Potential Biomarker For Lung Cancer Research Articles

Identifying the miRNA signature associated with survival time in patients with lung adenocarcinoma using miRNA expression profiles

Lung adenocarcinoma is a multifactorial disease. MicroRNA (miRNA) expression profiles are extensively used for discovering potential theranostic biomarkers of lung cancer. This work proposes an optimized support vector regression (SVR) method called SVR-LUAD to simultaneously identify a set of miRNAs referred to the miRNA signature for estimating the survival time of lung adenocarcinoma patients using their miRNA expression profiles. SVR-LUAD uses an inheritable bi-objective combinatorial genetic algorithm to identify a small set of informative miRNAs cooperating with SVR by maximizing estimation accuracy. SVR-LUAD identified 18 out of 332 miRNAs using 10-fold cross-validation and achieved a correlation coefficient of 0.88 ± 0.01 and mean absolute error of 0.56 ± 0.03 year between real and estimated survival time. SVR-LUAD performs well compared to some well-recognized regression methods. The miRNA signature consists of the 18 miRNAs which strongly correlates with lung adenocarcinoma: hsa-let-7f-1, hsa-miR-16-1, hsa-miR-152, hsa-miR-217, hsa-miR-18a, hsa-miR-193b, hsa-miR-3136, hsa-let-7g, hsa-miR-155, hsa-miR-3199-1, hsa-miR-219-2, hsa-miR-1254, hsa-miR-1291, hsa-miR-192, hsa-miR-3653, hsa-miR-3934, hsa-miR-342, and hsa-miR-141. Gene ontology annotation and pathway analysis of the miRNA signature revealed its biological significance in cancer and cellular pathways. This miRNA signature could aid in the development of novel therapeutic approaches to the treatment of lung adenocarcinoma.

The effects of segmentation algorithms on the measurement of 18F-FDG PET texture parameters in non-small cell lung cancer

BackgroundMeasures of tumour heterogeneity derived from 18-fluoro-2-deoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) scans are increasingly reported as potential biomarkers of non-small cell lung cancer (NSCLC) for classification and prognostication. Several segmentation algorithms have been used to delineate tumours, but their effects on the reproducibility and predictive and prognostic capability of derived parameters have not been evaluated. The purpose of our study was to retrospectively compare various segmentation algorithms in terms of inter-observer reproducibility and prognostic capability of texture parameters derived from non-small cell lung cancer (NSCLC) 18F-FDG PET/CT images.Fifty three NSCLC patients (mean age 65.8 years; 31 males) underwent pre-chemoradiotherapy 18F-FDG PET/CT scans. Three readers segmented tumours using freehand (FH), 40% of maximum intensity threshold (40P), and fuzzy locally adaptive Bayesian (FLAB) algorithms. Intraclass correlation coefficient (ICC) was used to measure the inter-observer variability of the texture features derived by the three segmentation algorithms. Univariate cox regression was used on 12 commonly reported texture features to predict overall survival (OS) for each segmentation algorithm. Model quality was compared across segmentation algorithms using Akaike information criterion (AIC).Results40P was the most reproducible algorithm (median ICC 0.9; interquartile range [IQR] 0.85–0.92) compared with FLAB (median ICC 0.83; IQR 0.77–0.86) and FH (median ICC 0.77; IQR 0.7–0.85). On univariate cox regression analysis, 40P found 2 out of 12 variables, i.e. first-order entropy and grey-level co-occurence matrix (GLCM) entropy, to be significantly associated with OS; FH and FLAB found 1, i.e., first-order entropy. For each tested variable, survival models for all three segmentation algorithms were of similar quality, exhibiting comparable AIC values with overlapping 95% CIs.ConclusionsCompared with both FLAB and FH, segmentation with 40P yields superior inter-observer reproducibility of texture features. Survival models generated by all three segmentation algorithms are of at least equivalent utility. Our findings suggest that a segmentation algorithm using a 40% of maximum threshold is acceptable for texture analysis of 18F-FDG PET in NSCLC.

