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BACKGROUND: There are few effective treatments specifically aimed at basal bladder cancer. OBJECTIVE: Female F344 rats administered N-butyl-N-(4-hydroxybutyl)-nitrosamine (OH-BBN) develop large invasive bladder cancers. We determined the efficacy of daily vs weekly dosing of EGFR inhibitors, determined the efficacy of naproxen combined with an EGFR inhibitor, and performed RNA analysis of bladder tumors treated for 5 days with EGFR inhibitors or NO-naproxen to identify pharmacodynamic biomarkers. METHODS: Erlotinib (6 mg/Kg BW daily or 21 or 42 mg/Kg BW weekly), lapatinib (25 or 75 mg/Kg BW daily or 263 or 525 mg/Kg BW weekly) and/or naproxen (30 mg/Kg BW daily) were administered to OH-BBN-treated rats beginning 2–12 weeks post OH-BBN. Rats were sacrificed 28 weeks after the final OH-BBN treatment to determine the effects of the EGFR inhibitors + naproxen on bladder weights and tumor development. In a separate study, rats were treated with OH-BBN. When palpable tumors developed, rats were treated with erlotinib, lapatinib, gefitinib, or the NSAID NO-naproxen for 5 days. RNA analysis was performed on the tumors. RESULTS: Daily or weekly dosing of erlotinib or lapatinib and daily dosing of naproxen reduced large tumor formation up to 70%, while combining daily lapatinib and naproxen reduced tumors 100%. RNA Analysis: All EGFR inhibitors strongly reduced cell proliferation and chromosome replication pathways, while NO-naproxen altered the G protein receptor, oxygen homeostasis and immune function pathways. CONCLUSIONS: While daily and weekly dosing with EGFR inhibitors and naproxen were effective, combining lapatinib and naproxen yielded no tumors. This might encourage its clinical use in an adjuvant setting with superficial basal tumors, and perhaps even in a more advanced setting. Furthermore, RNA analysis identified specific pathways that might be potential pharmacodynamic biomarkers in clinical trials.

Cervical cancer is second most frequent cancer of women in the world. HPV infection is now a well established cause of cervical cancer . Currently used screening programmes are detecting cases in which only 15-20 percent of women found to have an abnormality signicant enough to need treatment, other 80-85 percent were probably false alarms. The oncogenic process in cervical cancer is initiated and mediated by upregulation of E6/E7 mRNA proteins and their over expression. So HPV E6 mRNA detection as a triage test could actually detect a neoplastic transformation and may help to reduce the false alarms. To compare the expression of HPV E6 mRN AIMS AND OBJECTIVES : A verses the HPV DNA as a biomarker in the screening of cervical cancer .Biopsy is used as gold standard for screening. This a prospective MATERIALSAND METHODS: study conducted in Institute of Social Obstetrics and Govt. Kasturba Gandhi hospital, Madras medical college, 41 cases positive for VIA/VILI in colposcopy were selected and subjected to conventional cytology and cervical biopsy ,part of biopsy was collected in RNA later solution and were typed for HPV DNA 16& 18,HPV E6mRNA Expression.the results of above test are compared with histopathology as gold standard. RESULTS: The specicity of E6 mRNA was 100% for both high grade and low grade lesions.But the sensitivity was less than HPV DNA and cytology for both low and high grade lesions.With increasing severity of lesion expression of E6 mRNA was found to increase. Low positivity CONCLUSION: rate and the high specicity makes E6 mRNA better biomarker in a screening of cervical cancer.

Understanding the molecular composition of pathogenic tissues is a critical step in understanding the pathophysiology of disease and designing therapeutics. First described in 2009, single cell RNA sequencing (scRNAseq) is a methodology whereby thousands of cells are simultaneously isolated into individual micro-environments that can be altered experimentally and the genome-wide RNA expression of each cell is captured. It has undergone significant technological improvement over the last decade and gained tremendous popularity. scRNAseq is an improvement over prior pooled RNA analyses which cannot identify the cellular composition and heterogeneity of a tissue of interest. This new approach offers new opportunity for new discovery, as tissue samples can now be sub-categorized into groups of cell types based on genome-wide gene expression in an unbiased fashion. As ophthalmologists, we are uniquely positioned to obtain pathologic samples from the eye for further study. ScRNAseq has already been applied in ophthalmology to characterize retinal tissue, and it may offer the key to understanding various pathological processes in the future.

Renal oncocytoma (RO) accounts for 5% of renal cancers and generally behaves as a benign tumor with favorable long-term prognosis. It is difficult to confidently distinguish between benign RO and other renal malignancies, particularly chromophobe renal cell carcinoma (chRCC). Therefore, RO is often managed aggressively with surgery. We sought to identify molecular biomarkers to distinguish RO from chRCC and other malignant renal cancer mimics. In a 44-patient discovery cohort, we identified a significant differential abundance of nine genes in RO relative to chRCC. These genes were used to train a classifier to distinguish RO from chRCC in an independent 57-patient cohort. The trained classifier was then validated in five independent cohorts comprising 89 total patients. This nine-gene classifier trained on the basis of differential gene expression showed 93% sensitivity and 98% specificity for distinguishing RO from chRCC across the pooled validation cohorts, with a c-statistic of 0.978. This tool may be a useful adjunct to other diagnostic modalities to decrease the diagnostic and management uncertainty associated with small renal masses and to enable clinicians to recommend more confidently less aggressive management for some tumors. PATIENT SUMMARY: Renal oncocytoma is generally a benign form of kidney cancer that does not necessarily require surgical removal. However, it is difficult to distinguish renal oncocytoma from other more aggressive forms of kidney cancer, so it is treated most commonly with surgery. We built a classification tool based on the RNA levels of nine genes that may help avoid these surgeries by reliably distinguishing renal oncocytoma from other forms of kidney cancer.

Background RNA-Seq is an increasing used methodology to study either coding and non-coding RNA expression. There are many software tools available for each phase of the RNA-Seq analysis and each of them uses different algorithms. Furthermore, the analysis consists of several steps regarding alignment (primary-analysis), quantification, differential analysis (secondary-analysis) and any tertiary-analysis and can therefore be time-consuming to deal with each step separately, in addition to requiring a computer knowledge. For this reason, the development of an automated pipeline that allows the entire analysis to be managed through a single initial command and that is easy to use even for those without computer skills can be useful. Faced with the vast availability of RNA-Seq analysis tools, it is first of all necessary to select a limited number of pipelines to include. For this purpose, we compared eight pipelines obtained by combining the most used tools and for each one we evaluated peak of RAM, time, sensitivity and specificity. Results The pipeline with shorter times, lower consumption of RAM and higher sensitivity is the one consisting in HISAT2 for alignment, featureCounts for quantification and edgeR for differential analysis. Here, we developed ARPIR, an automated pipeline that recurs by default to the cited pipeline, but it also allows to choose, between different tools, those of the pipelines having the best performances. Conclusions ARPIR allows the analysis of RNA-Seq data from groups undergoing different treatment allowing multiple comparisons in a single launch and can be used either for paired-end or single-end analysis. All the required prerequisites can be installed via a configuration script and the analysis can be launched via a graphical interface or by a template script. In addition, ARPIR makes a final tertiary-analysis that includes a Gene Ontology and Pathway analysis. The results can be viewed in an interactive Shiny App and exported in a report (pdf, word or html formats). ARPIR is an efficient and easy-to-use tool for RNA-Seq analysis from quality control to Pathway analysis that allows you to choose between different pipelines.

