A Panel of Sputum-Based Genomic Marker for Early Detection of Lung Cancer

High-Throughput Detection of Multiple miRNAs and Methylated DNA by Droplet Digital PCR

Altered miRNA expression and DNA methylation have highly active and diverse roles in carcinogenesis. Simultaneous detection of the molecular aberrations may have a synergistic effect on the diagnosis of malignancies. Herein, we develop a high-throughput assay for detecting multiple miRNAs and DNA methylation using droplet digital PCR (ddPCR) coupled with a 96-microwell plate. The microplate-based ddPCR could absolutely and reproducibly quantify 15 miRNAs and 14 DNA methylation sites with a high sensitivity (one copy/µL and 0.1%, respectively). Analyzing sputum and plasma of 40 lung cancer patients and 36 cancer-free smokers by this approach identified an integrated biomarker panel consisting of two sputum miRNAs (miRs-31-5p and 210-3p), one sputum DNA methylation (RASSF1A), and two plasma miRNAs (miR-21-5p and 126) for the diagnosis of lung cancer with higher sensitivity and specificity compared with a single type of biomarker. The diagnostic value of the integrated biomarker panel for the early detection of lung cancer was confirmed in a different cohort of 36 lung cancer patients and 39 cancer-free smokers. The high-throughput assay for quantification of multiple molecular aberrations across sputum and plasma could improve the early detection of lung cancer.

Microbiota Biomarkers for Lung Cancer

Non-small cell lung cancer (NSCLC) is the number one cancer killer and its early detection can reduce mortality. Accumulating evidences suggest an etiopathogenic role of microorganisms in lung tumorigenesis. Certain bacteria are found to be associated with NSCLC. Herein we evaluated the potential use of microbiome as biomarkers for the early detection of NSCLC. We used droplet digital PCR to analyze 25 NSCLC-associated bacterial genera in 31 lung tumor and the paired noncancerous lung tissues and sputum of 17 NSCLC patients and ten cancer-free smokers. Of the bacterial genera, four had altered abundances in lung tumor tissues, while five were aberrantly abundant in sputum of NSCLC patients compared with their normal counterparts (all p < 0.05). Acidovorax and Veillonella were further developed as a panel of sputum biomarkers that could diagnose lung squamous cell carcinoma (SCC) with 80% sensitivity and 89% specificity. The use of Capnocytophaga as a sputum biomarker identified lung adenocarcinoma (AC) with 72% sensitivity and 85% specificity. The use of Acidovorax as a sputum biomarker had 63% sensitivity and 96% specificity for distinguishing between SCC and AC, the two major types of NSCLC. The sputum biomarkers were further validated for the diagnostic values in a different cohort of 69 NSCLC cases and 79 cancer-free controls. Sputum microbiome might provide noninvasive biomarkers for the early detection and classification of NSCLC.

Autoantibodies against tumor-associated antigens in sputum as biomarkers for lung cancer

Tumor antigens (TAs) can initiate host immune responses and produce TA-associated autoantibody (TAAbs), potential cancer biomarkers. Sputum is directly generated from the upper and lower airways, and thus can be used as a surrogate sample for the diagnosis of lung cancer based on molecular analysis. To develop sputum TAAb biomarkers for the early detection of lung cancer, the leading cause of cancer death, we probed a protein microarray containing more than 9,000 antigens with sputum supernatants of a discovery set of 30 lung cancer patients and 30 cancer-free smokers. Twenty-eight TAs with higher reactivity in sputum of lung cancer cases vs. controls were identified. The diagnostic significance of TAAbs against the TAs was determined by enzyme-linked immunosorbent assays (ELISAs) in sputum of the discovery set and additional 166 lung cancer patients and 213 cancer-free smokers (validation set). Three sputum TAAbs against DDX6, ENO1, and 14-3-3ζ were developed as a biomarker panel with 81% sensitivity and 83% specificity for diagnosis of lung cancer, regardless of stages, locations, and histological types of lung tumors. This study provides the first evidence that sputum TAAbs could be used as biomarkers for the early detection of lung cancer.

A Non-Coding RNA Landscape of Bronchial Epitheliums of Lung Cancer Patients

We propose to systematically identify a non-coding RNA (ncRNA) profile of exfoliated bronchial epitheliums of sputum from lung cancer patients. Bronchial epithelial cells enriched from sputum of 32 lung cancer patients and 33 cancer-free smokers were analyzed by next-generation sequencing to comprehensively characterize the ncRNA profiles. In addition, 108 miRNAs, 88 small nucleolar RNAs, 13 piwi-interacting RNAs, 6 transfer RNAs, 4 ribosomal RNAs, 19 small nuclear RNAs, and 25 long-noncoding (lnc) RNAs displayed a significantly different level in bronchial epitheliums of sputum of lung cancer patients versus cancer-free smokers (all <0.001). PCR analysis confirmed their different expression levels in the sputum specimens. A high expression of SNHG9, an lncRNA, was validated in 78 lung tumor tissues, and the expression was inversely associated with overall survival of lung cancer patients (p = 0.002). Knockdown of SNHG9 in cancer cells reduced the cell growth, proliferation, and invasion in vitro and tumorigenesis in vivo. The multiple differentially expressed ncRNAs in bronchial epitheliums may contribute to the development and progression of lung cancer and provide potential biomarkers and therapeutic targets for the disease.

Sputum long non-coding RNA biomarkers for diagnosis of lung cancer

BACKGROUND

Analysis of molecular changes in sputum may help diagnose lung cancer. Long non-coding RNAs (lncRNAs) play vital roles in various biological processes, and their dysregulations contribute to the development and progression of lung tumorigenesis. Herein, we determine whether aberrant lncRNAs could be used as potential sputum biomarkers for lung cancer.

