Novel Biomarkers For Prediction Research Articles

11P Human papillomavirus integration: A novel biomarker for prediction of overtreatment in cervical intraepithelial neoplasia grade 2 or 3 patients with non-high-grade cytology abnormalities

11P Human papillomavirus integration: A novel biomarker for prediction of overtreatment in cervical intraepithelial neoplasia grade 2 or 3 patients with non-high-grade cytology abnormalities

Role of stanniocalcin-1 and proenkephalin-A as novel biomarkers in prediction of newly diagnosed type 2 diabetic patients

Role of stanniocalcin-1 and proenkephalin-A as novel biomarkers in prediction of newly diagnosed type 2 diabetic patients

Investigation of type 1 collagen a1 chain in plasma as a potential novel biomarker for prediction of coronary heart disease

Abstract Background Remodeling of the extracellular matrix (ECM) plays a crucial role in development and progression of atherosclerosis. Collagens, in particular type I collagen, are the most abundant ECM proteins in an atherosclerotic plaque. Recently, type I collagen α1 chain (COL1α1) in plasma was identified as a potential predictor of coronary heart disease (CHD). Aim The aim was to further confirm the predictive value of COL1α1 and also to investigate its correlates in a population-based cohort as well as changes over time in patients with manifest CHD in Sweden. Methods In a total of 1007 well-characterized individuals (50% women), 86 CHD cases and 184 sex- and age-matched controls were identified at 13 years follow-up. CHD at follow-up was defined as first-time event of myocardial infarction (MI) or invasive coronary intervention. Plasma levels of COL1α1 was quantified by the Luminex assay while PRO-C1 and C1M, two markers of type I collagen synthesis and degradation, respectively, were quantified by ELISA. In Cox proportional hazard analysis, log2 values of biomarker levels were used. In addition, temporal change of COL1α1 levels was also examined in a cohort of 125 patients with acute MI followed for 6 months. Results COL1α1 levels were significantly associated with incident CHD, both unadjusted (HR = 0.69, 95% CI 0.56–0.87, p=0.001) and after multiple adjustment (HR = 0.55, 95% CI 0.41–0.75, p<0.001). PRO-C1 was similarly associated with CHD, unadjusted (HR = 0.62, 95% CI 0.47–0.82, p=0.001) as well as adjusted (HR = 0.61, 95% CI 0.43–0.86, p=0.005), while C1M was not. In patients with acute MI, COL1α1 levels remained stable over 6 months. COL1α1 was significantly correlated to PRO-C1 (r=0.73, p<0.001), while there were no correlations to C1M, markers of inflammation (C-reactive protein, interleukin-6, matrix metalloproteinase-9) or myocardial injury (troponin T). Conclusions Circulating COL1α1 in plasma was independently and inversely associated with incident CHD. Furthermore, COL1α1 levels appeared to be relatively stable after an acute MI. COL1α1 levels seem to reflect collagen synthesis rather than collagen degradation and inflammation. Future studies are needed to confirm whether COL1α1 is a clinically useful marker and/or predictor of CHD. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): This research was in part financed by a grant from the Region of Östergötland, Sweden, aimed towards scientists early in their career. We would like to thank the people behind this grant for contributing to this research.This research was also partly supported by Futurum - the academy for healthcare in Region Jönköping County.

Novel Biomarkers for Prediction of Acute Kidney Injury After Open Heart Surgery: A Comparative Study

Novel Biomarkers for Prediction of Acute Kidney Injury After Open Heart Surgery: A Comparative Study

Pentraxin 3 in Circulating Microvesicles: a Potential Biomarker for Acute Heart Failure After Cardiac Surgery with Cardiopulmonary Bypass.

The aim of this study was to investigate whether pentraxin 3 (PTX3) in microvesicles (MVs) can be a valuable biomarker for the prediction of acute heart failure (AHF) after cardiac surgery with cardiopulmonary bypass (CPB). One hundred and twenty-four patients undergoing cardiac surgery with CPB were included and analyzed (29 with AHF and 95 without AHF). The concentrations of PTX3 in MVs isolated from plasma were measured by ELISA kits before, 12h, and 3days after surgery. Patients' demographics, medical history, surgical data, and laboratory results were collected. The levels of PTX3 in MVs were significantly elevated during perioperative surgery, which was increased more in the AHF group. The concentrations of PTX3 in MVs at postoperative 12h were independent risk factors for AHF with the area under the ROC curve of 0.920. The concentration of PTX3 in MVs may be a novel biomarker for prediction of AHF after cardiac surgery.

