Diagnostic Biomarker For Non-small Cell Lung Cancer Research Articles

Serum Splicing Factor Proline- and Glutamine-Rich Is a Diagnostic Marker for Non-Small-Cell Lung Cancer and Other Solid Cancers.

Cancer markers are measurable molecules in blood or tissues that are produced by tumor cells or immune cells in response to cancer progression. They play an important role in clinical diagnosis, prognosis, and therapy monitoring. Splicing factor proline- and glutamine-rich (SFPQ) plays an important role in cancer growth and metastasis. SFPQ is not only more highly expressed in non-small-cell lung cancer (NSCLC) cells than it is in controls, but also highly expressed in cancer cells in patients with other solid cancers. Thus, a new enzyme-linked immunosorbent assay (ELISA) for detecting SFPQ was developed, in which the SFPQ protein is trapped by the first specific mAb coated on a microplate, and then recognized by a second specific mAb. This assay allows for the specific detection of SFPQ in the serum of patients with solid cancer. Regarding NSCLC, the serum SFPQ levels distinguished the non-cancer controls from the patients with NSCLC, with an area under the curve of 0.876, a sensitivity of 87%, and a specificity of 94%. The serum SFPQ levels were significantly elevated in the patients with NSCLC or other solid cancers. In conclusion, serum SFPQ could be a promising novel diagnostic biomarker for NSCLC and other malignancies.

Deficiency of circ_0103809 Attenuates Non-small Cell Lung Cancer Malignant Progression by Controlling miR-153-3p/HDAC1 Network.

Circular RNAs are vital players in tumorigenesis. We held the purpose to investigate the role and mechanism of circ_0103809 in non-small cell lung cancer (NSCLC).The expressions of circ_0103809, miR-153-3p and HDAC1 mRNA were determined using quantitative real-time PCR assay, and HDAC1 protein was quantified using western blot analysis. MTT, EdU, flow cytometry, tube-formation, wound healing and tube-formation assays were conducted for functional analysis. The predicted relationship among circ_0103809, miR-153-3p and HDAC1 was ascertained using dual-luciferase analysis, RIP assay and pull-down analysis. Animal models were further constructed to realize circ_0103809's role in vivo.Circ_0103809 was upregulated NSCLC specimens, cells and serum-derived exosomes. Serum exosomal circ_0103809 had the potency to be a diagnostic biomarker for NSCLC. Circ_0103809 silencing inhibited NSCLC cell growth, metastasis and angiogenesis and triggered cell cycle arrest and apoptosis. Circ_0103809 deficiency also suppressed the growth of transplanted tumors. Circ_0103809 acted as the miR-153-3p sponge, and the biological effects of circ_0103809 knockdown were relieved by miR-153-3p inhibition. HDAC1 was directly targeted by miR-153-3p, and miR-153-3p enrichment inhibited NSCLC cell malignant phenotypes by sequestering HDAC1.Circ_0103809 knockdown repressed NSCLC malignant progression partly by regulating miR-153-3p/HDAC1 signaling.

Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer

This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and functional correlation analysis was performed. The machine learning algorithms were used to screen the potential biomarkers of NSCLC. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. The protein and mRNA expression levels of potential biomarkers were verified based on the Human Protein Atlas (HPA) database and qRT-PCR. CIBERSORT was used to evaluate the infiltration of immune cells in NSCLC tissues, and the correlation between potential biomarkers and infiltrated immune cell was analyzed. Finally, specific siRNAs were utilized to reduce the GDF10, NCKAP5, and RTKN2 expression in A549 and H1975 cells. The proliferation ability of A549 and H1975 cells was detected by MTT assay. A total of 848 upregulated DEGs and 1308 downregulated DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were mainly related to cell division. Disease ontology (DO) enrichment analysis showed that the diseases with these DEGs were mainly lung diseases, including NSCLC. In addition,three potential biomarkers were identified: GDF10, NCKAP5, and RTKN2. Immune cell infiltration analysis showed that resting NK cells, activated dendritic cells, and Tregs may be involved in the pathogenesis of NSCLC. Meanwhile, GDF10, NCKAP5, and RTKN2 were negatively correlated with Tregs and naïve B cells but were positively correlated with activated dendritic cells and resting NK cells. Immunohistochemical staining showed that the expression of GDF10, NCKAP5, and RTKN2 in the lung tissue of patients with NSCLC was lower than that of normal lung tissue. qRT-PCR also confirmed that the mRNA expression of three biomarkers in NSCLC cell lines A549 and H1975 were significantly lower than those in human normal lung epithelial cells BEAS-2B. An MTT assay showed that GDF10, NCKAP5, and RTKN2 knockdown significantly promoted the proliferation of A549 and H1975 cells. The in vitro experiments showed that GDF10, NCKAP5, and RTKN2 played the inhibitory effects on NSCLC cell lines proliferation. Hence, GDF10, NCKAP5, and RTKN2 can be used as diagnostic biomarkers for NSCLC.

