Advancing serum peptidomic profiling by data-independent acquisition for clear-cell renal cell carcinoma detection and biomarker discovery

Lin, Lin; Zheng, Jiaxin; Zheng, Fangjian; Cai, Zonglong; Yu, Quan

doi:10.1016/j.jprot.2020.103671

Cited by 20 publications

(11 citation statements)

References 55 publications

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“…The MS/MS methodology employed here is mainly identifying serum peptides and polypeptides (peptidome) and not intact larger proteins. This serum peptidome has been proposed to be more disease specific than organismal proteomes [ 37 ]. It is known that peptides can pass freely as well as pass in regulated fashion through the blood–brain barrier [ 38 ] Thus, this methodology could be gleaning biochemical phenotype information directly from the brain affected by AD.…”

Section: Resultsmentioning

confidence: 99%

“…IPA is used in this context to predict cellular pathways that are possibly changing based on altered gene expression parameters [ 28 ]. In this case, serum peptidome changes are utilized which are valid gene expression markers for disease states [ 37 ]. The serum peptidome is hypothesized to better reflect an organism’s systemic phenotype and associated disease states than individual organ proteomes or the proteome in general.…”

Section: Resultsmentioning

confidence: 99%

“…Examination of biomolecules in peripheral blood, e.g., peptides/proteins that change with AD, has the potential to provide diagnostic, phenotypic, mechanistic, and therapeutic insights into this disorder. The serum peptidome is a valid gene expression entity for study and was shown to correlate with specific disease states [ 19 , 20 , 21 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

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Distinguishing Alzheimer’s Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis

et al. 2021

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It is important to develop minimally invasive biomarker platforms to help in the identification and monitoring of patients with Alzheimer’s disease (AD). Assisting in the understanding of biochemical mechanisms as well as identifying potential novel biomarkers and therapeutic targets would be an added benefit of such platforms. This study utilizes a simplified and novel serum profiling platform, using mass spectrometry (MS), to help distinguish AD patient groups (mild and moderate) and controls, as well as to aid in understanding of biochemical phenotypes and possible disease development. A comparison of discriminating sera mass peaks between AD patients and control individuals was performed using leave one [serum sample] out cross validation (LOOCV) combined with a novel peak classification valuation (PCV) procedure. LOOCV/PCV was able to distinguish significant sera mass peak differences between a group of mild AD patients and control individuals with a p value of 10−13. This value became non-significant (p = 0.09) when the same sera samples were randomly allocated between the two groups and reanalyzed by LOOCV/PCV. This is indicative of physiological group differences in the original true-pathology binary group comparison. Similarities and differences between AD patients and traumatic brain injury (TBI) patients were also discernable using this novel LOOCV/PCV platform. MS/MS peptide analysis was performed on serum mass peaks comparing mild AD patients with control individuals. Bioinformatics analysis suggested that cell pathways/biochemical phenotypes affected in AD include those involving neuronal cell death, vasculature, neurogenesis, and AD/dementia/amyloidosis. Inflammation, autoimmunity, autophagy, and blood–brain barrier pathways also appear to be relevant to AD. An impaired VWF/ADAMTS13 vasculature axis with connections to F8 (factor VIII) and LRP1 and NOTCH1 was indicated and is proposed to be important in AD development.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Distinguishing Alzheimer’s Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis

et al. 2021

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“…The signal needs to be deconvoluted based on the retention time matching of related precursor and product ions. While technically challenging, this approach is gaining traction within the proteomics community and its application for studying endogenous peptides is beginning to be adopted. , Lin was the first to apply a DIA strategy to a disease-related peptidomics study, when profiling the serum peptidome of patients with clear-cell renal cell carcinoma. This approach was reported to improve the sensitivity and reproducibility of peptide measurement compared with DDA, as DIA results were 95.4% reproducible over triplicate acquisitions, with quantitative figures showing coefficients of variation (CV) of <10%.…”

Section: Methodologies For Peptidomics Analysismentioning

confidence: 99%

Peptidomics: A Review of Clinical Applications and Methodologies

et al. 2021

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Improvements in both liquid chromatography (LC) and mass spectrometry (MS) instrumentation have greatly enhanced proteomic and small molecule metabolomic analysis in recent years. Less focus has been on the improved capability to detect and quantify small bioactive peptides, even though the exact sequences of the peptide species produced can have important biological consequences. Endogenous bioactive peptide hormones, for example, are generated by the targeted and regulated cleavage of peptides from their prohormone sequence. This process may include organ specific variants, as proglucagon is converted to glucagon in the pancreas but glucagon-like peptide-1 (GLP-1) in the small intestine, with glucagon raising, whereas GLP-1, as an incretin, lowering blood glucose. Therefore, peptidomics workflows must preserve the structure of the processed peptide products to prevent the misidentification of ambiguous peptide species. The poor in vivo and in vitro stability of peptides in biological matrices is a major factor that needs to be considered when developing methods to study them. The bioinformatic analysis of peptidomics data sets requires the inclusion of specific posttranslational modifications, which are critical for the function of many bioactive peptides. This review aims to discuss and contrast the various extraction, analytical, and bioinformatics approaches used for human peptidomics studies in a multitude of matrices.

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“…A promising approach is represented by the DIA-based MS workflow, able to detect numerous peptides and proteins with better reproducibility starting from a low sample amount [49]. This approach showed the high potential of serum peptidome study in RCC: the comparison of 31 RCC patients and 31 healthy subjects led to discover 833 differential peptides, most of which are related to extracellular matrix degradation [50]. However, alterations in serum peptidome can also derive by nonspecific action of proteases during (and after) clotting, whose risk increases with higher cancer stage [51].…”

Section: Liquid Biopsymentioning

confidence: 99%

Prognostic significance of proteomics and multi-omics studies in renal carcinoma

Raimondo

Pitto

2020

Expert Review of Proteomics

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Introduction Renal carcinoma and in particular its most common variant, the clear cell subtype, is often diagnosed incidentally through abdominal imaging. Rather frequently, the tumour is discovered at an early stage. However, 20% to 40% of patients undergoing nephrectomy for clinically localized renal cancer, even after accurate histological and clinical classification, will develop metastasis or recurrence, justifying the associated mortality rate. Therefore, even if renal carcinoma is not among the most frequent nor deadly cancers, a better prognostication is needed.Areas covered Recently proteomics or other -omics combinations have been applied to both cancer tissues, on the neoplasia itself and surrounding microenvironment, cultured cells and biological fluids (so-called liquid biopsy) generating a list of prognostic molecular tools that will be reviewed in the present paper. Expert opinion.Although promising, none of the approaches listed above has been yet translated in clinics. This is likely due to the peculiar genetic and phenotypic heterogeneity of this cancer, which makes nearly each tumour different from all the others. Attempts to overcome this issue will be also revised. In particular we will discuss how the application of -omics integrated approaches could provide the determinants of response to the different targeted drugs.

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Advancing serum peptidomic profiling by data-independent acquisition for clear-cell renal cell carcinoma detection and biomarker discovery

Cited by 20 publications

References 55 publications

Distinguishing Alzheimer’s Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis

Distinguishing Alzheimer’s Disease Patients and Biochemical Phenotype Analysis Using a Novel Serum Profiling Platform: Potential Involvement of the VWF/ADAMTS13 Axis

Peptidomics: A Review of Clinical Applications and Methodologies

Prognostic significance of proteomics and multi-omics studies in renal carcinoma

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