TMT (tandem mass tag) quantitative proteomics is an advanced mass spectrometry-based technique that has found extensive applications in biomedical research. This technology employs a chemical labeling strategy to label proteins in different samples with unique isotopic tags, allowing for their simultaneous identification and quantification in a single experiment.
TMT quantitative proteomics has emerged as a powerful tool in disease biomarker research. By comparing protein expression levels between different groups or conditions, this approach enables the identification of potential biomarkers associated with specific diseases. Two notable applications of TMT quantitative proteomics are in the study of breast cancer (MBC and TNBC) and inflammatory arthritis.
Case 1. Protein Profiling of MBC and TNBC through TMT Quantitative Proteomics (1)
Metaplastic breast cancer (MBC) is a highly aggressive subtype of triple-negative breast cancer (TNBC), accounting for 0.2-5% of all invasive breast cancers and occurring at a later age. Clinical observations have shown that MBC is more prone to metastasis and drug resistance, with the spindle cell carcinoma subtype having the worst prognosis. Currently, little is known about the mechanisms underlying the occurrence and metastasis of MBC, and there are no specific guidelines available for clinical treatment reference.
In this study, the authors utilized TMT-labeled proteomics technology to analyze 27 clinical samples, identifying a total of 5798 proteins. Principal component analysis (PCA) and consensus clustering results demonstrated a clear distinction between normal breast tissue and tumor tissue. Significant differences were also observed between MBC squamous cell carcinoma and sarcomatoid samples. Some subtypes of MBC (such as spindle cell carcinoma and squamous cell carcinoma) showed partial overlap with TNBC.
GO functional analysis revealed that, compared to normal tissue, downregulated proteins in MBC are mainly involved in tumor suppressor factors, extracellular matrix activity, and wound healing-related proteins. These data indicate that MBC exhibits a distinct protein expression profile compared to normal tissue and exhibits dysregulation in carcinogenesis-related pathways.
To better identify the unique proteomic features of different histological subtypes in MBC, the authors grouped the MBC samples based on histological subtypes (assigning samples with mixed features to the histological subtype they predominantly resembled). Compared to TNBC, MBC showed dysregulation of proteins associated with the immune system (mainly involving humoral immunity) and extracellular structural tissue. Different MBC subtypes exhibited distinct biological functions: squamous cell carcinoma was associated with keratinization-related proteins, spindle cell carcinoma with protein hydrolysis and cascade activation-related proteins, and sarcomatoid carcinoma with proteins related to leukocyte activation and exocytosis.
Furthermore, the authors conducted Gene Set Enrichment Analysis (GSEA) and found that, compared to TNBC, MBC showed significant upregulation of epithelial-mesenchymal transition (EMT) and significant downregulation of oxidative phosphorylation (OXPHOS) pathway. Significant expression differences were observed for genes such as MYC, MTORC1, E2F, OXPHOS, EMT, TP53, and PI3K among different pathological subtypes. These results revealed unique protein characteristics and specific pathways in MBC histological subtypes.
This study focused on characterizing the global proteomic profile of MBC using TMT quantitative proteomics, revealing distinct protein expression features among different MBC subtypes.
Case 2. Screening Extracellular Vesicle Protein Biomarkers in Inflammatory Arthritis Using TMT Quantitative Proteomics (2)
Inflammatory arthritis (IA) is a significant clinical manifestation of rheumatic immune diseases and often leads to joint pain, restricted mobility, and, ultimately, joint deformities and disability. The pathological features of inflammatory arthritis include synovitis and synovial hyperplasia. Clinically, inflammatory arthritis can be further classified into gout, axial spondyloarthritis (ax-SpA), rheumatoid arthritis (RA), and osteoarthritis (OA).
Currently, there is a lack of research on differential protein profiling of extracellular vesicles in synovial fluid among these four different classifications of inflammatory arthritis. Therefore, the authors conducted proteomic analysis and bioinformatics analysis using tandem mass tag (TMT) labeling combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) technology to study the extracellular vesicles in the synovial fluid of patients with gout, ax-SpA, RA, and OA.
First, the authors determined the size of the extracted extracellular vesicles and measured their concentration to ensure proper calibration for subsequent differential analysis. Additionally, the detection of characteristic vesicular proteins (CD81, TSG101) was performed to confirm the successful extraction of extracellular vesicles.
The authors conducted principal component analysis (PCA) and found that the four groups were well distinguished, validating the rationale behind the grouping. They then performed pairwise comparisons between each group and presented the differential proteins using volcano plots and heatmaps.
In comparison to the OA, axSpA, and RA groups, 69 specific extracellular vesicle proteins were identified in the gout group. Notably, lysozyme C, a specific extracellular vesicle protein, was found to be highly expressed in the gout group. This suggests a potential association between lysozyme C and gout. Pathway enrichment analysis revealed that the highly expressed extracellular vesicle proteins in gout, such as α-1-acid glycoprotein, desmocollin-1, and hornerin, were significantly involved in "neutrophil degranulation".
In the axSpA group, 84 specific extracellular vesicle proteins were identified. Sec24C, a transport protein, exhibited significantly higher expression in axSpA compared to the other groups, while its expression in RA, gout, and OA was comparable. This indicates that Sec24C may serve as a specific protein marker for axSpA. Other highly expressed proteins in axSpA included citrate synthase, fumarate hydratase, isocitrate dehydrogenase [NAD] subunit beta, and dihydrolipoyllysine-residue acetyltransferase component of pyruvate dehydrogenase complex, all of which are involved in the "citric acid cycle (TCA cycle)".
In the RA group, 184 specific extracellular vesicle proteins were identified. PZP (pregnancy zone protein) showed higher expression in RA compared to the other groups, with axSpA and OA showing higher expression than the gout group. ELISA results confirmed that PZP levels were higher in the RA group compared to OA, gout, and axSpA, consistent with the TMT-LC-MS/MS data. PZP may be involved in the occurrence and development of IA inflammation.
The authors conducted a systematic analysis of differential extracellular vesicle proteins in the synovial fluid of patients with gout, axSpA, RA, and OA using TMT quantitative proteomics. Through bioinformatics analysis and literature review, they partially revealed specific synovial fluid markers and potential pathogenic mechanisms associated with gout, axSpA, RA, and OA.
References
- Djomehri, Sabra I., et al. "Quantitative proteomic landscape of metaplastic breast carcinoma pathological subtypes and their relationship to triple-negative tumors." Nature communications 11.1 (2020): 1723.
- Huang, Yukai, et al. "TMT-based quantitative proteomics analysis of synovial fluid-derived exosomes in inflammatory arthritis." Frontiers in Immunology 13 (2022).