Pyroptosis-Related Gene Model Predicts Prognosis and Immune Microenvironment for Non-Small-Cell Lung Cancer.

Non-small-cell lung cancer (NSCLC) has a high incidence and mortality worldwide. Moreover, it needs more accurate means for predicting prognosis and treatments. Pyroptosis is a novel form of cell death about inflammation which was highly related to the occurrence and development of tumors. Despite having some studies about pyroptosis-related genes (PRGs) and cancer, the correlation has not been explored enough between PRGs and immune in NSCLC. In this study, we constructed a PRG model by WGCNA to access the prognosis value PRGs have. The testing cohort (n = 464) with four datasets from the GEO database conducted a survival analysis to confirm the stability of the prognostic model. The risk score and age are examined as independent prognostic factors. Based on the PRGs, we found multiple pathways enriched in immune in NSCLC. Separating samples into three subtypes by consensus cluster analysis, Cluster 3 was identified as immune-inflamed phenotype with an optimistic prognostic outcome. A three-gene PRG signature (BNIP3, CASP9, and CAPN1) was identified, and BNIP3 was identified as the core gene. Knockdown of BNIP3 significantly inhibited the growth of H358 cells and induced pyroptosis. In conclusion, the model construction based on PRGs provides novel insights into the prediction of NSCLC prognosis, and BNIP3 can serve as a diagnostic biomarker for NSCLC.

A Novel Hypoxia-Related Gene Signature with Strong Predicting Ability in Non-Small-Cell Lung Cancer Identified by Comprehensive Profiling.

Background Non-small-cell lung cancer (NSCLC) is the most common malignant tumor among males and females worldwide. Hypoxia is a typical feature of the tumor microenvironment, and it affects cancer development. Circular RNAs (circRNAs) have been reported to sponge miRNAs to regulate target gene expression and play an essential role in tumorigenesis and progression. This study is aimed at identifying whether circRNAs could be used as the diagnostic biomarkers for NSCLC. Methods The heterogeneity of samples in this study was assessed by principal component analysis (PCA). Furthermore, the Gene Expression Omnibus (GEO) database was normalized by the affy R package. We further screened the differentially expressed genes (DEGs) and differentially expressed circular RNAs (DEcircRNAs) using the DEseq2 R package. Moreover, we analyzed the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment of DEGs using the cluster profile R package. Besides, the Gene Set Enrichment Analysis (GSEA) was used to identify the biological function of DEGs. The interaction between DEGs and the competing endogenous RNAs (ceRNA) network was detected using STRING and visualized using Cytoscape. Starbase predicted the miRNAs of target hub genes, and miRanda predicted the target miRNAs of circRNAs. The RNA-seq profiler and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Then, the variables were assessed by the univariate and multivariate Cox proportional hazard regression models. Significant variables in the univariate Cox proportional hazard regression model were included in the multivariate Cox proportional hazard regression model to analyze the association between the variables of clinical features. Furthermore, the overall survival of variables was determined by the Kaplan-Meier survival curve, and the time-dependent receiver operating characteristic (ROC) curve analysis was used to calculate and validate the risk score in NSCLC patients. Moreover, predictive nomograms were constructed and used to predict the prognostic features between the high-risk and low-risk score groups. Results We screened a total of 2039 DEGs, including 1293 upregulated DEGs and 746 downregulated DEGs in hypoxia-treated A549 cells. A549 cells treated with hypoxia had a total of 70 DEcircRNAs, including 21 upregulated and 49 downregulated DEcircRNAs, compared to A549 cells treated with normoxia. The upregulated genes were significantly enriched in 284 GO terms and 42 KEGG pathways, while the downregulated genes were significantly enriched in 184 GO terms and 25 KEGG pathways. Moreover, the function analysis by GSEA showed enrichment in the enzyme-linked receptor protein signaling pathway, hypoxia-inducible factor- (HIF-) 1 signaling pathway, and G protein-coupled receptor (GPCR) downstream signaling. Furthermore, six hub modules and 10 hub genes, CDC45, EXO1, PLK1, RFC4, CCNB1, CDC6, MCM10, DLGAP5, AURKA, and POLE2, were identified. The ceRNA network was constructed, and it consisted of 4 circRNAs, 14 miRNAs, and 38 mRNAs. The ROC curve was constructed and calculated. The area under the curve (AUC) value was 0.62, and the optimal threshold was 0.28. Based on the optimal threshold, the patients were divided into the high-risk score and low-risk score groups. The survival rate in the high-risk score group was lower than that in the low-risk score group. The expression of SERPINE1, STC2, and LPCAT1; clinical stage; and age of the patient were significantly correlated with the high-risk score. Moreover, nomograms were established based on the risk factors in multivariate analysis, and the median survival time, 3-year survival probability, and 5-year survival were possibly predicted according to nomograms. Conclusion The ceRNA network associated with NSCLC was identified, and the hub genes, circRNAs, might act as the potential biomarkers for NSCLC.

