Project description:To date, a variety of studies have employed gene expression profiling to classify ovarian carcinomas in clinically relevant subtypes. These studies provided valuable first clues to molecular changes in ovarian cancer that might be exploited in new treatment strategies. However, most studies were of relatively limited size and the number of overlapping genes in the identified profiles was minimal. Although identification of gene expression profiles associated with clinically relevant subtypes in ovarian cancer is important, knowledge is now emerging rapidly on how genes interact in pathways, networks and complexes; this allows us to unravel those cellular pathways determining the biological behavior of ovarian cancer, that might be successfully targeted with drugs. The aim of our study was: 1) To develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, 2) to assess the association of pathways and transcription factors with overall survival, and 3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers. According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available data set of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent data set to assess the similarities with results from our own data set. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 vs. 41 months, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that comprised the overall survival profile were also able to discriminate between the two risk groups in the independent data set. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival of which 16 and 12 respectively were confirmed in the independent dataset. Our study provides new clues to genes, pathways and transcription factors which contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies. Keywords: Oncology/Gynecological Cancers, Genetics and Genomics/Cancer Genetics, Genetics and Genomics/Gene Expression, Genetics and Genomics/Genomics According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. Two randomly selected samples were hybridized together on the arrays for intensity-based instead of ratio-based analysis of the microarray data.
Project description:To date, a variety of studies have employed gene expression profiling to classify ovarian carcinomas in clinically relevant subtypes. These studies provided valuable first clues to molecular changes in ovarian cancer that might be exploited in new treatment strategies. However, most studies were of relatively limited size and the number of overlapping genes in the identified profiles was minimal. Although identification of gene expression profiles associated with clinically relevant subtypes in ovarian cancer is important, knowledge is now emerging rapidly on how genes interact in pathways, networks and complexes; this allows us to unravel those cellular pathways determining the biological behavior of ovarian cancer, that might be successfully targeted with drugs. The aim of our study was: 1) To develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, 2) to assess the association of pathways and transcription factors with overall survival, and 3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers. According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available data set of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent data set to assess the similarities with results from our own data set. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 vs. 41 months, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that comprised the overall survival profile were also able to discriminate between the two risk groups in the independent data set. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival of which 16 and 12 respectively were confirmed in the independent dataset. Our study provides new clues to genes, pathways and transcription factors which contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies. Keywords: Oncology/Gynecological Cancers, Genetics and Genomics/Cancer Genetics, Genetics and Genomics/Gene Expression, Genetics and Genomics/Genomics
Project description:Kynureninase is a member of a large family of catalytically diverse but structurally homologous pyridoxal 5'-phosphate (PLP) dependent enzymes known as the aspartate aminotransferase superfamily or alpha-family. The Homo sapiens and other eukaryotic constitutive kynureninases preferentially catalyze the hydrolytic cleavage of 3-hydroxy-l-kynurenine to produce 3-hydroxyanthranilate and l-alanine, while l-kynurenine is the substrate of many prokaryotic inducible kynureninases. The human enzyme was cloned with an N-terminal hexahistidine tag, expressed, and purified from a bacterial expression system using Ni metal ion affinity chromatography. Kinetic characterization of the recombinant enzyme reveals classic Michaelis-Menten behavior, with a Km of 28.3 +/- 1.9 microM and a specific activity of 1.75 micromol min-1 mg-1 for 3-hydroxy-dl-kynurenine. Crystals of recombinant kynureninase that diffracted to 2.0 A were obtained, and the atomic structure of the PLP-bound holoenzyme was determined by molecular replacement using the Pseudomonas fluorescens kynureninase structure (PDB entry 1qz9) as the phasing model. A structural superposition with the P. fluorescens kynureninase revealed that these two structures resemble the "open" and "closed" conformations of aspartate aminotransferase. The comparison illustrates the dynamic nature of these proteins' small domains and reveals a role for Arg-434 similar to its role in other AAT alpha-family members. Docking of 3-hydroxy-l-kynurenine into the human kynureninase active site suggests that Asn-333 and His-102 are involved in substrate binding and molecular discrimination between inducible and constitutive kynureninase substrates.
Project description:Transcriptional profiling of ovarian cancer spheroids reveals genes and related biological pathways associated with cisplatin resistance
Project description:As the evolution of miRNA genes has been found to be one of the important factors in formation of the modern type of man, we performed a comparative analysis of the evolution of miRNA genes in two archaic hominines, Homo sapiens neanderthalensis and Homo sapiens denisova, and elucidated the expression of their target mRNAs in bain.A comparative analysis of the genomes of primates, including species in the genus Homo, identified a group of miRNA genes having fixed substitutions with important implications for the evolution of Homo sapiens neanderthalensis and Homo sapiens denisova. The mRNAs targeted by miRNAs with mutations specific for Homo sapiens denisova exhibited enhanced expression during postnatal brain development in modern humans. By contrast, the expression of mRNAs targeted by miRNAs bearing variations specific for Homo sapiens neanderthalensis was shown to be enhanced in prenatal brain development.Our results highlight the importance of changes in miRNA gene sequences in the course of Homo sapiens denisova and Homo sapiens neanderthalensis evolution. The genetic alterations of miRNAs regulating the spatiotemporal expression of multiple genes in the prenatal and postnatal brain may contribute to the progressive evolution of brain function, which is consistent with the observations of fine technical and typological properties of tools and decorative items reported from archaeological Denisovan sites. The data also suggest that differential spatial-temporal regulation of gene products promoted by the subspecies-specific mutations in the miRNA genes might have occurred in the brains of Homo sapiens denisova and Homo sapiens neanderthalensis, potentially contributing to the cultural differences between these two archaic hominines.
Project description:Ovarian cancer is the fifth most common form of cancer in women in the United States. Epithelial ovarian cancer is the most common and is highly lethal. In 2014, there will be an estimated 21,980 new cases and 14,270 deaths from ovarian cancer in the United States. No major strides have been made to improve survival over the past decade. Ovarian cancer is notable for initial chemotherapy sensitivity (>75% response rates) using combination platinum and taxane chemotherapy following debulking surgery. However, eventually, the vast majority of these women (>75-80%) will have their cancer recur within 12 to 24 months after diagnosis and will die of progressively chemotherapy-resistant diseases. Transcription factors act as master switches of various biochemical pathways by regulating gene transcription. Large number of studies demonstrated the role of transcription factors in cancer development and progression. However, transcription factors involved in the pathogenesis of ovarian cancer have not been explored thoroughly. Therefore, we propose to using transcriptome profiling to generate a transcription factor gene signature for high-grade serous ovarian cancer.