A concurrent canonical and modified miRNAome pan-cancer study on TCGA and TARGET cohorts leads to an enhanced resolution in cancer

MiRNA Epitranscriptomics has placed a new layer of complexity in the cancer field. Despite miRNA editing and shifted miRNA isoforms are gaining attention due to recent improvements in next-generation sequencing, a simultaneous study of both modifications in cancer is still missing. Here, we concurrently profiled multiple miRNA modifications, such as A-to-I RNA editing and shifted miRNA isoforms, in >13K adult and pediatric tumor samples across 38 distinct cancer cohorts from The Cancer Genome Atlas and The Therapeutically Applicable Research to Generate Effective Treatments datasets. We investigated the differences among canonical miRNAs and a wider comprehensive miRNAome from the expression, clustering, dysregulation, and prognostic perspective. Interestingly, the wider miRNAome boosted clustering results, uniquely outlining cohorts' clinical-pathological features. The abundance of expressed miRNA isoforms directly related to the activation/deactivation of critical carcinogenesis pathways. We found dysregulated modified miRNAs characterized by an opposite expression trend than their canonical counterparts in cancer, potentially impacting their targetome and function. Our study emphasizes the importance of modified miRNAs as potential cancer biomarkers and gene expression regulators, outlining once more the importance of going beyond the well-established paradigm of one-mature-miRNA per miRNA arm.

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Tumor IsomiR Encyclopedia (TIE): a pan-cancer database of miRNA isoforms

10.1101/2020.08.20.259713 ◽

2020 ◽

Author(s):

Xavier Bofill-De Ros ◽

Brian Luke ◽

Robert Guthridge ◽

Uma Mudunuri ◽

Michael Loss ◽

...

Keyword(s):

Data Aggregation ◽

Low Frequency ◽

The Cancer Genome Atlas ◽

Sequence Length ◽

Pediatric Tumor ◽

Master Regulators ◽

Pathological Conditions ◽

Cancer Genome Atlas ◽

Advanced Analysis ◽

Pan Cancer

ABSTRACTMicroRNAs (miRNAs) function as master regulators of gene expression in many physiological and pathological conditions including cancer. Sequence variants or isoforms (isomiRs) can account for between 40 to 60% of total miRNA counts, yet despite this overwhelming abundance, their function continues to be debated. Recent studies demonstrate that certain isomiRs can regulate unique sets of target mRNAs by altering their seed sequence or stabilizing 3’ pairing, while others are decay intermediates indicating an active miRNA turnover. Given their short sequence length and high heterogeneity, mapping isomiRs can be challenging; without adequate depth and data aggregation, low frequency events are often disregarded. To address these challenges, we present the Tumor IsomiR Encyclopedia (TIE): a dynamic database of isomiRs from over 10,000 adult and pediatric tumor samples in The Cancer Genome Atlas (TCGA) and The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) projects. A key novelty of TIE is its ability to annotate heterogeneous isomiR sequences and aggregate the variants obtained across all samples and datasets. The database provides annotation of templated and non-templated nucleotides as well as other advanced analysis. All data can be browsed online or downloaded as simple spreadsheets. Here we show analysis of isomiRs of miR-21 and miR-30a to demonstrate the utility of TIE. TIE search engine and data are hosted at https://isomir.ccr.cancer.gov/.

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Molecular Correlates of Metastasis by Systematic Pan-Cancer Analysis Across The Cancer Genome Atlas

Molecular Cancer Research ◽

10.1158/1541-7786.mcr-18-0601 ◽

2018 ◽

Vol 17 (2) ◽

pp. 476-487 ◽

Cited By ~ 8

Author(s):

Fengju Chen ◽

Yiqun Zhang ◽

Sooryanarayana Varambally ◽

Chad J. Creighton

Keyword(s):

Cancer Genome ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas ◽

Pan Cancer ◽

Genome Atlas

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

International Journal of Molecular Sciences ◽

10.3390/ijms19103250 ◽

2018 ◽

Vol 19 (10) ◽

pp. 3250 ◽

Cited By ~ 9

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.

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Integrated Dissection of lncRNA-Perturbated Triplets Reveals Novel Prognostic Signatures Across Cancer Types

International Journal of Molecular Sciences ◽

10.3390/ijms21176087 ◽

2020 ◽

Vol 21 (17) ◽

pp. 6087

Author(s):

Yunzhen Wei ◽

Limeng Zhou ◽

Yingzhang Huang ◽

Dianjing Guo

Keyword(s):

Cancer Biology ◽

Noncoding Rna ◽

The Cancer Genome Atlas ◽

Dynamic Changes ◽

Computational Framework ◽

Potential Biomarker ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Tcga Dataset ◽

