Update on biomarkers for the detection of lung cancer

Combined detection of serum IL-6 and CEA contributes to the diagnosis of lung adenocarcinoma in situ

Background

Effective discrimination of lung adenocarcinoma (LUAD) in situ (AIS) from benign pulmonary nodules (BPN) is critical for the early diagnosis of AIS. Our pilot study in a small cohort of 90 serum samples has shown that serum interleukin 6 (IL-6) detection can distinguish AIS from BPN and health controls (HC). In this study, we intend to comprehensively define the diagnostic value of individual and combined detection of serum IL-6 related to the traditional tumor markers carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) for AIS.

Methods

The diagnostic performance of serum IL-6 along with CEA and CYFRA21-1 were evaluated in a large cohort of 300 serum samples by a chemiluminescence immunoassay and an electrochemiluminescence immunoassay. A training set comprised of 65 AIS, 65 BPN, and 65 HC samples was used to develop the predictive model for AIS. Data obtained from an independent validation set was applied to evaluate and validate the predictive model.

Results

In the training set, the levels of serum IL-6 and CEA in the AIS group were significantly higher than those in the BPN/HC group (P < 0.05). There was no significant difference in serum CYFRA21-1 levels between the AIS group and the BPN/HC group (P> 0.05). Serum IL-6 and CEA levels for AIS patients showed an area under the curve (AUC) of 0.622 with 23.1% sensitivity at 90.7% specificity, and an AUC of 0.672 with 24.6% sensitivity at 97.6% specificity, respectively. The combination of serum IL-6 and CEA presented an AUC of 0.739, with 60.0% sensitivity at 95.4% specificity. The combination of serum IL-6 and CEA showed an AUC of 0.767 for AIS patients, with 57.1% sensitivity at 91.4% specificity in the validation set.

Conclusions

IL-6 shows potential as a prospective serum biomarker for the diagnosis of AIS, and the combination of serum IL-6 with CEA may contribute to increased accuracy in AIS diagnosis. However, it is worth noting that further research is still necessary to validate and optimize the diagnostic efficacy of these biomarkers and to address potential sensitivity limitations.

Evaluation of Expression Levels of NFATc2 and PPARG Genes Two Effector Elements of WNT Pathway in Non-Small Cell Lung Carcinoma

Background

There is an emergency need in discovering an efficient profile of molecular biomarkers for early diagnosis of Non-small cell lung cancer (NSCLC). Transcription factors as important groups of regulators that are able to adjust the cell cycles have attracted the attention of most researchers recently. NFATc2 and PPARG are two important factors that have been selected for this project to assess their potential for being a biomarker for NSCLC.

Materials and Methods

Here in this study, 50 NSCLC patients were included. During bronchoscopy, which was their routine diagnostic approach, we collected tumoral and marginal normal tissues. After the extraction of the total RNA from the tissues, cDNA was synthesized, and the transcriptional level of NFATc2 and PPARG was examined by quantitative real-time PCR. Subsequently, the data were analyzed by proper statistical analyses.

Results

The mRNA expression of NFATc2 and PPARG were down-regulated in biopsy tissues of NSCLC patients compared with their pair marginal tissues (Pvalues were 0.0011 and <0.0001 respectively). Moreover, both of them had significant AUC (area under the curve) in the ROC curve analysis (0.65 for NFATc2 and 0.81 for PPARG, Pvalue <0.05).

Conclusion

It appears that mRNA expression of NFATc2 and PPARG possesses the potential to be regarded as a diagnostic or prognostic biomarker for NSCLC.

Fucosylated exosomal miRNAs as promising biomarkers for the diagnosis of early lung adenocarcinoma

Background

Considering the absence of apparent symptoms at the early stage, most patients with lung adenocarcinoma (LUAD) present at an advanced stage, leading to a dismal 5-year survival rate of <20%. Thus, finding perspective non-invasive biomarkers for early LUAD is very essential.

