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Four molecular classifications of pancreatic ductal adenocarcinoma (PDAC), biologically and clinically relevant and based on gene expression profiles, were established in the recent years, including the Collisson's, Moffitt's ("tumor" and "stroma" classifications), and Bailey's classifications. The aim of this study was to validate the prognostic value of the Moffitt's classifications and to compare the Collisson's, Moffitt's, and Bailey's classifications in a large series of samples. We collected clinical and gene expression data of PDAC samples from 15 public data sets, resulting in a total of 846 primary cancer samples, including 601 with survival annotation. All samples were classified according to each of the four multigene classifiers. We confirmed the independent prognostic value of the Moffitt "tumor", Moffitt "stroma", and Bailey's classifications, but not that of the Collisson's classification. Despite a relatively low gene overlap, all classifications were associated with pathological grade, an important prognostic feature and reflect of intrinsic molecular characteristics of tumors. The concordance rate in term of "good-prognosis" vs. "poor-prognosis" prediction by classifiers was relatively high (from 73 to 86%) between the three "tumor" classifications based on tumor gene lists (Collisson, Moffitt "tumor", Bailey), but low (from 50 to 60%) with the Moffitt's stroma classification based on stroma genes. Multivariate analysis incorporating the four classifiers together retained as significant variables the Moffitt "stroma" and Bailey classifications, highlighting the complementarity of classifiers based on tumor epithelium (Bailey) and tumor stroma (Moffitt stroma). Our results reinforce the clinical validity of subtyping in PDAC, which should be regarded as a collection of separate diseases. Beside their clinical utility that remains to be demonstrated, the clinical interest of the subtypes, notably those from Bailey's and Moffitt's "stroma" classifiers that show independent prognostic value, will be reinforced by the identification of new biomarkers and/or therapeutic targets in each subtype for designing and testing novel specific targeted therapies. [ABSTRACT FROM AUTHOR]

Background: Pancreatic carcinoma is one of the most lethal human cancers. In patients with resectable tumors, surgery followed by adjuvant chemotherapy is the only curative treatment. However, the 5-year survival is 20%. Because of a strong metastatic propensity, neoadjuvant chemotherapy is being tested in randomized clinical trials. In this context, improving the selection of patients for immediate surgery or neoadjuvant chemotherapy is crucial, and high-throughput molecular analyses may help; the present study aims to address this.Methods: Clinicopathological and gene expression data of 695 pancreatic carcinoma samples were collected from nine datasets and supervised analysis was applied to search for a gene expression signature predictive for overall survival (OS) in the 601 informative operated patients. The signature was identified in a learning set of patients and tested for its robustness in a large independent validation set.Results: Supervised analysis identified 1400 genes differentially expressed between two selected patient groups in the learning set, namely 17 long-term survivors (LTS; ≥ 36 months after surgery) and 22 short-term survivors (STS; dead of disease between 2 and 6 months after surgery). From these, a 25-gene prognostic classifier was developed, which identified two classes ("STS-like" and "LTS-like") in the independent validation set (n = 562), with a 25% (95% CI 18-33) and 48% (95% CI 42-54) 2-year OS (P = 4.33 × 10-9), respectively. Importantly, the prognostic value of this classifier was independent from both clinicopathological prognostic features and molecular subtypes in multivariate analysis, and existed in each of the nine datasets separately. The generation of 100,000 random gene signatures by a resampling scheme showed the non-random nature of our prognostic classifier.Conclusion: This study, the largest prognostic study of gene expression profiles in pancreatic carcinoma, reports a 25-gene signature associated with post-operative OS independently of classical factors and molecular subtypes. This classifier may help select patients with resectable disease for either immediate surgery (the LTS-like class) or neoadjuvant chemotherapy (the STS-like class). Its assessment in the current prospective trials of adjuvant and neoadjuvant chemotherapy trials is warranted, as well as the functional analysis of the classifier genes, which may provide new therapeutic targets. [ABSTRACT FROM AUTHOR]

