Elodie Manié

Ploidy and Large-Scale Genomic Instability Consistently Identify Basal-like Breast Carcinomas with BRCA1/2 Inactivation

BRCA1 inactivation is a frequent event in basal-like breast carcinomas (BLC). However, BRCA1 can be inactivated by multiple mechanisms and determining its status is not a trivial issue. As an alternate approach, we profiled 65 BLC cases using single-nucleotide polymorphism arrays to define a signature of BRCA1-associated genomic instability. Large-scale state transitions (LST), defined as chromosomal break between adjacent regions of at least 10 Mb, were found to be a robust indicator of BRCA1 status in this setting. Two major ploidy-specific cutoffs in LST distributions were sufficient to distinguish highly rearranged BLCs with 85% of proven BRCA1-inactivated cases from less rearranged BLCs devoid of proven BRCA1-inactivated cases. The genomic signature we defined was validated in a second independent series of 55 primary BLC cases and 17 BLC-derived tumor cell lines. High numbers of LSTs resembling BRCA1-inactivated BLC were observed in 4 primary BLC cases and 2 BLC cell lines that harbored BRCA2 mutations. Overall, the genomic signature we defined predicted BRCA1/2 inactivation in BLCs with 100% sensitivity and 90% specificity (97% accuracy). This assay may ease the challenge of selecting patients for genetic testing or recruitment to clinical trials of novel emerging therapies that target DNA repair deficiencies in cancer.

Genome Alteration Print (GAP): a tool to visualize and mine complex cancer genomic profiles obtained by SNP arrays

We describe a method for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured with single-nucleotide polymorphism (SNP) arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. Assignments were verified by DNA indexes of primary tumors and karyotypes of cell lines. The method performs well even for poor-quality data, low tumor content, and highly rearranged tumor genomes.

Beta-catenin status in paediatric medulloblastomas: correlation of immunohistochemical expression with mutational status, genetic profiles, and clinical characteristics†

Medulloblastoma is the most frequent malignant paediatric brain tumour. The activation of the Wnt/β‐catenin pathway occurs in 10‐15% of medulloblastomas and has been recently described as a marker for favourable patient outcome. We report a series of 72 paediatric medulloblastomas evaluated for β‐catenin protein expression, CTNNB1 mutations, and comparative genomic hybridization. Gene expression profiles were also available in a subset of 40 cases. Immunostaining of β‐catenin showed extensive nuclear staining (>50% of the tumour cells) in six cases and focal nuclear staining (<10% of cells) in three cases. The other cases either exhibited a signal strictly limited to the cytoplasm (58 cases) or were negative (five cases). CTNNB1 mutations were detected in all β‐catenin extensively nucleopositive cases. The expression profiles of these cases documented strong activation of the Wnt/β‐catenin pathway. Remarkably, five out of these six tumours showed a complete loss of chromosome 6. In contrast, cases with focal nuclear β‐catenin staining, as well as tumours with negative or cytoplasmic staining, never demonstrated CTNNB1 mutation, Wnt/β‐catenin pathway activation or chromosome 6 loss. Patients with extensive nuclear staining were significantly older at diagnosis and were in continuous complete remission after a mean follow‐up of 75.7 months (range 27.5–121.2 months) from diagnosis. All three patients with focal nuclear staining of β‐catenin died within 36 months from diagnosis. Altogether, these data confirm and extend previous observations that CTNNB1‐mutated tumours represent a distinct molecular subgroup of medulloblastomas with favourable outcome, indicating that therapy de‐escalation should be considered. International consensus on the definition criteria of this distinct medulloblastoma subgroup should be achieved. Copyright

Germline BAP1 Mutations Predispose to Renal Cell Carcinomas

The genetic cause of some familial nonsyndromic renal cell carcinomas (RCC) defined by at least two affected first-degree relatives is unknown. By combining whole-exome sequencing and tumor profiling in a family prone to cases of RCC, we identified a germline BAP1 mutation c.277A>G (p.Thr93Ala) as the probable genetic basis of RCC predisposition. This mutation segregated with all four RCC-affected relatives. Furthermore, BAP1 was found to be inactivated in RCC-affected individuals from this family. No BAP1 mutations were identified in 32 familial cases presenting with only RCC. We then screened for germline BAP1 deleterious mutations in familial aggregations of cancers within the spectrum of the recently described BAP1-associated tumor predisposition syndrome, including uveal melanoma, malignant pleural mesothelioma, and cutaneous melanoma. Among the 11 families that included individuals identified as carrying germline deleterious BAP1 mutations, 6 families presented with 9 RCC-affected individuals, demonstrating a significantly increased risk for RCC. This strongly argues that RCC belongs to the BAP1 syndrome and that BAP1 is a RCC-predisposition gene.

