MALDI-TOF Mass Spectrometry in Clinical Analysis and Research

Li, Dandan; Yi, Jia; Han, Guobin; Qiao, Liang

doi:10.1021/acsmeasuresciau.2c00019

Cited by 40 publications

(26 citation statements)

References 119 publications

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“…MALDI-TOF MS is increasingly gaining ground in research and clinical laboratories. 35,36 MALDI-TOF MS technology has high sensitivity, high analytical power, and high resolution and will be important in M-protein identification in the future. [19][20][21] The increase in the use of MALDI-TOF MS-based techniques in detecting M-proteins has prompted the IMWG to submit suggestions on using MALDI-TOF MS in PCDs and to encourage more research on MALDI-TOF MS. 37 Recently, MALDI-TOF MS method was developed to detect M-proteins in serum.…”

Section: Discussionmentioning

confidence: 99%

Rapid detection of serum free light chains by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Kaya

Serdar

Aksungar

et al. 2023

Eur J Mass Spectrom (Chichester)

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Introduction: Serum free light chain (FLC) measurements are increasingly prominent for patients with plasma cell disorders (PCDs) in screening, prognostic stratification, and monitoring therapy responses. Objectives: We aimed to develop a sensitive, reliable, and accurate method for diagnosing PCDs that can notably decrease the time and cost of current methods. Methods: Here, we present a novel approach for FLC measurement using immunoenrichment on micro-affinity chromatography in combination with matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) detection. In this study, serum free kappa (κ) and free lambda (λ) light chain (LC) levels in the serum of 105 patients were compared between the nephelometric serum FLC quantification and MALDI-TOF MS detection. Results: Cohen's kappa coefficient between the MALDI-TOF MS-based method and the FLC assay revealed an almost perfect agreement in the case of normal (negative) results (κ = 0.92; 95% confidence interval (CI): 0.837 to 0.968) and a good agreement in the case of increased (positive) results (κ = 0.76; 95% CI: 0.608 to 0.870). In Spearman's correlation analysis, the best correlation was found between serum free κ/λ ratios (r = 0.628, 0.496 to 0.732; p <0.0001). Our method showed sensitivity (92.5%) and specificity (76.3%) for discrimination between the κ/λ FLC ratio compared to the serum FLC assay. Conclusion: The proposed method can significantly contribute to diagnosing and monitoring PCDs as it can significantly be time-saving, cost-effective in FLC measurement.

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Section: Discussionmentioning

confidence: 99%

Rapid detection of serum free light chains by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Kaya

Serdar

Aksungar

et al. 2023

Eur J Mass Spectrom (Chichester)

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“…MALDI mass spectrometry imaging (MALDI-MSI) is a powerful technique by which the spatial and temporal distribution of proteoforms and biomolecules can be investigated directly from a tissue section without the need for extraction, purification, and separation measures [ 79 ]. The MSI is based on the mapping of the corresponding ion intensities along with the determination of the spatial distribution of many molecules in a sample.…”

Section: Advances In Proteomic Technologies Used In the Study Of Cancermentioning

confidence: 99%

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Punetha

Kotiya

2023

Proteomes

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Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

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“…Transcriptomics can either refer to exploratory analysis of the entire transcriptome, primarily using RNA sequencing (RNA-seq) [34], or to targeted analysis of known RNAs using techniques such as gene expression panels (GEPs). Of all MS-based quantitative strategies, in the analysis of nucleic acids most often used is matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS), recently improved with the time-of-flight (ToF) feature [35]. This appliance should nevertheless recoil due to high initial costs, especially since it does not require trained laboratory personnel [36].…”

Section: Ms-based Quantitative Strategies and Analysis Of Proteome Ge...mentioning

confidence: 99%

Mass Spectrometry-Based Techniques Towards OMICS 2.0

Šoša¹

2023

Preprint

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The literature was scoped to help place mass spectrometric (MS) platforms in the spotlight of the life sciences, as a tool of OMICS and OMICS 2.0 technologies. Moreover, today’s appliances are so handy, that they literally place a whole lab on a single chip. Methods of OMICS (and the most recently developed term OMICS 2.0) are tackled, having in mind their aptness for educational purposes, as well as their feasibility. This same topic was highlighted in many reviews that have been periodically published. The author’s initial interest was the forensic application of MS, but since these interests changed, terms such as “biosensors” were also examined, so the review included means of discovery of efficient biomarkers and clinical therapeutic targets. Aside from simply reviewing the research status and the future perspectives, this article tackles terms such as Society 5.0 and OMICS 2.0. However, within the framework of this review, physical chemistry, bioinformatics, or specific software solutions were not specifically studied. Since the topic of generating permanent collections of digital content for retrospective analysis was also reviewed, the need for loads of data – cloud storage was discussed in the context of MS. These large quantities of data are easier to operate with if generated by MS, rather than by any other commercially available assay. In this manner, the review has strengthened an in-depth understanding of the applications of MS.

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MALDI-TOF Mass Spectrometry in Clinical Analysis and Research

Cited by 40 publications

References 119 publications

Rapid detection of serum free light chains by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Rapid detection of serum free light chains by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Mass Spectrometry-Based Techniques Towards OMICS 2.0

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