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Lung Cancer and Personalized Medicine: Novel Therapies and Clinical Management

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Attention for Chapter 3: Lung Cancer and Personalized Medicine: Novel Therapies and Clinical Management
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Chapter title
Lung Cancer and Personalized Medicine: Novel Therapies and Clinical Management
Chapter number 3
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_3
Pubmed ID
Book ISBNs
978-3-31-924931-5, 978-3-31-924932-2
Authors

Mittal, Vivek, Vivek Mittal

Editors

Aamir Ahmad, Shirish M. Gadgeel

Abstract

The progression of a cancer cell into a metastatic entity contributes to more than 90 % of cancer related deaths. Therefore, the prevention and treatment of metastasis is an unmet clinical need. Epithelial to mesenchymal transition (EMT) is an evolutionary conserved developmental program, which is induced during cancer progression and contributes to metastatic colonization. EMT endows metastatic properties upon cancer cells by enhancing mobility, invasion, and resistance to apoptotic stimuli. Furthermore, EMT-derived tumor cells acquire stem cell properties and exhibit therapeutic resistance. The disseminated tumor cells recruited to distant organs are suggested to subsequently undergo an EMT reversion through mesenchymal to epithelial transition (MET), necessary for efficient colonization and macrometastasis. A major focus of cancer research is to determine the cellular and molecular mechanisms underlying EMT/MET in tumor invasion, dissemination and metastasis. In this chapter, we will focus on the contribution of the EMT signaling pathways in lung cancer progression, cancer stem cells and acquired resistance to EGFR tyrosine kinase inhibitors and chemotherapy. We will also discuss the potential of targeting EMT pathways as an attractive strategy for the treatment of lung cancer.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 101 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 17%
Student > Master 16 16%
Student > Bachelor 16 16%
Researcher 9 9%
Other 6 6%
Other 14 14%
Unknown 23 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 27 27%
Medicine and Dentistry 20 20%
Agricultural and Biological Sciences 10 10%
Pharmacology, Toxicology and Pharmaceutical Science 7 7%
Nursing and Health Professions 2 2%
Other 9 9%
Unknown 26 26%