Accelerated Lysis and Proteolytic Digestion of Biopsy-Level Fresh-Frozen and FFPE Tissue Samples Using Pressure Cycling Technology

2020 ◽  
Vol 19 (5) ◽  
pp. 1982-1990 ◽  
Author(s):  
Huanhuan Gao ◽  
Fangfei Zhang ◽  
Shuang Liang ◽  
Qiushi Zhang ◽  
Mengge Lyu ◽  
...  
Keyword(s):  
Ffpe Tissue ◽  
Proteolytic Digestion ◽  
Tissue Samples ◽  
Pressure Cycling ◽  
Fresh Frozen ◽  
Pressure Cycling Technology

scholarly journals Protein Classifier for Thyroid Nodules Learned from Rapidly Acquired Proteotypes

2020 ◽  
Author(s):  
Yaoting Sun ◽  
Sathiyamoorthy Selvarajan ◽  
Zelin Zang ◽  
Wei Liu ◽  
Yi Zhu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Thyroid Nodules ◽  
Thyroid Tissue ◽  
Tissue Samples ◽  
Pressure Cycling ◽  
Data Independent Acquisition ◽  
Artificial Neural ◽  
Pressure Cycling Technology ◽  
Sizeable Number

SUMMARYUp to 30% of thyroid nodules cannot be accurately classified as benign or malignant by cytopathology. Diagnostic accuracy can be improved by nucleic acid-based testing, yet a sizeable number of diagnostic thyroidectomies remains unavoidable. In order to develop a protein classifier for thyroid nodules, we analyzed the quantitative proteomes of 1,725 retrospective thyroid tissue samples from 578 patients using pressure-cycling technology and data-independent acquisition mass spectrometry. With artificial neural networks, a classifier of 14 proteins achieved over 93% accuracy in classifying malignant thyroid nodules. This classifier was validated in retrospective samples of 271 patients (91% accuracy), and prospective samples of 62 patients (88% accuracy) from four independent centers. These rapidly acquired proteotypes and artificial neural networks supported the establishment of an effective protein classifier for classifying thyroid nodules.

scholarly journals High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification

2019 ◽  
Author(s):  
Yi Zhu ◽  
Tobias Weiss ◽  
Qiushi Zhang ◽  
Rui Sun ◽  
Bo Wang ◽  
...  
Keyword(s):  
Biomarker Discovery ◽  
Temporal Stability ◽  
B Cell Lymphoma ◽  
Ffpe Tissue ◽  
Tissue Samples ◽  
Pattern Similarity ◽  
Ffpe Samples ◽  
Fresh Frozen ◽  
Peroxidase Enzyme ◽  
High Degree

AbstractFormalin-fixed, paraffin-embedded (FFPE), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here we developed a pressure cycling technology (PCT)-SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PCa) and diffuse large B-cell lymphoma (DLBCL) samples. We show that the proteome patterns of FFPE PCa tissue samples and their analogous fresh frozen (FF) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PCa tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between one to 15 years in a biobank and show a high degree of the proteome pattern similarity between two types histological region of small FFPE samples, i.e. punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of certain degree of biological variations. Applying the method to two independent DLBCL cohorts we identified myeloperoxidase (MPO), a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PCa and DLBCL have been discovered.

scholarly journals Identification of protein abundance changes in biopsy-level hepatocellular carcinoma tissues using PCT-SWATH

2018 ◽  
Author(s):  
Yi Zhu ◽  
Jiang Zhu ◽  
Cong Lu ◽  
Ping Sun ◽  
Wei Xie ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Matched Control ◽  
Protein Abundance ◽  
Tissue Samples ◽  
Pressure Cycling ◽  
Tumor Tissues ◽  
Wet Weight ◽  
Pressure Cycling Technology ◽  
Related Proteins ◽  
Short Timeframe

AbstractIn this study, we optimized the pressure-cycling technology (PCT) and SWATH mass spectrometry workflow to analyze biopsy-level tissue samples (2 mg wet weight) from 19 hepatocellular carcinoma (HCC) patients. Using OpenSWATH and pan-human spectral library, we quantified 11,787 proteotypic peptides from 2,579 SwissProt proteins in 76 HCC tissue samples within about 9 working days (from receiving tissue to SWATH data). The coefficient of variation (CV) of peptide yield using PCT was 32.9%, and the R2 of peptide quantification was 0.9729. We identified protein changes in malignant tissues compared to matched control samples in HCC patients, and further stratified patient samples into groups with high α-fetoprotein (AFP) expression or HBV infection. In aggregate, the data identified 23 upregulated pathways and 13 ones. We observed enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues. 16 proteins of high documented relevance to HCC are highlighted in our data. We also identified changes of virus-infection-related proteins including PKM, CTPS1 and ALDOB in the HBV+ HCC subcohort. In conclusion, we demonstrate the practicality of performing proteomic analysis of biopsy-level tissue samples with PCT-SWATH methodology with moderate effort and within a relatively short timeframe.

scholarly journals Comparison of different digestion methods for proteomic analysis of isolated cells and FFPE tissue samples

Talanta ◽  
2021 ◽  
pp. 122568
Author(s):  
Artur Pirog ◽  
Jakub Faktor ◽  
Zuzanna Urban-Wojciuk ◽  
Sachin Kote ◽  
Elżbieta Chruściel ◽  
...  
Keyword(s):  
Proteomic Analysis ◽  
Ffpe Tissue ◽  
Isolated Cells ◽  
Tissue Samples ◽  
Digestion Methods

scholarly journals The Dutch National TissueArchive Portal enables efficient, consistent, and transparent procurement of diagnostic tissue samples for scientific use

2021 ◽  
Author(s):  
Robin Verjans ◽  
Annette H. Bruggink ◽  
Robby Kibbelaar ◽  
Jos Bart ◽  
Aletta Debernardi ◽  
...  
Keyword(s):  
The Netherlands ◽  
Tissue Sample ◽  
Ffpe Tissue ◽  
Tissue Samples ◽  
Internet Portal ◽  
Formalin Fixed Paraffin ◽  
Practical Support ◽  
Formalin Fixed Paraffin Embedded ◽  
The Rich ◽  
Formalin Fixed

AbstractBiobanks play a crucial role in enabling biomedical research by facilitating scientific use of valuable human biomaterials. The PALGA foundation—a nationwide network and registry of histo- and cytopathology in the Netherlands—was established to promote the provision of data within and between pathology departments, and to make the resulting knowledge available for healthcare. Apart from the pathology data, we aimed to utilize PALGA’s nationwide network to find and access the rich wealth of Formalin-Fixed Paraffin-Embedded (FFPE) tissue samples for scientific use.  We implemented the Dutch National TissueArchive Portal (DNTP) to utilize PALGA’s nationwide network for requesting FFPE tissue samples. The DNTP consists of (1) a centrally organized internet portal to improve the assessing, processing, harmonization, and monitoring of the procurement process, while (2) dedicated HUB-employees provide practical support at peripheral pathology departments. Since incorporation of the DNTP, both the number of filed requests for FFPE tissue samples and the amount of HUB-mediated support increased 55 and 29% respectively. In line, the sample procurement duration time decreased significantly (− 47%). These findings indicate that implementation of the DNTP improved the frequency, efficiency, and transparency of FFPE tissue sample procurement for research in the Netherlands. To conclude, the need for biological resources is growing persistently to enable precision medicine. Here, we access PALGA’s national, pathology network by implementation of the DNTP to allow for efficient, consistent, and transparent exchange of FFPE tissue samples for research across the Netherlands.

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