Pan Cancer

Long noncoding RNA (lncRNA)/microRNA(miRNA)/mRNA triplets contribute to cancer biology. However, identifying significative triplets remains a major challenge for cancer research. The dynamic changes among factors of the triplets have been less understood. Here, by integrating target information and expression datasets, we proposed a novel computational framework to identify the triplets termed as “lncRNA-perturbated triplets”. We applied the framework to five cancer datasets in The Cancer Genome Atlas (TCGA) project and identified 109 triplets. We showed that the paired miRNAs and mRNAs were widely perturbated by lncRNAs in different cancer types. LncRNA perturbators and lncRNA-perturbated mRNAs showed significantly higher evolutionary conservation than other lncRNAs and mRNAs. Importantly, the lncRNA-perturbated triplets exhibited high cancer specificity. The pan-cancer perturbator OIP5-AS1 had higher expression level than that of the cancer-specific perturbators. These lncRNA perturbators were significantly enriched in known cancer-related pathways. Furthermore, among the 25 lncRNA in the 109 triplets, lncRNA SNHG7 was identified as a stable potential biomarker in lung adenocarcinoma (LUAD) by combining the TCGA dataset and two independent GEO datasets. Results from cell transfection also indicated that overexpression of lncRNA SNHG7 and TUG1 enhanced the expression of the corresponding mRNA PNMA2 and CDC7 in LUAD. Our study provides a systematic dissection of lncRNA-perturbated triplets and facilitates our understanding of the molecular roles of lncRNAs in cancers.

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Pan-Cancer Analysis of the Genomic Alterations and Mutations of the Matrisome

Cancers ◽

10.3390/cancers12082046 ◽

2020 ◽

Vol 12 (8) ◽

pp. 2046 ◽

Cited By ~ 2

Author(s):

Valerio Izzi ◽

Martin N. Davis ◽

Alexandra Naba

Keyword(s):

Cancer Progression ◽

Protein Function ◽

The Cancer Genome Atlas ◽

Copy Number Alterations ◽

Cellular Functions ◽

Genomic Alterations ◽

Genes Encoding ◽

Cancer Genome Atlas ◽

Biomechanical Changes ◽

Pan Cancer

The extracellular matrix (ECM) is a master regulator of all cellular functions and a major component of the tumor microenvironment. We previously defined the “matrisome” as the ensemble of genes encoding ECM proteins and proteins modulating ECM structure or function. While compositional and biomechanical changes in the ECM regulate cancer progression, no study has investigated the genomic alterations of matrisome genes in cancers and their consequences. Here, mining The Cancer Genome Atlas (TCGA) data, we found that copy number alterations and mutations are frequent in matrisome genes, even more so than in the rest of the genome. We also found that these alterations are predicted to significantly impact gene expression and protein function. Moreover, we identified matrisome genes whose mutational burden is an independent predictor of survival. We propose that studying genomic alterations of matrisome genes will further our understanding of the roles of this compartment in cancer progression and will lead to the development of innovative therapeutic strategies targeting the ECM.

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The Gasdermin E gene Potential as a Pan-Cancer Biomarker, While Discriminating between Different Tumor Types

Cancers ◽

10.3390/cancers11111810 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1810 ◽

Cited By ~ 3

Author(s):

Joe Ibrahim ◽

Ken Op de Beeck ◽

Erik Fransen ◽

Marc Peeters ◽

Guy Van Camp

Keyword(s):

The Cancer Genome Atlas ◽

Tumor Type ◽

E Gene ◽

Normal Tissues ◽

Incidence And Mortality ◽

Cancer Genome Atlas ◽

Cancer Setting ◽

Tumor Types ◽

Methylation Patterns ◽

Pan Cancer

Due to the elevated rates of incidence and mortality of cancer, early and accurate detection is crucial for achieving optimal treatment. Molecular biomarkers remain important screening and detection tools, especially in light of novel blood-based assays. DNA methylation in cancer has been linked to tumorigenesis, but its value as a biomarker has not been fully explored. In this study, we have investigated the methylation patterns of the Gasdermin E gene across 14 different tumor types using The Cancer Genome Atlas (TCGA) methylation data (N = 6502). We were able to identify six CpG sites that could effectively distinguish tumors from normal samples in a pan-cancer setting (AUC = 0.86). This combination of pan-cancer biomarkers was validated in six independent datasets (AUC = 0.84–0.97). Moreover, we tested 74,613 different combinations of six CpG probes, where we identified tumor-specific signatures that could differentiate one tumor type versus all the others (AUC = 0.79–0.98). In all, methylation patterns exhibited great variation between cancer and normal tissues, but were also tumor specific. Our analyses highlight that a Gasdermin E methylation biomarker assay, not only has the potential for being a methylation-specific pan-cancer detection marker, but it also possesses the capacity to discriminate between different types of tumors.

