Adult Brain Tumor, Lung Cancer, Radiation Toxicity
Conditions
Keywords
Biomarker, Radiation
Brief summary
This research trial studies metabolomic and other molecular profiling to identify predictive biomarkers for radiation toxicity and survival in patients with lung or brain cancers receiving radiation therapy. Studying samples of blood, urine, and tissue from patients with lung or brain cancer in the laboratory may help doctors identify and learn more about biomarkers related to cancer and predict which patients are at higher risk for developing radiation side effects and how well patients will respond to radiation treatment.
Detailed description
PRIMARY OBJECTIVES: I. Metabolomic and epigenetic urine and blood profiles of patients undergoing radiation therapy for lung cancer associated with the development of radiation pneumonitis. II. Metabolomic and epigenetic urine and blood profiles of patients undergoing radiation therapy for brain cancer associated with the development of radiation necrosis. SECONDARY OBJECTIVES: I. Metabolomic and epigenetic urine, blood, and tissue profiles of patients undergoing radiation therapy for lung and brain cancer associated with survival. OUTLINE: Collected blood, urine, and tissue samples are analyzed for biomarkers via metabolomic and epigenetic profiling using mass spectrometry, array, and sequencing-based technology.
Interventions
OTHERlaboratory biomarker analysis
Correlative studies
Sponsors
Ohio State University Comprehensive Cancer Center
Study design
Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Consultation with the Radiation Oncology department of the Ohio State University (OSU) Comprehensive Cancer Center * The following diagnoses will be included: malignant neoplasm of the brain; primary malignant neoplasm of trachea bronchus and lung; primary malignant neoplasm of the cervix uteri and primary malignant neoplasm the prostate
Exclusion criteria
* Being an inmate
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Potential predictive biomarkers for the development of radiation pneumonitis for lung cancer patients | Baseline | For each biomarker, linear mixed model (with group and time interaction and repeated measurement for each patient over time) on the log-transformed expression level will be used to detect if it is differentially expressed after controlling for the effects of the co-variates (such as age, disease status, and treatment details). |
| Potential predictive biomarkers for the development of radiation necrosis for brain cancer patients | Baseline | For each biomarker, linear mixed model (with group and time interaction and repeated measurement for each patient over time) on the log-transformed expression level will be used to detect if it is differentially expressed after controlling for the effects of the co-variates (such as age, disease status, and treatment details). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Biomarkers that are prognostically significant on disease free or overall survival, identified using the survival analysis | Baseline | Kaplan Meier analysis and logrank test to identify biomarkers that are prognostically significant. |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORArnab Chakravarti, MD
Ohio State University Comprehensive Cancer Center
Outcome results
None listed