Using large databases to study cancer genomics in an undergraduate classroom

Area of Science:

• Oncology
• Bioinformatics
• Genetics

Background:

• Cancer databases offer valuable resources for global analysis of patient data and original studies.
• Educational curricula often lack hands-on experience with these powerful cancer research databases.
• Understanding driver mutations is crucial for cancer research and personalized medicine.

Purpose of the Study:

• To develop a laboratory module enabling students to explore original cancer study databases.
• To investigate the expression and incidence of cancer driver mutations using real-world data.
• To enhance student understanding of genetic alterations in cancer and their clinical implications.

Main Methods:

• Students analyze specific patient demographic data and cancer types.
• mRNA expression levels associated with gene mutations are examined.
• Determination of whether mutations act as tumor suppressors or oncogenes.
• Identification of actionable mutations and their correlation with patient survival.

Main Results:

• Students gain experience in analyzing large-scale cancer genomic and clinical datasets.
• The module facilitates understanding of global trends in cancer driver mutations.
• Students learn to differentiate between tumor suppressors and oncogenes based on expression data.
• Actionable mutations and their prognostic significance are explored.

Conclusions:

• This lab module provides a practical approach to learning about cancer genomics.
• It empowers students to analyze driver mutations and patient-specific features from global databases.
• The experience bridges the gap between theoretical knowledge and practical application in cancer research.