METHODS

Using reverse transcription PCR, we measure expressions of lung cancer-associated lncRNAs in sputum of a discovery cohort of 67 lung cancer patients and 65 cancer-free smokers with benign diseases and a validation cohort of 59 lung cancer patients and 60 cancer-free smokers with benign diseases.

RESULTS

In the discovery cohort, four of the lncRNAs displayed a significantly different level in sputum of lung cancer patients vs.cancer-free smokers with benign diseases (all P< 0.001). From the four lncRNAs, three lncRNAs (SNHG1, H19, and HOTAIR) are identified as a biomarker panel, producing 82.09% sensitivity and 89.23% specificity for diagnosis of lung cancer. Furthermore, the biomarker panel has a higher sensitivity (82.09% vs. 52.24%, P= 0.02) and a similar specificity compared with sputum cytology (89.23% vs. 90.77%, P= 0.45). In addition, the lncRNA biomarker panel had a higher sensitivity (87.50% vs. 70.07%, p= 0.03) for diagnosis of squamous cell carcinoma compared with adenocarcinoma of the lung, while maintaining the same specificity (89.23%). The potential of the sputum lncRNA biomarkers for lung cancer detection is confirmed in the validation cohort.

CONCLUSION

We have for the first time shown that the analysis of lncRNAs in sputum might be a noninvasive approach for diagnosis of lung cancer.

The Skp2 Pathway: A Critical Target for Cancer Therapy

Strictly regulated protein degradation by ubiquitin-proteasome system (UPS) is essential for various cellular processes whose dysregulation is linked to serious diseases including cancer. Skp2, a well characterized component of Skp2-SCF E3 ligase complex, is able to conjugate both K48-linked ubiquitin chains and K63-linked ubiquitin chains on its diverse substrates, inducing proteasome mediated proteolysis or modulating the function of tagged substrates respectively. Overexpression of Skp2 is observed in various human cancers associated with poor survival and adverse therapeutic outcomes, which in turn suggests that Skp2 engages in tumorigenic activity. To that end, the oncogenic properties of Skp2 are demonstrated by various genetic mouse models, highlighting the potential of Skp2 as a target for tackling cancer. In this article, we will describe the downstream substrates of Skp2 as well as upstream regulators for Skp2-SCF complex activity. We will further summarize the comprehensive oncogenic functions of Skp2 while describing diverse strategies and therapeutic platforms currently available for developing Skp2 inhibitors.

MicroRNA-based biomarkers for diagnosis of non-small cell lung cancer (NSCLC)

Background

The development of biomarkers for the early detection of non‐small cell lung cancer (NSCLC) is clinically important. We have developed miRNA biomarkers in sputum and plasma, respectively, for NSCLC. Herein, we evaluate whether integrated analysis of the miRNAs across the different types of specimens could improve the early detection of NSCLC.

Methods

Using reverse transcription PCR, we determined expressions of two miRNAs (miRs‐31‐5p and 210‐3p) in sputum and three miRNAs (miRs‐21‐5p, 210‐3p, and 486‐5p) in plasma of a training cohort of 76 NSCLC patients and 72 cancer‐free smokers. The results were validated in a testing cohort of 56 NSCLC patients and 55 cancer‐free smokers.

Results

The panels of two sputum miRNAs and three plasma miRNAs had 65.8–75.0% sensitivities and 83.3–87.5% specificities for diagnosis of NSCLC in the training cohort. The individual sputum or plasma miRNA panel had a higher sensitivity for squamous cell carcinoma or adenocarcinoma of the lung, respectively. From the miRNAs, we optimized an integrated panel of biomarkers consisting of two sputum miRNAs (miRs‐31‐5p and 210‐3p) and one plasma miRNA (miR‐21‐5p) that had higher sensitivity (85.5%) and specificity (91.7%) for diagnosis of NSCLC compared with the individual panels alone. Furthermore, the performance of the integrated panel of biomarkers was independent of histology and stage of NSCLC, and patients' age, sex, and ethnicity. The performance of the integrated panel of biomarkers was confirmed in the testing cohort.

Conclusions

Integrating biomarkers across different body fluids would synergistically improve the early detection of NSCLC.

Key points

Lung cancer is a heterogeneous disease and develops from complex aberrations.

Integrating sputum and plasma miRNAs has higher accuracy than when they are used alone

MicroRNAs in sputum specimen as noninvasive biomarkers for the diagnosis of nonsmall cell lung cancer: An updated meta-analysis

BACKGROUND

Nonsmall cell lung cancer (NSCLC) is a serious leading cause of death worldwide. Recently, multiple researches have identified that microRNA (miRNA) in sputum could be a useful tool for NSCLC diagnosis. The objective of this study was to assess whether aberrant miRNA expression could be regarded as a useful biomarker in sputum specimen for the diagnosis of NSCLC.

METHODS

Eligible studies were searched in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP databases up to June 2018. We calculated the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) to investigate the diagnostic value of miRNA in sputum for NSCLC. MetaDisc1.4 and STATA12.0 were used to analyze the retrieved data.

RESULTS

Finally, a total of 14 articles were included in this meta-analysis involving 1009 NSCLC patients and 1006 controls. The results were as followed: the pooled sensitivity, specificity, PLR, NLR, DOR, were 0.75 (95%CI:0.72-0.78), 0.88 (95%CI:0.86-0.90), 5.70 (95%CI:4.82-6.75), 0.30 (95%CI:0.26-0.34), 22.43 (95%CI:17.48-28.79), respectively. The AUC of overall summary receiver operator characteristic curve (SROC) was 0.8917.

