scholarly journals In-silico performance, validation, and modeling of the Nanostring Banff Human Organ transplant gene panel using archival data from human kidney transplants

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
R. N. Smith
Keyword(s):  
Gene Expression ◽  
Microarray Data ◽  
In Silico ◽  
Organ Transplant ◽  
Human Kidney ◽  
Gene Panel ◽  
Gene Expressions ◽  
Tissue Samples ◽  
Human Organ ◽  
Archival Tissue

Abstract Background RNA gene expression of renal transplantation biopsies is commonly used to identify the immunological patterns of graft rejection. Mostly done with microarrays, seminal findings defined the patterns of gene sets associated with rejection and non-rejection kidney allograft diagnoses. To make gene expression more accessible, the Molecular Diagnostics Working Group of the Banff Foundation for Allograft Pathology and NanoString Technologies partnered to create the Banff Human Organ Transplant Panel (BHOT), a gene panel set of 770 genes as a surrogate for microarrays (~ 50,000 genes). The advantage of this platform is that gene expressions are quantifiable on formalin fixed and paraffin embedded archival tissue samples, making gene expression analyses more accessible. The purpose of this report is to test in silico the utility of the BHOT panel as a surrogate for microarrays on archival microarray data and test the performance of the modelled BHOT data. Methods BHOT genes as a subset of genes from downloaded archival public microarray data on human renal allograft gene expression were analyzed and modelled by a variety of statistical methods. Results Three methods of parsing genes verify that the BHOT panel readily identifies renal rejection and non-rejection diagnoses using in silico statistical analyses of seminal archival databases. Multiple modelling algorithms show a highly variable pattern of misclassifications per sample, either between differently constructed principal components or between modelling algorithms. The misclassifications are related to the gene expression heterogeneity within a given diagnosis because clustering the data into 9 groups modelled with fewer misclassifications. Conclusion This report supports using the Banff Human Organ Transplant Panel for gene expression of human renal allografts as a surrogate for microarrays on archival tissue. The data modelled satisfactorily with aggregate diagnoses although with limited per sample accuracy and, thereby, reflects and confirms the modelling complexity and the challenges of modelling gene expression as previously reported.

scholarly journals Validation of the Nanostring of the Banff Human Organ Transplant Gene Panel in Archival Data from Human Kidney Transplants and its Modelling Complexity

2020 ◽  
Author(s):  
Rex Smith
Keyword(s):  
Gene Expression ◽  
New Technology ◽  
Organ Transplant ◽  
Human Kidney ◽  
Gene Panel ◽  
Gene Expressions ◽  
Tissue Samples ◽  
Human Organ ◽  
Expression Arrays ◽  
Gene Expression Heterogeneity

Abstract Background RNA gene expression of renal transplantation biopsies is commonly used to identify rejection. Mostly done with microarrays, seminal findings describe and define the patterns of genes associated with types of rejection and non-rejection kidney allograft diagnoses. To make gene expression more accessible for pathology laboratories, the Molecular Diagnostics Working Group of the Banff Foundation for Allograft Pathology and NanoString Technologies partnered to create the Banff Human Organ Transplant Panel (BHOT), a gene panel set of 770 genes as a substitute for microarrays (~ 50,000 genes). The advantage of this platform is that gene expressions are quantifiable on formalin fixed and paraffin embedded archival tissue samples. This new technology, thus, makes gene expressions cheaper and accessible to more laboratories and investigators. The purpose of this report is to validate the BHOT panel as a surrogate for microarrays and test the accuracy of the modelled BHOT data. Results This limited NanoString gene set readily identifies renal rejection and non-rejection diagnostic patterns using in silico statistical analyses of seminal archival databases derived from renal transplant RNA expression arrays. Multiple modelling algorithms show a highly variable pattern within the error matrices per sample. The discrepancies within the error matrices are most likely related to the gene expression heterogeneity of samples within a given pathological diagnosis. This was confirmed by clustering the data into 8 groups, which modelled with fewer misclassifications. Conclusion This report validates gene expression of human renal allografts using the Banff Human Organ Transplant Panel as a surrogate for microarrays and confirms the its modelling complexity.

scholarly journals Microarray Based Functional Analysis of Myricetin and Proteomic Study on Its Anti-Inflammatory Property

