The state of molecular biomarkers for the early detection of lung cancer

Plasma exosomes contain protein biomarkers valuable for the diagnosis of lung cancer

Accumulating evidence indicates that exosomal proteins are critical in diagnosing malignant tumors. To identify novel exosomal biomarkers for lung cancer diagnosis, we isolated plasma exosomes from 517 lung cancer patients and 168 healthy controls (NLs)-186 lung adenocarcinoma (LUAD) patients (screening (SN): 20, validation (VD): 166), 159 lung squamous carcinoma (LUSC) patients (SN: 20, VD: 139), 172 benign nodules (LUBN) patients (SN: 20, VD: 152) and 168 NLs (SN: 20, VD: 148)-and randomly assigned them to the SN or VD group. Proteomic analysis by LC-MS/MS and PRM were performed on all groups. The candidate humoral markers were evaluated and screened by a machine learning method. All selected biomarkers were identified in the VD groups. For LUAD, a 7-protein panel had AUCs of 97.9% and 87.6% in the training and test sets, respectively, and 89.5% for early LUAD. For LUSC, an 8-protein panel showed AUCs of 99.1% and 87.0% in the training and test sets and 92.3% for early LUSC. For LUAD + LUSC (LC), an 8-protein panel showed AUCs of 85.9% and 80.3% in the training and test sets and 87.1% for early LC diagnosis. The characteristics of the exosomal proteome make exosomes potential diagnostic tools.

Cigarette smoke sustains immunosuppressive microenvironment inducing M2 macrophage polarization and viability in lung cancer settings

BACKGROUND

It is amply demonstrated that cigarette smoke (CS) has a high impact on lung tumor progression worsening lung cancer patient prognosis and response to therapies. Alteration of immune cell types and functions in smokers' lungs have been strictly related with smoke detrimental effects. However, the role of CS in dictating an inflammatory or immunosuppressive lung microenvironment still needs to be elucidated. Here, we investigated the effect of in vitro exposure to cigarette smoke extract (CSE) focusing on macrophages.

METHODS

Immortalized murine macrophages RAW 264.7 cells were cultured in the presence of CS extract and their polarization has been assessed by Real-time PCR and cytofluorimetric analysis, viability has been assessed by SRB assay and 3D-cultures and activation by exposure to Poly(I:C). Moreover, interaction with Lewis lung carcinoma (LLC1) murine cell models in the presence of CS extract were analyzed by confocal microscopy.

RESULTS

Obtained results indicate that CS induces macrophages polarization towards the M2 phenotype and M2-phenotype macrophages are resistant to the CS toxic activity. Moreover, CS impairs TLR3-mediated M2-M1 phenotype shift thus contributing to the M2 enrichment in lung smokers.

CONCLUSIONS

These findings indicate that, in lung cancer microenvironment of smokers, CS can contribute to the M2-phenotype macrophages prevalence by different mechanisms, ultimately, driving an anti-inflammatory, likely immunosuppressive, microenvironment in lung cancer smokers.

Salivary metabolomic biomarkers for non-invasive lung cancer detection

Identifying novel biomarkers for early detection of lung cancer is crucial. Non-invasively available saliva is an ideal biofluid for biomarker exploration; however, the rationale underlying biomarker detection from organs distal to the oral cavity in saliva requires clarification. Therefore, we analyzed metabolomic profiles of cancer tissues compared with those of adjacent non-cancerous tissues, as well as plasma and saliva samples collected from patients with lung cancer (n = 109 pairs). Additionally, we analyzed plasma and saliva samples collected from control participants (n = 83 and 71, respectively). Capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry were performed to comprehensively quantify hydrophilic metabolites. Paired tissues were compared, revealing 53 significantly different metabolites. Plasma and saliva showed 44 and 40 significantly different metabolites, respectively, between patients and controls. Of these, 12 metabolites exhibited significant differences in all three comparisons and primarily belonged to the polyamine and amino acid pathways; N1-acetylspermidine exhibited the highest discrimination ability. A combination of 12 salivary metabolites was evaluated using a machine learning method to differentiate patients with lung cancer from controls. Salivary data were randomly split into training and validation datasets. Areas under the receiver operating characteristic curve were 0.744 for cross-validation using training data and 0.792 for validation data. This model exhibited a higher discrimination ability for N1-acetylspermidine than that for other metabolites. The probability of lung cancer calculated using this model was independent of most patient characteristics. These results suggest that consistently different salivary biomarkers in both plasma and lung tissues might facilitate non-invasive lung cancer screening.

Implementation of a Pilot Study to Analyze Circulating Tumor DNA in Early-Stage Lung Cancer

INTRODUCTION

Liquid biopsies based on plasma circulating tumour deoxyribonucleic acid (ctDNA) have shown promise in monitoring lung cancer evolution. The expression of ctDNA across time, its relationship with clinicopathological parameters and its association with lung cancer progression through imaging allow us to weigh how useful ctDNA could be in monitoring surgically resectable lung cancer. The aim of this study was to assess the impact of ctDNA analysis implementation in early-stage lung cancer.

METHODS

A cohort of 47 patients was sequentially recruited. Only 34 patients with early-stage lung cancer were included. All patients had a tissue specimen and five blood samples drawn: at the preoperative stage, from the pulmonary vein, at surgical discharge, at the first follow-up and at the last follow-up. All blood samples were evaluated for ctDNA expression.

RESULTS

On average, the maximum yield of ctDNA was obtained in liquid biopsies at the surgical discharge of patients when compared with PO, PV, and F1 (p < 0.0001, p < 0.0001, p < 0.0001 respectively). No statistically significant differences were found when comparing the last follow-up to surgical discharge ctDNA expression (p = 0.851). The correlation between ctDNA concentration according to five-time points and the four clinicopathological characteristics showed that patients younger than 70 years had a statistically significant reduction of the concentration of ctDNA at the preoperative and surgical discharge time point [β = -16 734 (-27 707; - 5760); p = 0.003; β = -21 785 (-38 447; -5123); p = 0.010], as opposed to an increase of the concentration of ctDNA at the pulmonary vein and last follow-up time points [β = 8369 (0.359; 16 378); p = 0.041; β = 34 402 (12 549; 56 254); p = 0.002] all with a confidence level of 95%. In the cases where actionable mutations were identified in tissue biopsies, the expected mutation was found in five out of six patients plasma samples at the pre-operatory time point and in two out of six patients plasma samples at the pulmonary vein time point. Two out of six patients with actionable mutations had disease progression.

CONCLUSION

The results of this pilot study suggest that the maximum yield of ctDNA is obtained at the surgical discharge of the patients and that the pre-operatory timepoint is the one offering the highest sensitivity for the detection of actionable mutations in ctDNA in early-stage lung cancer.

Combining Low-Dose Computer-Tomography-Based Radiomics and Serum Metabolomics for Diagnosis of Malignant Nodules in Participants of Lung Cancer Screening Studies

Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum metabolome is a promising source of auxiliary biomarkers that could help enhance the precision of lung cancer diagnosis in CT-based screening. Thus, we aimed to verify whether the combination of these two techniques, which provides local/morphological and systemic/molecular features of disease at the same time, increases the performance of lung cancer classification models. The collected cohort consists of 1086 patients with radiomic and 246 patients with serum metabolomic evaluations. Different machine learning techniques, i.e., random forest and logistic regression were applied for each omics. Next, model predictions were combined with various integration methods to create a final model. The best single omics models were characterized by an AUC of 83% in radiomics and 60% in serum metabolomics. The model integration only slightly increased the performance of the combined model (AUC equal to 85%), which was not statistically significant. We concluded that radiomics itself has a good ability to discriminate lung cancer from benign lesions. However, additional research is needed to test whether its combination with other molecular assessments would further improve the diagnosis of screening-detected lung nodules.

Serum Metabolomic Profiles for Distinguishing Lung Cancer From Pulmonary Tuberculosis: Identification of Rapid and Noninvasive Biomarker

BACKGROUND

Pulmonary tuberculosis (PTB) and lung cancer (LC) have similar clinical symptoms and atypical imaging findings, which are easily misdiagnosed. There is an urgent need for a noninvasive and accurate biomarker to distinguish LC from PTB.

METHODS

A total of 694 subjects were enrolled and divided into discovery set (n = 122), identification set (n = 214), and validation set (n = 358). Metabolites were identified by multivariate and univariate analyses. Receiver operating characteristic curve were used to evaluate the diagnostic efficacy of biomarkers.