CONCLUSION

Our comprehensive analysis indicated that miRNAs in sputum specimen may be noninvasive diagnostic biomarkers for NSCLC. However, much more studies should be conducted before clinical application.

Fucosylation genes as circulating biomarkers for lung cancer

PURPOSE

Fucosyltransferases (FUTs) catalyze fucosylation, which plays a central role in biological processes. Aberrant fucosylation is associated with malignant transformation. Here we investigated whether transcriptional levels of genes coding the FUTs in plasma could provide cell-free circulating biomarkers for lung cancer.

METHODS

mRNA expression of all 13 Futs (Fut1-11, Pofut1, and Pofut2) was evaluated by PCR assay in 48 lung tumor tissues and the 48 matched noncancerous lung tissues, and plasma of 64 lung cancer patients and 32 cancer-free individuals to develop plasma Fut biomarkers. The developed plasma Fut biomarkers were validated in an independent cohort of 40 lung cancer patients and 20 controls for their diagnostic performance.

RESULTS

Four of the 13 Futs showed a different transcriptional level in 48 lung tumor tissues compared with the 48 matched nonconscious tissues (all < 0.05). Two (Fut8, and Pofut1) of the four Futs had a higher plasma level in 64 lung cancer patients compared with 32 control subjects, and consistent with that in lung tissue specimens. Combined analysis of the two Futs produced 81% sensitivity and 86% specificity for diagnosis of lung cancer, and was independent of stage and histology of lung tumors. The diagnostic performance of the two plasma biomarkers was successfully validated in the different cohort of 40 lung cancer patients and 20 control individuals.

CONCLUSION

The fucosylation genes may provide new circulating biomarkers for the early detection of lung cancer.

Skp2 expression has different clinicopathological and prognostic implications in lung adenocarcinoma and squamous cell carcinoma

High expression of S-phase kinase associated protein 2 (Skp2) is associated with numerous clinicopathological parameters, including histology, lymph node metastasis, smoking status, differentiation and Tumor-Node-Metastasis stage in non-small cell lung cancer (NSCLC). Skp2 protein is overexpressed in lung squamous cell carcinoma (LUSC), compared with lung adenocarcinoma (LUAD), whilst the clinicopathological and prognostic implications in LUAD or LUSC remain unclear. A larger study is required to assess the differences in Skp2 expression between these NSCLC types. In the present study, the clinicopathological features and immunohistochemical expression of the Skp2 protein were studied in 500 patients with NSCLC (351 with LUAD and 149 with LUSC). Survival analyses were performed using Kaplan-Meier method and Cox regression model. Skp2 associated genes were identified based on the data from The Cancer Genome Atlas database. Skp2 was overexpressed in patients with LUSC, compared with LUAD (P<0.001). In histology subgroup analysis, differences in Skp2 protein expression were observed in patients with LUAD, based on sex, differentiation, smoking history, stage, lymph node metastasis and tumor diameter (P<0.05), but not in patients with LUSC except for smoking status. High Skp2 protein expression in patients with LUAD was associated with reduced overall survival (OS; P<0.001), but not in patients with LUSC (P=0.686). The multivariate analysis demonstrated that Skp2 expression is an independent unfavorable prognostic factor for OS in patients with LUAD (RR=1.845, P<0.05). Bioinformatics analyses revealed that minichromosome maintenance complex component 2, cell division cycle 45, replication factor C subunit 4, which are differently expressed in LUAD and LUSC, are associated with Skp2 expression and participate in DNA replication and G₁/S transition. Skp2 protein expression differs in LUAD and LUSC. The clinicopathological and prognostic implications based on Skp2 expression in LUAD and LUSC should be considered different. LUSC with high Skp2 expression may have robust proliferation ability.

An epigenetic classifier for early stage lung cancer

Background

Methylated genes detected in sputum are promise biomarkers for lung cancer. Yet the current PCR technologies for quantification of DNA methylation and diagnostic value of the sputum biomarkers are not sufficient to be used for lung cancer early detection. The emerging droplet digital PCR (ddPCR) is a straightforward means for precise, direct, and absolute quantification of nucleic acids. Here, we investigate whether ddPCR can sensitively and robustly quantify DNA methylation in sputum for more precise diagnosis of lung cancer.

Results

First, the analytic performance of methylation-specific ddPCR (ddMSP) and quantitative methylation-specific PCR (qMSP) is determined in methylated and unmethylated DNA samples. Second, 29 genes, previously proposed as potential sputum biomarkers for lung cancer, are analyzed by using ddMSP in a training set of 127 lung cancer patients and 159 controls. ddMSP has higher sensitivity, precision, and reproducibility for quantification of methylation compared with qMSP (all p < 0.05). A classifier comprising four sputum methylation biomarkers for lung cancer is developed by using ddMSP, producing 86.6% sensitivity and 90.6% specificity, independent of stage and histology of lung cancer (all p > 0.05). The classifier has higher accuracy compared with sputum cytology (88.8 vs. 70.6%, p < 0.01). The diagnostic performance is confirmed in a testing set of 89 cases and 107 controls.

Conclusions

ddMSP is a robust tool for reliable quantification of DNA methylation in sputum, and the epigenetic classifier could help diagnose lung cancer at the early stage.

