Chapter title |
Next-Generation Sequencing and Applications to the Diagnosis and Treatment of Lung Cancer.
|
---|---|
Chapter number | 7 |
Book title |
Lung Cancer and Personalized Medicine: Novel Therapies and Clinical Management
|
Published in |
Advances in experimental medicine and biology, December 2015
|
DOI | 10.1007/978-3-319-24932-2_7 |
Pubmed ID | |
Book ISBNs |
978-3-31-924931-5, 978-3-31-924932-2
|
Authors |
Kruglyak, Kristina M, Lin, Erick, Ong, Frank S, Kristina M. Kruglyak Ph.D., Erick Lin M.D., Ph.D., Frank S. Ong M.D., Kristina M. Kruglyak, Erick Lin, Frank S. Ong, Kruglyak, Kristina M., Ong, Frank S. |
Editors |
Aamir Ahmad, Shirish M. Gadgeel |
Abstract |
Cancer is a genetic disease characterized by uncontrolled growth of abnormal cells. Over time, somatic mutations accumulate in the cells of an individual due to replication errors, chromosome segregation errors, or DNA damage. When not caught by traditional mechanisms, these somatic mutations can lead to cellular proliferation, the hallmark of cancer. Lung cancer is the leading cause of cancer-related mortality in the United States, accounting for approximately 160,000 deaths annually. Five year survival rates for lung cancer remain low (<50 %) for all stages, with even worse prognosis (<15 %) in late stage cases. Technological advances, including advances in next-generation sequencing (NGS), offer the vision of personalized medicine or precision oncology, wherein an individual's treatment can be based on his or her individual molecular profile, rather than on historical population-based medicine. Towards this end, NGS has already been used to identify new biomarker candidates for the early diagnosis of lung cancer and is increasingly used to guide personalized treatment decisions. In this review we will provide a high-level overview of NGS technology and summarize its application to the diagnosis and treatment of lung cancer. We will also describe how NGS can drive advances that bring us closer to precision oncology and discuss some of the technical challenges that will need to be overcome in order to realize this ultimate goal. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 58 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 8 | 14% |
Student > Bachelor | 7 | 12% |
Researcher | 6 | 10% |
Student > Postgraduate | 5 | 9% |
Student > Ph. D. Student | 4 | 7% |
Other | 8 | 14% |
Unknown | 20 | 34% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 11 | 19% |
Biochemistry, Genetics and Molecular Biology | 8 | 14% |
Computer Science | 3 | 5% |
Agricultural and Biological Sciences | 3 | 5% |
Social Sciences | 3 | 5% |
Other | 7 | 12% |
Unknown | 23 | 40% |