Plasma N-acetylputrescine, cadaverine and 1,3-diaminopropane: potential biomarkers of lung cancer used to evaluate the efficacy of anticancer drugs.

Polyamines have been widely investigated as potential biomarkers for various types of cancers, including lung cancer, which is one of the most common causes of death from cancer worldwide. This study was carried out to evaluate the value of polyamines that serve as early diagnostic and cancer progression markers as well as drug evaluation for lung cancer (squamous cell carcinoma of lung, SCCL). SCCL was induced in Wistar rats by intratracheal instillation of 3-methylcholanthrene and treated with three different anti-cancer drugs, Aidi injections, fluorouracil, and a combination of them. After carcinogenesis for 28, 70 and 98 days and therapy for 28 and 56 days, the polyamine levels in plasma of SCCL, healthy and treated rats were determined using a UHPLC-MS/MS assay base on the means of targeted metabolomics. Results showed that increased N-acetylputrescine, cadaverine and 1,3-diaminopropane levels were associated with progression of SCCL. The levels of cadaverine and 1,3-diaminopropane returned to normal after administration of the three different kinds of anticancer drug. In addition, the suitability of using N-acetylputrescine, cadaverine and 1,3-diaminopropane as biomarkers was confirmed by PLS-DA and ROC analysis. It can provide an innovative and effective way for the clinical diagnosis, prevention and treatment of lung cancer, and stimulate a theoretical basis for the design and development of new anticancer drugs. At the same time, this increased the clinical options for polyamines as cancer biomarkers.

Single-cell RNA sequencing reveals an altered gene expression pattern as a result of CRISPR/cas9-mediated deletion of Gene 33/Mig6 and chronic exposure to hexavalent chromium in human lung epithelial cells

Gene 33 (Mig6, ERRFI1) is an adaptor protein with multiple cellular functions. We recently reported that depletion of this protein promotes lung epithelial cell transformation induced by hexavalent chromium [Cr(VI)]. However, the early molecular events that mediate this process are not clear. In the present study, we used single-cell RNA sequencing to compare gene expression profiles between BEAS-2B lung epithelial cells chronically exposed to a sublethal dose of Cr(VI) with or without CRISPR/cas9-mediated deletion of Gene 33. Our data reveal 83 differentially expressed genes. The most notable changes are genes associated with cell adhesion, oxidative stresses, protein ubiquitination, epithelial-mesenchymal transition/metastasis, and WNT signaling. Up-regulation of some neuro-specific genes is also evident, particularly ubiquitin carboxyl-terminal hydrolase L1 (UCHL1), a deubiquitinase and potential biomarker for lung cancer. Gene 33 deletion and/or Cr(VI) exposure did not cause discernable changes in cell morphology. However, Gene 33 deletion led to a modest but significant reduction of cells in the G2/M phase of the cell cycle regardless of Cr(VI) exposure. Gene 33 deletion also significantly reduced cell proliferation. Interestingly, Cr(VI) exposure eliminated the difference in cell proliferation between the two genotypes. Gene 33 deletion also significantly elevated cell migration. Our data indicate that combined Gene 33 deletion and chronic Cr(VI) exposure produces a gene expression pattern and a phenotype resemble those of the transformed lung epithelial cells. Given the known association of UCHL1 with lung cancer, we propose that UCHL1 is an important player in the early stage of lung epithelial cell transformation and tumorigenesis.