RESULTS

Seven metabolites were identified and validated. Phenylalanylphenylalanine for distinguishing LC from PTB yielded an area under the curve of 0.89, sensitivity of 71%, and specificity of 92%. It also showed good diagnostic abilities in discovery set and identification set. Compared with that in healthy volunteers (median [interquartile range], 1.57 [1.01, 2.34] μg/mL), it was elevated in LC (4.76 [2.74, 7.08] μg/mL; ratio of median, [ROM] = 3.03, P < .01) and reduced in PTB (1.06 [0.51, 2.09] μg/mL; ROM = 0.68, P < .05).

CONCLUSIONS

The metabolomic profile of LC and PTB was described and a key biomarker identified. We produced a rapid and noninvasive method to supplement existing clinical diagnostic examinations for distinguishing LC from PTB.

A novel multimodal prediction model based on DNA methylation biomarkers and low-dose computed tomography images for identifying early-stage lung cancer

Objective

DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer. This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor 4 gene (PTGER4) DNA methylation in plasma, appearance subtype of pulmonary nodules (PNs) and low-dose computed tomography (LDCT) images to distinguish early-stage lung cancers.

Methods

We developed a multimodal prediction model with a training set of 257 individuals. The performance of the multimodal prediction model was further validated in an independent validation set of 42 subjects. In addition, we explored the association between SHOX2/PTGER4 DNA methylation and driver gene mutations in lung cancer based on data from The Cancer Genome Atlas (TCGA) portal.

Results

There were significant differences between the early-stage lung cancers and benign groups in the methylation levels. The area under a receiver operator characteristic curve (AUC) of SHOX2 in patients with solid nodules, mixed ground-glass opacity nodules and pure ground-glass opacity nodules were 0.693, 0.497 and 0.864, respectively, while the AUCs of PTGER4 were 0.559, 0.739 and 0.619, respectively. With the highest AUC of 0.894, the novel multimodal prediction model outperformed the Mayo Clinic model (0.519) and LDCT-based deep learning model (0.842) in the independent validation set. Database analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 mutations.

Conclusions

The present multimodal prediction model could more efficiently distinguish early-stage lung cancer from benign PNs. A prognostic index based on DNA methylation and lung cancer driver gene alterations may separate the patients into groups with good or poor prognosis.

The journey of stage III and IV non-small cell lung cancer patients in the Brazilian private healthcare system: a retrospective study

Non-small cell lung cancer (NSCLC) is still diagnosed at late stages in Brazil. The availability of newer treatment options has changed patient management, however, few real-world data have been published since then. This is a population-based retrospective cohort study that aims to evaluate the characteristics of stage III/IV NSCLC patients and their journey in the Brazilian private healthcare system. Patients aged ≥18 years, residing in Brazil who had their first medical appointment between 2016 and 2018 were included in the study. The sociodemographic and clinical characteristics of the patients and time intervals of interest were described. A total of 10,394 patients were analyzed. The majority of the patients were male (58.5%) with a median age of 64.0 (IQR = 58.0 - 71.0) years. In relation to characteristics of the disease, most of the tumors were characterized as adenocarcinomas (52.3%) and diagnosed at stage IV (72.2%). Most patients arrived at the hospital with an established NSCLC diagnosis, while 45.7% were diagnosed at the first medical appointment in the hospital or later. For patients who were diagnosed at the first medical appointment or later, a median interval of 15.0 (IQR = 6.0 - 33.0) days was observed between the first medical appointment and the diagnosis. The first treatment was given after a median of 25.0 (IQR = 6.0 - 49.0) days after diagnosis for patients without a prior diagnosis, and 57.0 (IQR: 33.0 - 98.0) days for patients with a prior diagnosis. The most common treatments were chemotherapy alone (33.8%), chemotherapy combined with radiotherapy (21.5%), radiotherapy alone (13.1%), adjuvant or neoadjuvant treatment (9.3%), surgery (3.3%), and immunotherapy (0.7%; alone or combined). At the end of follow-up (September, 2020), 52.3% of the patients had died. Despite having more treatment options in the private sector, data show that there is a need to improve access to technologies.

ESOMIR: a curated database of biomarker genes and miRNAs associated with esophageal cancer

'Esophageal cancer' (EC) is a highly aggressive and deadly complex disease. It comprises two types, esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), with Barrett's esophagus (BE) being the only known precursor. Recent research has revealed that microRNAs (miRNAs) play a crucial role in the development, prognosis and treatment of EC and are involved in various human diseases. Biological databases have become essential for cancer research as they provide information on genes, proteins, pathways and their interactions. These databases collect, store and manage large amounts of molecular data, which can be used to identify patterns, predict outcomes and generate hypotheses. However, no comprehensive database exists for EC and miRNA relationships. To address this gap, we developed a dynamic database named 'ESOMIR (miRNA in esophageal cancer) (https://esomir.dqweilab-sjtu.com)', which includes information about targeted genes and miRNAs associated with EC. The database uses analysis and prediction methods, including experimentally endorsed miRNA(s) information. ESOMIR is a user-friendly interface that allows easy access to EC-associated data by searching for miRNAs, target genes, sequences, chromosomal positions and associated signaling pathways. The search modules are designed to provide specific data access to users based on their requirements. Additionally, the database provides information about network interactions, signaling pathways and region information of chromosomes associated with the 3'untranslated region (3'UTR) or 5'UTR and exon sites. Users can also access energy levels of specific miRNAs with targeted genes. A fuzzy term search is included in each module to enhance the ease of use for researchers. ESOMIR can be a valuable tool for researchers and clinicians to gain insight into EC, including identifying biomarkers and treatments for this aggressive tumor. Database URL https://esomir.dqweilab-sjtu.com.

Effective lung cancer control: An unaccomplished challenge in cancer research

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

Metabolic biomarkers in lung cancer screening and early diagnosis (Review)

Late diagnosis is one of the major contributing factors to the high mortality rate of lung cancer, which is now the leading cause of cancer-associated mortality worldwide. At present, low-dose CT (LDCT) screening in the high-risk population, in which lung cancer incidence is higher than that of the low-risk population is the predominant diagnostic strategy. Although this has efficiently reduced lung cancer mortality in large randomized trials, LDCT screening has high false-positive rates, resulting in excessive subsequent follow-up procedures and radiation exposure. Complementation of LDCT examination with biofluid-based biomarkers has been documented to increase efficacy, and this type of preliminary screening can potentially reduce potential radioactive damage to low-risk populations and the burden of hospital resources. Several molecular signatures based on components of the biofluid metabolome that can possibly discriminate patients with lung cancer from healthy individuals have been proposed over the past two decades. In the present review, advancements in currently available technologies in metabolomics were reviewed, with particular focus on their possible application in lung cancer screening and early detection.

Biomarkers in Lung Cancer Screening: a Narrative Review

Although when used as a lung cancer screening tool low-dose computed tomography (LDCT) has demonstrated a significant reduction in lung cancer related mortality, it is not without pitfalls. The associated high false positive rate, inability to distinguish between benign and malignant nodules, cumulative radiation exposure, and resulting patient anxiety have all demonstrated the need for adjunctive testing in lung cancer screening. Current research focuses on developing liquid biomarkers to complement imaging as non-invasive lung cancer diagnostics. Biomarkers can be useful for both the early detection and diagnosis of disease, thereby decreasing the number of unnecessary radiologic tests performed. Biomarkers can stratify cancer risk to further enrich the screening population and augment existing risk prediction. Finally, biomarkers can be used to distinguish benign from malignant nodules in lung cancer screening. While many biomarkers require further validation studies, several, including autoantibodies and blood protein profiling, are available for clinical use. This paper describes the need for biomarkers as a lung cancer screening tool, both in terms of diagnosis and risk assessment. Additionally, this paper will discuss the goals of biomarker use, describe properties of a good biomarker, and review several of the most promising biomarkers currently being studied including autoantibodies, complement fragments, microRNA, blood proteins, circulating tumor DNA, and DNA methylation. Finally, we will describe future directions in the field of biomarker development.

