Evaluating Molecular Biomarkers for the Early Detection of Lung Cancer: When Is a Biomarker Ready for Clinical Use? An Official American Thoracic Society Policy Statement

Outcomes of clinical utility in amyloid-PET studies: state of art and future perspectives

PURPOSE

To review how outcomes of clinical utility are operationalized in current amyloid-PET validation studies, to prepare for formal assessment of clinical utility of amyloid-PET-based diagnosis.

METHODS

Systematic review of amyloid-PET research studies published up to April 2020 that included outcomes of clinical utility. We extracted and analyzed (a) outcome categories, (b) their definition, and (c) their methods of assessment.

RESULTS

Thirty-two studies were eligible. (a) Outcome categories were clinician-centered (found in 25/32 studies, 78%), patient-/caregiver-centered (in 9/32 studies, 28%), and health economics-centered (5/32, 16%). (b) Definition: Outcomes were mainly defined by clinical researchers; only the ABIDE study expressly included stakeholders in group discussions. Clinician-centered outcomes mainly consisted of incremental diagnostic value (25/32, 78%) and change in patient management (17/32, 53%); patient-/caregiver-centered outcomes considered distress after amyloid-pet-based diagnosis disclosure (8/32, 25%), including quantified burden of procedure for patients' outcomes (n = 8) (1/8, 12.5%), impact of disclosure of results (6/8, 75%), and psychological implications of biomarker-based diagnosis (75%); and health economics outcomes focused on costs to achieve a high-confidence etiological diagnosis (5/32, 16%) and impact on quality of life (1/32, 3%). (c) Assessment: all outcome categories were operationalized inconsistently across studies, employing 26 different tools without formal rationale for selection.

CONCLUSION

Current studies validating amyloid-PET already assessed outcomes for clinical utility, although non-clinician-based outcomes were inconsistent. A wider participation of stakeholders may help produce a more thorough and systematic definition and assessment of outcomes of clinical utility and help collect evidence informing decisions on reimbursement of amyloid-PET.

Contribution of a Blood-Based Protein Biomarker Panel to the Classification of Indeterminate Pulmonary Nodules

RATIONALE

The workup and longitudinal monitoring for subjects presenting with pulmonary nodules is a pressing clinical problem. A blood-based biomarker panel potentially has utility for identifying subjects at higher risk for harboring a malignant nodule for whom additional workup would be indicated or subjects at reduced risk for whom imaging-based follow-up would be indicated.

OBJECTIVES

To assess whether a previously described four-protein biomarker panel, reported to improve assessment of lung cancer risk compared with a smoking-based lung cancer risk model, can provide discrimination between benign and malignant indeterminate pulmonary nodules.

METHODS

A previously validated multiplex enzyme-linked immunoassay was performed on matched case and control samples from each cohort.

MEASUREMENTS

The biomarker panel was tested in two case-control cohorts of patients presenting with indeterminate pulmonary nodules at the University of Pittsburgh Medical Center and the University of Texas Southwestern.

MAIN RESULTS

In both cohorts, the biomarker panel resulted in improved prediction of lung cancer risk over a model on the basis of nodule size alone. Of particular note, the addition of the marker panel to nodule size greatly improved sensitivity at a high specificity in both cohorts.

CONCLUSIONS

A four-marker biomarker panel, previously validated to improve lung cancer risk prediction, was found to also have utility in distinguishing benign from malignant indeterminate pulmonary nodules. Its performance in improving sensitivity at a high specificity indicates potential utility of the marker panel in assessing likelihood of malignancy in otherwise indeterminate nodules.

Molecular biomarkers in early stage lung cancer

Low dose computed tomography (LDCT) screening, together with the recent advances in targeted and immunotherapies, have shown to improve non-small cell lung cancer (NSCLC) survival. Furthermore, screening has increased the number of early stage-detected tumors, allowing for surgical resection and multimodality treatments when needed. The need for improved sensitivity and specificity of NSCLC screening has led to increased interest in combining clinical and radiological data with molecular data. The development of biomarkers is poised to refine inclusion criteria for LDCT screening programs. Biomarkers may also be useful to better characterize the risk of indeterminate nodules found in the course of screening or to refine prognosis and help in the management of screening detected tumors. The clinical implications of these biomarkers are still being investigated and whether or not biomarkers will be included in further decision-making algorithms in the context of screening and early lung cancer management still needs to be determined. However, it seems clear that there is much room for improvement even in early stage lung cancer disease-free survival (DFS) rates; thus, biomarkers may be the key to refine risk-stratification and treatment of these patients. Clinicians’ capacity to register, integrate, and analyze all the available data in both high risk individuals and early stage NSCLC patients will lead to a better understanding of the disease’s mechanisms, and will have a direct impact in diagnosis, treatment, and follow up of these patients. In this review, we aim to summarize all the available data regarding the role of biomarkers in LDCT screening and early stage NSCLC from a multidisciplinary perspective. We have highlighted clinical implications, the need to combine risk stratification, clinical data, radiomics, molecular information and artificial intelligence in order to improve clinical decision-making, especially regarding early diagnostics and adjuvant therapy. We also discuss current and future perspectives for biomarker implementation in routine clinical practice.

Chr15q25 genetic variant (rs16969968) independently confers risk of lung cancer, COPD and smoking intensity in a prospective study of high-risk smokers

IMPORTANCE

While cholinergic receptor nicotinic alpha 5 (CHRNA5) variants have been linked to lung cancer, chronic obstructive pulmonary disease (COPD) and smoking addiction in case-controls studies, their corelationship is not well understood and requires retesting in a cohort study.

