Expert Review of Proteomics最新文献

Introduction: Blood-based tau proteoforms have emerged as specific, scalable biomarkers of Alzheimer's pathology, addressing the limitations of symptom-based diagnosis, neuroimaging, and invasive cerebrospinal fluid (CSF) testing. This review synthesizes advances in tau phosphorylation and truncation biology, evaluates translation from CSF to plasma with state-of-the-art proteomics, and outlines the analytical standards and cross-matrix calibration needed for clinical adoption.

Areas covered: We conducted a literature search in PubMed and Google Scholar. We reviewed studies published between January 2005 and September 2025 investigating tau proteoforms in Alzheimer's disease.

Expert opinion: Blood-based tau proteoforms are poised to move Alzheimer's diagnostics from specialized imaging to accessible frontline testing, with plasma p-tau217 approaching positron emission tomography (PET) and CSF performance and multi-analyte panels with glial fibrillary acidic protein (GFAP) or neurofilament light (NfL) improving differential diagnosis while reducing invasiveness and cost. Building on the first FDA-cleared plasma assay (Lumipulse G p-tau217/Aβ1-42 Ratio) in May 2025, we anticipate a dual pathway over the next decade in which referral centers use high-plex mass spectrometry (MS) panels for phosphoforms and truncations, while primary care adopts automated high-throughput immunoassays (e.g. chemiluminescent enzyme immunoassay (CLEIA)) for triage, supported by harmonized standard operating procedures (SOPs), cross-matrix calibration, and robust reference materials.

Introduction: Mass spectrometry (MS)-based proteomics, especially the targeted applications, hold great potential as Laboratory Developed Tests (LDTs) for clinical applications. They are suitable for widespread clinical use due to their impressive sample/protein multiplexing capabilities, analytical sensitivity and replicability, adaptability to diverse clinical samples, and highly evolved sample processing protocols. Although multiple LDTs have been developed and approved by regulatory agencies, various areas still need improvement.

Areas covered: This article focuses on introducing MS-based LDT as a potential clinical technology, its superiority over low-throughput or antibody-based methods, existing hurdles in the adoption of such LDTs in clinics, what they can adopt to, and regulatory and analytical considerations that need to be addressed to develop a robust MS-based LDT.

Expert opinion: Recent efforts to optimize instrumentation and sample preparation for MS-based applications have made these LDTs promising contenders for clinical utilization. With focused research to answer quality assessment requirements, data interpretability, method scalability, and ease of use, MS-based LDTs can revolutionize clinical diagnostics. Drawing parallels to other omics technologies, these LDTs can address the long-standing multiplexing hinge and further establish multi-protein diagnostics as next-generation diagnostics of low-throughput methods.

Introduction: Protein tyrosine sulfation is of growing scientific interest due to its biological and clinical significance, yet it remains an underexplored post-translational modification (PTM). Catalyzed by Golgi-localized TPST1 and TPST2, tyrosine sulfation modulates protein-protein interactions and receptor-ligand binding in inflammation, hemostasis, immunity, and viral entry. Despite functional relevance, this modification is underrepresented in databases such as UniProt (accessed July 2025), in large part due to a lack of robust analytical strategies. Advances in mass spectrometry (MS)-based analyses have recently improved sensitivity of detection, expanding the known tyrosine 'sulfome.' Systematic profiling of sulfated residues can now be undertaken, expanding knowledge of their regulatory roles in both health and disease, and for pioneering new sulfation-targeted therapeutics.

Areas covered: We review known biological roles of protein sulfation by TPSTs and approaches for characterization of sulfation of tyrosine and other residues such as cysteine. More broadly, we consider how these strategies might be useful in a clinical context.

Expert opinion: High throughput MS-based proteomics has proven invaluable for the discovery of PTMs, advancing understanding of their roles in human health and disease. With recent advances in strategies for the characterization of protein sulfation, the field is now ready for exploration in a clinical context.

Introduction: Cardiovascular diseases (CVD) are the leading cause of death worldwide. Systemic remodeling of metabolism is a major pathophysiological response to cardiac dysfunction and its complications. Metabolomics is thus an important technological platform for discovering new biomarkers, elucidating disease mechanisms, and stratifying patients for personalized therapeutic options.

Areas covered: We summarize the progress in clinical metabolomics across major domains of CVD based on studies published from 2020 to 2025. We focus on large-scale prospective clinical research studies for primary and secondary prevention, highlighting metabolite signatures for risk stratification and outcome prediction. We review specific areas of CVD, including acute coronary syndromes, cardiomyopathy, valvular heart disease, heart failure, atrial fibrillation, and pulmonary artery disease.

Expert opinion: Metabolomics provides unique value in CVD risk prediction and biomarker identification across populations, offering complementary information to traditional risk factors. It provides direct readout of systemic metabolic state and enable discovery of metabolic pathways associated with the pathophysiology of CVDs. Metabolomics is therefore an important phenotyping modality in CVD research and clinical care.

