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Find video protocols related to scientific articles indexed in Pubmed.
Genome-driven integrated classification of breast cancer validated in over 7,500 samples.
Genome Biol.
PUBLISHED: 08-28-2014
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IntClust is a classification of breast cancer comprising 10 subtypes based on molecular drivers identified through the integration of genomic and transcriptomic data from 1,000 breast tumors and validated in a further 1,000. We present a reliable method for subtyping breast tumors into the IntClust subtypes based on gene expression and demonstrate the clinical and biological validity of the IntClust classification.
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A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer.
Mol Oncol
PUBLISHED: 08-08-2014
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Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER-) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER- disease. None of the expression-based predictors were prognostic in the ER- subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER- breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer.
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TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance.
Clin. Cancer Res.
PUBLISHED: 05-06-2014
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In breast cancer, the TP53 gene is frequently mutated and the mutations have been associated with poor prognosis. The prognostic impact of the different types of TP53 mutations across the different molecular subtypes is still poorly understood. Here, we characterize the spectrum and prognostic significance of TP53 mutations with respect to the PAM50 subtypes and integrative clusters (IC).
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Amplification of TRIM44: pairing a prognostic target with potential therapeutic strategy.
J. Natl. Cancer Inst.
PUBLISHED: 04-28-2014
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Many prognostic biomarkers have been proposed recently. However, there is a lack of therapeutic strategies exploiting novel prognostic biomarkers. We aimed to propose therapeutic options in patients with overexpression of TRIM44, a recently identified prognostic gene.
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Genomic and protein expression analysis reveals flap endonuclease 1 (FEN1) as a key biomarker in breast and ovarian cancer.
Mol Oncol
PUBLISHED: 02-25-2014
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FEN1 has key roles in Okazaki fragment maturation during replication, long patch base excision repair, rescue of stalled replication forks, maintenance of telomere stability and apoptosis. FEN1 may be dysregulated in breast and ovarian cancers and have clinicopathological significance in patients. We comprehensively investigated FEN1 mRNA expression in multiple cohorts of breast cancer [training set (128), test set (249), external validation (1952)]. FEN1 protein expression was evaluated in 568 oestrogen receptor (ER) negative breast cancers, 894 ER positive breast cancers and 156 ovarian epithelial cancers. FEN1 mRNA overexpression was highly significantly associated with high grade (p = 4.89 × 10(-57)), high mitotic index (p = 5.25 × 10(-28)), pleomorphism (p = 6.31 × 10(-19)), ER negative (p = 9.02 × 10(-35)), PR negative (p = 9.24 × 10(-24)), triple negative phenotype (p = 6.67 × 10(-21)), PAM50.Her2 (p = 5.19 × 10(-13)), PAM50. Basal (p = 2.7 × 10(-41)), PAM50.LumB (p = 1.56 × 10(-26)), integrative molecular cluster 1 (intClust.1) (p = 7.47 × 10(-12)), intClust.5 (p = 4.05 × 10(-12)) and intClust. 10 (p = 7.59 × 10(-38)) breast cancers. FEN1 mRNA overexpression is associated with poor breast cancer specific survival in univariate (p = 4.4 × 10(-16)) and multivariate analysis (p = 9.19 × 10(-7)). At the protein level, in ER positive tumours, FEN1 overexpression remains significantly linked to high grade, high mitotic index and pleomorphism (ps < 0.01). In ER negative tumours, high FEN1 is significantly associated with pleomorphism, tumour type, lymphovascular invasion, triple negative phenotype, EGFR and HER2 expression (ps < 0.05). In ER positive as well as in ER negative tumours, FEN1 protein overexpression is associated with poor survival in univariate and multivariate analysis (ps < 0.01). In ovarian epithelial cancers, similarly, FEN1 overexpression is associated with high grade, high stage and poor survival (ps < 0.05). We conclude that FEN1 is a promising biomarker in breast and ovarian epithelial cancer.
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JARID1B is a luminal lineage-driving oncogene in breast cancer.
Cancer Cell
PUBLISHED: 02-12-2014
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Recurrent mutations in histone-modifying enzymes imply key roles in tumorigenesis, yet their functional relevance is largely unknown. Here, we show that JARID1B, encoding a histone H3 lysine 4 (H3K4) demethylase, is frequently amplified and overexpressed in luminal breast tumors and a somatic mutation in a basal-like breast cancer results in the gain of unique chromatin binding and luminal expression and splicing patterns. Downregulation of JARID1B in luminal cells induces basal genes expression and growth arrest, which is rescued by TGF? pathway inhibitors. Integrated JARID1B chromatin binding, H3K4 methylation, and expression profiles suggest a key function for JARID1B in luminal cell-specific expression programs. High luminal JARID1B activity is associated with poor outcome in patients with hormone receptor-positive breast tumors.