Abstract 5307: Analysis of volatile organic compounds for the diagnosis of lung cancer

Abstract Background: Lung cancer is the leading cause of cancer-related deaths in the world. The prognosis of lung cancer depends on disease detection at an early stage. Recently, effectiveness of lung cancer screening by using low dose computed tomography scanning have been showing. However, it still has problems such as cost of screening and radiation exposure. Thus, less invasive and cost beneficial lung cancer screening procedure would be needed. In this context, several study to understand the efficacy of molecules from expiration of patients as a lung cancer screening were showing, but it was still controversial. In this study, we investigated to determine whether volatile organic compounds (VOC) from patients could be used for the detection for lung cancer by using novel small and unique absorbent material named MonoTrap . Method: The subjects’ gas was collected from skin and exhaled breath in a MonoTrap (GL sciences), and the VOCs were analyzed by gas chromatography/ mass spectrometry (GC/MS). First of all, we preliminary analyzed for both sample from skin and exhaled breath for 12 patients and 11 healthy volunteers to clarify which samples were more sensitive to diagnose lung cancer. Subsequently, each VOC was determined in detail for 7 healthy individuals and 4 lung cancer patients and these values were statistically analyzed. Results: By preliminary study, characteristics of VOC derived from skin were significantly correlated with cancer condition as compared with healthy volunteer by using comprehensive multivariate analysis. Therefore, we performed further quantitative analysis by targeting unique individual molecules derived from skin. In VOCs from skin, Mann-Whitney U test showed that 4-hydroxy-4-methyl-2-pentanone, hexadecane, and acetamide were significantly higher in lung cancer patients (p=0.036, p=0.006, p=0.036, respectively). Conclusion: In this study, we found that 3 kinds of VOCs could be a potential diagnostic biomarkers of lung cancer. Further prospective study is now planning to validate these data using large number samples. Citation Format: Takuya Inoue, Hironori Takagi, Yuki Owada, Yuzuru Watanabe, Mitsuro Fukuhara, Takumi Yamaura, Satoshi Muto, Naoyuki Okabe, Yuki Matsumura, Takeo Hasegawa, Takeda Manami, Atsushi Sato, Hiroyuki Suzuki. Analysis of volatile organic compounds for the diagnosis of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5307. doi:10.1158/1538-7445.AM2017-5307

Combination of CALR and PDIA3 is a potential prognostic biomarker for non-small cell lung cancer.

Proteomic-based approaches for biomarker discovery are promising strategies used in cancer research. In this study, we performed quantitative proteomic analysis on 16 paired samples of non-small cell lung cancer (NSCLC) and adjacent non-tumor lung tissues using label-free quantitative proteomics and liquid chromatography-tandem mass spectrometry/mass spectrometry (LC-MS/MS) to identify differentially expressed proteins. A total of 91 proteins were differentially expressed in NSCLC compared with adjacent non-tumor lung tissues among 4047 identified proteins (fold change > 1.5 or < 0.67, P < 0.05). Gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis and ingenuity pathway analysis (IPA) of 91 dysregulated proteins showed that they were related to the cancer-associated biological processes. We confirmed that the candidate proteins, calreticulin (CALR) and protein disulfide isomerase family A member 3 (PDIA3) were overexpressed in NSCLC by real-time PCR using 20 paired samples and western blot using 5 paired samples. PDIA3 expression was highly associated with CALR expression (Spearman r = 0.345, P = 0.001) and they were co-localized and interacted with each other in A549 and H460 cells. Moreover, survival analysis performed in tissue microarray with 88 samples indicated that low expression of both CALR and PDIA3 in NSCLC was positively associated with poor overall survival. Combination of CALR and PDIA3 might serve as an efficient biomarker and improved the prediction of NSCLC prognosis significantly (P = 0.023). Our results collectively provide a potential biomarker dataset for NSCLC prognosis, especially the prognostic value of combined expression of CALR and PDIA3.

A pilot study using metagenomic sequencing of the sputum microbiome suggests potential bacterial biomarkers for lung cancer.

