. We conclude that cHL-related miRNA levels in circulating EVs reflect the presence of vital tumor tissue and are suitable for therapy response and relapse monitoring in individual cHL patients.

FUNDING. Cancer Center Amsterdam Foundation (CCA-2013), Dutch Cancer Society (KWF-5510), Technology Foundation STW (STW Perspectief CANCER-ID).

The extracellular RNA repertoire in circulating extracellular vesicles is useful indicator of therapy response and relapse in classical Hodgkin lymphoma patients.

Aberrant Expression of miR-323a-5p in Patients with Refractory Epilepsy Caused by Focal Cortical Dysplasia

BACKGROUND

Epilepsy remains one of the most common clinical neurological disorders. About a third of patients with epilepsy are refractory to drug treatment, mainly as a result of focal cortical dysplasia (FCD). In this study, we analyzed the aberrant expression of microRNAs (miRNAs) in the cortex and plasma of FCD patients.

METHODS

Cortical samples were collected from nine patients with refractory epilepsy caused by FCD who underwent surgery, and from eight volunteers (control group) undergoing emergency surgery for hypertensive cerebral hemorrhage. miRNA expression in the cortex was detected by microarray analysis and miR-323a-5p expression levels in the cortex were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). We also collected plasma samples from 30 patients with refractory epilepsy caused by FCD and from 23 healthy controls, and compared differential expression of miR-323a-5p in the plasma using qRT-PCR.

RESULTS

miRNA microarray analysis showed that expression of miR-323a-5p was upregulated in the FCD group compared with the control group, and miR-323a-5p expression levels in the cortex analyzed by qRT-PCR supported those obtained by microarray analysis. Plasma levels of miR-323a-5p were significantly higher in patient plasma compared with the healthy controls, as determined by qRT-PCR. Furthermore, expression of miR-323a-5p was positively correlated with the duration of epilepsy (p = 0.014) and seizure frequency (p = 0.043). The effectiveness of surgery in patients with FCD was significantly poorer in patients with high plasma levels of miR-323a-5p compared with those with low levels.

CONCLUSIONS

The expression of miR-323a-5p was significantly elevated in the cortex and plasma of FCD patients. These results suggest that abnormal expression of miR-323a-5p could be used for improving the current diagnosis of FCD and monitoring treatment responses in patients with FCD.

Identification of miRNAs as non-invasive biomarkers for early diagnosis of lung cancers

Current clinical diagnostic methods lack the specificity in detecting lung cancer patients. The issue is particularly critical for stage I and II patients. Considerable evidence showed microRNA plays a very important role in lung carcinogenesis. Here, we identified a panel of 41 miRNAs significantly elevated in patients with lung cancer, of which eight miRNAs were further validated in an independent sample cohort. Classification analysis using the panel of eight miRNAs generated a discriminatory power of 93.3 % sensitivity and 93.8 % specificity in separating non-small-cell lung cancer (NSCLC) patients from normal controls, indicating the miRNAs have a potential clinical utility in discriminating NSCLC. Interestingly, miR-1244 was found significantly elevated in the serum samples of lung cancer patients, and the test characteristics of the single miRNA were area under the curve (AUC) of 0.832 in NSCLC vs healthy controls, and 0.861 in NSCLC vs patients with unidentified pulmonary nodules. This is the first study showing serum miR-1244 could be a biomarker to screen lung cancer patients from the high-risk population.

Plasma miR-19b and miR-183 as Potential Biomarkers of Lung Cancer

Lung cancer is a complex disease that often manifests at the point when treatment is not effective. Introduction of blood-based complementary diagnostics using molecular markers may enhance early detection of this disease and help reduce the burden of lung cancer. Here we evaluated the diagnostic potential of seven plasma miRNA biomarkers (miR-21, -19b, -126, -25, -205, -183, -125b) by quantitative reverse transcription PCR. Influence clinical and demographical characteristics, including age, tumor stage and cancer subtype on miRNA levels was investigated. Four miRNAs were significantly dysregulated (miR-19b, -21, -25, -183) in lung cancer patients. Combination of miR-19b and miR-183 provided detection of lung cancer with 94.7% sensitivity and 95.2% specificity (AUC = 0.990). Thus, miRNAs have shown the potential to discriminate histological subtypes of lung cancer and reliably distinguish lung cancer patients from healthy individuals.