Circulating exosome-derived miR-122-5p is a novel biomarker for prediction of postoperative atrial fibrillation.

Postoperative atrial fibrillation (POAF) is a frequent complication associated with increased periprocedural mortality and morbidity after cardiac surgery. Our study aimed to identify the difference in exosomal miRNA and further explore its role in the diagnosis of POAF. First, the differentially expressed miRNAs (DEMs) were obtained by high-throughput RNA sequencing. Second, the DEMs target genes were put into gene ontology (GO) and KEGG pathway analysis. Third, real-time quantification PCR (RT-qPCR) was used to verify the DEMs. Finally, we revealed 23 DEMs in POAF patients. Furthermore, analysis of gene function revealed that DEMs may affect atrial structure through many signaling pathways. We also found that miR-122-5p was up-regulated in POAF patients, but there are no significant changes in miR-191-5p, miR-181a-5p, miR-155-5p and miR-151a-5p. Our study revealed that exosomal miRNAs exert enormous potential in evaluating the severity or prognostic of POAF.

The Importance of SNPs at miRNA Binding Sites as Biomarkers of Gastric and Colorectal Cancers: A Systematic Review.

Dysregulated mRNA–miRNA profiles might have the prospective to be used for early diagnosis of gastrointestinal cancers, estimating survival, and predicting response to treatment. Here, a novel biomarker based on miRNAs binding to mRNAs in single nucleotide polymorphism (SNP) sites related to gastrointestinal cancers is introduced that could act as an early diagnosis. The electronic databases used for the recruiting published articles included EMBASE, SCOPUS, Web of Science, and PubMed, based on MESH keywords and PRISMA methodology. Based on the considered criteria, different experimental articles were reviewed, during which 15 studies with the desired criteria were collected. Accordingly, novel biomarkers in prediction, early prognosis, and diagnosis of gastrointestinal cancers were highlighted. Moreover, it was found that 20 SNP sites and 16 miRNAs were involved in gastrointestinal cancers, with altered expression patterns associated with clinicopathological and demographic data. The results of this systematic study revealed that SNPs could affect the binding of miRNAs in the SNP sites that might play a principal role in the progression, invasion, and susceptibility of gastrointestinal cancers. In addition, it was found that the profiles of SNPs and miRNAs could serve as a convenient approach for the prognosis and diagnosis of gastric and colorectal cancers.

Identification of HBEGF+ fibroblasts in the remission of rheumatoid arthritis by integrating single-cell RNA sequencing datasets and bulk RNA sequencing datasets

