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

Multilocus analysis of SNP and metabolic data within a given pathway

BACKGROUND: Complex traits, which are under the influence of multiple and possibly interacting genes, have become a subject of new statistical methodological research. One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common multifactorial diseases and their association to different quantitative phenotypic traits. RESULTS: Two types of data from the same metabolic pathway were used in the analysis: categorical measurements of 18 SNPs; and quantitative measurements of plasma levels of several steroids and their precursors. Using the combinatorial partitioning method we tested various thresholds for each metabolic trait and each individual SNP locus. One SNP in CYP19, 3UTR, two SNPs in CYP1B1 (R48G and A119S) and one in CYP1A1 (T461N) were significantly differently distributed between the high and low level metabolic groups. The leave one out cross validation method showed that 6 SNPs in concert make 65% correct prediction of phenotype. Further we used pattern recognition, computing the p-value by Monte Carlo simulation to identify sets of SNPs and physiological characteristics such as age and weight that contribute to a given metabolic level. Since the SNPs detected by both methods reside either in the same gene (CYP1B1) or in 3 different genes in immediate vicinity on chromosome 15 (CYP19, CYP11 and CYP1A1) we investigated the possibility that they form intragenic and intergenic haplotypes, which may jointly account for a higher activity in the pathway. We identified such haplotypes associated with metabolic levels. CONCLUSION: The methods reported here may enable to study multiple low-penetrance genetic factors that together determine various quantitative phenotypic traits. Our preliminary data suggest that several genes coding for proteins involved in a common pathway, that happen to be located on common chromosomal areas and may form intragenic haplotypes, together account for a higher activity of the whole pathway

Expression of full-length p53 and its isoform Δp53 in breast carcinomas in relation to mutation status and clinical parameters

BACKGROUND: The tumor suppressor gene p53 (TP53) controls numerous signaling pathways and is frequently mutated in human cancers. Novel p53 isoforms suggest alternative splicing as a regulatory feature of p53 activity. RESULTS: In this study we have analyzed mRNA expression of both wild-type and mutated p53 and its respective Δp53 isoform in 88 tumor samples from breast cancer in relation to clinical parameters and molecular subgroups. Three-dimensional structure differences for the novel internally deleted p53 isoform Δp53 have been predicted. We confirmed the expression of Δp53 mRNA in tumors using quantitative real-time PCR technique. The mRNA expression levels of the two isoforms were strongly correlated in both wild-type and p53-mutated tumors, with the level of the Δp53 isoform being approximately 1/3 of that of the full-length p53 mRNA. Patients expressing mutated full-length p53 and non-mutated (wild-type) Δp53, "mutational hybrids", showed a slightly higher frequency of patients with distant metastasis at time of diagnosis compared to other patients with p53 mutations, but otherwise did not differ significantly in any other clinical parameter. Interestingly, the p53 wild-type tumors showed a wide range of mRNA expression of both p53 isoforms. Tumors with mRNA expression levels in the upper or lower quartile were significantly associated with grade and molecular subtypes. In tumors with missense or in frame mutations the mRNA expression levels of both isoforms were significantly elevated, and in tumors with nonsense, frame shift or splice mutations the mRNA levels were significantly reduced compared to those expressing wild-type p53. CONCLUSION: Expression of p53 is accompanied by the functionally different isoform Δp53 at the mRNA level in cell lines and human breast tumors. Investigations of "mutational hybrid" patients highlighted that wild-type Δp53 does not compensates for mutated p53, but rather may be associated with a worse prognosis. In tumors, both isoforms show strong correlations in different mutation-dependent mRNA expression patterns

Relationship between p53 and p27 expression following HER2 signaling

HER2, frequently associated with low p27 expression in breast tumors, when activated has been found to upmodulate p53 in tumor cells. The aim of this work was to investigate the role of p53 in the connection between HER2 and p27. Fifty-two breast tumor specimens, characterized for p53 mutations, were analyzed immunohistochemically (IHC) for HER2, p53 and p27 expression. p27, inversely associated with HER2, was found in 29% of tumors with IHC-negative mutated p53 versus 93% of tumors with accumulation of p53 protein and 59% with wild-type p53 (p=0.001), indicating a direct association between p53 and p27 expression. HER2-overexpressing cell lines carrying wild-type or null p53 protein, and treated with heregulin beta1 (HRG), were analyzed for expression and subcellular localization of p53 and p27. In HER2-overexpressing cells stimulated with HRG, p27 protein expression increased in parallel with p53 with no corresponding increase in p27 transcript. No p27 increase was observed in p53-null cells. Transfection with wild-type p53 restored p27 upmodulation in HRG-stimulated cells, indicating a crucial role of p53 in determining p27 upmodulation following HER2 activation. Together, our data demonstrate the crucial role of p53 in determining p27 upmodulation following HER2 activation. This could have implications in the response to Transtuzumab therapy

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