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Urinary arsenic levels influenced by abandoned mine tailings in the Southernmost Baja California Peninsula, Mexico.
Environ Geochem Health
PUBLISHED: 02-08-2014
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Gold has been mined at San Antonio-El Triunfo, (Baja California Sur, Mexico) since the 18th century. This area has approximately 5,700 inhabitants living in the San Juan de Los Planes and El Carrizal hydrographic basins, close to more than 100 abandoned mining sites containing tailings contaminated with potentially toxic elements such as arsenic. To evaluate the arsenic exposure of humans living in the surrounding areas, urinary arsenic species, such as inorganic arsenic (iAs) and the metabolites mono-methylated (MMA) and di-methylated arsenic acids (DMA), were evaluated in 275 residents (18-84 years of age). Arsenic species in urine were analyzed by hydride generation-cryotrapping-atomic absorption spectrometry, which excludes the non-toxic forms of arsenic such as those found in seafood. Urinary samples contained a total arsenic concentration (sum of arsenical species) which ranged from 1.3 to 398.7 ng mL(-1), indicating 33% of the inhabitants exceeded the biological exposition index (BEI = 35 ng mL(-1)), the permissible limit for occupational exposure. The mean relative urinary arsenic species were 9, 11 and 80% for iAs, MMA and DMA, respectively, in the Los Planes basin, and 17, 10 and 73%, respectively, in the El Carrizal basin. These data indicated that environmental intervention is required to address potential health issues in this area.
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Master regulators of FGFR2 signalling and breast cancer risk.
Nat Commun
PUBLISHED: 05-03-2013
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The fibroblast growth factor receptor 2 (FGFR2) locus has been consistently identified as a breast cancer risk locus in independent genome-wide association studies. However, the molecular mechanisms underlying FGFR2-mediated risk are still unknown. Using model systems we show that FGFR2-regulated genes are preferentially linked to breast cancer risk loci in expression quantitative trait loci analysis, supporting the concept that risk genes cluster in pathways. Using a network derived from 2,000 transcriptional profiles we identify SPDEF, ER?, FOXA1, GATA3 and PTTG1 as master regulators of fibroblast growth factor receptor 2 signalling, and show that ER? occupancy responds to fibroblast growth factor receptor 2 signalling. Our results indicate that ER?, FOXA1 and GATA3 contribute to the regulation of breast cancer susceptibility genes, which is consistent with the effects of anti-oestrogen treatment in breast cancer prevention, and suggest that fibroblast growth factor receptor 2 signalling has an important role in mediating breast cancer risk.
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Improving breast cancer survival analysis through competition-based multidimensional modeling.
PLoS Comput. Biol.
PUBLISHED: 05-01-2013
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Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.
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Systematic analysis of challenge-driven improvements in molecular prognostic models for breast cancer.
Sci Transl Med
PUBLISHED: 04-19-2013
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Although molecular prognostics in breast cancer are among the most successful examples of translating genomic analysis to clinical applications, optimal approaches to breast cancer clinical risk prediction remain controversial. The Sage Bionetworks-DREAM Breast Cancer Prognosis Challenge (BCC) is a crowdsourced research study for breast cancer prognostic modeling using genome-scale data. The BCC provided a community of data analysts with a common platform for data access and blinded evaluation of model accuracy in predicting breast cancer survival on the basis of gene expression data, copy number data, and clinical covariates. This approach offered the opportunity to assess whether a crowdsourced community Challenge would generate models of breast cancer prognosis commensurate with or exceeding current best-in-class approaches. The BCC comprised multiple rounds of blinded evaluations on held-out portions of data on 1981 patients, resulting in more than 1400 models submitted as open source code. Participants then retrained their models on the full data set of 1981 samples and submitted up to five models for validation in a newly generated data set of 184 breast cancer patients. Analysis of the BCC results suggests that the best-performing modeling strategy outperformed previously reported methods in blinded evaluations; model performance was consistent across several independent evaluations; and aggregating community-developed models achieved performance on par with the best-performing individual models.
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Analysis of circulating tumor DNA to monitor metastatic breast cancer.
N. Engl. J. Med.
PUBLISHED: 03-13-2013
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The management of metastatic breast cancer requires monitoring of the tumor burden to determine the response to treatment, and improved biomarkers are needed. Biomarkers such as cancer antigen 15-3 (CA 15-3) and circulating tumor cells have been widely studied. However, circulating cell-free DNA carrying tumor-specific alterations (circulating tumor DNA) has not been extensively investigated or compared with other circulating biomarkers in breast cancer.
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Finding common regions of alteration in copy number data.
Methods Mol. Biol.