Study on plasma amino acids and piperonamide as potential diagnostic biomarkers of non-small cell lung cancer.

BackgroundThe value of plasma threonine, cysteine, and piperonamide as diagnostic biomarkers for non-small cell lung cancer (NSCLC) has been rarely explored. The lack of a validation set containing confounders is common to most previous metabolomics studies. The purpose of this study was to explore and validate the value of plasma amino acids and piperonamide as diagnostic biomarkers for NSCLC using liquid chromatography-tandem mass spectrometry (LC-MS/MS).MethodsA total of 250 participants were included in this study, including 167 patients with pathologically confirmed NSCLC and 83 healthy controls (HCs). These participants were divided into training set, validation set 1, and validation set 2 in chronological order and in a certain proportion. The plasma levels of 22 amino acids and 1 piperonamide in these pre-treatment NSCLC patients and HCs were measured by LC-MS/MS. Metabolic biomarkers were identified after multivariate analysis, univariate analysis, receiver operating characteristic (ROC) analysis. Furthermore, these biomarkers and transcriptomic data were subjected to joint pathway analysis.ResultsThe area under the ROC curve (AUC) values for threonine, piperonamide, arginine, alanine, cysteine, methionine, and histidine in the integrated data set were 0.911, 0.848, 0.909, 0.869, 0.786, 0.597 and 0.637, respectively. This panel composed of these 7 metabolites showed good diagnostic capability for NSCLC (the AUC of this diagnostic panel in each data set was greater than 0.9). The specificity of this diagnostic panel in validation set 2, which included confounders, was 0.970, similar to that of the other datasets. The presence of confounding factors had little effect on the diagnostic accuracy of this panel. The ROC analysis of this diagnostic panel between all stage I NSCLC patients and HCs showed AUC, sensitivity, and specificity of 1.000, 1.000, and 0.988, respectively. Moreover, PSAT1, SHMT2, AOC3, and MAOB were found to be involved in the metabolism of threonine and cysteine.ConclusionsPlasma amino acids and piperonamide have potential as diagnostic biomarkers in NSCLC. This metabolic biomarker panel appears useful for the diagnosis and screening of NSCLC. In addition, metabolomic and transcriptomic integration pathway analysis may help elucidate the mechanism of NSCLC occurrence and development and even reveal new treatment vulnerabilities.

