Abstract
BackgroundAutologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood.MethodsIsobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF 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 in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses.ResultsiTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling.ConclusionsSeveral candidate biomarkers for baseline prediction of ACI outcome were 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.
Highlights
Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why
Identification of proteins to predict ACI outcome prior to stage I or stage II isobaric tags for absolute and relative quantitation (iTRAQ) nLC-MS/MS highlighted 16 proteins that were differentially abundant between responders and non-responders to ACI at baseline (Table 2)
Prior to stage II of the ACI procedure, 12 proteins displayed differential abundance between responders and nonresponders (Table 3). At both stages of treatment, synovial fluid (SF) analysed using iTRAQ nLC-MS/MS identified a greater number of differentially abundant proteins between individuals who did or did not respond well to ACI compared with SF that had undergone protein normalisation using the ProteoMinerTM protein enrichment kit
Summary
Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. We recently published the first study [3], to our knowledge, in which a proteomic approach has been used with the aim of identifying candidate biomarkers to predict the success of ACI, a cellular therapy for the treatment of traumatic cartilage injury [4, 5]. This therapy is composed of a two-stage procedure: During the initial surgery (stage I), healthy cartilage is harvested from a minor load-bearing region of the joint, chondrocytes are isolated and culture is expanded for 3–4 weeks prior to a second surgery (stage II), in which the chondrocytes are implanted into the cartilage defect [5, 6]. The identification of such a biomarker(s) for ACI and other cartilage repair strategies would allow for the better stratification of patients prior to joint surgery and may provide candidates for therapies to improve ACI success
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