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Tao Li ◽  
Jihe Zhu ◽  
Fangming Deng ◽  
Weiguo Wu ◽  
Zhibing Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metabolic Disease ◽  
Microarray Data ◽  
Inflammatory Cytokine ◽  
Gene Expressions ◽  
Genome Wide ◽  
Proteomic Study ◽  
Anti Inflammatory ◽  
First Time

Myricetin has been reported as a promising chemopreventive compound with multiple biofunctions. To evaluate its influence on gene expressions in genome-wide set and further investigate its anti-inflammatory property, the present study performed Gene Ontology and Ingenuity Pathway Analysis (IPA) to describe the basic gene expression characteristics by myricetin treatment in HepG2 cells, confirmed its multi-biofunction by real-time fluorescent quantitative PCR (RT-qPCR), and further verified its anti-inflammatory property by Western blotting and bio-plex-based cytokines assay. The IPA data showed that 337 gene expressions (48% of the top molecules) are disturbed over 2-fold, and the most possible biofunctions of myricetin are the effect on “cardiovascular disease, metabolic disease, and lipid metabolism,” via regulation of 28 molecules with statistic score of 46. RT-qPCR data confirmed the accuracy of microarray data, and cytokines assay results indicated that 6 of the total 27 inflammatory cytokine secretions were significantly inhibited by myricetin pretreatment, including TNF-α, IFN-γ, IL-1α, IL-1β, IL-2, and IL-6. The present study is the first time to elucidate the multi-function of myricetin in genome-wide set by IPA analysis and verify its anti-inflammatory property by proteomics of cytokines assay. Therefore, these results enrich the comprehensive bioactivities of myricetin and reveal that myricetin has powerful anti-inflammatory property, which provides encouragement for in vivo studies to verify its possible health benefits.

scholarly journals Bicluster Method to Predict Gene Patterns to Classify Differential Gene Expressions in Non-Small Cell Lung Cancer

2019 ◽  
Vol 9 (1) ◽  
pp. 5057-5065
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Big Data ◽  
Large Datasets ◽  
Epithelial Tissue ◽  
Gene Expressions ◽  
Tissue Samples ◽  
Differential Gene ◽  
Differential Expressed Genes ◽  
Never Smokers

In recent years, there are numerous efforts to overcome the constraints of data mining approaches to classify "BIG DATA". There are several types of data which has identical and similar expressions but there are dependent classification algorithms to predict these classes of expressions. Totally Different algorithms have been developed and enforced to research and differentiate the categories of data groups based on their functions. Zero-suppressed Binary Decision Diagram (ZBDD) algorithms help to classify the data with several categories. In the present study, lung cancer gene expression datasets 25 samples contain 10 mouth buccal cavity epithelial tissue samples and 15 nasal epithelial tissue samples from never smokers and current smokers were used to classify the genes and their expressions with various conditions. Using R and BioConductor software to normalize and predict differential expressed genes by Affy, Affycore tools and Limma packages to predict the gene expression with various functional properties. ZBDD algorithm and parallel coordination helps to predict the functional genes and the results shows 345 nasal epithelial genes were predict of which 54 genes were present in bicluster and 35 genes from mouth epithelial tissues show 14 were present in ZBDD bicluster. The results conclude that ZBDD algorithm has great advantage to classify big data and this algorithm can introduce in any large datasets for the accurate predict of large datasets.

In silico identification of an epithelial core signature in human tumors.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 10628-10628
Author(s):  
Chirayu Pankaj Goswami ◽  
Oscar D. Cano ◽  
Yesim Gokmen-Polar ◽  
Sunil S. Badve
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Expression Analysis ◽  
In Silico ◽  
Differential Expression Analysis ◽  
Gene Signature ◽  
Venn Diagram ◽  
Expression Data ◽  
Tissue Samples ◽  
Gene Probes

