Optimization and evaluation of T7 based RNA linear amplification protocols for cDNA microarray analysis

BACKGROUND: T7 based linear amplification of RNA is used to obtain sufficient antisense RNA for microarray expression profiling. We optimized and systematically evaluated the fidelity and reproducibility of different amplification protocols using total RNA obtained from primary human breast carcinomas and high-density cDNA microarrays. RESULTS: Using an optimized protocol, the average correlation coefficient of gene expression of 11,123 cDNA clones between amplified and unamplified samples is 0.82 (0.85 when a virtual array was created using repeatedly amplified samples to minimize experimental variation). Less than 4% of genes show changes in expression level by 2-fold or greater after amplification compared to unamplified samples. Most changes due to amplification are not systematic both within one tumor sample and between different tumors. Amplification appears to dampen the variation of gene expression for some genes when compared to unamplified poly(A)(+) RNA. The reproducibility between repeatedly amplified samples is 0.97 when performed on the same day, but drops to 0.90 when performed weeks apart. The fidelity and reproducibility of amplification is not affected by decreasing the amount of input total RNA in the 0.3–3 micrograms range. Adding template-switching primer, DNA ligase, or column purification of double-stranded cDNA does not improve the fidelity of amplification. The correlation coefficient between amplified and unamplified samples is higher when total RNA is used as template for both experimental and reference RNA amplification. CONCLUSION: T7 based linear amplification reproducibly generates amplified RNA that closely approximates original sample for gene expression profiling using cDNA microarrays

Intratumoural mRNA expression of genes from the oestradiol metabolic pathway and clinical and histopathological parameters of breast cancer

INTRODUCTION: The expression of the oestrogen receptor (ER) is one of the more important clinical parameters of breast cancer. However, the relationship between the ER and its ligand, oestradiol, and the enzymes that synthesise it are not well understood. The expression of mRNA transcripts of members of the oestradiol metabolic and signalling pathways including the ER was studied in detail. METHOD: mRNA transcripts for aromatase (CYP19), 17-β-hydroxysteroid dehydrogenase I, 17-β-hydroxysteroid dehydrogenase II, ERα, ERβ, steroid sulfatase (STS), oestradiol sulfotransferase (EST), cyclin D(1 )(CYCLD1) and ERBB2 were fluorometrically quantified by competitive RT-PCR using an internal standard in 155 breast carcinomas. In addition, the transcripts of CYP19 were analysed for alternative splicing/usage of exon 1 and an alternative poly A tail. RESULTS: A great variability of expression was observed, ranging from 0 to 2376 amol/mg RNA. The highest levels were observed for STS and EST, and the lowest levels (close to zero) were observed for the 17-β-hydroxysteroid dehydrogenase isoenzymes. The levels of mRNA expression were analysed with respect to clinical and histopathological parameters as well as for disease-free survival. High correlation of the mRNA expression of STS, EST and 17-β-hydroxysteroid dehydrogenase in the tumours suggested a common regulation, possibly by their common metabolite (oestradiol). Hierarchical clustering analysis in the 155 patients resulted in two main clusters, representing the ERα-negative and ERα-positive breast cancer cases. The mRNA expression of the oestradiol metabolising enzymes did not follow the expression of the ERα in all cases, leading to the formation of several subclasses of tumours. Patients with no expression of CYP19 and patients with high levels of expression of STS had significantly shorter disease-free survival time (P > 0.0005 and P < 0.03, respectively). Expression of ERβ mRNA was a better prognostic factor than that of ERα in this material. CONCLUSION: Our results indicate the importance of CYP19 and the enzymes regulating the oestrone sulfate metabolism as factors of disease-free survival in breast cancer, in addition to the well-known factors ER and ERBB2

PathTracer: High-sensitivity detection of differential pathway activity in tumours

Abstract: Gene expression profiling of tumours is an important source of information for cancer patient stratification. Detecting subtle alterations of gene expression remains a challenge, however. Here, we propose a novel tool for high-sensitivity detection of differential pathway activity in tumours. For a pathway defined by a collection of genes, the samples are projected onto a low-dimensional manifold in the subspace spanned by those genes. For each sample, a score is next found by calculating the distance between each projected sample and the projection of a subgroup of reference samples. Depending on the aim of the analysis and the available data, the reference samples may represent e.g. normal tissue or tumour samples with a particular genotype or phenotype. The proposed tool, PathTracer, is demonstrated on gene expression data from 1952 invasive breast cancer samples, 10 DCIS, 9 benign samples and 144 tumour adjacent normal breast tissue samples. PathTracer scores are shown to predict survival, clinical subtypes, cellular proliferation and genomic instability. Furthermore, predictions are shown to outperform those obtained with other comparable methods

Intratumor heterogeneity defines treatment-resistant HER2+ breast tumors.