Methods

We developed a fucose-captured strategy based on lentil lectin-magnetic beads to isolate fucosylated exosomes from serum. Then, a prospective study was conducted to define the diagnostic value of serum exosomal miRNAs for early LUAD. A total of 310 participants were enrolled, including 146 LUAD, 98 benign pulmonary nodules (BPNs), and 66 healthy controls (HCs). Firstly, exosome miRNAs in the discovery cohort (n = 24) were profiled by small RNA sequencing. Secondly, 12 differentially expressed miRNAs (DEmiRs) were selected for further screening in a screening cohort (n = 64) by qRT-PCR. Finally, four candidate miRNAs were selected for further validation in a validating cohort (n = 222).

Results

This study demonstrated the feasibility of a fucose-captured strategy for the isolation of fucosylated exosomes from serum, evidenced with exosomal characteristics identified by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and Western blotting, as well as rapid and convenient operation of <10 min. Furthermore, a miRNA panel for early LUAD composed of miR4732-5p, miR451a, miR486-5p, and miR139-3p was defined with an AUC of 0.8554 at 91.07% sensitivity and 66.36% specificity.

Conclusions

The fucose-captured strategy provides a reliable, as well as rapid and convenient, approach for the isolation of tumor-derived exosomes from serum. A four-fucosylated exosomal miRNA panel presents good performance for early LUAD diagnosis.

Serum and Serum Exosomal CircRNAs hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 as Diagnostic Biomarkers for Lung Adenocarcinoma

Background

Circular RNAs (circRNAs) play an important role in tumorigenesis and several circulating circRNA signatures are closely associated with tumor diagnosis. However, the expression and clinical significance of the two forms of circulating circRNAs, serum and serum exosomal, in patients with lung adenocarcinoma (LUAD), have not been characterized.

Methods

Three differentially expressed exosomal circRNAs, hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896, were selected based on previous exosomal circRNA sequencing data analyses of LUAD patients. The expression of these circRNAs in serum and serum-derived exosomes of LUAD patients was assessed using quantitative real-time PCR (qRT-PCR), and correlations between circRNA expression and clinicopathological characteristics were analyzed. The reliability of serum and serum exosomal hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 to diagnose LUAD was evaluated using receiver operating characteristic (ROC) analysis.

Results

Expression of serum and serum exosomal hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 were significantly higher in LUAD patients than in healthy donors, and significantly lower after surgery. These three serum exosomal circRNAs were also associated with a higher cancer stage. Exosomal hsa_circ_0001492 expression was positively correlated with carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) levels. An association between the expression of the three serum circRNAs and clinical characteristics was not observed. In addition, the three serum exosomal circRNAs had higher diagnostic sensitivity and specificity than the serum circRNAs, and the area under the curve (AUC) of all three serum exosomal circRNAs was &gt;0.75. The combination of exosomal hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896 had better diagnostic sensitivity and specificity than that of a single marker, with an AUC value of 0.805.

Conclusions

The serum and serum exosomal circRNAs, hsa_circ_0001492, hsa_circ_0001439, and hsa_circ_0000896, were upregulated in LUAD patients. Serum exosomal circRNAs may serve as more effective biomarkers than serum circRNAs for LUAD diagnosis and may further aid the detection of this disease.

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.

Combination of Serum miRNAs with Serum Exosomal miRNAs in Early Diagnosis for Non-Small-Cell Lung Cancer

Purpose

Circulating microRNAs (miRNAs) have shown the potential for non-invasive diagnosis of various types of malignancies at an early stage. The aim of the study was to explore the feasibility of a combination of 8 serum miRNAs related to non-small-cell lung cancer (NSCLC) with the corresponding serum exosomal miRNAs in early diagnosis for the patients with NSCLC.

Methods

We measured 8 serum miRNAs and the corresponding serum exosomal miRNAs including miR-21-5p, miR-126-3p, miR-141-3p, miR-146a-5p, miR-155-5p, miR-222-3p, miR-223-3p, and miR-486-5p in 48 patients with early NSCLC at stages I/II, 32 patients with lung benign lesion (LBL), and 48 healthy control (HC) by quantitative real-time polymerase chain reaction (qRT-PCR).

