PXD008321-2

PXD008321 is an original dataset announced via ProteomeXchange.

Title	Two independent proteomic approaches provide the most comprehensive analysis of the synovial fluid proteome in responders and non-responders to Autologous Chondrocyte Implantation
Description	Background: Results obtained from our previous study using a label-free quantitation (LF) proteomic approach in which dynamic range compression was used to profile lower abundance proteins, demonstrated few proteins that were differentially abundant within the synovial fluid (SF) when comparing Autologous Chondrocyte Implantation (ACI) responders and non-responders at baseline (1). This study builds upon our previous findings by assessing higher abundance proteins within these SFs; providing a more global proteome analysis from which we can understand more fully the biology underlying ACI success or failure. Methods: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomics was used to assess SFs from ACI responders (mean Lysholm improvement of 33; n=14) and non-responders (mean Lysholm decrease of 14; n=13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins were investigated using pathway analyses and the iTRAQ proteomic dataset was combined with our published proteomic dataset of dynamically compressed SFs, from which an interactome network model of systemic protein interactions was generated. Results: iTRAQ proteomics has confirmed our previous finding that there is a marked proteome shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥2.0 fold change between Stages I and II in responders and non-responders, respectively) and has highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, that were not found in the LF study; 16 of which were altered at baseline. Two protein abundance changes (Complement C1S subcomponent and Matrix metalloproteinase 3 (MMP3), have been biochemically validated. Combination of the iTRAQ and LF proteomic datasets has generated in-depth SF proteome information that has been used to generate interactome networks representing ACI success or failure, from which functional pathways that are dysregulated in ACI non-responders have been identified. Conclusions: Several candidate biomarkers for baseline prediction of ACI outcome have been identified. A holistic overview of the SF proteome in responders and non-responders to ACI has been profiled providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders.
HostingRepository	PRIDE
AnnounceDate	2018-05-03
AnnouncementXML	Submission_2018-05-23_00:36:58.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Sally Shirran
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	iTRAQ4plex-116 reporter+balance reagent acylated residue
Instrument	TripleTOF 5600

Revision	Datetime	Status	ChangeLog Entry
0	2017-11-29 02:30:42	ID requested
1	2018-05-03 04:13:48	announced
⏵ 2	2018-05-23 00:36:59	announced	Updated publication reference for PubMed record(s): 29720234.

Hulme CH, Wilson EL, Fuller HR, Roberts S, Richardson JB, Gallacher P, Peffers MJ, Shirran SL, Botting CH, Wright KT, Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation. Arthritis Res Ther, 20(1):87(2018) [pubmed]

curator keyword: Biomedical

submitter keyword: Autologous Chondrocyte Implantation (ACI)

iTRAQ proteomics

Label-free quantification proteomics

Synovial Fluid

Cartilage repair

Osteoarthritis

Karina Wright
contact affiliation	Institute of Science and Technology in Medicine, Keele Univeristy, Keele, Staffordshire, UK Robert Jones and Agnes Hunt Orthopaedic Hospital, Oswestry, Shropshire, UK
contact email	karina.wright@rjah.nhs.uk
lab head
Sally Shirran
contact affiliation	University of St Andrews
contact email	ss101@st-andrews.ac.uk
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD008321
     1. Label: PRIDE project
     2. Name: Two independent proteomic approaches provide the most comprehensive analysis of the synovial fluid proteome in responders and non-responders to Autologous Chondrocyte Implantation