Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

<p>Abstract</p> <p>Background</p> <p>Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms.</p> <p>Results</p> <p>The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies.</p> <p>Conclusions</p> <p>We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package <it>rocc </it>is freely available at <url>http://cran.r-project.org/web/packages/rocc/index.html</url>.</p

RGG: A general GUI Framework for R scripts

<p>Abstract</p> <p>Background</p> <p>R is the leading open source statistics software with a vast number of biostatistical and bioinformatical analysis packages. To exploit the advantages of R, extensive scripting/programming skills are required.</p> <p>Results</p> <p>We have developed a software tool called R GUI Generator (RGG) which enables the easy generation of Graphical User Interfaces (GUIs) for the programming language R by adding a few Extensible Markup Language (XML) – tags. RGG consists of an XML-based GUI definition language and a Java-based GUI engine. GUIs are generated in runtime from defined GUI tags that are embedded into the R script. User-GUI input is returned to the R code and replaces the XML-tags. RGG files can be developed using any text editor. The current version of RGG is available as a stand-alone software (RGGRunner) and as a plug-in for JGR.</p> <p>Conclusion</p> <p>RGG is a general GUI framework for R that has the potential to introduce R statistics (R packages, built-in functions and scripts) to users with limited programming skills and helps to bridge the gap between R developers and GUI-dependent users. RGG aims to abstract the GUI development from individual GUI toolkits by using an XML-based GUI definition language. Thus RGG can be easily integrated in any software. The RGG project further includes the development of a web-based repository for RGG-GUIs. RGG is an open source project licensed under the Lesser General Public License (LGPL) and can be downloaded freely at <url>http://rgg.r-forge.r-project.org</url></p

An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized.Whole-genome DNA methylation analysis using Illumina Infinium HumanMethylation450 BeadChip arrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The Cancer Genome Atlas data, including methylation profiles of 669 human breast tumors, was used for validation. The identified epitypes were characterized by integration with publicly available genome-wide data, including gene expression levels, DNA copy numbers, whole-exome sequencing data, and chromatin states.We identified seven breast cancer epitypes. One epitype was distinctly associated with basal-like tumors and with BRCA1 mutations, one epitype contained a subset of ERBB2-amplified tumors characterized by multiple additional amplifications and the most complex genomes, and one epitype displayed a methylation profile similar to normal epithelial cells. Luminal tumors were stratified into the remaining four epitypes, with differences in promoter hypermethylation, global hypomethylation, proliferative rates, and genomic instability. Specific hyper- and hypomethylation across the basal-like epitype was rare. However, we observed that the candidate genomic instability drivers BRCA1 and HORMAD1 displayed aberrant methylation linked to gene expression levels in some basal-like tumors. Hypomethylation in luminal tumors was associated with DNA repeats and subtelomeric regions. We observed two dominant patterns of aberrant methylation in breast cancer. One pattern, constitutively methylated in both basal-like and luminal breast cancer, was linked to genes with promoters in a Polycomb-repressed state in normal epithelial cells and displayed no correlation with gene expression levels. The second pattern correlated with gene expression levels and was associated with methylation in luminal tumors and genes with active promoters in normal epithelial cells.Our results suggest that hypermethylation patterns across basal-like breast cancer may have limited influence on tumor progression and instead reflect the repressed chromatin state of the tissue of origin. On the contrary, hypermethylation patterns specific to luminal breast cancer influence gene expression, may contribute to tumor progression, and may present an actionable epigenetic alteration in a subset of luminal breast cancers.Swedish Cancer Society Swedish Research Counci

A Molecular Taxonomy for Urothelial Carcinoma.

