Functional genomics in translational cancer research: Focus on breast cancer

Conventional molecular and genetic methods for studying cancer are limited to the analysis of one locus at a time. A cluster of genes that are regulated together can be identified by DNA microarray, and the functional relationships can uncover new aspects of cancer biology. Breast cancer can be used to provide a model to demonstrate the current approaches to the molecular analysis of cancer. Meta-analysis is an important tool for the identification and validation of differentially expressed genes to increase power in clinical and biological studies across different sets of data. Recently, meta-analysis approaches have been applied to large collections of microarray datasets to investigate molecular commonalities of multiple cancer types not only to find the common molecular pathways in tumour development but also to compare the individual datasets to other cancer datasets to identify new sets of genes. Several investigators agree that microarray results should be validated. One commonly used method is quantitative reverse transcription PCR (qRT-PCR) to validate the expression profiles of the target genes obtained through microarray experiments. qRT-PCR is attractive for clinical use, since it can be automated and performed on fresh or archived formalin-fixed, paraffin-embedded tissue samples. The outcome of these analyses might accelerate the application of basic research findings into daily clinical practice through translational research and may have an impact on foreseeing the clinical outcome, predicting tumour response to specific therapy, identification of new prognostic biomarkers, discovering targets for the development of novel therapies and providing further insights into tumour biology. © The Author 2008. Published by Oxford University Press

Relative expression of rRNA transcripts and 45S rDNA promoter methylation status are dysregulated in tumors in comparison with matched-normal tissues in breast cancer

Ribosomal RNA (rRNA) expression, one of the most important factors regulating ribosome production, is primarily controlled by a CG-rich 45S rDNA promoter. However, the DNA methylation state of the 45S rDNA promoter, as well as its effect on rRNA gene expression in types of human cancers is controversial. In the present study we analyzed the methylation status of the rDNA promoter (-380 to +53 bp) as well as associated rRNA expression levels in breast cancer cell lines and breast tumor-normal tissue pairs. We found that the aforementioned regulatory region was extensively methylated (74-96%) in all cell lines and in 68% (13/19 tumor-normal pairs) of the tumors. Expression levels of rRNA transcripts 18S, 28S, 5.8S and 45S external transcribed spacer (45S ETS) greatly varied in the breast cancer cell lines regardless of their methylation status. Analyses of rRNA transcript expression levels in the breast tumor and normal matched tissues showed no significant difference when normalized with TBP. On the other hand, using the geometric mean of the rRNA expression values (GM-rRNA) as reference enabled us to identify significant changes in the relative expression of rRNAs in the tissue samples. We propose GM-rRNA normalization as a novel strategy to analyze expression differences between rRNA transcripts. Accordingly, the 18S rRNA/GM-rRNA ratio was significantly higher whereas the 5.8S rRNA/GM-rRNA ratio was significantly lower in breast tumor samples than this ratio in the matched normal samples. Moreover, the 18S rRNA/GM-rRNA ratio was negatively correlated with the 45S rDNA promoter methylation level in the normal breast tissue samples, yet not in the breast tumors. Significant correlations observed between the expression levels of rRNA transcripts in the normal samples were lost in the tumor samples. We showed that the expression of rRNA transcripts may not be based solely on promoter methylation. Carcinogenesis may cause dysregulation of the correlation between spliced rRNA expression levels, possibly due to changes in rRNA processing, which requires further investigation

Identification of endogenous reference genes for qRT-PCR analysis in normal matched breast tumor tissues

Quantitative gene expression measurements from tumor tissue are frequently compared with matched normal and/or adjacent tumor tissue expression for diagnostic marker gene selection as well as assessment of the degree of transcriptional deregulation in cancer. Selection of an appropriate reference gene (RG) or an RG panel, which varies depending on cancer type, molecular subtypes, and the normal tissues used for interindividual calibration, is crucial for the accurate quantification of gene expression. Several RG panels have been suggested in breast cancer for making comparisons among tumor subtypes, cell lines, and benign/malignant tumors. In this study, expression patterns of 15 widely used endogenous RGs (ACTB, TBP, GAPDH, SDHA, HPRT, HMBS, B2M, PPIA, GUSB, YWHAZ2, PGK1, RPLP0, PUM1, MRPL19, and RPL41), and three candidate genes that were selected through analysis of two independent microarray datasets (IL22RA1, TTC22, ZNF224) were determined in 23 primary breast tumors and their matched normal tissues using qRT-PCR. Additionally, 18S rRNA, ACTB, and SDHA were tested using randomly primed cDNAs from 13 breast tumor pairs to assess the rRNA/mRNA ratio. The tumors exhibited significantly lower rRNA/mRNA ratio when compared to their normals, on average. The expression of the studied RGs in breast tumors did not exhibit differences in terms of grade, ER, or PR status. The stability of RGs was examined based on two different statistical models, namely GeNorm and NormFinder. Among the 18 tested endogenous reference genes, ACTB and SDHA were identified as the most suitable reference genes for the normalization of qRT-PCR data in the analysis of normal matched tumor breast tissue pairs by both programs. In addition, the expression of the gelsolin (GSN) gene, a well-known downregulated target in breast tumors, was analyzed using the two most suitable genes and different RG combinations to validate their effectiveness as a normalization factor (NF). The GSN expression of the tumors used in this study was significantly lower than that of normals showing the effectivity of using ACTB and SDHA as suitable RGs in this set of tumor-normal tissue panel. The combinational use of the best performing two RGs (ACTB and SDHA) as a normalization factor can be recommended to minimize sample variability and to increase the accuracy and resolution of gene expression normalization in tumor-normal paired breast cancer qRT-PCR studies. Copyright © 2009 Cognizant Comm. Corp. All rights reserved

