Dataset Information

Biomarker Discovery for Immunotherapy of Pituitary Adenomas: Enhanced Robustness and Prediction Ability by Modern Computational Tools.

ABSTRACT: Pituitary adenoma (PA) is prevalent in the general population. Due to its severe complications and aggressive infiltration into the surrounding brain structure, the effective management of PA is required. Till now, no drug has been approved for treating non-functional PA, and the removal of cancerous cells from the pituitary is still under experimental investigation. Due to its superior specificity and safety profile, immunotherapy stands as one of the most promising strategies for dealing with PA refractory to the standard treatment, and various studies have been carried out to discover immune-related gene markers as target candidates. However, the lists of gene markers identified among different studies are reported to be highly inconsistent because of the greatly limited number of samples analyzed in each study. It is thus essential to substantially enlarge the sample size and comprehensively assess the robustness of the identified immune-related gene markers. Herein, a novel strategy of direct data integration (DDI) was proposed to combine available PA microarray datasets, which significantly enlarged the sample size. First, the robustness of the gene markers identified by DDI strategy was found to be substantially enhanced compared with that of previous studies. Then, the DDI of all reported PA-related microarray datasets were conducted to achieve a comprehensive identification of PA gene markers, and 66 immune-related genes were discovered as target candidates for PA immunotherapy. Finally, based on the analysis of human protein?protein interaction network, some promising target candidates (GAL, LMO4, STAT3, PD-L1, TGFB and TGFBR3) were proposed for PA immunotherapy. The strategy proposed together with the immune-related markers identified in this study provided a useful guidance for the development of novel immunotherapy for PA.

SUBMITTER: Yang Q

PROVIDER: S-EPMC6337483 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Biomarker Discovery for Immunotherapy of Pituitary Adenomas: Enhanced Robustness and Prediction Ability by Modern Computational Tools.

Yang Qingxia Q Wang Yunxia Y Zhang Song S Tang Jing J Li Fengcheng F Yin Jiayi J Li Yi Y Fu Jianbo J Li Bo B Luo Yongchao Y Xue Weiwei W Zhu Feng F

International journal of molecular sciences 20190103 1

Pituitary adenoma (PA) is prevalent in the general population. Due to its severe complications and aggressive infiltration into the surrounding brain structure, the effective management of PA is required. Till now, no drug has been approved for treating non-functional PA, and the removal of cancerous cells from the pituitary is still under experimental investigation. Due to its superior specificity and safety profile, immunotherapy stands as one of the most promising strategies for dealing with ...[more]

PMID: 30609812

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Project description:BackgroundComplete resection of invasive pituitary adenoma is usually difficult, resulting in a high recurrence rate. Therefore, it is needed to find potential diagnostic markers and therapeutic targets for invasive pituitary adenoma.MethodsWe collected samples from patients with invasive and non-invasive pituitary adenomas from Beijing Tiantan Hospital for protein extraction and quantitative analysis. We identified differential proteins (DEPs) by differential analysis of the two groups. The intersection of differential proteins related to invasion and epithelial-mesenchymal transition (EMT) in the GeneCards database was identified as EMT-DEPs. The protein network of EMT-DEPs was analyzed using the STRING database and Cytoscape software, and the hub EMT-DEPs were obtained by the MCC algorithm of the cytoHubba plugin. Correlation analysis was used to obtain the interpairing proteins among EMT-DEPs, and core EMT-DEPs were identified based on the number of paired proteins. The Venn program was used to identify the intersection of hub EMT-DEPs and core EMT-DEPs as key EMT-DEPs. Finally, a series of analyses plus experiments were used to verify the correlation of the target protein with invasion and EMT in pituitary adenoma.ResultsQuantitative comparison of proteins between invasive and non-invasive pituitary adenomas indicated 833 differential proteins. The overlaps of EMT-related proteins and differential proteins consisted of 46 EMT-DEPs. There were 6 intersections between the hub EMT-DEPs and core EMT-DEPs. Using quantitative protein data and GSE169498 chip, we found that solute carrier family 2 member 1 (SLC2A1) was our target protein. SLC2A1 was significantly correlated with the invasiveness of pituitary adenoma, and the ROC curve was satisfactory. The functions and pathways of SLC2A1 and paired protein enrichment were closely linked to the EMT. Consistently, SLC2A1 expression was significantly and positively correlated with the expression of classical markers of EMT. The final experiment revealed that SLC2A1 was significantly upregulated in invasive pituitary adenoma.ConclusionSLC2A1 is significantly upregulated in invasive pituitary adenoma with satisfactory predictive value. It may regulate EMT. It may be a potential diagnostic marker for invasive pituitary adenoma.