OBJECTIVE

To re-examine the association between the CHRNA5 variant (rs16969968 AA genotype) and the development of lung cancer, relative to its association with COPD and smoking.

METHODS

In 9270 Non-Hispanic white subjects from the National Lung Screening Trial, a substudy of high-risk smokers were followed for an average of 6.4 years. We compared CHRNA5 genotype according to baseline smoking exposure, lung function and COPD status. We also compared the lung cancer incidence rate, and used multiple logistic regression and mediation analysis to examine the role of the AA genotype of the CHRNA5 variant in smoking exposure, COPD and lung cancer.

RESULTS

As previously reported, we found the AA high-risk genotype was associated with lower lung function (p=0.005), greater smoking intensity (p<0.001), the presence of COPD (OR 1.28 (95% CI 1.10 to 1.49) p=0.0015) and the development of lung cancer (HR 1.41, (95% CI 1.03 to 1.93) p=0.03). In a mediation analyses, the AA genotype was independently associated with smoking intensity (OR 1.42 (95% CI 1.25 to 1.60, p<0.0001), COPD (OR 1.25, (95% CI 1.66 to 2.53), p=0.0015) and developing lung cancer (OR 1.37, (95% CI 1.03 to 1.82) p=0.03).

CONCLUSION

In this large-prospective study, we found the CHRNA5 rs 16 969 968 AA genotype to be independently associated with smoking exposure, COPD and lung cancer (triple whammy effect).

Data preprocessing workflow for exhaled breath analysis by GC/MS using open sources

The noninvasive diagnosis and monitoring of high prevalence diseases such as cardiovascular diseases, cancers and chronic respiratory diseases are currently priority objectives in the area of health. In this regard, the analysis of volatile organic compounds (VOCs) has been identified as a potential noninvasive tool for the diagnosis and surveillance of several diseases. Despite the advantages of this strategy, it is not yet a routine clinical tool. The lack of reproducible protocols for each step of the biomarker discovery phase is an obstacle of the current state. Specifically, this issue is present at the data preprocessing step. Thus, an open source workflow for preprocessing the data obtained by the analysis of exhaled breath samples using gas chromatography coupled with single quadrupole mass spectrometry (GC/MS) is presented in this paper. This workflow is based on the connection of two approaches to transform raw data into a useful matrix for statistical analysis. Moreover, this workflow includes matching compounds from breath samples with a spectral library. Three free packages (xcms, cliqueMS and eRah) written in the language R are used for this purpose. Furthermore, this paper presents a suitable protocol for exhaled breath sample collection from infants under 2 years of age for GC/MS.

Lung cancer screening by nodule volume in Lung-RADS v1.1: negative baseline CT yields potential for increased screening interval

Objectives

The 2019 Lung CT Screening Reporting & Data System version 1.1 (Lung-RADS v1.1) introduced volumetric categories for nodule management. The aims of this study were to report the distribution of Lung-RADS v1.1 volumetric categories and to analyse lung cancer (LC) outcomes within 3 years for exploring personalized algorithm for lung cancer screening (LCS).

Methods

Subjects from the Multicentric Italian Lung Detection (MILD) trial were retrospectively selected by National Lung Screening Trial (NLST) criteria. Baseline characteristics included selected pre-test metrics and nodule characterization according to the volume-based categories of Lung-RADS v1.1. Nodule volume was obtained by segmentation with dedicated semi-automatic software. Primary outcome was diagnosis of LC, tested by univariate and multivariable models. Secondary outcome was stage of LC. Increased interval algorithms were simulated for testing rate of delayed diagnosis (RDD) and reduction of low-dose computed tomography (LDCT) burden.

Results

In 1248 NLST-eligible subjects, LC frequency was 1.2% at 1 year, 1.8% at 2 years and 2.6% at 3 years. Nodule volume in Lung-RADS v1.1 was a strong predictor of LC: positive LDCT showed an odds ratio (OR) of 75.60 at 1 year (p < 0.0001), and indeterminate LDCT showed an OR of 9.16 at 2 years (p = 0.0068) and an OR of 6.35 at 3 years (p = 0.0042). In the first 2 years after negative LDCT, 100% of resected LC was stage I. The simulations of low-frequency screening showed a RDD of 13.6–21.9% and a potential reduction of LDCT burden of 25.5–41%.

Conclusions

Nodule volume by semi-automatic software allowed stratification of LC risk across Lung-RADS v1.1 categories. Personalized screening algorithm by increased interval seems feasible in 80% of NLST eligible.

Key Points

• Using semi-automatic segmentation of nodule volume, Lung-RADS v1.1 selected 10.8% of subjects with positive CT and 96.87 relative risk of lung cancer at 1 year, compared to negative CT.

• Negative low-dose CT by Lung-RADS v1.1 was found in 80.6% of NLST eligible and yielded 40 times lower relative risk of lung cancer at 2 years, compared to positive low-dose CT; annual screening could be preference sensitive in this group.

• Semi-automatic segmentation of nodule volume and increased screening interval by volumetric Lung-RADS v1.1 could retrospectively suggest a 25.5–41% reduction of LDCT burden, at the cost of 13.6–21.9% rate of delayed diagnosis.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07275-w) contains supplementary material, which is available to authorized users.