An integromic signature for lung cancer early detection

We previously developed three microRNAs (miRs-21, 210, and 486-5p), two long noncoding RNAs (lncRNAs) (SNHG1 and RMRP), and two fucosyltransferase (FUT) genes (FUT8 and POFUT1) as potential plasma biomarkers for lung cancer. However, the diagnostic performance of the individual panels is not sufficient to be used in the clinics. Given the heterogeneity of lung tumors developed from multifactorial molecular aberrations, we determine whether integrating the different classes of molecular biomarkers can improve diagnosis of lung cancer. By using droplet digital PCR, we analyze expression of the seven genes in plasma of a development cohort of 64 lung cancer patients and 33 cancer-free individuals. The panels of three miRNAs (miRs-21, 210, and 486-5p), two lncRNAs (SNHG1 and RMRP), and two FUTs (FUT8 and POFUT1) have a sensitivity of 81-86% and a specificity of 84-87% for diagnosis of lung cancer. From the seven genes, an integromic plasma signature comprising miR-210, SNHG1, and FUT8 is developed that produces higher sensitivity (95.45%) and specificity (96.97%) compared with the individual biomarker panels (all p<0.05). The diagnostic value of the signature was confirmed in a validation cohort of 40 lung cancer patients and 29 controls, independent of stage and histological type of lung tumor, and patients' age, sex, and smoking status (all p>0.05). The integration of the different categories of biomarkers might improve diagnosis of lung cancer.

Integrating Circulating Immunological and Sputum Biomarkers for the Early Detection of Lung Cancer

We have demonstrated that assessments of microRNA (miRNA) expressions in circulating peripheral blood mononucleated cell (PBMC) and sputum specimens, respectively, may help diagnose lung cancer. To assess the individual and combined analysis of the miRNAs across the different body fluids for lung cancer early detection, we analyse a panel of 3 sputum miRNAs (miRs-21, 31, and 210) and a panel of 2 PBMC miRNAs (miRs-19b-3p and 29b-3p) in a discovery cohort of 68 patients with lung cancer and 66 cancer-free smokers. We find that integrating 2 sputum miRNAs (miRs-31 and 210) and 1 PBMC miRNA (miR-19b-3p) has higher sensitivity (86.8%) and specificity (92.4%) compared with the individual panels. The synergistic value of the integrated panel of 3 biomarkers is confirmed in a validation cohort, independent of stage and histological type of lung cancer, and patients' age, sex, and ethnicity. Integrating circulating immunological and sputum biomarkers could improve the early detection of lung cancer.

Abnormal DNA methylation may contribute to the progression of osteosarcoma

The identification of optimal methylation biomarkers to achieve maximum diagnostic ability remains a challenge. The present study aimed to elucidate the potential molecular mechanisms underlying osteosarcoma (OS) using DNA methylation analysis. Based on the GSE36002 dataset obtained from the Gene Expression Omnibus database, differentially methylated genes were extracted between patients with OS and controls using t-tests. Subsequently, hierarchical clustering was performed to segregate the samples into two distinct clusters, OS and normal. Gene Ontology (GO) and pathway enrichment analyses for differentially methylated genes were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein-protein interaction (PPI) network was established, followed by hub gene identification. Using the cut-off threshold of ≥0.2 average β-value difference, 3,725 unique CpGs (2,862 genes) were identified to be differentially methylated between the OS and normal groups. Among these 2,862 genes, 510 genes were differentially hypermethylated and 2,352 were differentially hypomethylated. The differentially hypermethylated genes were primarily involved in 20 GO terms, and the top 3 terms were associated with potassium ion transport. For differentially hypomethylated genes, GO functions principally included passive transmembrane transporter activity, channel activity and metal ion transmembrane transporter activity. In addition, a total of 10 significant pathways were enriched by differentially hypomethylated genes; notably, neuroactive ligand-receptor interaction was the most significant pathway. Based on a connectivity degree >90, 7 hub genes were selected from the PPI network, including neuromedin U (NMU; degree=103) and NMU receptor 1 (NMUR1; degree=103). Functional terms (potassium ion transport, transmembrane transporter activity, and neuroactive ligand-receptor interaction) and hub genes (NMU and NMUR1) may serve as potential targets for the treatment and diagnosis of OS.

Clinical Utility of Chromosomal Aneusomy in Individuals at High Risk of Lung Cancer

INTRODUCTION

Low-dose computed tomography screening for lung cancer has a high false-positive rate with frequent discovery of indeterminate pulmonary nodules. Noninvasive biomarkers are needed to reduce false positives and improve risk stratification. A retrospective longitudinal evaluation was performed to assess chromosomal aneusomy in sputum by fluorescence in situ hybridization (CA-FISH) in four nested case-control studies.

METHODS

Receiver operating characteristic analysis resulted in two grouped cohorts: a high-risk cohort (Colorado High-Risk Cohort and Colorado Nodule Cohort [68 case patients and 69 controls]) and a screening cohort (American College of Radiology Imaging Network/National Lung Screening Trial and Pittsburgh Lung Screening Study [97 case patients and 185 controls]). The CA-FISH assay was a four-target DNA panel encompassing the EGFR and v-myc avian myelocytomatosis viral oncogene homolog (MYC) genes, and the 5p15 and centromere 6 regions or the fibroblast growth factor 1 gene (FGFR1) and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha gene (PIK3CA). A four-category scale (normal, probably normal, probably abnormal, and abnormal) was applied. Sensitivity, specificity, and positive and negative likelihood ratios (LRs) (with 95% confidence intervals [CIs]) were estimated for each cohort.

RESULTS

Sensitivity and specificity were, respectively, 0.67 (95% CI: 0.55-0.78) and 0.94 (95% CI: 0.85-0.98) for high-risk participants and 0.20 (95% CI: 0.13-0.30) and 0.84 (95% CI: 0.78-0.89) for screening participants. The positive and negative LRs were, respectively, 11.66 (95% CI: 4.44-30.63) and 0.34 (95% CI: 0.24-0.48) for high-risk participants and 1.36 (95% CI: 0.81-2.28) and 0.93 (95% CI: 0.83-1.05) for screening participants.