Lack of association between the MDM2-SNP309 polymorphism and breast cancer risk

Background: A T-to-G polymorphism (SNP309) at the promoter region of MDM2 has been recently reported to extend the Sp1 binding site that positively regulates the MDM2 transcription level and consequently, its expression level. MDM2 is the negative regulator of p53 tumor suppressor protein and elevated levels of MDM2 hamper the stress response driven by the p53 pathway. Whether MDM2-SNP309 was associated with breast cancer as a predisposing factor was investigated. Patients and Methods: A case-control study of 223 females diagnosed with breast cancer and 149 female controls sampled from the Turkish population was carried out and the T/G MDM2-SNP309 genotype of participants was determined. Results: There was no significant association of the G/G or G/T genotypes with breast cancer risk (odds ratio (OR) 1.14, 95% confidence interval (CI) 0.59-2.22, and OR 1.20, 95% CI 0.67-2.12, respectively). Stratification of the data for onset age or for menopausal status at the time of diagnosis also revealed no association for either group

A ranking-based meta-analysis reveals let-7 family as a meta-signature for grade classification in breast cancer

Breast cancer is one of the most important causes of cancer-related deaths worldwide in women. In addition to gene expression studies, the progressing work in the miRNA area including miRNA microarray studies, brings new aspects to the research on the cancer development and progression. Microarray technology has been widely used to find new biomarkers in research and many transcriptomic microarray studies are available in public databases. In this study, the breast cancer miRNA and mRNA microarray studies were collected according to the availability of their data and clinical information, and combined by a newly developed ranking-based meta-analysis approach to find out candidate miRNA biomarkers (meta-miRNAs) that classify breast cancers according to their grades and explain the relation between miRNAs and mRNAs. This approach provided meta-miRNAs specific to breast cancer grades, pointing out let-7 family members as grade classifiers. The qRTPCR studies performed with independent breast tumors confirmed the potential biomarker role of let-7 family members (meta-miRNAs). The concordance between the meta-mRNAs and miRNA target genes specific to tumor grade (common genes) supported the idea of mRNAs as miRNA targets. The pathway analysis results showed that most of the let-7 family miRNA targets, and also common genes, were significantly taking part in cancer-related pathways. The qRT-PCR studies, together with bioinformatic analyses, confirmed the results of meta-analysis approach, which is dynamic and allows combining datasets from different platforms. © 2015 Oztemur et al

Inhibition of focal adhesion kinase with her-2 targeted antibody pertuzumab (Omnitarg®, 2C4) in breast cancer cells

Pertuzumab (Omnitarg®, 2C4) is a recombinant humanized monoclonal antibody targeted to extracellular region of HER-2. Previous results proved the inhibitory effect of Pertuzumab on the survival of breast cancer cells via MAPK and Akt pathway. Focal adhesion kinase (FAK) regulates multiple cellular processes including growth, differentiation, adhesion, motility and apoptosis. Here, we aimed to investigate the effects of Pertuzumab on ligand activated total FAK expression and phosphorylation in the HER-2 overexpressing BT-474 breast cancer cell line. Heregulin was used for ligand activation. We have found that FAK expression and phosphorylation were inhibited in with Pertuzumab in breast cancer cells

Combined metabolic activators improve cognitive functions in Alzheimer’s disease patients: a randomised, double-blinded, placebo-controlled phase-II trial