Objective: This study aims to investigate the influence of Kuntai capsules on the expression level of leukemia inhibitory factor (LIF), insulin-like growth factor-I (IGF-1) and epidermal growth factor (EGF) during the mouse implantation window of superovulation period and controlled ovarian hyperstimulation period. Methods: A total of 90 female mice were randomly divided into six groups (n=15, each group). The RNA expression of EGF, LIF and IGF-1 in the endometrium on the 4th day of pregnancy was detected using the fluorescence quantitative PCR method, and the relative expression of these three factors in each group was compared. Results: The mRNA expression of these three factors in the endometrium during the mouse implantation window period was significantly lower in the superovulation group and COH group than in the control group (P

The purpose of this research was to investigate the diagnostic and prognostic value of circulating SFRP5 (cSFRP5) in colorectal cancer (CRC). We evaluated preoperative cSFRP5 levels in CRC patients and controls (n = 208). We found significantly higher cSFRP5 levels in CRC patients compared with non-CRC controls (p < 0.001). Levels of cSFRP5 were significantly lower in CRC patients with either vascular invasion (p = 0.001) or liver metastasis (p = 0.016). High cSFRP5 levels were associated with longer disease-free survival in both univariate (p = 0.024) and multivariate (p = 0.015) analyses. Analysis of an independent tissue cohort from The Cancer Genome Atlas database revealed significantly lower SFRP5 RNA expression in CRC tumor tissue compared with adjacent normal mucosa (n = 590 vs 47; p

In colorectal cancer (CRC), high expression of trefoil factor 3 (TFF3) is associated with tumor progression and reduced patient survival; however, bioinformatics analyses of public 'omics' databases show low TFF3 expression in CRCs as compared to normal tissues. Thus, we examined TFF3 expression in CRCs and matching normal tissues to evaluate its role in CRC progression. TFF3 gene expression was characterized using the bioinformatics portal UALCAN (http://ualcan.path.uab.edu). Tissue microarrays (TMAs) of archival CRC specimens (n=96) were immunostained with anti‑human TFF3 antibodies. Immunohistochemical (IHC) staining intensity was semi‑quantitatively scored. For this cohort, the median follow‑up was 5.4 years. Associations between clinical and pathological variables were determined using Chi‑square or Fisher's exact tests. Univariate disease‑free survival was estimated by the Kaplan‑Meier method. Omics data analyses by UALCAN showed downregulation of TFF3 expression in CRC relative to normal tissue at protein (χ2, P

Background/aim Bone morphogenetic protein-15 (BMP-15) is one of the maturation indicators of the ovarian follicular pool. The aim of this study was to investigate the possible difference of follicular fluid (FF) BMP-15 RNA expression among low, normal, and high responder women attending controlled ovarian hyperstimulation-intracytoplasmic sperm injection (COH-ICSI) cycles. Materials and methods This cross-sectional study was conducted with 75 FFs of COH-ICSI cycles performed at the IVF Unit of University Hospital. Twenty FF from low response (group 1), 27 FF from normal response (group 2), and 28 FF from high response (group 3) were recruited for the study between September 2014 and February 2015. Cycle parameters were collected from patient files. FF BMP-15 RNA expression was evaluated with real-time polymerase chain reaction analysis. Statistical analysis was done with SPSS 16.0 version (SPSS Chicago, IL, USA). Results The mean age, infertility duration, and body mass index (BMI) of patients were 31.1 ± 4.4 years, 7.4 ± 4.5 years, and 25.6 ± 4.1 kg/m2, respectively. There was no significant difference among groups for age, infertility duration, and BMI. There was no significant difference among groups for fertilization rate, implantation rate, pregnancy rate, and live birth rate. Among the 3 groups, FF BMP-15 RNA overexpression and lower expression rates were not significantly different. In all groups, overexpression showed dominance. The pregnancy rate was 45% among women with lower expression and the pregnancy rate among women with overexpression was 26% (P = 0.02). BMP-15 overexpression showed impact on becoming pregnant (OR = 3.7, 95% CI = 1.245–11.299, P = 0.019). Conclusion In this study, there was no significant difference in FF BMP-15 RNA expression levels among low, normal, and high responder women. However, overexpression of FF BMP-15 RNA showed a negative impact on pregnancy rates of women who attended COH-ICSI cycles.

Purpose of Investigation The purpose of this study was to study the expression of adenosine diphosphate ribosylation factor GTPase-activating protein 3 (ArfGAP3) in the anterior vaginal wall of patients with pelvic organ prolapse (POP). Materials and Methods From July 2016 to July 2018, the anterior vaginal wall of 31 POP patients (pelvic organ prolapse quantification [POP-Q] II-III [n = 10] and POP-Q IV [n = 21]) with pelvic floor dysfunction-related symptoms who underwent vaginal hysterectomy were enrolled in POP group in the Department of Gynecology of Wuhan University People’s Hospital. The anterior vaginal wall of 28 non-POP patients who underwent vaginal hysterectomy was selected as control group. The expression of 3 groups was determined by immunohistochemical staining, Western blotting, and quantitative real-time fluorescence polymerase chain reaction. Results The expression levels of ArfGAP3 of POP-Q II-III and POP-Q IV groups were lower than the control group (P < 0.05), and there were significant differences between POP-Q II-III and POP-Q IV groups (P < 0.05). Conclusions The expression of ArfGAP3 in the anterior vaginal wall of POP patients decreased, which was related to the pathogenesis and clinical grading of POP.

In the era of precision medicine, accurate and reproducible assignment of cell-of-origin (COO) in diffuse large B-cell lymphoma patients has become important. The Lymph2Cx assay is accurately determining COO by analyzing RNA expression of 20 selected genes while the Hans algorithm based on immunohistochemistry is the most popular method for routine daily diagnosis. However, there are discrepancies between the 2 methods, which need to be evaluated for better correlation. We prospectively analyzed 156 cases of diffuse large B-cell lymphoma, not otherwise specified to analyze the characteristics of discrepancy groups of COO determined by Lymph2Cx and Hans algorithm. We investigated the pattern and cause of discrepancy of COO assigned by the 2 methods. Hans algorithm classified 50 cases (32%) as germinal-center B-cell-like (GCB) type and 106 cases (68%) as non-GCB type. Lymph2Cx assay assigned 43 cases (28%) as GCB type, 94 cases (60%) as activated B-cell-like type, and 19 cases (12%) as intermediate/unclassified type. The agreement rate was 86% after exclusion of unclassified type. With regard to the clinicopathologic factors related with discrepancy between Hans algorithm and Lymph2Cx assay, endoscopic biopsy of the gastrointestinal tract (4/11, 36%) showed higher discrepancy rate (P=0.052). Immunophenotypically, CD10/BCL6/MUM1 GCB type and CD10/BCL6//MUM1 (=30%, low level expression) non-GCB type exhibited a significantly higher discrepancy rate (6/13, 46%; 4/13, 31%) (P=0.0001). Activated B-cell-like subgroup via Lymph2Cx assay predicted poor progression-free survival (mean survival duration 28.6 mo, P=0.049) compared with the GCB and unclassified type. Hans algorithm revealed no significant difference in progression-free survival and overall survival (P=0.122 and 0.121). These results suggest that when assigning COO via Hans algorithm, CD10/BCL6/MUM1 GCB type and CD10/BCL6/MUM1 (=30%, low level) non-GCB type require careful interpretation, especially if the MUM1 staining is weak and heterogeneous in the biopsied specimen.