CONCLUSION

The high positive LR of sputum CA-FISH indicates that it could be a useful adjunct to low-dose computed tomography for lung cancer in high-risk settings. For screening, however, its low positive LR limits clinical utility. Prospective assessment of CA-FISH in the incidentally identified indeterminate nodule setting is ongoing in the Colorado Pulmonary Nodule Biomarker Trial.

A prediction model for distinguishing lung squamous cell carcinoma from adenocarcinoma

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

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma

INTRODUCTION

Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

Analysis of small nucleolar RNAs in sputum for lung cancer diagnosis

Molecular analysis of sputum presents a noninvasive approach for diagnosis of lung cancer. We have shown that dysregulation of small nucleolar RNAs (snoRNAs) plays a vital role in lung tumorigenesis. We have also identified six snoRNAs whose changes are associated with lung cancer. Here we investigated if analysis of the snoRNAs in sputum could provide a potential tool for diagnosis of lung cancer. Using qRT-PCR, we determined expressions of the six snoRNAs in sputum of a training set of 59 lung cancer patients and 61 cancer-free smokers to develop a biomarker panel, which was validated in a testing set of 67 lung cancer patients and 69 cancer-free smokers for the diagnostic performance. The snoRNAs were robustly measurable in sputum. In the training set, a panel of two snoRNA biomarkers (snoRD66 and snoRD78) was developed, producing 74.58% sensitivity and 83.61% specificity for identifying lung cancer. The snoRNA biomarkers had a significantly higher sensitivity (74.58%) compared with sputum cytology (45.76%) (P < 0.05). The changes of the snoRNAs were not associated with stage and histology of lung cancer (All P >0.05). The performance of the biomarker panel was confirmed in the testing cohort. We report for the first time that sputum snoRNA biomarkers might be useful to improve diagnosis of lung cancer.

Integrating DNA methylation and microRNA biomarkers in sputum for lung cancer detection

Background

Abnormal microRNA (miRNA) expressions and promoter methylation of genes detected in sputum may provide biomarkers for non-small lung cancer (NSCLC). Here, we evaluate the individual and combined analysis of the two classes of sputum molecular biomarkers for NSCLC detection.

Results

We analyze expression of 3 miRNAs (miR-21, miR-31, and miR-210) and methylation of 3 genes (RASSF1A, PRDM14, and 3OST2), which were previously identified as potential biomarkers for NSCLC, in sputum of a set of 117 stage I NSCLC patients and 174 cancer-free smokers. The results are validated in a different set of 144 stage I NSCLC patients and 171 controls. The panel of 3 miRNA biomarkers has 81.5 % sensitivity and 85.9 % specificity; the panel of 3 methylation biomarkers displays 82.9 % sensitivity and 76.4 % specificity for NSCLC detection. Integrated analysis of 2 miRNAs (miR-31 and miR-210) and 2 genes (RASSF1A and 3OST2) yields higher sensitivity (87.3 %) and specificity (90.3 %) compared with the individual panels of the biomarkers (P < 0.05). Combined analysis of all the 3 miRNAs and 3 genes does not have performance superior to that of the panel of 2 miRNAs and 2 genes (P > 0.05). The performance of combined use of the two classes of biomarkers was confirmed in the validation set.

Conclusions

The integration of two different classes of biomarkers synergistically improves both the sensitivity and the specificity for the early detection of NSCLC.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-016-0275-5) contains supplementary material, which is available to authorized users.

Huntingtin-Interacting Protein-1 Is an Early-Stage Prognostic Biomarker of Lung Adenocarcinoma and Suppresses Metastasis via Akt-mediated Epithelial-Mesenchymal Transition

RATIONALE

Non-small cell lung cancer (NSCLC) carries a poor survival rate mainly because of metastasis. However, the molecular mechanisms that govern NSCLC metastasis have not been described. Because huntingtin-interacting protein-1 (HIP1) is known to play a role in tumorigenesis, we tested the involvement of HIP1 in NSCLC progression and metastasis.

OBJECTIVES

HIP1 expression was measured in human NSCLC tumors, and correlation with survival outcome was evaluated. Furthermore, we investigated the ability of HIP1 to suppress metastasis. The molecular mechanism by which HIP1 contributes to suppress metastasis was investigated.

METHODS

We used tissue arrays containing samples from 121 patients with NSCLC to analyze HIP1 expression by immunohistochemistry. To investigate the role of HIP1 expression on metastasis, we evaluated cellular mobility, migration, and invasion using lung adenocarcinoma (AdCA) cells with modified HIP1 expression levels. The human disease mouse models with the same cells were applied to evaluate the HIP1 suppressing metastasis and its mechanism in vivo.

MEASUREMENTS AND MAIN RESULTS

HIP1 expression in AdCA progression was found to be an early-stage prognostic biomarker, with low expression correlated to poor prognosis. We also found HIP1 to be a metastatic suppressor in AdCA. HIP1 significantly repressed the mobility of lung cancer cells in vitro and in vivo and regulated the epithelial-mesenchymal transition by repressing AKT/glycogen synthase kinase-3β/β-catenin signaling.

CONCLUSIONS

HIP1 serves as an early-stage prognostic biomarker and a metastatic suppressor. Reduced expression during AdCA progression can relieve HIP1 suppression of Akt-mediated epithelial-mesenchymal transition and thereby lead to development of late metastases and poor prognosis.