Serum exosomal hsa_circ_0069313 has a potential to diagnose more aggressive non-small cell lung cancer

BackgroundCircular RNAs (circRNAs) derived from exosomes are involved in the carcinogenesis and development of non-small cell lung cancer (NSCLC), showing great potential to be diagnostic biomarkers for NSCLC. MethodsSerum exosomes were isolated with an exosome isolation kit, and verified by western blot, transmission electron microscopy and a potentiometric analyzer. Five differentially expressed exosomal circRNAs, including hsa_circ_0069313, hsa_circ_0063526, hsa_circ_0010522, hsa_circ_0048677 and hsa_circ_0001946, were selected based on the circRNA array analyses and the published documents in Pubmed. The serum and serum exosomal levels of the above five circRNAs were quantified by qRT-PCR. The diagnostic power of serum and serum exosomal hsa_circ_0069313 was evaluated by receiver operating characteristic (ROC) test. ResultsThe levels of hsa_circ_0069313 in serum exosomes were statistically lower than those in the matched serum samples. In contrast, the levels of hsa_circ_0063526, hsa_circ_0010522, hsa_circ_0048677 and hsa_circ_0001946 showed no statistical difference in the sera and serum exosomes of healthy donors. The levels of serum and serum exosomal hsa_circ_0069313 were notably elevated in the NSCLC group compared to the healthy, pneumonia and benign lung tumor groups. Furthermore, serum and serum exosomal hsa_circ_0069313 could differ benign lung tumor and NSCLC with AUC values of 0.803 and 0.749, respectively. Intriguingly, the higher levels of serum exosomal hsa_circ_0069313 were associated with stage III-IV, lymph node metastasis and distant metastasis of NSCLC. ConclusionsSerum and serum exosomal hsa_circ_0069313 have the potential to discriminate NSCLC and benign lung tumor. The higher levels of serum exosomal hsa_circ_0069313 are linked to more aggressive pathological features of NSCLC.

Plasma SNORD83A as a potential biomarker for early diagnosis of non-small-cell lung cancer.

Aim: This study aimed to access the efficacy of plasma small nucleolar RNAs in early diagnosis of non-small-cell lung cancer (NSCLC). Methods: SNORD83A was selected based on databases and further verified in 48 paired formalin-fixed, paraffin-embeddedtissues, as well as in plasma from 150 NSCLC patients and 150 healthy donors. The diagnostic efficiency of plasma SNORD83A, as well as in combinationwith carcinoembryonic antigen, was determined by receiver operating characteristic analysis. Results: SNORD83A was significantly increased not only in tissues but also in plasma from NSCLC patients compared with those from healthy donors. Plasma SNORD83A wasable to act as adiagnostic biomarker for NSCLC. The diagnostic efficiency of carcinoembryonic antigen was alsosignificantly elevatedfor early-stage NSCLC when combined with SNORD83A. Conclusion: SNORD83A can serve as adiagnostic biomarker for NSCLC.

Abstract 3126: Serum miR-4687-3p as the diagnostic biomarker for NSCLC

Abstract Objective: The lack of useful biomarker contributes to the increased morbidity and mortality of non-small cell lung cancer (NSCLC) partly. However, biomarkers in blood have become increasingly appreciated in diagnosis of NSCLC. This study, we aimed to identify serum miRNAs for diagnosing NSCLC. Methods: Microarray were used to detect 2549 miRNAs in serum from NSCLC patients (n=10) and healthy individuals (n=10) and gain differentially expressed miRNAs. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) assay were applied to validate the expression of selected miRNAs in validation set consisting of sera from 60 participants. Area under the receiver operating characteristic curve (AUC) was used to evaluate diagnostic accuracy of the chosen miRNAs. Tissue expression of the selected miRNA was analyzed based on TCGA database. Subsequently, the target gene of the miRNAs were predicted by TargetScan and Gene ontology (GO) and KEGG pathway enrichment analysis tested by R (clusterProfiler package). The effect of miR-4687-3p on proliferation, invasion, and metastasis of lung cancer cells were investigated through CCK-8 and Transwell assay. Results: We identified serum miR-4687-3p that provided a high diagnostic accuracy of NSCLC (AUC=0.69, 95%CI: 0.543-0.815) in validation data set. According to TCGA database, we also found that the tissue miR-4687-3p level were significantly higher in NSCLC tissues than normal tissues (p<0.05). GO and KEGG pathway enrichment analysis showed that postsynaptic specialization and TGF-β signaling pathway were significantly enriched. Up-regulated miR-4687-3p by miR-4687-3p mimic could promote the proliferation, invasion, and metastasis of the NSCLC cells, compared with mimic negative control. Meanwhile, applying miR-4687-3p inhibitor could suppressed the proliferation, invasion, and metastasis of the NSCLC cells. Conclusion: Our study on the first reported that serum miR-4687-3p levels may have clinical potentials as a novel non-invasive diagnostic biomarker for NSCLC patients. Key words: NSCLC, miR-4687-3p, microarray, bioinformatics, biomarker Citation Format: Man Liu, Jun Ouyang, Qiufang Si, Yulin Wang, Ting Yang, Xue Zhang, Di Jiang, Jianying Zhang, Liping Dai. Serum miR-4687-3p as the diagnostic biomarker for NSCLC [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3126.