The outcome in esophageal adenocarcinoma (EAC) is still poor with only 20% of patients in Western populations surviving for more than 5 years. Almost nothing is known about the precise composition of immune cells and their gene expression profiles in primary resected EACs and also nothing compared to neoadjuvant treated EACs. This study analyzes and compares immune profiles of primary resected and neoadjuvant treated esophageal adenocarcinoma and unravels possible targets for immunotherapy. We analyzed 47 EAC in total considering a set of 30 primary treatment-naive EACs and 17 neoadjuvant pretreated (12 × CROSS, 5 × FLOT) using the Nanostring's panel-based gene expression platform including 770 genes being important in malignant tumors and their immune micromileu. Most of the significantly altered genes are involved in the regulation of immune responses, T-and B cell functions as well as antigen processing. Chemokine-receptor axes like the CXCL9, -10,-11/CXCR3- are prominent in esophageal adenocarcinoma with a fold change of up to 9.5 promoting cancer cell proliferation and metastasis. ARG1, as a regulator of T-cell fate is sixfold down-regulated in untreated primary esophageal tumors. The influence of the currently used neoadjuvant treatment revealed a down-regulation of nearly all important checkpoint markers and inflammatory related genes in the local microenvironment. We found a higher expression of checkpoint markers like LAG3, TIM3, CTLA4 and CD276 in comparison to PD-L1/PD-1 supporting clinical trials analyzing the efficacy of a combination of different checkpoint inhibitors in EACs. We found an up-regulation of CD38 or LILRB1 as examples of additional immune escape mechanism. Electronic supplementary material The online version of this article (10.1007/s00262-019-02475-w) contains supplementary material, which is available to authorized users.

Background Transcriptome data generates massive amounts of information that can be used for characterization and prognosis of patient outcomes for many diseases. The goal of our research is to predict the survival time of lung adenocarcinoma patients and improve the accuracy of classifying the long-survival cohort and short-survival cohort. Methods We filtered prognostic features related with survival time of lung adenocarcinoma patients by the method of Relief and predicted whether survival time of the patient is >3 years or not—using eight machine learning algorithms (Support Vector Machines, Random Forests, Logistic Regression, Naïve Bayes, Linear Regression, Support Vector Regression (kernel Poly), Support Vector Regression (kernel Linear), and Ridge Regression). Then the best-performed algorithm was chosen to build a predictive model of survival time of lung adenocarcinoma patients. Further, another dataset was used to verify the stability and suitability of this model. We explored the underlying mechanisms of RNA expression changes with the corresponding DNA mutations and DNA methylation patterns in the 22 selected genetic features. Results The best machine learning algorithm was Naïve Bayes (accuracy=75%, AUC =0.81) using the top 22 genetic features, and this algorithm had the stable and great performance on another dataset as well. The coupled mutation number of the long-survival group (>6 years) was less than the short-survival group (

Background The interaction between the muscle methylome and transcriptome is understudied during ageing and periods of resistance training in young, but especially older adults. More information is needed on the role of retained methylome training adaptations in muscle memory to understand muscle phenotypical and molecular restoration after inactivity or disuse. Methods We measured CpG methylation (microarray) and RNA expression (RNA sequencing) in young (n = 5; age = 22 ± 2 years) and older (n = 6; age = 65 ± 5 years) vastus lateralis muscle samples, taken at baseline, after 12 weeks of resistance training, after training interruption (2 weeks of leg immobilization in young men, 12 weeks of detraining in older men) and after 12 weeks of retraining to identify muscle memory-related adaptations and rejuvenating effects of training. Results We report that of the 427 differentially expressed genes with advanced age (FDR < 0.1), 71% contained differentially methylated (dm)CpGs in older versus young muscle (FDR < 0.1, M-value difference >0.4). The more dmCpGs within a gene, the clearer the inverse methylation–expression relationship. Around 73% of the age-related dmCpGs approached younger methylation levels when older muscle was trained for 12 weeks. A second resistance training period after training cessation increased the number of hypomethylated CpGs and upregulated genes in both young and older muscle. We found indication for an epi-memory within pro-proliferating AMOTL1 in young muscle and mechanosensing-related VCL in older muscle. For the first time, we integrate muscle methylome and transcriptome data in relation to both ageing and training-induced/inactivity-induced responses and identify focal adhesion as an important pathway herein. Conclusions This preliminary evidence indicates that previously trained muscle is more responsive to training than untrained muscle at methylome and transcriptome level and recurrent resistance training can partially restore ageing-induced methylome alterations., JCSM Rapid Communications, 5 (1), ISSN:2617-1619

The GPS (Oncotype Dx® Genomic Prostate Score) test is a RNA expression assay which can be performed on prostate biopsies. We sought to determine whether the GPS was associated with an increased risk of adverse pathology findings in men enrolled on active surveillance who later underwent radical prostatectomy.We identified all patients on active surveillance at University of California-San Francisco who had Gleason score 3 + 3 or low volume (33% or fewer positive cores) Gleason score 3 + 4 prostate cancer, GPS testing at diagnostic or confirmatory biopsy, clinical stage T1/T2, prostate specific antigen less than 20 and a clinical CAPRA (Cancer of the Prostate Risk Assessment) score less than 6. The primary outcome was adverse pathology, defined as Gleason score 4 + 3 or greater, stage pT3a or greater, or pN1. The secondary outcome was biochemical recurrence, defined as 2 consecutive prostate specific antigen measurements greater than 0.05 ng/ml following radical prostatectomy.Of the 215 men 179 (83%) were at low risk and 36 (17%) were at intermediate risk by CAPRA scoring. The median GPS was 26.4 (IQR 18.8-34.6). On multivariate analysis a higher GPS was associated with an increased risk of adverse pathology at delayed radical prostatectomy (HR/5 units 1.16, 95% CI 1.06-1.26, p0.01). A higher GPS was also associated with an increased risk of biochemical recurrence (HR/5 units 1.10, 95% CI 1.00-1.21, p=0.04).In patients who undergo radical prostatectomy after a period on active surveillance, as in those who undergo immediate prostatectomy, a higher GPS is associated with an increased risk of adverse pathology. The GPS is also associated with biochemical recurrence following radical prostatectomy in such patients.

RNA expression based molecular testing has the potential to improve clinical decision making as an adjunct to histopathological interpretation of prostate cancer biopsies. The GPS (Oncotype Dx Genomic Prostate Score®) assay has been proposed as a predictor of more severe pathology at prostatectomy but its true clinical value is uncertain. We hypothesized that some of the predictive usefulness of this assay relates to its correlation with histopathological features which are apparent but not typically reported on prostate biopsies.In this retrospective, single center cohort we determined an RNA based GPS of prostate biopsies. We retrospectively reviewed the histopathological features of biopsy cores with the score and assessed tumor length, Gleason pattern 4 amount and type, and stromal reaction type. Associations between the GPS and histopathological features were assessed by linear mixed models.From May 2013 to August 2015 a GPS was determined in 319 biopsies in a total of 296 patients. Of the types of Gleason pattern 4 the expansile cribriform, simple cribriform, poorly formed and fused patterns were associated with a higher GPS. The expansile cribriform pattern had the strongest association. The glomerulation pattern was associated with a lower GPS and an increasing stromal reaction also positively correlated with the GPS. A model incorporating these pathological features accounted for 36.9% of the variation in the score.The stromal reaction and the type of Gleason pattern 4 are histopathological features which are not typically reported for prostate biopsies but they correlate with the GPS. These data suggest that more detailed analysis of prostate histopathology might substitute for some of the information gained from this molecular diagnostic assay.

