scholarly journals Comparative gene expression profiling of ADAMs, MMPs, TIMPs, EMMPRIN, EGF-R and VEGFA in low grade meningioma

2016 ◽  
Vol 49 (6) ◽  
pp. 2309-2318 ◽  
Author(s):  
Harcharan K. Rooprai ◽  
Andrew J. Martin ◽  
Andrew King ◽  
Usha D. Appadu ◽  
Huw Jones ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Low Grade

scholarly journals FXYD3: A Promising Biomarker for Urothelial Carcinoma

2011 ◽  
Vol 6 ◽  
pp. BMI.S6487 ◽  
Author(s):  
ZhongFa Zhang ◽  
See-Tong Pang ◽  
Katherine A. Kasper ◽  
Chunyan Luan ◽  
Bill Wondergem ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Diagnosis ◽  
Urothelial Carcinoma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Low Grade ◽  
Mrna Levels ◽  
Kidney Tumor ◽  
Normal Kidney ◽  
Tumor Subtypes

Objective Urothelial carcinoma (UC) of the kidney is a relatively rare but aggressive form of kidney cancer. Differential diagnosis of renal UC from renal cell carcinoma (RCC) can be difficult, but is critical for correct patient management. We aimed to use global gene expression profiling to identify genes specifically expressed in urothelial carcinoma (UC) of the kidney, with purpose of finding new biomarkers for differential diagnosis of UC of both upper and lower tract from normal tissues. Materials and Methods Microarray gene expression profiling was performed on a variety of human kidney tumor samples, including clear cell, papillary, chromophobe, oncocytoma, renal UC and normal kidney controls. Differentially expressed mRNAs in various kidney tumor subtypes were thus identified. Protein expression in human UC tumor samples from both upper and lower urinary tract was evaluated by immunohistochemistry. Results FXYD3 (MAT-8) mRNA was specifically expressed in UC of the kidney and not in normal kidney tissue or in any RCC tumor subtypes. FXYD3 mRNA levels displayed equal or better prediction rate for the detection of renal UC than the mRNA levels of selected known UC markers as p63, vimentin, S100P, KRT20 and KRT7. Finally, immunohistochemical staining of clinical UC samples showed that FXYD3 protein is overexpressed in majority of UC of the upper genitourinary tract (encompassing the kidney, ~90%) and in majority of high grade bladder UC (~84%, it's < 40% in low grade tumors, P < 0.001) compared to normal kidney and bladder tissues. Conclusion FXYD3 may be a promising novel biomarker for the differential diagnosis of renal UC and a promising prognosis marker of UC from bladder. Because it was identified genome-widely, FXYD3 may have important biological ramifications for the genetic study of UC.

scholarly journals Gene Expression Profiling in Human High-Grade Astrocytomas

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Zhongyu Liu ◽  
Zhiqiang Yao ◽  
Chao Li ◽  
Yicheng Lu ◽  
Chunfang Gao
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Anaplastic Astrocytoma ◽  
Low Grade ◽  
Diffuse Astrocytoma ◽  
Who Grade ◽  
Grade Ii ◽  
Who Grade Iii ◽  
Grade Iii

Diffuse astrocytoma of (WHO grade II) has a tendency to progress spontaneously to anaplastic astrocytoma (WHO grade III) and/or glioblastoma (WHO grade IV). However, the molecular basis of astrocytoma progression is still poorly understood. In current study, an essential initial step toward this goal is the establishment of the taxonomy of tumors on the basis of their gene expression profiles. We have used gene expression profiling, unsupervised (hierarchal cluster (HCL) and principal component analysis (PCA)) and supervised (prediction analysis for microarrays (PAM)) learning methods, to demonstrate the presence of three distinct gene expression signatures of astrocytomas (ACMs), which correspond to diffuse or low-grade astrocytoma (WHO grade II), Anaplastic astrocytoma (WHO grade III) and Glioblastoma multiforme (WHO grade IV). We also demonstrate a 171 gene-based classifier that characterize the distinction between these pathologic/molecular subsets of astrocytomas. These results further define molecular subtypes of astrocytomas and may potentially be used to define potential targets and further refine stratification approaches for therapy. In addition, this study demonstrates that combining gene expression analysis with detailed annotated pathway and gene ontology (GO) category resources was applied to highly enriched normal and tumor population; it can yield an understanding of the critical biological mechanism of astrocytomas.