Clinical potential of gene mutations in lung cancer

Lung cancer is the most common cancer type worldwide and the leading cause of cancer related deaths in the United States. The majority of newly diagnosed patients present with late stage metastatic lung cancer that is inoperable and resistant to therapies. High-throughput genomic technologies have made the identification of genetic mutations that promote lung cancer progression possible. Identification of the mutations that drive lung cancer provided new targets for non-small cell lung cancer (NSCLC) treatment and led to the development of targeted therapies such as tyrosine kinase inhibitors that can be used to combat the molecular changes that promote cancer progression. Development of targeted therapies is not the only clinical benefit of gene analysis studies. Biomarkers identified from gene analysis can be used for early lung cancer detection, determine patient’s prognosis and response to therapy, and monitor disease progression. Biomarkers can be used to identify the NSCLC patient population that would most benefit from treatment (targeted therapies or chemotherapies), providing clinicians tools that can be used to develop a personalized treatment plan. This review explores the clinical potential of NSCLC genetic studies on diagnosing and treating NSCLC.

Sputum microRNA biomarkers for identifying lung cancer in indeterminate solitary pulmonary nodules

PURPOSE

The early detection of lung cancer in heavy smokers by low-dose CT (LDCT) can reduce the mortality. However, LDCT screening increases the number of indeterminate solitary pulmonary nodules (SPN) in asymptomatic individuals, leading to overdiagnosis. Making a definitive preoperative diagnosis of malignant SPNs has been a clinical challenge. We have demonstrated that sputum miRNAs could provide potential biomarkers for lung cancer. Here, we aimed to develop sputum miRNA biomarkers for diagnosis of malignant SPNs.

EXPERIMENTAL DESIGN

Using quantitative RT-PCR, we evaluated expressions of 13 sputum miRNAs, previously identified sputum miRNA signatures of lung cancer, in a training set of 122 patients with either malignant (n = 60) or benign SPNs (n = 62) to define a panel of biomarkers. We then validated the biomarker panel in an internal testing set of 136 patients with either malignant (n = 67) or benign SPNs (n = 69), and an external testing cohort of 155 patients with either malignant (n = 76) or benign SPNs (n = 79).

RESULTS

In the training set, a panel of three miRNA biomarkers (miRs21, 31, and 210) was developed, producing 82.93% sensitivity and 87.84% specificity for identifying malignant SPNs. The sensitivity and specificity of the biomarkers in the two independent testing cohorts were 82.09% and 88.41%, 80.52% and 86.08%, respectively, confirming the diagnostic value.

CONCLUSIONS

Sputum miRNA biomarkers may improve LDCT screening for lung cancer in heavy smokers by preoperatively diagnosing malignant SPNs. Nevertheless, a prospective study in a large population to validate the biomarkers is needed.

Analysis of Lung Flute-collected Sputum for Lung Cancer Diagnosis

Molecular analysis of sputum can help diagnose lung cancer. We have demonstrated that Lung Flute can be used to collect sputum from individuals who cannot spontaneously expectorate sputum. The objective of this study is to further evaluate the performance of the Lung Flute by comparing the characteristics of parallel samples collected with and without the Lung Flute and the usefulness for diagnosis of lung cancer. Fifty-six early-stage lung cancer patients (40 current smokers and 16 former smokers) and 73 cancer-free individuals (52 current smokers and 21 former smokers) were instructed to spontaneously cough and use Lung Flute for sputum sampling. Sputum cytology and polymerase chain reaction analysis of three miRNAs (miRs-21, 31, and 210) were performed in the specimens. All 92 current smokers and 11 (28.7%) of 37 former smokers spontaneously expectorated sputum and also produced sputum when using the Lung Flute. Twenty-seven former smokers (70.3%) who could not spontaneously expectorate sputum, however, were able to produce sputum when using the Lung Flute. The specimens were of low respiratory origin without contamination from other sources, eg, saliva. There was no difference of sputum volume and cell populations, diagnostic efficiency of cytology, and analysis of the miRNAs in the specimens collected by the two approaches. Analysis of the sputum miRNAs produced 83.93% sensitivity and 87.67% specificity for identifying lung cancer. Therefore, sputum collected by the Lung Flute has comparable features as spontaneously expectorated sputum. Using the Lung Flute enables former smokers who cannot spontaneously expectorate to provide adequate sputum to improve sputum collection for lung cancer diagnosis.

Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)

Background

DNA methylation was suggested as the promising biomarker for lung cancer diagnosis. However, it is a great challenge to search for the optimal combination of methylation biomarkers to obtain maximum diagnostic performance.

Results

In this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency for non-small cell lung cancer (NSCLC) in a large Chinese Han NSCLC retrospective cohort. Three high-throughput DNA methylation microarray datasets (458 samples) were collected in the discovery stage. After normalization, batch effect elimination and integration, significantly differentially methylated genes and the best combination of the biomarkers were determined by the leave-one-out SVM (support vector machine) feature selection procedure. Then, candidate promoters were examined by the methylation status determined single nucleotide primer extension technique (MSD-SNuPET) in an independent set of 150 pairwise NSCLC/normal tissues. Four statistical models with fivefold cross-validation were used to evaluate the performance of the discriminatory algorithms. The sensitivity, specificity and accuracy were 86.3%, 95.7% and 91%, respectively, in Bayes tree model. The logistic regression model incorporated five gene methylation signatures at AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, adjusted for age, sex and smoking, showed robust performances in which the sensitivity, specificity, accuracy, and area under the curve (AUC) were 78%, 97%, 87%, and 0.91, respectively.

Conclusions

In summary, a high-throughput DNA methylation microarray dataset followed by batch effect elimination can be a good strategy to discover optimal DNA methylation diagnostic panels. Methylation profiles of AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, could be an effective methylation-based assay for NSCLC diagnosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-014-0035-3) contains supplementary material, which is available to authorized users.

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.

Analysis of MicroRNAs in sputum to improve computed tomography for lung cancer diagnosis

INTRODUCTION

Computed tomography (CT) plays a central role in lung cancer diagnosis. However, CT has relatively low specificity, presenting a challenge in clinical settings. We previously identified 12 microRNAs (miRNAs) whose expressions in tumor tissues were associated with lung cancer.