We determined whether prostate multiparametric magnetic resonance imaging and genomic biomarkers might help further define patients with favorable intermediate risk prostate cancer which could safely be considered suitable for active surveillance.From our institutional database we identified 509 patients who underwent radical prostatectomy with preoperative magnetic resonance imaging and a postoperative Decipher® prostate cancer test. According to the NCCN® (National Comprehensive Cancer Network®) risk stratification 125 men had favorable intermediate and 171 had unfavorable intermediate risk disease. Univariable and multivariable binary logistic regression analyses were done to test the utility of different variables in predicting adverse pathology, defined as Gleason Grade Group greater than 2, pT3b or pN1.On univariable analysis favorable intermediate risk, multiparametric magnetic resonance imaging and the prostate cancer test significantly predicted adverse pathology. On multivariable analysis favorable intermediate risk and the prostate cancer test maintained independent predictive value while multiparametric magnetic resonance imaging did not meet statistical significance (p = 0.059). The 19 patients at favorable intermediate risk with high genomic risk had an adverse pathology rate slightly higher than patients at unfavorable intermediate risk (42.1% vs 39.8%, p = 0.56). Those at low genomic risk had an adverse pathology rate slightly lower than patients at very low or low risk (7.5% vs 10.2%, p = 0.84). The 31 patients at favorable intermediate risk but at high multiparametric magnetic resonance imaging and genomic risk had an adverse pathology rate slightly lower than patients at unfavorable intermediate risk (25.8% vs 39.8%, p = 0.14). Those at low multiparametric magnetic resonance imaging and genomic risk had an adverse pathology rate slightly lower than patients at very low or low risk (8.5% vs 10.2%, p = 0.89).Multiparametric magnetic resonance imaging and the Decipher test allowed us to better define the risk of adverse pathology in patients at favorable intermediate risk who were diagnosed with prostate cancer.

Accurate prediction of the human pharmacokinetics (PK) of a candidate monoclonal antibody from nonclinical data is critical to maximize the success of clinical trials. However, for monoclonal antibodies exhibiting nonlinear clearance due to target-mediated drug disposition, PK predictions are particularly challenging. That challenge is further compounded for molecules lacking cross-reactivity in a nonhuman primate, in which case a surrogate antibody selective for the target in rodent may be required. For these cases, prediction of human PK must account for any interspecies differences in binding kinetics, target expression, target turnover, and potentially epitope. We present here a model-based method for predicting the human PK of MAB92 (also known as BI 655130), a humanized IgG1κ monoclonal antibody directed against human IL-36R. Preclinical PK was generated in the mouse with a chimeric rat anti-mouse IgG2a surrogate antibody cross-reactive against mouse IL-36R. Target-specific parameters such as antibody binding affinity (KD), internalization rate of the drug target complex (kint), target degradation rate (kdeg), and target abundance (R0) were integrated into the model. Two different methods of assigning human R0 were evaluated: the first assumed comparable expression between human and mouse and the second used high-resolution mRNA transcriptome data (FANTOM5) as a surrogate for expression. Utilizing the mouse R0 to predict human PK, AUC0-∞ was substantially underpredicted for nonsaturating doses; however, after correcting for differences in RNA transcriptome between species, AUC0-∞ was predicted largely within 1.5-fold of observations in first-in-human studies, demonstrating the validity of the modeling approach. Our results suggest that semi-mechanistic models incorporating RNA transcriptome data and target-specific parameters may improve the predictivity of first-in-human PK.

Background: Chromosome 1p/19q codeletion is increasingly being recognized as the crucial genetic marker for glioma patients and have been included in WHO classification of glioma in 2016. Fluorescent in situ hybridization, a widely used method in detecting 1p/19q status, has some methodological limitations which might influence the clinical management for doctors. Here, we attempted to explore an RNA sequencing computational method to detect 1p/19q status. Methods: We included 692 samples with 1p/19q status information from TCGA cohort as training set and 222 samples with 1p/19q status information from REMBRANDT cohort as validation set. We reviewed and compared five tools: TSPairs, GSVA, PAM, Caret, smoother, with respect to their accuracy, sensitivity and specificity. Results: In TCGA cohort, the GSVA method showed the highest accuracy (98.4%) in predicting 1p/19q status (sensitivity=95.5%, specificity=99.6%) and smoother method showed the second-highest accuracy (accuracy=97.8%, sensitivity=96.4%, specificity=98.3%). While in REMBRANDT cohort, smoother method exhibited the highest accuracy (98.6%) (sensitivity= 96.7%, specificity=98.9%) in 1p/19q status prediction. Conclusions: Our independent assessment of five tools revealed that smoother method was selected as the most stable and accurate method in predicting 1p/19q status. This method could be regarded as a potential alternative method for clinical practice in future.

Programs to prevent mother-to-child HIV transmission do not reduce the number of infants exposed during pregnancy and breastfeeding. HIV-exposed but uninfected children (HEU) present higher risk of morbidity and mortality than HIV-unexposed and uninfected children (UU). In this line, the study of immune biomarkers in HIV could improve prediction of disease progression, allowing to diminish comorbidity risk. Dried blood specimens (DBS) are an alternative to serum for collecting and transporting samples in countries with limited infrastructure and especially interesting for groups such as pediatrics, where obtaining a high sample volume is challenging. This study explores the usefulness of DBS for immune profile monitoring in samples from 30 children under clinical follow-up in Kinshasa: 10 HIV-infected (HIV+), 10 HEU, and 10 UU. We have measured the gene expression levels of 12 immune and inflammatory markers (CD14, IL-6, TNFα, HVEM, B7.1, HIF-1α, Siglec-10, IRAK-M, CD163, B7H5, PD-L1, and Galectin-9) in DBS samples by reverse transcription of total RNA and RT-qPCR. Principal component analysis, Kruskal–Wallis test, and Mann–Whitney test were performed in order to study group differences. HIV+ children presented significantly higher levels of seven biomarkers (CD14, IL-6 HVEM, B7.1, Siglec-10, HIF-1α, and CD163) than the UU group. In HEU, we found seven biomarkers significantly elevated (CD14, IL-6, HVEM, B7.1, Siglec-10, HIF-1α, and IRAK-M) vs. UU. Six biomarkers (CD14, IL-6, HVEM, B7.1, Siglec-10, and HIF-1α) showed a significantly higher expression in both HIV+ and HEU vs. UU, with HVEM and CD14 being significantly overexpressed among HIV+ vs. HEU. Our data reveal the utility of DBS for immune response monitoring. Moreover, significant differences in specific biomarker expression across groups strongly suggest the effect of HIV infection and/or HIV exposure on these immune biomarkers' expressions.

