PROTEOMICS – Clinical Applications最新文献

Purpose: The SARS-CoV-2 pandemic prompted the development and use of next-generation vaccines. Among these, mRNA-based vaccines consist of injectable solutions of mRNA encoding for a recombinant Spike, which is distinguishable from the wild-type protein due to specific amino acid variations introduced to maintain the protein in a prefused state. This work presents a proteomic approach to reveal the presence of recombinant Spike protein in vaccinated subjects regardless of antibody titer.

Experimental design: Mass spectrometry examination of biological samples was used to detect the presence of specific fragments of recombinant Spike protein in subjects who received mRNA-based vaccines.

Results: The specific PP-Spike fragment was found in 50% of the biological samples analyzed, and its presence was independent of the SARS-CoV-2 IgG antibody titer. The minimum and maximum time at which PP-Spike was detected after vaccination was 69 and 187 days, respectively.

Conclusions and clinical relevance: The presented method allows to evaluate the half-life of the Spike protein molecule "PP" and to consider the risks or benefits in continuing to administer additional booster doses of the SARS-CoV-2 mRNA vaccine. This approach is of valuable support to complement antibody level monitoring and represents the first proteomic detection of recombinant Spike in vaccinated subjects.

Purpose: Stroke is the sudden death of brain cells in a localized area due to an inadequate blood flow or blood vessel rupture, and it seriously affects the quality of life. The metabolite biomarkers are needed for predicting the functional outcome of acute ischemic stroke (AIS).

Experimental design: To identify biomarkers for AIS, untargeted LC/MS metabolomics was performed on plasma samples from subjects with favorable prognosis (mRS ≤ 2) and unfavorable prognosis (mRS > 2). The identified markers were further absolutely quantified by a targeted MRM approach.

Results: There were 10 upregulated and 26 downregulated markers. Among these candidates, one was successfully identified as glycocholic acid and then absolutely quantified in plasma samples. Glycocholic acid could discriminate between subjects with favorable and unfavorable prognosis with an area under the curve (AUC) of 0.68 and odds ratio of 5.88.

Conclusions and clinical relevance: Glycocholic acid was identified as a potential plasma metabolite marker of non-progressive outcomes after ischemic stroke and could serve as predictive prognostic markers for clinical acute stroke outcomes.

Purpose: This pilot study aimed to use proteomic profiling of sonicate fluid samples to compare host response during Staphylococcus aureus-associated periprosthetic joint infection (PJI) and non-infected arthroplasty failure (NIAF) and identify potential novel biomarkers differentiating the two.

Experimental design: In this pilot study, eight sonicate fluid samples (four from NIAF and four from S. aureus PJI) were studied. Samples were reduced, alkylated, and trypsinized overnight, followed by analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a high-resolution Orbitrap Eclipse mass spectrometer. MaxQuant software suite was used for protein identification, filtering, and label-free quantitation.

Results: Principal component analysis of the identified proteins clearly separated S. aureus PJI and NIAF samples. Overall, 810 proteins were identified based on their detection in at least three out of four samples from each group; 35 statistically significant differentially abundant proteins (DAPs) were found (two-sample t-test p-values ≤0.05 and log₂ fold-change values ≥2 or ≤-2). Gene ontology pathway analysis found that microbial defense responses, specifically those related to neutrophil activation, to be increased in S. aureus PJI compared to NIAF samples.

Conclusion and clinical relevance: Proteomic profiling of sonicate fluid using LC-MS/MS differentiated S. aureus PJI and NIAF in this pilot study. Further work is needed using a larger sample size and including non-S. aureus PJI and a diversty of NIAF-types.

Purpose: Small cell lung cancer (SCLC) is one of the malignant cancers with aggressive progression and poor prognosis. Bronchoalveolar lavage fluid (BALF) has been arising recently as a potential source of biomarkers for lung cancers. In this study, we performed quantitative BALF proteomic analysis to identify potential biomarkers for SCLC.

Experimental design: BALF were collected from tumor-bearing lungs and non-tumor lungs of five SCLC patients. Then, BALF proteomes were prepared for a TMT-based quantitative mass spectrometry analysis. Differentially expressed proteins (DEP) were identified when considering individual variation. Potential SCLC biomarker candidates were validated by immunohistochemistry (IHC). A public database of multiple SCLC cell lines was used to evaluate the correlation of these markers with SCLC subtypes and chemo-drug responses.

Results: We identified 460 BALF proteins in SCLC patients and observed considerable individual variation among the patients. Immunohistochemical analysis and bioinformatics resulted in the identification of CNDP2 and RNPEP as potential subtype markers for ASCL1 and NEUROD1, respectively. In addition, CNDP2 was found to be positively correlated with responses to etoposide, carboplatin, and irinotecan.

