The prognostic value of estrogen receptor beta and proline-, glutamic acid- and leucine-rich protein 1 (PELP1) expression in ovarian cancer

Background: Proline-, glutamic acid-, and leucine-rich protein 1 (PELP1), a coregulator of the estrogen receptors (ERs) alpha and beta, is a potential proto-oncogene in hormone dependent gynecological malignancies. To better understand the role of PELP1 in epithelial ovarian cancer (EOC), the protein expression and prognostic significance of PELP1 was evaluated together with ERalpha and ERbeta in EOC tissues. Methods: The expression of PELP1, ERalpha, and ERbeta was characterized in tumor tissues of 63 EOC patients. The prognostic value was calculated performing log-rank tests and multivariate Cox-Regression analysis. In a second step, validation analysis in an independent set of 86 serous EOC patients was performed. Results: Nuclear PELP1 expression was present in 76.2% of the samples. Prevalence of PELP1 expression in mucinous tumors was significantly lower (37.5%) compared to serous (85.7%) and endometrioid tumors (86.7%). A significant association between PELP1 expression and nuclear ERbeta staining was found (p=0.01). Positive PELP1 expression was associated with better disease-free survival (DFS) (p=0.004) and overall survival (OS) (p=0.04). The combined expression of ERbeta+/PELP1+ revealed an independent association with better DFS (HR 0.3 [0.1-0.7], p=0.004) and OS (HR 0.3 [0.1-0.7], p=0.005). In the validation set, the combined expression of ERbeta+/PELP1+ was not associated with DFS (HR 0.7 [0.4-1.3], p=0.3) and OS (HR 0.7 [0.3-1.4], p=0.3). Conclusion: Positive immunohistochemical staining for the ER coregulator PELP1, alone and in combination with ERbeta, might be of prognostic relevance in EOC.Stefanie Aust, Peter Horak, Dietmar Pils, Sophie Pils, Christoph Grimm, Reinhard Horvat, Dan Tong, Bernd Schmid, Paul Speiser, Alexander Reinthaller, and Stephan Polteraue

DNA damage predicts prognosis and treatment response in colorectal liver metastases superior to immunogenic cell death and T cells

Preclinical models indicate that DNA damage induces type I interferon (IFN), which is crucial for the induction of an anti-tumor immune response. In human cancers, however, the association between DNA damage and an immunogenic cell death (ICD), including the release and sensing of danger signals, the subsequent ER stress response and a functional IFN system, is less clear. Methods: Neoadjuvant-treated colorectal liver metastases (CLM) patients, undergoing liver resection in with a curative intent, were retrospectively enrolled in this study (n=33). DNA damage (gammaH2AX), RNA and DNA sensors (RIG-I, DDX41, cGAS, STING), ER stress response (p-PKR, p-eIF2alpha, CALR), type I and type II IFN- induced proteins (MxA, GBP1), mature dendritic cells (CD208), and cytotoxic and memory T cells (CD3, CD8, CD45RO) were investigated by an immunohistochemistry whole-slide tissue scanning approach and further correlated with recurrence-free survival (RFS), overall survival (OS), radiographic and pathologic therapy response. Results: gammaH2AX is a negative prognostic marker for RFS (HR 1.32, 95% CI 1.04-1.69, p=0.023) and OS (HR 1.61, 95% CI 1.23-2.11, p<0.001). A model comprising of DDX41, STING and p-PKR predicts radiographic therapy response (AUC=0.785, p=0.002). gammaH2AX predicts prognosis superior to the prognostic value of CD8. CALR positively correlates with GBP1, CD8 and cGAS. A model consisting of gammaH2AX, p-eIF2alpha, DDX41, cGAS, CD208 and CD45RO predicts pathological therapy response (AUC=0.944, p<0.001). Conclusion: In contrast to preclinical models, DNA damage inversely correlated with ICD and its associated T cell infiltrate and potentially serves as a therapeutic target in CLM

Analysis of congenital disorder of glycosylation-Id in a yeast model system shows diverse site-specific under-glycosylation of glycoproteins

