Francesca Cordero

The molecular landscape of colorectal cancer cell lines unveils clinically actionable kinase targets

The development of molecularly targeted anticancer agents relies on large panels of tumour-specific preclinical models closely recapitulating the molecular heterogeneity observed in patients. Here we describe the mutational and gene expression analyses of 151 colorectal cancer (CRC) cell lines. We find that the whole spectrum of CRC molecular and transcriptional subtypes, previously defined in patients, is represented in this cell line compendium. Transcriptional outlier analysis identifies RAS/BRAF wild-type cells, resistant to EGFR blockade, functionally and pharmacologically addicted to kinase genes including ALK, FGFR2, NTRK1/2 and RET. The same genes are present as expression outliers in CRC patient samples. Genomic rearrangements (translocations) involving the ALK and NTRK1 genes are associated with the overexpression of the corresponding proteins in CRC specimens. The approach described here can be used to pinpoint CRCs with exquisite dependencies to individual kinases for which clinically approved drugs are already available.

Selection of suitable reference genes for accurate normalization of gene expression profile studies in non-small cell lung cancer

BackgroundIn real-time RT quantitative PCR (qPCR) the accuracy of normalized data is highly dependent on the reliability of the reference genes (RGs). Failure to use an appropriate control gene for normalization of qPCR data may result in biased gene expression profiles, as well as low precision, so that only gross changes in expression level are declared statistically significant or patterns of expression are erroneously characterized. Therefore, it is essential to determine whether potential RGs are appropriate for specific experimental purposes. Aim of this study was to identify and validate RGs for use in the differentiation of normal and tumor lung expression profiles.MethodsA meta-analysis of lung cancer transcription profiles generated with the GeneChip technology was used to identify five putative RGs. Their consistency and that of seven commonly used RGs was tested by using Taqman probes on 18 paired normal-tumor lung snap-frozen specimens obtained from non-small-cell lung cancer (NSCLC) patients during primary curative resection.ResultsThe 12 RGs displayed showed a wide range of Ct values: except for rRNA18S (mean 9.8), the mean values of all the commercial RGs and ESD ranged from 19 to 26, whereas those of the microarray-selected RGs (BTF-3, YAP1, HIST1H2BC, RPL30) exceeded 26. RG expression stability within sample populations and under the experimental conditions (tumour versus normal lung specimens) was evaluated by: (1) descriptive statistic; (2) equivalence test; (3) GeNorm applet. All these approaches indicated that the most stable RGs were POLR2A, rRNA18S, YAP1 and ESD.ConclusionThese data suggest that POLR2A, rRNA18S, YAP1 and ESD are the most suitable RGs for gene expression profile studies in NSCLC. Furthermore, they highlight the limitations of commercial RGs and indicate that meta-data analysis of genome-wide transcription profiling studies may identify new RGs.In real-time RT quantitative PCR (qPCR) the accuracy of normalized data is highly dependent on the reliability of the reference genes (RGs). Failure to use an appropriate control gene for normalization of qPCR data may result in biased gene expression profiles, as well as low precision, so that only gross changes in expression level are declared statistically significant or patterns of expression are erroneously characterized. Therefore, it is essential to determine whether potential RGs are appropriate for specific experimental purposes. Aim of this study was to identify and validate RGs for use in the differentiation of normal and tumor lung expression profiles. A meta-analysis of lung cancer transcription profiles generated with the GeneChip technology was used to identify five putative RGs. Their consistency and that of seven commonly used RGs was tested by using Taqman probes on 18 paired normal-tumor lung snap-frozen specimens obtained from non-small-cell lung cancer (NSCLC) patients during primary curative resection. The 12 RGs displayed showed a wide range of Ct values: except for rRNA18S (mean 9.8), the mean values of all the commercial RGs and ESD ranged from 19 to 26, whereas those of the microarray-selected RGs (BTF-3, YAP1, HIST1H2BC, RPL30) exceeded 26. RG expression stability within sample populations and under the experimental conditions (tumour versus normal lung specimens) was evaluated by: (1) descriptive statistic; (2) equivalence test; (3) GeNorm applet. All these approaches indicated that the most stable RGs were POLR2A, rRNA18S, YAP1 and ESD. These data suggest that POLR2A, rRNA18S, YAP1 and ESD are the most suitable RGs for gene expression profile studies in NSCLC. Furthermore, they highlight the limitations of commercial RGs and indicate that meta-data analysis of genome-wide transcription profiling studies may identify new RGs.

Microarray data analysis and mining approaches.

