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RISS 인기검색어
- 검색키워드
- 저자 : Juarez-Mendez, S. (검색결과 3 건)
- 무료
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Data Mining for Identification of Molecular Targets in Ovarian Cancer
Villegas-Ruiz, Vanessa,Juarez-Mendez, Sergio Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.4
Ovarian cancer is possibly the sixth most common malignancy worldwide, in Mexico representing the fourth leading cause of gynecological cancer death more than 70% being diagnosed at an advanced stage and the survival being very poor. Ovarian tumors are classified according to histological characteristics, epithelial ovarian cancer as the most common (~80%). We here used high-density microarrays and a systems biology approach to identify tissue-associated deregulated genes. Non-malignant ovarian tumors showed a gene expression profile associated with immune mediated inflammatory responses (28 genes), whereas malignant tumors had a gene expression profile related to cell cycle regulation (1,329 genes) and ovarian cell lines to cell cycling and metabolism (1,664 genes).
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Villegas-Ruiz, Vanessa,Moreno, Jose,Jacome-Lopez, Karina,Zentella-Dehesa, Alejandro,Juarez-Mendez, Sergio Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.5
There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.
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Synaptic Vesicle Protein 2 (SV2) Isoforms
Bandala, Cindy,Miliar-Garcia, A.,Mejia-Barradas, C.M.,Anaya-Ruiz, M.,Luna-Arias, J.P.,Bazan-Mendez, C.I.,Gomez-Lopez, M.,Juarez-Mendez, S.,Lara-Padilla, E. Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.10
New molecular markers of cancer had emerged with novel applications in cancer prevention and therapeutics, including for breast cancer of unknown causes, which has a high impact on the health of women worldwide. The purpose of this research was to detemine protein and mRNA expression of synaptic vesicle 2 (SV2) isoforms A, B and C in breast cancer cell lines. Cultured cell lines MDA-MB-231, SKBR3, T47D were lysed and their protein and mRNA expression analyzed by real-time PCR and western blot technique, respectively. SV2A, B proteins were identified in non-tumor (MCF-10A) and tumor cell lines (MDA-MB-231 and T47D) while SV2C only was found in the T47D cell line. Furthermore, the genomic expression was consistent with protein expression for a such cell line, but in MDA-MB-231 there was no SV2B genomic expression, and the SV2C mRNA and protein were not found in the non tumoral cell line. These findings suggest a possible cellular transdifferentiation to neural character in breast cancer, of possible relevance to cancer development, and point to possible use of SV2 as molecular marker and a vehicle for cancer treatment with botulinum toxin.
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