| Chapter title |
Systems Biology Approaches in Cancer Pathology
|
|---|---|
| Chapter number | 13 |
| Book title |
Cancer Systems Biology
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7493-1_13 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7492-4, 978-1-4939-7493-1
|
| Authors |
Aaron DeWard, Rebecca J. Critchley-Thorne |
| Abstract |
The complex network of the tissue system, in both pre-neoplastic tissues and tumors, demonstrates the need for a systems biology approach to cancer pathology, in which quantification of key tissue system processes is combined with informatics tools to produce actionable scores to aid clinical decision-making. A systems biology approach to cancer pathology enables integration of key system features that are relevant to diagnoses, patient outcomes, and responses to therapies. Key tissue system features relevant to cancer pathology include molecular and morphologic abnormalities in epithelia, cellular changes in the stroma such as immune infiltrates, and relationships between components of the system, such as interactions and spatial relationships between epithelial and stromal components, and also between specific immune cell subsets. Here, we describe a method for objective quantification of multiple epithelial and stromal biomarkers in the context of tissue architecture to generate a high dimensional tissue profile that can be used to build multivariable predictive models for cancer pathology. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 75% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 40% |
| Student > Master | 3 | 20% |
| Student > Bachelor | 1 | 7% |
| Student > Ph. D. Student | 1 | 7% |
| Unknown | 4 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 33% |
| Medicine and Dentistry | 3 | 20% |
| Agricultural and Biological Sciences | 1 | 7% |
| Engineering | 1 | 7% |
| Unknown | 5 | 33% |