scholarly journals Platform-Independent Classification System to Predict Molecular Subtypes of High-Grade Serous Ovarian Carcinoma

2019 ◽  
pp. 1-9 ◽  
Author(s):  
Arunima Shilpi ◽  
Manoj Kandpal ◽  
Yanrong Ji ◽  
Brandon L. Seagle ◽  
Shohreh Shahabi ◽  
...  
Keyword(s):  
Classification System ◽  
Molecular Subtypes ◽  
Exon Array ◽  
The Cancer Genome Atlas ◽  
Data Sets ◽  
Rna Seq ◽  
Molecular Subtyping ◽  
Serous Ovarian Carcinoma ◽  
Independent Gene ◽  
Cancer Genome Atlas

PURPOSE Molecular cancer subtyping is an important tool in predicting prognosis and developing novel precision medicine approaches. We developed a novel platform-independent gene expression–based classification system for molecular subtyping of patients with high-grade serous ovarian carcinoma (HGSOC). METHODS Unprocessed exon array (569 tumor and nine normal) and RNA sequencing (RNA-seq; 376 tumor) HGSOC data sets, with clinical annotations, were downloaded from the Genomic Data Commons portal. Sample clustering was performed by non-negative matrix factorization by using isoform-level expression estimates. The association between the subtypes and overall survival was evaluated by Cox proportional hazards regression model after adjusting for the covariates. A novel classification system was developed for HGSOC molecular subtyping. Robustness and generalizability of the gene signatures were validated using independent microarray and RNA-seq data sets. RESULTS Sample clustering recaptured the four known The Cancer Genome Atlas molecular subtypes but switched the subtype for 22% of the cases, which resulted in significant ( P = .006) survival differences among the refined subgroups. After adjusting for covariate effects, the mesenchymal subgroup was found to be at an increased hazard for death compared with the immunoreactive subgroup. Both gene- and isoform-level signatures achieved more than 92% prediction accuracy when tested on independent samples profiled on the exon array platform. When the classifier was applied to RNA-seq data, the subtyping calls agreed with the predictions made from exon array data for 95% of the 279 samples profiled by both platforms. CONCLUSION Isoform-level expression analysis successfully stratifies patients with HGSOC into groups with differing prognosis and has led to the development of robust, platform-independent gene signatures for HGSOC molecular subtyping. The association of the refined The Cancer Genome Atlas HGSOC subtypes with overall survival, independent of covariates, enhances the clinical annotation of the HGSOC cohort.

scholarly journals WebMeV: a Cloud Platform for Analyzing and Visualizing Cancer Genomic Data

2017 ◽  
Author(s):  
Yaoyu E. Wang ◽  
Lev Kuznetsov ◽  
Antony Partensky ◽  
Jalil Farid ◽  
John Quackenbush
Keyword(s):  
Genomic Data ◽  
Data Access ◽  
The Cancer Genome Atlas ◽  
Data Sets ◽  
Rna Seq ◽  
Cloud Platform ◽  
Web Based ◽  
Public Data ◽  
Cancer Genome Atlas ◽  
Effective Use

AbstractAlthough large, complex genomic data sets are increasingly easy to generate, and the number of publicly available data sets in cancer and other diseases is rapidly growing, the lack of intuitive, easy to use analysis tools has remained a barrier to the effective use of such data. WebMeV (https://mev.tm4.org) is an open-source, web-based tool that gives users access to sophisticated tools for analysis of RNA-Seq and other data in an interface designed to democratize data access. WebMeV combines cloud-based technologies with a simple user interface to allow users to access large public data sets such as that from The Cancer Genome Atlas (TCGA) or to upload their own. The interface allows users to visualize data and to apply advanced data mining analysis methods to explore the data and draw biologically meaningful conclusions. We provide an overview of WebMeV and demonstrate two simple use cases that illustrate the value of putting data analysis in the hands of those looking to explore the underlying biology of the systems being studied.