Targeted therapy for patients with HER2-positive (HER2+) breast cancer has improved overall survival, but many patients still suffer relapse and death from the disease. Intratumor heterogeneity of both estrogen receptor (ER) and HER2 expression has been proposed to play a key role in treatment failure, but little work has been done to comprehensively study this heterogeneity at the single-cell level. In this study, we explored the clinical impact of intratumor heterogeneity of ER protein expression, HER2 protein expression, and HER2 gene copy number alterations. Using combined immunofluorescence and in situ hybridization on tissue sections followed by a validated computational approach, we analyzed more than 13 000 single tumor cells across 37 HER2+ breast tumors. The samples were taken both before and after neoadjuvant chemotherapy plus HER2-targeted treatment, enabling us to study tumor evolution as well. We found that intratumor heterogeneity for HER2 copy number varied substantially between patient samples. Highly heterogeneous tumors were associated with significantly shorter disease-free survival and fewer long-term survivors. Patients for which HER2 characteristics did not change during treatment had a significantly worse outcome. This work shows the impact of intratumor heterogeneity in molecular diagnostics for treatment selection in HER2+ breast cancer patients and the power of computational scoring methods to evaluate in situ molecular markers in tissue biopsies

Commonly used medications and endometrial cancer survival: a population-based cohort study.

Genomic Identification of Significant Targets (GISTIC) outputs for Circular Binary Segmentation (CBS) - or Piecewise Constant Fit (PCF) - segmented input data. The number of peaks attained by GISTIC on the y-axis is plotted against the two changing parameters α for CBS and γ for PCF on the x-axis. GISTIC peaks of amplification applying CBS-segmented data are illustrated in pink and PCF-segmented data in red, respectively. Deletion peaks are colored in green for CBS-segmented input data and in blue for PCF-segmented data. From top to bottom are shown GISTIC focal peaks for breast, ovarian, endometrial, and cervical cancers, to the left for PCF-segmented input data (A, C, E, and G) and to the right for CBS-segmented input data (B, D, F and H), respectively. For further analysis are the selected α and γ highlighted with a colored square. (PDF 362 kb

Lysophosphatidic Acid-Induced Transcriptional Profile Represents Serous Epithelial Ovarian Carcinoma and Worsened Prognosis

BACKGROUND:Lysophosphatidic acid (LPA) governs a number of physiologic and pathophysiological processes. Malignant ascites fluid is rich in LPA, and LPA receptors are aberrantly expressed by ovarian cancer cells, implicating LPA in the initiation and progression of ovarian cancer. However, there is an absence of systematic data critically analyzing the transcriptional changes induced by LPA in ovarian cancer. METHODOLOGY AND PRINCIPAL FINDINGS:In this study, gene expression profiling was used to examine LPA-mediated transcription by exogenously adding LPA to human epithelial ovarian cancer cells for 24 h to mimic long-term stimulation in the tumor microenvironment. The resultant transcriptional profile comprised a 39-gene signature that closely correlated to serous epithelial ovarian carcinoma. Hierarchical clustering of ovarian cancer patient specimens demonstrated that the signature is associated with worsened prognosis. Patients with LPA-signature-positive ovarian tumors have reduced disease-specific and progression-free survival times. They have a higher frequency of stage IIIc serous carcinoma and a greater proportion is deceased. Among the 39-gene signature, a group of seven genes associated with cell adhesion recapitulated the results. Out of those seven, claudin-1, an adhesion molecule and phenotypic epithelial marker, is the only independent biomarker of serous epithelial ovarian carcinoma. Knockdown of claudin-1 expression in ovarian cancer cells reduces LPA-mediated cellular adhesion, enhances suspended cells and reduces LPA-mediated migration. CONCLUSIONS:The data suggest that transcriptional events mediated by LPA in the tumor microenvironment influence tumor progression through modulation of cell adhesion molecules like claudin-1 and, for the first time, report an LPA-mediated expression signature in ovarian cancer that predicts a worse prognosis