Statistical inference for net benefit measures in biomarker validation studies

Referral strategies based on risk scores and medical tests are commonly proposed. Direct assessment of their clinical utility requires implementing the strategy and is not possible in the early phases of biomarker research. Prior to late-phase studies, net benefit measures can be used to assess the potential clinical impact of a proposed strategy. Validation studies, in which the biomarker defines a prespecified referral strategy, are a gold standard approach to evaluating biomarker potential. Uncertainty, quantified by a confidence interval, is important to consider when deciding whether a biomarker warrants an impact study, does not demonstrate clinical potential, or that more data are needed. We establish distribution theory for empirical estimators of net benefit and propose empirical estimators of variance. The primary results are for the most commonly employed estimators of net benefit: from cohort and unmatched case-control samples, and for point estimates and net benefit curves. Novel estimators of net benefit under stratified two-phase and categorically matched case-control sampling are proposed and distribution theory developed. Results for common variants of net benefit and for estimation from right-censored outcomes are also presented. We motivate and demonstrate the methodology with examples from lung cancer research and highlight its application to study design.

Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician's Point of View

Starting from the work of Ulivi and colleagues, we aim to summarize the research area of biomarkers for early diagnosis and early stage lung cancer.

Approaches to lung nodule risk assessment: clinician intuition versus prediction models

Pulmonary nodules are increasingly identified on imaging exams performed for a number of clinical presentations and can pose a diagnostic problem for clinicians. Guideline-directed management algorithms are structured on nodule pre-test probability of malignancy. The risk of malignancy can be clinician-assigned or calculated utilizing validated risk prediction calculators. Once pre-test probability of cancer is estimated, nodule management options range from a conservative approach with serial imaging to more invasive measures including biopsy procedures or surgical resection. Here we review pulmonary nodule management with a focus on methods for assigning malignancy risk and highlight novel ways currently under active research to improve nodule risk assessment and management.

The diagnostic value of a seven-autoantibody panel and a nomogram with a scoring table for predicting the risk of non-small-cell lung cancer

The early detection of non-small-cell lung cancer (NSCLC) remains a common concern. The aim of our study was to validate the diagnostic value of a seven-autoantibody (7-AAB) panel compared with radiological diagnosis for NSCLC. We constructed a nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC. We prospectively enrolled 268 patients who presented with radiological lesions and underwent both the 7-AAB panel test and pathological diagnosis by surgical resection. A comparison between the 7-AAB panel and radiological diagnosis was performed. A nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC were constructed and internally validated. The 7-AAB panel test had a specificity of 90.2% and a positive predictive value (PPV) of 92.7%, which were significantly higher than those of the radiological diagnosis. The 7-AAB panel also showed a preferable sensitivity in patients with early-stage disease. Seven factors, including the 7-AAB panel results, were integrated into the nomogram. For more convenient application, we formulated a scoring table based on the nomogram. The area under the receiver operating characteristic curve was 0.840 and 0.860 in the training group and validation group, respectively, which was higher than that using the 7-AAB panel or radiological diagnosis alone. This study reveals that our 7-AAB panel has clinical value in the diagnosis of NSCLC. The utility of our nomogram and the scoring table indicated that they have the potential to assist clinicians in avoiding unnecessary treatment or needless follow-up.

Circulating tumor DNA as an early cancer detection tool

Circulating tumor DNA holds substantial promise as an early detection biomarker, particularly for cancers that do not have currently accepted screening methodologies, such as ovarian, pancreatic, and gastric cancers. Many features intrinsic to ctDNA analysis may be leveraged to enhance its use as an early cancer detection biomarker: including ctDNA fragment lengths, DNA copy number variations, and associated patient phenotypic information. Furthermore, ctDNA testing may be synergistically used with other multi-omic biomarkers to enhance early detection. For instance, assays may incorporate early detection proteins (i.e., CA-125), epigenetic markers, circulating tumor RNA, nucleosomes, exosomes, and associated immune markers. Many companies are currently competing to develop a marketable early cancer detection test that leverages ctDNA. Although some hurdles (like early stage disease assay accuracy, high implementation costs, confounding from clonal hematopoiesis, and lack of clinical utility studies) need to be addressed before integration into healthcare, ctDNA assays hold substantial potential as an early cancer screening test.

Identification of Three lncRNAs as Potential Predictive Biomarkers of Lung Adenocarcinoma

Background

Lung cancer is the most common cancer and the most common cause of cancer-related death worldwide. However, the molecular mechanism of its development is unclear. It is imperative to identify more novel biomarkers.

Methods

Two datasets (GSE70880 and GSE113852) were downloaded from the Gene Expression Omnibus (GEO) database and used to identify the differentially expressed genes (DEGs) between lung cancer tissues and normal tissues. Then, we constructed a competing endogenous RNA (ceRNA) network and a protein-protein interaction (PPI) network and performed gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and survival analyses to identify potential biomarkers that are related to the diagnosis and prognosis of lung cancer.

Results

A total of 41 lncRNAs and 805 mRNAs were differentially expressed in lung cancer. The ceRNA network contained four lncRNAs (CLDN10-AS1, SFTA1P, SRGAP3-AS2, and ADAMTS9-AS2), 21 miRNAs, and 48 mRNAs. Functional analyses revealed that the genes in the ceRNA network were mainly enriched in cell migration, transmembrane receptor, and protein kinase activity. mRNAs DLGAP5, E2F7, MCM7, RACGAP1, and RRM2 had the highest connectivity in the PPI network. Immunohistochemistry (IHC) demonstrated that mRNAs DLGAP5, MCM7, RACGAP1, and RRM2 were upregulated in lung adenocarcinoma (LUAD). Survival analyses showed that lncRNAs CLDN10-AS1, SFTA1P, and ADAMTS9-AS2 were associated with the prognosis of LUAD.