BackgroundFibroblasts are important structural cells in synovium and play key roles in maintaining the synovial homeostasis. By single-cell RNA sequencing (scRNA-seq), subpopulation of synovium-resident cells has been reported to protect intra-articular structures from chronic inflammation and promote tissue repair. However, a significant number of researchers have concentrated on the role of fibroblasts in the progress of rheumatoid arthritis (RA) while few reports had described the contribution of distinct fibroblast subsets in the RA remission. It is helpful to understand the role of fibroblast subpopulations in the RA process to provide predictive biomarkers and address RA remission mechanisms. Here, we found HBEGF+ fibroblasts that contributed to RA remission by integrating scRNA-seq datasets and bulk RNA sequencing (bulk RNA-seq) datasets.MethodThree single-cell RNA datasets of cells harvested from RA patients were processed and integrated by Seurat and Harmony R packages. After identifying cell types by classic marker genes, the integrated dataset was used to run CellChat for analysis of cell-cell communication. Specially, EGF signaling pathway was found and HBEGF+ fibroblasts were identified based on HBEGF expression. Differential expressed genes of HBEGF+ were shown in heatmap and volcano plot and used to run gene ontology (GO) enrichment analysis. Next, bulk RNA-seq datasets of synovium under different conditions (health, osteoarthritis (OA), rheumatoid arthritis, before and after classical treatment) were compared to show expression change of HBEGF and gene markers that are mainly expressed by HBEGF+ fibroblasts such as CLIC5, PDGFD, BDH2, and ENPP1. Finally, two single-cell RNA sequencing datasets of synovial cells from mice were integrated to identify Hbegf+ fibroblasts and calculate the population of Hbegf+ fibroblasts under different joint conditions (health, K/BxN serum transfer arthritis (STA), and remission of STA).ResultAfter integrating three single-cell RNA sequencing datasets, we identified 11 clusters of synovial cells, such as fibroblasts, mural cells, endothelial cells, CD4+ T cells, CD8+ T cells, natural killer cells, synovium macrophage, peripheral blood macrophages, plasma cells, B cells, and STMN1+ cells. We found fibroblasts had an extensive communication network with other clusters and interacted with synovial macrophages through EGF signaling pathway via analysis of cell-cell communication between synovial cells. HBEGF, ligand to EGF signaling pathway, was highly expressed by a subset of fibroblasts and macrophages, and EGFR, receptor to EGF signaling pathway, was highly expressed by fibroblasts and meniscus cells. Moreover, HBEGF was downregulated under RA state and it had an increase after classical treatment. We then defined fibroblasts with high expression of HBEGF as HBEGF+ fibroblasts. In addition, we also found that HBEGF+ fibroblasts highly expressed CRTAC1, ITGB8, SCARA5, THBS4, and ITGBL1, genes relative to encoding extracellular matrix proteins and engaged in positive regulation of cell migration and motility, cellular component movement, and cell growth by GO enrichment analysis. We eventually identified HBEGF+ fibroblasts specially expressed CLIC5, PDGFD, BDH2, and ENPP1, which positively correlated with the expression of HBEGF. Moreover, the expression of CLIC5, PDGFD, BDH2, and ENPP1 was downregulated under RA state and elevated by classical therapy. On the contrary, the HBEGF+ macrophages specially expressed SLAMF8, GK, L1RN, and JAK2, which negatively correlated with the expression of HBEGF. The expression was upregulated in SLAMF8, GK, L1RN, and JAK2 under the RA state, whereas it was decreased after classical treatment. In mice, the number of Hbegf+ fibroblasts was reduced in the RA synovium but increased in the RA remitting synovium.ConclusionsHBEGF+ fibroblasts play a role in the remission of rheumatoid arthritis, and HBEGF has potential to become a novel biomarker for prediction of RA progress.

Body composition predictors of mortality on computed tomography in patients with spinal metastases undergoing surgical treatment

Background contextAlthough survival of patients with spinal metastases has improved over the last decades due to advances in multi-modal therapy, there are currently no reliable predictors of mortality. Body composition measurements obtained using computed tomography (CT) have been recently proposed as biomarkers for survival in patients with and without cancer. Patients with cancer routinely undergo CT for staging or surveillance of therapy. Body composition assessed using opportunistic CTs might be used to determine survival in patients with spinal metastases. PurposeThe purpose of this study was to determine the value of body composition measures obtained on opportunistic abdomen CTs to predict 90-day and 1-year mortality in patients with spinal metastases undergoing surgery. We hypothesized that low muscle and abdominal fat mass were positive predictors of mortality. Study designRetrospective study at a single tertiary care center in the United States. Patient sampleThis retrospective study included 196 patients between 2001 and 2016 that were 18 years of age or older, underwent surgical treatment for spinal metastases, and had a preoperative CT of the abdomen within three months prior to surgery. Outcome measuresNinety-day and 1-year mortality by any cause. MethodsQuantification of cross-sectional areas (CSA) and CT attenuation of abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and paraspinous and abdominal skeletal muscle were performed on CT images at the level of L4 using an in-house automated algorithm. Sarcopenia was determined by total muscle CSA (cm2) divided by height squared (m2) with cutoff values of <52.4 cm2/m2 for men and <38.5 cm2/m2 for women. Bivariate and multivariate Cox proportional-hazard analyses were used to determine the associations between body compositions and 90-day and 1-year mortality. ResultsThe median age was 62 years (interquartile range=53–70). The mortality rate for 90-day was 24% and 1-year 54%. The presence of sarcopenia was associated with an increased 1-year mortality rate of 66% compared with a 1-year mortality rate of 41% in patients without sarcopenia (hazard ratio, 1.68; 95% confidence interval, 1.08–2.61; p=.02) after adjusting for various clinical factors including primary tumor type, ECOG performance status, additional metastases, neurology status, and systemic therapy. Additional analysis showed an association between sarcopenia and increased 1-year mortality when controlling for the prognostic modified Bauer score (HR, 1.58; 95%CI, 1.04–2.40; p=.03). Abdominal fat CSAs or muscle attenuation were not independently associated with mortality. ConclusionsThe presence of sarcopenia is associated with an increased risk of 1-year mortality for patients surgically treated for spinal metastases. Sarcopenia retained an independent association with mortality when controlling for the prognostic modified Bauer score. This implies that body composition measurements such as sarcopenia could serve as novel biomarkers for prediction of mortality and may supplement other existing prognostic tools to improve shared decision making for patients with spinal metastases that are contemplating surgical treatment.

