scholarly journals Longitudinal Bottom-Up Proteomics of Serum, Serum Extracellular Vesicles, and Cerebrospinal Fluid Reveals Candidate Biomarkers for Early Detection of Glioblastoma in a Murine Model

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 5992
Author(s):  
Francesco Greco ◽  
Federica Anastasi ◽  
Luca Fidia Pardini ◽  
Marialaura Dilillo ◽  
Eleonora Vannini ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Extracellular Vesicles ◽  
Murine Model ◽  
Biomarker Discovery ◽  
Early Stage ◽  
Protein Profile ◽  
Survival Rates ◽  
Non Invasive ◽  
Tumor Stages ◽  
Early Effects

Glioblastoma Multiforme (GBM) is a brain tumor with a poor prognosis and low survival rates. GBM is diagnosed at an advanced stage, so little information is available on the early stage of the disease and few improvements have been made for earlier diagnosis. Longitudinal murine models are a promising platform for biomarker discovery as they allow access to the early stages of the disease. Nevertheless, their use in proteomics has been limited owing to the low sample amount that can be collected at each longitudinal time point. Here we used optimized microproteomics workflows to investigate longitudinal changes in the protein profile of serum, serum small extracellular vesicles (sEVs), and cerebrospinal fluid (CSF) in a GBM murine model. Baseline, pre-symptomatic, and symptomatic tumor stages were determined using non-invasive motor tests. Forty-four proteins displayed significant differences in signal intensities during GBM progression. Dysregulated proteins are involved in cell motility, cell growth, and angiogenesis. Most of the dysregulated proteins already exhibited a difference from baseline at the pre-symptomatic stage of the disease, suggesting that early effects of GBM might be detectable before symptom onset.

scholarly journals Proteomic analysis of extracellular vesicles in cerebrospinal fluid of patients with Alzheimer’s disease

2020 ◽  
Author(s):  
Davide Chiasserini ◽  
Irene Bijnsdorp ◽  
Giovanni Bellomo ◽  
Pier Luigi Orvietani ◽  
Sander R. Piersma ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Extracellular Vesicles ◽  
Biomarker Discovery ◽  
Neurodegenerative Disorder ◽  
High Resolution Mass Spectrometry ◽  
Biological Fluids ◽  
Protein Profile ◽  
Protein Markers

AbstractCerebrospinal fluid (CSF) contains different types of extracellular vesicles (EVs) with undisclosed biomarker potential for neurodegenerative diseases. The aims of the present study were: i) to compare the proteome EVs isolated using different ultracentrifugation speed ii) to preliminary explore the EVs proteome in a common neurodegenerative disorder, Alzheimer’s disease (AD) compared to neurological controls. CSF samples from control subjects and AD patients were pooled separately (15 mL) and subjected to ultracentrifugation (UC) at different speeds (20,000g and 100,000g) to isolate separate EV fractions (P20 and P100). The proteome was analysed using high-resolution mass spectrometry (LC-MS/MS) and comparisons were made using bioinformatic analysis. EVs isolated at 100,000g (P100) had a proteome consistent with vesicles secreted via an ESCRT-dependent mechanism, being highly enriched in alix (PDCD6IP), syntenin-1 (SDCBP) and TSG101. EVs isolated at 20,000g were substantially different, showing enrichment in cytoskeletal and cell adhesion molecules. The pools from patients diagnosed with AD showed a distinct protein profile of CSF EVs, with increased levels of ADAM10, SPON1, CH3IL1 and MDK in the P100 fraction. CSF EV offer a new potential biosource of protein markers for AD detection and a complementary framework to the analysis of whole biological fluids for biomarker discovery.

scholarly journals Next-Generation Biomarkers for Cholangiocarcinoma

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3222
Author(s):  
Pedro M. Rodrigues ◽  
Arndt Vogel ◽  
Marco Arrese ◽  
Domingo C. Balderramo ◽  
Juan W. Valle ◽  
...  
Keyword(s):  
Biomarker Discovery ◽  
Tumor Development ◽  
Predictive Biomarkers ◽  
Disease Diagnosis ◽  
Future Research ◽  
Tumor Biopsy ◽  
Non Invasive ◽  
Tumor Stages ◽  
At Risk Populations ◽  
Early Tumor

