The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge

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Abstract

The Cancer Genome Atlas (TCGA) is a public funded project that aims to catalogue and discover major cancer-causing genomic alterations to create a comprehensive “atlas” of cancer genomic profiles. So far, TCGA researchers have analysed large cohorts of over 30 human tumours through large-scale genome sequencing and integrated multi-dimensional analyses. Studies of individual cancer types, as well as comprehensive pan-cancer analyses have extended current knowledge of tumorigenesis. A major goal of the project was to provide publicly available datasets to help improve diagnostic methods, treatment standards, and finally to prevent cancer. This review discusses the current status of TCGA Research Network structure, purpose, and achievements.

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Most cited references 36

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The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository.

Kenneth Clark, Bruce A Vendt, Kirk Smith … (2013)

The National Institutes of Health have placed significant emphasis on sharing of research data to support secondary research. Investigators have been encouraged to publish their clinical and imaging data as part of fulfilling their grant obligations. Realizing it was not sufficient to merely ask investigators to publish their collection of imaging and clinical data, the National Cancer Institute (NCI) created the open source National Biomedical Image Archive software package as a mechanism for centralized hosting of cancer related imaging. NCI has contracted with Washington University in Saint Louis to create The Cancer Imaging Archive (TCIA)-an open-source, open-access information resource to support research, development, and educational initiatives utilizing advanced medical imaging of cancer. In its first year of operation, TCIA accumulated 23 collections (3.3 million images). Operating and maintaining a high-availability image archive is a complex challenge involving varied archive-specific resources and driven by the needs of both image submitters and image consumers. Quality archives of any type (traditional library, PubMed, refereed journals) require management and customer service. This paper describes the management tasks and user support model for TCIA.

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Genetic instabilities in human cancers.

C Lengauer, K Kinzler, B Vogelstein (1998)

Whether and how human tumours are genetically unstable has been debated for decades. There is now evidence that most cancers may indeed be genetically unstable, but that the instability exists at two distinct levels. In a small subset of tumours, the instability is observed at the nucleotide level and results in base substitutions or deletions or insertions of a few nucleotides. In most other cancers, the instability is observed at the chromosome level, resulting in losses and gains of whole chromosomes or large portions thereof. Recognition and comparison of these instabilities are leading to new insights into tumour pathogenesis.

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Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.

Katherine A. Hoadley, Christina Yau, Denise M Wolf … (2014)

Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies. Copyright © 2014 Elsevier Inc. All rights reserved.

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Author and article information

Journal

Journal ID (nlm-ta): Contemp Oncol (Pozn)

Journal ID (iso-abbrev): Contemp Oncol (Pozn)

Journal ID (publisher-id): WO

Title: Contemporary Oncology

Publisher: Termedia Publishing House

ISSN (Print): 1428-2526

ISSN (Electronic): 1897-4309

Publication date (Electronic): 20 January 2015

Publication date (Print): 2015

Volume: 19

Issue: 1A

Pages: A68-A77

Affiliations

[1 ]Postgraduate School of Molecular Medicine, Medical University of Warsaw, Warsaw, Poland

[2 ]Laboratory of Gene Therapy, Department of Cancer Immunology, The Greater Poland Cancer Centre, Poznan, Poland

[3 ]Department of Cancer Immunology and Diagnostics, Chair of Medical Biotechnology, Poznan University of Medical Sciences, Poznan, Poland

Author notes

Address for correspondence: Katarzyna Tomczak, Laboratory of Gene Therapy, Department of Cancer Immunology, Greater Poland Cancer Centre, Garbary 15, 61-866 Poznan, Poland and Postgraduate School of Molecular Medicine, Medical University of Warsaw. e-mail: tomczak.kate@ 123456gmail.com

Article

Publisher ID: 24047

DOI: 10.5114/wo.2014.47136

PMC ID: 4322527

PubMed ID: 25691825

SO-VID: 9b86e0cc-829d-4d37-90bf-cf8ed2e4cd4e

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge

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Abstract

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Genome Integrity

Most cited references 36

The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository.

Genetic instabilities in human cancers.

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.

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