E-PROT-59
Ontology highlight
ABSTRACT:
PROVIDER: E-PROT-59 | ExpressionAtlas | 2022-01-24
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-PROT-59-analysis-methods.tsv | Tabular | |||
| E-PROT-59-analytics.tsv | Tabular | |||
| E-PROT-59-apply_fixes_zooma_mappings.done | Other | |||
| E-PROT-59-configuration.xml | Xml | |||
| E-PROT-59-percentile-ranks.tsv | Tabular |
Items per page: 5 1 - 5 of 30 |
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Project description:DDA and SWATH analysis of human kidney tissues. Data set used for PCT-SWATH paper. PCT-SWATH provides the first method to generate a digital map representing the proteome of biopsy level clinical samples from which thousands of proteins can be accurately quantified with a high degree of reproducibility across sample sets.
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Project description:Uhlén2015 - Human tissue-based proteome metabolic network - kidney
Human kidney specific proteome metabolic network
This model is described in the article:
Tissue-based map of the human proteome
Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, Sivertsson Å, Kampf C, Sjöstedt E, Asplund A, Olsson I, Edllund K, Lundberg E, Navani S, Szigyarto AC, Odeberg J, Djureinovic D, Takanen JO, Hober S, Alm T, Edqvist P, Berlin H, Tegel H, Mulder J, Rockberg J, Nilsson P, Schwenk JM, Hamsten M, von Feilitzen K, Forsberg M, Persson L, Johansson F, Zwahlen M, von Heijne G, Nielsen J, Pontén F.
Science 2015 January; 347(6220)
Abstract:
Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray–based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.
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MODEL1411240019.
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2015-01-28 | MODEL1411240019 | BioModels
Project description:here we processed 105 biopsy-level tissues from 39 prostate cancer patients using pressure cycling technology (PCT) and SWATH-MS
2018-10-17 | PXD004589 | Pride
Project description:Intra-tumor heterogeneity (ITH) has been studied at the morphologic, genomic, and transcriptomic level, but not proteomic level. Recent advances in mass spectrometric (MS) proteome quantification techniques, exemplified by SWATH-MS, a massively parallel targeting method, now also support precise quantitative proteomic comparisons across multiple samples, thus identifying molecular and implied functional differences. Here we used SWATH-MS to analyze the proteome profiles of a set of fresh-frozen prostate tissue samples derived from radical prostatectomy specimens. A high confidence set of 1,906 proteins were consistently quantified across 60 biopsy-level tissue samples from three prostatectomy patients, each consisting of 1.0 mm punch biopsies from histologically malignant (acinar and ductal adenocarcinoma) and matching benign prostatic hyperplasia tissues. The quantitative protein profiles allowed independent quantification of the degree of intra-tumor heterogeneity for each protein in benign and malignant tissues. We found that while majority of the proteins showed comparably low intra-tumor variability, 122 proteins were highly variable in malignant and/or matching benign tissues. We observed that proteins that varied between patients or tissue types also tended to be highly variable within prostate tissues, suggesting that these variability patterns will be a critical selection criterion in future protein biomarker studies. The data also permitted investigation of the heterogeneity of multiple biochemical pathways. The high variability of several of the pathways, including Glypican-1 network, alpha-linolenic acid metabolism and celecoxib pathway, explained contradictory results regarding them in the literature. In conclusion, we demonstrated a methodology for investigating proteomic intra-tumor heterogeneity from biopsy-level tissue samples, and quantified the degree of intra-tumor heterogeneity of 1,906 proteins in prostate tumors. The method and data presented here have advanced our understanding of tumor biology and offered critical insights for future biomarker development.
