The poor prognosis of patients with soft-tissue sarcoma as not changed in the past several decades, highlighting the necessity for new therapeutic approaches. T-cell based immunotherapies are a promising alternative to traditional cancer treatments due to their ability to target only malignant cells, leaving benign cells unharmed. The development of successful immunotherapy requires the identification and characterization of targetable immunogenic tumor antigens. Cancer-testis antigens (CTA) are a group of highly immunogenic tumor-associated proteins that have emerged as potential targets for CD8+ T-cell recognition. In addition to identifying a targetable antigen, it is crucial to understand the tumor immune microenvironment. The level of immune infiltration and mechanisms of immune suppression within the tumor play important roles in the outcome of immunotherapy. The goal of this study is to identify targetable immunogenic antigens for T-cell based immunotherapy and to characterize the tumor immune microenvironment in human dedifferentiated liposarcoma (DDLS) by Nanostring and IHC. To assess the complexity of the human DDLS tumor immune microenvironment and to identify target antigens we used the nCounter NanoString platform to generate a gene expression profile for hundreds of genes from RNA obtained from 29 DDLS and 10 control fat FFPE samples. To classify inflammatory status of DDLS tumors, we performed hierarchical clustering based on expression levels of selected tumor inflammatory signature genes (CCL5, CD27, CD274, CD276, CD8A, CMKLR1, CXCL9, CXCR6, HLA-DQA1, HLA-E, IDO1, LAG3, PDCDILG2, PSMB10, STAT1, TIGIT). To confirm protein expression and distribution of identified antigens, we performed immunohistochemistry on human tissue micro-arrays encompassing DDLPS tumor tissues and matched normal control tissue from 63 patients. IHC for the cancer testis antigens PBK, SPA17, MAGE-A3, NY-ESO-1 and SSX2 was performed, and the staining results were scored by two authors based on maximal staining intensity on a scale of zero to three (absent=0, weak=1, moderate=2, or strong=3) and the percentage of tumor cells that stained. Hierarchical clustering of DDLS tumors based on expression of tumor inflammation signature genes revealed two distinct groups, consisting of 15 inflamed tumor and 14 non-inflamed tumors, demonstrating tumor heterogeneity within the DDLS sarcoma subtype. All antigens were found to be expressed in DDLS at an mRNA level. SPA17 was expressed at the highest levels in DDLS, however, this antigen was expressed at high levels in normal fat. Notably, antigens PBK and TTK had the largest fold change increase in expression in DDLS compared to normal fat controls. Immunohistochemical analysis of selected antigens revealed that PBK was found to be expressed in 96% (52/54) of DDLS samples at high levels. Other antigens were absent or expressed at low levels in DDLS; MAGEA3 in 15.87% (10/63) NY-ESO-1 in 6.35% (4/62) and SSX2 in 12.7% (8/63) and SPA17 in 5.5% (3/54). This data shows considerable inter-tumoral heterogeneity of inflammation, which should be taken into consideration when designing an immunotherapy for DDLS. To date, these results show promising expression of PBK antigen in DDLS, which may be used as a target in the future development of an immunotherapy for sarcoma

Tendinopathy can commonly occur around the foot and ankle resulting in isolated rupture, debilitating pain and degenerative foot deformity. The pathophysiology and key cells involved are not fully understood. This is partly because the dense collagen matrix that surrounds relatively few resident cells limits the ability of previous techniques to identify and target those cells of interest. In this study, we apply novel single cell RNA sequencing (CITE-Seq) techniques to healthy and tendinopathic foot/ankle tendons. For the first time we have identified multiple sub-populations of cells in human tendons. These findings challenge the view that there is a single principal tendon cell type and open new avenues for further study. Healthy tendon samples were obtained from patients undergoing tendon transfer procedures; including tibialis posterior and FHL. Diseased tendon samples were obtained during debridement of intractable Achilles and peroneal tendinopathy, and during fusion of degenerative joints. Single cell RNA sequencing with surface proteomic analysis identified 10 sub-populations of human tendon derived cells. These included groups expressing genes associated with fibro-adipogenic progenitors (FAPs) as well as ITGA7+VCAM1- recently described in mouse muscle but, as yet, not human tendon. In addition we have identified previously unrecognised sub-classes of collagen type 1 associated tendon cells. Each sub-class expresses a different set of extra-cellular matrix genes suggesting they each play a unique role in maintaining the structural integrity of normal tendon. Diseased tendon harboured a greater proportion of macrophages and cytotoxic lymphocytes than healthy tendon. This inflammatory response is potentially driven by resident tendon fibroblasts which show increased expression of pro-inflammatory cytokines. Finally, identification of a previously unknown sub-population of cells found predominantly in tendinopathic tissue offers new insight into the underlying pathophysiology. Further work aims to identify novel proteins targets for possible therapeutic pathways