Project description:Background and aimAbout a third of Pituitary Neuroendocrine Tumors (PitNETs) may show aggressive behavior. Many efforts have been performed for identifying possible predictive factors to early determine the future behavior of PitNETs. Programmed cell death ligand 1 (PD-L1) expression was associated with a more aggressive biology in different solid tumors, but its role in PitNET is not well-established yet. Our study aims to analyze PD-L1 expression in a surgical cohort of PitNETs to determine its association with radiological invasion and pathology findings, as well as with long-term recurrence rates.MethodsWe performed a retrospective analysis in a series of 86 PitNETs. Clinical presentation and radiological features of the preoperative period were collected, as well as pathological data and follow-up data. The rate of PD-L1 expression was immunohistochemically evaluated and expressed as a tumor proportion score (TPS). We assessed its relationship with cavernous sinus invasion and Trouillas' classification as primary outcomes. Secondary outcomes included the TPS' relationship with histopathological markers of proliferation, hormonal expression, tumor size and long-term recurrence rates. We calculated the optimal cut-point for the primary outcomes while maximizing the product of the sensitivity and specificity and then we evaluated the significance of secondary outcomes with logistic regression analysis.ResultsEighty-six patients were included in the analysis; 50 cases were non-functional PitNETs. The TPS for PD-L1 showed a highly right-skewed distribution in our sample, as 30.2% of patients scored 0. Using Trouillas' classification, we found that "proliferative" cases have a significantly higher probability to express PD-L1 in more than 30% of tumor cells (OR: 5.78; CI 95%: 1.80-18.4). This same cut-point was also associated with p53 expression. A positive association was found between PD-L1 expression and GH expression (p = 0.001; OR: 5.44; CI 95%: 1.98-14.98), while an inverse relationship was found with FSH/LH expression (p = 0.014; OR = 0.27, CI 95%: 0.10-0.76). No association was found with CS invasion, tumor size, bone erosion or dura invasion. We could not find any association between PD-L1 expression and recurrence.ConclusionsPD-L1 expression was associated with proliferative grades of Trouillas' classification and p53 expression. We also confirmed a higher expression of PD-L1 in somatotroph tumors. Larger studies are necessary to investigate the relationship between PD-L1 expression and aggressive behaviors.

Project description:Background: Dopamine agonists (DA) are the first line therapy for prolactinoma and symptomatic hyperprolactinemia; use as an adjuvant treatment for acromegaly and Cushing's disease is rare. Some patients develop de novo psychiatric symptoms or have exacerbation of pre-existing conditions during DA therapy. A practical, clinically sensitive depression and impulse control disorders (ICD; particularly hypersexuality and gambling disorders) detection tool is important for identifying at risk patients. The Barratt Impulsivity Scale (BIS-11) and the 9-item Patient Health Questionnaire (PHQ-9) are sensitive in identifying impulsivity and depression. Objective: Detail use of the BIS-11 and PHQ-9 as screening tools for depression and ICD in patients with pituitary disease at a high-volume academic pituitary center. Methods: DA-treated and naïve patients with pituitary disease were included. Patients with a known history of depression or psychiatric disorder were excluded. PHQ-9 standardized interpretation criteria were utilized to classify depression severity. For BIS-11, threshold was established based on previous studies. Statistical analysis was with SPSS version 25. Results: Seventy-six DA-treated and 27 naïve patients were included. Moderate and moderately severe depression were more prevalent in DA-treated patients; severe depression only found in DA-treated patients. A normal BIS-11 score was noted in 76.69%; higher scores (not significant) were noted in DA-treated patients. There was a positive correlation between higher BIS-11 and PHQ-9 scores; higher in DA-treated patients (r = 0.52, p < 0.001) than DA-naïve patients. Patients with BIS-11 scores ≥60 were younger and received lower cumulative DA doses compared to patients with BIS scores <60. There was no association between male sex and BIS-11 ≥60 and male sex did not increase the odds of increased scores (OR = 0.66, CI95% 0.25-1.76, p = 0.41). No significant difference was found for macroadenoma, prolactin levels, testosterone levels, hypogonadism, testosterone replacement in men, and increased impulsivity or depression scores. Conclusion: Use of PHQ-9 and BIS-11 is practical for routine screening of depression and ICD during outpatient pituitary clinic visits for patients with pituitary disease both naïve to treatment and during DA therapy. We recommend close follow-up after initiation of DA therapy for younger patients, regardless of dose.

Dataset Information

Biomarker Discovery for Immunotherapy of Pituitary Adenomas: Enhanced Robustness and Prediction Ability by Modern Computational Tools.

Publications

Biomarker Discovery for Immunotherapy of Pituitary Adenomas: Enhanced Robustness and Prediction Ability by Modern Computational Tools.

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