Kidney Injury Monitoring in Tobramycin-Treated Rhesus Monkeys: Supplementing Urinary Kidney Biomarkers With Kidney Biopsy Gene Expression Profiling

2021 ◽  
pp. 019262332110491
Author(s):  
Yi-Zhong Gu ◽  
Larry Handt ◽  
Katerina Vlasakova ◽  
Vasudevan Bakthavatchalu ◽  
Roger Smith ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Messenger Rna ◽  
Rhesus Monkeys ◽  
Kidney Biopsy ◽  
Kidney Injury ◽  
Low Grade ◽  
Biopsy Specimens ◽  
Targeted Gene Expression

Kidney biopsies are used sparingly to diagnose kidney injury in the clinic. Here we have conducted a small exploratory study to directly compare the low-grade kidney injury monitoring performance of serum safety biomarkers, novel urine safety biomarkers, microscopic histopathology and targeted gene expression alterations in kidney biopsy specimens in rhesus monkeys treated with tobramycin. Targeted gene expression increases were observed in the kidney biopsy samples and whole kidney sections for kidney injury molecule 1 ( KIM-1), clusterin ( CLU), osteopontin ( OPN) messenger RNA transcripts. In addition, increases of the urinary kidney safety protein biomarkers including KIM-1, CLU, OPN were also observed. These increases in gene expression and urinary protein end point were in concordance with the eventual low-grade kidney lesions seen in terminal tissue sections. In contrast, conventional serum biomarkers blood urea nitrogen and serum creatinine were not as sensitive in monitoring kidney injury. Although these data do not support routinely adding kidney biopsies to regular toxicology studies, they provide evidence on the value and limitations of incorporating gene expression profiling on kidney biopsy specimens, further underscore the value of urinary kidney safety biomarkers for improved low-grade kidney injury monitoring, and open the door for future definitive studies.

scholarly journals Identifying low-grade cellular rejection after heart transplantation in children by using gene expression profiling

2018 ◽  
Vol 50 (3) ◽  
pp. 190-196 ◽  
Author(s):  
Annie Xin ◽  
Melissa G. Y. Lee ◽  
Yifang Hu ◽  
Vera Ignjatovic ◽  
William Y. Shi ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Heart Transplantation ◽  
Gene Expression Profiling ◽  
T Cell Receptor ◽  
Expression Profiling ◽  
Gene Families ◽  
Cell Receptor ◽  
Low Grade ◽  
Immunoglobulin Gene

Endomyocardial biopsy (EMB) remains the gold standard for detecting rejection after heart transplantation but is costly and invasive. This study aims to distinguish no rejection (0R) from low-grade rejection (1R/2R) after heart transplantation in children by using global gene expression profiling in blood. A total of 106 blood samples with corresponding EMB from 18 children who underwent heart transplantation from 2011 to 2014 were analyzed (18 baseline/pretransplantation samples, 88 EMB samples). Corresponding rejection grades for each blood sample were 0R in 39% (34/88), 1R in 51% (45/88), and 2R in 10% (9/88). mRNA from each sample was sequenced. Differential expression analysis was performed at the gene level. A k-nearest neighbor (kNN) analysis was applied to the most differentially expressed (DE) genes to identify rejection after transplantation. Mean age at transplantation was 10.0 ± 5.4 yr. Expression of B cell and T cell receptor sequences was used to measure the effect of posttransplantation immunosuppression. Follow-up samples had lower levels of immunoglobulin gene families compared with pretransplantation ( P < 3E-5) (lower numbers of activated B cells). T cell receptor alpha and beta gene families had decreased expression in 0R samples compared with pretransplantation ( P < 4E-5) but recovered to near baseline levels in 1R/2R samples. kNN using the most DE gene (MKS1) and k = 9 nearest neighbors correctly identified 83% (73/88) of 1R/2R compared with 0R by leave-one-out cross validation. Using a genomic approach we can distinguish low-grade cellular allograft rejection (1R/2R) from no rejection (0R) after heart transplantation in children despite a wide age range.

Custom microarray for glycobiologists: considerations for glycosyltransferase gene expression profiling

2002 ◽  
Vol 69 ◽  
pp. 135-142 ◽  
Author(s):  
Elena M. Comelli ◽  
Margarida Amado ◽  
Steven R. Head ◽  
James C. Paulson
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Affymetrix Genechip ◽  
Microarray Technology ◽  
Gene Arrays ◽  
Glycosyltransferase Gene

The development of microarray technology offers the unprecedented possibility of studying the expression of thousands of genes in one experiment. Its exploitation in the glycobiology field will eventually allow the parallel investigation of the expression of many glycosyltransferases, which will ultimately lead to an understanding of the regulation of glycoconjugate synthesis. While numerous gene arrays are available on the market, e.g. the Affymetrix GeneChip® arrays, glycosyltransferases are not adequately represented, which makes comprehensive surveys of their gene expression difficult. This chapter describes the main issues related to the establishment of a custom glycogenes array.

278: Gene Expression Profiling of Prostatic Epithelial Cells in Two-Dimensional Versus Three-Dimensional Cultures

2007 ◽  
Vol 177 (4S) ◽  
pp. 93-93
Author(s):  
Toshiyuki Tsunoda ◽  
Junichi Inocuchi ◽  
Darren Tyson ◽  
Seiji Naito ◽  
David K. Ornstein
Keyword(s):  
Gene Expression ◽  
Epithelial Cells ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Three Dimensional ◽  
Two Dimensional

748: Gene Expression Profiling of Renal Medullary Carcinoma

2004 ◽  
Vol 171 (4S) ◽  
pp. 198-199 ◽  
Author(s):  
Ximing J. Yang ◽  
Jun Sugimura ◽  
Maria S. Tretiakova ◽  
Bin T. Teh
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Medullary Carcinoma ◽  
Renal Medullary Carcinoma
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