Mining microarray data to predict the histological grade of a breast cancer

BACKGROUND: The aim of this study was to develop an original method to extract sets of relevant molecular biomarkers (gene sequences) that can be used for class prediction and can be included as prognostic and predictive tools. MATERIALS AND METHODS: The method is based on sequential patterns used as features for class prediction. We applied it to classify breast cancer tumors according to their histological grade. RESULTS: We obtained very good recall and precision for grades 1 and 3 tumors, but, like other authors, our results were less satisfactory for grade 2 tumors. CONCLUSIONS: We demonstrated the interest of sequential patterns for class prediction of microarrays and we now have the material to use them for prognostic and predictive applications

Breast tumor PDXs are genetically plastic and correspond to a subset of aggressive cancers prone to relapse.

The authors wish to thank the personnel of the IRCM animal facility team, the histology (RHEM) platform, the Affymetrix platform of Montpellier and Dr Caroline Mollevi from the Biostatistics platform at ICM for their help in this project. The constant support of ICM and SIRIC Montpellier-Cancer is gratefully acknowledged.International audiencePatient derived xenografts (PDXs) are increasingly appreciated models in cancer research, particularly for preclinical testing, as they reflect the patient's tumor biology more accurately than cancer cell lines. We have established a collection of 20 breast PDXs and characterized their biological and clinical features, as well as their genetic stability. While most PDXs originated from triple negative breast cancers (70%), our collection comprised five ER + cases (25%). Remarkably, the tumors that produced PDXs derived from a subset of aggressive breast cancers with a high proportion of grade 3 tumors and reduced recurrence-free survival. Consistent with this, we found significant differences between the transcriptomic signatures of tumors that produced a PDX (Take) and those that did not (No Take). The PDXs faithfully recapitulate the histological features of their primary tumors, and retain an excellent conservation of molecular classification assignment and Copy Number Change (CNC). Furthermore, the CNC profiles of different PDXs established from the same tumor overlap significantly. However, a small fraction of CNCs in the primary tumor that correspond to oligoclonal events were gradually lost during sequential passaging, suggesting that the PDXs' genetic structure eventually stabilizes around a dominant clone present in the tumor of origin. Finally, de novo occurring genetic events covering up to 9% of the genome were found in only a minority of the PDXs, showing that PDXs have limited genetic instability. These data show that breast cancer PDXs represent a subset of aggressive tumors prone to relapse, and that despite of an excellent conservation of original features, they remain genetically dynamic elements

Remaniements chromosomiques dans les cancers du sein. Etude du bras long du chromosome 17

MONTPELLIER-BU Sciences (341722106) / SudocSudocFranceF

Handling Fuzzy Gaps in Sequential Patterns: Application to Health

International audienceDealing with numerical data for mining novel knowledge is a non trivial task that has received much attention in the last years. However, it is still not easy to handle such data, especially when large volumes of values must be analyzed. In our work, we focus on biological data from DNA chips that biologists study in order to try and discover new gene correlations that could help understanding diseases like breast cancer. In this framework, we consider the values from the DNA microarrays, which convey the behavior of some genes, and we want to discover how these behaviors are correlated. This data are considered as being ordered as numerical values can be sorted. In previous work, sequential patterns like (1 5)(2) have been discovered, meaning that genes 1 and 5 have the same expression level followed by gene 2 that has a higher expression value. However, such data are very noisy and considering close values as ordered is often false. We thus consider here fuzzy rankings based on a fuzzy partition provided by the experts. Rules can then better characterize how genes are correlated

SLUG and Truncated TAL1 Reduce Glioblastoma Stem Cell Growth Downstream of Notch1 and Define Distinct Vascular Subpopulations in Glioblastoma Multiforme

International audienceGlioblastomas (GBM) are high-grade brain tumors, containing cells with distinct phenotypes and tumorigenic potentials, notably aggressive and treatment-resistant multipotent glioblastoma stem cells (GSC). The molecular mechanisms controlling GSC plasticity and growth have only partly been elucidated. Contact with endothelial cells and the Notch1 pathway control GSC proliferation and fate. We used three GSC cultures and glioma resections to examine the expression, regulation, and role of two transcription factors, SLUG (SNAI2) and TAL1 (SCL), involved in epithelial to mesenchymal transition (EMT), hematopoiesis, vascular identity, and treatment resistance in various cancers. In vitro, SLUG and a truncated isoform of TAL1 (TAL1-PP22) were strongly upregulated upon Notch1 activation in GSC, together with LMO2, a known cofactor of TAL1, which formed a complex with truncated TAL1. SLUG was also upregulated by TGF-β1 treatment and by co-culture with endothelial cells. In patient samples, the full-length isoform TAL1-PP42 was expressed in all glioma grades. In contrast, SLUG and truncated TAL1 were preferentially overexpressed in GBMs. SLUG and TAL1 are expressed in the tumor microenvironment by perivascular and endothelial cells, respectively, and to a minor extent, by a fraction of epidermal growth factor receptor (EGFR) -amplified GBM cells. Mechanistically, both SLUG and truncated TAL1 reduced GSC growth after their respective overexpression. Collectively, this study provides new evidence for the role of SLUG and TAL1 in regulating GSC plasticity and growth