METHODS

Using quantitative reverse transcriptase polymerase chain reaction, we aimed to identify miRNA biomarkers in sputum that could complement CT for diagnosis of lung cancer.

RESULTS

In a training set consisting of 66 lung cancer patients and 68 cancer-free smokers, 10 of the 12 miRNAs were differentially expressed between the cases and controls (p ≤ 0.01). From the miRNAs, a logistic regression model was built on the basis of miR-31 and miR-210, both of which had the best prediction for lung cancer, producing an area under receiver operating characteristic curve of 0.83. Combined use of the two miRNAs yielded 65.2% sensitivity and 89.7% specificity, CT had 93.9% sensitivity and 83.8% specificity for lung cancer diagnosis. Notably, combined analysis of the miRNA biomarkers and CT produced a higher specificity than does CT used alone (91.2% versus 83.8%; p < 0.05). The diagnostic performance of the biomarkers was confirmed in a testing set comprising 64 lung cancer patients and 73 cancer-free smokers.

CONCLUSION

The sputum miRNA biomarkers might be useful in improving CT for diagnosis of lung cancer, but further independent validation on an external and prospective cohort of patients is required.

Identification of ENO1 as a potential sputum biomarker for early-stage lung cancer by shotgun proteomics

BACKGROUND

Lung cancer is the leading cancer killer. Early detection will reduce the related deaths. The objective of this study was to identify potential biomarkers for early-stage lung cancer in sputum supernatant.

MATERIALS AND METHODS

Using shotgun proteomics, we detected changes in protein profiles that were associated with lung cancer by analyzing sputum supernatants from 6 patients with early-stage lung cancer and 5 cancer-free controls. Using western blotting, we validated the proteomic results in 22 lung cancer cases and 22 controls. Using enzyme-linked immunosorbent assay (ELISA), we evaluated the diagnostic performance of the biomarker candidates in an independent set of 35 cases and 36 controls.

RESULTS

Proteomics identified 8 biomarker candidates for lung cancer. Western blotting validation of the candidates showed that enolase 1 (ENO1) displayed a higher expression level in patients with cancer than in cancer-free individuals (P = .015). ELISA revealed that the assessment of ENO1 expression in sputum supernatant had 58.33% sensitivity and 80.00% specificity in distinguishing patients with stage I lung cancer from cancer-free individuals.

CONCLUSION

The analysis of protein biomarkers in sputum may provide a potential approach for the early detection of lung cancer. Future validation of all the candidates defined by shotgun proteomics in a large cohort study may help develop additional biomarkers that can be added to ENO1 to provide more diagnostic efficacy for lung cancer.

Digital PCR quantification of miRNAs in sputum for diagnosis of lung cancer

PURPOSE

MicroRNAs (miRNAs) play important roles in the initiation and progression of lung cancer. Measuring miRNA expression levels in sputum could provide a potential approach for the diagnosis of lung cancer. The emerging digital PCR is a straightforward technique for precise, direct, and absolute quantification of nucleic acids. The objective of the study was to investigate whether digital PCR could be used to quantify miRNAs in sputum for lung cancer diagnosis.

METHODS

We first determined and compared dynamic ranges of digital PCR and conventional quantitative reverse transcriptase PCR (qRT-PCR) for miRNA quantification using RNA isolated from sputum of five healthy individuals. We then used digital PCR to quantify copy number of two lung cancer-associated miRNAs (miR-31 and miR-210) in 35 lung cancer patients and 40 cancer-free controls.

RESULTS

Copy number of the miRNAs measured by digital PCR displayed a linear response to input cDNA amount in a twofold dilution series over seven orders of magnitude. miRNA quantification determined by digital PCR assay was in good agreement with that obtained from qRT-PCR analysis in sputum. Furthermore, combined quantification of miR-31 and miR-210 copy number by using digital PCR in sputum of the cases and controls provided 65.71 % sensitivity and 85.00 % specificity for lung cancer diagnosis.

CONCLUSION

As digital PCR becomes more established, it would be a robust tool for quantitative assessment of miRNA copy number in sputum for lung cancer diagnosis.

A novel in silico reverse-transcriptomics-based identification and blood-based validation of a panel of sub-type specific biomarkers in lung cancer

Lung cancer accounts for the highest number of cancer-related deaths worldwide. Early diagnosis significantly increases the disease-free survival rate and a large amount of effort has been expended in screening trials and the development of early molecular diagnostics. However, a gold standard diagnostic strategy is not yet available. Here, based on miRNA expression profile in lung cancer and using a novel in silico reverse-transcriptomics approach, followed by analysis of the interactome; we have identified potential transcription factor (TF) markers that would facilitate diagnosis of subtype specific lung cancer. A subset of seven TF markers has been used in a microarray screen and was then validated by blood-based qPCR using stage-II and IV non-small cell lung carcinomas (NSCLC). Our results suggest that overexpression of HMGA1, E2F6, IRF1, and TFDP1 and downregulation or no expression of SUV39H1, RBL1, and HNRPD in blood is suitable for diagnosis of lung adenocarcinoma and squamous cell carcinoma sub-types of NSCLC. Here, E2F6 was, for the first time, found to be upregulated in NSCLC blood samples. The miRNA-TF-miRNA interaction based molecular mechanisms of these seven markers in NSCLC revealed that HMGA1 and TFDP1 play vital roles in lung cancer tumorigenesis. The strategy developed in this work is applicable to any other cancer or disease and can assist in the identification of potential biomarkers.