Local recurrence along the biopsy track is a known complication of percutaneous needle biopsy of malignant musculoskeletal tumours. In order to completely excise the track with the tumour its identification is essential, but this becomes increasingly difficult over time. In an initial prospective study, 22 of 45 patients (48.8%) identified over a three-month period, treated by resection of a musculoskeletal tumour, had an unidentifiable biopsy site at operation, with identification statistically more difficult after 50 days. We therefore introduced the practice of marking the biopsy site with India ink. In all 55 patients undergoing this procedure, the biopsy track was identified pre-operatively (100%); this difference was statistically significant. We recommend this technique as a safe, easy and accurate means of ensuring adequate excision of the biopsy track. Cite this article: Bone Joint J 2013;95-B:250–3

Many orthopedic departments provide their patients with implant-specific identification cards. These cards should assist patients in various security checks and while undergoing revision surgery, especially if performed far from the primary hospital. This retrospective study was performed to evaluate patients’ use of these cards. In our department, each arthroplasty patient receives an implant-specific identification card. A phone survey was conducted among two groups of consecutive patients who underwent a lower limb arthroplasty – first group consisted of 108 patients operated a year earlier and second – 120 patients operated 3 years earlier. In the first group, 97 patients (90%) replied and in the second group – 83 patients (69%). The patients were asked the following: whether they received the card, where they keep it, what do they know about its purposes, and have they used the card for security or medical reasons. 17 patients (18%) in one-year group and 18 patients (22%) in three-years group didn’t remember the card. The rest of the patients knew the location of the card, but most of them (80% in one-year group and 72%in three-years group) knew only about the security usage of the card and not about the medical one. Many patients complained that they were not given adequate explanations about the card. Implant-specific identification cards have significant value for arthroplasty patients. However, patients use them mostly for security checks. The medical usage of this card should be explained when they receive it, so the patients can assist their surgeons while performing a revision surgery

Objectives. Osteoporosis is a chronic disease. The aim of this study was to identify key genes in osteoporosis. Methods. Microarray data sets GSE56815 and GSE56814, comprising 67 osteoporosis blood samples and 62 control blood samples, were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in osteoporosis using Limma package (3.2.1) and Meta-MA packages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify biological functions. Furthermore, the transcriptional regulatory network was established between the top 20 DEGs and transcriptional factors using the UCSC ENCODE Genome Browser. Receiver operating characteristic (ROC) analysis was applied to investigate the diagnostic value of several DEGs. Results. A total of 1320 DEGs were obtained, of which 855 were up-regulated and 465 were down-regulated. These differentially expressed genes were enriched in Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, mainly associated with gene expression and osteoclast differentiation. In the transcriptional regulatory network, there were 6038 interactions pairs involving 88 transcriptional factors. In addition, the quantitative reverse transcriptase-polymerase chain reaction result validated the expression of several genes (VPS35, FCGR2A, TBCA, HIRA, TYROBP, and JUND). Finally, ROC analyses showed that VPS35, HIRA, PHF20 and NFKB2 had a significant diagnostic value for osteoporosis. Conclusion. Genes such as VPS35, FCGR2A, TBCA, HIRA, TYROBP, JUND, PHF20, NFKB2, RPL35A and BICD2 may be considered to be potential pathogenic genes of osteoporosis and may be useful for further study of the mechanisms underlying osteoporosis. Cite this article: B. Xia, Y. Li, J. Zhou, B. Tian, L. Feng. Identification of potential pathogenic genes associated with osteoporosis. Bone Joint Res 2017;6:640–648. DOI: 10.1302/2046-3758.612.BJR-2017-0102.R1