CDK inhibition results in pharmacologic BRCAness increasing sensitivity to olaparib in BRCA1-WT and olaparib resistant in Triple Negative Breast Cancer

International audienceOne in three Triple Negative Breast Cancer (TNBC) is Homologous Recombination Deficient (HRD) and susceptible to respond to PARP inhibitor (PARPi), however, resistance resulting from functional HR restoration is frequent. Thus, pharmacologic approaches that induce HRD are of interest. We investigated the effectiveness of CDK-inhibition to induce HRD and increase PARPi sensitivity of TNBC cell lines and PDX models. Two CDK-inhibitors (CDKi), the broad range dinaciclib and the CDK12-specific SR-4835, strongly reduced the expression of key HR genes and impaired HR functionality, as illustrated by BRCA1 and RAD51 nuclear foci obliteration. Consequently, both CDKis showed synergism with olaparib, as well as with cisplatin and gemcitabine, in a range of TNBC cell lines and particularly in olaparib-resistant models. In vivo assays on PDX validated the efficacy of dinaciclib which increased the sensitivity to olaparib of 5/6 models, including two olaparib-resistant and one BRCA1-WT model. However, no olaparib response improvement was observed in vivo with SR-4835. These data support that the implementation of CDK-inhibitors could be effective to sensitize TNBC to olaparib as well as possibly to cisplatin or gemcitabine

Estrogen and retinoic acid antagonistically regulate several microRNA genes to control aerobic glycolysis in breast cancer cells.

International audienceIn addition to estrogen receptor modulators, retinoic acid and other retinoids are promising agents to prevent breast cancer. Retinoic acid and estrogen exert antagonistic regulations on the transcription of coding genes and we evaluated here whether these two compounds have similar effects on microRNAs. Using an integrative approach based on several bioinformatics resources together with experimental validations, we indeed found that retinoic acid positively regulates miR-210 and miR-23a/24-2 expressions and is counteracted by estrogen. Conversely, estrogen increased miR-17/92 and miR-424/450b expressions and is inhibited by retinoic acid. In silico functional enrichment further revealed that this combination of transcriptional/post-transcriptional regulations fully impacts on the molecular effects of estrogen and retinoic acid. Besides, we unveiled a novel effect of retinoic acid on aerobic glycolysis. We specifically showed that it increases extracellular lactate production, an effect counteracted by the miR-210 and the miR-23a/24-2, which simultaneously target lactate dehydrogenase A and B mRNAs. Together our results provide a new framework to better understand the estrogen/retinoic acid antagonism in breast cancer cells

Genetic variability in MCF-7 sublines: evidence of rapid genomic and RNA expression profile modifications.

International audienceBACKGROUND: Both phenotypic and cytogenetic variability have been reported for clones of breast carcinoma cell lines but have not been comprehensively studied. Despite this, cell lines such as MCF-7 cells are extensively used as model systems. METHODS: In this work we documented, using CGH and RNA expression profiles, the genetic variability at the genomic and RNA expression levels of MCF-7 cells of different origins. Eight MCF-7 sublines collected from different sources were studied as well as 3 subclones isolated from one of the sublines by limit dilution. RESULTS: MCF-7 sublines showed important differences in copy number alteration (CNA) profiles. Overall numbers of events ranged from 28 to 41. Involved chromosomal regions varied greatly from a subline to another. A total of 62 chromosomal regions were affected by either gains or losses in the 11 sublines studied. We performed a phylogenetic analysis of CGH profiles using maximum parsimony in order to reconstruct the putative filiation of the 11 MCF-7 sublines. The phylogenetic tree obtained showed that the MCF-7 clade was characterized by a restricted set of 8 CNAs and that the most divergent subline occupied the position closest to the common ancestor. Expression profiles of 8 MCF-7 sublines were analyzed along with those of 19 unrelated breast cancer cell lines using home made cDNA arrays comprising 720 genes. Hierarchical clustering analysis of the expression data showed that 7/8 MCF-7 sublines were grouped forming a cluster while the remaining subline clustered with unrelated breast cancer cell lines. These data thus showed that MCF-7 sublines differed at both the genomic and phenotypic levels. CONCLUSIONS: The analysis of CGH profiles of the parent subline and its three subclones supported the heteroclonal nature of MCF-7 cells. This strongly suggested that the genetic plasticity of MCF-7 cells was related to their intrinsic capacity to generate clonal heterogeneity. We propose that MCF-7, and possibly the breast tumor it was derived from, evolved in a node like pattern, rather than according to a linear progression model. Due to their capacity to undergo rapid genetic changes MCF-7 cells could represent an interesting model for genetic evolution of breast tumors