<p>Plasma Long Non-Coding RNA RP11-438N5.3 Level for Non-Small Cell Lung Cancer Diagnosis [Letter]</p>

Plasma Long Non-Coding RNA RP11-438N5.3 Level for Non-Small Cell Lung Cancer Diagnosis [Letter] Chun-Qiu Yang,1 Guo-Ming Zhang2 1Department of Laboratory Medicine, Taihe County People’s Hospital, Fuyang 236600, People’s Republic of China; 2Department of Laboratory Medicine, Shuyang People’s Hospital, Shuyang Hospital Affiliated to Xuzhou Medical University, Shuyang 223600, People’s Republic of ChinaCorrespondence: Guo-Ming ZhangDepartment of Laboratory Medicine, Shuyang People’s Hospital, The Affiliated Shuyang Hospital of Xuzhou Medical University, Shuyang 223600, People’s Republic of ChinaEmail gm@xzhmu.edu.cn Chen et al1 published an article entitled “Plasma Long Non-Coding RNA RP11-438N5.3 as a Novel Biomarker for Non-Small Cell Lung Cancer” in Cancer management and research. To evaluate the diagnostic efficiency of Plasma level of RP11-438N5.3 for non-small-cell lung cancer (NCLC), the investigators enrolled 69 NCLC patients and 69 healthy controls in this study. Plasma level of RP11-438N5.3 was determined using quantitative reverse transcription PCR (qRT-PCR), and receiver operating characteristic (ROC) curve analysis was assessed to determine the diagnostic performance of Plasma level of RP11-438N5.3 level in NCLC.They found that Plasma level of RP11-438N5.3 level was significantly lower in NCLC patients than healthy controls and the area under ROC curve (AUC) is 0.814. Therefore, they concluded that the Plasma level of RP11-438N5.3 was a novel diagnostic biomarker for NCLC. View the original paper by Chen and colleagues

Cyclin-dependent kinase 6 (CDK6) is a candidate diagnostic biomarker for early non-small cell lung cancer

BackgroundCyclin-dependent kinase 6 (CDK6) is an important regulatory protein of the cell cycle and plays an important role in tumor progression. The aim of this study was to investigate the expression of CDK6 in T1 stage non-small cell lung cancer (NSCLC) and to explore the association of CDK6 with the clinicopathological features of the disease.MethodsCDK6 expression was analyzed by real-time PCR (RT-PCR) and immunohistochemistry (IHC) in tumor tissue samples and the distal normal tissue samples from 56 T1 stage NSCLC patients. The correlation between CDK6 expression and clinicopathological features was analyzed using the independent samples t-test and nonparametric tests.ResultsWe found CDK6 had a tendency to increase in tumor tissues compared to normal tissues at the transcriptional level (P=0.073). Moreover, the expression of CDK6 protein in NSCLC tissues was also significantly higher than in normal lung tissues (P=0.003). With an increase of smoking quantity, the expression of CDK6 mRNA was increased (P=0.009). Remarkably, CDK6 expression was increased in squamous cell carcinoma (SCC) tissues but decreased in adenocarcinoma (AD) tissues at both the transcription and protein levels (P<0.001). After stratification based on pathological type, CDK6 gene expression was not associated with any clinicopathological features in SCC, while it was negatively associated with tumor diameter in AD (P=0.049).ConclusionsTaken together, these results indicated that abnormal expression of the CDK6 gene in NSCLC might be associated with pathological type, which may serve as a diagnostic biomarker for NSCLC.