Clinical value of miR-191-5p in predicting the neurological outcome after out-of-hospital cardiac arrest.

The diagnostic and prognostic value of microRNAs (miRNA) in human disease has been confirmed in a number of clinical studies. The purpose of this study was to investigate the predictive value of miR-191-5p in the neurological outcome of patients recovering from out-of-hospital cardiac arrest (OHCA). A total of 260 patients undergoing the target temperature management trial were analyzed. The expression level of serum miR-191-5p was detected by qRT-PCR at 48h after return of spontaneous circulation (ROSC). ROC curve was established to evaluate the ability of miR-191-5p as a biomarker for predicting adverse neurological outcomes after OHCA. Kaplan-Meier curve and Cox regression analysis were used for survival analysis. One hundred eighteen patients (45%) had poor neurological outcomes at 6months. The expression level of serum miR-191-5p in patients with poor neurological outcomes was significantly lower than that in patients with good neurological prognosis (P < 0.001) and was not associated with TTM trial. The AUC, sensitivity, and specificity of the ROC curve were 0.899, 84.7%, and 82.4%, respectively, suggesting that the level of miR-191-5p had the ability to predict neurological outcome. By the end of the experiment, 88 patients (34%) were dead. Results of survival analysis showed that lower miR-191-5p expression level was significantly associated with lower survival rate (HR: 0.344, 95% CI = 0.208-0.567, P < 0.001). The level of miR-191-5p was down-regulated in patients with poor neurological outcomes, and it could be used as a promising novel biomarker for prediction of neurological outcome and survival after OHCA.

111. Can body composition measures on computed tomography predict mortality in patients with spinal metastases undergoing surgery?

<h3>BACKGROUND CONTEXT</h3> Although survival of patients with spinal metastases has improved in recent decades due to advances in multimodal therapy, there are currently no reliable predictors of mortality. Computed tomography (CT) body composition measurements have been recently proposed as biomarkers for survival in patients with and without cancer. Patients with cancer routinely undergo CT for staging or surveillance of therapy and body composition assessed using opportunistic CTs might be used to determine survival in patients with spinal metastases. <h3>PURPOSE</h3> The purpose of our study was to determine the value of body composition measures obtained on opportunistic abdomen CTs to predict 90-day and 1-year mortality in patients with spinal metastases undergoing surgery. We hypothesized that low muscle and abdominal fat mass were predictors of mortality. <h3>STUDY DESIGN/SETTING</h3> Retrospective cohort. <h3>PATIENT SAMPLE</h3> Between 2001 and 2016, 196 patients who underwent surgery for spinal metastases at a single tertiary center underwent CT of the abdomen within three months prior to surgery. <h3>OUTCOME MEASURES</h3> Ninety-day and 1-year mortality. <h3>Methods</h3> Quantification of cross-sectional areas (CSA) and CT attenuation in Hounsfield units (HU) of abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and paraspinous skeletal muscle were performed on CT images at the level of L4 using an in-house automated algorithm under the supervision of a fellowship-trained musculoskeletal radiologist. Sarcopenia was determined by total muscle area (cm²) divided by height squared (m²) with cutoff values of <52.4 cm²/m² for men and <38.5 cm²/m² for women. Bivariate and multivariate Cox proportional-hazard analyses were used to determine the associations between body compositions and 90-day and 1-year mortality. <h3>Results</h3> The median age was 62 years (interquartile range = 53-70). Mortality rates at 90 days and 1 year were 24% and 54%, respectively. Sarcopenia and decreased muscle attenuation were associated with increased mortality for both timepoints (p=0.04 and p=0.04, respectively) after controlling for sex, age, body mass index, Charlson Comorbidity score, primary tumor type, visceral metastases, and duration between diagnosis of spinal metastases and surgery. Decreased SAT area was associated with increased 90-day mortality after controlling for the same covariates (p<0.01). <h3>Conclusions</h3> Decreased muscle attenuation and sarcopenia are independently associated with an increased risk of 90-day and 1-year mortality for patients surgically treated for spinal metastases, and low SAT CSA is independently associated with increased risk of 90-day mortality. Therefore, body composition measurements could serve as novel biomarkers for prediction of mortality in patients with spinal metastases. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.