PUBLISHED: 02-16-2013
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In this chapter, we review some recent methods designed for detecting recurrent copy number regions, that is, genomic regions that show evidence of being altered in a set of samples. We analyze Affymetrix SNP6 data from 87 Her2-type breast tumors from a recent study using three different methods, showing different definitions and features of common regions: studying heterogeneity in copy number profiles, refining candidates for driver oncogenes, and consolidating broad amplifications.
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Chronic stress and calcium oxalate stone disease: influence on blood cortisol and urine composition.
Urology
PUBLISHED: 02-10-2013
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To evaluate the influence of chronic stress (CS) on urine composition of calcium oxalate (CaOx) stone patients and controls.
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A new genome-driven integrated classification of breast cancer and its implications.
EMBO J.
PUBLISHED: 01-17-2013
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Breast cancer is a group of heterogeneous diseases that show substantial variation in their molecular and clinical characteristics. This heterogeneity poses significant challenges not only in breast cancer management, but also in studying the biology of the disease. Recently, rapid progress has been made in understanding the genomic diversity of breast cancer. These advances led to the characterisation of a new genome-driven integrated classification of breast cancer, which substantially refines the existing classification systems currently used. The novel classification integrates molecular information on the genomic and transcriptomic landscapes of breast cancer to define 10 integrative clusters, each associated with distinct clinical outcomes and providing new insights into the underlying biology and potential molecular drivers. These findings have profound implications both for the individualisation of treatment approaches, bringing us a step closer to the realisation of personalised cancer management in breast cancer, but also provide a new framework for studying the underlying biology of each novel subtype.
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Endogenous purification reveals GREB1 as a key estrogen receptor regulatory factor.
Cell Rep
PUBLISHED: 01-14-2013
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Estrogen receptor-? (ER) is the driving transcription factor in most breast cancers, and its associated proteins can influence drug response, but direct methods for identifying interacting proteins have been limited. We purified endogenous ER using an approach termed RIME (rapid immunoprecipitation mass spectrometry of endogenous proteins) and discovered the interactome under agonist- and antagonist-liganded conditions in breast cancer cells, revealing transcriptional networks in breast cancer. The most estrogen-enriched ER interactor is GREB1, a potential clinical biomarker with no known function. GREB1 is shown to be a chromatin-bound ER coactivator and is essential for ER-mediated transcription, because it stabilizes interactions between ER and additional cofactors. We show a GREB1-ER interaction in three xenograft tumors, and using a directed protein-protein approach, we find GREB1-ER interactions in half of ER(+) primary breast cancers. This finding is supported by histological expression of GREB1, which shows that GREB1 is expressed in half of ER(+) cancers, and predicts good clinical outcome. These findings reveal an unexpected role for GREB1 as an estrogen-specific ER cofactor that is expressed in drug-sensitive contexts.
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A prognostic gene signature for metastasis-free survival of triple negative breast cancer patients.
PLoS ONE
PUBLISHED: 01-01-2013
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Although triple negative breast cancers (TNBC) are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS), based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP). We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS) that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.
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Penalized regression elucidates aberration hotspots mediating subtype-specific transcriptional responses in breast cancer.
Bioinformatics
PUBLISHED: 07-30-2011
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Copy number alterations (CNAs) associated with cancer are known to contribute to genomic instability and gene deregulation. Integrating CNAs with gene expression helps to elucidate the mechanisms by which CNAs act and to identify the transcriptional downstream targets of CNAs. Such analyses can help to sort functional driver events from the many accompanying passenger alterations. However, the way CNAs affect gene expression can vary in different cellular contexts, for example between different subtypes of the same cancer. Thus, it is important to develop computational approaches capable of inferring differential connectivity of regulatory networks in different cellular contexts.
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ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium.
EMBO Mol Med
PUBLISHED: 01-16-2011
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The telomeric amplicon at 8p12 is common in oestrogen receptor-positive (ER+) breast cancers. Array-CGH and expression analyses of 1172 primary breast tumours revealed that ZNF703 was the single gene within the minimal amplicon and was amplified predominantly in the Luminal B subtype. Amplification was shown to correlate with increased gene and protein expression and was associated with a distinct expression signature and poor clinical outcome. ZNF703 transformed NIH 3T3 fibroblasts, behaving as a classical oncogene, and regulated proliferation in human luminal breast cancer cell lines and immortalized human mammary epithelial cells. Manipulation of ZNF703 expression in the luminal MCF7 cell line modified the effects of TGF? on proliferation. Overexpression of ZNF703 in normal human breast epithelial cells enhanced the frequency of in vitro colony-forming cells from luminal progenitors. Taken together, these data strongly point to ZNF703 as a novel oncogene in Luminal B breast cancer.
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waviCGH: a web application for the analysis and visualization of genomic copy number alterations.
Nucleic Acids Res.
