Mass Spectrometry Technologies for Biomarkers Identification and Disease Diagnosis

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 2827

Special Issue Editor


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Guest Editor
Centro Cardiologico Monzino, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Via Parea 4, 20138 Milan, Italy
Interests: biomarkers; mass spectrometry; atherosclerosis; biochemistry; biotechnology; cardiovascular disease; molecular and cellular biology; pharmacology; proteomics

Special Issue Information

Dear colleagues,

The unmet need for highly accurate methods of disease biomarker identification and diagnosis poses new challenges for developments in laboratory medicine.

Mass spectrometry (MS) is an analytical technique used for determining the elemental composition of samples, quantifying the mass of particles and molecules, and elucidating the chemical structure of molecules. It provides both structural and quantitative data and can be used in a “global” or “targeted” manner allowing the identification of thousands of biomolecules (proteins, lipids, and metabolites) from a biological sample.

Various types of MS with high specificity, such as liquid chromatography (LC-MS), gas chromatography (GC-MS), and matrix-assisted laser desorption/ionization/time-of-flight (MALDI-TOF MS), are being increasingly valued and utilized as tools in clinical laboratories.

Advances in mass spectrometry-based disease biomarker discoveries are continuously expanding the clinical diagnostic landscape. Although a number of MS-based in vitro diagnostics are already adopted in routine clinical practices, more are expected to undergo transition from bench to bedside in the near future. These MS techniques can indeed overcome the limitations of immunoassays and offer many advantages over earlier approaches.

The high sensitivity, specificity, and high-throughput capacity of mass spectrometry in biomolecules detection render this technology highly powerful in disease detection and therapy monitoring, thus representing the novel paradigm in clinical diagnosis.

Dr. Cristina Banfi
Guest Editor

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Published Papers (1 paper)

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Research

17 pages, 2664 KiB  
Article
Does the Urinary Proteome Reflect ccRCC Stage and Grade Progression?
by Lucia Santorelli, Martina Stella, Clizia Chinello, Giulia Capitoli, Isabella Piga, Andrew Smith, Angelica Grasso, Marco Grasso, Giorgio Bovo and Fulvio Magni
Diagnostics 2021, 11(12), 2369; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics11122369 - 16 Dec 2021
Cited by 6 | Viewed by 2049
Abstract
Due its ability to provide a global snapshot of kidney physiology, urine has emerged as a highly promising, non-invasive source in the search for new molecular indicators of disease diagnosis, prognosis, and surveillance. In particular, proteomics represents an ideal strategy for the identification [...] Read more.
Due its ability to provide a global snapshot of kidney physiology, urine has emerged as a highly promising, non-invasive source in the search for new molecular indicators of disease diagnosis, prognosis, and surveillance. In particular, proteomics represents an ideal strategy for the identification of urinary protein markers; thus, a urinomic approach could also represent a powerful tool in the investigation of the most common kidney cancer, which is clear cell Renal Cell Carcinoma (ccRCC). Currently, these tumors are classified after surgical removal using the TNM and nuclear grading systems and prognosis is usually predicted based upon staging. However, the aggressiveness and clinical outcomes of ccRCC remain heterogeneous within each stratified group, highlighting the need for novel molecular indicators that can predict the progression of these tumors. In our study, we explored the association between the urinary proteome and the ccRCC staging and grading classification. The urine proteome of 44 ccRCC patients with lesions of varying severity was analyzed via label-free proteomics. MS data revealed several proteins with altered abundance according to clinicopathological stratification. Specifically, we determined a panel of dysregulated proteins strictly related to stage and grade, suggesting the potential utility of MS-based urinomics as a complementary tool in the staging process of ccRCC. Full article
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