Introduction: Mitochondrial membrane proteins are key regulators of mitochondrial physiology and function. Voltage-dependent anion channel 1 (VDAC1), also termed mitochondrial porin, regulates metabolite and ion exchange across the outer mitochondrial membrane. It governs mitochondrial bioenergetics, apoptotic signaling, redox balance, and intracellular calcium homeostasis. VDAC1's function is shaped by its structure, expression, post-translational modifications, and interactions with other proteins, and is regulated by major signaling pathways including AMPK, PI3K/Akt, and mTOR. Furthermore, VDAC1 has not been extensively explored for its involvement in the crosstalk between cellular signalling and metabolism.

Areas covered: This review highlights the central role of VDAC1 in cancer progression, emphasizing its involvement in both metabolic reprogramming, a hallmark of cancer, and the modulation of key cellular signaling pathways. We summarize the multifaceted functions of VDAC1 in orchestrating metabolic flux and regulating oncogenic signaling networks.

Expert opinion: Metabolism and signal transduction are interconnected, but this crosstalk is not well explored. In recent years, the clinical significance of voltage-dependent anion channels in human health and disease has become more evident. It is worth exploring the role of VDAC1 as a metabolic and signaling pathway regulator. Studying this interconnection can give us a better understanding of cancer.

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia worldwide. Despite extensive research, the complex molecular mechanisms underlying AD remain incompletely understood, limiting diagnostic and therapeutic advancements.

Research design and methods: We presented an integrative, multi-layer computational framework to highlight proteins associated with AD-related brain changes using imaging, proteomic, genetic, and network-based analyses. Utilizing data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we combined cerebrospinal fluid (CSF) proteomics with structural brain MRI features through a supervised multi-omics integration method.

Results: This approach enabled the identification of key proteins linked to imaging traits. To contextualize these findings, proteins were mapped to their corresponding genes, investigated AD brain-imaging genetic associations through genome-wide association studies (GWAS) and applied network-based analyses. Proteins highlighted from both analyses were further verified in brain-specific databases to assess their functional roles, recurrence across studies, and spatial expression. Five proteins - APP, VGF, APOE, SCG3, and NCAN - were consistently associated with imaging-derived traits and are implicated in neurodegenerative mechanisms.

Conclusions: This study highlights the critical role of integrating imaging and proteomic data as part of the genotype-to-phenotype roadmap for AD, revealing molecular underpinnings of brain changes and offering a blueprint for the development of targeted therapeutic strategies.

Introduction: Ovarian cancer is the most lethal gynecologic malignancy and has seen little progress in early detection and treatment. Mass spectrometry-based proteomics is a powerful technique that can be used to understand tumor biology and identify novel biomarkers that could transform diagnosis, prognosis, and treatment.

Areas covered: This review highlights recent applications of proteomics in ovarian cancer research. Tissue studies have defined histotype-specific pathways and spatial proteomics focuses on intratumoral heterogeneity. Biofluid studies are growing with exciting potential for minimally invasive diagnostics. Post-translational modification profiling has explored signaling alterations and mechanisms of resistance. Proteogenomic integration has improved tumor classification, revealing protein-level alterations and regulatory mechanisms not captured by genomics. Literature was drawn mostly from studies of the past five years, with emphasis on translational applications.

Expert opinion: Proteomics has developed into a tool capable of providing clinically relevant, valuable insight. However, translation will depend on validation and standardization. Continued integration with other omics is critical for moving discoveries from the laboratory to the clinic. Importantly, there is an unmet need for proteomic analysis of less common subtypes, as seen by the bias of this review toward HGSOC.

Introduction: Middle-down proteomics (MDP) bridges bottom-up and top-down proteomics, analyzing 3-10 kDa peptides to enhance sequence coverage and post-translational modification (PTM) localization. This approach is crucial for decoding complex proteoforms and PTM networks, advancing insights into biological and disease processes. However, its application to complex samples like cell lysates or biofluids remains largely underexplored.

Areas covered: This review examines MDP's potential in complex biological samples, focusing on sample preparation, chromatography, mass spectrometry, and bioinformatics. We explore sample lysis, protein precipitation, and alternative proteases (GluC, thermolysin), supported by in-silico analyses revealing peptide length and charge distribution as key limitations for current enzymes. Advanced chromatographic techniques, ion mobility (FAIMS, TIMS), and fragmentation methods (ETD, EThcD) are discussed. Experimental challenges include peptide solubility, ionization efficiency, and bioinformatic complexity from missed cleavages and promiscuous protease specificity.

Expert opinion: MDP offers significant potential to uncover the 'dark' proteome, including PTM-rich regions and proteoforms undetectable by traditional workflows. However, a focused effort on improving high-throughput workflows will require optimizations to enzyme selection, LC-MS parameters, peptide ionization, ion mobility, ion fragmentation, and tailored algorithms are essential to drive MDP's adoption. Only then will deeper proteomic insights and breakthroughs in biological research be obtained.