Literature DB >> 34567287

Overview of omics biomarkers in pituitary neuroendocrine tumors to design future diagnosis and treatment strategies.

Busra Aydin1, Aysegul Caliskan1,2, Kazim Yalcin Arga1,3.   

Abstract

Pituitary neuroendocrine tumors (PitNETs) are the second most common type of intracranial neoplasia. Since their manifestation usually causes hormone hypersecretion, effective management of PitNETs is indisputably necessary. Most of the non-functioning PitNETs pose a real challenge in diagnosis as they grow without giving any signs. Despite the good response of prolactinomas to dopamine agonist therapy, some of these tumors persist or recur; also, about 20% are resistant and 10% behave aggressively. The silent corticotropinomas may not cause symptoms until the tumor mass causes a complication. In somatotropinomas, the possibility of recurrence after transsphenoidal resection is more common in pediatric patients than in adult patients. Therefore, detection of tumors at early stages or identification of recurrence and remission after transsphenoidal surgery would allow wiser management of the disease. Extensive studies have been performed to uncover potential signatures that can be used for preventive diagnosis and/or prognosis of PitNETs as well as for targeted therapy. These molecular signatures at multiple biological levels hold promise for the convergence of preventive approaches and patient-centered disease management and offer potential therapeutic strategies. In this review, we provide an overview of the omics-based biomarker research and highlight the multi-omics signatures that have been proposed as pitNET biomarkers. In addition, understanding the multi-omics data integration of current biomarker discovery strategies was discussed in terms of preventive, predictive, and personalized medicine. The topics discussed in this review will help to develop broader visions for pitNET research, diagnosis, and therapy, particularly in the context of personalized medicine. © European Association for Predictive, Preventive and Personalised Medicine (EPMA) 2021.

Entities:  

Keywords:  Biomarkers; Multi-omics data integration; Omics biomarkers; Pituitary adenoma; Pituitary neuroendocrine tumors; Predictive preventive personalized medicine

Year:  2021        PMID: 34567287      PMCID: PMC8417171          DOI: 10.1007/s13167-021-00246-1

Source DB:  PubMed          Journal:  EPMA J        ISSN: 1878-5077            Impact factor:   8.836


  108 in total

1.  Patterns of gene expression in pituitary carcinomas and adenomas analyzed by high-density oligonucleotide arrays, reverse transcriptase-quantitative PCR, and protein expression.

Authors:  Katharina H Ruebel; Alexey A Leontovich; Long Jin; Gail A Stilling; Heyu Zhang; Xiang Qian; Nobuki Nakamura; Bernd W Scheithauer; Kalman Kovacs; Ricardo V Lloyd
Journal:  Endocrine       Date:  2006-06       Impact factor: 3.633

2.  Exosomal hsa-miR-21-5p derived from growth hormone-secreting pituitary adenoma promotes abnormal bone formation in acromegaly.

Authors:  Yuanyuan Xiong; Yongjian Tang; Fan Fan; Yu Zeng; Chuntao Li; Gaofeng Zhou; Zhongliang Hu; Liyang Zhang; Zhixiong Liu
Journal:  Transl Res       Date:  2019-08-10       Impact factor: 7.012

3.  Nitroproteins from a human pituitary adenoma tissue discovered with a nitrotyrosine affinity column and tandem mass spectrometry.

Authors:  Xianquan Zhan; Dominic M Desiderio
Journal:  Anal Biochem       Date:  2006-06-05       Impact factor: 3.365

4.  Pituitary disease in MEN type 1 (MEN1): data from the France-Belgium MEN1 multicenter study.

Authors:  Bruno Vergès; Françoise Boureille; Pierre Goudet; Arnaud Murat; Albert Beckers; Geneviève Sassolas; Patrick Cougard; Béatrice Chambe; Corinne Montvernay; Alain Calender
Journal:  J Clin Endocrinol Metab       Date:  2002-02       Impact factor: 5.958

5.  Down-regulation of Wee1 kinase by a specific subset of microRNA in human sporadic pituitary adenomas.

Authors:  Henriett Butz; István Likó; Sándor Czirják; Péter Igaz; Mohammed Munayem Khan; Vladimir Zivkovic; Katalin Bálint; Márta Korbonits; Károly Rácz; Attila Patócs
Journal:  J Clin Endocrinol Metab       Date:  2010-07-28       Impact factor: 5.958

6.  Molecular pathogenesis of human prolactinomas identified by gene expression profiling, RT-qPCR, and proteomic analyses.

Authors:  Chheng-Orn Evans; Carlos S Moreno; Xianquan Zhan; Michael T McCabe; Paula M Vertino; Dominic M Desiderio; Nelson M Oyesiku
Journal:  Pituitary       Date:  2008       Impact factor: 4.107

7.  Quantitative Analysis of Proteome in Non-functional Pituitary Adenomas: Clinical Relevance and Potential Benefits for the Patients.

Authors:  Tingting Cheng; Ya Wang; Miaolong Lu; Xiaohan Zhan; Tian Zhou; Biao Li; Xianquan Zhan
Journal:  Front Endocrinol (Lausanne)       Date:  2019-12-05       Impact factor: 5.555

8.  Differential Interactome Proposes Subtype-Specific Biomarkers and Potential Therapeutics in Renal Cell Carcinomas.

Authors:  Aysegul Caliskan; Gizem Gulfidan; Raghu Sinha; Kazim Yalcin Arga
Journal:  J Pers Med       Date:  2021-02-23

9.  Position paper of the EPMA and EFLM: a global vision of the consolidated promotion of an integrative medical approach to advance health care.

Authors:  Olga Golubnitschaja; Ian D Watson; Elizabeta Topic; Sverre Sandberg; Maurizio Ferrari; Vincenzo Costigliola
Journal:  EPMA J       Date:  2013-05-10       Impact factor: 6.543

10.  TMT-based quantitative proteomics revealed follicle-stimulating hormone (FSH)-related molecular characterizations for potentially prognostic assessment and personalized treatment of FSH-positive non-functional pituitary adenomas.

Authors:  Ya Wang; Tingting Cheng; Miaolong Lu; Yun Mu; Biao Li; Xuejun Li; Xianquan Zhan
Journal:  EPMA J       Date:  2019-08-29       Impact factor: 6.543

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  2 in total

1.  Functional metabolome profiling may improve individual outcomes in colorectal cancer management implementing concepts of predictive, preventive, and personalized medical approach.

Authors:  Yu Yuan; Chenxin Yang; Yingzhi Wang; Mingming Sun; Chenghao Bi; Sitong Sun; Guijiang Sun; Jingpeng Hao; Lingling Li; Changliang Shan; Shuai Zhang; Yubo Li
Journal:  EPMA J       Date:  2022-01-27       Impact factor: 6.543

2.  Plasma complement C7 as a target in non-small cell lung cancer patients to implement 3P medicine strategies.

Authors:  Jae Gwang Park; Beom Kyu Choi; Youngjoo Lee; Eun Jung Jang; Sang Myung Woo; Jun Hwa Lee; Kyung-Hee Kim; Heeyoun Hwang; Wonyoung Choi; Se-Hoon Lee; Byong Chul Yoo
Journal:  EPMA J       Date:  2021-11-25       Impact factor: 6.543

  2 in total

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