scholarly journals PR/SET Domain Family and Cancer: Novel Insights from the Cancer Genome Atlas

2018 ◽  
Vol 19 (10) ◽  
pp. 3250 ◽  
Author(s):  
Anna Sorrentino ◽  
Antonio Federico ◽  
Monica Rienzo ◽  
Patrizia Gazzerro ◽  
Maurizio Bifulco ◽  
...  
Keyword(s):  
Family Members ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Driver Gene ◽  
Rna Seq ◽  
Set Domain ◽  
Primary Tumors ◽  
Cancer Genome Atlas ◽  
Pan Cancer ◽  
Genome Atlas

The PR/SET domain gene family (PRDM) encodes 19 different transcription factors that share a subtype of the SET domain [Su(var)3-9, enhancer-of-zeste and trithorax] known as the PRDF1-RIZ (PR) homology domain. This domain, with its potential methyltransferase activity, is followed by a variable number of zinc-finger motifs, which likely mediate protein–protein, protein–RNA, or protein–DNA interactions. Intriguingly, almost all PRDM family members express different isoforms, which likely play opposite roles in oncogenesis. Remarkably, several studies have described alterations in most of the family members in malignancies. Here, to obtain a pan-cancer overview of the genomic and transcriptomic alterations of PRDM genes, we reanalyzed the Exome- and RNA-Seq public datasets available at The Cancer Genome Atlas portal. Overall, PRDM2, PRDM3/MECOM, PRDM9, PRDM16 and ZFPM2/FOG2 were the most mutated genes with pan-cancer frequencies of protein-affecting mutations higher than 1%. Moreover, we observed heterogeneity in the mutation frequencies of these genes across tumors, with cancer types also reaching a value of about 20% of mutated samples for a specific PRDM gene. Of note, ZFPM1/FOG1 mutations occurred in 50% of adrenocortical carcinoma patients and were localized in a hotspot region. These findings, together with OncodriveCLUST results, suggest it could be putatively considered a cancer driver gene in this malignancy. Finally, transcriptome analysis from RNA-Seq data of paired samples revealed that transcription of PRDMs was significantly altered in several tumors. Specifically, PRDM12 and PRDM13 were largely overexpressed in many cancers whereas PRDM16 and ZFPM2/FOG2 were often downregulated. Some of these findings were also confirmed by real-time-PCR on primary tumors.

scholarly journals Visual Display of 5p-arm and 3p-arm miRNA Expression with a Mobile Application

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Chao-Yu Pan ◽  
Wei-Ting Kuo ◽  
Chien-Yuan Chiu ◽  
Wen-chang Lin
Keyword(s):  
Mirna Expression ◽  
Expression Patterns ◽  
Mirna Gene ◽  
Visual Display ◽  
Mature Mirnas ◽  
Mobile App ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
User Friendly

MicroRNAs (miRNAs) play important roles in human cancers. In previous studies, we have demonstrated that both 5p-arm and 3p-arm of mature miRNAs could be expressed from the same precursor and we further interrogated the 5p-arm and 3p-arm miRNA expression with a comprehensive arm feature annotation list. To assist biologists to visualize the differential 5p-arm and 3p-arm miRNA expression patterns, we utilized a user-friendly mobile App to display. The Cancer Genome Atlas (TCGA) miRNA-Seq expression information. We have collected over 4,500 miRNA-Seq datasets from 15 TCGA cancer types and further processed them with the 5p-arm and 3p-arm annotation analysis pipeline. In order to be displayed with the RNA-Seq Viewer App, annotated 5p-arm and 3p-arm miRNA expression information and miRNA gene loci information were converted into SQLite tables. In this distinct application, for any given miRNA gene, 5p-arm miRNA is illustrated on the top of chromosome ideogram and 3p-arm miRNA is illustrated on the bottom of chromosome ideogram. Users can then easily interrogate the differentially 5p-arm/3p-arm expressed miRNAs with their mobile devices. This study demonstrates the feasibility and utility of RNA-Seq Viewer App in addition to mRNA-Seq data visualization.

