The use of mass spectrometry in a proteome‐centered multiomics study of human pituitary adenomas

• Published in: Mass spectrometry reviews Vol. 41; no. 6; pp. 964 - 1013
• Main Authors: Li, Na, Desiderio, Dominic M., Zhan, Xianquan
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01.11.2022
• Subjects: Adenoma; Biomarkers; Brain cancer; Cancer; Drug development; Mass spectrometry; Mass spectroscopy; Metabolomics; Molecular modelling; molecular networks; multiomics; phenomics; Pituitary; pituitary adenoma; Pituitary gland; Proteomes; Proteomics; Scientific imaging; Therapeutic applications; Therapeutic targets; Transcriptomes; Tumorigenesis; Tumors
• ISSN: 0277-7037; 1098-2787; 1098-2787
• DOI: 10.1002/mas.21710

A pituitary adenoma (PA) is a common intracranial neoplasm, and is a complex, chronic, and whole‐body disease with multicausing factors, multiprocesses, and multiconsequences. It is very difficult to clarify molecular mechanism and treat PAs from the single‐factor strategy model. The rapid development of multiomics and systems biology changed the paradigms from a traditional single‐factor strategy to a multiparameter systematic strategy for effective management of PAs. A series of molecular alterations at the genome, transcriptome, proteome, peptidome, metabolome, and radiome levels are involved in pituitary tumorigenesis, and mutually associate into a complex molecular network system. Also, the center of multiomics is moving from structural genomics to phenomics, including proteomics and metabolomics in the medical sciences. Mass spectrometry (MS) has been extensively used in phenomics studies of human PAs to clarify molecular mechanisms, and to discover biomarkers and therapeutic targets/drugs. MS‐based proteomics and proteoform studies play central roles in the multiomics strategy of PAs. This article reviews the status of multiomics, multiomics‐based molecular pathway networks, molecular pathway network‐based pattern biomarkers and therapeutic targets/drugs, and future perspectives for personalized, predeictive, and preventive (3P) medicine in PAs.