Browsing by Subject "Gene Expression Profiling"

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Open Access
Adjuvant autologous melanoma vaccine for macroscopic stage III disease: survival, biomarkers, and improved response to CTLA-4 blockade
(Hindawi Limited, 2016) Lotem, M.; Merims, S.; Frank, S.; Hamburger, T.; Nissan, A.; Kadouri, L.; Cohen, J.; Straussman, R.; Eisenberg, G.; Frankenburg, S.; Carmon, E.; Alaiyan, B.; Shneibaum, S.; Ayyildiz, Z. O.; Isbilen, M.; Senses, K. M.; Ron, I.; Steinberg, H.; Smith, Y.; Shiloni, E.; Gure, A. O.; Peretz, T.
Background. There is not yet an agreed adjuvant treatment for melanoma patients with American Joint Committee on Cancer stages III B and C. We report administration of an autologous melanoma vaccine to prevent disease recurrence. Patients and Methods. 126 patients received eight doses of irradiated autologous melanoma cells conjugated to dinitrophenyl and mixed with BCG. Delayed type hypersensitivity (DTH) response to unmodified melanoma cells was determined on the vaccine days 5 and 8. Gene expression analysis was performed on 35 tumors from patients with good or poor survival. Results. Median overall survival was 88 months with a 5-year survival of 54%. Patients attaining a strong DTH response had a significantly better (p = 0.0001) 5-year overall survival of 75% compared with 44% in patients without a strong response. Gene expression array linked a 50-gene signature to prognosis, including a cluster of four cancer testis antigens: CTAG2 (NY-ESO-2), MAGEA1, SSX1, and SSX4. Thirty-five patients, who received an autologous vaccine, followed by ipilimumab for progressive disease, had a significantly improved 3-year survival of 46% compared with 19% in nonvaccinated patients treated with ipilimumab alone (p = 0.007). Conclusion. Improved survival in patients attaining a strong DTH and increased response rate with subsequent ipilimumab suggests that the autologous vaccine confers protective immunity.
Open Access
Application of a customized pathway-focused microarray for gene expression profiling of cellular homeostasis upon exposure to nicotine in PC12 cells
(2004) Konu Ö.; Xu X.; Ma J.Z.; Kane J.; Wang J.; Shi, S.J.; Li, M.D.
Maintenance of cellular homeostasis is integral to appropriate regulation of cellular signaling and cell growth and division. In this study, we report the development and quality assessment of a pathway-focused microarray comprising genes involved in cellular homeostasis. Since nicotine is known to have highly modulatory effects on the intracellular calcium homeostasis, we therefore tested the applicability of the homeostatic pathway-focused microarray on the gene expression in PC-12 cells treated with 1 mM nicotine for 48 h relative to the untreated control cells. We first provided a detailed description of the focused array with respect to its gene and pathway content and then assessed the array quality using a robust regression procedure that allows for the exclusion of unreliable measurements while decreasing the number of false positives. As a result, the mean correlation coefficient between duplicate measurements of the arrays used in this study (control vs. nicotine treatment, three samples each) has increased from 0.974±0.017 to 0.995±0.002. Furthermore, we found that nicotine affected various structural and signaling components of the AKT/PKB signaling pathway and protein synthesis and degradation processes in PC-12 cells. Since modulation of intracellular calcium concentrations ([Ca2+]i) and phosphatidylinositol signaling are important in various biological processes such as neurotransmitter release and tissue pathogenesis including tumor formation, we expect that the homeostatic pathway-focused microarray potentially can be used for the identification of unique gene expression profiles in comparative studies of drugs of abuse and diverse environmental stimuli, such as starvation and oxidative stress. © 2003 Elsevier B.V. All rights reserved.
Open Access
Identification of endogenous reference genes for qRT-PCR analysis in normal matched breast tumor tissues
(Cognizant Communication Corporation, 2009) Gur-Dedeoglu, B.; Konu, O.; Bozkurt, B.; Ergul, G.; Seckin, S.; Yulug, I. G.