Human adenoviruses (HAdVs) causes infections predominantly in infants and young children, and severe HAdVs pneumonia results in high lethality rate in children. CircRNAs are novel identified long non-coding RNAs and play important roles in gene regulation and pathogenesis of disease. To elucidate the roles of circRNAs in HAdVs pneumonia, we analyzed the circRNAs profiles of healthy children and children with HAdVs pneumonia including mild and severe cases, and identified 139 significant upregulated circRNAs in children with HAdVs pneumonia vs healthy controls, and 18 significant upregulated circRNAs in children with severe HAdVs pneumonia vs mild HAdVs pneumonia. In particular, hsa_circ_0002171 was found differently expressed in both groups, which may be taken as diagnostic biomarkers for HAdVs pneumonia and severe HAdVs pneumonia. To identify the underlying mechanisms of circRNAs in HAdVs pneumonia, we analyzed the transcriptome of children with HAdVs pneumonia and established circRNA-mRNA regulatory network. Enrichment of the differentially expressed (DE) target mRNAs demonstrated that DE genes between healthy controls vs HAdVs pneumonia were mainly involved in RNA splicing, while DE genes between children with mild and severe HAdVs pneumonia were mainly from the regulation of lymphocyte activation. Receiver operating characteristic (ROC) curve analysis suggested that hsa_circ_0002171 had significant value in HAdVs pneumonia and severe cases diagnosis. Taken together, profile of circRNA expression was altered in children with HAdVs pneumonia and severe cases. These results demonstrate that hsa_circ_0002171 as a potential diagnostic biomarker of HAdVs pneumonia and severe cases and may be a novel therapeutic target.

Acute myocardial infarction (AMI) is myocardial necrosis caused by the persistent interruption of myocardial blood supply, which has high incidence rate and high mortality in middle-aged and elderly people in the worldwide. Biomarkers play an important role in the early diagnosis and treatment of AMI. Recently, more and more researches confirmed that circRNA may be a potential diagnostic biomarker and therapeutic target for cardiovascular diseases. In this paper, a series of biological analyses were performed to find new effective circRNA biomarkers for AMI. Firstly, the expression levels of circRNAs in blood samples of patients with AMI and those with mild coronary stenosis were compared to reveal circRNAs which were involved in AMI. Then, circRNAs which were significant expressed abnormally in the blood samples of patients with AMI were selected from those circRNAs. Next, a ceRNA network was constructed based on interactions of circRNA, miRNA and mRNA through biological analyses to detect crucial circRNA associated with AMI. Finally, one circRNA was selected as candidate biomarker for AMI. To validate effectivity and efficiency of the candidate biomarker, fluorescence in situ hybridization, hypoxia model of human cardiomyocytes, and knockdown and overexpression analyses were performed on candidate circRNA biomarker. In conclusion, experimental results demonstrated that the candidate circRNA was an effective biomarker for diagnosis and therapy of AMI.

We implemented an automated system for single-cell classification using artificial neural networks (ANN). Our system takes single-cell gene expression sparse matrices and trains ANN to classify cell types and subtypes. The assemblies of ANNs predict cell classes by voting. We tested the system in a case study where we trained ANNs with a dataset containing approximately 120,000 single cells and tested the resulting model using an independent data set of 13,000 single cells. The overall accuracy of the 5-class classification was 95%. We trained and tested a total of 100 ANNs in 10 cycles. The prediction system demonstrated excellent reproducibility. The analysis of misclassifications indicated that 2% were likely classification errors, while the remaining 3% were likely due to mislabeled types and subtypes in the test set.

Background Vertebral fractures (VFs) are the most common clinical manifestation of osteoporosis associated with high morbimortality. A personal/familiar history of fractures increases the risk of fractures. The purpose of this study is to identify possible molecular markers associated with osteoporotic VFs in elderly women from community. Methods Transcriptomic analysis using Affymetrix HTA2 microarray was performed using whole blood samples of 240 subjects from a population‐based survey (Sao Paulo Ageing & Health [SPAH] study). Only elderly women with osteoporosis diagnosis by densitometry were analyzed, and divided in two groups: VF: women with osteoporosis and VFs versus no vertebral fracture (NVF): women with osteoporosis and NVFs. They were matched for age, chronic disease, medication use, and bone mineral density (BMD). The logistic regression model adjusted for age was applied for transcriptome data analysis. SYBR green‐based quantitative polymerase chain reaction (qPCR) was used to validate the most significant expression changes obtained in the microarray experiment. Results Microarray analysis identified 142 differentially expressed genes (DEGs, p, Our data identified and validated the association of SNTG2, TRAF3IP2, and ITGA6 with osteoporotic vertebral fracture (VF) in elderly women, independently of bone mineral density. These results suggest that these transcripts have potential clinical significance and may help to explain the molecular mechanisms and biological functions of VF.

Long non-coding RNA (lncRNA)-mediated competitive endogenous RNA (ceRNA) networks act as essential mechanisms in tumor initiation and progression, but their diagnostic and prognostic significance in prostate cancer (PCa) remains poorly understood. Presently, using the RNA expression data derived from multiple independent PCa-related studies, we constructed a high confidence and PCa-specific core ceRNA network by employing three lncRNA-gene inference approaches and key node filter strategies and then established a logistic model and risk score formula to evaluate its diagnostic and prognostic values, respectively. The core ceRNA network consists of 10 nodes, all of which are significantly associated with clinical outcomes. Combination of expression of the 10 ceRNAs with a logistic model achieved AUC of ROC and PR curve up to ∼96 and 99% in excluding normal prostate samples, respectively. Additionally, a risk score formula constructed with the ceRNAs exhibited significant association with disease-free survival. More importantly, utilizing the expression of RNAs in the core ceRNA network as a molecular signature, the TCGA-PRAD cohort was divided into four novel clinically relevant subgroups with distinct expression patterns, highlighting a feasible way for improving patient stratification in the future. Overall, we constructed a PCa-specific core ceRNA network, which provides diagnostic and prognostic value.

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization and iterative data visualization and biological validation. The approach was evaluated using a large cohort ($N=\kern0.5em 1649$) from the Carolina Breast Cancer Study, two cohorts of moderate sample size ($N=359$ and$130$) and a small published dataset ($N=12$). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoString’s commercial package, without diminishing biological variation, especially in long-term longitudinal multiphase or multisite cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization and visualization of NanoString nCounter data are an imperative component of study design that influences results in downstream analyses.

Lay Summary Researchers from the Scripps Clinic in La Jolla, CA recently looked at gene expression to better understand the role that diet plays in inflammatory bowel disease. Their findings suggest that diet may help modify inflammatory pathways in people with ulcerative colitis.

INTRODUCTION AND OBJECTIVE:Peripheral blood CD14/CD2 RNA expression ratios have shown associations with prostate biopsy features. The objectives of this study are: 1) To develop a computational imm...

PurposeThe aim of the present study was to assess whether SARS-CoV-2 can be detected in the expressed prostatic secretion (EPS) of patients with corona virus disease 2019 (COVID-19).Methods18 cases of COVID-19, and 5 suspected cases, were selected from three medical centers to detect the RNA expression of SARS-CoV-2 in their EPS with RT-PCR.ResultsResults were negative in all EPS samples for SARS-CoV-2 of suspected and confirmed patients.ConclusionsNo SARS-CoV-2 was expressed in EPS of patients with COVID-19.

A novel coronavirus (COVID-2019) was first identified in Wuhan, Hubei Province, and then spreads to the other Provinces of China. COVID-2019 was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-CoV. But the infection rate of COVID-2019 is much higher than SARS-CoV. The biophysical and structural evidence showed that the COVID-2019 binds ACE2 with 10~20 times affinity than SARS-CoV. TMPRSS2 cleaves ACE2 and facilitates the entry of the virus into host cells. The presence of SLC6A19 may block the access of TMPRSS2 to the cutting site on ACE2 and weaken the entry of COVID-2019 into host cells. Here based on the public single-cell RNA-Seq datasets, we analyzed the ACE2 expression in the nasal, mouth, lung, and colon tissues. We find that the number of ACE2-expressing cells in the nasal and mouth tissues is comparable to the number of ACE2-expressing cells in the lung and colon tissues. We also find that ACE2 tends to be co-expressed with TMPRSS2 and not co-expressed with SLC6A19 in the nasal and mouth tissues. With the results, we infer that nasal and mouth tissues may be the first host cells of COVID-2019 infection. In our previous report in medRxiv and a recurrent report in New England Journal of Medicine, the COVID-2019 load tends to be higher in the nasal-swabs than in throat-swabs. We believe the roles of nasal and mouth tissues in COVID-2019 infection should be investigated, and we need to pay more attention to protect nose and mouth from COVID-2019 infection.

