Title |
Emerging Understanding of Multiscale Tumor Heterogeneity
|
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Published in |
Frontiers in oncology, December 2014
|
DOI | 10.3389/fonc.2014.00366 |
Pubmed ID | |
Authors |
Michael J. Gerdes, Anup Sood, Christopher Sevinsky, Andrew D. Pris, Maria I. Zavodszky, Fiona Ginty |
Abstract |
Cancer is a multifaceted disease characterized by heterogeneous genetic alterations and cellular metabolism, at the organ, tissue, and cellular level. Key features of cancer heterogeneity are summarized by 10 acquired capabilities, which govern malignant transformation and progression of invasive tumors. The relative contribution of these hallmark features to the disease process varies between cancers. At the DNA and cellular level, germ-line and somatic gene mutations are found across all cancer types, causing abnormal protein production, cell behavior, and growth. The tumor microenvironment and its individual components (immune cells, fibroblasts, collagen, and blood vessels) can also facilitate or restrict tumor growth and metastasis. Oncology research is currently in the midst of a tremendous surge of comprehension of these disease mechanisms. This will lead not only to novel drug targets but also to new challenges in drug discovery. Integrated, multi-omic, multiplexed technologies are essential tools in the quest to understand all of the various cellular changes involved in tumorigenesis. This review examines features of cancer heterogeneity and discusses how multiplexed technologies can facilitate a more comprehensive understanding of these features. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 25% |
Switzerland | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 75% |
Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Switzerland | 1 | <1% |
Netherlands | 1 | <1% |
France | 1 | <1% |
United Kingdom | 1 | <1% |
Japan | 1 | <1% |
United States | 1 | <1% |
Poland | 1 | <1% |
Unknown | 174 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 51 | 28% |
Researcher | 32 | 18% |
Student > Master | 18 | 10% |
Student > Bachelor | 15 | 8% |
Student > Doctoral Student | 7 | 4% |
Other | 24 | 13% |
Unknown | 34 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 40 | 22% |
Biochemistry, Genetics and Molecular Biology | 37 | 20% |
Medicine and Dentistry | 22 | 12% |
Engineering | 13 | 7% |
Physics and Astronomy | 5 | 3% |
Other | 23 | 13% |
Unknown | 41 | 23% |