Two panels of plasma microRNAs as non-invasive biomarkers for prediction of recurrence in resectable NSCLC

The diagnosis of non-small cell lung carcinoma (NSCLC) at an early stage, as well as better prediction of outcome remains clinically challenging due to the lack of specific and robust non-invasive markers. The discovery of microRNAs (miRNAs), particularly those found in the bloodstream, has opened up new perspectives for tumor diagnosis and prognosis. The aim of our study was to determine whether expression profiles of specific miRNAs in plasma could accurately discriminate between NSCLC patients and controls, and whether they are able to predict the prognosis of resectable NSCLC patients. We therefore evaluated a series of seventeen NSCLC-related miRNAs by quantitative real-time (qRT)-PCR in plasma from 52 patients with I-IIIA stages NSCLC, 10 patients with chronic obstructive pulmonary disease (COPD) and 20-age, sex and smoking status-matched healthy individuals. We identified an eleven-plasma miRNA panel that could distinguish NSCLC patients from healthy subjects (AUC = 0.879). A six-plasma miRNA panel was able to discriminate between NSCLC patients and COPD patients (AUC = 0.944). Furthermore, we identified a three-miRNA plasma signature (high miR-155-5p, high miR-223-3p, and low miR-126-3p) that significantly associated with a higher risk for progression in adenocarcinoma patients. In addition, a three-miRNA plasma panel (high miR-20a-5p, low miR-152-3p, and low miR-199a-5p) significantly predicted survival of squamous cell carcinoma patients. In conclusion, we identified two plasma miRNA expression profiles that may be useful for predicting the outcome of patients with resectable NSCLC.

A proteomic approach to identification of plutonium-binding proteins in mammalian cells

Plutonium can enter the body through different routes and remains there for decades; however its specific biochemical interactions are poorly defined. We, for the first time, have studied plutonium-binding proteins using a metalloproteomic approach with rat PC12 cells. A combination of immobilized metal ion chromatography, 2D gel electrophoresis, and mass spectrometry was employed to analyze potential plutonium-binding proteins. Our results show that several proteins from PC12 cells show affinity towards Pu(4+)-NTA (plutonium bound to nitrilotriacetic acid). Proteins from seven different spots in the 2D gel were identified. In contrast to the previously known plutonium-binding proteins transferrin and ferritin, which bind ferric ions, most identified proteins in our experiment are known to bind calcium, magnesium, or divalent transition metal ions. The identified plutonium interacting proteins also have functional roles in downregulation of apoptosis and other pro-proliferative processes. MetaCore™ analysis based on this group of proteins produced a pathway with a statistically significant association with development of neoplastic diseases.

Genetic variants associated with the risk of chronic obstructive pulmonary disease with and without lung cancer

Chronic obstructive pulmonary disease (COPD) is a strong risk factor for lung cancer. Published studies about variations of genes encoding glutathione metabolism, DNA repair, and inflammatory response pathways in susceptibility to COPD were inconclusive. We evaluated 470 single-nucleotide polymorphisms (SNP) from 56 genes of these three pathways in 620 cases and 893 controls to identify susceptibility markers for COPD risk, using existing resources. We assessed SNP- and gene-level effects adjusting for sex, age, and smoking status. Differential genetic effects on disease risk with and without lung cancer were also assessed; cumulative risk models were established. Twenty-one SNPs were found to be significantly associated with risk of COPD (P < 0.01); gene-based analyses confirmed two genes (GCLC and GSS) and identified three additional genes (GSTO2, ERCC1, and RRM1). Carrying 12 high-risk alleles may increase risk by 2.7-fold; eight SNPs altered COPD risk without lung cancer by 3.1-fold and 4 SNPs altered the risk with lung cancer by 2.3-fold. Our findings indicate that multiple genetic variations in the three selected pathways contribute to COPD risk through GCLC, GSS, GSTO2, ERCC1, and RRM1 genes. Functional studies are needed to elucidate the mechanisms of these genes in the development of COPD, lung cancer, or both.

Small nucleolar RNA 42 acts as an oncogene in lung tumorigenesis

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death, reflecting the need for better understanding the oncogenesis, and developing new diagnostic and therapeutic targets for the malignancy. Emerging evidence suggests that small nucleolar RNAs (snoRNAs) have malfunctioning roles in tumorigenesis. Our recent study demonstrated that small nucleolar RNA 42 (SNORA42) was overexpressed in lung tumors. Here, we investigate the role of SNORA42 in tumorigenesis of NSCLC. We simultaneously assess genomic dosages and expression levels of SNORA42 and its host gene, KIAA0907, in 10 NSCLC cell lines and a human bronchial epithelial cell line. We then determine in vitro functional significance of SNORA42 in lung cancer cell lines through gain- and loss-of-function analyses. We also inoculate cancer cells with SNORA42-siRNA into mice through either tail vein or subcutaneous injection. We finally evaluate expression level of SNORA42 on frozen surgically resected lung tumor tissues of 64 patients with stage I NSCLC by using quantitative reverse transcriptase PCR assay. Genomic amplification and associated high expression of SNORA42 rather than KIAA0907 are frequently observed in lung cancer cells, suggesting that SNORA42 overexpression is activated by its genomic amplification. SNORA42 knockdown in NSCLC cells inhibits in vitro and in vivo tumorigenicity, whereas enforced SNORA42 expression in bronchial epitheliums increases cell growth and colony formation. Such pleiotropy of SNORA42 suppression could be achieved at least partially through increased apoptosis of NSCLC cells in a p53-dependent manner. SNORA42 expression in lung tumor tissue specimens is inversely correlated with survival of NSCLC patients. Therefore, SNORA42 activation could have an oncogenic role in lung tumorigenesis and provide potential diagnostic and therapeutic targets for the malignancy.