scholarly journals Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Fei Long ◽  
Jia-Hang Su ◽  
Bin Liang ◽  
Li-Li Su ◽  
Shu-Juan Jiang
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Expression Patterns ◽  
Small Cell ◽  
Normal Lung ◽  
Specific Gene ◽  
Small Cell Lung ◽  
Cancer Subtypes ◽  
Gene Modules

Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

scholarly journals Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Cancers ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 37 ◽  
Author(s):  
Magdalena Niemira ◽  
Francois Collin ◽  
Anna Szalkowska ◽  
Agnieszka Bielska ◽  
Karolina Chwialkowska ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Network Analysis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Molecular Signature ◽  
Normal Lung ◽  
Specific Gene ◽  
Small Cell Lung ◽  
Hub Genes

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

scholarly journals Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers

2018 ◽  
Author(s):  
DJ Wooten ◽  
SF Maddox ◽  
DR Tyson ◽  
Q Liu ◽  
JS Lim ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Systems Approach ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cancer Subtypes ◽  
Master Regulators

AbstractAdopting a systems approach, we devise a general workflow to define actionable subtypes in human cancers. Applied to small cell lung cancer (SCLC), the workflow identifies four subtypes based on global gene expression patterns and ontologies. Three correspond to known subtypes, while the fourth is a previously undescribed neuroendocrine variant (NEv2). Tumor deconvolution with subtype gene signatures shows that all of the subtypes are detectable in varying proportions in human and mouse tumors. To understand how multiple stable subtypes can arise within a tumor, we infer a network of transcription factors and develop BooleaBayes, a minimally-constrained Boolean rule-fitting approach. In silico perturbations of the network identify master regulators and destabilizers of its attractors. Specific to NEv2, BooleaBayes predicts ELF3 and NR0B1 as master regulators of the subtype, and TCF3 as a master destabilizer. Since the four subtypes exhibit differential drug sensitivity, with NEv2 consistently least sensitive, these findings may lead to actionable therapeutic strategies that consider SCLC intratumoral heterogeneity. Our systems-level approach should generalize to other cancer types.

The Key microRNAs Regulated the Development of Non-small Cell Lung Cancer by Targeting TGF-β-induced epithelial–mesenchymal Transition

2019 ◽  
Vol 22 (4) ◽  
pp. 238-244 ◽  
Author(s):  
Gang Chen ◽  
Bo Ye
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lines ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Nsclc Cell ◽  
Normal Lung ◽  
Migration And Invasion ◽  
Small Cell Lung ◽  
Mesenchymal Transition

Purpose: Epithelial-to-Mesenchymal Transition (EMT) was reported to play a key role in the development of Non-Small Cell Lung Cancer (NSCLC). The process of EMT is regulated by the changes of miRNAs expression. However, it is still unknown which miRNA changed the most in the process of canceration and whether these changes played a role in tumor development. Methods: A total of 36 SCLC patients treated in our hospital between 11th, 2015 and 10th, 2017 were enrolled. The samples of cancer tissues and paracancer tissues of patients were collected and analyzed. Then, the miRNAs in normal lung cells and NSCLC cells were also analyzed. In the presence of TGF-β, we transfected the miRNA mimics or inhibitor into NSCLC cells to investigate the role of the significantly altered miRNAs in cell migration and invasion and in the process of EMT. Results: MiR-330-3p was significantly up-regulated in NSCLC cell lines and tissues and miRNA- 205 was significantly down-regulated in NSCLC cell lines and NSCLC tissues. Transfected miRNA-205 mimics or miRMA-330-3p inhibitor inhibited the migration and invasion of NCIH1975 cell and restrained TGF-β-induced EMT in NSCLC cells. Conclusion: miRNA-330-3p and miRNA-205 changed the most in the process of canceration in NSCLC. Furthermore, miR-330-3p promoted cell invasion and metastasis in NSCLC probably by promoting EMT and miR-205 could restrain NSCLC likely by suppressing EMT.

scholarly journals Predicting Diagnostic Gene Biomarkers for Non-Small-Cell Lung Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Bin Liang ◽  
Yang Shao ◽  
Fei Long ◽  
Shu-Juan Jiang
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Association Network ◽  
Small Cell Lung ◽  
Functional Association ◽  
Functional Association Network ◽  
Gene Modules

Lung cancer is the primary reason for death due to cancer worldwide, and non-small-cell lung cancer (NSCLC) is the most common subtype of lung cancer. Most patients die from complications of NSCLC due to poor diagnosis. In this paper, we aimed to predict gene biomarkers that may be of use for diagnosis of NSCLC by integrating differential gene expression analysis with functional association network analysis. We first constructed an NSCLC-specific functional association network by combining gene expression correlation with functional association. Then, we applied a network partition algorithm to divide the network into gene modules and identify the most NSCLC-specific gene modules based on their differential expression pattern in between normal and NSCLC samples. Finally, from these modules, we identified genes that exhibited the most impact on the expression of their functionally associated genes in between normal and NSCLC samples and predicted them as NSCLC biomarkers. Literature review of the top predicted gene biomarkers suggested that most of them were already considered critical for development of NSCLC.