scholarly journals ERK1/2 signaling regulates the immune microenvironment and macrophage recruitment in glioblastoma

2019 ◽  
Vol 39 (9) ◽  
Author(s):  
Claire Lailler ◽  
Christophe Louandre ◽  
Mony Chenda Morisse ◽  
Thomas Lhossein ◽  
Corinne Godin ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Recent Observation ◽  
The Cancer Genome Atlas ◽  
Response To Treatment ◽  
Mrna Levels ◽  
Rna Seq ◽  
Immune Microenvironment ◽  
Oncogenic Signaling ◽  
Cancer Genome Atlas ◽  
Human Gbm

Abstract The tumor microenvironment is an important determinant of glioblastoma (GBM) progression and response to treatment. How oncogenic signaling in GBM cells modulates the composition of the tumor microenvironment and its activation is unclear. We aimed to explore the potential local immunoregulatory function of ERK1/2 signaling in GBM. Using proteomic and transcriptomic data (RNA seq) available for GBM tumors from The Cancer Genome Atlas (TCGA), we show that GBM with high levels of phosphorylated ERK1/2 have increased infiltration of tumor-associated macrophages (TAM) with a non-inflammatory M2 polarization. Using three human GBM cell lines in culture, we confirmed the existence of ERK1/2-dependent regulation of the production of the macrophage chemoattractant CCL2/MCP1. In contrast with this positive regulation of TAM recruitment, we found no evidence of a direct effect of ERK1/2 signaling on two other important aspects of TAM regulation by GBM cells: (1) the expression of the immune checkpoint ligands PD-L1 and PD-L2, expressed at high mRNA levels in GBM compared with other solid tumors; (2) the production of the tumor metabolite lactate recently reported to dampen tumor immunity by interacting with the receptor GPR65 present on the surface of TAM. Taken together, our observations suggest that ERK1/2 signaling regulates the recruitment of TAM in the GBM microenvironment. These findings highlight some potentially important particularities of the immune microenvironment in GBM and could provide an explanation for the recent observation that GBM with activated ERK1/2 signaling may respond better to anti-PD1 therapeutics.

scholarly journals IsoformSwitchAnalyzeR: analysis of changes in genome-wide patterns of alternative splicing and its functional consequences

2019 ◽  
Vol 35 (21) ◽  
pp. 4469-4471 ◽  
Author(s):  
Kristoffer Vitting-Seerup ◽  
Albin Sandelin
Keyword(s):  
Alternative Splicing ◽  
The Cancer Genome Atlas ◽  
Supplementary Information ◽  
Rna Seq ◽  
Genome Wide ◽  
Functional Consequences ◽  
Cancer Genome Atlas ◽  
Health And Disease ◽  
Splicing Patterns

Abstract Summary Alternative splicing is an important mechanism involved in health and disease. Recent work highlights the importance of investigating genome-wide changes in splicing patterns and the subsequent functional consequences. Current computational methods only support such analysis on a gene-by-gene basis. Therefore, we extended IsoformSwitchAnalyzeR R library to enable analysis of genome-wide changes in specific types of alternative splicing and predicted functional consequences of the resulting isoform switches. As a case study, we analyzed RNA-seq data from The Cancer Genome Atlas and found systematic changes in alternative splicing and the consequences of the associated isoform switches. Availability and implementation Windows, Linux and Mac OS: http://bioconductor.org/packages/IsoformSwitchAnalyzeR. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Target variant detection in leukemia using unaligned RNA-Seq reads