NGS-based multi-factor prediction model of platinum sensitivity for epithelial ovarian cancer

<h3>Objectives:</h3> Platinum sensitivity is the most important predictor of prognosis and response to further treatment in ovarian cancer, while it is still roughly prejudged in line with the interval of progression free survival in clinical practice. Realizing individualized precision medicine require refining predictive model that could enable selection of patients who would benefit from platinum-based or non-platinum containing therapy. The study aims to identify and integrate novel biomarkers for prediction of platinum sensitivity in ovarian cancer. <h3>Methods:</h3> 60 patients with epithelial ovarian cancer receiving standard initial treatment were recruited from 2016 to 2019. According to interval of progress free survival (PFS), 44 patients (PFS>6 months) and 16 patients (PFS≤6 months) were defined as platinum-sensitive and platinum-resistant recurrence, respectively. We performed next generation sequencing (NGS) analysis of the entire genomic features of ovarian tumor tissue samples obtained from debulking surgery. Multiple genomic variation were compared between platinum sensitive and resistant patients, including single-nucleotide variant (SNV), single base or indel signature, focal copy number variation (CNV), mutational clonality, whole-genome duplication (WGD), and co-variation in DNA damage repair (DDR) pathways. Collectively, a multi-factor-based prediction model was trained and validate with Lasso regression. <h3>Results:</h3> Analysis of single base signature revealed that the contribution of SBS10a in platinum-sensitive patients was significantly higher than that of platinum-resistant patients (P<0.05). Consistently, patients with SBS10a signature exhibited higher platinum sensitivity (P<0.01) and longer PFS than SBS10a negative patients (15.8m vs 10.1m, P<0.05). Focal CNVs involved in DDR pathways which believed to play a pivotal role in platinum response were emphatically investigated. The results demonstrated the incidence of FAM175A LOH in platinum-sensitive patients was significantly higher than that of platinum-resistant patients (P<0.01), meanwhile the median PFS of patients with FAM175A LOH was significantly longer than patients with wild-type FAM175A (16.5m vs 9.2m, P<0.05). Moreover, patients with WGD showed higher proportion of platinum resistance (P<0.01) and shorter median PFS than patients with normal chromosomal ploidy (9.1m vs 16.47m, p<0.05). Unlucky, there was no marked difference in the distribution of overall SNV or DDR related SNV with top frequency between platinum sensitive and resistant cases. Patients with clonal DDR mutations or co-variation in DDR pathways exhibited higher proportion of platinum response and longer PFS than patients without these variations, but the differences were not statistically significant. By integrating of SBS10a, FAM175A LOH and WGD which showed significant differences in platinum sensitivity in univariate analyses, a lasso regression model was employed to train and validate with all patients. A promising performance with the AUC value 0.864 was observed in ROC curve, suggesting the predictive performance of this model was favorable. <h3>Conclusions:</h3> Our study successfully established a prediction model containing three novel biomarkers FAM175A LOH, SBS10a mutation and WGD through in-depth mining of NGS, which has an extremely potential of predictive value for platinum sensitivity in epithelial ovarian cancer. However, it requires larger cohort for further validation.

Surface-Based Falff: A Potential Novel Biomarker for Prediction of Radiation Encephalopathy in Patients With Nasopharyngeal Carcinoma.