Conclusion

lncRNAs CLDN10-AS1, SFTA1P, and ADAMTS9-AS2 might be the biomarkers of LUAD. For the first time, we confirmed the important role of lncRNA CLDN10-AS1 in LUAD.

ESR/ERS statement paper on lung cancer screening

In Europe, lung cancer ranks third among the most common cancers, remaining the biggest killer. Since the publication of the first European Society of Radiology and European Respiratory Society joint white paper on lung cancer screening (LCS) in 2015, many new findings have been published and discussions have increased considerably. Thus, this updated expert opinion represents a narrative, non-systematic review of the evidence from LCS trials and description of the current practice of LCS as well as aspects that have not received adequate attention until now. Reaching out to the potential participants (persons at high risk), optimal communication and shared decision-making will be key starting points. Furthermore, standards for infrastructure, pathways and quality assurance are pivotal, including promoting tobacco cessation, benefits and harms, overdiagnosis, quality, minimum radiation exposure, definition of management of positive screen results and incidental findings linked to respective actions as well as cost-effectiveness. This requires a multidisciplinary team with experts from pulmonology and radiology as well as thoracic oncologists, thoracic surgeons, pathologists, family doctors, patient representatives and others. The ESR and ERS agree that Europe's health systems need to adapt to allow citizens to benefit from organised pathways, rather than unsupervised initiatives, to allow early diagnosis of lung cancer and reduce the mortality rate. Now is the time to set up and conduct demonstration programmes focusing, among other points, on methodology, standardisation, tobacco cessation, education on healthy lifestyle, cost-effectiveness and a central registry.

ESR/ERS statement paper on lung cancer screening

In Europe, lung cancer ranks third among the most common cancers, remaining the biggest killer. Since the publication of the first European Society of Radiology and European Respiratory Society joint white paper on lung cancer screening (LCS) in 2015, many new findings have been published and discussions have increased considerably. Thus, this updated expert opinion represents a narrative, non-systematic review of the evidence from LCS trials and description of the current practice of LCS as well as aspects that have not received adequate attention until now. Reaching out to the potential participants (persons at high risk), optimal communication and shared decision-making will be key starting points. Furthermore, standards for infrastructure, pathways and quality assurance are pivotal, including promoting tobacco cessation, benefits and harms, overdiagnosis, quality, minimum radiation exposure, definition of management of positive screen results and incidental findings linked to respective actions as well as cost-effectiveness. This requires a multidisciplinary team with experts from pulmonology and radiology as well as thoracic oncologists, thoracic surgeons, pathologists, family doctors, patient representatives and others. The ESR and ERS agree that Europe's health systems need to adapt to allow citizens to benefit from organised pathways, rather than unsupervised initiatives, to allow early diagnosis of lung cancer and reduce the mortality rate. Now is the time to set up and conduct demonstration programmes focusing, among other points, on methodology, standardisation, tobacco cessation, education on healthy lifestyle, cost-effectiveness and a central registry.Key Points• Pulmonologists and radiologists both have key roles in the set up of multidisciplinary LCS teams with experts from many other fields.• Pulmonologists identify people eligible for LCS, reach out to family doctors, share the decision-making process and promote tobacco cessation.• Radiologists ensure appropriate image quality, minimum dose and a standardised reading/reporting algorithm, together with a clear definition of a "positive screen".• Strict algorithms define the exact management of screen-detected nodules and incidental findings.• For LCS to be (cost-)effective, it has to target a population defined by risk prediction models.

Biomarkers in Lung Cancer

Biomarkers that focus on lung cancer risk assessment, detection, prognosis, diagnosis, and personalized treatment are in various stages of development. This article provides an overview of lung cancer biomarker development, focusing on clinical utility and highlighting 2 unmet clinical needs: selection of high-risk patients for lung cancer screening and differentiation of early lung cancer from benign pulmonary nodules. The authors highlight biomarkers under development and those lung cancer screening and nodule management biomarkers post-clinical validation. Finally, trends in lung cancer biomarker development that may improve accuracy and accelerate implementation in practice are discussed.

A panel of autoantibodies against tumor-associated antigens in the early immunodiagnosis of lung cancer

OBJECTIVE

Lung cancer (LC) is one of the most common malignant tumors worldwide with low five-year survival rate due to lack of effective diagnosis. This study aims to find an optimal combination of autoantibodies for detecting of early-stage LC.

METHODS

Nine relatively novel autoantibodies against tumor-associated (TAAs) (PSIP1, TOP2A, ACTR3, RPS6KA5, HMGB3, MMP12, GREM1, ZWINT and NUSAP1) were detected by using ELISA. Diagnostic models were developed by using the training set (n = 644) and further validated in another independent set (n = 248). We also evaluated the diagnostic accuracy of the model to detect benign lung diseases (BLD) from the early-stage lung cancer.