Results

The expression levels of 4 serum miRNAs including miR-21-5p, miR-141-3p, miR-222-3p, and miR-486-5p, and 2 serum exosomal miRNAs including miR-146a-5p and miR-486-5p in the early NSCLC group were significantly different from that in the LBL group and the HC group (P < 0.01). The areas under the receiver operating characteristic curves (AUC) of the 4 serum miRNAs and 2 serum exosomal miRNAs in the early NSCLC group were ≥0.697, of which serum exosomal miR-146a-5p and miR-486-5p were 0.813 and 0.886, respectively, and higher than that of the 4 serum miRNAs. Additionally, a combination of 4 serum miRNAs with 2 serum exosomal miRNAs improved the AUC to 0.960 for the patients with NSCLC at early stages, with a sensitivity of 85.42% and a specificity of 92.50%.

Conclusion

This study suggests that serum exosomal miRNAs other than serum miRNAs might be preferable biomarkers for the patients with NSCLC at early stages, and a combination of serum miRNAs with serum exosomal miRNAs contributes to the further improvement of early diagnosis for NSCLC.

The Combination of IgA and IgG autoantibodies against Transcriptional Intermediary Factor-1γ contributes to the early diagnosis of Lung Cancer

Objective: The aberrant expression of tumor-associated antigens (TAAs) is responsible for the release of large amounts of autoantibodies in sera, and serum autoantibody detection has been demonstrated to contribute to the early diagnosis of malignancies. Recent studies showed the closely correlation of transcriptional intermediary factor-1γ (TIF1γ) with some malignancies. In our pilot study, we found aberrantly high expression of TIF1γ protein existed in cancer tissues other than matched paracancerous tissues of patients with lung cancer (LC) at early stage by immunohistochemistry (IHC) staining. As a result, this study aims to detect the expression of autoantibodies against TIF1γ in sera of patients with LC at early stage by using enzyme-linked immunosorbent assay (ELISA) and investigate its potential value for the early diagnosis of LC. Methods: The expressions of TIF1γ protein in 60 pairs of LC tissues and matched paracancerous tissues were detected by IHC staining. The levels of anti-TIF1γ-IgA, IgG, IgM, and IgE in the sera of 248 patients with LC at early stage, 200 patients with lung benign lesions (LBL), and 218 healthy controls (HC) were detected by ELISA, respectively. Western blot was used to validate the ELISA results of serum autoantibodies against TIF1γ. Results: The positive rate of TIF1γ protein expression in LC tissues was 83.33%, which was significantly higher than 25.00% in paracancerous tissues (P<0.01). The levels and positive rates of serum anti-TIF1γ-IgM and anti-TIF1γ-IgE in early LC group had no significant difference from that in LBL group and HC group (P>0.05), while the levels and positive rates of anti-TIF1γ-IgA and anti-TIF1γ-IgG were significantly higher than that in LBL group and HC group (P<0.01), of which anti-TIF1γ-IgA showed the area under the receiver operating characteristic curve (AUC) of 0.704 for the patients with LC at early stage, with 28.20% sensitivity at 95.93% specificity, and anti-TIF1γ-IgG showed the AUC of 0.622 for the patients with LC at early stage, with 18.54% sensitivity at 94.25% specificity. The results of anti-TIF1γ-IgA and anti-TIF1γ-IgG in western blot were consistent with that in ELISA. Additionally, the combination of anti-TIF1γ-IgA and anti-TIF1γ-IgG improved the AUC to 0.734, with 38.31% sensitivity at 92.34% specificity. Conclusions: There is a strong humoral immune response to autologous TIF1γ existing in patients with early LC. Both serum anti-TIF1γ-IgA and anti-TIF1γ-IgG show the diagnostic value for the patients with LC at early stage, of which anti-TIF1γ-IgA is donstrated to be a preferable biomarker, and the combined detection of anti-TIF1γ-IgA and anti-TIF1γ-IgG might contribute to the further improvement of early diagnosis for LC.

Identification of lung cancer gene markers through kernel maximum mean discrepancy and information entropy

BACKGROUND

The early diagnosis of lung cancer has been a critical problem in clinical practice for a long time and identifying differentially expressed gene as disease marker is a promising solution. However, the most existing gene differential expression analysis (DEA) methods have two main drawbacks: First, these methods are based on fixed statistical hypotheses and not always effective; Second, these methods can not identify a certain expression level boundary when there is no obvious expression level gap between control and experiment groups.

