A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy

ABSTRACT

Introduction

Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation.

Areas covered

This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches.

Expert opinion

Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Plain Language Summary

Brain tumors are complex and diverse types of cancer that present significant challenges in their diagnosis, prognosis, and treatment. Proteomics, a field that focuses on studying proteins and their functions on a large scale has emerged as a powerful tool for understanding how brain tumors work at the molecular level. In this review, we offer a detailed look into the role of proteomics in studying brain tumor regulation, discussing recent advancements and insights gained from proteomic techniques. We explore various mass spectrometry-based proteomic methods, which help uncover unique protein patterns associated with brain tumors. By analyzing changes in protein expression, modifications, interactions, and location within cells, researchers have gained important knowledge about the underlying mechanisms of brain tumors. Proteomics also plays a crucial role in identifying potential biomarkers for early detection, predicting patient outcomes, and developing targeted therapies and immunotherapies. However, there are still challenges to overcome, such as integrating data from different ‘omics’ fields, standardizing protocols and analysis procedures and utilizing artificial intelligence to interpret complex proteomic data. We require more robust attempts at validating and translating all these findings for patient benefit.

KEYWORDS:

• Proteomics
• brain tumors
• medulloblastoma
• glioma
• meningioma
• biomarkers
• integrative omics
• signaling pathways

Acknowledgement

Parts of the figures were drawn by using pictures from Servier Medical Art. Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License (https://creativecommons.org/licenses/by/3.0/).

Article highlights

• Brain tumors are complex entities with multiple heterogeneities within diagnoses, leading to several difficulties in diagnosis, treatment, and management.

• There are multiple advanced tools in proteomics that are used to study brain tumors.

• Handling and standardizing big datasets generated from such tools is really crucial.

• Various platforms like HPM and CPTAC have come up with the aim to integrate high-quality data into a single resource platform.

• Advancement in proteomic technologies, and its integration with other omics datasets, has aided in determining various biomarkers; which can be used for diagnostic and prognostic purposes.

• Important signaling pathways belonging to various diagnoses can be targeted at the multi-nodal level for effective patient treatment and recovery.

• The path ahead requires thorough pre-clinical validation of the discoveries for effective clinical benefit.

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was funded by MHRD-UAY (UCHHATAR AVISHKAR YOJANA), project #34_IITB (2016) to SS and MASSFIIT (Mass Spectrometry Facility, IIT Bombay) for MS-based proteomics work (BT/PR13114/INF/22/206/2015). We also thank MERCK-COE (DO/2021-MLSP).