RESULTS

The areas under the receiver operating characteristic curve (AUC) for the model with three TAAs panel (GREM1, HMGB3 and PSIP1) was 0.711(95% CI 0.674-0.746) in the training set and 0.858 (95% CI 0.808-0.899) in the validation set, which demonstrated a higher diagnostic capability. The AUC of this three TAAs model was 0.833 (95%CI 0.780-0.878) in discriminating LC from BLD. This model could identify early-stage LC patients from normal control (NC) individuals, with AUC of 0.687(95% CI 0.634-0.736) in training set and AUC of 0.920(95% CI 0.860-0.960) in validation set, and the overall AUC for early-stage LC was 0.779(95% CI 0.739-0.816) when the training set and validation set were combined.

CONCLUSIONS

The model with three TAAs panel would detect LC with higher effectiveness, and might be potential screening method for the early LC.

Exhaled breath condensate biomarkers for lung cancer

Lung cancer is the main cause of cancer incidence and mortality worldwide and the identification of clinically useful biomarkers for lung cancer detection at both early and metastatic stage is a pressing medical need. Although many improvements have been made in the treatment and in the early screening of this cancer, most diagnosis are made at a late stage, when a lot of genetic and epigenetic changes have occurred. A promising source of biomarkers reflective of the pathogenesis of lung cancer is exhaled breath condensate (EBC), a biological fluid and a natural matrix of the respiratory tract. Molecules such as DNAs, RNAs, proteins, metabolites and volatile compounds are present in EBC, and their presence/absence or their variation in concentrations can be used as biomarkers. The aims of this review are to briefly describe exhaled breath composition, firstly, and then to document some of the EBC candidate biomarkers for lung cancer by dividing them according to their origin (genome, transcriptome, epigenome, metabolome, proteome and microbiota) in order to demonstrate the potential use of EBC as a helpful tool in cancer diagnostics, molecular profiling, therapy monitoring and screening of high risk individuals.

5-year overall survival in patients with lung cancer eligible or ineligible for screening according to US Preventive Services Task Force criteria: a prospective, observational cohort study

BACKGROUND

The US Preventive Services Task Force (USPSTF) recommends lung cancer screening among individuals aged 55-80 years with a 30 pack-year cigarette smoking history and, if they are former smokers, those who quit within the past 15 years. Our previous report found that two-thirds of newly diagnosed patients with lung cancer do not meet these criteria; they are reported to be either long-term quitters (≥15 years since quitting) or from a younger age group (age 50-54 years). We aimed to assess survival outcomes in these two subgroups.

METHODS

For this prospective, observational cohort study we identified and followed up patients aged 50-80 years with lung cancer, with a smoking history of 30 pack-years or more, and included both current smokers and former smokers who quit within the past 30 years. We identified patients from two cohorts in the USA: a hospital cohort (Mayo Clinic, Rochester, MN) and a community cohort (Olmsted County, MN). Patients were divided into those meeting USPSTF criteria (USPSTF group) versus those not meeting USPSTF criteria (long-term quitters or the younger age group). The main outcome was overall survival at 5 years after diagnosis. 5-year overall survival was analysed with and without matching age and pack-years smoked for long-term quitters. The USPSTF group was subdivided into two age subgroups (55-69 years and 70-80 years) for multivariable regression analysis.

FINDINGS

Between Jan 1, 1997, and Dec 31, 2017, 8739 patients with lung cancer were identified and followed up. Median follow-up was 6·5 (IQR 3·8-10·0) years, and median overall survival was 16·9 months (95% CI 16·2-17·5). 5-year overall survival was 27% (95% CI 25-30) in long-term quitters, 22% (19-25) in the younger age group, and 23% (22-24) in the USPSTF group. In both cohorts, 5-year overall survival did not differ significantly between long-term quitters and the USPSTF group (hospital cohort: hazard ratio [HR] 1·02 [95% CI 0·94-1·10]; p=0·72; community cohort: 0·97 [0·75-1·26]; p=0·82); matched analysis showed similar results in both cohorts. 5-year overall survival also did not differ significantly between the younger age group and the USPSTF group in both cohorts (hospital cohort: HR 1·16 [95% CI 0·98-1·38], p=0·08; community cohort: 1·16 [0·74-1·82]; p=0·52); multivariable regression analyses stratified by age group yielded similar findings.

INTERPRETATION

Patients with lung cancer who quit 15 or more years before diagnosis and those who are up to 5 years younger than the age cutoff recommended for screening, but otherwise meet USPSTF criteria, have a similar risk of death to those individuals who meet all USPSTF criteria. Individuals in both subgroups could benefit from screening, as expansion of USPSTF screening criteria to include these subgroups could enable earlier detection of lung cancer and improved survival outcomes.

FUNDING

National Institutes of Health and the Mayo Clinic Foundation.

Multiplex plasma protein profiling identifies novel markers to discriminate patients with adenocarcinoma of the lung

Background

The overall prognosis of non-small cell lung cancer (NSCLC) is poor, and currently only patients with localized disease are potentially curable. Therefore, preferably non-invasively determined biomarkers that detect NSCLC patients at early stages of the disease are of high clinical relevance. The aim of this study was to identify and validate novel protein markers in plasma using the highly sensitive DNA-assisted multiplex proximity extension assay (PEA) to discriminate NSCLC from other lung diseases.

Methods

Plasma samples were collected from a total of 343 patients who underwent surgical resection for different lung diseases, including 144 patients with lung adenocarcinoma (LAC), 68 patients with non-malignant lung disease, 83 patients with lung metastasis of colorectal cancers and 48 patients with typical carcinoid. One microliter of plasma was analyzed using PEA, allowing detection and quantification of 92 established cancer related proteins. The concentrations of the plasma proteins were compared between disease groups.