Lung cancer (LC) is the most prevalent cancer worldwide, and responsible for over 1.3 million deaths each year. Currently, LC has a low five year survival rates relative to other cancers, and thus, novel methods to screen for and diagnose malignancies are necessary to improve patient outcomes. Here, we report on a pilot-sized study to evaluate the potential of the sputum microbiome as a source of non-invasive bacterial biomarkers for lung cancer status and stage. Spontaneous sputum samples were collected from ten patients referred with possible LC, of which four were eventually diagnosed with LC (LC+), and six had no LC after one year (LC-). Of the seven bacterial species found in all samples, Streptococcus viridans was significantly higher in LC+ samples. Seven further bacterial species were found only in LC-, and 16 were found only in samples from LC+. Additional taxonomic differences were identified in regards to significant fold changes between LC+ and LC-cases, with five species having significantly higher abundances in LC+, with Granulicatella adiacens showing the highest level of abundance change. Functional differences, evident through significant fold changes, included polyamine metabolism and iron siderophore receptors. G. adiacens abundance was correlated with six other bacterial species, namely Enterococcus sp. 130, Streptococcus intermedius, Escherichia coli, S. viridans, Acinetobacter junii, and Streptococcus sp. 6, in LC+ samples only, which could also be related to LC stage. Spontaneous sputum appears to be a viable source of bacterial biomarkers which may have utility as biomarkers for LC status and stage.

Increased stathmin in serum as a potential tumor marker for lung adenocarcinoma.

Background: Stathmin has been found to be involved in malignant tumors; the aim of this study was to investigate the relationship between serum stathmin and clinico-pathological features of lung cancer. Methods: In three lung cancer cell lines, stathmin expression and its secretion level in the supernatant were examined by Western blot and enzyme-linked immunosorbent assay (ELISA). Expression of stathmin was examined by immunohistochemistry in 48 lung cancer tissues, and serum stathmin expression level was examined by ELISA in 96 patients with lung cancer and 82 normal individuals. Sensitivity and specificity of serum stathmin were determined by receiver operator characteristic curve (ROC). Results: In the three cell lines and their supernatant, stathmin levels were higher than those in 16 HBE cell line. Lung cancer tissues expressed higher level stathmin more frequently than normal lung tissue (P < 0.05). Serum stathmin level was significantly higher in the patients with lung cancer than in normal individuals (P < 0.001). Increased stathmin level in cancer tissue and serum were significantly associated with adenocarcinoma histology, lymph node metastasis and advanced stage. The threshold level of serum stathmin for distinguishing lung cancer from normal individuals was 1.86 ng/ml. The sensitivity and specificity were 93.7% and 91.5%, respectively. Conclusions: Measurement of serum stathmin level could be a potential biomarker for lung cancer, especically those of adenocarcinoma, with lymph node metastasis and at advanced clinical stages.

Eight potential biomarkers for distinguishing between lung adenocarcinoma and squamous cell carcinoma.

Lung adenocarcinoma (LADC) and squamous cell carcinoma (LSCC) are the most common non-small cell lung cancer histological phenotypes. Accurate diagnosis distinguishing between these two lung cancer types has clinical significance. For this study, we analyzed four Gene Expression Omnibus (GEO) datasets (GSE28571, GSE37745, GSE43580, and GSE50081). We then imported the datasets into the Gene-Cloud of Biotechnology Information online platform to identify genes differentially expressed in LADC and LSCC. We identified DSG3 (desmoglein 3), KRT5 (keratin 5), KRT6A (keratin 6A), KRT6B (keratin 6B), NKX2-1 (NK2 homeobox 1), SFTA2 (surfactant associated 2), SFTA3 (surfactant associated 3), and TMC5 (transmembrane channel-like 5) as potential biomarkers for distinguishing between LADC and LSCC. Receiver operating characteristic curve analysis suggested that KRT5 had the highest diagnostic value for discriminating between these two cancer types. Using the PrognoScan online survival analysis tool and the Kaplan-Meier Plotter, we found that high KRT6A or KRT6B levels, or low NKX2-1, SFTA3, or TMC5 levels correlated with unfavorable prognoses in LADC patients. Further studies will be needed to verify our findings in additional patient samples, and to elucidate the mechanisms of action of these potential biomarkers in non-small cell lung cancer.

Circulating microRNAs as novel biomarkers of ALK-positive nonsmall cell lung cancer and predictors of response to crizotinib therapy.

