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Molecular Profiling (molecular + profiling)

Distribution by Scientific Domains

Medical Sciences	80%

Selected Abstracts

Molecular profiling of platinum resistant ovarian cancer,

INTERNATIONAL JOURNAL OF CANCER, Issue 8 2006
Jozien Helleman
Abstract The aim of this study is to discover a gene set that can predict resistance to platinum-based chemotherapy in ovarian cancer. The study was performed on 96 primary ovarian adenocarcinoma specimens from 2 hospitals all treated with platinum-based chemotherapy. In our search for genes, 24 specimens of the discovery set (5 nonresponders and 19 responders) were profiled in duplicate with 18K cDNA microarrays. Confirmation was done using quantitative RT-PCR on 72 independent specimens (9 nonresponders and 63 responders). Sixty-nine genes were differentially expressed between the nonresponders (n = 5) and the responders (n = 19) in the discovery phase. An algorithm was constructed to identify predictive genes in this discovery set. This resulted in 9 genes (FN1, TOP2A, LBR, ASS, COL3A1, STK6, SGPP1, ITGAE, PCNA), which were confirmed with qRT-PCR. This gene set predicted platinum resistance in an independent validation set of 72 tumours with a sensitivity of 89% (95% CI: 0.68,1.09) and a specificity of 59% (95% CI: 0.47,0.71)(OR = 0.09, p = 0.026). Multivariable analysis including patient and tumour characteristics demonstrated that this set of 9 genes is independent for the prediction of resistance (p < 0.01). The findings of this study are the discovery of a gene signature that classifies the tumours, according to their response, and a 9-gene set that determines resistance in an independent validation set that outperforms patient and tumour characteristics. A larger independent multicentre study should further confirm whether this 9-gene set can identify the patients who will not respond to platinum-based chemotherapy and could benefit from other therapies. © 2005 Wiley-Liss, Inc. [source]

Intraocular pigmented proliferations in the context of cytologic evaluation

DIAGNOSTIC CYTOPATHOLOGY, Issue 11 2009
F.I.A.C.Article first published online: 22 JUL 200, Lourdes R. Ylagan M.D.
Abstract This article is written to give an overview of the various intraocular pigmented proliferations as it pertains to cytologic evaluation and interpretation. It reviews the various epithelial and melanocytic lesions, their location and the various clinical approaches the ophthalmologist uses to aspirate the lesion. It also reviews the current thinking in the differentiation between Class I and Class II melanomas and how molecular profiling may be necessary in its differentiation which could help stratify those patients whose tumors are refractory to treatment and may benefit from adjuvant chemotherapy and eye-sparing surgery. Diagn. Cytopathol. 2009. © 2009 Wiley-Liss, Inc. [source]

Epidermal growth factor receptor in relation to tumor development: EGFR-targeted anticancer therapy

FEBS JOURNAL, Issue 2 2010
Isamu Okamoto
The discovery that signaling by the epidermal growth factor receptor (EGFR) plays a key role in tumorigenesis prompted efforts to target this receptor in anticancer therapy. Two different types of EGFR-targeted therapeutic agents were subsequently developed: mAbs, such as cetuximab and panitumumab, which target the extracellular domain of the receptor, thereby inhibiting ligand-dependent EGFR signal transduction; and small-molecule tyrosine kinase inhibitors, such as gefitinib and erlotinib, which target the intracellular tyrosine kinase domain of the EGFR. Furthermore, recent clinical and laboratory studies have identified molecular markers that have the potential to improve the clinical effectiveness of EGFR-targeted therapies. This minireview summarizes the emerging role of molecular profiling in guiding the clinical use of anti-EGFR therapeutic agents. [source]

Heterogeneity in juvenile idiopathic arthritis: Impact of molecular profiling based on DNA polymorphism and gene expression patterns

ARTHRITIS & RHEUMATISM, Issue 9 2010
Susan D. Thompson
First page of article [source]

Multiple fuzzy neural network system for outcome prediction and classification of 220 lymphoma patients on the basis of molecular profiling

CANCER SCIENCE, Issue 10 2003
Tatsuya Ando
A fuzzy neural network (FNN) using gene expression profile data can select combinations of genes from thousands of genes, and is applicable to predict outcome for cancer patients after chemotherapy. However, wide clinical heterogeneity reduces the accuracy of prediction. To overcome this problem, we have proposed an FNN system based on majoritarian decision using multiple noninferior models. We used transcriptional profiling data, which were obtained from "Lymphochip" DNA microarrays (http://llmpp.nih.gov/DLBCL), reported by Rosenwald (N Engl J Med 2002; 346: 1937,47). When the data were analyzed by our FNN system, accuracy (73.4%) of outcome prediction using only 1 FNN model with 4 genes was higher than that (68.5%) of the Cox model using 17 genes. Higher accuracy (91%) was obtained when an FNN system with 9 noninferior models, consisting of 35 independent genes, was used. The genes selected by the system included genes that are informative in the prognosis of Diffuse large B-cell lymphoma (DLBCL), such as genes showing an expression pattern similar to that of CD10 and BCL-6 or similar to that of IRF-4 and BCL-4. We classified 220 DLBCL patients into 5 groups using the prediction results of 9 FNN models. These groups may correspond to DLBCL subtypes. In group A containing half of the 220 patients, patients with poor outcome were found to satisfy 2 rules, i.e., high expression of MAX dimerization with high expression of unknown A (LC_26146), or high expression of MAX dimerization with low expression of unknown B (LC_33144). The present paper is the first to describe the multiple noninferior FNN modeling system. This system is a powerful tool for predicting outcome and classifying patients, and is applicable to other heterogeneous diseases. [source]