Dataset Information

Predicting the regrowth of clinically non-functioning pituitary adenoma with a statistical model.

ABSTRACT:

Background

Compared with clinically functioning pituitary adenoma (FPA), clinically non-functioning pituitary adenoma (NFPA) lacks of detectable hypersecreting serum hormones and related symptoms which make it difficult to predict the prognosis and monitoring for postoperative tumour regrowth. We aim to investigate whether the expression of selected tumour-related proteins and clinical features could be used as tumour markers to effectively predict the regrowth of NFPA.

Method

Tumour samples were collected from 295 patients with NFPA from Beijing Tiantan Hospital. The expression levels of 41 tumour-associated proteins were assessed using tissue microarray analyses. Clinical characteristics were analysed via univariate and multivariate logistic regression analyses. Logistic regression algorithm was applied to build a prediction model based on the expression levels of selected proteins and clinical signatures, which was then assessed in the testing set.

Results

Three proteins and two clinical signatures were confirmed to be significantly related to the regrowth of NFPA, including cyclin-dependent kinase inhibitor 2A (CDKN2A/p16), WNT inhibitory factor 1 (WIF1), tumour growth factor beta (TGF-?), age and tumour volume. A prediction model was generated on the training set, which achieved a fivefold predictive accuracy of 81.2%. The prediction ability was validated on the testing set with an accuracy of 83.9%. The area under the receiver operating characteristic curves (AUC) for the signatures were 0.895 and 0.881 in the training and testing sets, respectively.

Conclusion

The prediction model could effectively predict the regrowth of NFPA, which may facilitate the prognostic evaluation and guide early interventions.

SUBMITTER: Cheng S

PROVIDER: S-EPMC6528212 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Publications

Predicting the regrowth of clinically non-functioning pituitary adenoma with a statistical model.

Cheng Sen S Wu Jiaqi J Li Chuzhong C Li Yangfang Y Liu Chunhui C Li Guilin G Li Wuju W Hu Shuofeng S Ying Xiaomin X Zhang Yazhuo Y

Journal of translational medicine 20190520 1

<h4>Background</h4>Compared with clinically functioning pituitary adenoma (FPA), clinically non-functioning pituitary adenoma (NFPA) lacks of detectable hypersecreting serum hormones and related symptoms which make it difficult to predict the prognosis and monitoring for postoperative tumour regrowth. We aim to investigate whether the expression of selected tumour-related proteins and clinical features could be used as tumour markers to effectively predict the regrowth of NFPA.<h4>Method</h4>Tum ...[more]

PMID: 31109334

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Project description:BackgroundTumor surrounding the internal carotid artery or invading to the cavernous sinus is an important characteristic of invasive pituitary adenoma, and a pivotal factor of tumor residue and regrowth. Without specific changes in serum hormone related to the adenohypophyseal cell of origin, clinically non-functioning pituitary adenoma is more likely to be diagnosed at invasive stages compared with functioning pituitary adenoma. The underlying mechanism of tumor invasion remains unknown. In this study, we aimed to identify key genes in tumor invasion by integrating analyses of DNA methylation and gene expression profiles.MethodGenome-wide DNA methylation and mRNA microarray analysis were performed for tumor samples from 68 patients at the Beijing Tiantan Hospital. Differentially expressed genes and methylated probes were identified based on an invasive vs non-invasive grouping. Differentially methylated probes in the promoter region of targeted genes were assessed. Pearson correlation analysis was used to identify genes with a strong association between DNA methylation status and expression levels. Pyrosequencing and RT-PCR were used to validate the methylation status and expression levels of candidate genes, respectively.ResultsA total of 8842 differentially methylated probes, located on 4582 genes, and 661 differentially expressed genes were identified. Both promoter methylation and expression alterations were observed for 115 genes with 58 genes showing a negative correlation between DNA methylation status and expression level. Nineteen genes that exhibited notably negative correlations between DNA methylation and gene expression levels, are involved in various gene ontologies and pathways, or played an important role in different diseases, were regarded as candidate genes. We found an increased methylation with a decreased expression of PHYHD1, LTBR, C22orf42, PRR5, ANKDD1A, RAB13, CAMKV, KIFC3, WNT4 and STAT6, and a decreased methylation with an increased expression of MYBPHL. The methylation status and expression levels of these genes were validated by pyrosequencing and RT-PCR.ConclusionsThe DNA methylation and expression levels of PHYHD1, LTBR, MYBPHL, C22orf42, PRR5, ANKDD1A, RAB13, CAMKV, KIFC3, WNT4 and STAT6 are associated with tumor invasion, and these genes may become the potential genes for targeted therapy.

Project description:PurposeNon-functioning pituitary adenoma (NFPA) is a very common type of intracranial tumor, which can be locally invasive and can have a high recurrence rate. The tumor microenvironment (TME) shows a high correlation with tumor pathogenesis and prognosis. The current study aimed to identify microenvironment-related genes in NFPAs and assess their prognostic value.Methods73 NFPA tumor samples were collected from Beijing Tiantan Hospital and transcriptional expression profiles were obtained through microarray analysis. The immune and stromal scores of each sample were calculated through the ESTIMATE algorithm, and the patients were divided into high and low immune/stromal score groups. Intersection differentially expressed genes (DEGs) were then obtained to construct a protein-protein interaction (PPI) network. Potential functions and pathways of intersection DEGs were then analyzed through Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. The prognostic value of these genes was evaluated. The quantitative real-time polymerase chain reaction in another set of NFPA samples was used to confirm the credibility of the bioinformatics analysis.ResultsThe immune/stromal scores were significantly correlated with cavernous sinus (CS) invasion. The Kaplan-Meier curve indicated that the high immune score group was significantly related to poor recurrence-free survival. We identified 497 intersection DEGs based on the high vs. low immune/stromal score groups. Function enrichment analyses of 497 DEGs and hub genes from the PPI network showed that these genes are mainly involved in the immune/inflammatory response, T cell activation, and the phosphatidylinositol 3 kinase-protein kinase B signaling pathway. Among the intersection DEGs, 88 genes were further verified as significantly expressed between the CS invasive group and the non-invasive group, and five genes were highly associated with NFPA prognosis.ConclusionWe screened out a series of critical genes associated with the TME in NFPAs. These genes may play a fundamental role in the development and prognosis of NFPA and may yield new therapeutic targets.

Dataset Information

Predicting the regrowth of clinically non-functioning pituitary adenoma with a statistical model.

Background

Method

Results

Conclusion

Publications

Predicting the regrowth of clinically non-functioning pituitary adenoma with a statistical model.

Similar Datasets

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