High Frequency of TP53 Mutation in BRCA1 and Sporadic Basal-like Carcinomas but not in BRCA1 Luminal Breast Tumors

Breast tumors with a germ-line mutation of BRCA1 (BRCA1 tumors) and basal-like carcinoma (BLC) are associated with a high rate of TP53 mutation. Because BRCA1 tumors frequently display a basal-like phenotype, this study was designed to determine whether TP53 mutations are correlated with the hereditary BRCA1 mutated status or the particular phenotype of these tumors. The TP53 gene status was first investigated in a series of 35 BRCA1 BLCs using immunohistochemistry, direct sequencing of the coding sequence, and functional analysis of separated alleles in yeast, and compared with the TP53 status in a series of 38 sporadic (nonhereditary) BLCs. Using this sensitive approach, TP53 was found to be frequently mutated in both BRCA1 (34 of 35, 97%) and sporadic (35 of 38, 92%) BLCs. However, the spectrum of mutation was different, particularly with a higher rate of complex mutations, such as insertion/deletion, in BRCA1 BLCs than in the sporadic group [14 of 33 (42%) and 3 of 34 (9%), [corrected] respectively; P = 0.002]. Secondly, the incidence of TP53 mutations was analyzed in 19 BRCA1 luminal tumors using the same strategy. Interestingly, only 10 of these 19 tumors were mutated (53%), a frequency similar to that found in grade-matched sporadic luminal tumors. In conclusion, TP53 mutation is highly recurrent in BLCs independently of BRCA1 status, but not a common feature of BRCA1 luminal tumors.

VAMP: Visualization and analysis of array-CGH, transcriptome and other molecular profiles

MOTIVATION Microarray-based CGH (Comparative Genomic Hybridization), transcriptome arrays and other large-scale genomic technologies are now routinely used to generate a vast amount of genomic profiles. Exploratory analysis of this data is crucial in helping to understand the data and to help form biological hypotheses. This step requires visualization of the data in a meaningful way to visualize the results and to perform first level analyses. RESULTS We have developed a graphical user interface for visualization and first level analysis of molecular profiles. It is currently in use at the Institut Curie for cancer research projects involving CGH arrays, transcriptome arrays, SNP (single nucleotide polymorphism) arrays, loss of heterozygosity results (LOH), and Chromatin ImmunoPrecipitation arrays (ChIP chips). The interface offers the possibility of studying these different types of information in a consistent way. Several views are proposed, such as the classical CGH karyotype view or genome-wide multi-tumor comparison. Many functionalities for analyzing CGH data are provided by the interface, including looking for recurrent regions of alterations, confrontation to transcriptome data or clinical information, and clustering. Our tool consists of PHP scripts and of an applet written in Java. It can be run on public datasets at http://bioinfo.curie.fr/vamp AVAILABILITY The VAMP software (Visualization and Analysis of array-CGH,transcriptome and other Molecular Profiles) is available upon request. It can be tested on public datasets at http://bioinfo.curie.fr/vamp. The documentation is available at http://bioinfo.curie.fr/vamp/doc.

BAC array CGH distinguishes mutually exclusive alterations that define clinicogenetic subtypes of gliomas

The pathological classification of gliomas constitutes a critical step of the clinical management of patients, yet it is frequently challenging. To assess the relationship between genetic abnormalities and clinicopathological characteristics, we have performed a genetic and clinical analysis of a series of gliomas. A total of 112 gliomas were analyzed by comparative genomic hybridization on a BAC array with a 1 megabase resolution. Altered regions were identified and correlation analysis enabled to retrieve significant associations and exclusions. Whole chromosomes (chrs) 1p and 19q losses with centromeric breakpoints and EGFR high level amplification were found to be mutually exclusive, permitting identification of 3 distinct, nonoverlapping groups of tumors with striking clinicopathological differences. Type A tumors with chrs 1p and 19q codeletion exhibited an oligodendroglial phenotype and a longer patient survival. Type B tumors were characterized by EGFR amplification. They harbored a WHO high grade of malignancy and a short patient survival. Finally, type C tumors displayed none of the previous patterns but the presence of chr 7 gain, chr 9p deletion and/or chr 10 loss. It included astrocytic tumors in patients younger than in type B and whose prognosis was highly dependent upon the number of alterations. A multivariate analysis based on a Cox model shows that age, WHO grade and genomic type provide complementary prognostic informations. Finally, our results highlight the potential of a whole‐genome analysis as an additional diagnostic in cases of unclear conventional genetic findings.