Aims

Rotator cuff tear (RCT) is the leading cause of shoulder pain, primarily associated with age-related tendon degeneration. This study aimed to elucidate the potential differential gene expressions in tendons across different age groups, and to investigate their roles in tendon degeneration.

Aim. Microbial identification in the setting of periprosthetic joint infections (PJI) is crucial to tailor the best combination of surgical and medical treatment. Given the high cost, low sensitivity and slow results associated with traditional cultures, s synovial fluid antibody assay was developed. We asked whether antibody testing may be used as a proxy to traditional culture in the setting of PJI. Method. A retrospective study of patients who underwent revision total hip (THA) and knee (TKA) arthroplasty between January 2019 and January 2020 was performed. All patients were aspirated prior to revision surgery and antibody testing was performed. All patients had samples harvested for culture as per standard of care. Results of the two tests and their concordance when an organism was identified were compared. A frequency table was used and a McNemar test was used to compare the two methods. Results. 419 patients were included in this study. Antibody testing had a sensitivity and specificity of 21.9% and 92.5%, respectively, compared to traditional cultures. There were 78.1% of false negative and 7.5% of false positives (McNemar test p<0.001). Of the 12 patients who had positive results in both tests, 5 (41.7%) had discordant pathogens identified in each test. Conclusions. Synovial fluid antibody testing performed poorly when used as a substitute for cultures and may not be a clinically adequate surrogate despite lower cost and faster results. Not only was there a low sensitivity, but also a high rate of discordant organisms between the two tests when both were positive

Aim. Bone and Joint Infections (BJIs) present with non-specific symptoms and can be caused by a wide variety of bacteria and fungi, including many anaerobes and microorganisms that can be challenging to culture or identify by traditional microbiological methods. Clinicians currently rely primarily on culture to identify the pathogen(s) responsible for infection. The BioFire. ®. FilmArray. ®. Bone and Joint Infection (BJI) Panel (BioFire Diagnostics, Salt Lake City, UT) was designed to detect 15 gram-positive (seven anaerobes), 14 gram-negative bacteria (one anaerobe), two yeast, and eight antimicrobial resistance (AMR) genes from synovial fluid specimens in an hour. The objective of this study was to evaluate the performance of an Investigational Use Only (IUO) version of the BioFire BJI Panel (BBJIP) compared to conventional used as reference methods. Method. In a monocentric study, leftover synovial fluid specimens were collected in a single institution including 4 hospitals and tested using conventional bacterial culture (Standard of Care (SoC)) according to routine procedures following French national recommendations. Specimen has been placed in a refrigerator (4°C) as soon as possible after collection and stored for less than or equal to 7 days before enrollment. Performance of the IUO version of the BBJIP was determined by comparison to SoC for species identification. Results. To date, 201 specimens have been collected and tested using BBJIP. A total of 39 pathogens were obtained in culture. Compared to SoC culture, the overall PPA was 89.7% (35 TP, 4 FN (SA, 1; Strepto Spp, 2; P. micra, 1) and the overall NPA was 99.7% with 16 FP for a total of 5374 bacterial targets screened. Two complementary molecular tests using home-made PCR are underway to definitively conclude about the FN et FP for BBJIP observed in the preset study. Conclusions. The BioFire BJI Panel appears as a promising, sensitive, specific, and robust test for rapid detection of 31 microorganisms (including anaerobes) and eight AMR genes in synovial fluid specimens. The number of pathogens and resistance markers included in the BioFire BJI Panel, together with a reduced time-to-result and increased diagnostic yield compared to culture, is expected to aid in the management of BJIs

Aims

This study aimed, through bioinformatics analysis and in vitro experiment validation, to identify the key extracellular proteins of intervertebral disc degeneration (IDD).