Clinically Correlated MicroRNAs in the Diagnosis of Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.

(1) Background. Non-small cell lung cancer (NSCLC) has a high mortality rate. MiRNAs have been found to be diagnostic biomarkers for NSCLC. However, controversial results exist. We conducted this meta-analysis to evaluate the diagnostic value of miRNAs for NSCLC. (2) Methods. Databases and reference lists were searched. Pooled sensitivity (SEN), specificity (SPE), and area under the curve (AUC) were applied to examine the general diagnostic efficacy, and subgroup analysis was also performed. (3) Results. Pooled SEN, SPE, and AUC were 85%, 88%, and 0.93, respectively, for 71 studies. Multiple miRNAs (AUC: 0.96) obtained higher diagnostic value than single miRNA (AUC: 0.86), and the same result was found for Caucasian population (AUC: 0.97) when compared with Asian (AUC: 0.91) and Caucasian/African population (AUC: 0.92). MiRNA had higher diagnostic efficacy when participants contained both smokers and nonsmokers (AUC is 0.95 for imbalanced group and 0.91 for balanced group) than when containing only smokers (AUC: 0.90). Meanwhile, AUC was 0.91 for both miR-21 and miR-210. (4) Conclusions. Multiple miRNAs such as miR-21 and miR-210 could be used as diagnostic tools for NSCLC, especially for the Caucasian and nonsmoking NSCLC.

P3.05-003 Serum Thioredoxin Reductase 1 as a Diagnostic Biomarker for Non-Small Cell Lung Cancer

Non-invasive diagnostic biomarkers for patients with suspicious non-small cell lung cancer (NSCLC) may provide needed guidance on invasive diagnostic and therapeutic decisions. Thioredoxin reductase 1 (TrxR1) is a pivotal intracellular redox sensor and antioxidant enzyme, and plays an important part in tumor growth, progression, metastasis, and chemotherapy resistance. The goal of this study is to test the feasibility of developing plasma TrxR1 as a novel diagnostic biomarker for NSCLC.

Diagnosis value of serum soluble B7-H4 expression in non-small cell lung cancer.

B7-H4, a member of the inhibitory B7 family, can restrain T cell proliferation, activation, cytokine secretion, and may be involved in immune evasion in cancer patients. This aim of the study was to determine the expression level of soluble B7-H4 (sB7-H4) in circulation and to subsequently evaluate the clinical significance of circulating sB7-H4 in patients with non-small cell lung cancer (NSCLC). Serum specimens from 128 patients with NSCLC, 100 healthy volunteers (HV), and 80 patients with benign lung diseases (BLD) were collected. The concentrations of sB7-H4 were measured by sandwich enzyme-linked immunosorbent assay. Serum sB7-H4 levels in patients with NSCLC were significantly higher than those in patients with BLD (P < 0.05), or those in HV (P < 0.05). Using a cutoff of 27.8 ng/mL, the sensitivity and specificity of sB7-H4 in differentiating between patients with NSCLC and patients with BLD, and between patients with NSCLC and HV was, 46.9% and 92.5%, and 54.7% and 95.0%, respectively. An area under the curve (AUC) for NSCLC resulting from sB7-H4 (0.863), which was significantly better than any other tumour markers tested including CA125 (0.763), and CEA (0.775). In conclusion, assessment of serum sB7-H4 levels could be considered as a diagnostic biomarker for NSCLC.

MicroRNA-99a is downregulated and promotes proliferation, migration and invasion in non-small cell lung cancer A549 and H1299 cells.

