Human semaphorins A(V) and IV reside in the 3p21.3 small cell lung cancer deletion region and demonstrate distinct expression patterns.

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.

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

BioMed Research International ◽

10.1155/2015/685303 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 7

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.

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Comprehensive Evaluation of Nuclear Factor-κΒ Expression Patterns in Non-Small Cell Lung Cancer

PLoS ONE ◽

10.1371/journal.pone.0132527 ◽

2015 ◽

Vol 10 (7) ◽

pp. e0132527 ◽

Cited By ~ 20

Author(s):

Ioanna Giopanou ◽

Ioannis Lilis ◽

Vassilios Papaleonidopoulos ◽

Antonia Marazioti ◽

Magda Spella ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Comprehensive Evaluation ◽

Expression Patterns ◽

Small Cell ◽

Nuclear Factor ◽

Small Cell Lung

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Expression, Prognosis and Gene Regulation Network of NFAT Transcription Factors in Non-Small Cell Lung Cancer

Pathology & Oncology Research ◽

10.3389/pore.2021.529240 ◽

2021 ◽

Vol 27 ◽

Author(s):

Jin Ma ◽

Rao Du ◽

Yan Huang ◽

Wen Zhong ◽

Huan Gui ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Mrna Expression ◽

Cell Lung Cancer ◽

Expression Patterns ◽

Lung Squamous Cell Carcinoma ◽

Small Cell ◽

Small Cell Lung ◽

Aberrant Expression ◽

Expression Levels

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide. The nuclear factor of activated T cells (NFAT) family is implicated in tumorigenesis and progression in various types of cancer. However, little is known about their expression patterns, distinct prognostic values, and potential regulatory networks in NSCLC. In this study, we comprehensively analyzed the distinct expression and prognostic value of NFATs in NSCLC through various large databases, including the Oncomine, UCSC Xena Browser, UALCAN databases, Kaplan–Meier Plotter, cBioPortal, and Enrichr. In lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), NFAT1/2/4/5 mRNA expression levels were significantly decreased and NFAT3 mRNA expression level was significantly increased. The cBioPortal database analysis showed that the mRNA dysregulation was one of the single most important factors for NFAT alteration in LUAD and LUSC and that both LUAD and LUSC cases with the alterations in the mRNA expression of NFATs had significantly better overall survival (OS). High expression levels of NFAT1/2/4/5 were significantly associated with better OS in LUAD, whereas high NFAT3 expression led to a worse OS. Overexpression of NFAT1/2 predicted better OS in LUSC, whereas high NFAT5 expression led to a worse OS. The networks for NFATs and the 50 most frequently altered neighbor genes in LUAD and LUSC were also constructed. NFATs and genes significantly associated with NFAT mRNA expression in LUAD and LUSC were significantly enriched in the cGMP-dependent protein kinase and Wnt signaling pathways. These results showed that the NFAT family members displayed varying degrees of abnormal expressions, suggesting that NFATs may be therapeutic targets for patients with NSCLC. Aberrant expression of NFATs was found to be associated with OS in the patients with NSCLC; among NFATs, NFAT3/4 may be new biomarkers for the prognosis of LUAD. However, further studies are required to validate our findings.

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Expression patterns of USP22 and potential targets BMI-1, PTEN, p-AKT in non-small-cell lung cancer

Lung Cancer ◽

10.1016/j.lungcan.2012.05.112 ◽

2012 ◽

Vol 77 (3) ◽

pp. 593-599 ◽

Cited By ~ 47

Author(s):

Jing Hu ◽

Yan-Long Liu ◽

Song-lin Piao ◽

Dong-dong Yang ◽

Yan-Mei Yang ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Expression Patterns ◽

Small Cell ◽

Small Cell Lung

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Comprehensive and Computable Molecular Diagnostic Panel (C2Dx) From Small Volume Specimens for Precision Oncology: Molecular Subtyping of Non-Small Cell Lung Cancer From Fine Needle Aspirates

Frontiers in Oncology ◽

10.3389/fonc.2021.584896 ◽

2021 ◽

Vol 11 ◽

Author(s):

Jing Su ◽

Lynn S. Huang ◽

Ryan Barnard ◽

Graham Parks ◽

James Cappellari ◽

...