Aims

Osteoarthritis (OA) is a common degenerative joint disease. The osteocyte transcriptome is highly relevant to osteocyte biology. This study aimed to explore the osteocyte transcriptome in subchondral bone affected by OA.

INTRODUCTION. The timely identification of outliers (implants, surgeons or patients) using prospectively collected registry data is confounded by many factors, including the assumption that the sampled population is representative of the entire cohort of patients. In this study we utilized a computer simulation of a joint registry to address the question: How does incomplete enrollment of patients in registries affect the reliability of identification of outliers, and what percent capture of the target population is sufficient?. MATERIALS AND METHODS. A synthetic registry was created consisting of 10,000 patients (100 surgeons), of whom, 1000 underwent joint replacement using a new implant. A predictive model for the risk of revision was created from data published by the Swedish TKR Registry and the AOANJRR. The pairing of patients, surgeons and implants was randomized and for each assignment, the probability of revision was computed. We then chose random samples of all patients in 10% increments from 10% to 100%, simulating incomplete capture of all potential cases by the registry. For each sample we calculated the number of cases of the new implant predicted to end in revision. The assignments were repeated 2000 times using implants with revision rates of 1.5%, 2.0% and 3.0% per annum vs. 1.0% for all other implants of the same class. RESULTS. The observed failure rate of the new implant averaged 2.0%, but varied from 0.7–3.8% over the 2000 trials, with 100% enrollment. With only 10% enrollment, the spread of failure rates increased to 0.0–7.8%, corresponding to a 152% increase in the variability of the observed revision rate. When enrollment was increased from 80% to 100%, the variability of the failure rate changed by only 9% from a range of 1.63% (1.23–2.86%) to 1.50% (1.30–2.80%) (90% CI). The reliability of detection of poorly performing implants improved dramatically with enrollment. With 70% enrollment, an implant with a 2.0% failure rate could be detected with 95% confidence, while a 3.0% implant became apparent with only 21% enrollment. Conversely, with even 100% enrollment it was not possible to identify implants with a 1.5% annual failure rate with 95% confidence. CONCLUSIONS. If registries collect a truly representative sample of only 50–80% of the total patient population, there will be only a slight increase in the risk of overlooking an inferior outlier, including poorly-performing implants, compared to 100% patient capture. Our results suggest that enrollment of every patient receiving a given treatment is not nearly as important as randomization of the sample subjected to analysis

We have investigated the errors in the identification of the transepicondylar axis and the anteroposterior axis between a minimally-invasive and a conventional approach in four fresh-frozen cadaver knees. The errors in aligning the femoral prosthesis were compared with the reference transepicondylar axis as established by CT. The error in the identification of the transepicondylar axis was significantly higher in the minimal approach (4.5° of internal rotation, . sd. 4) than in the conventional approach (3° of internal rotation, . sd. 4; p < 0.001). The errors in identifying the anteroposterior axis in the two approaches were 0° (. sd. 5) and 1.8° (. sd. 5) of internal rotation, respectively (p < 0.001)

Objectives. In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion. Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation. Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594–601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1

