Experiments were designed to evaluate changes in the transcriptome (mRNA levels) in the ovulatory, luteinizing follicle of rhesus monkeys, using a controlled ovulation model that permits analysis of the naturally selected, dominant follicle at specific intervals (0, 12, 24 and 36 h) after exposure to an ovulatory (exogenous hCG) stimulus during the menstrual cycle. Total RNA was prepared from individual follicles (n= 4-8/timepoint), with an aliquot used for microarray analysis (Affymetrix Rhesus Macaque Genome Array) and the remainder applied to quantitative real-time PCR (q-PCR) assays. The microarray data from individual samples distinctly clustered according to timepoints, and ovulated follicles displayed markedly different expression patterns from unruptured follicles at 36 h. Between timepoint comparisons revealed profound changes in mRNA expression profiles. The dynamic pattern of mRNA expression for steroidogenic enzymes (CYP17A, CYP19A, HSD3B2, HSD11B1 and HSD11B2), steroidogenic acute regulatory protein (StAR) and gonadotrophin receptors [LH/choriogonadotrophin receptor (LHCGR), FSH receptor (FSHR)] as determined by microarray analysis correlated precisely with those from blinded q-PCR assays. Patterns of mRNA expression for epidermal-growth-factor-like factors (amphiregulin, epiregulin) and processes [hyaluronan synthase 2 (HAS2), tumor necrosis factor alpha-induced protein 6 (TNFAIP6)] implicated in cumulus-oocyte maturation/expansion were also comparable between assays. Thus, several mRNAs displayed the expected expression pattern for purported theca (e.g. CYP17A), granulosa (CYP19A, FSHR), cumulus (HAS2, TNFAIP6) cell and surface epithelium (HSD11B)-related genes in the rodent/primate pre-ovulatory follicle. This database will be of great value in analyzing molecular and cellular pathways associated with periovulatory events in the primate follicle (e.g. follicle rupture, luteinization, inflammatory response and angiogenesis), and for identifying novel gene products controlling mammalian fertility.
The majority of the biological effects of estrogens in the reproductive tract are mediated by estrogen receptor (ER)alpha, which regulates transcription by several mechanisms. Because the tissue-specific effects of some ERalpha ligands may be caused by tissue-specific transcriptional mechanisms of ERalpha, we aimed to identify the contribution of DNA recognition to these mechanisms in two clinically important target organs, namely uterus and liver. We used a genetic mouse model that dissects DNA binding-dependent vs. independent transcriptional regulation elicited by ERalpha. The EAAE mutant harbors amino acid exchanges at four positions of the DNA-binding domain (DBD) of ERalpha. This construct was knocked in the ERalpha gene locus to produce ERalpha((EAAE/EAAE)) mice devoid of a functional ERalpha DBD. The phenotype of the ERalpha((EAAE/EAAE)) mice resembles the general loss-of-function phenotype of alphaER knockout mutant mice with hypoplastic uteri, hemorrhagic ovaries, and impaired mammary gland development. In agreement with this phenotype, the expression pattern of the ERalpha((EAAE/EAAE)) mutant mice in liver obtained by genome-wide gene expression profiling supports the observation of a near-complete loss of estrogen-dependent gene regulation in comparison with the wild type. Further gene expression analyses to validate the results of the microarray data were performed by quantitative RT-PCR. The analyses indicate that both gene activation and repression by estrogen-bound ERalpha rely on an intact DBD in vivo.
BackgroundTreatment of non-small cell lung cancer with novel targeted therapies is a major unmet clinical need. Alternative splicing is a mechanism which generates diverse protein products and is of functional relevance in cancer.ResultsIn this study, a genome-wide analysis of the alteration of splicing patterns between lung cancer and normal lung tissue was performed. We generated an exon array data set derived from matched pairs of lung cancer and normal lung tissue including both the adenocarcinoma and the squamous cell carcinoma subtypes. An enhanced workflow was developed to reliably detect differential splicing in an exon array data set. In total, 330 genes were found to be differentially spliced in non-small cell lung cancer compared to normal lung tissue. Microarray findings were validated with independent laboratory methods for CLSTN1, FN1, KIAA1217, MYO18A, NCOR2, NUMB, SLK, SYNE2, TPM1, (in total, 10 events) and ADD3, which was analysed in depth. We achieved a high validation rate of 69%. Evidence was found that the activity of FOX2, the splicing factor shown to cause cancer-specific splicing patterns in breast and ovarian cancer, is not altered at the transcript level in several cancer types including lung cancer.ConclusionsThis study demonstrates how alternatively spliced genes can reliably be identified in a cancer data set. Our findings underline that key processes of cancer progression in NSCLC are affected by alternative splicing, which can be exploited in the search for novel targeted therapies.
Our protein and gene expression analyses do not support application of molecular classifiers for prediction of clinical outcome in current routine diagnostic as a basis for patient-orientated therapy in stage UICC II colon cancer. Further studies are needed to develop prognosis signatures applicable in patient care.
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