Advances in the clinical application of high-throughput proteomics

Proteomics has become an essential area in medical research, propelled by the ability to quantitatively assess proteins on a large scale using high-throughput technologies. These technologies have unveiled new insights, such as the unexpected involvement of GAPDH in various cancers. While these findings have opened doors for clinical applications, they remain relatively limited, prompting the need to summarize recent advancements and explore future prospects.

Proteomic Technologies

The review elaborates on four key high-throughput proteomic techniques: mass spectrometry (MS), protein pathway array (PPA), next-generation tissue microarrays (ngTMA), and multiplex bead- or aptamer-based assays like Luminex® and Simoa®. Each of these techniques has unique strengths and limitations that dictate their appropriate usage in different clinical contexts. MS, for example, is crucial for analyzing protein isoforms and post-translational modifications, while PPA and ngTMA are better suited for large-scale antibody-based molecular analyses.

Advances in Clinical Applications

High-throughput proteomics has been instrumental in various fields, particularly cancer research. The review delves into its application across several types of cancers:

• Breast Cancer: Studies using PPA and mRNA microarrays have revealed significant pathway alterations and protein expressions, highlighting the complex regulatory mechanisms at play in breast cancer.
• Colorectal Cancer: Proteomics has identified key metabolic pathways and potential biomarkers for early detection, with studies employing gas chromatography-mass spectrometry and high-density antibody microarrays.
• Gastric Cancer: Proteomics has identified differentially expressed proteins and potential biomarkers, contributing to better understanding and treatment strategies for this cancer type.
• Bladder Cancer: The review discusses how proteomics has provided insights into diagnostic markers and therapeutic targets, utilizing advanced MS techniques to identify significant protein markers.
• Laryngeal Squamous Cell Carcinoma: Proteomic studies have uncovered potential biomarkers and developed risk models that could predict prognosis and guide treatment.
• COVID-19: The review also touches on the rapid application of high-throughput proteomics in understanding SARS-CoV-2, where it has been used to uncover host cell pathways affected by the virus, aiding in the development of potential treatments and vaccines.

Challenges

Several challenges hinder the broader clinical application of high-throughput proteomics:

• Protein Stability and Degradation: Proteins are more susceptible to degradation compared to DNA, complicating proteomic analyses.
• Statistical Modeling: Inappropriate data normalization can lead to inaccurate conclusions, highlighting the need for robust statistical models tailored to specific proteomic data.
• Data Integration: Integrating proteomic data with other omics data types remains challenging, especially given the limited availability of comprehensive data repositories.
• Clinical Validation: Moving proteomic discoveries into clinical practice requires rigorous validation, which is often hindered by the complexity of real-world clinical environments.

Advantages

Despite these challenges, high-throughput proteomics offers several advantages:

• Global Networks: Proteomics enables the exploration of complex protein-protein interactions and signaling networks, providing a global view of disease mechanisms.
• Discovery of New Proteins: MS-based methods allow for the discovery of novel proteins without the need for specific antibodies, making it a powerful tool for biomarker discovery.
• Synergy with Multi-omics: Integrating proteomic data with genomic and transcriptomic data can provide a comprehensive understanding of disease pathogenesis, leading to more effective personalized treatments.

Future Directions

The review outlines several promising areas for future research in high-throughput proteomics:

• Single-Cell Biology: Single-cell proteomics could revolutionize our understanding of cellular heterogeneity in diseases, offering insights at an unprecedented resolution.
• Individualized Proteomics: Personalized medicine will benefit from proteomic analyses tailored to individual patients, taking into account unique genetic and environmental factors.
• Digital Pathology and Deep Learning: The integration of proteomics with digital pathology and AI could enhance diagnostic accuracy and streamline data analysis.
• New Technologies: Emerging technologies such as 4-D proteomics and secondary ion mass spectrometry promise to further expand the capabilities of proteomics in clinical settings.

Conclusions

The clinical application of high-throughput proteomics is set to grow significantly, driven by technological innovations and the increasing integration of proteomics with other omic data types. Overcoming current challenges will be crucial in realizing the full potential of proteomics in transforming translational research, clinical practice, and public health.

 

Full text:

https://www.xiahepublishing.com/2472-0712/ERHM-2024-00006

 

The study was recently published in the Exploratory Research and Hypothesis in Medicine.

Exploratory Research and Hypothesis in Medicine (ERHM) publishes original exploratory research articles and state-of-the-art reviews that focus on novel findings and the most recent scientific advances that support new hypotheses in medicine. The journal accepts a wide range of topics, including innovative diagnostic and therapeutic modalities as well as insightful theories related to the practice of medicine. The exploratory research published in ERHM does not necessarily need to be comprehensive and conclusive, but the study design must be solid, the methodologies must be reliable, the results must be true, and the hypothesis must be rational and justifiable with evidence.

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