Large-scale RNA-Seq Transcriptome Analysis of 4043 Cancers and 548 Normal Tissue Controls across 12 TCGA Cancer Types

Li, Peng; Bian, Xiu Wu; Li, Di Kang; Xu, Chuan; Wang, Guang Ming; Xia, Qing; Xiong, Qing

doi:10.1038/srep13413

Cited by 109 publications

(93 citation statements)

References 175 publications

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“…Using systems biology approaches, others successfully clarified the role of small molecular decision circuits (e.g., Faratian et al, 2009; Gaglio et al, 2011; Tyson et al, 2011) and found commonalities across different cancers through pan-cancer analyses (e.g., Weinstein et al, 2013; Zack et al, 2013; Leiserson et al, 2014; Aran et al, 2015; Peng et al, 2015). However, few studies have addressed ROS metabolism using systems approaches (Zhang et al, 2010; Zhou et al, 2011; Zhan et al, 2012).…”

Section: Systems Biology and Personalized Medicine Approaches Are Funmentioning

confidence: 99%

New Challenges to Study Heterogeneity in Cancer Redox Metabolism

Benfeitas

Uhlén

Nielsen

et al. 2017

Front. Cell Dev. Biol.

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Reactive oxygen species (ROS) are important pathophysiological molecules involved in vital cellular processes. They are extremely harmful at high concentrations because they promote the generation of radicals and the oxidation of lipids, proteins, and nucleic acids, which can result in apoptosis. An imbalance of ROS and a disturbance of redox homeostasis are now recognized as a hallmark of complex diseases. Considering that ROS levels are significantly increased in cancer cells due to mitochondrial dysfunction, ROS metabolism has been targeted for the development of efficient treatment strategies, and antioxidants are used as potential chemotherapeutic drugs. However, initial ROS-focused clinical trials in which antioxidants were supplemented to patients provided inconsistent results, i.e., improved treatment or increased malignancy. These different outcomes may result from the highly heterogeneous redox responses of tumors in different patients. Hence, population-based treatment strategies are unsuitable and patient-tailored therapeutic approaches are required for the effective treatment of patients. Moreover, due to the crosstalk between ROS, reducing equivalents [e.g., NAD(P)H] and central metabolism, which is heterogeneous in cancer, finding the best therapeutic target requires the consideration of system-wide approaches that are capable of capturing the complex alterations observed in all of the associated pathways. Systems biology and engineering approaches may be employed to overcome these challenges, together with tools developed in personalized medicine. However, ROS- and redox-based therapies have yet to be addressed by these methodologies in the context of disease treatment. Here, we review the role of ROS and their coupled redox partners in tumorigenesis. Specifically, we highlight some of the challenges in understanding the role of hydrogen peroxide (H2O2), one of the most important ROS in pathophysiology in the progression of cancer. We also discuss its interplay with antioxidant defenses, such as the coupled peroxiredoxin/thioredoxin and glutathione/glutathione peroxidase systems, and its reducing equivalent metabolism. Finally, we highlight the need for system-level and patient-tailored approaches to clarify the roles of these systems and identify therapeutic targets through the use of the tools developed in personalized medicine.

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Section: Systems Biology and Personalized Medicine Approaches Are Funmentioning

confidence: 99%

New Challenges to Study Heterogeneity in Cancer Redox Metabolism

Benfeitas

Uhlén

Nielsen

et al. 2017

Front. Cell Dev. Biol.

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“…From a clinical perspective, HTS has great potential in the development of cancer diagnostics (Peng et al, 2015), the identification of disease-relevant genetic variations (Renkema et al, 2014;Liu et al, 2015), and clinical applications for regenerative therapy and personalized medicine (Casanova et al, 2014;Cox et al, 2015). In particular, the applications of HTS have been used to characterize the human oral microbiome, one of the most diverse microbial communities that is increasingly important for studying human oral cancers and pathogens (Xu and Gunsolley, 2014;Duran-Pinedo and Frias-Lopez, 2015).…”

Section: Introductionmentioning

confidence: 99%

Advances, practice, and clinical perspectives in high‐throughput sequencing

Park

Saito‐Adachi²,

Komiyama

et al. 2016

Oral Diseases

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Remarkable advances in high-throughput sequencing technologies have fundamentally changed our understanding of the genetic and epigenetic molecular bases underlying human health and diseases. As these technologies continue to revolutionize molecular biology leading to fresh perspectives, it is imperative to thoroughly consider the enormous excitement surrounding the technologies by highlighting the characteristics of platforms and their global trends as well as potential benefits and limitations. To date, with a variety of platforms, the technologies provide an impressive range of applications, including sequencing of whole genomes and transcriptomes, identifying of genome modifications, and profiling of protein interactions. Because these applications produce a flood of data, simultaneous development of bioinformatics tools is required to efficiently deal with the big data and to comprehensively analyze them. This review covers the major achievements and performances of the high-throughput sequencing and further summarizes the characteristics of their applications along with introducing applicable bioinformatics tools. Moreover, a step-by-step procedure for a practical transcriptome analysis is described employing an analytical pipeline. Clinical perspectives with special consideration to human oral health and diseases are also covered. Oral Diseases (2016) 22, 353-364

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“…Compared with traditional DNA sequencing technology, RNA sequencing can help understand the transcriptome via precisely and rapidly deriving wide-range strand information, such as transcripts, isoforms, gene fusions, and non-coding RNAs (Wang et al, 2009). The TCGA data that is generated by the RNASeq platform provides researchers with standardized and comprehensive cancer transcriptome profiles to discover biomarkers related to tumorigenesis and metastasis (Peng et al, 2015).…”

Section: Tcga Cancer Type and High-throughput Platform Generated Datamentioning

confidence: 99%

Identifying Scientific Project-generated Data Citation from Full-text Articles: An Investigation of TCGA Data Citation

Jiao¹,

Zheng²,

Kang³

et al. 2016

JDIS

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Purpose:In the open science era, it is typical to share project-generated scientific data by depositing it in an open and accessible database. Moreover, scientific publications are preserved in a digital library archive. It is challenging to identify the data usage that is mentioned in literature and associate it with its source. Here, we investigated the data usage of a government-funded cancer genomics project, The Cancer Genome Atlas (TCGA), via a full-text literature analysis.Design/methodology/approach: We focused on identifying articles using the TCGA dataset and constructing linkages between the articles and the specific TCGA dataset. First, we collected 5,372 TCGA-related articles from PubMed Central (PMC). Second, we constructed a benchmark set with 25 full-text articles that truly used the TCGA data in their studies, and we summarized the key features of the benchmark set. Third, the key features were applied to the remaining PMC full-text articles that were collected from PMC. Findings:The amount of publications that use TCGA data has increased significantly since 2011, although the TCGA project was launched in 2005. Additionally, we found that the critical areas of focus in the studies that use the TCGA data were glioblastoma multiforme, lung cancer, and breast cancer; meanwhile, data from the RNA-sequencing (RNA-seq) platform is the most preferable for use.

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Large-scale RNA-Seq Transcriptome Analysis of 4043 Cancers and 548 Normal Tissue Controls across 12 TCGA Cancer Types

Cited by 109 publications

References 175 publications

New Challenges to Study Heterogeneity in Cancer Redox Metabolism

New Challenges to Study Heterogeneity in Cancer Redox Metabolism

Advances, practice, and clinical perspectives in high‐throughput sequencing

Identifying Scientific Project-generated Data Citation from Full-text Articles: An Investigation of TCGA Data Citation

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