[Present Situation of Lung Cancer Screening Methods]

肺癌是目前恶性肿瘤死亡的首要原因，早期诊断对肺癌的预后至关重要。研究显示低剂量计算机断层扫描（computed tomography, CT）筛查可以使肺癌的死亡率下降。但其存在的问题不可忽视，如过高的假阳性率、过度诊断、辐射效应等。作为一种肿瘤无创筛查方法，血液相关肿瘤标志物的检测，在肺癌早期诊断中显示出良好的敏感性和特异性。如何利用现有的筛查手段，建立肺癌筛查综合模式，需要更多大规模的临床研究。

The Pursuit of Noninvasive Diagnosis of Lung Cancer

The noninvasive diagnosis of lung cancer remains a formidable challenge. Although tissue diagnosis will remain the gold standard for the foreseeable future, questions pertaining to the risks and costs associated with invasive diagnostic procedures are of prime relevance. This review addresses new modalities for improving the noninvasive evaluation of suspicious lung nodules. Ultimately, the goal is to translate early diagnosis into early treatment. We discuss how biomarkers could assist in distinguishing benign from malignant nodules and aggressive from indolent tumors. The field of biomarkers is rapidly expanding and progressing, and efforts are well underway to apply molecular diagnostics to address the shortcomings of current lung cancer diagnostic tools.

The International Epidemiology of Lung Cancer: Latest Trends, Disparities, and Tumor Characteristics

INTRODUCTION

Our aim was to update global lung cancer epidemiology and describe changing trends and disparities.

METHODS

We presented country-specific incidence and mortality from GLOBOCAN 2012 by region and socioeconomic factors via the Human Development Index (HDI). Between- and within-country incidence by histological type was analyzed by using International Agency for Research on Cancer data on cancer incidence on five continents. Trend analyses including data from the International Agency for Research on Cancer, cancer registries, and the WHO mortality database were conducted using joinpoint regression. Survival was compared between and within countries and by histological type.

RESULTS

In 2012, there were 1.82 and 1.59 million new lung cancer cases and deaths worldwide, respectively. Incidence was highest in countries with a very high HDI and lowest in countries with a low HDI (42.2 versus 7.9 in 100,000 for males and 21.8 versus 3.1 in 100,000 for females, respectively). In most countries with a very high HDI, as incidence in males decreased gradually (ranging from -0.3% in Spain to -2.5% in the United States each year), incidence in females continued to increase (with the increase ranging from 1.4% each year in Australia to 6.1% in recent years in Spain). Although histological type varied between countries, adenocarcinoma was more common than squamous cell carcinoma, particularly among females (e.g., in Chinese females, the adenocarcinoma-to-squamous cell carcinoma ratio was 6.6). Five-year relative survival varied from 2% (Libya) to 30% (Japan), with substantial within-country differences.

CONCLUSIONS

Lung cancer will continue to be a major health problem well through the first half of this century. Preventive strategies, particularly tobacco control, tailored to populations at highest risk are key to reducing the global burden of lung cancer.

Validation of the SHOX2/PTGER4 DNA Methylation Marker Panel for Plasma-Based Discrimination between Patients with Malignant and Nonmalignant Lung Disease

Introduction

Low-dose computed tomography (LDCT) is used for screening for lung cancer (LC) in high-risk patients in the United States. The definition of high risk and the impact of frequent false-positive results of low-dose computed tomography remains a challenge. DNA methylation biomarkers are valuable noninvasive diagnostic tools for cancer detection. This study reports on the evaluation of methylation markers in plasma DNA for LC detection and discrimination of malignant from nonmalignant lung disease.