Radiation encephalopathy (RE) is an important potential complication in patients with nasopharyngeal carcinoma (NPC) who undergo radiotherapy (RT) that can affect the quality of life. However, a functional imaging biomarker of pre-symptomatic RE has not yet been established. This study aimed to assess radiation-induced gray matter functional alterations and explore fractional amplitude of low-frequency fluctuation (fALFF) as an imaging biomarker for predicting or diagnosing RE in patients with NPC. A total of 60 patients with NPC were examined, 21 in the pre-RT cohort and 39 in the post-RT cohort. Patients in the post-RT cohort were further divided into two subgroups according to the occurrence of RE in follow-up: post-RT non−RE (n = 21) and post-RT REproved infollow−up (n = 18). Surface-based and volume-based fALFF were used to detect radiation-induced functional alterations. Functional derived features were then adopted to construct a predictive model for the diagnosis of RE. We observed that surface-based fALFF could sensitively detect radiation-induced functional alterations in the intratemporal brain regions (such as the hippocampus and superior temporal gyrus), as well as the extratemporal regions (such as the insula and prefrontal lobe); however, no significant intergroup differences were observed using volume-based fALFF. No significant correlation between fALFF and radiation dose to the ipsilateral temporal lobe was observed. Support vector machine (SVM) analysis revealed that surface-based fALFF in the bilateral superior temporal gyri and left insula exhibited impressive performance (accuracy = 80.49%) in identifying patients likely to develop RE. We conclude that surface-based fALFF may serve as a sensitive imaging biomarker in the prediction of RE.

Novel biomarkers for prediction of outcome and therapeutic response in juvenile idiopathic arthritis

Introduction The search for biomarkers in juvenile idiopathic arthritis (JIA) is a promising and rapidly expanding field of investigation. The biomarkers identified so far may help to dissect the clinical heterogeneity of the illness, measure the level of disease activity, predict clinical remission, relapse, response to medications, course over time, complications, and forestall disease flares. Areas covered We provide a summary of the most recent advances in the development and application of biomarkers in JIA. We performed a PubMed search for significant articles combining predetermined keywords related to biomarkers in non-systemic and systemic JIA, chronic uveitis, and macrophage activation syndrome (MAS).The biomarkers available or under study are presented and discussed separately for non-systemic and systemic subtypes and for the two main disease complications, uveitis and MAS. Expert opinion The incorporation of valid and reliable biomarkers in standard clinical care may help to design better patient-tailored treatment regimens and to improve the therapeutic strategies based on the treat-to-target approach. The establishment of biomarkers that predict the risk of disease flare may lead to define the optimal modalities for treatment discontinuation after the achievement of clinical remission.

Placenta-Derived MicroRNAs in the Pathophysiology of Human Pregnancy.

In placental mammals, reproductive success, and maternal-fetal health substantially depend on a well-being placenta, the interface between the fetus and the mother. Disorders in placental cells are tightly associated with adverse pregnancy outcomes including preeclampsia (PE), fetal growth restriction, etc. MicroRNAs (miRNAs) represent small non-coding RNAs that regulate post-transcriptional gene expression and are integral to a wide range of healthy or diseased cellular proceedings. Numerous miRNAs have been detected in human placenta and increasing evidence is revealing their important roles in regulating placental cell behaviors. Recent studies indicate that placenta-derived miRNAs can be released to the maternal circulation via encapsulating into the exosomes, and they potentially target various maternal cells to provide a hormone-like means of intercellular communication between the mother and the fetus. These placental exosome miRNAs are attracting more and more attention due to their differential expression in pregnant complications, which may provide novel biomarkers for prediction of the diseases. In this review, we briefly summarize the current knowledge and the perspectives of the placenta-derived miRNAs, especially the exosomal transfer of placental miRNAs and their pathophysiological relevance to PE. The possible exosomal-miRNA-targeted strategies for diagnosis, prognosis or therapy of PE are highlighted.

Novel biomarkers for prediction of outcome in hip fracture patients-An exploratory study.