The most common reasons for total joint arthroplasty (TJA) failure are aseptic loosening (AL) and prosthetic joint infection (PJI). There is a big clinical challenge to identify the patients with high risk of AL/PJI before the TJA surgery. Although there is evidence that genetic factors contribute to the individual susceptibility to AL/PJI, a predictive model for identification of patients with a high genetic risk of TJA failure has not been developed yet. We aimed to develop a risk evaluation tool utilising the AL/PJI-associated polymorphisms for identification of patients with high genetic risk of TJA failure based on inflammation-gene polymorphism panel. Based on allele and genotype frequencies of twenty-five single nucleotide polymorphisms (SNPs) in TNF, IL2, IL6, IL10, IL1b, IL-1Ra, MBL2, MMP1, FTO genes and those influencing the serum levels of biomarkers of TJA outcomes (IL6, CCL2/MCP-1, CRP, ESR) in peripheral blood obtained from patients with TJA (AL, n=110; PJI, n=93; no complications, n=123), we calculated a hazard ratio and a relative entropy of alleles and genotypes associated with AL and PJI and their combinations in patient subgroups. We conducted a risk evaluation tool based on the presence of risk alleles and genotypes in TNF (rs361525, rs1800629), DARC (rs12075), MBL2 (rs11003125) and FTO (rs9939609, rs9930506) genes associated with implant failure (AL/PJI). Of these, FTO gene variations (rs9939609, rs9930506) were associated mainly with PJI (P=0.001, OR=2.04, 95%CI=1.132–2.603; P=0.011, OR=1.72, 95%CI=1.338–3.096) and DARC (rs12075) with AL (P=0.005, OR=1.79, 95%CI=1.193–2.696). This tool calculates a hazard ratio of a combination of SNPs associated with AL and PJI for identification of patients with high and low risk of AL/PJI TJA failure. We proposed a risk evaluation tool for stratification of patients before the TJA surgery based on the genetic risk of AL/PJI development. The effect size for each genotype combination described in the study is small. Further multiparametric data analysis and studies on an extended patient cohort and other non-genetic and genetic parameters are ongoing. Grant support: AZV MZ CR VES16-131852A, VES15-27726A, IGA LF UP_2016_011

Introduction. The number of complex revision total hip arthroplasties (THA) is predicted to rise. The identification of acetabular bone defects prior to revision THA has important implications on technique and complexity of acetabular reconstruction. Paprosky et al. proposed a classification system including 3 main types with up to 3 subtypes focused on the integrity of the superior rim of the acetabulum and medial wall. However, the classification system is complex and its reliability has been questioned. The purpose of this study was to evaluate the effectiveness of different radiologic imaging modalities (plain radiographs, 2-D CT, 3-D CT reconstructions) in classifying acetabular defects in revision hip arthroplasty cases and their value of at different levels of orthopaedic training. Methods. Patients treated with revision total hip arthroplasty for acetabular bone defects between 2002–2012 were identified and 22 cases selected that had plain radiographs, 2-D CT and 3-D reconstructions available. Bone defects were classified independently by two fellowship-trained adult reconstruction surgeons. Representative sections were chosen and compiled into a timed presentation. Thirty-five residents from PGY-1 to PGY-5 and 4 attending orthopaedic surgeons were recruited for this study and received a 15-minute introduction to the classification system. Chi square analysis was utilized to examine the influence of image modality and level of training on the correct classification of acetabular bone loss using the Paprosky classification system with alpha=0.05. Results. The correct classification regardless of imaging of PGY levels was 30%. The level of training did not influence the ability to classify an acetabular defect (p=0.918). Correct classification was significantly influenced by the imaging used. Using x-ray led to 37% correctly identified defects, CT scans to 33% and 3D modeling to 30% of correct answers (p<0.001). For Class 1 defects, x-ray imaging had significantly higher number of correct classification (93%) compared to CT scans (67%) and 3D modeling (31%, p<0.001). Similarly, 2A defects were classified correctly with higher frequency on x-ray (49%) compared to CT scans (36%) or 3D modeling (15%, p=0.007). For type 2B, 2C, 3A and 3B defects, the type of imaging did not influence the frequency of correct answer. The level of training did not influence the frequency of correct classification regardless of the type of defect (p<0.05). However, there was a significant difference based on the defect type (p<0.001). Regardless of level of training or imaging, 64% of observers recognized type 1 defects, compared to only 16% correct recognition of 3B defects. Discussion. In the current study using different image modalities, residents regardless of the level of training were only able to classify 30% of defects correctly using the Paprosky classification system of acetabular defects. Using plain x-rays led to an increased number of correct classification, while regular CT scan and 3D CT reconstructions did not improve accuracy. The cost for advanced imaging when using this classification may not be justified. The Paprosky classification system of acetabular defects can be used for treatment decisions; however, it is complex and residents may require increased education in its use and identification of defects