PURPOSE: Even though urothelial cancer is the fourth most common tumor type among males, progress in treatment has been scarce. A problem in day-to-day clinical practice is that precise assessment of individual tumors is still fairly uncertain; consequently efforts have been undertaken to complement tumor evaluation with molecular biomarkers. An extension of this approach would be to base tumor classification primarily on molecular features. Here, we present a molecular taxonomy for urothelial carcinoma based on integrated genomics. EXPERIMENTAL DESIGN: We use gene expression profiles from 308 tumor cases to define five major urothelial carcinoma subtypes: urobasal A, genomically unstable, urobasal B, squamous cell carcinoma like, and an infiltrated class of tumors. Tumor subtypes were validated in three independent publically available data sets. The expression of 11 key genes was validated at the protein level by immunohistochemistry. RESULTS: The subtypes show distinct clinical outcomes and differ with respect to expression of cell-cycle genes, receptor tyrosine kinases particularly FGFR3, ERBB2, and EGFR, cytokeratins, and cell adhesion genes, as well as with respect to FGFR3, PIK3CA, and TP53 mutation frequency. The molecular subtypes cut across pathologic classification, and class-defining gene signatures show coordinated expression irrespective of pathologic stage and grade, suggesting the molecular phenotypes as intrinsic properties of the tumors. Available data indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathologic classification. CONCLUSIONS: We anticipate that the molecular taxonomy will be useful in future clinical investigations. Clin Cancer Res; 1-10. ©2012 AACR

PicoTesla absolute field readings with a hybrid 3He/87Rb magnetometer

We demonstrate the use of a hybrid 3He/87 magnetometer to measure absolute magnetic fields in the pT range. The measurements were undertaken by probing time-dependent 3He magnetisation using 87Rb zero-field magnetometers. Measurements were taken to demonstrate the use of the magnetometer in cancelling residual fields within a magnetic shield. It was shown that the absolute field could be reduced to the 10 pT level by using field readings from the magnetometer. Furthermore, the hybrid magnetometer was shown to be applicable for the reduction of gradient fields by optimising the effective 3He T2 time. This procedure represents a convenient and consistent way to provide a near zero magnetic field environment which can be potentially used as a base for generating desired magnetic field configurations for use in precision measurements

Efficacy of novel immunotherapy regimens in patients with metastatic melanoma with germline CDKN2A mutations

Inherited CDKN2A mutation is a strong risk factor for cutaneous melanoma. Moreover, carriers have been found to have poor melanoma-specific survival. In this study, responses to novel immunotherapy agents in CDKN2A mutation carriers with metastatic melanoma were evaluated

Efficacy of novel immunotherapy regimens in patients with metastatic melanoma with germline CDKN2A mutations

Background: Inherited CDKN2A mutation is a strong risk factor for cutaneous melanoma. Moreover, carriers have been found to have poor melanoma-specific survival. In this study, responses to novel immunotherapy agents in CDKN2A mutation carriers with metastatic melanoma were evaluated. Methods: CDKN2A mutation carriers that have developed metastatic melanoma and undergone immunotherapy treatments were identified among carriers enrolled in follow-up studies for familial melanoma. The carriers' responses were compared with responses reported in phase III clinical trials for CTLA-4 and PD-1 inhibitors. From publicly available data sets, melanomas with somatic CDKN2A mutation were analysed for association with tumour mutational load. Results: Eleven of 19 carriers (58%) responded to the therapy, a significantly higher frequency than observed in clinical trials (p=0.03, binomial test against an expected rate of 37%). Further, 6 of the 19 carriers (32%) had complete response, a significantly higher frequency than observed in clinical trials (p=0.01, binomial test against an expected rate of 7%). In 118 melanomas with somatic CDKN2A mutations, significantly higher total numbers of mutations were observed compared with 761 melanomas without CDKN2A mutation (Wilcoxon test, p<0.001). Conclusion: Patients with CDKN2A mutated melanoma may have improved immunotherapy responses due to increased tumour mutational load, resulting in more neoantigens and stronger antitumorous immune responses

Integrated Genomic and Gene Expression Profiling Identifies Two Major Genomic Circuits in Urothelial Carcinoma

Similar to other malignancies, urothelial carcinoma (UC) is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21), and BCL2L1 (20q11). We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development