Background: An accurate test to differentiate large artery stroke (LAS) patients from those with cardioembolic stroke (CES) would be of significant clinical utility. Using the Biomarkers of Acute Stroke Etiology (BASE) trial (NCT02014896) dataset, our purpose was to utilize blood gene expression signatures for accurately differentiating LAS from CES acute stroke etiologies. Methods: The BASE trial enrolled suspected stroke patients presenting to 20 hospitals within 24 hrs of symptom onset. Final gold standard diagnosis and stroke etiology were determined by an adjudication committee using all hospital data but blinded to RNA test results. Whole blood, obtained in PAX tubes, was frozen at -20C within 72 hrs and analyzed at a core lab (Ischemia Care, Dayton, OH) using Affymetrix HTA microarrays. Genes on the HTA microarray were filtered to eliminate genes with low expression or high CV (> 10%) when run on replicate samples leaving 9,513 potential signature genes. A two-way random forest classifier was built through cross validation of the training data resulting in a 45 gene diagnostic signature. Results: This is a planned interim cohort study of the 1700 patients enrolled in the BASE trial that does not include lacunar strokes, TIA, or stroke mimics. Overall, 222 patients were enrolled with NIHSS>5, 70 (32%) with LAS and 152 (68%) with CES; 59% were male, and median (IQR) age was 70.7 yrs (62.0, 80.2). Median (IQR) time from symptom onset to blood collection was 1200 (448, 1568) minutes. Coexistent pathology at presentation included atrial fibrillation 90 (48%), hypertension 153 (82%), hyperlipidemia 87 (47%), diabetes 60 (32%), and coronary artery disease 70 (37%). Patients were randomly divided into training (148), early symptom onset (18 hrs) validation (35). The diagnostic gene signature results in the early validation cohort distinguished LAS from CES; C-statistic 0.78 (0.50-1.0, 95% CI), sensitivity 0.90 (0.55-1.0, 95% CI) and specificity of 0.70 (0.43-1.0, 95% CI). Conclusion: Early RNA expression differentiates large artery stroke patients from those with cardioembolic stroke, and may have therapeutic and secondary prevention implications.

Background: Identifying atrial fibrillation in embolic stroke of ischemic stroke populations would be of significant clinical utility. Using the Biomarkers of Acute Stroke Etiology (BASE) trial (NCT02014896) dataset, our goal was to determine if blood gene expression signatures accurately differentiated patients with atrial fibrillation from large artery stroke patients. Methods: The BASE trial enrolled suspected stroke patients presenting to 20 hospitals within 24 hrs of symptom onset. Final gold standard diagnosis and stroke etiology were determined by an adjudication committee using all hospital data but blinded to RNA test results. Whole blood, obtained in PAXgene tubes, was frozen at -20C within 72 hrs and analyzed at a core lab (Ischemia Care, LLC, Dayton, OH) using Affymetrix HTA micro arrays. Approximately 38,000 genes on the HTA microarray were filtered to eliminate genes with low expression or high CV (> 10%) when run on replicate samples leaving 9,513 potential signature genes. A two-way random forest classifier was built through cross validation of the training data resulting in a 23 gene diagnostic signature. Results: There were 58 patients enrolled between 18 and 24 hours of symptom onset, with NIHSS>5, 27 (47%) with atrial fibrillation cause of stroke and 31 (53%) with large artery stroke; 64% were male, and median (IQR) age was 69.7 (62.8, 81.0). Median (IQR) time from symptoms to sample collection was 1323.5 (1208.8, 1381.3) minutes. Coexistent pathology at presentation was high blood pressure 49 (84%), hyperlipidemia 28 (48%), diabetes 9 (16%), and coronary artery disease 15 (26%). The panel was able to distinguish atrial fibrillation from large vessel stroke with a C-statistic 0.92 (0.55-1.0, 95% CI), sensitivity 0.90 (0.51-1.0, 95% CI) and specificity of 0.85. Conclusion: RNA expression differentiates strokes due to atrial fibrillation from large artery stroke and may have therapeutic and outcome implications in ischemic stroke populations.

Aim: We aimed to investigate the expression of voltage-gated potassium channels KCND1/KCND2/KCND3 in gastric cancer (GC) and normal stomach tissues and to investigate the prognostic value of the upregulated gene KCND2. Patients & methods: A retrospective analysis was performed using data from large available databases. Results: KCND2 was significantly upregulated at the mRNA and protein levels in GC compared with that in normal stomach tissues. High KCND2 RNA expression was independently associated with shorter overall survival (HR: 1.634, 95% CI: 1.135–2.352; p = 0.008) and recurrence-free survival (HR: 2.644, 95% CI: 1.438–4.863; p = 0.002). Data mining in the Kaplan–Meier plotter confirmed the prognostic value of KCND2. Conclusion: KCND2 upregulation is a valuable prognostic biomarker in GC patients, in terms of overall survival and recurrence-free survival

ObjectiveGastroenteropancreatic neuroendocrine tumours (GEP-NETs) encompass a diverse group of neoplasms that vary in their secretory products and in their location within the gastrointestinal tract. Their prevalence in the USA is increasing among all adult age groups.AimTo identify the possible derivation of GEP-NETs using genome-wide analyses to distinguish small intestinal neuroendocrine tumours, specifically duodenal gastrinomas (DGASTs), from pancreatic neuroendocrine tumours.DesignWhole exome sequencing and RNA-sequencing were performed on surgically resected GEP-NETs (discovery cohort). RNA transcript profiles available in the Gene Expression Omnibus were analysed using R integrated software (validation cohort). Digital spatial profiling (DSP) was used to analyse paraffin-embedded GEP-NETs. Human duodenal organoids were treated with 5 or 10 ng/mL of tumor necrosis factor alpha (TNFα) prior to qPCR and western blot analysis of neuroendocrine cell specification genes.ResultsBoth the discovery and validation cohorts of small intestinal neuroendocrine tumours induced expression of mesenchymal and calcium signalling pathways coincident with a decrease in intestine-specific genes. In particular, calcium-related, smooth muscle and cytoskeletal genes increased in DGASTs, but did not correlate with MEN1 mutation status. Interleukin 17 (IL-17) and tumor necrosis factor alpha (TNFα) signalling pathways were elevated in the DGAST RNA-sequencing. However, DSP analysis confirmed a paucity of immune cells in DGASTs compared with the adjacent tumour-associated Brunner’s glands. Immunofluorescent analysis showed production of these proinflammatory cytokines and phosphorylated signal transducer and activator of transcription 3 (pSTAT3) by the tumours and stroma. Human duodenal organoids treated with TNFα induced neuroendocrine tumour genes, SYP, CHGA and NKX6.3.ConclusionsStromal–epithelial interactions induce proinflammatory cytokines that promote Brunner’s gland reprogramming.