There is increasing evidence that microRNAs (miRNAs) are able to play a key role in the diagnosis and therapy of cancer. miRNA-99a (miR-99a), which is downregulated in several human malignancies, has been reported as a potential tumor suppressor. However, to the best of our knowledge, the expression and function of miR-99a has not been investigated in human non-small cell lung cancer (NSCLC) at present. The aim of the current study was to evaluate the association between NSCLC and miR-99a. miR-99a expression was analyzed in 15 pairs of NSCLC and non-cancerous tissue samples by reverse transcription-quantitative polymerase chain reaction. In addition, the NSCLC A549 and H1299 cell lines were transfected with miR-99a mimics, and the effect of miR-99a on the cell cycle, cell proliferation, migration and colony formation of A549 and H1299 cells was investigated. It was found that the level of miR-99a expression was significantly downregulated in NSCLC tissues and that ectopic overexpression of miR-99a significantly inhibited the growth of A549 and H1299 cells. Additionally, ectopic overexpression of miR-99a inhibited A549 and H1299 cell migration and invasion by inhibiting epithelial to mesenchymal transition. The downregulation of insulin-like growth factor 1 receptor (IGF-1R) by miR-99a and knockdown of IGF-1R mediated by siRNA were each found to phenocopy the effect of miR-99a overexpression in NSCLC. To the best of our knowledge, the present study demonstrated for the first time that, in NSCLC, miR-99a is downregulated and thus regulates proliferation, colony formation and migration through the IGF-1R pathway, which indicates that miR-99a is a diagnostic biomarker for NSCLC.

Altered miR-143 and miR-150 expressions in peripheral blood mononuclear cells for diagnosis of non-small cell lung cancer

Background Sensitive and specific biomarkers for identifying early stage of non-small cell lung cancer (NSCLC) are urgently needed to improve the therapeutic outcome and reduce the mortality. Small non-coding microRNAs (miRNAs) are key components of cancer development and are considered as potential biomarkers for cancer diagnosis and for monitoring treatment. The aim of this study was to determine whether aberrant miRNA expression can be used as a marker in peripheral blood mononuclear cells (PBMC) for the diagnosis of NSCLC. Methods The levels of two mature miRNAs (miR-143 and miR-150) were detected by probe-based stem-loop quantitative reverse-transcriptase PCR (RT-qPCR) in PBMC of 64 patients with NSCLC and 26 healthy individuals, and the relationship between miR-143 and miR-150 levels and clinical and pathological factors was explored. Results All endogenous miRNAs were present in peripheral blood in a remarkably stable form and detected by RT-qPCR. MiR-143 expression in the PBMC specimens was significantly lower in NSCLC patients than in healthy individuals (P &lt;0.0001). MiR-150 expression in the PBMC specimens was not significantly different between NSCLC patients and healthy individuals (P=0.260). MiR-150 expression was significantly higher in lung adenocarcinoma patients than in healthy individuals (P=0.001). There was a very strong difference in the expression level of miR-150 between lung adenocarcinoma patients and lung squamous cell carcinoma patients (P &lt;0.0001). In receiver operating characteristic curve (ROC) analysis, low expression of miR-143 showed the area under the ROC (AUC) of 0.885 for distinguishing cancer patients from healthy subjects. High expression of miR-150 had an AUC of 0.834 for distinguishing lung adenocarcinoma patients from healthy subjects. High expression of miR-150 had an AUC of 0.951 for distinguishing lung adenocarcinoma from lung squamous cell carcinoma. The miR-150 level was significantly associated with distant metastasis (P=0.014). Conclusions It is indicated that there is a potential for using miR-143 as a novel diagnostic biomarker for NSCLC. Moreover, miR-150 can be a highly accurate marker for differentiating adenocarcinoma from squamous cell carcinoma.

Biomarkers in Exhaled Breath Condensate and Serum of Chronic Obstructive Pulmonary Disease and Non-Small-Cell Lung Cancer.

