Modern middleware for the data acquisition of the Cherenkov Telescope Array

The data acquisition system (DAQ) of the future Cherenkov Telescope Array (CTA) must be ef- ficient, modular and robust to be able to cope with the very large data rate of up to 550 Gbps coming from many telescopes with different characteristics. The use of modern middleware, namely ZeroMQ and Protocol Buffers, can help to achieve these goals while keeping the development effort to a reasonable level. Protocol Buffers are used as an on-line data for- mat, while ZeroMQ is employed to communicate between processes. The DAQ will be controlled and monitored by the Alma Common Software (ACS). Protocol Buffers from Google are a way to define high-level data structures through an in- terface description language (IDL) and a meta-compiler. ZeroMQ is a middleware that augments the capabilities of TCP/IP sockets. It does not implement very high-level features like those found in CORBA for example, but makes use of sockets easier, more robust and almost as effective as raw TCP. The use of these two middlewares enabled us to rapidly develop a robust prototype of the DAQ including data persistence to compressed FITS files.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

Gene expression profile predicts outcome after anthracycline-based adjuvant chemotherapy in early breast cancer

International audiencePrognosis of early beast cancer is heterogeneous. Today, no histoclinical or biological factor predictive for clinical outcome after adjuvant anthracycline-based chemotherapy (CT) has been validated and introduced in routine use. Using DNA microarrays, we searched for a gene expression signature associated with metastatic relapse after adjuvant anthracycline-based CT without taxane. We profiled a multicentric series of 595 breast cancers including 498 treated with such adjuvant CT. The identification of the prognostic signature was done using a metagene-based supervised approach in a learning set of 323 patients. The signature was then tested on an independent validation set comprising 175 similarly treated patients, 128 of them from the PACS01 prospective clinical trial. We identified a 3-metagene predictor of metastatic relapse in the learning set, and confirmed its independent prognostic impact in the validation set. In multivariate analysis, the predictor outperformed the individual current prognostic factors, as well as the Nottingham Prognostic Index-based classifier, both in the learning and the validation sets, and added independent prognostic information. Among the patients treated with adjuvant anthracycline-based CT, with a median follow-up of 68 months, the 5-year metastasis-free survival was 82% in the "good-prognosis" group and 56% in the "poor-prognosis" group. Our predictor refines the prediction of metastasis-free survival after adjuvant anthracycline-based CT and might help tailoring adjuvant CT regimens

Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review

Clinicians can use biomarkers to guide therapeutic decisions in estrogen receptor positive (ER+) breast cancer. One such biomarker is cellular proliferation as evaluated by Ki-67. This biomarker has been extensively studied and is easily assayed by histopathologists but it is not currently accepted as a standard. This review focuses on its prognostic and predictive value, and on methodological considerations for its measurement and the cut-points used for treatment decision. Data describing study design, patients’ characteristics, methods used and results were extracted from papers published between January 1990 and July 2010. In addition, the studies were assessed using the REMARK tool. Ki-67 is an independent prognostic factor for disease-free survival (HR 1.05–1.72) in multivariate analyses studies using samples from randomized clinical trials with secondary central analysis of the biomarker. The level of evidence (LOE) was judged to be I-B with the recently revised definition of Simon. However, standardization of the techniques and scoring methods are needed for the integration of this biomarker in everyday practice. Ki-67 was not found to be predictive for long-term follow-up after chemotherapy. Nevertheless, high KI-67 was found to be associated with immediate pathological complete response in the neoadjuvant setting, with an LOE of II-B. The REMARK score improved over time (with a range of 6–13/20 vs. 10–18/20, before and after 2005, respectively). KI-67 could be considered as a prognostic biomarker for therapeutic decision. It is assessed with a simple assay that could be standardized. However, international guidelines are needed for routine clinical use

Association of GATA3, P53, Ki67 status and vascular peritumoral invasion are strongly prognostic in luminal breast cancer