Spatial normalization of array-CGH data

BackgroundArray-based comparative genomic hybridization (array-CGH) is a recently developed technique for analyzing changes in DNA copy number. As in all microarray analyses, normalization is required to correct for experimental artifacts while preserving the true biological signal. We investigated various sources of systematic variation in array-CGH data and identified two distinct types of spatial effect of no biological relevance as the predominant experimental artifacts: continuous spatial gradients and local spatial bias. Local spatial bias affects a large proportion of arrays, and has not previously been considered in array-CGH experiments.ResultsWe show that existing normalization techniques do not correct these spatial effects properly. We therefore developed an automatic method for the spatial normalization of array-CGH data. This method makes it possible to delineate and to eliminate and/or correct areas affected by spatial bias. It is based on the combination of a spatial segmentation algorithm called NEM (Neighborhood Expectation Maximization) and spatial trend estimation. We defined quality criteria for array-CGH data, demonstrating significant improvements in data quality with our method for three data sets coming from two different platforms (198, 175 and 26 BAC-arrays).ConclusionWe have designed an automatic algorithm for the spatial normalization of BAC CGH-array data, preventing the misinterpretation of experimental artifacts as biologically relevant outliers in the genomic profile. This algorithm is implemented in the R package MANOR (Micro-Array NORmalization), which is described at http://bioinfo.curie.fr/projects/manor and available from the Bioconductor site http://www.bioconductor.org. It can also be tested on the CAPweb bioinformatics platform at http://bioinfo.curie.fr/CAPweb.

X Inactive–Specific Transcript RNA Coating and Genetic Instability of the X Chromosome in BRCA1 Breast Tumors

Identification among breast tumors of those arising in a hereditary BRCA1 context remains a medical challenge. Abnormalities in X chromosome copy number and in the epigenetic stability of the inactive X chromosome (Xi) have been proposed to characterize BRCA1 breast tumors. In particular, it has been proposed that loss of BRCA1 function can lead to loss of X inactive-specific transcript (XIST) RNA association with the Xi. However, few studies have addressed this issue in a sufficiently large series of BRCA1 primary tumors. Here we assess X-chromosome status using single-cell (RNA and DNA fluorescence in situ hybridization) and global genomic (array-comparative genomic hybridization and allelotyping) approaches on a series of 11 well-defined BRCA1 tumors. We show that many or most cells of the tumors contain one or more XIST RNA domains. Furthermore, the number of XIST RNA domains per cell varied considerably even within a single tumor. Frequent X-chromosome allelic and copy number aberrations were found, in agreement with aberrant XIST RNA domain numbers. In summary, by combining multiple approaches to assess the genetics and epigenetics of a large series of BRCA1 primary tumors, we can conclude definitively that BRCA1 is not required for XIST RNA coating of the X chromosome. The intratumoral and intertumoral variability in XIST RNA domain number in BRCA1 tumors correlates with chromosomal genetic abnormalities, including gains, losses, reduplications, and rearrangements of the X-chromosome. Finally, we also show the necessity for combined global and single-cell approaches in the assessment of tumors with such a high degree of heterogeneity.

A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers

BRCA1 encodes a tumour suppressor protein that plays pivotal roles in homologous recombination (HR) DNA repair, cell‐cycle checkpoints, and transcriptional regulation. BRCA1 germline mutations confer a high risk of early‐onset breast and ovarian cancer. In more than 80% of cases, tumours arising in BRCA1 germline mutation carriers are oestrogen receptor (ER)‐negative; however, up to 15% are ER‐positive. It has been suggested that BRCA1 ER‐positive breast cancers constitute sporadic cancers arising in the context of a BRCA1 germline mutation rather than being causally related to BRCA1 loss‐of‐function. Whole‐genome massively parallel sequencing of ER‐positive and ER‐negative BRCA1 breast cancers, and their respective germline DNAs, was used to characterize the genetic landscape of BRCA1 cancers at base‐pair resolution. Only BRCA1 germline mutations, somatic loss of the wild‐type allele, and TP53 somatic mutations were recurrently found in the index cases. BRCA1 breast cancers displayed a mutational signature consistent with that caused by lack of HR DNA repair in both ER‐positive and ER‐negative cases. Sequencing analysis of independent cohorts of hereditary BRCA1 and sporadic non‐BRCA1 breast cancers for the presence of recurrent pathogenic mutations and/or homozygous deletions found in the index cases revealed that DAPK3, TMEM135, KIAA1797, PDE4D, and GATA4 are potential additional drivers of breast cancers. This study demonstrates that BRCA1 pathogenic germline mutations coupled with somatic loss of the wild‐type allele are not sufficient for hereditary breast cancers to display an ER‐negative phenotype, and has led to the identification of three potential novel breast cancer genes (ie DAPK3, TMEM135, and GATA4). Copyright