IPI59: An Actionable Biomarker to Improve Treatment Response in Serous Ovarian Carcinoma Patients

Despite improvements in operative management and therapies, overall survival rates in advanced ovarian cancer have remained largely unchanged over the past three decades. Although it is possible to identify high-risk patients following surgery, the knowledge does not provide information about the genomic aberrations conferring risk, or the implications for treatment. To address these challenges, we developed an integrative pathway-index model and applied it to messenger RNA expression from 458 patients with serous ovarian carcinoma from the Cancer Genome Atlas project. The biomarker derived from this approach, IPI59, contains 59 genes from six pathways. As we demonstrate using independent datasets from six studies, IPI59 is strongly associated with overall and progression-free survival, and also identifies high-risk patients who may benefit from enhanced adjuvant therapy.

Metabolic gene profile in early human fetal heart development

The primitive cardiac tube starts beating 6-8 weeks post fertilization in the developing embryo. In order to describe normal cardiac development during late first and early second trimester in human fetuses this study used microarray and pathways analysis and created a corresponding 'normal' database. Fourteen fetal hearts from human fetuses between 10 and 18 weeks of gestational age (GA) were prospectively collected at the time of elective termination of pregnancy. RNA from recovered tissues was used for transcriptome analysis with Affymetrix 1.0 ST microarray chip. From the amassed data we investigated differences in cardiac development within the 10-18 GA period dividing the sample by GA in three groups: 10-12 (H1), 13-15 (H2) and 16-18 (H3) weeks. A fold change of 2 or above adjusted for a false discovery rate of 5% was used as initial cutoff to determine differential gene expression for individual genes. Test for enrichment to identify functional groups was carried out using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Array analysis correctly identified the cardiac specific genes, and transcripts reported to be differentially expressed were confirmed by qRT-PCR. Single transcript and Ontology analysis showed first trimester heart expression of myosin-related genes to be up-regulated >5-fold compared with second trimester heart. In contrast the second trimester hearts showed further gestation-related increases in many genes involved in energy production and cardiac remodeling. In conclusion, fetal heart development during the first trimester was dominated by heart-specific genes coding for myocardial development and differentiation. During the second trimester, transcripts related to energy generation and cardiomyocyte communication for contractile coordination/proliferation were more dominant. Transcripts related to fatty acid metabolism can be seen as early as 10 weeks and clearly increase as the heart matures. Retinol receptor and gamma-aminobutyric acid (GABA) receptor transcripts were detected, and have not been described previously in human fetal heart during this period. For the first time global gene expression of heart has been described in human samples to create a database of normal development to understand and compare with known abnormal fetal heart development.

Differential changes in gene expression in human brain during late first trimester and early second trimester of pregnancy

OBJECTIVE

This study aimed to describe brain development during the first (B1) and second trimester (B3) in human fetuses.

DESIGN

Ten brains from 10 to 18 weeks of gestational age (GA) were collected, and the RNA was used for transcriptome analysis (Affymetrix 1.0 ST microarray chip). Differences in brain development within 10 to 18 GA were investigated by dividing the sample into 10 to 12 (B1), 13 to 15(B2) and 16 to 18(B3) weeks. A fold change of 2 or above, with a false discovery rate of 5%, was used as cut-off to determine differential gene expression for individual genes. Quantitative real-time PCR was used to confirm differences. Tests for enrichment procedures (using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) were then used to identify functional groups of mRNA.

RESULTS

At 10 to 12 weeks, brains showed neuronal migration to be upregulated. From 10 to 18 weeks, brains showed genes coding for neuronal migration, differentiation and connectivity upregulated. ALDH1A1 and NPY genes, marker of spinal cord and striatum, were upregulated in B1 and B3 brains, respectively. Also, SLITRK6-HAS2 and CRYAB-PCDH18 genes for ear and eye sensory input were upregulated in B1.

CONCLUSIONS

For the first time, brain global gene expression was described in human samples. Period B1 was dominated by genes coding for neuronal migration, differentiation, programmed cell death and sensory organs. B3 was dominated by neuronal proliferation, branching and myelination. Creating such a database will allow comparison with abnormals in future studies.

On the utility of pooling biological samples in microarray experiments

Over 15% of the data sets catalogued in the Gene Expression Omnibus Database involve RNA samples that have been pooled before hybridization. Pooling affects data quality and inference, but the exact effects are not yet known because pooling has not been systematically studied in the context of microarray experiments. Here we report on the results of an experiment designed to evaluate the utility of pooling and the impact on identifying differentially expressed genes. We find that inference for most genes is not adversely affected by pooling, and we recommend that pooling be done when fewer than three arrays are used in each condition. For larger designs, pooling does not significantly improve inferences if few subjects are pooled. The realized benefits in this case do not outweigh the price paid for loss of individual specific information. Pooling is beneficial when many subjects are pooled, provided that independent samples contribute to multiple pools.