METHODS

This paper proposed a novel approach to identify marker genes and gene expression level boundary for lung cancer. By calculating a kernel maximum mean discrepancy, our method can evaluate the expression differences between normal, normal adjacent to tumor (NAT) and tumor samples. For the potential marker genes, the expression level boundaries among different groups are defined with the information entropy method.

RESULTS

Compared with two conventional methods t-test and fold change, the top average ranked genes selected by our method can achieve better performance under all metrics in the 10-fold cross-validation. Then GO and KEGG enrichment analysis are conducted to explore the biological function of the top 100 ranked genes. At last, we choose the top 10 average ranked genes as lung cancer markers and their expression boundaries are calculated and reported.

CONCLUSION

The proposed approach is effective to identify gene markers for lung cancer diagnosis. It is not only more accurate than conventional DEA methods but also provides a reliable method to identify the gene expression level boundaries.

Untargeted metabolomics profiles delineate metabolic alterations in mouse plasma during lung carcinoma development using UPLC-QTOF/MS in MSE mode

In this work, an untargeted metabolomic method based on ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) in MSE (E represents collision energy) mode was exploited to determine the dynamic metabolic alterations in the plasma of male C57BL/6 mice during the onset and development of lung carcinoma. Plasma samples were collected from control and model mice (male C57BL/6 mice experimentally inoculated with the Lewis lung carcinoma cells) at 7 and 14 days post-inoculation (DPI). As a result, 15 dysregulated metabolites, including cholesterol sulphate, tiglylcarnitine, 1-palmitoylglycerophosphoinositol, 2-stearoylglycerophosphoinositol, stearoylcarnitine, PC(20:2(11Z,14Z)/16:0), PC(22:4(7Z,10Z,13Z,16Z)/14:0), PC(22:5(7Z,10Z,13Z,16Z,19Z)/14:0), PC(22:6(4Z,7Z,10Z,13Z,16Z,19Z)/16:0), 12,20-Dioxo-leukotriene B4, sphingosine 1-phosphate(d19:1-P), sphingomyelin(d18:0/16:1(9Z)), lysoPC(16:0), lysoPC(18:0) and lysoPC(20:4(5Z,8Z,11Z,14Z)), were identified in the plasma of model mice with xenografts at both 7 and 14 DPI. All the altered metabolites associated with the onset and development of lung carcinoma were involved in the metabolism of glycerophospholipid, fatty acid, sphingolipid and arachidonic acid. The feasible utility of these endogenous biomarkers as potential diagnostic indicators was validated through receiver operating characteristic curve analysis. Collectively, these findings provide a systematic view of metabolic changes linked to the onset and development of lung carcinoma.

Circulating Heat Shock Protein 70 Is a Novel Biomarker for Early Diagnosis of Lung Cancer

Heat shock protein 70 (HSP70) was a highly conserved protein which was significantly induced in response to cellular stresses. HSP70 played an important role in the pathogenesis of cancer which stabilized the production of large amount of oncogenic proteins and finally supported growth and survival of tumor. However, there was no report about the diagnosis of circulating HSP70 in lung cancer patients. In this study, a total of 297 participants (lung cancer: 197, healthy control: 100) were enrolled in the detection of circulating HSP70 level in plasma by ELISA assay. The results indicated that circulating HSP70 significantly decreased in lung cancer patients compared to healthy controls (P < 0.0001). Receiver operating characteristic (ROC) analysis showed that HSP70 (AUC: 82.2%, SN: 74.1%, SP: 80.0%) had higher diagnosis value than clinical existing biomarkers CEA (AUC: 80.1%, SN: 76.8%, SP: 67.3%) and CA 19-9 (AUC: 63.7%, SN: 64.2%, SP: 54.0%). In the analysis of early lung cancer patients, ROC results also revealed that HSP70 (AUC: 83.8%, SN: 71.2%, SP: 84.0%) have higher sensitivity, specificity, and AUC than CEA (AUC: 73.7%, SN: 73.2%, SP: 69.1%) and CA 19-9 (AUC: 61.5%, SN: 69.4%, SP: 53.4%). In analysis of specific histological classifications, HSP70 showed more valuable in the diagnosis of SCC (AUC: 85.9%, SN: 86.1.9%, SP: 81.0%) than ADC (AUC: 81.0%, SN: 69.1%, SP: 81.0%). Combined analysis of HSP70 and existing biomarker: CEA and CA 19-9 exhibited that HSP70 combined CEA and CA 19-9 showed the highest AUC (0.945, 95% CI, 0.855–1.000). The importance of our results was that we found decreased circulating HSP70, in combination with elevated CEA and CA 19-9, could be utilized in the diagnosis of early (stage I and II) lung cancer.