The Implication of Liquid Biopsy in the Non-small Cell Lung Cancer: Potential and Expectation

Nowadays, lung cancer has remained the most lethal cancer, despite great advances in diagnosis and treatment. However, a large proportion of patients were diagnosed with locally advanced or metastatic disease and have poor prognosis. Immunotherapy and targeted drugs have greatly improved the survival and prognosis of patients with advanced lung cancer. However, how to identify the optimal patients to accept those therapies and how to monitor therapeutic efficacy are still in dispute. In the past few decades, tissue biopsy, including percutaneous fine needle biopsy and surgical excision, has still been the gold standard for examining the gene mutation such as EGFR, ALK, ROS, and PD-1/PD/L1, which can indicate the follow-up treatment. Nevertheless, the biopsy techniques mentioned above were invasive and unrepeatable, which were not suitable for advanced patients. Liquid biopsy, accounting for heterogeneity compared with tissue biopsy, is an alternative technique for monitoring the mutation, and a large quantity of research has demonstrated its feasibility to detect the circulating tumor cell, cell-free DNA, circulating tumor DNA, and extracellular vesicles from peripheral venous blood. The proposal of the concept of precision medicine brings a novel medical model developed with the rapid progress of genome sequencing technology and the cross-application of bioinformation, which was based on personalized medicine. The emerging method of liquid biopsy might contribute to promoting the development of precision medicine. In this review, we intend to describe the liquid biopsy in non-small cell lung cancer in detail in the aspect of screening, diagnosis, monitoring, treatment, and drug resistance.

Data-driven identification of plasma metabolite clusters and metabolites of interest for potential detection of early-stage non-small cell lung cancer cases versus cancer-free controls

BACKGROUND

Metabolomics is a potential means for biofluid-based lung cancer detection. We conducted a non-targeted, data-driven assessment of plasma from early-stage non-small cell lung cancer (ES-NSCLC) cases versus cancer-free controls (CFC) to explore and identify the classes of metabolites for further targeted metabolomics biomarker development.

METHODS

Plasma from 250 ES-NSCLC cases and 250 CFCs underwent ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive and negative electrospray ionization (ESI) modes. Molecular feature extraction, formula generation, and find-by-ion tools annotated metabolic entities. Analysis was restricted to endogenous metabolites present in ≥ 80% of samples. Unsupervised hierarchical cluster analysis identified clusters of metabolites. The metabolites with the strongest correlation with the principal component of each cluster were included in logistic regression modeling to assess discriminatory performance with and without adjustment for clinical covariates.

RESULTS

A total of 1900 UHPLC-QTOF-MS assessments identified 1667 and 2032 endogenous metabolites in the ESI-positive and ESI-negative modes, respectively. After data filtration, 676 metabolites remained, and 12 clusters of metabolites were identified from each ESI mode. Multivariable logistic regression using the representative metabolite from each cluster revealed effective classification of cases from controls with overall diagnostic accuracy of 91% (ESI positive) and 94% (ESI negative). Metabolites of interest identified for further targeted analysis include the following: 1b, 3a, 12a-trihydroxy-5b-cholanoic acid, pyridoxamine 5'-phosphate, sphinganine 1-phosphate, gamma-CEHC, 20-carboxy-leukotriene B4, isodesmosine, and 18-hydroxycortisol.

CONCLUSIONS

Plasma-based metabolomic detection of early-stage NSCLC appears feasible. Further metabolomics studies targeting phospholipid, steroid, and fatty acid metabolism are warranted to further develop noninvasive metabolomics-based detection of early-stage NSCLC.

The potential applications of microparticles in the diagnosis, treatment, and prognosis of lung cancer

Microparticles (MPs) are 100–1000 nm heterogeneous submicron membranous vesicles derived from various cell types that express surface proteins and antigenic profiles suggestive of their cellular origin. MPs contain a diverse array of bioactive chemicals and surface receptors, including lipids, nucleic acids, and proteins, which are essential for cell-to-cell communication. The tumour microenvironment (TME) is enriched with MPs that can directly affect tumour progression through their interactions with receptors. Liquid biopsy, a minimally invasive test, is a promising alternative to tissue biopsy for the early screening of lung cancer (LC). The diverse biomolecular information from MPs provides a number of potential biomarkers for LC risk assessment, early detection, diagnosis, prognosis, and surveillance. Remodelling the TME, which profoundly influences immunotherapy and clinical outcomes, is an emerging strategy to improve immunotherapy. Tumour-derived MPs can reverse drug resistance and are ideal candidates for the creation of innovative and effective cancer vaccines. This review described the biogenesis and components of MPs and further summarised their main isolation and quantification methods. More importantly, the review presented the clinical application of MPs as predictive biomarkers in cancer diagnosis and prognosis, their role as therapeutic drug carriers, particularly in anti-tumour drug resistance, and their utility as cancer vaccines. Finally, we discussed current challenges that could impede the clinical use of MPs and determined that further studies on the functional roles of MPs in LC are required.

Proteomic Analysis of Human Sputum for the Diagnosis of Lung Disorders: Where Are We Today?

The identification of markers of inflammatory activity at the early stages of pulmonary diseases which share common characteristics that prevent their clear differentiation is of great significance to avoid misdiagnosis, and to understand the intrinsic molecular mechanism of the disorder. The combination of electrophoretic/chromatographic methods with mass spectrometry is currently a promising approach for the identification of candidate biomarkers of a disease. Since the fluid phase of sputum is a rich source of proteins which could provide an early diagnosis of specific lung disorders, it is frequently used in these studies. This report focuses on the state-of-the-art of the application, over the last ten years (2011-2021), of sputum proteomics in the investigation of severe lung disorders such as COPD; asthma; cystic fibrosis; lung cancer and those caused by COVID-19 infection. Analysis of the complete set of proteins found in sputum of patients affected by these disorders has allowed the identification of proteins whose levels change in response to the organism's condition. Understanding proteome dynamism may help in associating these proteins with alterations in the physiology or progression of diseases investigated.

Epigenetic imprinting alterations as effective diagnostic biomarkers for early-stage lung cancer and small pulmonary nodules

Background

Early lung cancer detection remains a clinical challenge for standard diagnostic biopsies due to insufficient tumor morphological evidence. As epigenetic alterations precede morphological changes, expression alterations of certain imprinted genes could serve as actionable diagnostic biomarkers for malignant lung lesions.

Results

Using the previously established quantitative chromogenic imprinted gene in situ hybridization (QCIGISH) method, elevated aberrant allelic expression of imprinted genes GNAS, GRB10, SNRPN and HM13 was observed in lung cancers over benign lesions and normal controls, which were pathologically confirmed among histologically stained normal, paracancerous and malignant tissue sections. Based on the differential imprinting signatures, a diagnostic grading model was built on 246 formalin-fixed and paraffin-embedded (FFPE) surgically resected lung tissue specimens, tested against 30 lung cytology and small biopsy specimens, and blindly validated in an independent cohort of 155 patients. The QCIGISH diagnostic model demonstrated 99.1% sensitivity (95% CI 97.5–100.0%) and 92.1% specificity (95% CI 83.5–100.0%) in the blinded validation set. Of particular importance, QCIGISH achieved 97.1% sensitivity (95% CI 91.6–100.0%) for carcinoma in situ to stage IB cancers with 100% sensitivity and 91.7% specificity (95% CI 76.0–100.0%) noted for pulmonary nodules with diameters ≤ 2 cm.

Conclusions

Our findings demonstrated the diagnostic value of epigenetic imprinting alterations as highly accurate translational biomarkers for a more definitive diagnosis of suspicious lung lesions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01203-5.

Comprehensive analysis of NGS and ARMS-PCR for detecting EGFR mutations based on 4467 cases of NSCLC patients

BACKGROUND

By comparing the detection rate and type of targeted gene mutations in non-small cell lung cancer (NSCLC) between amplification refractory mutation system PCR (ARMS-PCR) and next-generation sequencing (NGS), the characteristics and application advantages of non-small cell lung cancer detection are explained, providing a basis for clinicians to effectively select the corresponding detection methods.

METHODS AND MATERIALS

The cases of targeted genes for lung cancer were selected from the First Affiliated Hospital of Chongqing Medical University from January 2016 to October 2020. A sample of 4467 cases was selected, and they were diagnosed with NSCLC by Pathological biopsy. Sample sources include surgical resection, bronchoscope biopsy, metastatic biopsy, blood, sputum, cytology of pleural effusion. Among them, 3665 cases were detected by ARMS-PCR technique, and 802 cases were detected by NGS technology. The detection rate and type of ARMS-PCR and NGS techniques for EGFR gene mutations (including exon 18, exon 19, exon 20, exon 21 and so on) in different NSCLC samples were compared, respectively.