Asparagine-linked glycosylation is a common post translational modification of proteins in eukaryotes. Mutations in the human ALG3 gene cause changed levels and altered glycan structures on mature glycoproteins and are the cause of a severe congenital disorder of glycosylation (CDG-Id). Diverse glycoproteins are also under-glycosylated in Saccharomyces cerevisae alg3 mutants. Here we analyzed site-specific glycosylation occupancy in this yeast model system using peptide-N-glycosidase F to label glycosylation sites with an asparagine-aspartate conversion that creates a new endoproteinase AspN cleavage site, followed by proteolytic digestion, and detection of peptides and glycopeptides by LC-ESI-MS/MS. We used this analytical method to identify and measure site specific glycosylation occupancy in alg3 mutant and wild type yeast strains. We found decreased site specific N-glycosylation occupancy in the alg3 knockout strain preferentially at Asn-Xaa-Ser sequences located in secondary structural elements, features previously associated with poor glycosylation efficiency. Furthermore, we identified 26 previously experimentally unverified glycosylation sites. Our results provide insights into the underlying mechanisms of disease in CDG-Id, and our methodology will be useful in site specific glycosylation analysis in many model systems and clinical applications

Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling

The accuracy of protein structures, particularly their binding sites, is essential for the success of modeling protein complexes. Computationally inexpensive methodology is required for genome-wide modeling of such structures. For systematic evaluation of potential accuracy in high-throughput modeling of binding sites, a statistical analysis of target-template sequence alignments was performed for a representative set of protein complexes. For most of the complexes, alignments containing all residues of the interface were found. The full interface alignments were obtained even in the case of poor alignments where a relatively small part of the target sequence (as low as 40%) aligned to the template sequence, with a low overall alignment identity (<30%). Although such poor overall alignments might be considered inadequate for modeling of whole proteins, the alignment of the interfaces was strong enough for docking. In the set of homology models built on these alignments, one third of those ranked 1 by a simple sequence identity criteria had RMSD<5 Å, the accuracy suitable for low-resolution template free docking. Such models corresponded to multi-domain target proteins, whereas for single-domain proteins the best models had 5 Å<RMSD<10 Å, the accuracy suitable for less sensitive structure-alignment methods. Overall, ∼50% of complexes with the interfaces modeled by high-throughput techniques had accuracy suitable for meaningful docking experiments. This percentage will grow with the increasing availability of co-crystallized protein-protein complexes

Genomic structural variations lead to dysregulation of important coding and non-coding RNA species in dilated cardiomyopathy

The transcriptome needs to be tightly regulated by mechanisms that include transcription factors, enhancers, and repressors as well as non-coding RNAs. Besides this dynamic regulation, a large part of phenotypic variability of eukaryotes is expressed through changes in gene transcription caused by genetic variation. In this study, we evaluate genome-wide structural genomic variants (SVs) and their association with gene expression in the human heart. We detected 3,898 individual SVs affecting all classes of gene transcripts (e.g., mRNA, miRNA, lncRNA) and regulatory genomic regions (e.g., enhancer or TFBS). In a cohort of patients (n = 50) with dilated cardiomyopathy (DCM), 80,635 non-protein-coding elements of the genome are deleted or duplicated by SVs, containing 3,758 long non-coding RNAs and 1,756 protein-coding transcripts. 65.3% of the SV-eQTLs do not harbor a significant SNV-eQTL, and for the regions with both classes of association, we find similar effect sizes. In case of deleted protein-coding exons, we find downregulation of the associated transcripts, duplication events, however, do not show significant changes over all events. In summary, we are first to describe the genomic variability associated with SVs in heart failure due to DCM and dissect their impact on the transcriptome. Overall, SVs explain up to 7.5% of the variation of cardiac gene expression, underlining the importance to study human myocardial gene expression in the context of the individual genome. This has immediate implications for studies on basic mechanisms of cardiac maladaptation, biomarkers, and (gene) therapeutic studies alike

A multidisciplinary, multifactorial intervention program reduces postoperative falls and injuries after femoral neck fracture