10628 Background: Gene expression analysis is performed on grossly selected specimens often without any microscopic analysis of tumor content. In studies where histological analyses have been performed, cases having 80% or more tumor content are used for microarray analysis. The variability in amount of epithelial and stromal cells may generate to misleading differential expression analysis and selection for wrong targets for therapeutics. It is also often unclear, whether the genes identified are stromal or epithelial in origin. The goal of this study was to identify genes that define core epithelial phenotype; these genes could provide means of normalization of expression data. Methods: The CABIG GSK microarray (HG-U133_plus_2) data consisting of 950 cell lines from carcinoma (n=562), non-carcinoma (n=385) and normal tissue (n=3) was analyzed to identify epithelial specific genes. 10 carcinomas each from 11 sites (n=110) and an equal number of non-carcinomas were randomly selected. In silico analyses were performed by 1) identifying genes differentially expressed between carcinoma and non-carcinoma samples using a one way ANOVA; 2) identifying gene signature associated with carcinoma using Predictive Analysis of Microarrays (PAM) and 3) a weighted gene coexpression network analysis (WGCNA) was performed to identify co-expression modules. A similar analysis was also performed on tissue samples (E-GEOD-12360) from carcinomas and non-carcinomas. Venn-diagram was generated to identify intersecting set. Results: Comparison of the carcinoma and non-carcinoma samples using ANOVA identified 1455 differential expressed gene probes in cell lines and 540 gene probes in tissues (FDR=1E-10). The cell lines analysis identified 5 modules and a 65-gene signature (43 core and 22 accessory set) that was specific for epithelial cells. In the tissue analysis a 188-gene signature was similarly identified. Cross-comparison identified a smaller 31 gene intersecting set; this was not associated with loss of discriminatory power. Conclusions: A 31 geneset which can be used to determine the epithelial content of heterogeneous tumors, was identified. This study has the potential to significantly impact the use of microarray based gene expression data.

scholarly journals Caveolin-1 in Kidney Chronic Antibody-Mediated Rejection: An Integrated Immunohistochemical and Transcriptomic Analysis Based on the Banff Human Organ Transplant (B-HOT) Gene Panel

Biomedicines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1318
Author(s):  
Alessandro Gambella ◽  
Antonella Barreca ◽  
Simona Osella-Abate ◽  
Emanuel Bottasso ◽  
Manuela Maria Giarin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mhc Class Ii ◽  
Immune Cell ◽  
Nk Cell ◽  
Organ Transplant ◽  
Surrogate Marker ◽  
Conclusive Evidence ◽  
Human Organ ◽  
Caveolin 1 ◽  
Antibody Mediated Rejection

Caveolin-1 overexpression has previously been reported as a marker of endothelial injury in kidney chronic antibody-mediated rejection (c-ABMR), but conclusive evidence supporting its use for daily diagnostic practice is missing. This study aims to evaluate if Caveolin-1 can be considered an immunohistochemical surrogate marker of c-ABMR. Caveolin-1 expression was analyzed in a selected series of 22 c-ABMR samples and 11 controls. Caveolin-1 immunohistochemistry proved positive in peritubular and glomerular capillaries of c-ABMR specimens, irrespective of C4d status whereas all controls were negative. Multiplex gene expression profiling in c-ABMR cases confirmed Caveolin-1 overexpression and identified additional genes (n = 220) and pathways, including MHC Class II antigen presentation and Type II interferon signaling. No differences in terms of gene expression (including Caveolin-1 gene) were observed according to C4d status. Conversely, immune cell signatures showed a NK-cell prevalence in C4d-negative samples compared with a B-cell predominance in C4d-positive cases, a finding confirmed by immunohistochemical assessment. Finally, differentially expressed genes were observed between c-ABMR and controls in pathways associated with Caveolin-1 functions (angiogenesis, cell metabolism and cell–ECM interaction). Based on our findings, Caveolin-1 resulted as a key player in c-ABMR, supporting its role as a marker of this condition irrespective of C4d status.

scholarly journals Early upregulation of AR and steroidogenesis enzyme expressions after 3 months of androgen-deprivation therapy.

2020 ◽  
Author(s):  
Agus Rizal A.H. Hamid ◽  
Harun Kusuma Putra ◽  
Ningrum Paramita Sari ◽  
Putri Diana ◽  
Saras Serani Sesari ◽  
...  
Keyword(s):  
Gene Expression ◽  
Androgen Deprivation Therapy ◽  
Early Response ◽  
Androgen Deprivation ◽  
Progression Rate ◽  
Relative Gene Expression ◽  
Gene Expressions ◽  
Steroidogenic Enzyme ◽  
Tissue Samples ◽  
Relative Gene