2018-08-13 | PXD003497 | Pride
Project description:A total of 35 samples of renal tissues (15 DN, 10 DM, and 10 CON) were selected randomly from archived deidentified formalin-fixed paraffin-embedded DN biopsy tissue specimens. Normal control kidney tissues were obtained from kidneys that had been refused for use in transplantation due to vascular anomalies or from preimplant biopsy samples. Three random samples from each group were used for lncRNA microarrays
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Project description:The identification of biomarkers indicating the level of aggressiveness of prostate cancer (PCa) addresses an urgent clinical need to minimize the general over-treatment of patients with non-aggressive PCa, which account for the majority of PCa cases. In this study we combined N-glycopeptide isolation and SWATH-MS towards the molecular characterization of tumor malignancy and aggressiveness. Here, we isolated formerly N-linked glycopeptides from normal prostate (n=10), non-aggressive (n=22), aggressive (n=16) and metastatic PCa (n=25) tumor tissues and analyzed the samples by SWATH-MS, an emerging data independent mass spectrometric acquisition method that generates a single MS file containing fragment ion spectra of all ionized species of a sample. The resulting datasets were searched using a targeted data analysis strategy where a priori spectral reference library representing known N-glycosites of the human proteome was used to identify groups of signals in the SWATH-MS data. On-average we identified 1430 N-glycosites from each SWATH map of which 1057 were quantified across all samples. The 220 glycoproteins that showed significant quantitative changes associated diverse biological processes with the level of PCa aggressiveness and metastasis and indicated functional relationships with common PCa genomic mutations.
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Project description:Clinical kidney biopsies variably contain cortex and medulla depending on biopsy depth and angle. Therefore, biopsy composition may alter the transcriptional profile and confound conclusions drawn from differential gene expression analysis. To account for this in retrieval biopsies, we assessed differences in gene expression between paired cortex and medulla samples in n=5 human kidneys.
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Project description:LC-MS/MS analysis was performed on tissue and serum samples from ten PDX mice derived from ccRCC tissues obtained through nephrectomy, autopsy, or biopsy, as well as six control non-PDX serum samples, and 32 normal human kidney samples. All data was collected in triplicate.
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Project description:Proteomic methods typically involve lengthy, multi-step sample preparation protocols (14-16 hrs), especially for the lysis and digestion of solid tissue samples or cells. We developed a streamlined proteomic sample preparation protocol termed Accelerated Barocycler Lysis and Extraction (ABLE), that substantially reduces the time and cost of tissue sample processing. ABLE is based on pressure cycling technology (PCT) for rapid tissue solubilisation and reliable, controlled proteolytic digestion. Here, the previously reported PCT protocol was optimised using 1-4 mg biopsy punches from rat kidney. The tissue denaturant urea was substituted with a combination of sodium deoxycholate (SDC) and N-propanol. ABLE produced comparable numbers of protein identifications in half the sample preparation time and with reduced cost, being ready for MS injection in 3 hrs (vs the conventional urea PCT method of 6 hrs). To validate the method, it was applied across a diverse range of rat tissues (kidney, lung, muscle, brain, testis), human HEK 293 cells and ovarian tumours by coupling PCT with SWATH-mass spectrometry (SWATH-MS). There were similar numbers of quantified proteins between ABLE-SWATH and PCT-SWATH methods, with greater than 70% overlap for all sample types, except muscle with 58% overlap. The ABLE tissue processing protocol offers a standardised, high-throughput, efficient and reproducible proteomic preparation method, accelerating sample throughput for any type of MS analysis. Coupled with SWATH-MS, ABLE has the potential to accelerate proteomics analysis towards a clinically relevant turn-around-time.
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Project description:Surgical samples have long been used as important subjects for cancer research. In accordance with an increase of neoadjuvant therapy, biopsy samples have recently become imperative for cancer transcriptome. On the other hand, both biopsy and surgical samples are available for expression profiling for predicting clinical outcome by adjuvant therapy; however, it is still unclear whether surgical sample expression profiles are useful for the prediction by the use of biopsy samples because little has been done about comparative gene expression profiling between the two kinds of samples. When gene expression profiles were compared between biopsy and surgical samples, artificially induced epithelial-mesenchymal transition (aiEMT) was found in the surgical samples. This study will evoke the fundamental misinterpretation including underestimation of the prognostic evaluation power of markers by overestimation of EMT in past cancer research, and will furnish some advice for the near future as follows: 1) Understanding how long the tissues were under an ischemic condition; 2) Prevalence of biopsy samples for in vivo expression profiling with low biases on basic and clinical research; and 3) Checking cancer cell contents and normal- or necrotic-tissue contamination in biopsy samples for prevalence.
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