Circulating microRNAs are potential diagnostic and predictive biomarkers, but have not been investigated for patients with anaplastic lymphoma kinase (ALK)-positive lung cancer. In this exploratory study, we sought to identify potential plasma biomarkers for ALK-positive non-small cell lung cancer (NSCLC). A microRNA microarray was used to select ALK-related microRNAs in ALK-positive NSCLC (n = 3), ALK-negative NSCLC (n = 3), and healthy subjects (n = 3). Plasma levels of 21 microRNAs were differentially expressed for ALK-positive and ALK-negative NSCLC, including 14 down-regulated and 7 up-regulated microRNAs. We also identified 5s rRNA as the most stable endogenous control gene using geNorm and NormFinder algorithms. Candidate microRNAs in plasma from ALK-positive (n = 41) and ALK-negative NSCLC patients (n = 32) were quantified using real-time reverse transcriptase quantitative polymerase chain reaction. The expression levels of miR-28-5p, miR-362-5p, and miR-660-5p were all down-regulated in ALK-positive NSCLC, compared with ALK-negative NSCLC. The areas under the receiver operating characteristic curves of miR-28-5p, miR-362-5p, miR-660-5p, and 3-microRNAs panel were 0.873, 0.673, 0.760, and 0.876, respectively. The positive predictive values of miR-28-5p, miR-362-5p, and miR-660-5p were 96.43%, 80.77%, and 83.87%, respectively. Increased plasma levels of miR-660-5p after crizotinib treatment predicted good tumor response (p = 0.012). The pre-crizotinib levels of miR-362-5p were significantly associated with progression-free survival (p = 0.015). Thus, in this preliminary investigation, we identified a potential panel of 3 microRNAs for distinguishing between patients with ALK-positive and ALK-negative NSCLC. We also identified miR-660-5p and miR-362-5p as potential predictors for response to crizotinib treatment.

Paraoxonase-1 (PON1) induces metastatic potential and apoptosis escape via its antioxidative function in lung cancer cells.

Paraoxonase-1 (PON1) gene polymorphisms have been closely associated with the development of advanced cancers while PON1 secretion to the serum is linked with inhibition of oxidized high-density lipoprotein by its antioxidative function. Our group previously demonstrated that post-translational modification of serum PON1 in form of fucosylated PON1 is a potential biomarker of small cell lung cancer. Here, we interrogated the role of PON1 in the pathobiology of lung cancer (LC) by addressing cell-autonomous mechanisms using gain-of-function and loss-of-function approaches and protein expression profiling of tissue samples in our clinical biobank. PON1 expression in LC patient tissues varied between overexpression in squamous cell carcinoma and minimal loss in adenocarcinoma sub-types. Simultaneous overexpression of PON1 both at the gene and protein stability levels induced pro-oncogenic characteristics in LC cells and xenografts. PON1 overexpression supported metastatic progression of LC by decreasing G1/S ratio and LC cell senescence involving p21Waf1/Cip1. PON1 suppressed drug- and ligand-induced cell death and protected LC cells from genotoxic damages with maintained ATP levels, requiring p53-directed signals. PON1 promoted ROS deregulation protecting the mitochondria from dysregulation. PON1 knockdown resulted in the blockage of its antioxidant function in LC cells through Akt signaling with reduced invasive signature as a consequence of scant expression. Targeted glycolysis stimulated PON1 antioxidant activity regulating phosphorylation of AMPK-α. The functional data imply that exploitation of the antioxidative function of PON1 is consequential in driving LC pathogenesis at the cell-autonomous mechanistic level with consequences on tumor growth.