Results

The comparison between LAC and benign samples revealed significantly different plasma levels for four proteins; CXCL17, CEACAM5, VEGFR2 and ERBB3 (adjusted p-value < 0.05). A multi-parameter classifier was developed to discriminate between samples from LAC patients and from patients with non-malignant lung conditions. With a bootstrap aggregated decision tree algorithm (TreeBagger), a sensitivity of 93% and specificity of 64% was achieved to detect LAC in this risk population.

Conclusions

By applying the highly sensitive PEA, reliable protein profiles could be determined in microliter amounts of plasma. We further identified proteins that demonstrated different plasma concentration in defined disease groups and developed a signature that holds potential to be included in a screening assay for early lung cancer detection.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-5943-3) contains supplementary material, which is available to authorized users.

The potential impact of chronic obstructive pulmonary disease in lung cancer screening: implications for the screening clinic

Introduction: Following the findings of the National Lung Screening Trial (NLST), lung cancer screening is now recommended in the United States. However, post-hoc analyses of the NLST suggest that reducing lung cancer mortality through screening is highly dependent on the underlying characteristics of the screening participants, in particular, the presence of chronic obstructive pulmonary disease (COPD). Areas covered: In this review, we outline how outcomes in lung cancer screening are significantly affected by the presence of airflow limitation, as caused by COPD, and how this might impact the assessment of eligible smokers in a lung cancer screening clinic. Expert opinion: There is growing evidence showing that CT-based screening for lung cancer reduces lung cancer mortality. The benefits of screening exceed those seen in the NLST when screening is carried out in lower risk populations, for a longer duration, and when outcomes are compared with usual care control cohorts. In this article, we review data from a post-hoc analysis of the NLST. We suggest that whilst worsened airflow limitation is associated with greater lung cancer risk, there is also more aggressive lung cancer, reduced lung cancer operability, and for advanced COPD, reduced benefits from screening. We advocate an 'outcomes-based' approach to screening over a 'risk-based' approach.

Effect of a Rule-in Biomarker Test on Pulmonary Nodule Management: A Survey of Pulmonologists and Thoracic Surgeons

INTRODUCTION

The field of biomarker development is evolving to assist in determining benign from malignant pulmonary nodules. Although a prospective clinical utility would best to show how a biomarker affects patient treatment and outcomes, we sought to begin to understand how the results might alter management by determining how physicians would use the results of a rule-in blood test to manage pulmonary nodules.

MATERIALS AND METHODS

Pulmonologists and thoracic surgeons in the American College of Chest Physicians clinician database were invited to participate in an online survey. The participant demographic data were collected. Four hypothetical clinical vignettes were presented. The participants accessed the pretest probability (probability of cancer [pCA]) for malignancy and chose the management strategies as the case progressed. The management strategies chosen before and after the result of a rule-in biomarker test were compared and assessed for guideline concordance.

RESULTS

Of the 455 eligible participants who had opened the survey, 416 (92%) completed it: 332 pulmonologists and 84 thoracic surgeons. Although 91% of the participants were very comfortable managing nodules, depending on the case, 30% to 62% incorrectly assessed the pCA, with 22% to 62% overestimating the risk and 8% to 51% underestimating the risk. After a rule-in blood test result, the clinician change in management moved in the right direction in some cases but, in others, the physicians used the results incorrectly. Pulmonologists and thoracic surgeons differed in the management strategies, with surgeons recommending surgery more often.

CONCLUSIONS

Although the use of biomarker testing for pulmonary nodule evaluation is promising, without proper physician education, the potential for harm exists. Clinical utility studies are needed to appropriately inform the effect of biomarker use.

Update on screening for lung cancer

As the leading cause of cancer related death world wide, lung cancer is responsible for an enormous amount of suffering and disability. Detection of disease when it is surgically curable is associated with far greater odds of cure, and therefore it is a disease for which mass screening of high-risk populations has significant potential benefit. Starting in 2011, with the publication of the National Lung Screening Trial from United States (U.S.), mass screening programs have emerged throughout the U.S., as well as in other countries. More recently, large European screening trials have confirmed the potential mortality benefit of lung cancer screening. This invited non-systematic review paper covers the trial that data justify mass-screening, for lung cancer and proposes strategies for maximizing benefits and minimizing harms in the context of a mass public health lung cancer screening program.

Suppressing growth and invasion of human hepatocellular carcinoma cells by celecoxib through inhibition of cyclooxygenase-2

Purpose: Biomarkers are lacking in hepatocellular carcinoma (HCC). Cyclooxygenase-2 (COX-2) and its metabolites play crucial roles in the process of inflammation-tumor transformation. This study was aimed to detect COX-2 expression in HCC tissues and evaluate the effects of a COX-2 inhibitor, celecoxib, on biological behaviors of HCC cell lines in vitro.

Methods: COX-2 expression was detected by immunohistochemistry on a human HCC tissue microarray. The correlations of COX-2 expression with tumor clinicopathological variables and overall survival were analyzed. The proliferation, apoptosis, cell cycle distribution, invasion capacity, and related signaling molecules of HCC cells after incubated with COX-2 inhibitor celecoxib were evaluated in vitro.