The increasing mortality rates of cholangiocarcinoma (CCA) registered during the last decades are, at least in part, a result of the lack of accurate non-invasive biomarkers for early disease diagnosis, making the identification of patients who might benefit from potentially curative approaches (i.e., surgery) extremely challenging. The obscure CCA pathogenesis and associated etiological factors, as well as the lack of symptoms in patients with early tumor stages, highly compromises CCA identification and to predict tumor development in at-risk populations. Currently, CCA diagnosis is accomplished by the combination of clinical/biochemical features, radiological imaging and non-specific serum tumor biomarkers, although a tumor biopsy is still needed to confirm disease diagnosis. Furthermore, prognostic and predictive biomarkers are still lacking and urgently needed. During the recent years, high-throughput omics-based approaches have identified novel circulating biomarkers (diagnostic and prognostic) that might be included in large, international validation studies in the near future. In this review, we summarize and discuss the most recent advances in the field of biomarker discovery in CCA, providing new insights and future research directions.

scholarly journals Analysis of Cerebrospinal Fluid Extracellular Vesicles by Proximity Extension Assay: A Comparative Study of Four Isolation Kits

2020 ◽  
Vol 21 (24) ◽  
pp. 9425
Author(s):  
Sebastian Sjoqvist ◽  
Kentaro Otake ◽  
Yoshihiko Hirozane
Keyword(s):  
Cerebrospinal Fluid ◽  
Extracellular Vesicles ◽  
Proteomic Analysis ◽  
Magnetic Beads ◽  
Biomarker Discovery ◽  
De Novo ◽  
Size Exclusion ◽  
Cell Regulation ◽  
Promising Source ◽  
Proximity Extension Assay

There is a lack of reliable biomarkers for disorders of the central nervous system (CNS), and diagnostics still heavily rely on symptoms that are both subjective and difficult to quantify. The cerebrospinal fluid (CSF) is a promising source of biomarkers due to its close connection to the CNS. Extracellular vesicles are actively secreted by cells, and proteomic analysis of CSF extracellular vesicles (EVs) and their molecular composition likely reflects changes in the CNS to a higher extent compared with total CSF, especially in the case of neuroinflammation, which could increase blood–brain barrier permeability and cause an influx of plasma proteins into the CSF. We used proximity extension assay for proteomic analysis due to its high sensitivity. We believe that this methodology could be useful for de novo biomarker discovery for several CNS diseases. We compared four commercially available kits for EV isolation: MagCapture and ExoIntact (based on magnetic beads), EVSecond L70 (size-exclusion chromatography), and exoEasy (membrane affinity). The isolated EVs were characterized by nanoparticle tracking analysis, ELISA (CD63, CD81 and albumin), and proximity extension assay (PEA) using two different panels, each consisting of 92 markers. The exoEasy samples did not pass the built-in quality controls and were excluded from downstream analysis. The number of detectable proteins in the ExoIntact samples was considerably higher (~150% for the cardiovascular III panel and ~320% for the cell regulation panel) compared with other groups. ExoIntact also showed the highest intersample correlation with an average Pearson’s correlation coefficient of 0.991 compared with 0.985 and 0.927 for MagCapture and EVSecond, respectively. The median coefficient of variation was 5%, 8%, and 22% for ExoIntact, MagCapture, and EVSecond, respectively. Comparing total CSF and ExoIntact samples revealed 70 differentially expressed proteins in the cardiovascular III panel and 17 in the cell regulation panel. To our knowledge, this is the first time that CSF EVs were analyzed by PEA. In conclusion, analysis of CSF EVs by PEA is feasible, and different isolation kits give distinct results, with ExoIntact showing the highest number of identified proteins with the lowest variability.

scholarly journals Aberrant methylation ofPCDH10andRASSF1Agenes in blood samples for non-invasive diagnosis and prognostic assessment of gastric cancer