Quantitative gene expression measurements from tumor tissue are frequently compared with matched normal and/or adjacent tumor tissue expression for diagnostic marker gene selection as well as assessment of the degree of transcriptional deregulation in cancer. Selection of an appropriate reference gene (RG) or an RG panel, which varies depending on cancer type, molecular subtypes, and the normal tissues used for interindividual calibration, is crucial for the accurate quantification of gene expression. Several RG panels have been suggested in breast cancer for making comparisons among tumor subtypes, cell lines, and benign/malignant tumors. In this study, expression patterns of 15 widely used endogenous RGs (ACTB, TBP, GAPDH, SDHA, HPRT, HMBS, B2M, PPIA, GUSB, YWHAZ2, PGK1, RPLP0, PUM1, MRPL19, and RPL41), and three candidate genes that were selected through analysis of two independent microarray datasets (IL22RA1, TTC22, ZNF224) were determined in 23 primary breast tumors and their matched normal tissues using qRTPCR. Additionally, 18S rRNA, ACTB, and SDHA were tested using randomly primed cDNAs from 13 breast tumor pairs to assess the rRNA/mRNA ratio. The tumors exhibited significantly lower rRNA/mRNA ratio when compared to their normals, on average. The expression of the studied RGs in breast tumors did not exhibit differences in terms of grade, ER, or PR status. The stability of RGs was examined based on two different statistical models, namely GeNorm and NormFinder. Among the 18 tested endogenous reference genes, ACTB and SDHA were identified as the most suitable reference genes for the normalization of qRTPCR data in the analysis of normal matched tumor breast tissue pairs by both programs. In addition, the expression of the gelsolin (GSN) gene, a well-known downregulated target in breast tumors, was analyzed using the two most suitable genes and different RG combinations to validate their effectiveness as a normalization factor (NF). The GSN expression of the tumors used in this study was significantly lower than that of normals showing the effectivity of using ACTB and SDHA as suitable RGs in this set of tumor–normal tissue panel. The combinational use of the best performing two RGs (ACTB and SDHA) as a normalization factor can be recommended to minimize sample variability and to increase the accuracy and resolution of gene expression normalization in tumor–normal paired breast cancer qRT-PCR studies.
Open Access
Quantification of SLIT-ROBO transcripts in hepatocellular carcinoma reveals two groups of genes with coordinate expression
(BioMed Central, 2008) Avci, M. E.; Konu, O.; Yagci, T.
Background: SLIT-ROBO families of proteins mediate axon pathfinding and their expression is not solely confined to nervous system. Aberrant expression of SLIT-ROBO genes was repeatedly shown in a wide variety of cancers, yet data about their collective behavior in hepatocellular carcinoma (HCC) is missing. Hence, we quantified SLIT-ROBO transcripts in HCC cell lines, and in normal and tumor tissues from liver. Methods: Expression of SLIT-ROBO family members was quantified by real-time qRT-PCR in 14 HCC cell lines, 8 normal and 35 tumor tissues from the liver. ANOVA and Pearson's correlation analyses were performed in R environment, and different clinicopathological subgroups were pairwise compared in Minitab. Gene expression matrices of cell lines and tissues were analyzed by Mantel's association test. Results: Genewise hierarchical clustering revealed two subgroups with coordinate expression pattern in both the HCC cell lines and tissues: ROBO1, ROBO2, SLIT1 in one cluster, and ROBO4, SLIT2, SLIT3 in the other, respectively. Moreover, SLIT-ROBO expression predicted AFP-dependent subgrouping of HCC cell lines, but not that of liver tissues. ROBO1 and ROBO2 were significantly up-regulated, whereas SLIT3 was significantly down-regulated in cell lines with high-AFP background. When compared to normal liver tissue, ROBO1 was found to be significantly overexpressed, while ROBO4 was down-regulated in HCC. We also observed that ROBO1 and SLIT2 differentiated histopathological subgroups of liver tissues depending on both tumor staging and differentiation status. However, ROBO4 could discriminate poorly differentiated HCC from other subgroups. Conclusion: The present study is the first in comprehensive and quantitative evaluation of SLIT-ROBO family gene expression in HCC, and suggests that the expression of SLIT-ROBO genes is regulated in hepatocarcinogenesis. Our results implicate that SLIT-ROBO transcription profile is bi-modular in nature, and that each module shows intrinsic variability. We also provide quantitative evidence for potential use of ROBO1, ROBO4 and SLIT2 for prediction of tumor stage and differentiation status.