INTRODUCTION: This study evaluates whether a postoperative multidisciplinary, intervention program, including systematic assessment and treatment of fall risk factors, active prevention, detection, and treatment of postoperative complications, could reduce inpatient falls and fall-related injuries after a femoral neck fracture. METHODS: A randomized, controlled trial at the orthopedic and geriatric departments at Umeå University Hospital, Sweden, included 199 patients with femoral neck fracture, aged  ≥70 years. RESULTS: Twelve patients fell 18 times in the intervention group compared with 26 patients suffering 60 falls in the control group. Only one patient with dementia fell in the intervention group compared with 11 in the control group. The crude postoperative fall incidence rate was 6.29/1,000 days in the intervention group vs 16.28/1,000 days in the control group. The incidence rate ratio was 0.38 [95% confidence interval (CI): 0.20 – 0.76, p = 0.006] for the total sample and 0.07 (95% CI: 0.01–0.57, p=0.013) among patients with dementia. There were no new fractures in the intervention group but four in the control group. CONCLUSION: A team applying comprehensive geriatric assessment and rehabilitation, including prevention, detection, and treatment of fall risk factors, can successfully prevent inpatient falls and injuries, even in patients with dementia

Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins

<p>Abstract</p> <p>Background</p> <p>Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residue preferences have been widely used in many studies but the results are often not satisfactory. Although different amino acid compositions among the interaction sites of different complexes have been observed, such differences have not been integrated into the prediction process. Furthermore, the evolution information has not been exploited to achieve a more powerful propensity.</p> <p>Result</p> <p>In this study, the residue interface propensities of four kinds of complexes (homo-permanent complexes, homo-transient complexes, hetero-permanent complexes and hetero-transient complexes) are investigated. These propensities, combined with sequence profiles and accessible surface areas, are inputted to the support vector machine for the prediction of protein binding sites. Such propensities are further improved by taking evolutional information into consideration, which results in a class of novel propensities at the profile level, i.e. the binary profiles interface propensities. Experiment is performed on the 1139 non-redundant protein chains. Although different residue interface propensities among different complexes are observed, the improvement of the classifier with residue interface propensities can be negligible in comparison with that without propensities. The binary profile interface propensities can significantly improve the performance of binding sites prediction by about ten percent in term of both precision and recall.</p> <p>Conclusion</p> <p>Although there are minor differences among the four kinds of complexes, the residue interface propensities cannot provide efficient discrimination for the complicated interfaces of proteins. The binary profile interface propensities can significantly improve the performance of binding sites prediction of protein, which indicates that the propensities at the profile level are more accurate than those at the residue level.</p

In ovarian cancer the prognostic influence of HER2/neu is not dependent on the CXCR4/SDF-1 signalling pathway

HER2/neu overexpression is a driving force in the carcinogenesis of several human cancers. In breast cancer the prognostic influence of HER2/neu was shown to be at least partly based on increased metastatic potential mediated by the chemokine–chemokine receptor pair SDF-1(CXCL12)/CXCR4. We wanted to evaluate the influence of HER2/neu on ovarian cancer prognosis and to investigate whether compromised survival would correlate with CXCR4 expression and/or SDF-1 abundance. Therefore, we analysed HER2/neu, CXCR4, and SDF-1 in 148 ovarian tumour samples by means of immunohistochemistry on tissue microarrays. Overexpression of HER2/neu was found in 27.6% of ovarian cancer tissues and in 15% of ovarian borderline tumours. In ovarian cancer patients, overexpression of HER2/neu correlated closely with overall survival (univariate hazard ratio (HR) 2.59, P=0.005; multiple corrected HR 1.92, P=0.074). In contrast, CXCR4 expression and SDF-1 abundance had no impact on overall survival, and both parameters were not correlated with HER2/neu expression. As expected, cytoplasmic CXCR4 expression and SDF-1 abundance correlated closely (P<0.0001). Our results confirm a univariate influence of HER2/neu expression on overall survival, which was completely independent of the expression of CXCR4 and the abundance of SDF-1, implying significant differences between the HER2/neu downstream pathways in ovarian cancer compared with breast cancer