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Cyclin-Dependent Kinase and Antioxidant Gene Expression in Cancers with Poor Therapeutic Response

Pharmaceuticals ◽

10.3390/ph13020026 ◽

2020 ◽

Vol 13 (2) ◽

pp. 26

Author(s):

George S. Scaria ◽

Betsy T. Kren ◽

Mark A. Klein

Keyword(s):

Hepatocellular Carcinoma ◽

Pancreatic Cancer ◽

Antioxidant Defense ◽

Treatment Strategies ◽

The Cancer Genome Atlas ◽

Cyclin Dependent Kinase ◽

Critical Pathways ◽

Cancer Genome Atlas ◽

Antioxidant Gene Expression ◽

Pan Cancer

Pancreatic cancer, hepatocellular carcinoma (HCC), and mesothelioma are treatment-refractory cancers, and patients afflicted with these cancers generally have a very poor prognosis. The genomics of these tumors were analyzed as part of The Cancer Genome Atlas (TCGA) project. However, these analyses are an overview and may miss pathway interactions that could be exploited for therapeutic targeting. In this study, the TCGA Pan-Cancer datasets were queried via cBioPortal for correlations among mRNA expression of key genes in the cell cycle and mitochondrial (mt) antioxidant defense pathways. Here we describe these correlations. The results support further evaluation to develop combination treatment strategies that target these two critical pathways in pancreatic cancer, hepatocellular carcinoma, and mesothelioma.

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Erratum: Corrigendum: A pan-cancer proteomic perspective on The Cancer Genome Atlas

Nature Communications ◽

10.1038/ncomms5852 ◽

2015 ◽

Vol 6 (1) ◽

Cited By ~ 6

Author(s):

Rehan Akbani ◽

Patrick Kwok Shing Ng ◽

Henrica M.J. Werner ◽

Maria Shahmoradgoli ◽

Fan Zhang ◽

...

Keyword(s):

Cancer Genome ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas ◽

Pan Cancer ◽

Genome Atlas

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The Biological Function Delineated Across Pan-Cancer Levels Through lncRNA-Based Prognostic Risk Assessment Factors for Pancreatic Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.694652 ◽

2021 ◽

Vol 9 ◽

Author(s):

Xudong Tang ◽

Mengyan Zhang ◽

Liang Sun ◽

Fengyan Xu ◽

Xin Peng ◽

...

Keyword(s):

Pancreatic Cancer ◽

Prognostic Marker ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Research Network ◽

Molecular Characteristics ◽

Cancer Data ◽

Cancer Genome Atlas ◽

Pan Cancer ◽

Genome Atlas

Long non-coding RNAs (lncRNAs) play key roles in tumors and function not only as important molecular markers for cancer prognosis, but also as molecular characteristics at the pan-cancer level. Because of the poor prognosis of pancreatic cancer, accurate assessment of prognosis is a key issue in the development of treatment plans for pancreatic cancer. Here we analyzed pancreatic cancer data from The Cancer Genome Atlas and The Genotype Tissue Expression database using Cox regression and lasso regression in analyses using a combination of the two databases as well as only The Cancer Genome Atlas database (Cancer Genome Atlas Research Network et al., 2013). A prognostic risk score model with significant correlation with pancreatic cancer survival was constructed, and two lncRNAs were investigated. Additional analysis of 33 cancers using the two lncRNAs showed that lncRNA TsPOAP1-AS1 was a prognostic marker of seven cancers, among which pancreatic cancer was the most significant, and lncRNA mi600hg was a prognostic marker of ovarian cancer and pancreatic cancer. LncRNA TsPOAP1-AS1 is associated with clinical stage and tumor mutation burden of some cancers as well as a strong degree of immune infiltration in many cancers, while a strong correlation between lncRNA mi600hg and microsatellite instability was observed in several cancers. The results of this study help further our understanding of the different functions of lncRNAs in cancer and may aid in the clinical application of lncRNAs as prognostic factors for cancer.

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On the Reproducibility of TCGA Ovarian Cancer MicroRNA Profiles

10.1101/000315 ◽

2013 ◽

Author(s):

Ying-Wooi Wan ◽

Claire Mach ◽

Genevera I. Allen ◽

Matthew Anderson ◽

Zhandong Liu

Keyword(s):

Ovarian Cancer ◽

Cancer Survival ◽

Human Cancer ◽

The Cancer Genome Atlas ◽

Detection Algorithms ◽

Level 3 ◽

Cancer Genome Atlas ◽

Ovarian Cancer Survival ◽

Generation Sequencing

Dysregulated microRNA (miRNA) expression is a well-established feature of human cancer. However, the role of specific miRNAs in determining cancer outcomes remains unclear. Using Level 3 expression data from the Cancer Genome Atlas (TCGA), we identified 61 miRNAs that are associated with overall survival in 469 ovarian cancers profiled by microarray (p<0.01). We also identified 12 miRNAs that are associated with survival when miRNAs were profiled in the same specimens using Next Generation Sequencing (miRNA-Seq) (p<0.01). Surprisingly, only 1 miRNA transcript is associated with ovarian cancer survival in both datasets. Our analyses indicate that this discrepancy is due to the fact that miRNA levels reported by the two platforms correlate poorly, even after correcting for potential issues inherent to signal detection algorithms. Further investigation is warranted.

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