Results: Expression levels of COX-2 in HCC tissues were significantly higher than those in paracancerous tissues. The TNM stage III-IV, tumor size >5 cm, lymphovascular invasion and distant metastasis was higher in high COX-2 expression group compared with that in low COX-2 expression group. Patients with low COX-2 expression achieved better 5-year overall survival than those with high COX-2 expression. Treatment with celecoxib was sufficient to inhibit cell proliferation, promote apoptosis, and induce G0/G1 cell cycle arrest in HCC cells with concentration- and time-dependent manners. Celecoxib up-regulated E-cadherin protein through inhibiting COX-2-prostaglandin E2 (PGE2)-PGE2 receptor 2 (EP2)-p-Akt/p-ERK signaling pathway to suppress HCC cells migration and invasion.

Conclusion: High COX-2 expression was associated with advanced TNM stage, larger tumor size, increased lymphovascular invasion and short survival. Targeting inhibition of COX-2 by celecoxib exhibited anti-tumor activities by suppressing proliferation, promoting apoptosis, and inhibiting the aggressive properties of HCC cells.

Next-generation sequencing of circulating tumor DNA for detection of gene mutations in lung cancer: implications for precision treatment

Background

Lung cancer remains a major global health problem, which causes millions of deaths annually. Because the prognosis is mainly determined by the stage of lung cancer, precise early diagnosis is of great significance to improve the survival and prognosis. Circulating tumor DNA (ctDNA) has been recognized as a sensitive and specific biomarker for the detection of early- and late-stage lung cancer, and next-generation sequencing (NGS) of ctDNA has been accepted as a noninvasive tool for early identification and monitoring of cancer mutations. This study aimed to assess the value of NGS-based ctDNA analysis in detecting gene mutations in lung cancer patients.

Methods

A total of 101 subjects with pathological diagnosis of lung cancer were enrolled, and blood samples were collected. ctDNA samples were prepared and subjected to NGS assays.

Results

There were 31 cases harboring 40 gene mutations, and EGFR was the most frequently mutated gene (27.72%). In addition, there were seven cases with double mutations and one case with triple mutations, with EGFR p.T790M mutation exhibiting the highest frequency.

Conclusion

Our findings demonstrate that NGS of ctDNA is effective in detecting gene mutations in lung cancer patients, and may be used as a liquid biopsy for lung cancer, which facilitates the development of precision treatment regimens for lung cancer.

Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges

The present review is an update of the research and development efforts regarding the use of molecular biomarkers in the lung cancer screening setting. The two main unmet clinical needs, namely, the refinement of risk to improve the selection of individuals undergoing screening and the characterization of undetermined nodules found during the computed tomography-based screening process are the object of the biomarkers described in the present review. We first propose some principles to optimize lung cancer biomarker discovery projects. Then, we summarize the discovery and developmental status of currently promising molecular candidates, such as autoantibodies, complement fragments, microRNAs, circulating tumor DNA, DNA methylation, blood protein profiling, or RNA airway or nasal signatures. We also mention other emerging biomarkers or new technologies to follow, such as exhaled breath biomarkers, metabolomics, sputum cell imaging, genetic predisposition studies, and the integration of next-generation sequencing into study of circulating DNA. We also underline the importance of integrating different molecular technologies together with imaging, radiomics, and artificial intelligence. We list a number of completed, ongoing, or planned trials to show the clinical utility of molecular biomarkers. Finally, we comment on future research challenges in the field of biomarkers in the context of lung cancer screening and propose a design of a trial to test the clinical utility of one or several candidate biomarkers.

Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay

BACKGROUND

The increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identification of malignant nodules may represent a potentially curable form of lung cancer.

OBJECTIVE

To develop and validate a plasma-based multiplexed protein assay for classifying IPN by discriminating between those with a lung cancer diagnosis established pathologically and those found to be clinically and radiographically stable for at least one year.

METHODS

Using a novel technology, we developed assays for plasma proteins associated with lung cancer into a panel for characterizing the risk that an IPN found on chest imaging is malignant. The assay panel was evaluated with a cohort of 277 samples, all from current smokers with an IPN 4-30 mm. Subjects were divided into training and test sets to identify a Support Vector Machine (SVM) model for risk classification containing those proteins and clinical factors that added discriminatory information to the Veteran's Affairs (VA) Clinical Factors Model. The algorithm was then evaluated in an independent validation cohort.

RESULTS

Among the 97 validation study subjects, 68 were grouped as having intermediate risk by the VA model of which the SVM model correctly identified 44 (65%) of these intermediate-risk samples as low (n=16) or high risk (n=28). The SVM model negative predictive value (NPV) was 94% and its sensitivity was 94%.

CONCLUSION

The performance of the novel plasma protein biomarker assay supports its use as a noninvasive risk assessment aid for characterizing IPN. The high NPV of the SVM model suggests its application as a rule-out test to increase the confidence of providers to avoid aggressive interventions for their patients for whom the VA model result is an inconclusive, intermediate risk.

[China National Lung Cancer Screening Guideline with Low-dose Computed Tomography (2018 version)]

BACKGROUND

Lung cancer is the leading cause of cancer-related death in China. The results from a randomized controlled trial using annual low-dose computed tomography (LDCT) in specific high-risk groups demonstrated a 20% reduction in lung cancer mortality. The aim of tihs study is to establish the China National lung cancer screening guidelines for clinical practice.