A novel polyaniline/polypyrrole/graphene oxide fiber for the determination of volatile organic compounds in headspace gas of lung cell lines

Exploration of volatile organic compounds (VOCs) generated by lung cell lines is a powerful and non-invasive tool for the detection of potential volatile biomarkers of lung cancer. In this study, a simple and sensitive solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) method was developed for the determination of VOCs in the headspace gas of lung cell lines. For the purpose of preconcentration, a novel polyaniline/polypyrrole/graphene oxide (PANI/PPy/GO) coating was prepared on the surface of stainless steel fiber via in-situ electrochemical deposition for the first time. The characteristic properties of the coating were studied and the results revealed that the coating possessed large surface area, high extraction efficiency, excellent thermal and mechanical stability as well as long lifespan. Some parameters affecting the extraction efficiency such as synthesis conditions, extraction and desorption conditions were optimized. Under the optimal conditions, the method displayed relatively wide linear range (three or four orders of magnitude) with correlation coefficients above 0.9916. Low detection limits from 1.0 to 12ngL−1 were obtained. Relative standard deviations ranged from 1.2% to 18.0% indicating good repeatability and reproducibility of the method. This method has been successfully applied to analyze VOCs in the headspace gas of lung adenocarcinoma epithelial cell line (A549) and human embryonic fibroblast cell line (MRC-5).

Pathway deviation-based biomarker and multi-effect target identification in asbestos-related squamous cell carcinoma of the lung.

Asbestos-related lung carcinoma is one of the most devastating occupational cancers, and effective techniques for early diagnosis are still lacking. In the present study, a systematic approach was applied to detect a potential biomarker for asbestos-related lung cancer (ARLC); in particular asbestos-related squamous cell carcinoma (ARLC-SCC). Microarray data (GSE23822) were retrieved from the Gene Expression Omnibus database, including 26 ARLC-SCCs and 30 non-asbestos-related squamous cell lung carcinomas (NARLC-SCCs). Differentially expressed genes (DEGs) were identified by the limma package, and then a protein-protein interaction (PPI) network was constructed according to the BioGRID and HPRD databases. A novel scoring approach integrating an expression deviation score and network degree of the gene was then proposed to weight the DEGs. Subsequently, the important genes were uploaded to DAVID for pathway enrichment analysis. Pathway correlation analysis was carried out using Spearman's rank correlation coefficient of the pathscore. In total, 1,333 DEGs, 391 upregulated and 942 downregulated, were obtained between the ARLC-SCCs and NARLC-SCCs. A total of 524 important genes for ARLC-SCC were significantly enriched in 22 KEGG pathways. Correlation analysis of these pathways showed that the pathway of SNARE interactions in vesicular transport was significantly correlated with 12 other pathways. Additionally, obvious correlations were found between multiple pathways by sharing cross-talk genes (EGFR, PRKX, PDGFB, PIK3R3, SLK, IGF1, CDC42 and PRKCA). On the whole, our data demonstrate that 8 cross-talk genes were found to bridge multiple ARLC-SCC-specific pathways, which may be used as candidate biomarkers and potential multi-effect targets. As these genes are involved in multiple pathways, it is possible that drugs targeting these genes may thus be able to influence multiple pathways simultaneously.

Increased stathmin in serum as a potential tumor marker for lung adenocarcinoma.

Stathmin has been found to be involved in malignant tumors; the aim of this study was to investigate the relationship between serum stathmin and clinico-pathological features of lung cancer. In three lung cancer cell lines, stathmin expression and its secretion level in the supernatant were examined by Western blot and enzyme-linked immunosorbent assay (ELISA). Expression of stathmin was examined by immunohistochemistry in 48 lung cancer tissues, and serum stathmin expression level was examined by ELISA in 96 patients with lung cancer and 82 normal individuals. Sensitivity and specificity of serum stathmin were determined by receiver operator characteristic curve (ROC). In the three cell lines and their supernatant, stathmin levels were higher than those in 16 HBE cell line. Lung cancer tissues expressed higher level stathmin more frequently than normal lung tissue (P < 0.05). Serum stathmin level was significantly higher in the patients with lung cancer than in normal individuals (P < 0.001). Increased stathmin level in cancer tissue and serum were significantly associated with adenocarcinoma histology, lymph node metastasis and advanced stage. The threshold level of serum stathmin for distinguishing lung cancer from normal individuals was 1.86 ng/ml. The sensitivity and specificity were 93.7% and 91.5%, respectively. Measurement of serum stathmin level could be a potential biomarker for lung cancer, especically those of adenocarcinoma, with lymph node metastasis and at advanced clinical stages.