Current and Prospective Protein Biomarkers of Lung Cancer

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

A miR-SNP biomarker linked to an increased lung cancer survival by miRNA-mediated down-regulation of FZD4 expression and Wnt signaling

Through a new hypothesis-driven and microRNA-pathway-based SNP (miR-SNP) association study we identified a novel miR-SNP (rs713065) in the 3'UTR region of FZD4 gene linked with decreased risk of death in early stage NSCLC patients. We determined biological function and mechanism of action of this FZD4-miR-SNP biomarker in a cellular platform. Our data suggest that FZD4-miR-SNP loci may significantly influence overall survival in NSCLC patients by specifically interacting with miR-204 and modulating FZD4 expression and cellular function in the Wnt-signaling-driven tumor progression. Our findings are bridging the gap between the discovery of epidemiological SNP biomarkers and their biological function and will enable us to develop novel therapeutic strategies that specifically target epigenetic markers in the oncogenic Wnt/FZD signaling pathways in NSCLC.

INTEGRATIVE ANALYSIS FOR LUNG ADENOCARCINOMA PREDICTS MORPHOLOGICAL FEATURES ASSOCIATED WITH GENETIC VARIATIONS

Lung cancer is one of the most deadly cancers and lung adenocarcinoma (LUAD) is the most common histological type of lung cancer. However, LUAD is highly heterogeneous due to genetic difference as well as phenotypic differences such as cellular and tissue morphology. In this paper, we systematically examine the relationships between histological features and gene transcription. Specifically, we calculated 283 morphological features from histology images for 201 LUAD patients from TCGA project and identified the morphological feature with strong correlation with patient outcome. We then modeled the morphology feature using multiple co-expressed gene clusters using Lasso-regression. Many of the gene clusters are highly associated with genetic variations, specifically DNA copy number variations, implying that genetic variations play important roles in the development cancer morphology. As far as we know, our finding is the first to directly link the genetic variations and functional genomics to LUAD histology. These observations will lead to new insight on lung cancer development and potential new integrative biomarkers for prediction patient prognosis and response to treatments.

Serum calprotectin, CD26 and EGF to establish a panel for the diagnosis of lung cancer

Lung cancer is the most lethal neoplasia, and an early diagnosis is the best way for improving survival. Symptomatic patients attending Pulmonary Services could be diagnosed with lung cancer earlier if high-risk individuals are promptly separated from healthy individuals and patients with benign respiratory pathologies. We searched for a convenient non-invasive serum test to define which patients should have more immediate clinical tests. Six cancer-associated molecules (HB-EGF, EGF, EGFR, sCD26, VEGF, and Calprotectin) were investigated in this study. Markers were measured in serum by specific ELISAs, in an unselected population that included 72 lung cancer patients of different histological types and 56 control subjects (healthy individuals and patients with benign pulmonary pathologies). Boosted regression and random forests analysis were conducted for the selection of the best candidate biomarkers. A remarkable discriminatory capacity was observed for EGF, sCD26, and especially for Calprotectin, these three molecules constituting a marker panel boasting a sensitivity of 83% and specificity of 87%, resulting in an associated misclassification rate of 15%. Finally, an algorithm derived by logistic regression and a nomogram allowed generating classification scores in terms of the risk of a patient of suffering lung cancer. In conclusion, we propose a non-invasive test to identify patients at high-risk for lung cancer from a non-selected population attending a Pulmonary Service. The efficacy of this three-marker panel must be tested in a larger population for lung cancer.