O-256 Prognostic significance Brm expression patterns in non-small cell lung cancer (NSCLC)

Lung Cancer ◽  
2003 ◽  
Vol 41 ◽  
pp. S75
Author(s):  
Junya Fukuoka ◽  
Joanna Shih ◽  
Stephane Hewitt ◽  
William D. Travis ◽  
Jin Jen
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Expression Patterns ◽  
Prognostic Significance ◽  
Small Cell ◽  
Small Cell Lung

scholarly journals Kinesin superfamily protein 21B acts as an oncogene in non-small cell lung cancer

2020 ◽  
Author(s):  
Zhi-Gang Sun ◽  
Feng Pan ◽  
Jing-Bo Shao ◽  
Qian-Qian Yan ◽  
Lu Lu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Nude Mice ◽  
Cell Lung Cancer ◽  
A549 Cells ◽  
Small Cell ◽  
Normal Lung ◽  
Migration And Invasion ◽  
Small Cell Lung ◽  
Kinesin Superfamily

Abstract Background: Kinesin superfamily proteins (KIFs) serve as microtubule-dependent molecular motors, and are involved in the progression of many malignant tumors. In this study, we aimed to investigate the expression pattern and precise role of kinesin family member 21B (KIF21B) in non-small cell lung cancer (NSCLC). Methods: KIF21B expression in 72 cases of NSCLC tissues was measured by immunohistochemical staining (IHC). We used shRNA-KIF21B interference to silence KIF21B in NSCLC H1299 and A549 cells and normal lung epithelial bronchus BEAS-2B cells. The biological roles of KIF21B in the growth and metastasis abilities of NSCLC cells were measured by Cell Counting Kit-8 (CCK8), colony formation and Hoechst 33342/PI, wound-healing, and Transwell assays, respectively. Expression of apoptosis-related proteins was determined using western blot. The effect of KIF21B on tumor growth in vivo was examined using nude mice model. Results: KIF21B was up-regulated in NSCLC tissues, and correlated with pathological lymph node and pTNM stage, its high expression was predicted a poor prognosis of patients with NSCLC. Silencing of KIF21B mediated by lentivirus-delivered shRNA significantly inhibited the proliferation ability of H1299 and A549 cells. KIF21B knockdown increased apoptosis in H1299 and A549 cells, down-regulated the expression of Bcl-2 and up-regulated the expression of Bax and active Caspase 3. Moreover, KIF21B knockdown decreased the level of phosphorylated form of Akt (p-Akt) and Cyclin D1 expression in H1299 and A549 cells. In addition, silencing of KIF21B impeded the migration and invasion of H1299 and A549 cells. Further, silencing of KIF 21B dramatically inhibited xenograft growth in BALB/c nude mice. However, silencing of KIF21B did not affect the proliferation, migration and invasion of BEAS-2B cells.Conclusions: These results reveal that KIF21B is up-regulated in NSCLC and acts as an oncogene in the growth and metastasis of NSCLC, which may function as a potential therapeutic target and a prognostic biomarker for NSCLC.

scholarly journals Identifying Cross-Scale Associations between Radiomic and Pathomic Signatures of Non-Small Cell Lung Cancer Subtypes: Preliminary Results

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3663
Author(s):  
Charlems Alvarez-Jimenez ◽  
Alvaro A. Sandino ◽  
Prateek Prasanna ◽  
Amit Gupta ◽  
Satish E. Viswanath ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Density ◽  
Squamous Cell ◽  
Cell Lung Cancer ◽  
Ct Images ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cancer Subtypes ◽  
Initial Results

(1) Background: Despite the complementarity between radiology and histopathology, both from a diagnostic and a prognostic perspective, quantitative analyses of these modalities are usually performed in disconnected silos. This work presents initial results for differentiating two major non-small cell lung cancer (NSCLC) subtypes by exploring cross-scale associations between Computed Tomography (CT) images and corresponding digitized pathology images. (2) Methods: The analysis comprised three phases, (i) a multi-resolution cell density quantification to identify discriminant pathomic patterns for differentiating adenocarcinoma (ADC) and squamous cell carcinoma (SCC), (ii) radiomic characterization of CT images by using Haralick descriptors to quantify tumor textural heterogeneity as represented by gray-level co-occurrences to discriminate the two pathological subtypes, and (iii) quantitative correlation analysis between the multi-modal features to identify potential associations between them. This analysis was carried out using two publicly available digitized pathology databases (117 cases from TCGA and 54 cases from CPTAC) and a public radiological collection of CT images (101 cases from NSCLC-R). (3) Results: The top-ranked cell density pathomic features from the histopathology analysis were correlation, contrast, homogeneity, sum of entropy and difference of variance; which yielded a cross-validated AUC of 0.72 ± 0.02 on the training set (CPTAC) and hold-out validation AUC of 0.77 on the testing set (TCGA). Top-ranked co-occurrence radiomic features within NSCLC-R were contrast, correlation and sum of entropy which yielded a cross-validated AUC of 0.72 ± 0.01. Preliminary but significant cross-scale associations were identified between cell density statistics and CT intensity values using matched specimens available in the TCGA cohort, which were used to significantly improve the overall discriminatory performance of radiomic features in differentiating NSCLC subtypes (AUC = 0.78 ± 0.01). (4) Conclusions: Initial results suggest that cross-scale associations may exist between digital pathology and CT imaging which can be used to identify relevant radiomic and histopathology features to accurately distinguish lung adenocarcinomas from squamous cell carcinomas.