RESULTS

The total mutation rate of EGFR gene detected by ARMS-PCR was 47.6% while 42.4% detected by NGS which indicated that there was a significant difference between the two methods in detecting total mutation of EGFR gene (P < 0.001). In different exons, the EGFR mutation rate detected by two methods is various. The mutation rate of exon 19 by ARMS-PCR detection was evidently higher than that of NGS detection, while the mutation rate of exons 20 and 21 by ARMS-PCR detection were statistically significantly lower than that of NGS detection. Moreover, the multiple mutation rate detected by NGS was 16.3% which was much higher than the 2.7% detected by ARMS-PCR with statistically different.

CONCLUSION

It showed that NGS could direct the drug use for the resistant patients. However, some rare loci could be detected by NGS but the importance and directed meaning are still unknown and the number of rare mutations is rare too. Further research on new biomarkers and technique is still needed for early diagnosis, directing drug use and assessing the therapy prognosis.

Immunoaffinity Capillary Electrophoresis in the Era of Proteoforms, Liquid Biopsy and Preventive Medicine: A Potential Impact in the Diagnosis and Monitoring of Disease Progression

Over the years, multiple biomarkers have been used to aid in disease screening, diagnosis, prognosis, and response to therapy. As of late, protein biomarkers are gaining strength in their role for early disease diagnosis and prognosis in part due to the advancements in identification and characterization of a distinct functional pool of proteins known as proteoforms. Proteoforms are defined as all of the different molecular forms of a protein derived from a single gene caused by genetic variations, alternative spliced RNA transcripts and post-translational modifications. Monitoring the structural changes of each proteoform of a particular protein is essential to elucidate the complex molecular mechanisms that guide the course of disease. Clinical proteomics therefore holds the potential to offer further insight into disease pathology, progression, and prevention. Nevertheless, more technologically advanced diagnostic methods are needed to improve the reliability and clinical applicability of proteomics in preventive medicine. In this manuscript, we review the use of immunoaffinity capillary electrophoresis (IACE) as an emerging powerful diagnostic tool to isolate, separate, detect and characterize proteoform biomarkers obtained from liquid biopsy. IACE is an affinity capture-separation technology capable of isolating, concentrating and analyzing a wide range of biomarkers present in biological fluids. Isolation and concentration of target analytes is accomplished through binding to one or more biorecognition affinity ligands immobilized to a solid support, while separation and analysis are achieved by high-resolution capillary electrophoresis (CE) coupled to one or more detectors. IACE has the potential to generate rapid results with significant accuracy, leading to reliability and reproducibility in diagnosing and monitoring disease. Additionally, IACE has the capability of monitoring the efficacy of therapeutic agents by quantifying companion and complementary protein biomarkers. With advancements in telemedicine and artificial intelligence, the implementation of proteoform biomarker detection and analysis may significantly improve our capacity to identify medical conditions early and intervene in ways that improve health outcomes for individuals and populations.

Role of miR-182/PDCD4 axis in aggressive behavior of prostate cancer in the African Americans

Background

Prostate cancer is one of the most commonly diagnosed cancers among men. African Americans (AA) are at an increased risk of developing prostate cancer compared to European Americans (EA). miRNAs play a critical role in these tumors, leading to tumor progression. In this study, we investigated the role of miR-182 in racial disparity in prostate cancer.

Results

We found significantly increased levels of miR-182 in prostate cancer tissues compared to BPH. Also, miR-182 shows increased expression in AA prostate cancer cell line and tissue samples compared to EA. We performed biochemical recurrence (BCR) - free survival time in AA and EA patients and found that high miR-182 expression had significantly shorter BCR-free survival than patients with low miR-182 expression (P = 0.031). To elucidate the role of miR-182, we knocked down miR-182 in EA (DU-145 and LNCaP) and AA (MDA-PCa-2b) cell lines and found an increase in apoptosis, arrest of the cell cycle, and inhibition of colony formation in the AA cell line to a greater extent than EA cell lines.

Conclusions

Our results showed that PDCD4 is a direct miR-182 target and its inhibition is associated with aggressiveness and high Gleason grade in prostate cancer among AA. These findings show that miR-182 is highly expressed in AA patients and miR-182 may be a target for effective therapy in AA patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08723-6.

A panel of DNA methylation biomarkers for detection and improving diagnostic efficiency of lung cancer

Lung cancer remains the leading cause of cancer deaths worldwide. Although low-dose spiral computed tomography (LDCT) screening is used for the detection of lung cancer in a high-risk population, false-positive results of LDCT remain a clinical problem. Here, we developed a blood test of a novel panel of three established lung cancer methylation biomarkers for lung cancer detection. Short stature homeobox 2 gene (SHOX2), ras association domain family 1A gene (RASSF1A), and prostaglandin E receptor 4 gene (PTGER4) methylation was analyzed in a training cohort of 351 individuals (197 controls, 154 cases) and validated from an independent cohort of 149 subjects (89 controls, 60 cases). The novel panel biomarkers distinguished between malignant and benign lung disease at high sensitivity and specificity: 87.0% sensitivity [95% CI 80.2–91.5%], 98.0% specificity [95% CI 94.9–99.4%]. Sensitivity in adenocarcinoma, squamous cell carcinoma, small cell lung cancer, and other lung cancer was 89.0%, 87.5%, 85.7%, and 77.8%, respectively. Notably, cancer patients in stage I and II showed high diagnostic sensitivity at 82.5% and 90.5%, respectively. Moreover, the diagnostic efficiency did not show bias toward age, gender, smoking, and the presence of other (nonlung) cancers. The performance of the panel in the validation cohort confirmed the diagnostic value. These findings clearly showed that this panel of DNA methylation biomarkers was effective in detecting lung cancer noninvasively and may provide clinical utility in stand-alone or in combination with current imaging techniques to improve the diagnosis of lung cancer.

The Lipid Composition of Serum-Derived Small Extracellular Vesicles in Participants of a Lung Cancer Screening Study

Simple Summary

Molecular components of extracellular vesicles present in serum are potential biomarkers of lung cancer, however, none of them have been validated in the context of an actual early detection of lung cancer. Here, we compared the lipid profiles of vesicles obtained from participants in a lung cancer screening study, including patients with screening-detected cancer and individuals with benign pulmonary nodules or without pathological changes. A few lipids whose levels were different between compared groups were detected, including ceramide Cer(42:1) upregulated in vesicles from cancer patients. Furthermore, a high heterogeneity of lipid profiles of extracellular vesicles was observed, which impaired the performance of classification models based on specific compounds.

Abstract

Molecular components of exosomes and other classes of small extracellular vesicles (sEV) present in human biofluids are potential biomarkers with possible applicability in the early detection of lung cancer. Here, we compared the lipid profiles of serum-derived sEV from three groups of lung cancer screening participants: individuals without pulmonary alterations, individuals with benign lung nodules, and patients with screening-detected lung cancer (81 individuals in each group). Extracellular vesicles and particles were purified from serum by size-exclusion chromatography, and a fraction enriched in sEV and depleted of low-density lipoproteins (LDLs) was selected (similar sized vesicles was observed in all groups: 70–100 nm). The targeted mass-spectrometry-based approach enabled the detection of 352 lipids, including 201 compounds used in quantitative analyses. A few compounds, exemplified by Cer(42:1), i.e., a ceramide whose increased plasma/serum level was reported in different pathological conditions, were upregulated in vesicles from cancer patients. On the other hand, the contribution of phosphatidylcholines with poly-unsaturated acyl chains was reduced in vesicles from lung cancer patients. Cancer-related features detected in serum-derived sEV were different than those of the corresponding whole serum. A high heterogeneity of lipid profiles of sEV was observed, which markedly impaired the performance of classification models based on specific compounds (the three-state classifiers showed an average AUC = 0.65 and 0.58 in the training and test subsets, respectively).

Serum Metabolite Profiles in Participants of Lung Cancer Screening Study; Comparison of Two Independent Cohorts

Serum metabolome is a promising source of molecular biomarkers that could support early detection of lung cancer in screening programs based on low-dose computed tomography. Several panels of metabolites that differentiate lung cancer patients and healthy individuals were reported, yet none of them were validated in the population at high-risk of developing cancer. Here we analyzed serum metabolome profiles in participants of two lung cancer screening studies: MOLTEST-BIS (Poland, n = 369) and SMAC-1 (Italy, n = 93). Three groups of screening participants were included: lung cancer patients, individuals with benign pulmonary nodules, and those without any lung alterations. Concentrations of about 400 metabolites (lipids, amino acids, and biogenic amines) were measured by a mass spectrometry-based approach. We observed a reduced level of lipids, in particular cholesteryl esters, in sera of cancer patients from both studies. Despite several specific compounds showing significant differences between cancer patients and healthy controls within each study, only a few cancer-related features were common when both cohorts were compared, which included a reduced concentration of lysophosphatidylcholine LPC (18:0). Moreover, serum metabolome profiles in both noncancer groups were similar, and differences between cancer patients and both groups of healthy participants were comparable. Large heterogeneity in levels of specific metabolites was observed, both within and between cohorts, which markedly impaired the accuracy of classification models: The overall AUC values of three-state classifiers were 0.60 and 0.51 for the test (MOLTEST) and validation (SMAC) cohorts, respectively. Therefore, a hypothetical metabolite-based biomarker for early detection of lung cancer would require adjustment to lifestyle-related confounding factors that putatively affect the composition of serum metabolome.