2018 ◽  
Author(s):  
Eric Olivier Audemard ◽  
Patrick Gendron ◽  
Vincent-Philippe Lavallée ◽  
Josée Hébert ◽  
Guy Sauvageau ◽  
...  
Keyword(s):  
Variant Calling ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Read Mapping ◽  
Targeted Mutation ◽  
Cancer Genome Atlas ◽  
Computationally Intensive ◽  
And Performance ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

AbstractMutations identified in each Acute Myeloid Leukemia (AML) patients are useful for prognosis and to select targeted therapies. Detection of such mutations by the analysis of Next-Generation Sequencing (NGS) data requires a computationally intensive read mapping step and application of several variant calling methods. Targeted mutation identification drastically shifts the usual tradeoff between accuracy and performance by concentrating all computations over a small portion of sequence space. Here, we present km, an efficient approach leveraging k-mer decomposition of reads to identify targeted mutations. Our approach is versatile, as it can detect single-base mutations, several types of insertions and deletions, as well as fusions. We used two independent AML cohorts (The Cancer Genome Atlas and Leucegene), to show that mutation detection bykmis fast, accurate and mainly limited by sequencing depth. Therefore,kmallows to establish fast diagnostics from NGS data, and could be suitable for clinical applications.

scholarly journals Μελέτη μοριακών σηματοδοτικών μηχανισμών επαγωγής της κυτταρικής επιβίωσης και αποδιαφοροποίησης στον καρκίνο

2019 ◽  
Author(s):  
Ευστάθιος-Ιάσων Βλαχάβας
Keyword(s):  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Ο όρος καρκίνος χρησιμοποιείται όχι για μια ασθένεια, αλλά για ένα ευρύτερο σύνολο συσχετιζόμενων νοσημάτων, οι οποίες περιγράφονται από ένα κοινό χαρακτηριστικό: την αφύσικη ανάπτυξη κυττάρων που διαιρούνται ανεξέλεγκτα και μπορούν να διηθήσουν παρακείμενους ιστούς. Η μελέτη των μοριακών μηχανισμών που εμπλέκονται στη παθοφυσιολογία των καρκίνου, αποτελεί πεδίο έντονης έρευνας, γιατί η κατανόησή τους συνδέεται άμεσα με την ορθή αντιμετώπιση της νόσου. Στην παρούσα διατριβή, εστιάζουμε στον καρκίνο του παχέος εντέρου. Η πλειοψηφία των όγκων του παχέος εντέρου είναι αδενοκαρκινώματα, τα οποία προκύπτουν από τη δημιουργία πολυπόδων που σχηματίζονται στο εσωτερικό τοίχωμα του παχέος εντέρου και μπορούν να εξελιχθούν σε νεοπλασίες. Ο καρκίνος του παχέος εντέρου είναι μια ιδιαίτερα σύνθετη ασθένεια, με έντονα μεταβλητά μοριακά και γενετικά χαρακτηριστικά και με διαφορική απόκριση σε φαρμακευτικά σχήματα. Περίπου το 40% των περιπτώσεων ανιχνεύονται σε πρώιμο στάδιο με το ποσοστό της πενταετούς επιβίωσης να κυμαίνεται στο 90%. Επιπρόσθετα, αποτελεί μια αιτία θνησιμότητας στις χώρες του ανεπτυγμένου κόσμου, κυρίως λόγω του υψηλού μεταστατικού δυναμικού που παρουσιάζει. Συνολικά, τα παραπάνω στοιχεία καθιστούν επιτακτική την αξιοποίηση όλων των διαθέσιμων μοριακών πληροφοριών αλλά και ιατροβιολογικών δεδομένων για την εφαρμογή εξατομικευμένης θεραπείας στα πλαίσια της μεταφραστικής έρευνας.Την τελευταία δεκαετία, η εκτεταμένη αξιοποίηση των τεχνικών υψηλής απόδοσης, όπως οι μικροσυστοιχίες γονιδίων και οι τεχνολογίες αλληλούχισης νέας γενιάς για την ανάλυση της γονιδιακής έκφρασης σε διάφορους τύπους καρκίνου του παχέος εντέρου, συνέβαλε σημαντικά στην ταυτοποίηση σημαντικών γονιδιακών μεταλλαγών και στον χαρακτηρισμό γονιδίων που εμπλέκονται στην παθοφυσιολογία του συγκεκριμένου καρκίνου. Αν και οι τεχνολογίες αλληλούχισης νέας γενιάς παρουσιάζουν σημαντικές τεχνολογικές βελτιώσεις, οι μικροσυστοιχίες DNA εξακολουθούν να παραμένουν δημοφιλείς για την ανάλυση του μεταγραφώματος, αφενός γιατί παραμένουν πιο οικονομικές και αφετέρου προϋποθέτουν μια λιγότερο σύνθετη προετοιμασία δειγμάτων, συγκριτικά με τις μεθοδολογίες αλληλούχισης. Αντιπροσωπευτικά παραδείγματα για τη συμβολή των τεχνολογιών υψηλής απόδοσης αποτελούν ερευνητικές δημοσιεύσεις από τη διεθνή ερευνητική συνεργασία (The Cancer Genome Atlas) για τον μοριακό χαρακτηρισμού του καρκίνου του παχέος εντέρου, καθώς και τον χαρακτηρισμό συγκεκριμένων μοριακών υποτύπων με βάση γονιδιωματικά δεδομένα από διαφορετικές ερευνητικές ομάδες. Ωστόσο, η ιδιαίτερη ετερογένεια που παρουσιάζει ο συγκεκριμένος καρκίνος αλλά και η δυσκολία της ερμηνείας μοριακών δεδομένων υψηλής διαστασιμότητας που προκύπτουν από την ανάλυση μικροσυστοιχιών αλλά και DNA/RNA-Seq τεχνολογιών, δυσχεραίνουν την αξιοποίηση των διαφόρων γονιδιακών υπογραφών που περιγράφουν ένα συγκεκριμένο καρκινικό φαινότυπο, στην κλινική εφαρμογή.