Percutaneous biopsies can lead to seeding of tumour cells along the biopsy tract. Correct surgical management requires preoperative identification and excision of the biopsy tract at time of surgery. These tracts become increasingly difficult to identify with time, leading to risk of inadequate excision of the biopsy tract and recurrence of the tumour at the biopsy site. We conducted a prospective study involving 45 patients who had tissue biopsies for bone and soft tissue tumours between February and May 2008. All the biopsies were performed by consultant radiologist under ultrasound or CT guidance. Case note analysis, patient history and examination at the time of surgery were used to collect data. 23 of 45 patients had accurate identification of the biopsy tract by the surgeon at the time of excision. The mean time between biopsy and excision was 52 days (range 6–140). 22 of 45 patients had unidentifiable biopsy site, with the mean time between biopsy and excision being 98 days(range 13–164) p=0.0004(paired t test). All 4 patients who received post-biopsy radiotherapy had unidentifiable biopsy site tract (mean duration 104 days) and 11 of the 18 patients who underwent neoadjuvant chemotherapy had an unidentifiable biopsy tract (mean duration 108 days). We concluded that identification of biopsy site was more difficult after 50 days, especially in patients who underwent radiotherapy and chemotherapy. Following this study, all the patients who had biopsies of tumours had the site marked with India ink tattoo. We, then prospectively reviewed 36 patients between July and September 2010 who underwent excision of bone and soft tissue tumours and had their biopsy sites marked with India ink tattoo. After needle biopsy, one drop of the dye was applied at the site of the biopsy. This was taken up by capillary action beneath the dermis and remained present until the patient returned for their definitive surgery. The biopsy site was easily identifiable by the patients and the operating surgeon in all 36 patients. The mean time between biopsy and surgery was 77 days (range 10–299 days). Tattooing of the skin enabled the surgeon to accurately excise the biopsy tract along with the tumour. We recommend this technique of tattooing of the biopsy site with India ink, as it is safe, easily recognisable and permits accurate excision of the tract (including the tattoo), therefore preventing biopsy tract recurrence

Introduction: Seeding of bone or soft tissue tumour along the biopsy tract is a known complication of percutaneous biopsies. Correct surgical management requires preoperative Identification and excision of the biopsy tract at time of surgery. We aim to audit how well biopsy tract sites can be identified preoperatively and investigate factors influencing their Identification. Method: Prospective audit of patients who had tissue biopsies for bone and soft tissue tumours at the RNOH Stanmore and presented for surgery between February and April 2008. Case note analysis, patient history and examination at the time of surgery used to collect data. Results: 13/23 patients had their biopsy tract site accurately identified preoperatively, with a mean time gap of 43 days (6–118) between biopsy and excision. In 10/23 patients the biopsy site could not be accurately identified preoperatively. In these patients the mean time between biopsy and excision was 106 days (55–158) (p=< 0.05). 7 patients had neoadjuvant chemotherapy with a mean time gap of 110 days; in 5/7 the tract site was unidentifiable. One patient had preoperative radiotherapy and the biopsy site was unidentifiable. Discussion: This audit has shown that Identification of the biopsy site is more difficult after 40 days. In order to ensure accurate Identification of the biopsy site an Indian ink tattoo should be considered at time of biopsy. It may be particularly advisable for patients who are likely to require neoadjuvant chemotherapy or preoperative radiotherapy. On this basis we would recommend that all patients have the biopsy site marked at the time of biopsy and a further audit will be carried out to evaluate this change in practice

Stratification is required to ensure that only those patients likely to benefit, receive Autologous Chondrocyte Implantation (ACI); ideally by assessing a biomarker in the blood. This study aimed to assess differences in the plasma proteome of individuals who respond well or poorly to ACI.