Accurate diagnosis of pulmonary nodules using a noninvasive DNA methylation test

BACKGROUNDCurrent clinical management of patients with pulmonary nodules involves either repeated low-dose CT (LDCT)/CT scans or invasive procedures, yet causes significant patient misclassification. An accurate noninvasive test is needed to identify malignant nodules and reduce unnecessary invasive tests.METHODWe developed a diagnostic model based on targeted DNA methylation sequencing of 389 pulmonary nodule patients' plasma samples and then validation in 140 plasma samples independently. We tested the model in different stages and subtypes of pulmonary nodules.RESULTSA 100-feature model was developed and validated for pulmonary nodule diagnosis; the model achieved a receiver operating characteristic curve-AUC (ROC-AUC) of 0.843 on 140 independent validation samples, with an accuracy of 0.800. The performance was well maintained in (a) a 6 to 20 mm size subgroup (n = 100), with a sensitivity of 1.000 and adjusted negative predictive value (NPV) of 1.000 at 10% prevalence; (b) stage I malignancy (n = 90), with a sensitivity of 0.971; (c) different nodule types: solid nodules (n = 78) with a sensitivity of 1.000 and adjusted NPV of 1.000, part-solid nodules (n = 75) with a sensitivity of 0.947 and adjusted NPV of 0.983, and ground-glass nodules (n = 67) with a sensitivity of 0.964 and adjusted NPV of 0.989 at 10% prevalence. This methylation test, called PulmoSeek, outperformed PET-CT and 2 clinical prediction models (Mayo Clinic and Veterans Affairs) in discriminating malignant pulmonary nodules from benign ones.CONCLUSIONThis study suggests that the blood-based DNA methylation model may provide a better test for classifying pulmonary nodules, which could help facilitate the accurate diagnosis of early stage lung cancer from pulmonary nodule patients and guide clinical decisions.FUNDINGThe National Key Research and Development Program of China; Science and Technology Planning Project of Guangdong Province; The National Natural Science Foundation of China National.

Serum Exosomes and Their miRNA Load-A Potential Biomarker of Lung Cancer

Early detection of lung cancer in screening programs is a rational way to reduce mortality associated with this malignancy. Low-dose computed tomography, a diagnostic tool used in lung cancer screening, generates a relatively large number of false-positive results, and its complementation with molecular biomarkers would greatly improve the effectiveness of such programs. Several biomarkers of lung cancer based on different components of blood, including miRNA signatures, were proposed. However, only a few of them have been positively validated in the context of early cancer detection yet, which imposes a constant need for new biomarker candidates. An emerging source of cancer biomarkers are exosomes and other types of extracellular vesicles circulating in body fluids. Hence, different molecular components of serum/plasma-derived exosomes were tested and showed different levels in lung cancer patients and healthy individuals. Several studies focused on the miRNA component of these vesicles. Proposed signatures of exosome miRNA had promising diagnostic value, though none of them have yet been clinically validated. These signatures involved a few dozen miRNA species overall, including a few species that recurred in different signatures. It is worth noting that all these miRNA species have cancer-related functions and have been associated with lung cancer progression. Moreover, a few of them, including known oncomirs miR-17, miR-19, miR-21, and miR-221, appeared in multiple miRNA signatures of lung cancer based on both the whole serum/plasma and serum/plasma-derived exosomes.

Volatile Organic Compounds in Human Exhaled Breath to Diagnose Gastrointestinal Cancer: A Meta-Analysis

Introduction

Human exhaled volatile organic compounds (VOCs) are being extensively studied for the purposes of noninvasive cancer diagnoses. This article was primarily to assess the feasibility of utilizing exhaled VOCs analysis for gastrointestinal cancer (GIC) diagnosis.

Methods

PRISMA-based system searches were conducted for related studies of exhaled VOCs in GIC diagnosis based on predetermined criteria. Relevant articles on colorectal cancer and gastroesophageal cancer were summarized, and meta analysis was performed on articles providing sensitivity and specificity data.

Results

From 2,227 articles, 14 were found to meet inclusion criteria, six of which were on colorectal cancer (CRC) and eight on Gastroesophageal cancer(GEC). Five articles could provide specific data of sensitivity and specificity in GEC, which were used for meta-analysis. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated based on the combination of these data, and were 85.0% [95% confidence interval (CI): 79.0%-90.0%], 89.0% (95%CI: 86.0%-91.0%), 41.30 (21.56-79.10), and 0.93, respectively.

Conclusion

VOCs can distinguish gastrointestinal cancers from other gastrointestinal diseases, opening up a new avenue for the diagnosis and identification of gastrointestinal cancers, and the analysis of VOCs in exhaled breath has potential clinical application in screening. VOCs are promising tumor biomarkers for GIC diagnosis. Furthermore, limitations like the heterogeneity of diagnostic VOCs between studies should be minded.

Urinary fluorescent metabolite O-aminohippuric acid is a useful biomarker for lung cancer detection

INTRODUCTION

Urine contains diagnostically important metabolites that can act as natural fluorophores. However, whether these fluorescent metabolites can be used in lung cancer diagnosis is unknown.

OBJECTIVES

This study was conducted to determine whether fluorescent urinary metabolites could be useful biomarkers for lung cancer detection.

METHODS

A total of 46 lung cancer patients and 185 volunteers without cancer were evaluated between November 2013 and November 2014. Samples of the first urine of the day were collected from lung cancer patients and diagnosed at the Hamamatsu University School of Medicine and the Hamamatsu Medical Center prior to cancer treatment, and from volunteers without cancer at the Hamamatsu Medical Imaging Center. Fluorescent urinary metabolites were screened by high-performance liquid chromatography and select effective fluorescent substances for distinguishing cancer from non-cancer status.

RESULTS

The fraction of patients at each stage of cancer severity were: 41.3% stage I, 8.7% stage II, 19.6% stage III, and 30.4% stage IV. A robust predictive biomarker for lung cancer was selected by the multivariate logistic analysis of fluorescent metabolites and identified to be O-aminohippuric acid (OAH). The area under the curve (AUC) data for OAH was 0.837 (95% CI 0.769-0.898, P < 0.001).

CONCLUSION

We identified a fluorescent urinary metabolite that can predict lung cancer. OAH exceeds the AUC (0.817) of lung cancer detection by AminoIndex® cancer screening, can be analyzed non-invasively without additional sample processing, and may be a valuable addition to existing lung cancer prediction models.

Blood-based Biomarkers for Early Diagnosis of Lung Cancer: A Review Article

Lung cancer is the severe leading cause of cancer-related mortality worldwide. Early detection of lung cancer can significantly increase their survival rate. However, conventional lung cancer screening methods such as sputum cytology, chest X-rays, low-dose computed tomography, positron emission tomography, and magnetic resonance imaging, are radiational, and also expensive methods. Similarly, lung tumor tissue as invasive and difficult to obtain and potentially risky procedures, there is the immediate need of non-invasive, novel sensitive and reliable blood-based tumor markers which now has become an important area on research. This review will mainly focus on recently identified circulating biomarkers: circulating tumor cells, circulating tumor deoxyribonucleic acid, tumor-derived exosomes, circulating ribonucleic acid and micro ribonucleic acid, and tumor-educated platelets which may enable earlier diagnosis of lung cancer and their application in clinical practices.