scholarly journals Pan-cancer analysis reveals complex tumor-specific alternative polyadenylation

2017 ◽  
Author(s):  
Zhuyi Xue ◽  
René L Warren ◽  
Ewan A Gibb ◽  
Daniel MacMillan ◽  
Johnathan Wong ◽  
...  
Keyword(s):  
Alternative Polyadenylation ◽  
Length Change ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Rna Seq ◽  
Multiple Cancer ◽  
Tissue Samples ◽  
Cancer Genome Atlas ◽  
Specific Alternative ◽  
Cancer Types

AbstractAlternative polyadenylation (APA) of 3’ untranslated regions (3’ UTRs) has been implicated in cancer development. Earlier reports on APA in cancer primarily focused on 3’ UTR length modifications, and the conventional wisdom is that tumor cells preferentially express transcripts with shorter 3’ UTRs. Here, we analyzed the APA patterns of 114 genes, a select list of oncogenes and tumor suppressors, in 9,939 tumor and 729 normal tissue samples across 33 cancer types using RNA-Seq data from The Cancer Genome Atlas, and we found that the APA regulation machinery is much more complicated than what was previously thought. We report 77 cases (gene-cancer type pairs) of differential 3’ UTR cleavage patterns between normal and tumor tissues, involving 33 genes in 13 cancer types. For 15 genes, the tumor-specific cleavage patterns are recurrent across multiple cancer types. While the cleavage patterns in certain genes indicate apparent trends of 3’ UTR shortening in tumor samples, over half of the 77 cases imply 3’ UTR length change trends in cancer that are more complex than simple shortening or lengthening. This work extends the current understanding of APA regulation in cancer, and demonstrates how large volumes of RNA-seq data generated for characterizing cancer cohorts can be mined to investigate this process.

scholarly journals Explainable autoencoder-based representation learning for gene expression data