Little is known about the value of biomarkers for prognostication in hip fracture patients. The main objective of the present study was to assess if biomarkers add useful information to an existing risk score for prediction of 30-day mortality in patients suffering from out of hospital hip fractures. In a prospective observational single centre study, association between plasma concentration of ninety-two biomarkers at admission and 30-day mortality was analysed using logistic regression adjusted for risk factors included in Nottingham Hip Fracture Score (NHFS). Biomarkers associated with the outcome in the adjusted analysis were further evaluated by calculating the net reclassification improvement (NRI) and the change in area under the receiver operating characteristics curve (AUC) relative to the NHFS. 997 patients were included. Sixty-two patients died within 30days (6.2%). Eleven biomarkers were associated with 30-day mortality in adjusted analysis. Of these biomarkers Growth Differentiation Factor-15 (GDF-15) had NRI for the primary outcome (12.1%; 95% CI: 1.2-23.3) and Carbohydrate Antigen 125 (CA-125) improved the AUC relative to NHFS (improvement: 0.05; 95% CI: 0.01-0.10, P=.027). Both CA-125 and GDF-15 improved the AUC for a composite outcome of 30-day mortality and cardiovascular complications. Adding GDF-15 or CA-125 to the Nottingham Hip Fracture Score improves the discrimination with regard to predicting 30-day mortality and may help to identify a subgroup of hip fracture patients with a particularly poor prognosis. The value of these biomarkers should be explored in further studies to confirm clinical utility.

Prognostic significance of pre- and post-treatment PD-L1 expression in patients with primary high-grade non-muscle-invasive bladder cancer treated with BCG immunotherapy.

Programmed cell death-1 ligand-1 (PD-L1) expression has been associated with prognostic implications in urologic malignancies. We aimed to investigate prognostic significance of pre- and post-treatment PD-L1 expression in patients treated with BCG for high-grade non-muscle-invasive bladder cancer (NMIBC). We reviewed a total of 141 high-grade NMIBC cases treated with transurethral resection + ≥ 6 BCG instillations between 2004 and 2017. PD-L1 immunohistochemistry (IHC) scoring was done on 0-3 scale, and cut-off for positive and high-level PD-L1 expression was set to ≥ 1% and ≥ 5% staining of tumor-infiltrating immune cells (IC), respectively. Clinicopathologic characteristics and oncologic outcomes [recurrence-free (RFS) and progression-free survival (PFS)] were compared, stratified by PD-L1 positivity. The prognostic role of PD-L1 was assessed using Kaplan-Meier, and univariate and multivariate Cox regression analyses. Pre-treatment, 46.2% and 6.8% of high-grade NMIBC demonstrated positive and high-level PD-L1 expression, respectively. Positive PD-L1 expression was associated with submucosal invasion and refractory-tumor recurrence. PD-L1 expression was not associated with RFS or PFS in regression analysis. Post-treatment, 55.1% and 11.6% of recurrent tumors demonstrated positive and high-level PD-L1 expression, respectively. Down-regulation of PD-L1 expression was noted in patients with refractory recurrence (p = 0.012). Pre-treatment PD-L1 expression was associated with unfavorable pathological features in primary high-grade NMIBC and its expression level after BCG immunotherapy was significantly decreased in patients with refractory recurrence. PD-L1 expression did not have prognostic value for PFS or RFS; therefore, further research is necessary to identify novel biomarkers for prediction of disease outcomes in high-grade NMIBC.

Serum lncRNA TINCR Serve as a Novel Biomarker for Predicting the Prognosis in Triple-Negative Breast Cancer.

Background:Tissue differentiation-inducing non-protein coding RNA (TINCR) has been shown to play a crucial role in pathogenesis of various types of human cancer including breast cancer (BC). The purpose of this study was to determine the potential prognostic value of serum lncRNA TINCR in BC.Methods:Quantitative reverse transcription PCR (qRT-PCR) was performed to detect serum lncRNA TINCR levels in 72 triple-negative BC (TNBC) patients, 105 non-TNBC patients, 60 benign breast disease patients and 86 healthy subjects.Results:The results showed that serum lncRNA TINCR level was significantly increased in BC, especially in TNBC. High circulating lncRNA TINCR was significantly correlated with worse clinicopathological features and clinical outcome of TNBC. Multivariate analysis revealed that serum lncRNA TINCR was an independent prognostic factor for overall survival of TNBC. However, little association was found between serum lncRNA TINCR and the prognosis of non-TNBC.Conclusions:Taken together, our findings demonstrate that serum lncRNA TINCR might be a useful novel and non-invasive biomarker for the prognosis prediction of TNBC.