Immune-Signatures for Lung Cancer Diagnostics: Evaluation of Protein Microarray Data Normalization Strategies

New minimal invasive diagnostic methods for early detection of lung cancer are urgently needed. It is known that the immune system responds to tumors with production of tumor-autoantibodies. Protein microarrays are a suitable highly multiplexed platform for identification of autoantibody signatures against tumor-associated antigens (TAA). These microarrays can be probed using 0.1 mg immunoglobulin G (IgG), purified from 10 µL of plasma. We used a microarray comprising recombinant proteins derived from 15,417 cDNA clones for the screening of 100 lung cancer samples, including 25 samples of each main histological entity of lung cancer, and 100 controls. Since this number of samples cannot be processed at once, the resulting data showed non-biological variances due to “batch effects”. Our aim was to evaluate quantile normalization, “distance-weighted discrimination” (DWD), and “ComBat” for their effectiveness in data pre-processing for elucidating diagnostic immune-signatures. “ComBat” data adjustment outperformed the other methods and allowed us to identify classifiers for all lung cancer cases versus controls and small-cell, squamous cell, large-cell, and adenocarcinoma of the lung with an accuracy of 85%, 94%, 96%, 92%, and 83% (sensitivity of 0.85, 0.92, 0.96, 0.88, 0.83; specificity of 0.85, 0.96, 0.96, 0.96, 0.83), respectively. These promising data would be the basis for further validation using targeted autoantibody tests.

Early Detection of Lung Cancer in Serum by a Panel of MicroRNA Biomarkers

INTRODUCTION

The objective of the study was to develop a panel of microRNAs (miRNAs) as highly sensitive and specific biomarkers for lung cancer early detection.

MATERIALS AND METHODS

The study contained 2 phases: first, preliminary marker selection based on previous reports on the serum of 24 early stage lung cancer patients and 24 healthy control subjects by TaqMan probe-based real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR); and second, validation of miRNA markers on 94 early stage lung cancer, 48 stage III to IV lung cancer, and 111 healthy control serum samples.

RESULTS

A total of 3 miRNAs (miR-125a-5p, miR-25, and miR-126) were selected for further analysis in this study. The combination of the 3 miRNAs could produce 0.936 area under the receiver operating characteristic curve value in distinguishing early stage lung cancer patients from control subjects with 87.5% sensitivity and 87.5% specificity, respectively. The diagnostic value of the miRNA panel in an independent set of lung cancer patients confirmed the sensitivity and specificity.

CONCLUSION

The results demonstrated that the panel of miRNA biomarkers had the potential for the early detection of lung cancer.

Serum biomarkers reflecting specific tumor tissue remodeling processes are valuable diagnostic tools for lung cancer

Extracellular matrix (ECM) proteins, such as collagen type I and elastin, and intermediate filament (IMF) proteins, such as vimentin are modified and dysregulated as part of the malignant changes leading to disruption of tissue homeostasis. Noninvasive biomarkers that reflect such changes may have a great potential for cancer. Levels of matrix metalloproteinase (MMP) generated fragments of type I collagen (C1M), of elastin (ELM), and of citrullinated vimentin (VICM) were measured in serum from patients with lung cancer (n = 40), gastrointestinal cancer (n = 25), prostate cancer (n = 14), malignant melanoma (n = 7), chronic obstructive pulmonary disease (COPD) (n = 13), and idiopathic pulmonary fibrosis (IPF) (n = 10), as well as in age-matched controls (n = 33). The area under the receiver operating characteristics (AUROC) was calculated and a diagnostic decision tree generated from specific cutoff values. C1M and VICM were significantly elevated in lung cancer patients as compared with healthy controls (AUROC = 0.98, P < 0.0001) and other cancers (AUROC = 0.83 P < 0.0001). A trend was detected when comparing lung cancer with COPD+IPF. No difference could be seen for ELM. Interestingly, C1M and VICM were able to identify patients with lung cancer with a positive predictive value of 0.9 and an odds ratio of 40 (95% CI = 8.7–186, P < 0.0001). Biomarkers specifically reflecting degradation of collagen type I and citrullinated vimentin are applicable for lung cancer patients. Our data indicate that biomarkers reflecting ECM and IMF protein dysregulation are highly applicable in the lung cancer setting. We speculate that these markers may aid in diagnosing and characterizing patients with lung cancer.