PUBLISHED: 05-27-2010
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waviCGH is a versatile web server for the analysis and comparison of genomic copy number alterations in multiple samples from any species. waviCGH processes data generated by high density SNP-arrays, array-CGH or copy-number calls generated by any technique. waviCGH includes methods for pre-processing of the data, segmentation, calling of gains and losses, and minimal common regions determination over a set of experiments. The server is a user-friendly interface to the analytical methods, with emphasis on results visualization in a genomic context. Analysis tools are introduced to the user as the different steps to follow in an experimental protocol. All the analysis steps generate high quality images and tables ready to be imported into spreadsheet programs. Additionally, for human, mouse and rat, altered regions are represented in a biological context by mapping them into chromosomes in an integrated cytogenetic browser. waviCGH is available at http://wavi.bioinfo.cnio.es.
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RJaCGH: Bayesian analysis of aCGH arrays for detecting copy number changes and recurrent regions.
Bioinformatics
PUBLISHED: 05-06-2009
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Several methods have been proposed to detect copy number changes and recurrent regions of copy number variation from aCGH, but few methods return probabilities of alteration explicitly, which are the direct answer to the question is this probe/region altered? RJaCGH fits a Non-Homogeneous Hidden Markov model to the aCGH data using Markov Chain Monte Carlo with Reversible Jump, and returns the probability that each probe is gained or lost. Using these probabilites, recurrent regions (over sets of individuals) of copy number alteration can be found.
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Detection of recurrent copy number alterations in the genome: taking among-subject heterogeneity seriously.
BMC Bioinformatics
PUBLISHED: 04-01-2009
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Alterations in the number of copies of genomic DNA that are common or recurrent among diseased individuals are likely to contain disease-critical genes. Unfortunately, defining common or recurrent copy number alteration (CNA) regions remains a challenge. Moreover, the heterogeneous nature of many diseases requires that we search for common or recurrent CNA regions that affect only some subsets of the samples (without knowledge of the regions and subsets affected), but this is neglected by most methods.
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Copynumber: Efficient algorithms for single- and multi-track copy number segmentation.
BMC Genomics
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Cancer progression is associated with genomic instability and an accumulation of gains and losses of DNA. The growing variety of tools for measuring genomic copy numbers, including various types of array-CGH, SNP arrays and high-throughput sequencing, calls for a coherent framework offering unified and consistent handling of single- and multi-track segmentation problems. In addition, there is a demand for highly computationally efficient segmentation algorithms, due to the emergence of very high density scans of copy number.
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Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.
Sci Transl Med
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Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.
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TGF? induces the formation of tumour-initiating cells in claudinlow breast cancer.
Nat Commun
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The role of transforming growth factor-beta (TGF?) in the progression of different molecular subtypes of breast cancer has not been clarified. Here we show that TGF? increases breast tumour-initiating cell (BTIC) numbers but only in claudin(low) breast cancer cell lines by orchestrating a specific gene signature enriched in stem cell processes that predicts worse clinical outcome in breast cancer patients. NEDD9, a member of the Cas family of integrin scaffold proteins, is necessary to mediate these TGF?-specific effects through a positive feedback loop that integrates TGF?/Smad and Rho-actin-SRF-dependent signals. In normal human mammary epithelium, TGF? induces progenitor activity only in the basal/stem cell compartment, where claudin(low) cancers are presumed to arise. These data show opposing responses to TGF? in both breast malignant cell subtypes and normal mammary epithelial cell subpopulations and suggest therapeutic strategies for a subset of human breast cancers.
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The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.
Nature
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The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (copy number variants and single nucleotide polymorphisms) and acquired somatic copy number aberrations (CNAs) were associated with expression in ~40% of genes, with the landscape dominated by cis- and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP and MAP2K4. Unsupervised analysis of paired DNA–RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, oestrogen-receptor-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the ‘CNA-devoid’ subgroup and a basal-specific chromosome 5 deletion-associated mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic CNAs on the transcriptome.
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The clonal and mutational evolution spectrum of primary triple-negative breast cancers.
Nature
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Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed. Using deep re-sequencing measurements of allelic abundance for 2,414 somatic mutations, we determine for the first time-to our knowledge-in an epithelial tumour subtype, the relative abundance of clonal frequencies among cases representative of the population. We show that TNBCs vary widely in their clonal frequencies at the time of diagnosis, with the basal subtype of TNBC showing more variation than non-basal TNBC. Although p53 (also known as TP53), PIK3CA and PTEN somatic mutations seem to be clonally dominant compared to other genes, in some tumours their clonal frequencies are incompatible with founder status. Mutations in cytoskeletal, cell shape and motility proteins occurred at lower clonal frequencies, suggesting that they occurred later during tumour progression. Taken together, our results show that understanding the biology and therapeutic responses of patients with TNBC will require the determination of individual tumour clonal genotypes.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.