Novel biomarkers for prediction of acute kidney injury in acute heart failure.

Acute kidney injury (AKI) is a frequent event in patients with an acute heart failure (AHF) and is associated with a poor short and long-term outcome. The aim of this study was to describe diagnostic yield of selected novel biomarkers in prediction of AKI in patients admitted for AHF. We performed aprospective cohort study of 72 consecutive patients (46/26 M/F) aged 69±10,3 years admitted for AHF. Renal damage was defined according to KDIGO guidelines. Patients were divided into the two groups: AKI- (without renal injury, n=52) and AKI+ (with renal injury, n=20). Urine samples for AKI biomarkers measurements (NGAL, TIMP2, IGFBP7) were collected at the admission. The ROC and linear logistic regression of new biomarkers and selected clinical variables was performed for the evaluation of the AKI prediction. The patients with AKI+ were older (median age: 75 vs 64 years, p=0.01), had lower BMI (median: 28 vs 29.5 kg/m2, p=0.04), were with a higher proportion of patients with HF with a reduced ejection fraction (55 % vs 23.1 %, p=0.01) and a higher level of serum NTproBNP. Urinary NGAL at admission was significantly higher in the AKI+ compared to the AKI - group (152 vs 19.5 ng/mL, p<0.0001); also median of u-TIMP-2 and u-IGFBP-7 in the AKI+ patients was significantly higher: 194.1 versus 42.5 ng/mL (p<0.0001) and 379 versus 92.4 pg/mL (p<0.0001) resp. Age, u-NGAL, u-TIMP2, u-IGFBP7, s-haemoglobin, NTproBNP and LVEF were associated with the development of AKI. Urine concentration of IGFBP-7 was measured, which is the best marker for the prediction of AKI (AUC 0.94). Urine concentrations of NGAL, TIMP2, IGFBP7 at the time of admission for AHF predicted a development of AKI. Age, NTproBNP, LVEF and s-haemoglobin were also associated with AKI in AHF patients (Tab. 3, Fig. 3, Ref. 22). Text in PDF www.elis.sk Keywords: biomarkers, cardiorenal syndrome, acute heart failure.

P6358Novel biomarkers for prediction of acute cardiorenal syndrome

Abstract Objectives Acute kidney injury (AKI) is frequent event in patients with acute heart failure (AHF) and is associated with poor short and longterm outcome. Aim of the study was to decribe diagnostic yield of selected novel biomarkers in prediction of AKI in patients addmitted for AHF. Methods We performed a prospective cohort study of 72 consecutive patients (46/26 M/F) aged 69±10,3 years admitted for AHF. Renal damage was defined according to KDIGO guidelines. Patients were divided into two groups: AKI- (without renal injury, n=52) and AKI+ (with renal injury, n=20). Urine samples for AKI biomarkers measurements (NGAL, TIMP2, IGFBP7) were collected at admission. The ROC and linear logistic regression of new biomarkers and selected clinical variables was performed for evaluation of the AKI prediction. Results Patients with AKI + were older (median age: 75 vs. 64 years, p=0,01), had lower BMI (median: 28 vs. 29,5 kg/m2, p=0,04), were with higher proportion of patients with HF with reduced ejection fraction (55% vs 23,1%, p=0,01) and higher level of serum NTproBNP. Urinary NGAL at admission was significantly higher in the AKI+ compared to AKI – group (152 vs. 19,5 ng/ml, p &lt;.0001); also median of u-TIMP-2 and u-IGFBP-7 in the AKI+ patients were significantly higher: 194,1 versus 42,5 ng/ml (p&lt;0.0001) and 379 versus 92,4 pg/ml (p&lt;0.0001) resp. Age, u-NGAL, u-TIMP2, u-IGFBP7, s-hemoglobin, NTproBNP and LVEF were associated with the development of AKI. Urine concentration IGFBP-7 performs the best for the prediction AKI (AUC 0,94). Conclusion Urine concentrations of NGAL, TIMP2, IGFBP7 at the time of admission for AHF predict developement of AKI. Age, NTproBNP, LVEF and s-hemoglobin are also associated with AKI in AHF patients. Acknowledgement/Funding Project was supported by Slovak Society of Cardiology research grant 2015-2018.