Genetic Markers in Lung Cancer Diagnosis: A Review

Lung cancer is the most often diagnosed cancer in the world and the most frequent cause of cancer death. The prognosis for lung cancer is relatively poor and 75% of patients are diagnosed at its advanced stage. The currently used diagnostic tools are not sensitive enough and do not enable diagnosis at the early stage of the disease. Therefore, searching for new methods of early and accurate diagnosis of lung cancer is crucial for its effective treatment. Lung cancer is the result of multistage carcinogenesis with gradually increasing genetic and epigenetic changes. Screening for the characteristic genetic markers could enable the diagnosis of lung cancer at its early stage. The aim of this review was the summarization of both the preclinical and clinical approaches in the genetic diagnostics of lung cancer. The advancement of molecular strategies and analytic platforms makes it possible to analyze the genome changes leading to cancer development-i.e., the potential biomarkers of lung cancer. In the reviewed studies, the diagnostic values of microsatellite changes, DNA hypermethylation, and p53 and KRAS gene mutations, as well as microRNAs expression, have been analyzed as potential genetic markers. It seems that microRNAs and their expression profiles have the greatest diagnostic potential value in lung cancer diagnosis, but their quantification requires standardization.

Progress in research on the role of fibrinogen in lung cancer

Lung cancer is one of the most prevalent malignancies worldwide. Local recurrence and distant metastasis remain the major causes of treatment failure. It has been recognized that the process of tumor growth and metastasis involves multiple interactions between tumor and host. Various biomarkers have been used for predicting tumor recurrence, metastasis, and prognosis in patients with lung cancer. However, these biomarkers are still controversial and require further validation. The relationship between malignancy and coagulation system disorders has been explored for more than a century. Fibrinogen is the most abundant plasma coagulation factor synthesized mainly by hepatic cells. Increased plasma fibrinogen levels were observed in various carcinomas such as gastric cancer, colon cancer, and pancreatic cancer. Recent studies have also investigated the role of fibrinogen in patients with lung cancer. This review aimed to address the role of fibrinogen in lung cancer.

Novel Liquid Biomarker Panels for A Very Early Response Capturing of NSCLC Therapies in Advanced Stages

Computed tomography (CT) scans are the gold standard to measure treatment success of non-small cell lung cancer (NSCLC) therapies. Here, we investigated the very early tumor response of patients receiving chemotherapy or targeted therapies using a panel of already established and explorative liquid biomarkers. Blood samples from 50 patients were taken at baseline and at three early time points after therapy initiation. DNA mutations, a panel of 17 microRNAs, glycodelin, glutathione disulfide, glutathione, soluble caspase-cleaved cytokeratin 18 (M30 antigen), and soluble cytokeratin 18 (M65 antigen) were measured in serum and plasma samples. Baseline and first follow-up CT scans were evaluated and correlated with biomarker data. The detection rate of the individual biomarkers was between 56% and 100%. While only keratin 18 correlated with the tumor load at baseline, we found several individual markers correlating with the tumor response to treatment for each of the three time points of blood draws. A combination of the five best markers at each time point resulted in highly significant marker panels indicating therapeutic response (R² = 0.78, R² = 0.71, and R² = 0.71). Our study demonstrates that an early measurement of biomarkers immediately after therapy start can assess tumor response to treatment and might support an adaptation of treatment to improve patients’ outcome.

Affinity chromatography assisted comprehensive phosphoproteomics analysis of human saliva for lung cancer

Affinity chromatography is a powerful technology for phosphopeptide enrichment from body fluids. Saliva is a non-invasive body fluid for disease diagnosis, while few studies applied affinity enrichment for saliva phosphoproteome. In this study, we tested two kinds of affinity chromatography materials, Ti⁴⁺-IMAC (immobilized metal affinity chromatography) and CaTiO₃, for the enrichment of phosphopeptides. Through comparison, Ti⁴⁺-IMAC method was demonstrated as the superior one, which was utilized for the comprehensive analysis of salivary phosphoproteome. More than 360 phosphoproteins were specifically extracted and identified from human saliva. Ti⁴⁺-IMAC method was further applied to compare the phosphoprotein profiling in the saliva of lung cancer group and normal control group through label-free quantification. Accordingly, 477 and 699 phosphopeptides were enriched, respectively, which corresponded to 339 and 466 proteins. In total, 796 unique phosphopeptides were revealed for 517 saliva phosphoproteins. In particular, 709 phosphorylation sites were identified, among which 26 were up-regulated (>1.5) and 149 were down-regulated (<0.66) in lung cancer. Their corresponding proteins were mainly associated with cancer promotion, system disorder, and organismal injury. Our data collectively demonstrated that salivary phosphopeptides can be comprehensively characterized through Ti⁴⁺-IMAC method. These discovered phosphoprotein candidates might be used for lung cancer detection through salivary diagnostics.

MicroRNA Biomarker hsa-miR-195-5p for Detecting the Risk of Lung Cancer

Background

Lung cancer is one of the leading diagnosed cancers worldwide, and microRNAs could be used as biomarkers to diagnose lung cancer. hsa-miR-195 has been demonstrated to affect the prognosis of NSCLC (non-small-cell lung cancer) in a previous study. However, the diagnostic value of hsa-miR-195-5p in lung cancer has not been investigated.

Methods

To evaluate the ability of hsa-miR-195-5p to diagnose lung cancer, we compared the expression of hsa-miR-195-5p in lung cancer patients, COPD patients, and normal controls. Receiver operating characteristic (ROC) curve analysis was performed to investigate the sensitivity and specificity of hsa-miR-195-5p. Coexpression network and pathway analysis were carried out to explore the mechanism.

Results

We found that hsa-miR-195-5p had lower expression in lung cancer and COPD patients than in normal controls, and the AUC was 0.92 for diagnosing lung cancer. hsa-miR-143 correlated with hsa-miR-195-5p, and by combining these two microRNAs, the AUC was 0.97 for diagnosing lung cancer.

Conclusions

hsa-miR-195-5p may act as a biomarker that contributes to the diagnosis of lung cancer and the detection of its high-risk population.

Clinical significance of urinary plasminogen and fibrinogen gamma chain as novel potential diagnostic markers for non-small-cell lung cancer

BACKGROUND

Urinary proteins could be useful as markers for the detection of non-small-cell lung cancer (NSCLC). We investigated the levels of two different proteins in urine samples from NSCLC patients and assessed their diagnostic value.

METHODS

Urinary plasminogen (PLG) and fibrinogen gamma chain (FGG) levels in 112 NSCLC patients and 197 controls were detected using enzyme linked immunosorbent assay (ELISA). The expression of FGG and PLG in 20 NSCLC tissues and paired adjacent non-tumour tissues were detected through immunohistochemistry. The diagnostic value of FGG and PLG for NSCLC was evaluated through a receiver operating characteristic curve (ROC).

RESULTS

PLG and FGG were significantly elevated in NSCLC tissues vs paired adjacent non-tumour tissues (p = 0.000) and in urinary samples from NSCLC patients vs healthy controls (p = 0.000). The expression level of PLG in urinary samples was related only to the histological type (p = 0.001). Further, ROC curve analysis revealed that PLG, FGG, and their combination could distinguish NSCLC and its subtypes from healthy controls with an AUC ranging from 0.827 to 0. 947. By comparing urine samples with matching plasma CEA from NSCLC stage I-IV patients (n = 81) and healthy controls (n = 31), the combination of CEA with PLG or FGG showed that the AUC was 0.889 and 0.806, respectively, which is superior to a single biomarker alone.

CONCLUSIONS

These two urinary proteins could serve as potential markers for the diagnosis of NSCLC.

Validation of a serum 4-microRNA signature for the detection of lung cancer

BACKGROUND

Our previous studies have identified a serum-based 4-microRNA (4-miRNA) signature that may help distinguish patients with lung cancer (LC) from non-cancer controls (NCs). Here, we used an extended independent cohort of 398 subjects to further validate the diagnostic ability of this 4-miRNA signature.

METHODS

Using quantitative reverse transcription polymerase chain reaction (qRT-PCR), expression of the 4-miRNAs was assessed in a total of 398 sera that included 213 LC patients and 185 NCs. A logistic regression model using training-test sets, receiver operating characteristic (ROC) curve analysis and t-test were used to test the impact of varying expression of these miRNAs on its diagnostic accuracy for LC. The cell proliferation and colony formation affected by these miRNAs, as well as gene ontology (GO) analysis of miRNA target genes were performed.

RESULTS

The levels of the 4-miRNAs were significantly higher in the serum of patients with LCs as compared to NCs. Using a logistic regression prediction model based on training and test sets analysis, we obtained the area under the curve (AUC) of 0.921 [95% confidence interval (CI), 0.876-0.966] on the test set with specificity 90.6%, sensitivity 77.9%, accuracy 84.1%, positive predictive value (PPV) 89.8% and negative predictive value (NPV) 79.5%.

CONCLUSIONS

We have verified that this serum 4-miRNA signature could provide a promising noninvasive biomarker for the prediction of LC, particularly in patients with indeterminate lung nodules on screening CT scans.