Background: Inflammatory breast cancer (IBC) is the most rare and aggressive variant of breast cancer (BC); however, only a limited number of specific gene signatures with low generalization abilities are available and few reliable biomarkers are helpful to improve IBC classification into a molecularly distinct phenotype. We applied a network-based strategy to gain insight into master regulators (MRs) linked to IBC pathogenesis. Methods: In-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) on IBC/non-IBC (nIBC) gene expression data (n = 197) was employed to identify novel master regulators connected to the IBC phenotype. Pathway enrichment analysis was used to characterize predicted targets of candidate genes. The expression pattern of the most significant MRs was then evaluated by immunohistochemistry (IHC) in two independent cohorts of IBCs (n = 39) and nIBCs (n = 82) and normal breast tissues (n = 15) spotted on tissue microarrays. The staining pattern of non-neoplastic mammary epithelial cells was used as a normal control. Results: Using in-silico modeling of network-based strategy, we identified three top enriched MRs (NFAT5, CTNNB1 or β-catenin, and MGA) strongly linked to the IBC phenotype. By IHC assays, we found that IBC patients displayed a higher number of NFAT5-positive cases than nIBC (69.2% vs. 19.5%; p-value = 2.79 10-7). Accordingly, the majority of NFAT5-positive IBC samples revealed an aberrant nuclear expression in comparison with nIBC samples (70% vs. 12.5%; p-value = 0.000797). NFAT5 nuclear accumulation occurs regardless of WNT/β-catenin activated signaling in a substantial portion of IBCs, suggesting that NFAT5 pathway activation may have a relevant role in IBC pathogenesis. Accordingly, cytoplasmic NFAT5 and membranous β-catenin expression were preferentially linked to nIBC, accounting for the better prognosis of this phenotype. Conclusions: We provide evidence that NFAT-signaling pathway activation could help to identify aggressive forms of BC and potentially be a guide to assignment of phenotype-specific therapeutic agents. The NFAT5 transcription factor might be developed into routine clinical practice as a putative biomarker of IBC phenotype. [ABSTRACT FROM AUTHOR]

Background: The lastly identified claudin-low (CL) subtype of breast cancer (BC) remains poorly described as compared to the other molecular subtypes. We provide a comprehensive characterization of the largest series of CL samples reported so far. Methods: From a data set of 5447 invasive BC profiled using DNA microarrays, we identified 673 CL samples (12,4%) that we describe comparatively to the other molecular subtypes at several levels: clinicopathological, genomic, transcriptional, survival, and response to chemotherapy. Results: CL samples display profiles different from other subtypes. For example, they differ from basal tumors regarding the hormone receptor status, with a lower frequency of triple negative (TN) tumors (52% vs 76% for basal cases). Like basal tumors, they show high genomic instability with many gains and losses. At the transcriptional level, CL tumors are the most undifferentiated tumors along the mammary epithelial hierarchy. Compared to basal tumors, they show enrichment for epithelial-to-mesenchymal transition markers, immune response genes, and cancer stem cell--like features, and higher activity of estrogen receptor (ER), progesterone receptor (PR), EGFR, SRC and TGFβ pathways, but lower activity of MYC and PI3K pathways. The 5-year disease-free survival of CL cases (67%) and the rate of pathological complete response (pCR) to primary chemotherapy (32%) are close to those of poor-prognosis and good responder subtypes (basal and ERBB2-enriched). However, the prognostic features of CL tumors are closer to those observed in the whole BC series and in the luminal A subtype, including proliferation-related gene expression signatures (GES). Immunity-related GES valuable in basal breast cancers are not significant in CL tumors. By contrast, the GES predictive for pCR in CL tumors resemble more to those of basal and HER2-enriched tumors than to those of luminal A tumors. Conclusions: Many differences exist between CL and the other subtypes, notably basal. An unexpected finding concerns the relatively high numbers of ER-positive and non-TN tumors within CL subtype, suggesting a larger heterogeneity than in basal and luminal A subtypes. [ABSTRACT FROM AUTHOR]

Introduction Because of its high rate of metastasis, inflammatory breast cancer (IBC) has a poor prognosis compared with non-inflammatory types of breast cancer (non-IBC). In a recent study, Lehmann and colleagues identified seven subtypes of triple-negative breast cancer (TNBC). We hypothesized that the distribution of TNBC subtypes differs between TN-IBC and TNnon- IBC. We determined the subtypes and compared clinical outcomes by subtype in TNIBC and TN-non-IBC patients. Methods We determined TNBC subtypes in a TNBC cohort from the World IBC Consortium for which IBC status was known (39 cases of TN-IBC; 49 cases of TN-non-IBC). We then determined the associations between TNBC subtypes and IBC status and compared clinical outcomes between TNBC subtypes. Results We found the seven subtypes exist in both TN-IBC and TN-non-IBC. We found no association between TNBC subtype and IBC status (P = 0.47). TNBC subtype did not predict recurrence-free survival. IBC status was not a significant predictor of recurrence-free or overall survival in the TNBC cohort. Conclusions Our data show that, like TN-non-IBC, TN-IBC is a heterogeneous disease. Although clinical characteristics differ significantly between IBC and non-IBC, no unique IBC-specific TNBC subtypes were identified by mRNA gene expression profiles of the tumor. Studies are needed to identify the subtle molecular or microenvironmental differences that contribute to the differing clinical behaviors between TN-IBC and TN-non-IBC. [ABSTRACT FROM AUTHOR]