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2112 ◽  
Author(s):  
Charinya Pimson ◽  
Tipaya Ekalaksananan ◽  
Chamsai Pientong ◽  
Supannee Promthet ◽  
Nuntiput Putthanachote ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Median Survival ◽  
Early Stage ◽  
Survival Rates ◽  
Aberrant Methylation ◽  
Blood Samples ◽  
Cumulative Survival ◽  
Non Invasive ◽  
Severe Stage

Background.Assessment of DNA methylation of specific genes is one approach to the diagnosis of cancer worldwide. Early stage detection is necessary to reduce the mortality rate of cancers, including those occurring in the stomach. For this purpose, tumor cells in circulating blood offer promising candidates for non-invasive diagnosis. Transcriptional inactivation of tumor suppressor genes, likePCDH10andRASSF1A, by methylation is associated with progression of gastric cancer, and such methylation can therefore be utilized as a biomarker.Methods.The present research was conducted to evaluate DNA methylation in these two genes using blood samples of gastric cancer cases. Clinicopathological data were also analyzed and cumulative survival rates generated for comparison.Results.High frequencies ofPCDH10andRASSF1Amethylations in the gastric cancer group were noted (94.1% and 83.2%, respectively, as compared to 2.97% and 5.45% in 202 matched controls). Most patients (53.4%) were in severe stage of the disease, with a median survival time of 8.4 months after diagnosis. Likewise, the patients with metastases, orRASSF1AandPCDH10methylations, had median survival times of 7.3, 7.8, and 8.4 months, respectively. A Kaplan–Meier analysis showed that cumulative survival was significantly lower in those cases positive for methylation ofRASSF1Athan in their negative counterparts. Similarly, whereas almost 100% of patients positive forPCDH10methylation had died after five years, none of the negative cases died over this period. Notably, the methylations ofRASSF1AandPCDH10were found to be higher in the late-stage patients and were also significantly correlated with metastasis and histology.Conclusions.PCDH10andRASSF1Amethylations in blood samples can serve as potential non-invasive diagnostic indicators in blood for gastric cancer. In addition toRASSF1Amethylation, tumor stage proved to be a major prognostic factor in terms of survival rates.

scholarly journals Tandem mass spectrometry-based identification of protein profiles in the cerebrospinal fluid of Alzheimer’s dementia patients

2021 ◽  
Author(s):  
Anamika Misra ◽  
Sankha Shubhra Chakrabarti ◽  
Indrajeet Singh Gambhir ◽  
Meghraj Singh Baghel ◽  
Yugendra Ramchandra Patil
Keyword(s):  
Mass Spectrometry ◽  
Cerebrospinal Fluid ◽  
Growth Factor ◽  
Tandem Mass Spectrometry ◽  
Biomarker Discovery ◽  
Early Stage ◽  
Enrichment Analysis ◽  
Tandem Mass ◽  
Insulin Like Growth Factor ◽  
Proteomic Approach

Abstract Background: Alzheimer’s disease (AD) is the most common form of dementia and about two thirds cases are diagnosed late due to a long asymptomatic phase. There exists the need for newer biomarkers which can add accuracy to AD diagnosis, detect AD at an early stage, as also lend new pathogenic insights into AD. Recent AD biomarker discovery has focused on proteomic approaches, especially in the cerebrospinal fluid. Methods: We used a bottom-up proteomic approach. Cerebrospinal fluid (CSF) samples from 6 patients with AD and 6 controls were digested with trypsin and analyzed by using LC-MS/MS (tandem mass spectrometry). The peptide data from CSF samples of both AD and control groups was then subjected to bioinformatics analysis with STRING version 11.0. Protein-protein interaction networks were constructed, and enrichment analysis performed.Results: Significant up-regulation of 13 proteins in the CSF was observed in AD cases in comparison to controls, while 30 proteins were down-regulated. APOE and LGALS3BP were the upregulated proteins involved in closed network and the downregulated proteins were F2, PENK, IGF2, APOH, SAA1, AHSG, SPP1 and CD44. APOE, APOH, F2 and PENK shared common involvement in multiple biological processes as evident on enrichment. Regulation of insulin like growth factor involving IGF2, F2, APOE and AHSG and glycosaminoglycan binding involving APOE, APOH, F2, SAA1, and CD44 were major pathways of interest determined on bioinformatic analysis.Conclusion: Our study identified novel tentative biomarkers of AD which included F2, PENK and SAA1, as well as reinforced earlier described biomarkers such as APOE and AHSG. These findings need to be validated in larger sample sizes to evaluate their utility as true biomarkers. Further, the pathways of interest- insulin like growth factor regulation and glycosaminoglycan binding need to be studied further in the context of AD.