International audienceIntroduction: Breast cancers are traditionally divided into hormone-receptor positive and negative cases. This classification helps to guide patient management. However, a subgroup of hormone-receptor positive patients relapse irrespective of hormonal therapy. Gene expression profiling has classified breast tumours into five major subtypes with significant different outcome. The two luminal subtypes, A and B, show high expression of ESR1, GATA3 and FOXA1 genes. Prognostic biomarkers for oestrogen receptor (ER)-positive cases include progesterone receptor (PR) and androgen receptor (AR), and proteins related to proliferation or apoptotic resistance. The aim of this study was to identify the best predictors of success of hormonal therapy.Methods: By immunohistochemistry we studied 10 markers in a consecutive series of 832 cases of breast carcinoma treated at the Paoli-Calmettes Institute from 1990 to 2002 and deposited onto tissue microarrays (TMA). These markers were luminal-related markers ER, PR, AR, FOXA1 and GATA3 transcription factors, proliferation-related Ki67 and CCND1, ERBB2, anti-apoptotic BCL2 and P53. We also measured vascular peritumoural invasion (VPI), size, grade and lymph node involvement. For 143 cases, gene expression profiles were available. Adjuvant chemotherapy and hormonal therapy were given to high- and low-risk patients, respectively. The 162 events observed and taken into account were metastases.Results: Molecular expression of the 10 parameters and subtype with ER status were strongly correlated. Of the 67 luminal A cases of this series, 63 were ER-positive. Multivariate analyses showed the highly significant prognostic value of VPI (hazard ratio (HR) = 2.47), Ki67 (HR = 2.9), P53 (HR = 2.9) and GATA3 (HR = 0.5) for the 240 patients who received hormonal therapy.Conclusions: A panel of three antibodies (Ki67, P53 and GATA3) associated with VPI can significantly improve the traditional prognosticators in predicting outcome for ER-positive breast cancer patients receiving hormonal therapy

The On-Site Analysis of the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) observatory will be one of the largest ground-based very high-energy gamma-ray observatories. The On-Site Analysis will be the first CTA scientific analysis of data acquired from the array of telescopes, in both northern and southern sites. The On-Site Analysis will have two pipelines: the Level-A pipeline (also known as Real-Time Analysis, RTA) and the level-B one. The RTA performs data quality monitoring and must be able to issue automated alerts on variable and transient astrophysical sources within 30 seconds from the last acquired Cherenkov event that contributes to the alert, with a sensitivity not worse than the one achieved by the final pipeline by more than a factor of 3. The Level-B Analysis has a better sensitivity (not be worse than the final one by a factor of 2) and the results should be available within 10 hours from the acquisition of the data: for this reason this analysis could be performed at the end of an observation or next morning. The latency (in particular for the RTA) and the sensitivity requirements are challenging because of the large data rate, a few GByte/s. The remote connection to the CTA candidate site with a rather limited network bandwidth makes the issue of the exported data size extremely critical and prevents any kind of processing in real-time of the data outside the site of the telescopes. For these reasons the analysis will be performed on-site with infrastructures co-located with the telescopes, with limited electrical power availability and with a reduced possibility of human intervention. This means, for example, that the on-site hardware infrastructure should have low-power consumption. A substantial effort towards the optimization of high-throughput computing service is envisioned to provide hardware and software solutions with high-throughput, low-power consumption at a low-cost.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

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

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

A whole-genome sequence and transcriptome perspective on HER2-positive breast cancers.

HER2-positive breast cancer has long proven to be a clinically distinct class of breast cancers for which several targeted therapies are now available. However, resistance to the treatment associated with specific gene expressions or mutations has been observed, revealing the underlying diversity of these cancers. Therefore, understanding the full extent of the HER2-positive disease heterogeneity still remains challenging. Here we carry out an in-depth genomic characterization of 64 HER2-positive breast tumour genomes that exhibit four subgroups, based on the expression data, with distinctive genomic features in terms of somatic mutations, copy-number changes or structural variations. The results suggest that, despite being clinically defined by a specific gene amplification, HER2-positive tumours melt into the whole luminal-basal breast cancer spectrum rather than standing apart. The results also lead to a refined ERBB2 amplicon of 106 kb and show that several cases of amplifications are compatible with a breakage-fusion-bridge mechanism

A whole-genome sequence and transcriptome perspective on HER2-positive breast cancers

