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      Co-expression Network Analysis Elucidated a Core Module in Association With Prognosis of Non-functioning Non-invasive Human Pituitary Adenoma

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          Abstract

          Non-functioning pituitary adenomas (NFPAs) are tumors with clinically challenging features since they have insidious progression. A complex network of gene interactions is thought to have roles in tumor formation and progression. Therefore, revealing the genetic network behind NFPA tumorigenesis is not only essential to attain further knowledge of tumor biology, but also plays a fundamental role in the development of efficacious treatment strategies. Differential co-expression network analysis is an outstanding approach for elucidation of groups of genes which show distinct co-expression patterns among phenotypes. In this study, we carried out a differential co-expression network analysis of NFPA-associated transcriptome dataset ( n = 40) considering invasive ( n = 22) and non-invasive ( n = 18) phenotypes. Furthermore, we identified differentially co-expressed and co-regulated mRNA modules, which might be considered as potential systems biomarkers for NFPA prognosis and invasiveness. As a result, we have identified a novel 13-gene module, including CEACAM6, CYP4B1, EIF2S2, HID1, IFFO1, MYO18A, PDCD2, SGIP1, SWSAP1, and four unknown genes ( A_24_P127621, A_24_P255786, A_24_P683553, and A_24_P916979), which was able to categorize the patients into two groups as invasive and non-invasive NFPA with distinct prognosis. The prognostic core module genes were associated with progression and prognosis of brain and glandular based cancers as well. Furthermore, these module genes were also expressed in blood, salivary gland, and spinal cord tissues. These results may provide the evidence on featured gene module which might play a prominent role in NFPA prognosis and sub-typing as effective biomarkers and therapeutic targets in the future.

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          Most cited references 54

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          Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

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            SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis

            Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R.
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              Prevalence of pituitary adenomas: a community-based, cross-sectional study in Banbury (Oxfordshire, UK).

              Pituitary adenomas (PAs) are associated with increased morbidity and mortality. The optimal delivery of services and the provision of care for patients with PAs require distribution of the resources proportionate to the impact of these conditions on the community. Currently, the resource allocation for PAs in the health care system is lacking a reliable and an up-to-date epidemiological background that would reflect the recent advances in the diagnostic technologies, leading to the earlier recognition of these tumours. To determine the prevalence, the diagnostic delay and the characteristics of patients with PA in a well-defined geographical area of the UK (Banbury, Oxfordshire). Sixteen general practitioner (GP) surgeries covering the area of Banbury and a total population of 89 334 inhabitants were asked to participate in the study (data confirmed on 31 July 2006). Fourteen surgeries with a total of 81,449 inhabitants (91% of the study population) agreed to take part. All cases of PAs were found following an exhaustive computer database search of agreed terms by the staff of each Practice and data on age, gender, presenting manifestations and their duration, imaging features at diagnosis, history of multiple endocrine neoplasia type 1 and family history of PA were collected. A total of 63 patients with PA were identified amongst the study population of 81,149, with a prevalence of 77.6 PA cases/100,000 inhabitants (prolactinomas; PRLoma: 44.4, nonfunctioning PAs: 22.2, acromegaly; ACRO: 8.6, corticotroph adenoma: 1.2 and unknown functional status; UFS: 1.2/100,000 inhabitants). The distribution of each PA subtype was for PRLoma 57%, nonfunctioning PAs 28%, ACRO 11%, corticotroph adenoma 2% and UFS 2%. The median age at diagnosis and the duration of symptoms until diagnosis (in years) were for PRLoma 32.0 and 1.5, nonfunctioning PAs 51.5 and 0.8, ACRO 47 and 4.5 and corticotroph adenoma 57 and 7, respectively. PRLoma was the most frequent PA diagnosed up to the age of 60 years (0-20 years: 75% and 20-60 years: 61% of PAs) and nonfunctioning PA after the age of 60 years (60% of PAs). Nonfunctioning PAs dominated in men (57% of all men with PA) and PRLoma in women (76% of all women with PA). Five patients (7.9%) presented with classical pituitary apoplexy, with a prevalence of 6.2 cases/100,000 inhabitants. Based on a well-defined population in Banbury (Oxfordshire, UK), we have shown that PAs have a fourfold increased prevalence than previously thought; our data confirm that PAs have a higher burden on the Health Care System and optimal resource distribution for both clinical care and research activities aiming to improve the outcome of these patients are needed.
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                Author and article information

                Contributors
                Journal
                Front Endocrinol (Lausanne)
                Front Endocrinol (Lausanne)
                Front. Endocrinol.
                Frontiers in Endocrinology
                Frontiers Media S.A.
                1664-2392
                06 June 2019
                2019
                : 10
                Affiliations
                Department of Bioengineering, Marmara University , Istanbul, Turkey
                Author notes

                Edited by: Hidenori Fukuoka, Kobe University, Japan

                Reviewed by: Moises Mercado, Mexican Social Security Institute (IMSS), Mexico; Murat Aydin Sav, Yeditepe University, Turkey

                *Correspondence: Kazim Yalcin Arga kazim.arga@ 123456marmara.edu.tr

                This article was submitted to Pituitary Endocrinology, a section of the journal Frontiers in Endocrinology

                Article
                10.3389/fendo.2019.00361
                6563679
                Copyright © 2019 Aydin and Arga.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 10, Tables: 2, Equations: 1, References: 72, Pages: 15, Words: 8966
                Categories
                Endocrinology
                Original Research

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