Review of Various Tasks Performed in the Preprocessing Phase of a Diabetic Retinopathy Diagnosis System

2020 ◽  
Vol 16 (4) ◽  
pp. 397-426
Author(s):  
Muhammad Nadeem Ashraf ◽  
Muhammad Hussain ◽  
Zulfiqar Habib
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
Early Stage ◽  
Spherical Shape ◽  
Cost Effective ◽  
Lesion Detection ◽  
Diabetic Patients ◽  
Cad System ◽  
Non Invasive ◽  
Optic Discs

Diabetic Retinopathy (DR) is a major cause of blindness in diabetic patients. The increasing population of diabetic patients and difficulty to diagnose it at an early stage are limiting the screening capabilities of manual diagnosis by ophthalmologists. Color fundus images are widely used to detect DR lesions due to their comfortable, cost-effective and non-invasive acquisition procedure. Computer Aided Diagnosis (CAD) of DR based on these images can assist ophthalmologists and help in saving many sight years of diabetic patients. In a CAD system, preprocessing is a crucial phase, which significantly affects its performance. Commonly used preprocessing operations are the enhancement of poor contrast, balancing the illumination imbalance due to the spherical shape of a retina, noise reduction, image resizing to support multi-resolution, color normalization, extraction of a field of view (FOV), etc. Also, the presence of blood vessels and optic discs makes the lesion detection more challenging because these two artifacts exhibit specific attributes, which are similar to those of DR lesions. Preprocessing operations can be broadly divided into three categories: 1) fixing the native defects, 2) segmentation of blood vessels, and 3) localization and segmentation of optic discs. This paper presents a review of the state-of-the-art preprocessing techniques related to three categories of operations, highlighting their significant aspects and limitations. The survey is concluded with the most effective preprocessing methods, which have been shown to improve the accuracy and efficiency of the CAD systems.

scholarly journals The survival rates and risk factors of implants in the early stage: a retrospective study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yong Yang ◽  
Huiting Hu ◽  
Mianyan Zeng ◽  
Hongxing Chu ◽  
Zekun Gan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Survival Rate ◽  
Dental Implants ◽  
Bone Quality ◽  
Early Stage ◽  
Survival Rates ◽  
Bone Augmentation ◽  
Early Survival ◽  
Immediate Implantation ◽  
Implant Length

Abstract Background Few large-sample studies in China have focused on the early survival of dental implants. The present study aimed to report the early survival rates of implants and determine the related influencing factors. Methods All patients receiving dental implants at our institution between 2006 and 2017 were included. The endpoint of the study was early survival rates of implants, according to gender, age, maxilla/mandible, dental position, bone augmentation, bone augmentation category, immediate implant, submerged implant category, implant diameter, implant length, implant torque, and other related factors. Initially, SPSS22.0 was used for statistical analysis. The Chi-square test was used to screen all factors, and those with p < 0.05 were further introduced into a multiple logistic regression model to illustrate the risk factors for early survival rates of implants. Results In this study, we included 1078 cases (601 males and 477 females) with 2053 implants. After implantation, 1974 implants were retained, and the early survival rate was 96.15%. Patients aged 30–60 years (OR  2.392), with Class I bone quality (OR  3.689), bone augmentation (OR  1.742), immediate implantation (OR  3.509), and implant length < 10 mm (OR  2.972), were said to possess risk factors conducive to early survival rates. Conclusions The early survival rate of implants in our cohort exceeded 96%, with risk factors including age, tooth position, bone quality, implant length, bone augmentation surgery, and immediate implantation. When the above factors coexist, implant placement should be treated carefully.

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