Isobaric tag for relative and absolute quantitation (ITRAQ) mass spectrometry and label-free proteomics analyses were performed in tandem as described previously by our group (Hulme et al., 2017; 2018; 2021) using plasma collected from ACI responders (n=10) compared with non-responders (n=10) at each stage of surgery (Stage I, cartilage harvest and Stage II, cell implantation).

iTRAQ using pooled plasma detected 16 proteins that were differentially abundant at baseline in ACI responders compared with non-responders (n=10) (≥±2.0 fold; p<0.05). Responders demonstrated a mean Lysholm (patient reported functional score from 0–100) improvement of 33±13 and non-responders a mean worsening of −13±13 points. The most pronounced plasma proteome shift was seen in response to Stage I surgery in ACI non-responders, with 48 proteins being differentially abundant between the two surgical procedures. We have previously noted this marked shift in response to initial surgery in the SF of ACI non-responders, several of these proteins were associated with the Acute Phase Response. One of these proteins, clusterin, could be confirmed in patients’ plasma using an independent immunoassay using individual samples. Label-free proteomic data from individual samples identified only cartilage acidic protein-1 (known to associate with osteoarthritis progression) to be significantly more abundant at Stage I in the plasma of non-responders.

This study indicates that proteins can be identified within the plasma that have potential use in ACI patient stratification. Further work is required to validate the findings of this discovery-phase work in larger ACI cohorts.

Introduction. Local recurrence of tumours along the biopsy tract is a known complication of percutaneous closed needle biopsy. Correct surgical management requires preoperative identification and excision of the biopsy tract at time of surgery. These tracts become increasingly difficult to identify with time, leading to risk of inadequate excision of the biopsy tract and recurrence of the tumour at the biopsy site. Materials/Methods. In a prospective study conducted at our institution, 22 of the 45 patients with musculoskeletal tumours (49%) had unidentifiable biopsy sites, with a mean duration between biopsy and definite surgery being 98 days (range 13–164 days). We concluded that identification of the biopsy site was more difficult after 50 days. Radiotherapy related scar formation and the longer time duration between biopsy and definite surgery in patients requiring neoadjuvant therapy made identification more unlikely. Consequently, all patients received India ink skin tattoo to mark the biopsy site at the time of the needle biopsy. 56 patients were then prospectively reviewed on the day of surgery to identify the biopsy site. Results. The biopsy tract was easily identifiable in all 56 patients (100%) by junior and senior orthopaedic surgeons. The mean duration between the skin tattoo and surgery was 68 days (range 12–299 days). Radiotherapy and chemotherapy did not influence the identification of the tattoo site. Conclusions. Tattooing the skin with India ink enabled the surgeon to accurately excise the biopsy tract. We recommend this technique of tattooing the biopsy site with India ink as it is safe, easily recognisable and aids in accurate excision of the tract and the tattoo site

Introduction. Yellow flags are psychosocial indicators which are associated with a greater likelihood of progression to persistent pain and disability and are referred to as obstacles to recovery. It is not known how effective clinicians are in detecting them. Our objective was to determine if clinicians were able to detect them in secondary care. Methods. 111 new referrals in a specialist spine clinic completed the Oswestry Disability Index (ODI) and a range of other validated questionnaires including the yellow flag questionnaire adapted from the psychosocial flags framework. Clinicians blinded to the patient data completed a standardized form to determine which and how many yellow flags they had identified. Results. The average number of yellow flags per patient was 5 (range: 0–9). Clinician sensitivity in detecting yellow flags was poor, identifying only 2 on average. The most common yellow flag reported by patients was fear of movement or injury (88%), and this was also the yellow flag most frequently missed by clinicians, being identified correctly in only 45% of patients. The most commonly misidentified was patient uncertainty, in 28% of patients. Patients who reported more yellow flags were more likely to score higher on their ODI (p<0.01), Modified somatic perception score (p<0.01) and Modified Zung Depression Index (p<0.01). They also had poorer Low Back Outcome Scores (LBOS) (p<0.01). Conclusion. Clinician sensitivity in detecting yellow flags is poor. Improved identification of obstacles to recovery may improve outcomes. Clinicians may improve detection of these obstacles by having a simple set of questions completed by the patient