Abstract Background: Androgen-Deprivation Therapy (ADT) is a standard treatment for advanced prostate cancer (PCa). However, there is a high recurrence or progression rate during ADT. Until now, there is no evidence on when the progression starts. This study would like to evaluate the early response of intraprostatic androgen receptor (AR) and steroidogenic enzyme gene expressions in ADT.Methods: Prostate tissue samples were taken from PCa patients with urinary retention, who had ADT (ADT- PCa; n=10), and further grouped into ≤12 months (n=4) and ADT >12 months (n=6). ADT-PCa group were then compared with BPH (n=12) and primary (no treatment) PCa tissues (n=16). AR and steroidogenic enzyme genes were extracted from Formalin Fixed Paraffin embedded (FFPE) tissues and analysed using rtPCR. Protein expressions were evaluated by immunohistochemistry of specific antibodies. Results: AR gene expression was found higher in ADT-PCa group compared to BPH and primary PCa. Both ADT ≤12 and > 12 months subgroups had significantly higher relative gene expression of AR (p 0.01 and 0.03) compared to primary PCa. AR protein expression in ADT-PCa group showed an increase trend in ADT ≤12 months subgroup and a significantly elevated expression AR protein in ADT >12 months subgroup compared with PCa (100%; p <0.01). Half (50%) of ADT ≤12 months patients were found to have upregulation of AR, and one undergone upregulation from only 3 months of ADT. A trend of elevating relative gene expression of SRD5A3 were also found within the groups given ADT. Conclusion: There are upregulation of AR and steroidogenic enzymes in ADT-PCa patients, as early as 3 months without showing PSA elevation. Steroidogenic enzyme, especially SRD5A3 expression was also showing upregulation before PSA rises.

In silico and ex vivo approaches identify a role for toll-like receptor 4 in the biology of sporadic colorectal cancer.

2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 460-460
Author(s):  
D. A. Sussman ◽  
R. Santaolalla ◽  
J. Clarke ◽  
M. T. Abreu
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Microarray Data ◽  
In Silico ◽  
Receptor Expression ◽  
Data Sets ◽  
Toll Like Receptor ◽  
Tlr4 Expression ◽  
Toll Like Receptor 4 ◽  
Oncogenic Pathways

460 Background: Several lines of evidence suggest that the host response to bacteria plays a role in the development of colorectal cancer (CRC). Work on innate immune signaling has shown that toll-like receptor-4 (TLR4) is required for colitis-associated neoplasia in a mouse model, suggesting that TLRs may be a critical link between colonic bacteria and the development of colon cancer. The objective of the present study was to test the hypothesis that dysregulated TLR4 expression occurs in a subset of sporadic colorectal cancers. Methods: Bioinformatic and immunohistochemical approaches were used to test the hypothesis. Publicly available, online microarray data sets of gene expression data (Oncomine and Gene Expression Omnibus) were searched for information relevant to CRC. Searches were included if data sets contained human patient data with paired samples, ≥ 20 subjects per study, and use of standardized microarray platforms. Excluded searches contained patients with genetic cancer syndromes or colitis. Associations were investigated between TLR4 expression and oncogenic pathways. Staining of human CRCs for TLR4 was performed in a consecutive series of 10 patients at the University of Miami. Intensity of staining for TLR4 was calculated using immunofluorescence and NIH's ImageJ software. 5 different areas per 10x-field were quantified per tumor. Results: Heat maps were generated from the microarray data and demonstrated an increased expression of TLR4 in colon adenomas and CRCs when compared to matched samples of normal colonic mucosa. In silico, expression of TLR4 was positively correlated with expression of COX-2, β-catenin, and EGFR. By IHC, 30% of CRCs have increased TLR4 expression compared with histologically normal epithelium obtained from the tumor margins. ImageJ analysis revealed that CRC's could be segregated based on fluorescent intensity into negative, intermediate, and strongly positive samples. Conclusions: TLR4 receptor expression defines a subset of patients with sporadic CRC and is associated with expression of key oncogenic pathways. Further study is needed to establish the relationship between TLR4 and CRC outcomes. No significant financial relationships to disclose.

scholarly journals Early upregulation of AR and steroidogenesis enzyme expressions after 3 months of androgen-deprivation therapy.