Purpose: There is poor functional recovery following delayed peripheral nerve repair since both muscle and Schwann cells (SC) undergo denervation atrophy. We investigated the specific temporal effect of nerve/SC denervation on recovery as well as changes in RNA expression in the nerves that may elucidate changes in recovery potential. We hypothesized that functional recovery would be worse after prolonged nerve/SC denervation and that the expression profiles would differ. Methods: Our study was conducted using a forelimb model in adult Lewis rats. Each animal underwent unilateral forelimb denervation of 8, 12, 16, or 24 weeks duration. In the functional recovery arm of the study, the ulnar nerve was denervated proximally or a sham surgery was performed. After the denervation period had elapsed, an in situ nerve transfer of median to ulnar to median nerve was performed. Functional recovery was then measured by stimulated grip strength weekly for 12 weeks. In the RNA expression arm, median and ulnar nerves were denervated. The same time points were used with the addition of a 1-week denervation group. After the denervation period, the median and ulnar nerves were harvested bilaterally. To create a comprehensive RNA-Seq dataset, the median nerve, with an average length of 3 cm, was homogenized and RNA was purified. RNA-sequencing was carried out using TrueSeq RiboZero gold kit. Samples were analyzed through FastQC, aligned to reference genome using STAR and quantified as transcripts per million (TPM) using Salmon. Principle component analysis was performed, followed by differential gene analysis using a linear mixed effects model to control for the control nerves being from the same animals. Results: Functional recovery was statistically significantly different depending on the duration of nerve/SC denervation (P0.05, we identified 1624 genes differentially expressed, of which 327 genes were upregulated and rest (1297 genes) downregulated with denervation. Conclusions: Prolonged nerve/SC denervation of more than 12 weeks resulted in significantly worse functional recovery. RNA sequencing demonstrated that not only were there many genes differentially expressed, but these appear to vary with duration of denervation as well. Further investigation into the specific genes and their changes over time will allow us to know why recovery potential is decreased and targets for interventions to improve recovery.

The epic arms race between microbes and their predators was the driving force behind the evolution and diversification of the truly remarkable microbial adaptive immune system CRISPR-Cas. CRISPR-Cas systems mediate defense through three stages: recording of nucleic acid species, multiplexed RNA expression and processing, and eventually RNA-guided cleavage of hostile genetic elements. The entire process is orchestrated by a plethora of effector proteins endowed with specialized functions for manipulating genetic material. Investigating this treasure trove substantially fostered the development of the RNA-guided DNA endonuclease Cas9 into a versatile molecular tool for synthetic biology and biomedicine. Here, we review the developments of Cas9 and other CRISPR-Cas components for applications in synthetic biology as well as highlight emerging CRISPR-Cas-based genetic recorders and memory devices.

Background: Despite increased understanding of the pathophysiology of rotator cuff tears and the evolution of rotator cuff repair, healing failure remains a substantial problem. The critical roles played by biological factors have been emphasized, but little is known of the implications of gene expression profile differences at the time of repair. Purpose: To document the relationship between the perioperative gene expression of healed and unhealed rotator cuffs by RNA microarray analysis. Study Design: Case-control study; Level of evidence, 3. Methods: Superior (supraspinatus involvement) and posterosuperior (supraspinatus and infraspinatus involvement) tears were included in the study. Samples of rotator cuff tendons were prospectively collected during rotator cuff surgery. Three samples were harvested at the tendon ends of tears from the anterior, middle (apex), and posterior parts using an arthroscopic punch. Seven patients with an unhealed rotator cuff were matched one-to-one with patients with a healed rotator cuff by sex, age, tear size, and fatty degeneration of rotator cuff muscles. mRNA microarray analysis was used to identify genetic differences between healed and unhealed rotator cuff tendons. Gene ontology and gene association files were obtained from the Gene Ontology Consortium, and the Gene Ontology system in DAVID was used to identify enhanced biological processes. Results: Microarray analyses identified 262 genes that were differentially expressed by at least 1.5-fold between the healed and unhealed groups. Overall, in the healed group, 103 genes were significantly downregulated, and 159 were significantly upregulated. DAVID Functional Annotation Cluster analysis showed that in the healed group, the genes most upregulated were related to the G protein–coupled receptor protein signaling pathway and to the neurological system. On the other hand, the genes most downregulated were related to immune and inflammatory responses. BMP5 was the gene most upregulated in the healed group, and the majority of downregulated genes were involved in the immune/inflammatory response. Conclusion: The downregulation of inflammatory response genes and the upregulation of cell differentiation genes in torn rotator cuffs at the time of surgery are related to rotator cuff healing. These results provide useful baseline information for future biological studies on rotator cuff healing.

// Jing Wang 1, * , Xue Yang 1, * , Haofeng Chen 2 , Xuewei Wang 1 , Xiangyu Wang 1 , Yi Fang 1 , Zhenyu Jia 3 and Jidong Gao 1 1 Department of Breast Surgical Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China 2 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China 3 Department of Botany and Plant Sciences, University of California, Riverside, California, United States * These authors have contributed equally to this work Correspondence to: Jidong Gao, email: gaojidong@cicams.ac.cn Yi Fang, email: fangyi0501@vip.sina.com Zhenyu Jia, email: zhenyuj@ucr.edu Keywords: breast cancer, next generation sequencing, RNA expression, MLPA, 21-gene Received: January 17, 2017 Accepted: March 28, 2017 Published: May 02, 2017 ABSTRACT RNA in formalin-fixed and paraffin-embedded (FFPE) tissues provides large amount of information indicating disease stages, histological tumor types and grades, as well as clinical outcomes. However, Detection of RNA expression levels in formalin-fixed and paraffin-embedded samples is extremely difficult due to poor RNA quality. Here we developed a high-throughput method, Reverse Transcription-Multiple Ligation-dependent Probe Sequencing (RT-MLPSeq), to determine expression levels of multiple transcripts in FFPE samples. By combining Reverse Transcription-Multiple Ligation-dependent Amplification method and next generation sequencing technology, RT-MLPSeq overcomes the limit of probe length in multiplex ligation-dependent probe amplification assay and thus could detect expression levels of transcripts without quantitative limitations. We proved that different RT-MLPSeq probes targeting on the same transcripts have highly consistent results and the starting RNA/cDNA input could be as little as 1 ng. RT-MLPSeq also presented consistent relative RNA levels of selected 13 genes with reverse transcription quantitative PCR. Finally, we demonstrated the application of the new RT-MLPSeq method by measuring the mRNA expression levels of 21 genes which can be used for accurate calculation of the breast cancer recurrence score – an index that has been widely used for managing breast cancer patients.

Acute ischemic stroke affects over 800,000 US adults annually, with hundreds of thousands more experiencing a transient ischemic attack. Emergent evaluation, prompt acute treatment, and identification of stroke or TIA (transient ischemic attack) etiology for specific secondary prevention are critical for decreasing further morbidity and mortality of cerebrovascular disease. The Biomarkers of Acute Stroke Etiology (BASE) study is a multicenter observational study to identify serum markers defining the etiology of acute ischemic stroke. Observational trial of patients presenting to the hospital within 24h of stroke onset. Blood samples are collected at arrival, 24, and 48h later, and RNA gene expression is utilized to identify stroke etiology marker candidates. The BASE study began January 2014. At the time of writing, there are 22 recruiting sites. Enrollment is ongoing, expected to hit 1000 patients by March 2017. The BASE study could potentially aid in focusing the initial diagnostic evaluation to determine stroke etiology, with more rapidly initiated targeted evaluations and secondary prevention strategies.Clinical Trial Registration Clinicaltrials.gov NCT02014896 https://clinicaltrials.gov/ct2/show/NCT02014896?term=biomarkers+of+acute+stroke+etiology&rank=1.