Microarray based transcription profiling is now a consolidated methodology and has widespread use in areas such as pharmacogenomics, diagnostics and drug target identification. Large-scale microarray studies are also becoming crucial to a new way of conceiving experimental biology. A main issue in microarray transcription profiling is data analysis and mining. When microarrays became a methodology of general use, considerable effort was made to produce algorithms and methods for the identification of differentially expressed genes. More recently, the focus has switched to algorithms and database development for microarray data mining. Furthermore, the evolution of microarray technology is allowing researchers to grasp the regulative nature of transcription, integrating basic expression analysis with mRNA characteristics, i.e. exon-based arrays, and with DNA characteristics, i.e. comparative genomic hybridization, single nucleotide polymorphism, tiling and promoter structure. In this article, we will review approaches used to detect differentially expressed genes and to link differential expression to specific biological functions.

State-of-the-art fusion-finder algorithms sensitivity and specificity.

Background. Gene fusions arising from chromosomal translocations have been implicated in cancer. RNA-seq has the potential to discover such rearrangements generating functional proteins (chimera/fusion). Recently, many methods for chimeras detection have been published. However, specificity and sensitivity of those tools were not extensively investigated in a comparative way. Results. We tested eight fusion-detection tools (FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse, Bellerophontes, ChimeraScan, and TopHat-fusion) to detect fusion events using synthetic and real datasets encompassing chimeras. The comparison analysis run only on synthetic data could generate misleading results since we found no counterpart on real dataset. Furthermore, most tools report a very high number of false positive chimeras. In particular, the most sensitive tool, ChimeraScan, reports a large number of false positives that we were able to significantly reduce by devising and applying two filters to remove fusions not supported by fusion junction-spanning reads or encompassing large intronic regions. Conclusions. The discordant results obtained using synthetic and real datasets suggest that synthetic datasets encompassing fusion events may not fully catch the complexity of RNA-seq experiment. Moreover, fusion detection tools are still limited in sensitivity or specificity; thus, there is space for further improvement in the fusion-finder algorithms.

Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space

For the vast majority of species – including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and second-generation sequencing technology to efficiently approach denovo selective genome sequencing. We show that combinatorial pooling is a cost-effective and practical alternative to exhaustive DNA barcoding when preparing sequencing libraries for hundreds or thousands of DNA samples, such as in this case gene-bearing minimum-tiling-path BAC clones. The novelty of the protocol hinges on the computational ability to efficiently compare hundred millions of short reads and assign them to the correct BAC clones (deconvolution) so that the assembly can be carried out clone-by-clone. Experimental results on simulated data for the rice genome show that the deconvolution is very accurate, and the resulting BAC assemblies have high quality. Results on real data for a gene-rich subset of the barley genome confirm that the deconvolution is accurate and the BAC assemblies have good quality. While our method cannot provide the level of completeness that one would achieve with a comprehensive whole-genome sequencing project, we show that it is quite successful in reconstructing the gene sequences within BACs. In the case of plants such as barley, this level of sequence knowledge is sufficient to support critical end-point objectives such as map-based cloning and marker-assisted breeding.

Genome-wide activity of unliganded estrogen receptor-α in breast cancer cells

Significance Estrogen receptor-α (ERα) is a key protein in breast cancer and treatments targeting ERα are among the most widely used and effective in clinics. Although the role of estrogen-stimulated ERα in breast cancer has been exhaustively described, the functions of ERα in the absence of estrogen is hill-defined. In this work, we show that ERα binds extensively to the genome of breast cancer cells in the absence of estrogen, where it regulates the expression of hundreds of genes endowed with developmental functions. Our data suggest that ERα has a fundamental role in the homeostasis of luminal epithelial cells also when estrogen is ablated physiologically or pharmacologically. Estrogen receptor-α (ERα) has central role in hormone-dependent breast cancer and its ligand-induced functions have been extensively characterized. However, evidence exists that ERα has functions that are independent of ligands. In the present work, we investigated the binding of ERα to chromatin in the absence of ligands and its functions on gene regulation. We demonstrated that in MCF7 breast cancer cells unliganded ERα binds to more than 4,000 chromatin sites. Unexpectedly, although almost entirely comprised in the larger group of estrogen-induced binding sites, we found that unliganded-ERα binding is specifically linked to genes with developmental functions, compared with estrogen-induced binding. Moreover, we found that siRNA-mediated down-regulation of ERα in absence of estrogen is accompanied by changes in the expression levels of hundreds of coding and noncoding RNAs. Down-regulated mRNAs showed enrichment in genes related to epithelial cell growth and development. Stable ERα down-regulation using shRNA, which caused cell growth arrest, was accompanied by increased H3K27me3 at ERα binding sites. Finally, we found that FOXA1 and AP2γ binding to several sites is decreased upon ERα silencing, suggesting that unliganded ERα participates, together with other factors, in the maintenance of the luminal-specific cistrome in breast cancer cells.