2019 ◽  
Author(s):  
Agus Rizal A.H. Hamid ◽  
Harun Kusuma Putra ◽  
Ningrum Paramita Sari ◽  
Putri Diana ◽  
Saras Serani Sesari ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Expression ◽  
Early Response ◽  
Relative Gene Expression ◽  
Gene Expressions ◽  
Steroidogenic Enzyme ◽  
Tissue Samples ◽  
Elevated Expression ◽  
Ffpe Tissues ◽  
Relative Gene

Abstract Purpose This study would like to evaluate the early response of intraprostatic androgen receptor (AR) and steroidogenic enzyme gene expressions in ADT. Methods Prostate tissue samples were taken from PCa patients with urinary retention, who had ADT (ADT- PCa; n=10), and further grouped into ≤12 months (n=4) and ADT >12 months (n=6). ADT-PCa group were then compared with BPH (n=12) and primary (no treatment) PCa tissues (n=16). AR and steroidogenic enzyme genes were extracted from Formalin Fixed Paraffin embedded (FFPE) tissues and analysed using rtPCR. Protein expressions were evaluated by immunohistochemistry of specific antibodies. Results AR gene expression was found higher in ADT-PCa group compared to BPH and primary PCa. Both ADT ≤12 and > 12 months subgroups had significantly higher relative gene expression of AR (p 0.01 and 0.03) compared to primary PCa. AR protein expression in ADT-PCa group showed an increase trend in ADT ≤12 months subgroup and a significantly elevated expression AR protein in ADT >12 months subgroup compared with PCa (100%; p <0.01). Half (50%) of ADT ≤12 months patients were found to have upregulation of AR, and one undergone upregulation from only 3 months of ADT. A trend of elevating relative gene expression and protein expression of SRD5A1 and SRD5A3 were also found in one patient with 3 months of ADT. Conclusion There are upregulation of AR and steroidogenic enzymes in ADT-PCa patients, as early as 3 months without showing PSA elevation. Steroidogenic enzyme, especially SRD5A, expression was also upregulated before PSA rises.

Gene expression levels of HER2 and IL-8 and polymorphism in IL-8 associated with clinical outcome in advanced or metastatic gastric cancer treated with lapatinib in SWOG 0413 trial

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 4647-4647 ◽  
Author(s):  
H. Chang ◽  
M. Azuma ◽  
B. Goldman ◽  
F. Nagashima ◽  
S. Iqbal ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Clinical Outcome ◽  
Cyclin D1 ◽  
Kinase Inhibitor ◽  
Metastatic Gastric Cancer ◽  
Gene Expressions ◽  
Tissue Samples ◽  
Expression Levels ◽  
Gene Expression Levels

4647 Background: Lapatinib (GW572016) is a dual tyrosine kinase inhibitor of EGFR and HER2. In SWOG0413 trial, advanced or metastatic gastric cancer patients were treated with lapatinib. In this study, we investigated whether gene expressions and polymorphisms of EGF and angiogenesis pathway genes were associated with clinical outcome in the patients enrolled in SWOG0413 trial. Methods: A total of 46 patients were enrolled in SWOG0413 trial and treated with lapatinib. Blood and tissue samples were available from 42 and 37 patients, respectively. RT-PCR was performed for intratumoral gene expression levels of EGFR, HER2, VEGF, IL-8, COX2 and cyclin D1 genes. We also analyzed 8 polymorphisms in the EGF, EGFR, HER2, VEGF, IL-8, COX2 and cyclin D1 genes by PCR-RFLP. Results: Patients who have lower IL-8 [median overall survival (OS), 6 vs 3 months, p=0.03] and higher HER2 (6 vs 3 months, p=0.005) gene expression levels showed better OS. According to gene polymorphisms, patients who have A allele of IL-8 T251A polymorphism showed improved OS (A/A, 10 months vs T/A, 5 months vs T/T 3 months, p=0.04). And patients with A allele of IL-8 T251A and T allele of VEGF C936T polymorphisms showed better response rates (p<0.01, p<0.01, respectively). All other polymorphisms and gene expressions did not show significant association with clinical outcome. Conclusions: Our results suggest that intratumoral gene expression levels of HER2 and IL-8 and polymorphism in IL-8 are potential molecular predictors for survival in patients with advanced or metastatic gastric cancer treated with lapatinib. And polymorphisms in IL-8 and VEGF genes may be potential markers in predicting response in this population. A larger prospective study is needed to validate and confirm these preliminary findings. [Table: see text]

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