73 research outputs found

    What do we learn from HER2-positive breast cancer genomic profiles?

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    Patients with a tumor presenting amplification of the HER2 gene are currently proposed trastuzumab (herceptin) and this has greatly changed their outcome. However, a number of HER2-positive cancers show intrinsic or acquired resistance to trastuzumab and there are clear indications that they form a heterogeneous group of tumors. A paper in this issue of Breast Cancer Research addresses this heterogeneity at the genomic level

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

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    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

    A new molecular breast cancer subclass defined from a large scale real-time quantitative RT-PCR study

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    BACKGROUND: Current histo-pathological prognostic factors are not very helpful in predicting the clinical outcome of breast cancer due to the disease's heterogeneity. Molecular profiling using a large panel of genes could help to classify breast tumours and to define signatures which are predictive of their clinical behaviour. METHODS: To this aim, quantitative RT-PCR amplification was used to study the RNA expression levels of 47 genes in 199 primary breast tumours and 6 normal breast tissues. Genes were selected on the basis of their potential implication in hormonal sensitivity of breast tumours. Normalized RT-PCR data were analysed in an unsupervised manner by pairwise hierarchical clustering, and the statistical relevance of the defined subclasses was assessed by Chi2 analysis. The robustness of the selected subgroups was evaluated by classifying an external and independent set of tumours using these Chi2-defined molecular signatures. RESULTS: Hierarchical clustering of gene expression data allowed us to define a series of tumour subgroups that were either reminiscent of previously reported classifications, or represented putative new subtypes. The Chi2 analysis of these subgroups allowed us to define specific molecular signatures for some of them whose reliability was further demonstrated by using the validation data set. A new breast cancer subclass, called subgroup 7, that we defined in that way, was particularly interesting as it gathered tumours with specific bioclinical features including a low rate of recurrence during a 5 year follow-up. CONCLUSION: The analysis of the expression of 47 genes in 199 primary breast tumours allowed classifying them into a series of molecular subgroups. The subgroup 7, which has been highlighted by our study, was remarkable as it gathered tumours with specific bioclinical features including a low rate of recurrence. Although this finding should be confirmed by using a larger tumour cohort, it suggests that gene expression profiling using a minimal set of genes may allow the discovery of new subclasses of breast cancer that are characterized by specific molecular signatures and exhibit specific bioclinical features

    Anomalies genomiques dans le cancer du sein

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    SIGLEINIST T 77268 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

    Caractérisation du contingent de cellules souches cancéreuses au cours de la cancérogenèse mammaire

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    MONTPELLIER-BU Pharmacie (341722105) / SudocSudocFranceF

    Elaboration d'un nouveau modèle pour la caractérisation de nouveaux gènes impliqués dans la stabilité des sites fragiles

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    Les sites fragiles sont des sites récurrents de cassures, favorisant l'apparition de remaniements chromosomiques et participant ainsi à la progression tumorale. Les mécanismes et les gènes impliqués dans cette fragilité chromosomique sont actuellement peu connus. Afin de mieux comprendre ces mécanismes, nous avons établis un nouveau modèle d'étude. Ce modèle est constitué de clones cellulaires issus de la lignée HCT116 MMR déficiente, pour lesquels un ou plusieurs gènes cibles, potentiellement impliqués dans la stabilité des sites fragiles, possèdent une mutation l'inactivant partiellement. Nous avons sélectionné et analysé 20 gènes codant pour des protéines impliquées dans les voies de signalisation de la réponse aux dommages de l'ADN, au stress réplicatif et à la condensation des chromosomes. Nous avons ainsi établi une collection de 200 clones cellulaires qui portent des mutations dans 13 gènes étudiés. Nous avons ensuite mis en évidence le rôle de la mutation obtenue dans le gène ATR dans l'inactivation de ce dernier en favorisant l'accumulation des cassures au niveau des sites fragiles. Ces résultats nous ont permis de proposer un système modèle constituant un outil de choix pour l'étude des sites fragiles. Dans une étude menée en parallèle, nous nous sommes intéressés au gène MCPH1/BRIT1 codant pour une protéine impliquée dans plusieurs processus cellulaires. Nous avons pu mettre en évidence qu'une dérégulation du gène MCPH1/BRIT1 engendre une instabilité chromosomique et une accumulation des cassures au niveau des sites fragilesCommon fragile sites are chomosomal regions involved in recurrent breaks, which are "expressed" under various physiological stresses, most of them are known to disturb DNA replication. A direct link between fragile sites and emergence of various types of chromosomal rearrangement has been established, even in early stages of tumorigenesis. However, only few genes involved in genome stability at fragile sites have been identified. The aim of this study is to identify new genes involved in the expression of fragile sites and to elucidate molecular processes that affect their stability. We established a cell based system on a mismatch repair deficient background. 20 candidate genes were targeted in this study. We examined the incidence of frameshift mutations in 32 mononucleotide repeats of these genes. 17 frameshift mutations were found. We demonstrate that frameshift mutations affecting coding mononucleotide repeat of ATR, inactivate one of the two alleles leading to formation of breaks at fragile sites. This collection of clones gives us a unique cellular model to study precisely the maintenance of genome stability at fragile sites. Furthermore, we have investigated the effects of the deregulation of the expression of MCPH1/BRIT1 on common fragile site stability. MCPH1/BRIT1 acts as a regulator of both the intra-S and G2/M keckpoints. We show that deregulation of the expression of MCPH1/BRIT1 increase H2AX phosphorylation suggesting the accumulation of DNA double-strand breaks. This leads to formation of breaks at fragile sites. These findings demonstrate a critical role for the MCPH1/BRIT1 in regulating chromosome stability, and in particular, common fragile siteMONTPELLIER-BU Médecine UPM (341722108) / SudocMONTPELLIER-BU Médecine (341722104) / SudocSudocFranceF

    Modeling risk stratification in human cancer.

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    International audienceMOTIVATION: Despite huge prognostic promises, gene expression-based survival assessment is rarely used in clinical routine. Main reasons include difficulties in performing and reporting analyses and restriction in most methods to one high-risk group with the vast majority of patients being unassessed. The present study aims at limiting these difficulties by (i) mathematically defining the number of risk groups without any a priori assumption; (ii) computing the risk of an independent cohort by considering each patient as a new patient incorporated to the validation cohort and (iii) providing an open-access Web site to freely compute risk for every new patient. RESULTS: Using the gene expression profiles of 551 patients with multiple myeloma, 602 with breast-cancer and 460 with glioma, we developed a model combining running log-rank tests under controlled chi-square conditions and multiple testing corrections to build a risk score and a classification algorithm using simultaneous global and between-group log-rank chi-square maximization. For each cancer entity, we provide a statistically significant three-group risk prediction model, which is corroborated with publicly available validation cohorts. CONCLUSION: In constraining between-group significances, the risk score compares favorably with previous risk classifications. AVAILABILITY: Risk assessment is freely available on the Web at https://gliserv.montp.inserm.fr/PrognoWeb/ for personal or test data files. Web site implementation in Perl, R and Apache
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