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Cancer Diagnostics with DNA Microarrays

  • ID: 2326519
  • Book
  • 272 Pages
  • John Wiley and Sons Ltd
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Learn how to use DNA microarrays in the fight against cancer

This text provides a first–time comprehensive review and analysis of the state of the art in clinical applications of DNA microarray data in cancer diagnostics. The acclaimed author, an international authority in the field, reviews published clinical trials for ten common cancer types. Moreover, the text provides a meta–analysis of these trials to highlight where the results concur.

The author begins with a discussion of the state of DNA microarray technology, emphasizing important aspects of data analysis. Emerging technologies within the field of DNA microarrays are presented. Next, readers learn the statistical analysis techniques needed to interpret the data. Finally, the author examines some major human cancer types where microarrays have been applied with success. The author concludes, based on the evidence and his own studies in the field, that the results are so convincing for several cancer types that DNA microarrays are ready to be deployed in clinical practice.

The text provides many features for researchers and clinicians who want to use microarrays as a hands–on diagnostic tool, including:

  • Examples and mini–cases that illustrate real–world applications
  • Further reading suggestions in each chapter to facilitate continued investigation of particular topics
  • Detailed recipes and software code for executing the techniques and analysis described in the text
  • Accessible, straightforward presentations that do not presume special training in statistics or bioinformatics

With the promise of DNA microarrays leading to more accurate cancer diagnoses, this text is an invaluable guide that opens the door to better care for cancer patients.

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1. Introduction to DNA Microarray Technology.

2. Image Analysis.

3. Basic Data Analysis.

4. Visualization by Reduction of Dimensionality.

5. Cluster Analysis.

6. Molecular Classifiers for Cancer.

7. Survival Analysis.

8. Meta–Analysis.

9. The Design of Probes.

10. Software Issues and Data Formats.

11. Breast Cancer.

12. Leukemia.

13. Lymphoma.

14. Lung Cancer.

15. Bladder Cancer.

16. Colon Cancer.

17. Ovarian Cancer.

18. Prostate Cancer.

19. Melanoma.

20. Brain Tumors.

21. Organ or Tissue Specific Classification.

22. Sample Collection and Stability.



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Steen Knudsen
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