Conclusions and clinical relevance: BALF is an emerging source of biomarkers, making it useful for the diagnosis and prognosis of lung cancers. We characterized the proteomes of paired BALF samples collected from tumor-bearing and non-tumor lungs of SCLC patients. Several proteins were found elevated in tumor-bearing BALF, and especially CNDP2 and RNPEP appeared to be potential indicators for ASLC1-high and NEUROD1-high subtypes of SCLC, respectively. The positive correlation of CNDP2 with chemo-drug responses would help to make decisions for treatment of SCLC patients. These putative biomarkers could be comprehensively investigated for a clinical use towards precision medicine.

Purpose: Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The occurrence and development of HCC are closely related to epigenetic modifications. Epigenetic modifications can regulate gene expression and related functions through DNA methylation. This paper presents an association analysis method of HCC-related hub proteins and hub genes.

Experimental design: Bioinformatics analysis of HCC-related DNA methylation data is carried out to clarify the molecular mechanism of HCC-related genes and to find hub genes (genes with more connections in the network) by constructing in the gene interaction network. This paper proposes an accurate prediction method of protein-protein interaction (PPI) based on deep learning model DeepSG2PPI. The trained DeepSG2PPI model predicts the interaction relationship between the synthetic proteins regulated by HCC-related genes.

Results: This paper finds that four genes are the intersection of hub genes and hub proteins. The four genes are: FBL, CCNB2, ALDH18A1, and RPLP0. The association of RPLP0 gene with HCC is a new finding of this study. RPLP0 is expected to become a new biomarker for the treatment, diagnosis, and prognosis of HCC. The four proteins corresponding to the four genes are: ENSP00000221801, ENSP00000288207, ENSP00000360268, and ENSP00000449328.

Conclusions and clinical relevance: The association between the hub genes with the hub proteins is analyzed. The mutual verification of the hub genes and the hub proteins can obtain more credible HCC-related genes and proteins, which is helpful for the diagnosis, treatment, and drug development of HCC.

Lactate was once considered to be a by-product of energy metabolism, but its unique biological value was only gradually explored with the advent of the Warburg effect. As an end product of glycolysis, lactate can act as a substrate for energy metabolism, a signal transduction molecule, a regulator of the tumor microenvironment and immune cells, and a regulator of the deubiquitination of specific enzymes, and is involved in various biological aspects of tumor regulation, including energy shuttling, growth and invasion, angiogenesis and immune escape. Furthermore, we describe a novel lactate-dependent epigenetic modification, namely histone lactylation modification, and review the progress of its study in tumors, mainly involving the reprogramming of tumor phenotypes, regulation of related gene expression, mediation of the glycolytic process in tumor stem cells (CSCs) and influence on the tumor immune microenvironment. The study of epigenetic regulation of tumor genes by histone modification is still in its infancy, and we expect that by summarizing the effects of lactate and histone modification on tumor and related gene regulation, we will clarify the scientific significance of future histone modification studies and the problems to be solved, and open up new fields for targeted tumor therapy.

Purpose: Proteoglycans (PGs) are negatively charged macromolecules containing a core protein and single or several glycosaminoglycan chains attached by covalent bond. They are distributed in all tissues, including extracellular matrix (ECM), cell surface, and basement membrane. They are involved in major pathways and cell signalling cascades which modulate several vital physiological functions of the body. They have also emerged as a target molecule for cancer treatment and as possible biomarkers for early cancer detection. Among cancers, breast cancer is a highly invasive and heterogenous type and has become the major cause of mortality especially among women. So, this review revisits the studies on PGs characterization in breast cancer using LC-MS/MS-based proteomics approach, which will be further helpful for identification of potential PGs-based biomarkers or therapeutic targets.

Experimental design: There is a lack of comprehensive knowledge on the use of LC-MS/MS-based proteomics approaches to identify and characterize PGs in breast cancer.

Results: LC-MS/MS assisted PGs characterization in breast cancer revealed the vital PGs in breast cancer invasion and progression. In addition, comprehensive profiling and characterization of PGs in breast cancer are efficiently carried out by this approach.

Conclusions: Proteomics techniques including LC-MS/MS-based identification of proteoglycans is effectively carried out in breast cancer research. Identification of expression at different stages of breast cancer is a major challenge, and LC-MS/MS-based profiling of PGs can boost novel strategies to treat breast cancer, which involve targeting PGs, and also aid early diagnosis using PGs as biomarkers.