A novel PHD-finger protein 14/KIF4A complex overexpressed in lung cancer is involved in cell mitosis regulation and tumorigenesis

The plant homeodomain (PHD) finger-containing proteins have been implicated in many human diseases including cancer. In this study, we found that PHF14, a newly identified PHD finger protein, is highly expressed in lung cancer. The high expression level of PHF14 was associated with adenocarcinoma and poor survival in lung cancer patients. Knocking down PHF14 suppressed cancer cell growth and carcinogenesis, while over-expressing PHF14 promoted cell proliferation. During cell division, PHF14 directly bound to and co-localized with KIF4A (a nuclear motor protein involved in lung carcinogenesis) to form a functional complex. Similarly to the effect of KIF4A depletion, silencing PHF14 in several cell lines caused cell mitotic defects, prolonged M phase, and inhibited cell proliferation. What's more, these two proteins had a synergistic effect on cell proliferation and were significantly co-overexpressed in lung cancer tissues. Our data provide new insights into the biological significance of PHD finger proteins and imply that PHF14 may be a potential biomarker for lung cancer.

P1.05-018 LncRNA16 is a Potential Biomarker for Early-Stage Lung Cancer That Promotes Cell Proliferation by Regulating the Cell Cycle

Early diagnosis of lung cancer greatly reduces mortality; however, the lack of suitable plasma biomarkers presents a major obstacle. Recent studies showed that long noncoding RNAs (lncRNAs) play important roles in cancer initiation and development. Here, we identify differential expressed lncRNAs by using custom designed microarray on 20 lung cancer samples and evaluate the expression by Real-time PCR (qRT-PCR) on 118 lung cancer samples. The role of lncRNA16 in lung cancer was studied in vitro and in vivo, utilizing the lung cancer cell line PC9, A549 and xenograft mouse models. lncRNA16 (ENST00000539303) expression level was highly in lung cancer (80/118) and in plasma (32/42) of lung cancer patients. In early stage, lncRNA16 expression levels were significantly higher compare to that in adjacent matched normal tissues (Figure 1C-1F). Importantly, this increase was mirrored in plasma samples of early stage lung cancer patients (Figure 2A). Our study reveals that knockdown of lncRNA16 inhibited proliferation of PC9 cells in vitro and also inhibited tumor growth in xenograft mouse models. Specifically, we show that lncRNA16 promotes G2/M transition through regulating cyclin B1 transcription. In conclusion, lncRNA16 was identified as a potential biomarker for lung cancer diagnosis, as it displayed significantly elevated levels in cancer patient over baseline. Furthermore, we showed that the false-negative rate is significantly lower compared to markers those widely used for lung cancer assessment.

TAp73 upregulates IL-1β in cancer cells: Potential biomarker in lung and breast cancer?

p73 is a transcription factor belonging to the p53 tumour suppressor family. p73−/− mice exhibit a range of phenotypes including neurological, reproductive and inflammatory defects. Although the role of p73 in the control of genomic stability explains part of these phenotypes, a clear mechanism of how p73 participates in the inflammatory response is still elusive. Interleukin-1β (IL-1β) has a crucial role in mediating the inflammatory response. Because of its high potency to induce inflammation, the activation and secretion of IL-1β is tightly regulated by large protein complexes, named inflammasomes. Inflammasomes regulate activation of proinflammatory caspase-1, which in turn proteolytically processes its substrates, including pro-IL-1β. Caspase-1 gene transcription is strongly activated by p53 protein family members including p73. Here, we have addressed whether p73 might be directly involved in IL-1β regulation and therefore in the control of the inflammatory response. Our results show that TAp73β upregulates pro-IL-1β mRNA and processed IL-1β protein. In addition, analysis of breast and lung cancer patient cohorts demonstrated that interaction between p73 and IL-1β predicts a negative survival outcome in these human cancers.