2021 ◽  
Author(s):  
Yang Yu ◽  
Pathum Kossinna ◽  
Wenyuan Liao ◽  
Qingrun Zhang
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Hidden Variables ◽  
Representation Learning ◽  
The Cancer Genome Atlas ◽  
Expression Data ◽  
Rna Seq ◽  
Gene Expression Data Analysis ◽  
Cancer Genome Atlas ◽  
Modern Machine

Modern machine learning methods have been extensively utilized in gene expression data analysis. In particular, autoencoders (AE) have been employed in processing noisy and heterogenous RNA-Seq data. However, AEs usually lead to "black-box" hidden variables difficult to interpret, hindering downstream experimental validation and clinical translation. To bridge the gap between complicated models and biological interpretations, we developed a tool, XAE4Exp (eXplainable AutoEncoder for Expression data), which integrates AE and SHapley Additive exPlanations (SHAP), a flagship technique in the field of eXplainable AI (XAI). It quantitatively evaluates the contributions of each gene to the hidden structure learned by an AE, substantially improving the expandability of AE outcomes. By applying XAE4Exp to The Cancer Genome Atlas (TCGA) breast cancer gene expression data, we identified genes that are not differentially expressed, and pathways in various cancer-related classes. This tool will enable researchers and practitioners to analyze high-dimensional expression data intuitively, paving the way towards broader uses of deep learning.

scholarly journals Comprehensive analysis based on DNA methylation and RNA-seq reveals hypermethylation of the up-regulated WT1 gene with potential mechanisms in PAM50 subtypes of breast cancer

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11377
Author(s):  
Chongyang Ren ◽  
Xiaojiang Tang ◽  
Haitao Lan
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Mechanisms ◽  
Molecular Subtypes ◽  
Wilms Tumor ◽  
Expression Profiles ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Body Region ◽  
Rna Seq

Background Breast cancer (BC), one of the most widespread cancers worldwide, caused the deaths of more than 600,000 women in 2018, accounting for about 15% of all cancer-associated deaths in women that year. In this study, we aimed to discover potential prognostic biomarkers and explore their molecular mechanisms in different BC subtypes using DNA methylation and RNA-seq. Methods We downloaded the DNA methylation datasets and the RNA expression profiles of primary tissues of the four BC molecular subtypes (luminal A, luminal B, basal-like, and HER2-enriched), as well as the survival information from The Cancer Genome Atlas (TCGA). The highly expressed and hypermethylated genes across all the four subtypes were screened. We examined the methylation sites and the downstream co-expressed genes of the selected genes and validated their prognostic value using a different dataset (GSE20685). For selected transcription factors, the downstream genes were predicted based on the Gene Transcription Regulation Database (GTRD). The tumor microenvironment was also evaluated based on the TCGA dataset. Results We found that Wilms tumor gene 1 (WT1), a transcription factor, was highly expressed and hypermethylated in all the four BC subtypes. All the WT1 methylation sites exhibited hypermethylation. The methylation levels of the TSS200 and 1stExon regions were negatively correlated with WT1 expression in two BC subtypes, while that of the gene body region was positively associated with WT1 expression in three BC subtypes. Patients with low WT1 expression had better overall survival (OS). Five genes including COL11A1, GFAP, FGF5, CD300LG, and IGFL2 were predicted as the downstream genes of WT1. Those five genes were dysregulated in the four BC subtypes. Patients with a favorable 6-gene signature (low expression of WT1 and its five predicted downstream genes) exhibited better OS than that with an unfavorable 6-gene signature. We also found a correlation between WT1 and tamoxifen using STITCH. Higher infiltration rates of CD8 T cells, plasma cells, and monocytes were found in the lower quartile WT1 group and the favorable 6-gene signature group. In conclusion, we demonstrated that WT1 is hypermethylated and up-regulated in the four BC molecular subtypes and a 6-gene signature may predict BC prognosis.

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