Background: With the advance of post-genomic technologies, the need for tools to manage large scale data in biology becomes more pressing. This involves annotating and storing data securely, as well as granting permissions flexibly with several technologies (all array types, flow cytometry, proteomics) for collaborative work and data sharing. This task is not easily achieved with most systems available today. Findings: We developed Djeen (Database for Joomla!'s Extensible Engine), a new Research Information Management System (RIMS) for collaborative projects. Djeen is a user-friendly application, designed to streamline data storage and annotation collaboratively. Its database model, kept simple, is compliant with most technologies and allows storing and managing of heterogeneous data with the same system. Advanced permissions are managed through different roles. Templates allow Minimum Information (MI) compliance. Conclusion: Djeen allows managing project associated with heterogeneous data types while enforcing annotation integrity and minimum information. Projects are managed within a hierarchy and user permissions are finelygrained for each project, user and group. Djeen Component source code (version 1.5.1) and installation documentation are available under CeCILL license from http://sourceforge.net/projects/djeen/files and supplementary material. [ABSTRACT FROM AUTHOR]

Background: Around 20% of breast cancers (BC) show ERBB2 gene amplification and overexpression of the ERBB2 tyrosine kinase receptor. They are associated with a poor prognosis but can benefit from targeted therapy. A better knowledge of these BCs, genomically and biologically heterogeneous, may help understand their behavior and design new therapeutic strategies. Methods: We defined the high resolution genome and gene expression profiles of 54 ERBB2-amplified BCs using 244K oligonucleotide array-comparative genomic hybridization and whole-genome DNA microarrays. Expression of ERBB2, phosphorylated ERBB2, EGFR, IGF1R and FOXA1 proteins was assessed by immunohistochemistry to evaluate the functional ERBB2 status and identify co-expressions. Results: First, we identified the ERBB2-C17orf37-GRB7 genomic segment as the minimal common 17q12-q21 amplicon, and CRKRS and IKZF3 as the most frequent centromeric and telomeric amplicon borders, respectively. Second, GISTIC analysis identified 17 other genome regions affected by copy number aberration (CNA) (amplifications, gains, losses). The expression of 37 genes of these regions was deregulated. Third, two types of heterogeneity were observed in ERBB2-amplified BCs. The genomic profiles of estrogen receptor-postive (ER+) and negative (ER-) ERBB2-amplified BCs were different. The WNT/b-catenin signaling pathway was involved in ERERBB2- amplified BCs, and PVT1 and TRPS1 were candidate oncogenes associated with ER+ ERBB2-amplified BCs. The size of the ERBB2 amplicon was different in inflammatory (IBC) and non-inflammatory BCs. ERBB2-amplified IBCs were characterized by the downregulated and upregulated mRNA expression of ten and two genes in proportion to CNA, respectively. IHC results showed (i) a linear relationship between ERBB2 gene amplification and its gene and protein expressions with a good correlation between ERBB2 expression and phosphorylation status; (ii) a potential signaling cross-talk between EGFR or IGF1R and ERBB2, which could influence response of ERBB2-positive BCs to inhibitors. FOXA1 was frequently coexpressed with ERBB2 but its expression did not impact on the outcome of patients with ERBB2-amplified tumors. Conclusion: We have shown that ER+ and ER- ERBB2-amplified BCs are different, distinguished ERBB2 amplicons in IBC and non-IBC, and identified genomic features that may be useful in the design of alternative therapeutical strategies. [ABSTRACT FROM AUTHOR]