Chronic obstructive pulmonary disease (COPD) and lung cancer are leading causes of deaths worldwide which are associated with chronic inflammation and oxidative stress. Lung cancer, in particular, has a very high mortality rate due to the characteristically late diagnosis. As such, identification of novel biomarkers which allow for early diagnosis of these diseases could improve outcome and survival rate. Markers of oxidative stress in exhaled breath condensate (EBC) are examples of potential diagnostic markers for both COPD and non-small-cell lung cancer (NSCLC). They may even be useful in monitoring treatment response. In the serum, S100A8, S100A9, and S100A12 of the S100 proteins are proinflammatory markers. They have been indicated in several inflammatory diseases and cancers including secondary metastasis into the lung. It is highly likely that they not only have the potential to be diagnostic biomarkers for NSCLC but also prognostic indicators and therapeutic targets.

Diagnostic and prognostic role of plasma levels of two forms of cytokeratin 18 in patients with non-small-cell lung cancer

Purpose Cytokeratin 18 (CK18) can be used as a serum biomarker for carcinoma cell death, whereas caspase-cleaved (ccCK18) fragments reflect tumour apoptosis. We explored the potential diagnostic and prognostic role of circulating CK18 and ccCK18 in patients with non-small-cell lung cancer (NSCLC) in comparison with Cyfra 21.1, a fragment of cytokeratin 19. Methods Subject cohorts consisted of 200 healthy blood donors (HBD), 113 patients with benign lung diseases (BLD) and 179 NSCLC cases. Plasma levels of ccCK18, total CK18 and Cyfra 21.1 were determined with ELISA assays. Results Plasma levels of ccCK18 and total CK18 were higher in the NSCLC group compared to the HBD and BLD cohorts ( p < 0.0001). Using a cut-off of 104 U/L for ccCK18 and 302 U/L for total CK18 (95% specificity in the HBD group) the diagnostic accuracy of both CK18 forms to distinguish between NSCLC and BLD cases was 56%, whereas it was 94% for Cyfra 21.1. Multivariate survival analysis showed that total CK18 was a stronger prognostic factor than both ccCK18 and Cyfra 21.1 (HR 0.64 for low versus high total CK18 levels, 95% confidence interval (CI) 0.50–0.82; p = 0.0004) in the entire NSCLC cohort and in 78 patients with locally advanced or metastatic disease treated with chemoradiotherapy or first-line chemotherapy (HR 0.70 95% CI 0.52–0.94; p = 0.018). Conclusions Cyfra 21.1 is a useful diagnostic biomarker for NSCLC. Total CK18 shows a promising potential as prognostic marker in NSCLC patients, independently of the therapeutical intervention. In contrast, ccCK18 was not of prognostic value in NSCLC, suggesting that tumour necrosis is of particular importance in this disease.

A PROLIFERATION-INDUCING LIGAND: A NEW BIOMARKER FOR NON-SMALL CELL LUNG CANCER

To identify a proliferation-inducing ligand (APRIL) expression profile in tumor tissue and sputum of lung cancer, and evaluate the possibility of an assistant diagnosis of lung cancer by real-time fluorescence quantitative polymerase chain reaction (RTQ-PCR) in sputum as well, the authors analyzed the expression of APRIL mRNA in 75 tissue samples and 71 corresponding sputum samples of lung cancer by RTQ-PCR and analyzed their correlation. APRIL protein expression was also observed in tumor tissues by Western blot and immunohistochemistry. The expression analysis revealed APRIL expression was elevated in non-small cell lung cancer (NSCLC) and the expression of APRIL protein was located in the membrane and cytoplasm of tumor cells by immunohistochemiscal staining. Compared to benign pulmonary disease and healthy volunteers, the expression of APRIL mRNA in sputum of lung cancer was elevated (both P <. 001). When cut-off values for positivity were set at the mean + 2SD of mRNA expression in healthy volunteers, the positive rate for APRIL mRNA expression was 81.7% (58/71) in sputum samples of lung cancer, 3.2% (2/62) in benign pulmonary disease, and 1.5% (1/65) in healthy volunteers. The correlation was evident between the expression level of APRIL mRNA of tissue samples and that of sputum samples (P <. 001, r =. 702). These results support the possibility that the APRIL gene may play a key role in lung cancer, especially in NSCLC. The elevated expression level of APRIL mRNA in sputum of NSCLC suggested that APRIL mRNA may serve as an effective and convenient diagnostic biomarker for NSCLC.