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Cell Biology JoVE (Open Access) Citable · DOI

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

DOI: 10.3791/2414-v
What you'll learn
  • ✓ Design and structure a comprehensive relational database for thoracic oncology translational research
  • ✓ Query and retrieve clinical and laboratory data efficiently from integrated database tables
  • ✓ Import, export, and manage multi-source data for cancer research applications
  • ✓ Apply database methodology to analyze protein expression patterns in lung cancer specimens
Protocol

A thoracic oncology database was developed to serve as a comprehensive repository for clinical and laboratory data for the purposes of translational research. The database will serve translational cancer researchers within the Thoracic Oncology Research Program. This database is adaptable to other cancer models, as well as other human diseases.

Difficulty
intermediate
Total time
~2-4 weeks (database design and population); ~5-10 min per query/export

Steps

1
Collect and organize thoracic oncology specimens

Gather clinical samples and associated laboratory data for database entry. Establish specimen collection protocols and documentation standards.

▶ 02:04
2
Design database table structure and contents

Define relational table schemas, data fields, and relationships to organize clinical and laboratory information. Establish data validation rules and field specifications.

▶ 02:28
3
Query database for research data retrieval

Execute structured queries to extract and filter relevant clinical and laboratory data from the integrated database for analysis.

▶ 06:13
4
Import and export data between systems

Transfer data into the database from external sources and export results in standardized formats for downstream analysis and reporting.

▶ 07:50
5
Analyze protein expression in lung cancer

Apply database methodology to investigate clinical significance of paxillin over-expression in non-small cell lung cancer patient cohorts.

▶ 08:52
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