Background: Many alterations are involved in mammary oncogenesis, including amplifications of oncogenes and losses of tumor suppressor genes (TSG). Losses may affect almost all chromosome arms and many TSGs remain to be identified. Results: We studied 307 primary breast tumors and 47 breast cancer cell lines by high resolution array comparative genomic hybridization (aCGH). We identified a region on 18p11.31 lost in about 20% of the tumors and 40% of the cell lines. The minimal common region of loss (Chr18:6,366,938-6,375,929 bp) targeted the L3MBTL4 gene. This gene was also targeted by breakage in one tumor and in two cell lines. We studied the exon sequence of L3MBTL4 in 180 primary tumor samples and 47 cell lines and found six missense and one nonsense heterozygous mutations. Compared with normal breast tissue, L3MBTL4 mRNA expression was downregulated in 73% of the tumors notably in luminal, ERBB2 and normal-like subtypes. Losses of the 18p11 region were associated with low L3MBTL4 expression level. Integrated analysis combining genome and gene expression profiles of the same tumors pointed to 14 other potential 18p TSG candidates. Downregulated expression of ZFP161, PPP4R1 and YES1 was correlated with luminal B molecular subtype. Low ZFP161 gene expression was associated with adverse clinical outcome. Conclusion: We have identified L3MBTL4 as a potential TSG of chromosome arm 18p. The gene is targeted by deletion, breakage and mutations and its mRNA is downregulated in breast tumors. Additional 18p TSG candidates might explain the aggressive phenotype associated with the loss of 18p in breast tumors. [ABSTRACT FROM AUTHOR]

Background: Oncogene amplification and overexpression occur in tumor cells. Amplification status may provide diagnostic and prognostic information and may lead to new treatment strategies. Chromosomal regions 8p12, 8q24, 11q13, 17q12 and 20q13 are recurrently amplified in breast cancers. Methods: To assess the frequencies and clinical impact of amplifications, we analyzed 547 invasive breast tumors organized in a tissue microarray (TMA) by fluorescence in situ hybridization (FISH) and calculated correlations with histoclinical features and prognosis. BAC probes were designed for: (i) two 8p12 subregions centered on RAB11FIP1 and FGFR1 loci, respectively; (ii) 11q13 region centered on CCND1; (iii) 12p13 region spanning NOL1; and (iv) three 20q13 subregions centered on MYBL2, ZNF217 and AURKA, respectively. Regions 8q24 and 17q12 were analyzed with MYC and ERBB2 commercial probes, respectively. Results: We observed amplification of 8p12 (amplified at RAB11FIP1 and/or FGFR1) in 22.8%, 8q24 in 6.1%, 11q13 in 19.6%, 12p13 in 4.1%, 17q12 in 9.9%, 20q13Z (amplified at ZNF217 only) in 9.9%, and 20q13Co (co-amplification of two or three 20q13 loci) in 8.5% of cases. The 8q24, 12p13, and 17q12 amplifications were correlated with high grade. The most frequent single amplifications were 8p12 (9.8%), 8q24 (3.3%) and 12p13 (3.3%), 20q13Z and 20q13Co (1.6%) regions. The 17q12 and 11q13 regions were never found amplified alone. The most frequent co-amplification was 8p12/11q13. Amplifications of 8p12 and 17q12 were associated with poor outcome. Amplification of 12p13 was associated with basal molecular subtype. Conclusion: Our results establish the frequencies, prognostic impacts and subtype associations of various amplifications and co-amplifications in breast cancers. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "E2F4 regulatory program predicts patient survival prognosis in breast cancer" by S. S. Khaleel and colleagues that was published in the previous issue.

Background: Solitary Fibrous Tumours (SFT) and haemangiopericytomas (HPC) are rare meningeal tumours that have to be distinguished from meningiomas and more rarely from synovial sarcomas. We recently found that ALDH1A1 was overexpressed in SFT and HPC as compared to soft tissue sarcomas. Using whole-genome DNA microarrays, we defined the gene expression profiles of 16 SFT/HPC (9 HPC and 7 SFT). Expression profiles were compared to publicly available expression profiles of additional SFT or HPC, meningiomas and synovial sarcomas. We also performed an immunohistochemical (IHC) study with anti-ALDH1 and anti-CD34 antibodies on Tissue Micro-Arrays including 38 SFT (25 meningeal and 13 extrameningeal), 55 meningeal haemangiopericytomas (24 grade II, 31 grade III), 163 meningiomas (86 grade I, 62 grade II, 15 grade III) and 98 genetically confirmed synovial sarcomas., Results: ALDH1A1 gene was overexpressed in SFT/HPC, as compared to meningiomas and synovial sarcomas. These findings were confirmed at the protein level. 84% of the SFT and 85.4% of the HPC were positive with anti-ALDH1 antibody, while only 7.1% of synovial sarcomas and 1.2% of meningiomas showed consistent expression. Positivity was usually more diffuse in SFT/HPC compared to other tumours with more than 50% of tumour cells immunostained in 32% of SFT and 50.8% of HPC. ALDH1 was a sensitive and specific marker for the diagnosis of SFT (SE = 84%, SP = 98.8%) and HPC (SE = 84.5%, SP = 98.7%) of the meninges. In association with CD34, ALDH1 expression had a specificity and positive predictive value of 100%., Conclusion: We show that ALDH1, a stem cell marker, is an accurate diagnostic marker for SFT and HPC, which improves the diagnostic value of CD34. ALDH1 could also be a new therapeutic target for these tumours which are not sensitive to conventional chemotherapy.