Luda Diatchenko, MD, PhD is a Canada Excellence Research Chair in Human Pain Genetics, Professor, Faculty of Medicine, Department of Anesthesia and Faculty of Dentistry at McGill University, Alan Edwards Centre for Research on Pain. She earned her MD and PhD in the field of molecular biology from the Russian State Medical University. She started her career in industry, she was a Leader of the RNA Expression Group at Clontech, Inc., and subsequently, Director of Gene Discovery at Attagene, Inc. During this time, she was actively involved in the development of several widely used and widely cited molecular tools for the analysis of gene expression and regulation. Her academic career started at 2000 in the Center for Neurosensory Disorders at University of North Carolina. Her research since then is focused on determining the cellular and molecular biological mechanisms by which functional genetic variations impact human pain perception and risk of development of chronic pain conditions, enabling new approaches to identify new drug targets, treatment responses to analgesics and diagnostic. Multiple collaborative activities allow the Diatchenko group to take basic genetic findings all the way from human association studies, through molecular and cellular mechanisms to animal models and ultimately to human clinical trials. In total, she has authored or co-authored over 120 peer-reviewed research papers in journals, ten book chapters and edited a book in human pain genetics. She is a member and an active officer of several national and international scientific societies, including the International Association for the Study of Pain and the American Pain Society.

Summary Although RNA expression data are accumulating at a remarkable speed, gaining insights from them still requires laborious analyses, which hinder many biological and biomedical researchers. This report introduces a visual analytics framework that applies several well-known visualization techniques to leverage understanding of an RNA expression dataset. Our analyses on glycosaminoglycan-related genes have demonstrated the broad application of this tool, anexVis (analysis of RNA expression), to advance the understanding of tissue-specific glycosaminoglycan regulation and functions, and potentially other biological pathways. Availability and implementation The application is accessible at https://anexvis.chpc.utah.edu/, source codes deposited on GitHub. Supplementary information Supplementary data are available at Bioinformatics online.

Chronic gastro-abdominal pain with altered bowel habits are associated with pathologies including gastroenteritis, autoimmune and inflammatory bowel disease, and irritable bowel syndrome (IBS). In IBS, diagnostic evidence of infection or inflammation are absent, yet symptoms nonetheless include chronic abdominal pain and alterations of stool frequency and consistency, with most common subtypes including diarrhea-predominant (IBS-D) or constipation predominant (IBS-C). [1, 2] IBS is a common clinical complaint in westernized nations, with females more frequently diagnosed than males [3]. Obesity is also associated with increased likelihood of chronic pain [4], and is associated with intestinal dysbiosis, and systemic inflammatory signatures [5]. Improving personalized medicine therefore requires patient stratification based on a combination of biological factors contributing to the individual’s symptom and biomarker spectrum. The “buffy coat” method isolates leukocytes and PBMCs from whole blood, comprises the immune cell population in peripheral blood. These cells are relatively inactive but are primed to respond to generalized and localized immune activation signals; they are under active investigation as diagnostic biomarkers [6]. Collection of buffy coat is a standard method in clinical laboratories; detection of immune activation via RNA expression biomarkers will be informative of differential biological response, and be tractable to collect in clinical settings. Results of differential expression, pathway analysis, and cell-type abundance analysis from buffy coat RNA, is presented here using variables for BMI, Gender, and IBS-subtype from publicly available Nanostring RNA expression and phenotypic data from the NCBI GEO database.

“miRNA colorectal cancer” (https://mirna-coadread.omics.si/) is a freely available web application for studying microRNA and mRNA expression and their correlation in colorectal cancer. To the best of our knowledge, “miRNA colorectal cancer” has the largest knowledge base of miRNA-target gene expressions and correlations in colorectal cancer, based on the largest available sample size from the same source of data. Data from high-throughput molecular profiling of 295 colon and rectum adenocarcinoma samples from The Cancer Genome Atlas was analyzed and integrated into our knowledge base. The objective of developing this web application was to help researchers to discover the behavior and role of miRNA-target gene interactions in colorectal cancer. For this purpose, results of differential expression and correlation analyses of miRNA and mRNA data collected in our knowledge base are available through web forms. To validate our knowledge base experimentally, we selected genes FN1, TGFB2, RND3, ZEB1 and ZEB2 and miRNAs hsa-miR-200a/b/c-3p, hsa-miR-141-3p and hsa-miR-429. Both approaches revealed a negative correlation between miRNA hsa-miR-200b/c-3p and its target gene FN1 and between hsa-miR-200a-3p and its target TGFB2, thus supporting the usefulness of the developed knowledge base.

Background Current diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, resulting in overdiagnosis and overtreatment of clinically insignificant tumors. Thus, to improve the management of PC, novel biomarkers are urgently needed. Results In this study, we integrated genome-wide methylome (Illumina 450K DNA methylation array (450K)) and RNA sequencing (RNAseq) data performed in a discovery set of 27 PC and 15 adjacent normal (AN) prostate tissue samples to identify candidate driver genes involved in PC development and/or progression. We found significant enrichment for homeobox genes among the most aberrantly methylated and transcriptionally dysregulated genes in PC. Specifically, homeobox gene MEIS2 (Myeloid Ecotropic viral Insertion Site 2) was significantly hypermethylated (p p 500 PC and AN tissue samples in total (TCGA cohort analyzed by 450K and RNAseq). Furthermore, in three independent radical prostatectomy (RP) cohorts (n > 700 patients in total), low MEIS2 transcriptional expression was significantly associated with poor biochemical recurrence (BCR) free survival (p = 0.0084, 0.0001, and 0.0191, respectively; log-rank test). Next, we analyzed another RP cohort consisting of > 200 PC, AN, and benign prostatic hyperplasia (BPH) samples by quantitative methylation-specific PCR (qMSP) and found that MEIS2 was significantly hypermethylated (p 0.84. Moreover, in this cohort, aberrant MEIS2 hypermethylation was significantly associated with post-operative BCR (p = 0.0068, log-rank test), which was subsequently confirmed (p = 0.0067; log-rank test) in the independent TCGA validation cohort (497 RP patients; 450K data). Conclusions To the best of our knowledge, this is the first study to investigate, demonstrate, and independently validate a prognostic biomarker potential for MEIS2 at the transcriptional expression level and at the DNA methylation level in PC.

ACTL10 is a member of the actin family; however, despite previous studies suggesting that certain proteins in this family may be related to the pathogenesis of leukemia, to the best of our knowledge, no studies to date have demonstrated any association between ACTAL10 and leukemia. Thus, the present study aimed to determine the association between ACTL10 expression levels, DNA methylation levels and the clinical prognosis in cytogenic normal acute myeloid leukemia (CN-AML). Data from seventy-five patients with CN-AML and patients with AML treated with chemotherapy or allogeneic hematopoietic stem cell transplantation were obtained from The Cancer Genome Atlas (TCGA) dataset and were used to analyze the clinical prognosis of ACTL10 RNA expression levels and DNA methylation levels. In addition, the study also investigated the combined clinical prognosis of ACTL10 RNA expression levels and ACTL10 DNA methylation levels in 74 patients with CN-AML from the TCGA dataset. ACTL10 RNA expression levels were observed to be highly expressed in patients with CD34+/CD38+ AML (P