Background: Alzheimer’s disease (AD) is associated with metabolic abnormalities linked to critical elements of neurodegeneration. We recently administered\ua0combined metabolic activators (CMA) to the AD rat model and observed that CMA improves the AD-associated histological parameters in the animals. CMA promotes mitochondrial fatty acid uptake from the cytosol, facilitates fatty acid oxidation in the mitochondria, and alleviates oxidative stress. Methods: Here, we designed a randomised, double-blinded, placebo-controlled phase-II clinical trial and studied the effect of CMA administration on the global metabolism of AD patients. One-dose CMA included 12.35\ua0g L-serine (61.75%), 1\ua0g nicotinamide riboside (5%), 2.55\ua0g\ua0N-acetyl-L-cysteine (12.75%), and 3.73\ua0g L-carnitine tartrate (18.65%). AD patients received one dose of CMA or placebo daily during the first 28\ua0days and twice daily between day 28 and day 84. The primary endpoint was the difference in the cognitive function and daily living activity scores between the placebo and the treatment arms. The secondary aim of this study was to evaluate the safety and tolerability of CMA. A comprehensive plasma metabolome and proteome analysis was also performed to evaluate the efficacy of the CMA in AD patients. Results: We showed a significant decrease of AD Assessment Scale-cognitive subscale (ADAS-Cog) score on day 84 vs day 0 (P = 0.00001, 29% improvement) in the CMA group. Moreover, there was a significant decline (P = 0.0073) in ADAS-Cog scores (improvement of cognitive functions) in the\ua0CMA compared to the placebo group in patients with higher ADAS-Cog scores. Improved cognitive functions in AD patients were supported by the relevant alterations in the hippocampal volumes and cortical thickness based on imaging analysis. Moreover, the plasma levels of proteins and metabolites associated with NAD + and glutathione metabolism were significantly improved after CMA treatment. Conclusion: Our results indicate that treatment of AD patients with CMA can lead to enhanced cognitive functions and improved clinical parameters associated with phenomics, metabolomics, proteomics and imaging analysis. Trial registration\ua0ClinicalTrials.gov NCT04044131 Registered 17 July 2019, https://clinicaltrials.gov/ct2/show/NCT04044131

Lack of association between RNASEL Arg462Gln variant and the risk of breast cancer

Background: The RNASEL G1385A variant was recently found to be implicated in the development of prostate cancer. Considering the function of RNase L and the pleiotropic effects of mutations associated with cancer, we sought to investigate whether the RNASEL G1385A variant is a risk factor for breast cancer. Patients and Methods: A total of 453 breast cancer patients and 382 age- and sex-matched controls from Greece and Turkey were analyzed. Genotyping for the RNASEL G1385A variant was performed using an Amplification Refractory Mutation System (ARMS). Results: Statistical evaluation of the RNASEL G1385A genotype distribution among breast cancer patients and controls revealed no significant association between the presence of the risk genotype and the occurrence of breast cancer. Conclusion: Although an increasing number of studies report an association between the RNASEL G1385A variant and prostate cancer risk, this variant does not appear to be implicated in the development of breast cancer

The Ability to Generate Senescent Progeny as a Mechanism Underlying Breast Cancer Cell Heterogeneity

Background Breast cancer is a remarkably heterogeneous disease. Luminal, basal-like, "normal-like", and ERBB2+ subgroups were identified and were shown to have different prognoses. The mechanisms underlying this heterogeneity are poorly understood. In our study, we explored the role of cellular differentiation and senescence as a potential cause of heterogeneity. Methodology/Principal Findings A panel of breast cancer cell lines, isogenic clones, and breast tumors were used. Based on their ability to generate senescent progeny under low-density clonogenic conditions, we classified breast cancer cell lines as senescent cell progenitor (SCP) and immortal cell progenitor (ICP) subtypes. All SCP cell lines expressed estrogen receptor (ER). Loss of ER expression combined with the accumulation of p21Cip1 correlated with senescence in these cell lines. p21Cip1 knockdown, estrogen-mediated ER activation or ectopic ER overexpression protected cells against senescence. In contrast, tamoxifen triggered a robust senescence response. As ER expression has been linked to luminal differentiation, we compared the differentiation status of SCP and ICP cell lines using stem/progenitor, luminal, and myoepithelial markers. The SCP cells produced CD24+ or ER+ luminal-like and ASMA+ myoepithelial-like progeny, in addition to CD44+ stem/progenitor-like cells. In contrast, ICP cell lines acted as differentiation-defective stem/progenitor cells. Some ICP cell lines generated only CD44+/CD24-/ER-/ASMA- progenitor/stem-like cells, and others also produced CD24+/ER- luminal-like, but not ASMA+ myoepithelial-like cells. Furthermore, gene expression profiles clustered SCP cell lines with luminal A and "normal-like" tumors, and ICP cell lines with luminal B and basal-like tumors. The ICP cells displayed higher tumorigenicity in immunodeficient mice. Conclusions/Significance Luminal A and "normal-like" breast cancer cell lines were able to generate luminal-like and myoepithelial-like progeny undergoing senescence arrest. In contrast, luminal B/basal-like cell lines acted as stem/progenitor cells with defective differentiation capacities. Our findings suggest that the malignancy of breast tumors is directly correlated with stem/progenitor phenotypes and poor differentiation potential. © 2010 Mumcuoglu et al