Methods

Circulating DNA was extracted from 3.5-mL plasma samples, treated with bisulfite using a commercially available kit, purified, and assayed by real-time polymerase chain reaction for assessment of DNA methylation of short stature homeobox 2 gene (SHOX2), prostaglandin E receptor 4 gene (PTGER4), and forkhead box L2 gene (FOXL2). In three independent case-control studies these assays were evaluated and optimized. The resultant assay, a triplex polymerase chain reaction combining SHOX2, PTGER4, and the reference gene actin, beta gene (ACTB), was validated using plasma from patients with and without malignant disease.

Results

A panel of SHOX2 and PTGER4 provided promising results in three independent case-control studies examining a total of 330 plasma specimens (area under the receiver operating characteristic curve = 91%–98%). A validation study with 172 patient samples demonstrated significant discriminatory performance in distinguishing patients with LC from subjects without malignancy (area under the curve = 0.88). At a fixed specificity of 90%, sensitivity for LC was 67%; at a fixed sensitivity of 90%, specificity was 73%.

Conclusions

Measurement of SHOX2 and PTGER4 methylation in plasma DNA allowed detection of LC and differentiation of nonmalignant diseases. Development of a diagnostic test based on this panel may provide clinical utility in combination with current imaging techniques to improve LC risk stratification.

Multiplexed Serum Biomarkers for the Detection of Lung Cancer

Currently, there is no available biomarker for lung cancer diagnosis. Here we recruited 844 lung cancer patients and 620 healthy participants from six hospitals. A total of four serum proteins was identified and subsequently assessed in the training and validation cohorts. The concentrations of four serum proteins were found to be significantly higher in lung cancer patients compared with healthy participants. The area under the curve (AUC) for the 4-biomarker were 0.86 in the training cohort, and 0.87 in the validation cohort. The classification improved to a corrected AUC of 0.90 and 0.89 respectively following addition of sex, age and smoking status. Similar results were observed for early-stage lung cancer. Remarkably, in a blinded test with a suspicious pulmonary nodule, the adjusted prediction model correctly discriminated the patients with 86.96% sensitivity and 98.25% specificity. These results demonstrated the 4-biomarker panel improved lung cancer prediction beyond that of known risk factors. Moreover, the biomarkers were valuable in differentiating benign nodules which will remain indolent from those that are likely to progress and therefore might serve as an adjuvant diagnosis tool for LDCT scanning.

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A multicentric, case–control study was conducted to identify serum proteins for diagnosing lung cancer.

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A 4-marker panel improved lung cancer prediction beyond that of known risk factors.

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The biomarkers can detect lung cancer especially stage I–II from healthy controls or benign nodule patients.

Currently, low dose chest computed tomography (LDCT) leads to a high false-positive result. Here we identified a panel of four serum proteins, which provides the potential for accurate diagnosis of lung cancer in a multicentric study. More importantly, the biomarkers allowed accurate detection of lung cancer cases especially stage I-II cases from normal and benign nodule subjects. These results suggest that the 4-protein panel might be a useful biomarker for diagnosing lung cancer patients and help discriminate early stage patients, which may serve as an adjuvant diagnosis tool for LDCT scanning in the future.

Lung cancer screening: Current status and perspective

Lung cancer screening by low-dose computed tomography (CT) has been proven to reduce lung cancer-related mortality by 20%, in the National Lung cancer Screening Trial (NLST). Low-dose CT acquisition protocols should result in effective dose not exceeding 1.5mSv, and should be read by radiologists who have an expertise in the field. A volumetry-based approach similar to that used in the NELSON study allows reducing the rate of positive screens around 2%. The major harm of screening is overdiagnosis, which correspond to the detection of indolent tumours that would not cause the subject death. Ongoing research for the development of useful biomarkers to be combined to imaging could improve the accuracy of lung cancer screening.