An integrated approach of immunogenomics and bioinformatics to identify new Tumor Associated Antigens (TAA) for mammary cancer immunological prevention

BackgroundNeoplastic transformation is a multistep process in which distinct gene products of specific cell regulatory pathways are involved at each stage. Identification of overexpressed genes provides an unprecedented opportunity to address the immune system against antigens typical of defined stages of neoplastic transformation. HER-2/neu/ERBB2 (Her2) oncogene is a prototype of deregulated oncogenic protein kinase membrane receptors. Mice transgenic for rat Her2 (BALB-neuT mice) were studied to evaluate the stage in which vaccines can prevent the onset of Her2 driven mammary carcinomas. As Her2 is not overexpressed in all mammary carcinomas, definition of an additional set of tumor associated antigens (TAAs) expressed at defined stages by most breast carcinomas would allow a broader coverage of vaccination. To address this question, a meta-analysis was performed on two transcription profile studies [1, 2] to identify a set of new TAA targets to be used instead of or in conjunction with Her2.ResultsThe five TAAs identified (Tes, Rcn2, Rnf4, Cradd, Galnt3) are those whose expression is linearly related to the tumor mass increase in BALB-neuT mammary glands. Moreover, they have a low expression in normal tissues and are generally expressed in human breast tumors, though at a lower level than Her2.ConclusionAlthough the number of putative TAAs identified is limited, this pilot study suggests that meta-analysis of expression profiles produces results that could assist in the designing of pre-clinical immunopreventive vaccines.

Mutant SOD1 and mitochondrial damage alter expression and splicing of genes controlling neuritogenesis in models of neurodegeneration

Mitochondrial dysfunction has been implicated in the pathogenesis of a number of neurodegenerative disorders including Parkinson, Alzheimer, and Amyotrophic Lateral Sclerosis (ALS). In addition, aberrant mRNA splicing has been documented in neurodegeneration. To characterize the cellular response to mitochondrial perturbations at the level of gene expression and alternative pre‐mRNA splicing we used splicing‐sensitive microarrays to profile human neuroblastoma SH‐SY5Y cells treated with paraquat, a neurotoxic herbicide that induces the formation of reactive oxygen species and causes mitochondrial damage in animal models, and SH‐SY5Y cells stably expressing the mutant G93A‐SOD1 protein, one of the genetic causes of ALS. In both models we identified a common set of genes whose expression and alternative splicing are deregulated. Pathway analysis of the deregulated genes revealed enrichment in genes involved in neuritogenesis, axon growth and guidance, and synaptogenesis. Alterations in transcription and pre‐mRNA splicing of candidate genes were confirmed experimentally in the cell line models as well as in brain and spinal cord of transgenic mice carrying the G93A‐SOD1 mutation. Our findings expand the realm of the pathways implicated in neurodegeneration and suggest that alterations of axonal function may descend directly from mitochondrial damage. Hum Mutat 31:1–15, 2011.

Inflammation and breast cancer. Inflammatory component of mammary carcinogenesis in ErbB2 transgenic mice

This review addresses genes differentially expressed in the mammary gland transcriptome during the progression of mammary carcinogenesis in BALB/c mice that are transgenic for the rat neu (ERBB2, or HER-2/neu) oncogene (BALB-neuT664V-E mice). The Ingenuity knowledge database was used to characterize four functional association networks whose hub genes are directly linked to inflammation (specifically, the genes encoding IL-1β, tumour necrosis factor, interferon-γ, and monocyte chemoattractant protein-1/CC chemokine ligand-2) and are increasingly expressed during such progression. In silico meta-analysis in a human breast cancer dataset suggests that proinflammatory activation in the mammary glands of these mice reflects a general pattern of human breast cancer.

Sequencing of 15 622 gene-bearing BACs clarifies the gene-dense regions of the barley genome

Summary Barley (Hordeum vulgare L.) possesses a large and highly repetitive genome of 5.1 Gb that has hindered the development of a complete sequence. In 2012, the International Barley Sequencing Consortium released a resource integrating whole‐genome shotgun sequences with a physical and genetic framework. However, because only 6278 bacterial artificial chromosome (BACs) in the physical map were sequenced, fine structure was limited. To gain access to the gene‐containing portion of the barley genome at high resolution, we identified and sequenced 15 622 BACs representing the minimal tiling path of 72 052 physical‐mapped gene‐bearing BACs. This generated ~1.7 Gb of genomic sequence containing an estimated 2/3 of all Morex barley genes. Exploration of these sequenced BACs revealed that although distal ends of chromosomes contain most of the gene‐enriched BACs and are characterized by high recombination rates, there are also gene‐dense regions with suppressed recombination. We made use of published map‐anchored sequence data from Aegilops tauschii to develop a synteny viewer between barley and the ancestor of the wheat D‐genome. Except for some notable inversions, there is a high level of collinearity between the two species. The software HarvEST:Barley provides facile access to BAC sequences and their annotations, along with the barley–Ae. tauschii synteny viewer. These BAC sequences constitute a resource to improve the efficiency of marker development, map‐based cloning, and comparative genomics in barley and related crops. Additional knowledge about regions of the barley genome that are gene‐dense but low recombination is particularly relevant.