FGB and FGG derived from plasma exosomes as potential biomarkers to distinguish benign from malignant pulmonary nodules

Previous proteomic analysis (label-free) of plasma exosomes revealed that the expression of FGG and FGB was significantly higher in the malignant pulmonary nodules group, compared to the benign pulmonary nodules group. The present study was performed to evaluate the role of plasma exosomal proteins FGB and FGG in the diagnosis of benign and malignant pulmonary nodules. We examined the expression levels of FGB and FGG in plasma exosomes from 63 patients before surgery. Postoperative pathological diagnosis confirmed that 43 cases were malignant and 20 cases were benign. The ROC curve was used to describe the sensitivity, specificity, area under the curve (AUC) of the biomarker and the corresponding 95% confidence interval. We confirmed that the expression levels of FGB and FGG were higher in the plasma exosomes of malignant group than in the benign group. The sensitivity and AUC of FGB combined with FGG detection to determine the nature of pulmonary nodules are superior to single FGB or FGG detection. FGB and FGG might represent novel and sensitive biomarker to distinguish benign from malignant pulmonary nodules.

Dramatically changed immune-related molecules as early diagnostic biomarkers of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the main type of lung cancer, with a low 5-year survival rate because of the absence of effective clinical biomarkers for early diagnosis. Based on the immunosurveillance theory, we proposed that changes in the immune system are more pronounced than tumour-associated antigens during the early stage of cancer. Therefore, a new strategy was designed to screen early diagnostic biomarkers from peripheral leukocytes in early-stage NSCLCs with transcriptome sequencing. A total of 358 immune-related differentially expressed genes were identified between early-NSCLC patients and healthy individuals. Orosomucoid-1 (ORM1, a acute phase protein), the total ORM and chitotriosidase-1 (involved in degradation of chitobiose) were selected for further verification in 210 serum samples by western blotting, ELISA and nephelometry immunoassay (based on immuno-scatter turbidmetry). Receiver operating characteristic curve analysis show that ORM1 and total ORM have excellent diagnostic efficacies, with area under the curve of 0.862 and 0.920, respectively, which significantly distinguished very early-NSCLC (IA) from healthy samples. Flow cytometry results showed that CD15⁺ neutrophils made up 73% of ORM1⁺ peripheral leukocytes. In mouse lung cancer model, serum ORM1, but not liver ORM1, changed significantly in the early stage of NSCLC. ORM1 expression in peripheral leukocytes was regulated by TGF-β and mediated by the TGF-β/Smad signalling pathway. Our results indicated that combined ORM and TGF-β could be a promising clinical biomarker in the diagnosis of early NSCLC.

Are There New Biomarkers in Tissue and Liquid Biopsies for the Early Detection of Non-Small Cell Lung Cancer?

Lung cancer is one of the most lethal malignancies worldwide, mainly due to its late diagnoses. The detection of molecular markers on samples provided from routine bronchoscopy including several liquid-based cytology tests (e.g., bronchoaspirate, bronchoalveolar lavage) and/or on easily obtained specimens such as sputum could represent a new approach to improve the sensitivity in lung cancer diagnoses. Recently growing interest has been reported for "noninvasive" liquid biopsy as a valuable source for molecular profiling. Unfortunately, a biomarker and/or composition of biomarkers capable of detecting early-stage lung cancer has yet to be discovered even if in the last few years there has been, through the use of revolutionary new technologies, an explosion of lung cancer biomarkers. Assay sensitivity and specificity need to be improved particularly when new approaches and/or tools are used. We have focused on the most important markers detected in tissue, and on several cytological specimens and liquid biopsies overall.

Detection of early lung cancer among military personnel (DECAMP) consortium: study protocols

BACKGROUND

Lung cancer is the leading cause of cancer-related death due in large part to our inability to diagnose it at an early and potentially curable stage. Screening for lung cancer via low dose computed tomographic (LDCT) imaging has been demonstrated to improve mortality but also results in a high rate of false positive tests. The identification and application of non-invasive molecular biomarkers that improve the performance of CT imaging for the detection of lung cancer in high risk individuals would aid in clinical decision-making, eliminate the need for unnecessary LDCT follow-up, and further refine the screening criteria for an already large high-risk population.

METHODS

The Detection of Early Lung Cancer Among Military Personnel (DECAMP) consortium is conducting two multicenter prospective studies with the goals of developing an integrated panel of both airway and blood-based molecular biomarkers that discriminate benign and malignant indeterminate nodules detected on CT scan as well as predict the future development of lung cancer in high-risk individuals. To achieve these goals, DECAMP is compiling an extensive array of biospecimens including nasal brushings, serum, plasma and intrathoracic airway samples (bronchial brushings and bronchial biopsies) from normal-appearing airway epithelium.

DISCUSSION

This bank of samples is the foundation for multiple DECAMP efforts focused on the identification of those at greatest risk of developing lung cancer as well as the discrimination of benign and malignant pulmonary nodules. The clinical, imaging and biospecimen repositories will serve as a resource for the biomedical community and their investigation of the molecular basis of chronic respiratory disease.

TRIAL REGISTRATION

Retrospectively registered as NCT01785342 - DECAMP-1: Diagnosis and Surveillance of Indeterminate Pulmonary Nodules (DECAMP-1). Date of Registration: February 7, 2013. Retrospectively registered as NCT02504697 - DECAMP-2: Screening of Patients With Early Stage Lung Cancer or at High Risk for Developing Lung Cancer (DECAMP-2). Date of Registration: July 22, 2015.

A New Approach for the Diagnosis of Systemic and Oral Diseases Based on Salivary Biomolecules

Early diagnosis represents the target of contemporary medicine and has an important role in the prognosis and further treatment. Saliva is a biofluid that generated a high interest among researchers due to its multiple advantages over other body fluids. The multitude of components that can act as biomarkers influenced the existing technologies to develop protocols that could allow saliva to become the new noninvasive diagnostic method. Saliva as a diagnostic tool can bring substantial addition to the diagnostic armamentarium, providing important information about oral and general health. The diagnostic applications of saliva extended and had a rapid evolution due to the advancement in salivaomics. The present review summarizes the latest researches in saliva-related studies and explores the information and correlations that saliva can offer regarding the systemic and oral diseases, highlighting its great potential of diagnosis. It is expected that in the future specific guidelines and results regarding the salivary diagnostics are to be available, together with high-sensitivity and specificity tests for multiple systemic and oral diseases.

Proteomic analysis of plasma exosomes to differentiate malignant from benign pulmonary nodules

Background

It is difficult to distinguish benign pulmonary nodules (PNs) from malignant PNs by conventional examination. Therefore, novel biomarkers that can identify the nature of PNs are needed. Exosomes have recently been identified as an attractive alternative approach since tumor-specific molecules can be found in exosomes isolated from biological fluids.

Methods

Plasma exosomes were extracted via the exoEasy reagent method. The major proteins from plasma exosomes in patients with PNs were identified via labelfree analysis and screened for differentially expressed proteins. A GO classification analysis and KEGG pathway analysis were performed on plasma exosomal protein from patients with benign and malignant PNs.

Results

Western blot confirmed that protein expression of CD63 and CD9 could be detected in the exosome extract. Via a search of the human Uniprot database, 736 plasma exosome proteins from patients with PNs were detected using high-confidence peptides. There were 33 differentially expressed proteins in the benign and malignant PNs. Of these, 12 proteins were only expressed in the benign PNs group, while 9 proteins were only expressed in the malignant PNs group. We further obtained important information on signaling pathways and nodal proteins related to differential benign and malignant PNs via bioinformatic analysis methods such as GO, KEGG, and String.

Conclusions

This study provides a new perspective on the identification of novel detection strategies for benign and malignant PNs. We hope our findings can provide clues for the identification of benign and malignant PNs.

Electronic supplementary material

The online version of this article (10.1186/s12014-019-9225-5) contains supplementary material, which is available to authorized users.