HER2-positive breast cancer has long proven to be a clinically distinct class of breast cancers for which several targeted therapies are now available. However, resistance to the treatment associated with specific gene expressions or mutations has been observed, revealing the underlying diversity of these cancers. Therefore, understanding the full extent of the HER2-positive disease heterogeneity still remains challenging. Here we carry out an in-depth genomic characterization of 64 HER2-positive breast tumour genomes that exhibit four subgroups, based on the expression data, with distinctive genomic features in terms of somatic mutations, copy-number changes or structural variations. The results suggest that, despite being clinically defined by a specific gene amplification, HER2-positive tumours melt into the whole luminal-basal breast cancer spectrum rather than standing apart. The results also lead to a refined ERBB2 amplicon of 106 kb and show that several cases of amplifications are compatible with a breakage-fusion-bridge mechanism

Protein expression, survival and docetaxel benefit in node-positive breast cancer treated with adjuvant chemotherapy in the FNCLCC - PACS 01 randomized trial

International audienceABSTRACT: INTRODUCTION: The PACS01 trial has demonstrated that docetaxel addition to adjuvant anthracycline-based chemotherapy improves disease-free survival (DFS) and overall survival of node-positive early breast cancer (EBC). We searched for prognostic and predictive markers for docetaxel benefit. METHODS: Tumor samples from 1.099 recruited women were analyzed for the expression of 34 selected proteins using immunohistochemistry. The prognostic and predictive values of each marker and four molecular subtypes (luminal A, luminal B, HER2-overexpressing, and triple-negative) were tested. RESULTS: Progesterone receptor-negativity (HR=0.66; 95%CI 0.47-0.92, P=0.013), and Ki67-positivity (HR=1.53; 95%CI 1.12-2.08, P=0.007) were independent adverse prognostic factors. Out of the 34 proteins, only Ki67-positivity was associated with DFS improvement with docetaxel addition (adjusted HR=0.51, 95%CI 0.33-0.79 for Ki67-positive versus HR=1.10, 95%CI 0.75-1.61 for Ki67-negative tumors, P for interaction=0.012). Molecular subtyping predicted the docetaxel benefit, but without providing additional information to Ki67 status. The luminal A subtype did not benefit from docetaxel (HR=1.16, 95%CI 0.73-1.84); the reduction in the relapse risk was 53% (HR=0.47, 95%CI 0.22-1.01), 34% (HR=0.66, 95%CI 0.37-1.19), and 12% (HR=0.88, 95%CI 0.49-1.57) in the luminal B, HER2-overexpressing, and triple-negative subtypes, respectively. CONCLUSIONS: In patients with node-positive EBC receiving adjuvant anthracycline-based chemotherapy, the most powerful predictor of docetaxel benefit is Ki67-positivity

Multifactorial Analysis of Differences Between Sporadic Breast Cancers and Cancers Involving BRCA1 and BRCA2 Mutations

Background: We have previously demonstrated that breast cancers associated with inherited BRCA1 and BRCA2 gene mutations differ from each other in their histopathologic appearances and that each of these types differs from breast cancers in patients unselected for family history (i.e., sporadic cancers). We have now conducted a more detailed examination of cytologic and architectural features of these tumors. Methods: Specimens of tumor tissue (5-µm-thick sections) were examined independently by two pathologists, who were unaware of the case or control subject status, for the presence of cell mitosis, lymphocytic infiltration, continuous pushing margins, and solid sheets of cancer cells; cell nuclei, cell nucleoli, cell necrosis, and cell borders were also evaluated. The resulting data were combined with previously available information on tumor type and tumor grade and further evaluated by multifactorial analysis. All statistical tests are two-sided. Results: Cancers associated with BRCA1 mutations exhibited higher mitotic counts (P = .001), a greater proportion of the tumor with a continuous pushing margin (P<.0001), and more lymphocytic infiltration (P = .002) than sporadic (i.e., control) cancers. Cancers associated with BRCA2 mutations exhibited a higher score for tubule formation (fewer tubules) (P = .0002), a higher proportion of the tumor perimeter with a continuous pushing margin (P<.0001), and a lower mitotic count (P = .003) than control cancers. Conclusions: Our study has identified key features of the histologic phenotypes of breast cancers in carriers of mutant BRCA1 and BRCA2 genes. This information may improve the classification of breast cancers in individuals with a family history of the disease and may ultimately aid in the clinical management of patients. [J Natl Cancer Inst 1998;90:1138-45