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Small Volume ◽

Expression Patterns ◽

Small Cell ◽

Molecular Diagnostic ◽

Precision Oncology ◽

Small Cell Lung ◽

Transcriptomic Data

The Comprehensive, Computable NanoString Diagnostic gene panel (C2Dx) is a promising solution to address the need for a molecular pathological research and diagnostic tool for precision oncology utilizing small volume tumor specimens. We translate subtyping-related gene expression patterns of Non-Small Cell Lung Cancer (NSCLC) derived from public transcriptomic data which establish a highly robust and accurate subtyping system. The C2Dx demonstrates supreme performance on the NanoString platform using microgram-level FNA samples and has excellent portability to frozen tissues and RNA-Seq transcriptomic data. This workflow shows great potential for research and the clinical practice of cancer molecular diagnosis.

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Coexpression patterns of IDO-1, PD-L1 and EGFR in non-small cell lung cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e14279 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e14279-e14279 ◽

Cited By ~ 1

Author(s):

Weili Wang ◽

Chen Zhang ◽

Liang Cheng ◽

Jianyue Jin ◽

Feng-Ming Spring Kong

Keyword(s):

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Target Therapy ◽

Expression Patterns ◽

Small Cell ◽

Treatment Modalities ◽

Small Cell Lung ◽

Indoleamine 2 ◽

Nsclc Patients

e14279 Background: Indoleamine-2, 3-dioxygenase (IDO), a well-established immune suppressor, may offset efficacy of immune checkpoint inhibitors (ICIs) such as programmed death receptor ligand-1(PD-L1) by inducing unfavorable tumor microenvironment. The unpredictability of one ICI response may partially due to the concomitant presence of other ICIs. Therefore, increasing interest has been focus on the dual ICIs or the combination of ICIs with conventional treatment modalities such as radiotherapy, chemotherapy as well as target therapy. This study aimed to study the coexpression patterns and significance of IDO-1, PD-L1 and epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC). Methods: Patients with newly diagnosed NSCLC enrolled in three prospective surgery clinical trials were included in this study. The expressions of IDO-1, PD-L1 and EGFR were evaluated by immunohistochemistry (IHC). For positive cases, the percentile score and H-score were generated respectively from two independent pathologists. The descriptive analysis of Crosstab was used to compare the distributions of these biomarkers expression by pathological types. Results: A total of 117 patients (adenocarcinoma -54%, squamous cell carcinoma -32% and others -14%) with pretreatment tissue specimen available for IHC analysis were studied. Of these, 105 (90%) were from lung primary and 12 (10%) from distant metastasis sites. The expressions of IDO-1 (≥ 1%), PD-L1 ((≥ 1%) and EGFR (≥ 90% or intensity = 3) were identified in 43%, 40% and 52% of NSCLC patients. For IDO-1 and PD-L1, coexpression rates were 21% for co-positive and 37% for co-negative. However, there were still 42% patients showed isolated PD-L1 (20%) or IDO-1 expression (22%). The coexpression rates for EGFR and IDO-1 were 21% for co-positive and 26% for co-negative. The coexpression rates for EGFR and PD-L1 were 20% for co-positive and 25% for co-negative. 38% patients had a positive EGFR with either IDO-1 or PD-L1 positive. The expression patterns were not significant associated with clinical factors including pathological types and differentiation grades. Conclusions: IDO-1 and PD-L1 expression patterns may be useful in the selection of NSCLC patients for dual ICIs immunotherapy. The combinations of EGFR target therapy with immunotherapy may benefit some of NSCLC patients. However, testing expression status of EGFR and immune checkpoints becomes essential since majority of NSCLC patients exhibits EGFR positive with IDO-1 or PD-L1 negative patterns.

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