Background: Basal breast cancers (BCs) represent ~15% of BCs. Although overall poor, prognosis is heterogeneous. Identification of good- versus poor-prognosis patients is difficult or impossible using the standard histoclinical features and the recently defined prognostic gene expression signatures (GES). Kinases are often activated or overexpressed in cancers, and constitute targets for successful therapies. We sought to define a prognostic model of basal BCs based on kinome expression profiling., Methods: DNA microarray-based gene expression and histoclinical data of 2515 early BCs from thirteen datasets were collected. We searched for a kinome-based GES associated with disease-free survival (DFS) in basal BCs of the learning set using a metagene-based approach. The signature was then tested in basal tumors of the independent validation set., Results: A total of 591 samples were basal. We identified a 28-kinase metagene associated with DFS in the learning set (N = 73). This metagene was associated with immune response and particularly cytotoxic T-cell response. On multivariate analysis, a metagene-based predictor outperformed the classical prognostic factors, both in the learning and the validation (N = 518) sets, independently of the lymphocyte infiltrate. In the validation set, patients whose tumors overexpressed the metagene had a 78% 5-year DFS versus 54% for other patients (p = 1.62E-4, log-rank test)., Conclusions: Based on kinome expression, we identified a predictor that separated basal BCs into two subgroups of different prognosis. Tumors associated with higher activation of cytotoxic tumor-infiltrative lymphocytes harbored a better prognosis. Such classification should help tailor the treatment and develop new therapies based on immune response manipulation.

Introduction: Breast cancer is a complex and heterogeneous disease at the molecular level. Evolution is difficult to predict according to classical histoclinical prognostic factors. Different studies highlight the importance of large-scale molecular expression analyses to improve taxonomy of breast cancer and prognostic classification. Identification of new molecular markers that refine this taxonomy and improve patient management is a priority in the field of breast cancer research.Nectins are cell adhesion molecules involved in the regulation of epithelial physiology. We present here Nectin-4/PVRL4 as a new histological and serological tumor associated marker for breast carcinoma., Methods: Expression of Nectin-4 protein was measured on a panel of 78 primary cells and cell lines from different origins and 57 breast tumors by FACS analysis and immunohistochemistry (IHC), respectively. mRNA expression was measured by quantitative PCR. Serum Nectin-4 was detected by ELISA and compared with CEA and CA15.3 markers, on panels of 45 sera from healthy donors, 53 sera from patients with non-metastatic breast carcinoma (MBC) at diagnosis, and 182 sera from patients with MBC. Distribution of histological/serological molecular markers and histoclinical parameters were compared using the standard Chi-2 test., Results: Nectin-4 was not detected in normal breast epithelium. By contrast, Nectin-4 was expressed in 61% of ductal breast carcinoma vs 6% in lobular type. Expression of Nectin-4 strongly correlated with the basal-like markers EGFR, P53, and P-cadherin, and negatively correlated with the luminal-like markers ER, PR and GATA3. All but one ER/PR-negative tumors expressed Nectin-4. The detection of Nectin-4 in serum improves the follow-up of patients with MBC: the association CEA/CA15.3/Nectin-4 allowed to monitor 74% of these patients compared to 67% with the association CEA/CA15.3. Serum Nectin-4 is a marker of disease progression, and levels correlate with the number of metastases (P = 0.038). Serum Nectin-4 is also a marker of therapeutic efficiency and correlates, in 90% of cases, with clinical evolution., Conclusion: Nectin-4 is a new tumor-associated antigen for breast carcinoma. Nectin-4 is a new bio-marker whose use could help refine breast cancer taxonomy and improve patients' follow-up. Nectin-4 emerges as a potential target for breast cancer immunotherapy.