Long Non-Coding RNA Expression Signature Hallmarks Promising Efficacy in Identification of Human Non-Small Cell Lung Cancer: a Meta-Analysis Study.

The long non-coding RNAs (lncRNAs) are significantly altered in an expanding list of malignant neoplasms, suggesting that they might be popularized as potential biomarkers for cancer detection. This study sought to validate the diagnostic efficacy of lncRNA expression signature(s) as potential biomarker(s) for non-small cell lung cancer (NSCLC) diagnosis. We conducted the online databases search for all eligible studies. A quantitative meta-analysis was performed using Stata 12.0 and Meta-Disc 1.4 statistical programs. Sensitivity analysis and a meta-regression test were applied to deeply trace the underlying heterogeneity sources. Eight cohorts comprised 775 NSCLC patients and 630 matched controls were included. Our data manifested that lncRNA expression profiling harbored a pooled sensitivity of 0.77 (95% CI: 0.71 - 0.82) and specificity of 0.86 (95% CI: 0.80 - 0.90) in discriminating NSCLC cases from cancer-free individuals, along with an AUC (area under the curve) value of 0.88. Further subgroup analysis revealed that paralleled testing of lncRNAs (sensitivity, specificity, and AUC of 0.90, 0.80 and 0.96, respectively) substantially strengthened the diagnostic efficacy as compared with the single testing pattern (sensitivity, specificity, and AUC of 0.71, 0.77 and 0.82, respectively). Other stratified analysis of ethnicity, histology type, and test matrix also presented robust results. Altogether, our results indicate that lncRNA expression signature(s) might be applicable as complementary biomarker(s) for the identification of NSCLC.

MiRNA-129-5p suppresses cell proliferation and invasion in lung cancer by targeting microspherule protein 1, E-cadherin and vimentin.

Downregulation of microRNA-129 (miR-129) has been described in various types of cancer, however, the significance of miR-129 in lung cancer has not been investigated. The present study, for the first time, determined miR-129-5p expression levels in both lung cancer cell lines and primary lung cancer tissues and also studied the effect of miR-129-5p on the proliferation and invasiveness of lung cancer cells. The results showed that miR-129-5p expression was significantly reduced in both lung cancer cell lines and primary lung cancer tissues (P<0.05). Further research revealed that miR-129-5p could suppress the proliferation and invasion capability of lung cancer cells. Bioinformatics analysis suggested three cancer-related miR-129-5p target genes: Microspherule protein 1 (MCRS1), E-cadherin and vimentin. Further investigation via reverse transcription-quantitative polymerase chain reaction and western blot analysis showed that miR-129-5p was able to reduce the expression levels of MCRS1 and vimentin and enhance the expression of E-cadherin at both the messenger RNA and protein levels. The present results indicate that miR-129-5p is able to suppress lung cancer cell viability and invasion, which may occur via the modulating of MCRS1, E-cadherin and vimentin expression. These findings suggest that miR-129-5p may be a potential biomarker and/or treatment strategy for lung cancer.

Plasma miR-19b and miR-183 as Potential Biomarkers of Lung Cancer.

Lung cancer is a complex disease that often manifests at the point when treatment is not effective. Introduction of blood-based complementary diagnostics using molecular markers may enhance early detection of this disease and help reduce the burden of lung cancer. Here we evaluated the diagnostic potential of seven plasma miRNA biomarkers (miR-21, -19b, -126, -25, -205, -183, -125b) by quantitative reverse transcription PCR. Influence clinical and demographical characteristics, including age, tumor stage and cancer subtype on miRNA levels was investigated. Four miRNAs were significantly dysregulated (miR-19b, -21, -25, -183) in lung cancer patients. Combination of miR-19b and miR-183 provided detection of lung cancer with 94.7% sensitivity and 95.2% specificity (AUC = 0.990). Thus, miRNAs have shown the potential to discriminate histological subtypes of lung cancer and reliably distinguish lung cancer patients from healthy individuals.