Abstract
BackgroundLung cancer is the leading cause of cancer mortality worldwide, mainly due to late diagnosis, poor prognosis and tumor heterogeneity. Thus, the need for biomarkers that will aid classification, treatment and monitoring remains intense and challenging and depends on the better understanding of the tumor pathobiology and underlying mechanisms. The deregulation of gene expression is a hallmark of cancer and a critical parameter is the stability of mRNAs that may lead to increased oncogene and/or decreased tumor suppressor transcript and protein levels. The shortening of mRNA poly(A) tails determines mRNA stability, as it is usually the first step in mRNA degradation, and is catalyzed by deadenylases. Herein, we assess the clinical significance of deadenylases and we study their role on gene expression in squamous cell lung carcinoma (SCC).MethodsComputational transcriptomic analysis from a publicly available microarray was performed in order to examine the expression of deadenylases in SCC patient samples. Subsequently we employed real-time PCR in clinical samples in order to validate the bioinformatics results regarding the gene expression of deadenylases. Selected deadenylases were silenced in NCI-H520 and Hep2 human cancer cell lines and the effect on gene expression was analyzed with cDNA microarrays.ResultsThe in silico analysis revealed that the expression of several deadenylases is altered in SCC. Quantitative real-time PCR showed that four deadenylases, PARN, CNOT6, CNOT7 and NOC, are differentially expressed in our SCC clinical samples. PARN overexpression correlated with younger patient age and CNOT6 overexpression with non-metastatic tumors. Kaplan-Meier analysis suggests that increased levels of PARN and NOC correlate with significantly increased survival. Gene expression analysis upon PARN and NOC silencing in lung cancer cells revealed gene expression deregulation that was functionally enriched for gene ontologies related to cell adhesion, cell junction, muscle contraction and metabolism.ConclusionsOur results highlight the clinical significance of PARN and NOC on the survival in SCC diagnosed patients. We demonstrate that the enzymes are implicated in important phenotypes pertinent to cancer biology and provide information on their role in the regulation of gene expression in SCC. Overall, our results support an emerging role for deadenylases in SCC and contribute to the understanding of their role in cancer biology.Electronic supplementary materialThe online version of this article (doi:10.1186/s12943-015-0457-3) contains supplementary material, which is available to authorized users.
Highlights
Lung cancer is the leading cause of cancer mortality worldwide, mainly due to late diagnosis, poor prognosis and tumor heterogeneity
Computational trascriptomic analysis of deadenylases expression in squamous cell lung carcinoma Based on our previous work on the expression of deadenylases in acute leukemias [18], we opted to assess by means of computational transcriptomics the gene expression profiles of all known deadenylases in SCC as compared to healthy lung tissue serving as control
Upon Poly(A)-specific ribonuclease (PARN) silencing, we observed a significant increase of PTGIR mRNA levels (Fig. 4c), while it was undetectable in wild-type cells, in line with previous reports on the limited expression of the receptor in non-small-cell lung cancer (NSCLC) [29]
Summary
Lung cancer is the leading cause of cancer mortality worldwide, mainly due to late diagnosis, poor prognosis and tumor heterogeneity. Over the last decade, encouraging treatments have emerged, for adenocarcinoma This is not the case for SCC as diagnosis is often challenging and several immunohistochemical markers are used for its histological classification [2]. It is evident that there is a need for systematic classification of the molecular counterparts of lung tumors as well as the development of surrogates with respect to their phenotypic components, such as histological tumor type. These will contribute to the development of improved clinical prognostic tools and treatment strategies. The results of such studies provided molecular signatures that may be useful for the prediction of patient survival and response to therapy [7,8,9,10]
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