METHODS

The China lung cancer early detection and treatment expert group (CLCEDTEG) established the China National Lung Cancer Screening Guideline with multidisciplinary representation including 4 thoracic surgeons, 4 thoracic radiologists, 2 medical oncologists, 2 pulmonologists, 2 pathologist, and 2 epidemiologist. Members have engaged in interdisciplinary collaborations regarding lung cancer screening and clinical care of patients with at risk for lung cancer. The expert group reviewed the literature, including screening trials in the United States and Europe and China, and discussed local best clinical practices in the China. A consensus-based guidelines, China National Lung Cancer Screening Guideline (CNLCSG), was recommended by CLCEDTEG appointed by the National Health and Family Planning Commission, based on results of the National Lung Screening Trial, systematic review of evidence related to LDCT screening, and protocol of lung cancer screening program conducted in rural China.

RESULTS

Annual lung cancer screening with LDCT is recommended for high risk individuals aged 50-74 years who have at least a 20 pack-year smoking history and who currently smoke or have quit within the past five years. Individualized decision making should be conducted before LDCT screening. LDCT screening also represents an opportunity to educate patients as to the health risks of smoking; thus, education should be integrated into the screening process in order to assist smoking cessation.

CONCLUSIONS

A lung cancer screening guideline is recommended for the high-risk population in China. Additional research , including LDCT combined with biomarkers, is needed to optimize the approach to low-dose CT screening in the future.

Metabolome-based biomarkers: their potential role in the early detection of lung cancer

Lung cancer is the leading cause of cancer-related death worldwide, and a major problem affecting its mortality is the late diagnosis of the majority of cases, where treatment options are limited and overall prognosis is very bad. Currently, a low-dose computed tomography (LD-CT) screening in the high-risk group is the only available diagnostic strategy that could reduce mortality due to this malignancy. However, the LD-CT screening test suffers from a high false positive rate. Hence, complementation of LD-CT examination with blood-based biomarkers is a rational approach to increase efficacy and reduce the cost of early lung cancer screening programs. Several molecular signatures that discriminate between patients with early lung cancer and healthy individuals have been proposed in recent years, which are based on components of serum/plasma metabolome. However, none of these signatures has been validated by independent studies based on material collected during real lung cancer screening. Therefore, the validation of the real diagnostic value of these otherwise promising candidates remains a critical step in this challenging field of cancer diagnostics.

Chronic obstructive pulmonary disease (COPD) and lung cancer screening

The primary aim of lung cancer screening is to improve survival from lung cancer by identifying early stage non-small cell lung cancers and prolong survival through their surgical removal. In a post-hoc analysis of 10,054 screening participants from the National Lung Screening Trial (NLST) we show that the risk of lung cancer, according to the PLCOm2012 model, is closely related to the likelihood of having chronic obstructive pulmonary disease (COPD). Those at greatest risk for lung cancer have the highest prevalence of COPD and greater likelihood of dying of a non-lung cancer cause. This "competing cause of death" effect occurs because smokers eligible for lung cancer screening have a high prevalence of comorbid disease and greater likelihood of dying from cardiovascular disease, respiratory disease or other cancers. This means high risk smokers at greatest risk of lung cancer may not necessarily benefit from screening due to greater inoperability and premature death. In this analysis we show that the benefit of annual computed tomography (CT) screening is greatest in those with normal lung function or only mild-to-moderate COPD. We found no mortality benefit in those with severe or very severe COPD (GOLD 3-4). We also show that the efficiency of screening, based on optimizing the number of lung cancer deaths averted per 1,000 persons screened, is best achieved by screening those at intermediate risk. By combining clinical risk variables with a gene-based risk score, even greater reductions in lung cancer mortality can be achieved with CT. We suggest a biomarker-led outcomes-based approach may help to better define which eligible smokers might defer screening (low risk of lung cancer), discontinue screening (high risk of overtreatment with little benefit) or continue screening to achieve the greatest reduction in lung cancer mortality.

Assessment of Plasma Proteomics Biomarker's Ability to Distinguish Benign From Malignant Lung Nodules: Results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) Trial

Background

Lung nodules are a diagnostic challenge, with an estimated yearly incidence of 1.6 million in the United States. This study evaluated the accuracy of an integrated proteomic classifier in identifying benign nodules in patients with a pretest probability of cancer (pCA) ≤ 50%.

Methods

A prospective, multicenter observational trial of 685 patients with 8- to 30-mm lung nodules was conducted. Multiple reaction monitoring mass spectrometry was used to measure the relative abundance of two plasma proteins, LG3BP and C163A. Results were integrated with a clinical risk prediction model to identify likely benign nodules. Sensitivity, specificity, and negative predictive value were calculated. Estimates of potential changes in invasive testing had the integrated classifier results been available and acted on were made.

Results

A subgroup of 178 patients with a clinician-assessed pCA ≤ 50% had a 16% prevalence of lung cancer. The integrated classifier demonstrated a sensitivity of 97% (CI, 82-100), a specificity of 44% (CI, 36-52), and a negative predictive value of 98% (CI, 92-100) in distinguishing benign from malignant nodules. The classifier performed better than PET, validated lung nodule risk models, and physician cancer probability estimates (P < .001). If the integrated classifier results were used to direct care, 40% fewer procedures would be performed on benign nodules, and 3% of malignant nodules would be misclassified.

Conclusions

When used in patients with lung nodules with a pCA ≤ 50%, the integrated classifier accurately identifies benign lung nodules with good performance characteristics. If used in clinical practice, invasive procedures could be reduced by diverting benign nodules to surveillance.

Trial Registry

ClinicalTrials.gov; No.: NCT01752114; URL: www.clinicaltrials.gov).