scholarly journals Loading MicroRNA-376c in Extracellular Vesicles Inhibits Properties of Non-Small Cell Lung Cancer Cells by Targeting YTHDF1

2020 ◽  
Vol 19 ◽  
pp. 153303382097752
Author(s):  
Jianying Zhou ◽  
Dan Xiao ◽  
Tingting Qiu ◽  
Jun Li ◽  
Zhentian Liu
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Extracellular Vesicles ◽  
Cell Lung Cancer ◽  
Rna Binding ◽  
Biological Activities ◽  
Expression Patterns ◽  
Small Cell ◽  
Luciferase Reporter ◽  
Small Cell Lung

Objective: Extracellular vesicles (Evs) secreted from cells have been revealed to mediate signal transduction between cells. Nevertheless, the mechanisms through which molecules transported by EVs function remain to be elucidated. In the present study, the functional relevance of endothelial cells (ECs)-secreted Evs carrying microRNA-376c (miR-376c) in the biological activities of non-small cell lung cancer (NSCLC) cells was investigated, including the related mechanisms. Methods: Two cell lines with the highest YTH N6-methyladenosine (m6A) RNA binding protein 1 (YTHDF1) expression were selected for subsequent experiments. Cellular proliferation, migration, invasion and apoptosis were measured by EdU, wound healing, Transwell assays and flow cytometry, respectively. The binding relationship between miR-376c and YTHDF1 was analyzed by dual-luciferase reporter assays. The miR-376c, YTHDF1 and β-catenin expression was evaluated by qPCR assays and western blot assays. Results: The expression patterns of YTHDF1 were higher in NSCLC cells, whereas miR-376c was reduced versus the normal bronchial epithelial cells. Silencing of YTHDF1 repressed NSCLC cell proliferation, invasion and migration abilities, whereas enhanced apoptosis. miR-376c negatively modulated YTHDF1 expression. Under co-culture conditions, ECs transmitted miR-376c into NSCLC cells through Evs, and inhibited the intracellular YTHDF1 expression and the Wnt/β-catenin pathway activation. Rescue experiments revealed that YTHDF1 overexpression reversed the inhibitory role of miR-376c released by EC-Evs in NSCLC cells. Conclusion: EC-delivered Evs inhibit YTHDF1 expression and the Wnt/β-catenin pathway induction via miR-376c overexpression, thus inhibiting the malignant phenotypes of NSCLC cells.

scholarly journals Promoter Methylation of Selected Genes in Non-Small-Cell Lung Cancer Patients and Cell Lines

2020 ◽  
Vol 21 (13) ◽  
pp. 4595
Author(s):  
Victoria Sarne ◽  
Samuel Huter ◽  
Sandrina Braunmueller ◽  
Lisa Rakob ◽  
Nico Jacobi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lines ◽  
Cell Lung Cancer ◽  
Promoter Methylation ◽  
Small Cell ◽  
Marker Genes ◽  
Specific Gene ◽  
Small Cell Lung ◽  
The Impact

Specific gene promoter DNA methylation is becoming a powerful epigenetic biomarker in cancer diagnostics. Five genes (CDH1, CDKN2Ap16, RASSF1A, TERT, and WT1) were selected based on their frequently published potential as epigenetic markers. Diagnostic promoter methylation assays were generated based on bisulfite-converted DNA pyrosequencing. The methylation patterns of 144 non-small-cell lung cancer (NSCLC) and 7 healthy control formalin-fixed paraffin-embedded (FFPE) samples were analyzed to evaluate the applicability of the putative diagnostic markers. Statistically significant changes in methylation levels are shown for TERT and WT1. Furthermore, 12 NSCLC and two benign lung cell lines were characterized for promoter methylation. The in vitro tests involved a comparison of promoter methylation in 2D and 3D cultures, as well as therapeutic tests investigating the impact of CDH1/CDKN2Ap16/RASSF1A/TERT/WT1 promoter methylation on sensitivity to tyrosine kinase inhibitor (TKI) and DNA methyl-transferase inhibitor (DNMTI) treatments. We conclude that the selected markers have potential and putative impacts as diagnostic or even predictive marker genes, although a closer examination of the resulting protein expression and pathway regulation is needed.

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