Application of Proteomics in Cancer: Recent Trends and Approaches for Biomarkers Discovery

Abstract

Proteomics has become an important field in molecular sciences, as it provides valuable information on the identity, expression levels, and modification of proteins. For example, cancer proteomics unraveled key information in mechanistic studies on tumor growth and metastasis, which has contributed to the identification of clinically applicable biomarkers as well as therapeutic targets. Several cancer proteome databases have been established and are being shared worldwide. Importantly, the integration of proteomics studies with other omics is providing extensive data related to molecular mechanisms and target modulators. These data may be analyzed and processed through bioinformatic pipelines to obtain useful information. The purpose of this review is to provide an overview of cancer proteomics and recent advances in proteomic techniques. In particular, we aim to offer insights into current proteomics studies of brain cancer, in which proteomic applications are in a relatively early stage. This review covers applications of proteomics from the discovery of biomarkers to the characterization of molecular mechanisms through advances in technology. Moreover, it addresses global trends in proteomics approaches for translational research. As a core method in translational research, the continued development of this field is expected to provide valuable information at a scale beyond that previously seen.

Enhancing the therapeutic efficacy of nanoparticles for cancer treatment using versatile targeted strategies

“…A number of receptors are overexpressed on the tumor cell surface, which enables them to be distinguished from healthy cells at the molecular level. Moreover, the progressive use of tumor proteomics and bioinformatics has contributed significantly to the discovery of these specific receptors [ 24 ]. The addition of specific ligands on the nanoplatform surfaces allows them to selectively target tumor cells.…”

Machine Learning: A New Prospect in Multi-Omics Data Analysis of Cancer

“…At the broader level of the omics branches, the proteomics field can be defined, which studies all the contents of the expressed proteins in the cells. Since proteomes are the result of gene expression and are also involved in biological structures and processes, applying proteomics to study cancers can open new doors into discovering novel prognostic, diagnostic, and therapeutic approaches as well as classification of tumors (Kwon et al, 2021). In this regard, methods such as mass spectrometry (MS), enzyme-linked immunosorbent assay, immunoblotting (western blot), and protein microarray can help gain broad insights into cell proteomes and identify processes involved in cancer (Panis et al, 2019).…”

Wheat Proteomics for Abiotic Stress Tolerance and Root System Architecture: Current Status and Future Prospects

“…Identified proteins together with their biological functions of stress tolerance and RSA, can be used as protein markers or genetic markers (genes that encode those proteins) development for marker-assisted breeding or genetic engineering; 2DE = two- dimensional gel electrophoresis; 2DE-PAGE = 2D polyacrylamide gel electrophoresis; 2D-DIGE = 2D difference gel electrophoresis; SWATH-MS = sequential window acquisition of all theoretical fragment ion spectra mass spectrometry; iTRAQ = isobaric tags for relative and absolute quantitation; TMT = tandem mass tag; MALDI-TOF = matrix-assisted laser desorption/ionization- time-of-fight; Q-TOF = quadrupole- time-of-fight and ESI = electrospray ionization. Images of LC-MS, a protein structure, wheat plant and mitochondria are modified from different sources [ 41 , 42 , 43 , 44 ].…”