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Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

The Thoracic Oncology Program Database Project was created to serve as a comprehensive, verified, and accessible repository for well-annotated cancer specimens and clinical data to be available to researchers within the Thoracic Oncology Research Program. This database also captures a large volume of genomic and proteomic data obtained from various tumor tissue studies. A team of clinical and basic science researchers, a biostatistician, and a bioinformatics expert was convened to design the database. Variables of interest were clearly defined and their descriptions were written within a standard operating manual to ensure consistency of data annotation. Using a protocol for prospective tissue banking and another protocol for retrospective banking, tumor and normal tissue samples from patients consented to these protocols were collected. Clinical information such as demographics, cancer characterization, and treatment plans for these patients were abstracted and entered into an Access database. Proteomic and genomic data have been included in the database and have been linked to clinical information for patients described within the database. The data from each table were linked using the relationships function in Microsoft Access to allow the database manager to connect clinical and laboratory information during a query. The queried data can then be exported for statistical analysis and hypothesis generation.

1. Two university protocols were developed for the purposes of this initiative. The first protocol allows for the prospective procurement of tissues from lung cancer, esophageal cancer, carcinoid tumor, thymoma, and mesothelioma patients. The protocol also allows blood and other bodily fluids to be collected from patients for biomarker studies. The protocol permits researchers to obtain clinical information from the patient source of such specimens via chart abstraction and to store both specimen and clinical data in a protected database. 2. The second protocol is similar to the first except that it allows researchers to access previously banked tissues and other samples obtained during the course of a patient's cancer diagnosis and treatment. Patients who have consented to surgery at the University of Chicago and who have signed this protocol are eligible.

Clinical Data Collection Protocol:
1. Patients being seen at the University of Chicago Medical Center for treatment of the aforementioned malignancies were included in this protocol. 2. Eligible patients were identified by their treating oncologist and were consented by a member of the clinical team trained in the two protocols. 3. Once consented, a patient's medical history information was obtained via chart abstraction and was entered into the database by a member of the clinical support team.
1. Tissues containing a known or suspected malignancy obtained during a patient's standard clinical care via biopsy or surgery were included in this protocol. No additional tissue, outside of what was necessary for a patient's diagnostic workup, was obtained. 2. After surgical removal of the sample necessary for the preparation of permanent sections, the residual tissue was placed on ice. 3. A tissue procurement technician transported the residual sample on ice to the pathology department. 4. Residual tissues were weighed, measured, transferred to storage, labeled, and properly documented according to the standard operating procedure. 5. Long-term storage of the specimens was maintained in a -80°C freezer in the pathology department. 6. In order to access tissue samples from patients who had already undergone surgery for a thoracic malignancy, lists of patients maintained by collaborating surgeons and radiation oncologists were referenced. In this manner patients of interest were identified. Their tumor tissue samples could be retrieved from the department of pathology if consent was obtained.

Blood samples
7. During clinically indicated blood draws, the protocol also allowed for an additional two to six tubes of blood in a 5 mL green top (Heparin) tube, one 10mL purple top tube (EDTA germline DNA) and one 10 mL red top (Serum) tube of blood. 8. Up to six samples at different time points were taken, with the date of the blood draw annotated. 9. Blood samples were centrifuged at 2000 rpm for 10 minutes. 10. Plasma and serum components were aliquoted in cryovial tubes in 1 mL portions. 11. For the collection of white blood cells, the upper 1-2 mL of the interface/red blood cell fraction were resuspended with 1-2 mL of cell preservation medium (MEM EBS media + 10% fetal cal serum+ 5% DMSO). 12. All samples were frozen slowly in an isopropyl freezing box at 70-80°C for 16-24 hours then transferred to a -70°C to -80°C storage box. 13. All samples were labeled with a bar-coded unique identifier and appropriately documented in the sample procurement form by a lab technician.

Other body fluids:
14. Fluid not collected for clinical use could be collected and stored under this protocol. Sputum samples were collected and sent for cytology. Sputum samples were stored on ice at 4°C while being transferred. 15. Sputum samples were then transferred to 15 mL Falcon tubes and centrifuged at 1400 rpm for 10 minutes. 16. The supernatant was aliquoted in 4 mL portions in 6mL cyrovials. Cyrovials were placed in a freezer, on dry ice, or in an isopropyl freezing box to be subsequently frozen to a -70°C to -80°C. After 16-24 hours, samples were transferred to a -70°C to -80°C storage box. 17. All samples were labeled with a bar-coded unique identifier and appropriately documented in the sample procurement form by a lab technician.

Building the Informatics Infrastructure:
1. After evaluating a number of database management programs, Microsoft Access was selected as the program to house clinical and laboratory data for the Thoracic Oncology Program Database Project based on its operability and ability to link related sets of data. 2. A team of clinicians, basic science researchers, a biostatistician, and a bioinformatics expert was convened to identify variables of interest to capture within the database. 3. The team identified data elements related to patient demographics, cancer characterization, epidemiological factors, and specimen annotation based on the needs of thoracic oncology researchers and referring to standards set regarding Common Data Elements (CDEs) by the National Cancer Institute. 4. The team developed a coding scheme to make data analyzable for research purposes. When possible, data was coded using numeric variables so as to reduce the amount of free-text entered into the database. 5. Variables of interest were divided among seven different tables within Microsoft Access to capture varied aspects of related information. Table: 3. Research assistants who are trained in the protocol are responsible for performing a systematic update of the database every six months to obtain the most recent data available. This is particularly important for fields such as vital status and date of last contact, as these fields have a direct impact on survival analyses performed on the data.

Access to the Database:
1. The database is only accessible to individuals who are HIPAA compliant and are included under the IRB protocol. Access is further reduced to individuals trained in Microsoft Access and who have direct responsibilities for updating or modifying the data. 2. Researchers who have contributed to the database may request information from the database from the data manager, but they themselves are not permitted to access the data directly. 3. The data manager provides de-identified information to the requesting researchers by removing variables such as the medical record number and the patient's name when generating an export query.

Representative Results:
A researcher may be interested in knowing the clinical significance of over-expression of the protein Paxillin in non-small cell lung cancer. As this researcher has generated a great deal of TMA data in the database for Paxillin, the data manager approves the researcher's request to access clinical information to correlate with the laboratory data. The data manager runs a query where he combines both the Patients As the two tables are linked via the medical record number, patient information from individuals whose tumors have been studied for Paxillin expression are included in the output. The results can be filtered so that only patients with non-small cell lung cancer are displayed. The results can be further refined based on the needs of the researcher.
These results can be exported for primary data analysis by the biostatistician and the results are then shared with the researcher.