Global Epidemiology of Lung Cancer

While lung cancer has been the leading cause of cancer-related deaths for many years in the United States, incidence and mortality statistics - among other measures - vary widely worldwide. The aim of this study was to review the evidence on lung cancer epidemiology, including data of international scope with comparisons of economically, socially, and biologically different patient groups. In industrialized nations, evolving social and cultural smoking patterns have led to rising or plateauing rates of lung cancer in women, lagging the long-declining smoking and cancer incidence rates in men. In contrast, emerging economies vary widely in smoking practices and cancer incidence but commonly also harbor risks from environmental exposures, particularly widespread air pollution. Recent research has also revealed clinical, radiologic, and pathologic correlates, leading to greater knowledge in molecular profiling and targeted therapeutics, as well as an emphasis on the rising incidence of adenocarcinoma histology. Furthermore, emergent evidence about the benefits of lung cancer screening has led to efforts to identify high-risk smokers and development of prediction tools. This review also includes a discussion on the epidemiologic characteristics of special groups including women and nonsmokers. Varying trends in smoking largely dictate international patterns in lung cancer incidence and mortality. With declining smoking rates in developed countries and knowledge gains made through molecular profiling of tumors, the emergence of new risk factors and disease features will lead to changes in the landscape of lung cancer epidemiology.

Identification a novel clinical biomarker in early diagnosis of human non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a malignant tumor with high morbidity and mortality. The clinical biomarkers currently used for the early diagnosis of lung cancer have poor sensitivity and specificity. Therefore, it is urgent to identify sensitive biomarkers for the early detection of NSCLC to improve the patient survival of patients. In our previously study, we identified glycoprotein alpha-1-antichymotrypsin (AACT) as an early biomarker of NSCLC. In this study, serum glycopeptides were enriched using the high-GlcNAc-specific binding lectin, AANL/AAL2, for further quantitative proteomics analysis using LC-MS/MS. A total of 55 differentially expressed proteins were identified by using demethylation labelling proteomics. Serum paraoxonase/arylesterase 1 (PON1) was selected for validation by western blotting and lectin-ELISA in samples from 120 enrolled patients. Our data showed that AANL-enriched PON1 has better diagnostic performance than total PON1 in early NSCLC, since it differed between early Stage I tumor samples and tumor-free samples (healthy and benign). Combining AANL-enriched PON1 with carcinoembryonic antigen (CEA) significantly improved the diagnostic specificity of CEA. Moreover, combined AANL-enriched PON1 and AANL-enriched AACT was significantly different between early NSCLC samples and tumor-free samples with an AUC of 0.940, 94.4% sensitivity, and 90.2% specificity. Our findings suggest that combined AANL-enriched PON1 and AANL-enriched AACT is a potential clinical biomarker for the early diagnosis of NSCLC.

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.

SOX30 specially prevents Wnt-signaling to suppress metastasis and improve prognosis of lung adenocarcinoma patients

BACKGROUND

Different histological subtypes of non-small cell lung cancer (NSCLC) show different molecular characteristics and responses to therapeutic strategy. Identification of specific gene, clarification of its special roles and molecular mechanisms are crucial for developing new therapeutic approach for particular subtype patients.

METHODS

Surgical specimens of 540 NSCLC patients were recruited. Immunohistochemistry was used to detect SOX30 expression, and correlations with clinical parameters were analyzed. Functional experiments and gene ontology analysis were performed to investigate roles of SOX30. Network analysis, TOP/FOP-Flash assays, luciferase reporter assays and ChIP-PCR assays were performed to determine the mechanism. Survival analyses were calculated by Kaplan-Meier and Cox regression. Recovery experiment was investigated the importance of the target of SOX30.

RESULTS

SOX30 expression is closely associated with histological types of NSCLC, and metastasis of adenocarcinoma (ADC) patients but not of squamous cell carcinoma (SCC) patients. SOX30 strongly inhibits cancer cell migration and invasion in ADC cell lines, whrereas not affects cell migration and invasion in SCC cell lines. The genes associated with SOX30 preferentially enrich in metastasis process and Wnt-signaling in only ADC patients. Consistently, SOX30 is negatively associated with the expression of Wnt-signaling and metastasis-related gene CTNNB1 (β-catenin) in ADC, but not in SCC. At the molecular level, SOX30 represses Wnt-signaling by directly transcriptional inhibition of CTNNB1 in ADC, and also not in SCC. In the clinical, SOX30 is a favorable and independent prognostic factor in ADC patients, whereas is an unfavorable and independent prognostic factor in SCC patients. Moreover, SOX30 expression is a double face early-stage prognostic biomarker in ADC and SCC patients. In addition, forcible restoration of CTNNB1 indeed can inhibit the anti-metastatic role of SOX30 in ADC patients.

CONCLUSIONS

In early-stage ADC patients, elevated SOX30 expression inhibits tumor-metastasis by directly binding to CTNNB1 promoter resulting in a favorable prognosis of these patients. However, in early-stage SCC patients, SOX30 has no inhibitory role on tumor-metastasis due to not binding to CTNNB1 promoter leading to an unfavorable prognosis of the patients. This study highlights a special role and prognostic value of SOX30 in ADC, providing a novel therapeutic target for particular subtype NSCLC patients.

Clinical biomarkers for cancer recognition and prevention: A novel approach with optical measurements

Cancer is the most important cause of death worldwide, and early cancer detection is the most fundamental factor for efficacy of treatment, prognosis, and increasing survival rate. Over the years great effort has been devoted to discovering and testing new biomarkers that can improve its diagnosis, especially at an early stage. Here we report the potential usefulness of new, easily applicable, non-invasive and relatively low-cost clinical biomarkers, based on abnormalities of oral mucosa spectral reflectance and fractal geometry of the vascular networks in several different tissues, for identification of hereditary non-polyposis colorectal cancer carriers as well for detection of other tumors, even at an early stage. In the near future the methodology/technology of these procedures should be improved, thus making possible their applicability worldwide as screening tools for early recognition and prevention of cancer.

[Prognostic Value of Neutrophil-to-lymphocyte Ratio in Patients with Lung Adenocarcinoma Treated with Radical Dissection]

BACKGROUND

Previous studies have shown that the neutrophil-to-lymphocyte ratio (NLR) has a significant impact on the prognosis of many malignant tumors such as gastric cancer, colorectal cancer and pancreatic cancer, but the study on the prognosis of patients with resectable lung adenocarcinoma is less. The aim of this study is to investigate the correlation between the NLR and the clinicopathologic features of adenocarcinoma of lung patients who underwent radical pneumonectomy. Furthermore, this study aimed to clarify the predictive and prognostic significance of NLR in patients who underwent pneumonectomy for lung adenocarcinoma.

METHODS

This study reviewed the medical records of 163 patients with lung adenocarcinoma who underwent pneumonectomy. The receiver operating characteristic (ROC) curve and Youden index were used to determine the cut-off value of the NLR. Survival curves were described by Kaplan-Meier method and compared by Log-rank test. The univariate and multivariate analyses were performed with the Cox proportional hazard model to identify the prognostic factors.

RESULTS

When the NLR value was 2.96, the Youden index was maximal, with a sensitivity of 77.5% and a specificity of 75.9%. The 5-year survival rate in the low NLR group was higher than that in the high NLR group (P<0.05). The univariate and multivariate analyses showed that TNM staging and NLR were independent factors in predicting survival rate.

CONCLUSIONS

The NLR value was a simple and useful tool to predict the prognosis of lung adenocarcinoma after radical pneumonectomy.

Overexpression of DJ-1 correlates with aggressive clinicopathological characteristics and poor prognosis in malignant tumors: a meta-analysis

Purpose

A number of studies have investigated the role of DJ-1 in the development and progression of malignant tumors. This meta-analysis aims to systematically estimate the rela-tionship between the expression level of DJ-1 and the malignant biological behaviors of tumors and to assess the clinical significances of DJ-1 in the prognosis and diagnosis of cancer.

Materials and methods

We searched PubMed, Web of Science, China National Knowledge Infrastructure and Wanfang databases from inception to December 1, 2017. Pooled odds ratio (OR) and hazard ratio (HR) with their 95% confidence interval and the diagnostic value of DJ-1 were calculated.

Results

Fourteen eligible studies with a total of 1,947 subjects were enrolled in our meta-analysis. The results showed that DJ-1 was overexpressed in cancer patients compared with noncancer patients (OR = 30.72), and elevated expression of DJ-1 was demonstrated to be closely associated with high tumor-node-metastasis stage (OR = 5.52), poor differentiated degree (OR = 2.46), positive lymph node metastasis (OR = 4.12) and worse overall survival (HR = 2.23). In addition, the combined sensitivity and specificity for DJ-1 to discern malignant tumors were 0.73 and 0.93, respectively. The diagnostic OR was 34.87, and the area under the summary receiver operating characteristic curve was 0.88.

Conclusion

This meta-analysis demonstrated that DJ-1 was an important biomarker in tumor assessment and prognosis prediction.