Novel Blood Biomarkers for Early Detection of Depression in Prostate Cancer: A Translational Study
Depressive disorder is the leading cause of disability worldwide. Its economic burden was over 83.1 billion USD in the year 2000. People with multiple chronic conditions (MCCs), including comorbid depression and cancer, now comprise over one-quarter of the U.S. population, and that percentage continues to grow. Cancer patients with depression could experience low energy, decreased drive, trouble making decisions, and uselessness/helplessness, showing a significantly higher risk for adverse outcomes and complications, including increased clinic visits, medication intake complications, and mortality, as well as poorer Quality of Life (QOL).
This study investigates the relationship between pre-existing depression and survival rates in prostate cancer patients using data from the NCI-sponsored Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. We aim to develop a novel multiplexed assay prototype for detecting depression-associated biomarkers in blood samples from the PLCO cohort. This approach is innovative and has not been previously explored.
The primary challenge in identifying depression in cancer patients lies in the lack of objective diagnostic tools. Current methods rely on symptom descriptions and medical history. Recent studies have identified protein markers, including P11 (S100A10), brain-derived neurotrophic factor (BDNF), FKBP5, and cytokines, that could improve diagnostic accuracy. Preliminary data suggest these biomarkers may offer superior diagnostic power. Using PLCO data and Luminex Multianalyte Profiling (LabMAP) technology, capable of detecting up to 100 biomarkers in 25–50 µL of serum, we aim to validate these biomarkers. We hypothesize that depression influences the survival in prostate cancer patients and that a multi-marker panel can improve diagnostic sensitivity and specificity. We will verify the relationship between biomarkers and depression in cancer patients; profile depression across cancer types and linking biomarkers to patient outcomes; examine the dynamic relationship between biomarkers and depression across the cancer spectrum, and investigating gene-environment interactions in depression, focusing on biomarkers, demographics, and patient outcomes. This study seeks to develop objective diagnostic tools for depression in cancer, enabling timely interventions to improve patient outcomes, QOL, and survival rates.
AimsThis study investigates the relationship between pre-existing depression and survival rates in prostate cancer patients using data from the NCI-sponsored Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. We aim to develop a novel multiplexed assay prototype for detecting depression-associated biomarkers in blood samples from the PLCO cohort. This approach is innovative and has not been previously explored.
The primary challenge in identifying depression in cancer patients lies in the lack of objective diagnostic tools. Current methods rely on symptom descriptions and medical history. Recent studies have identified protein markers, including P11 (S100A10), brain-derived neurotrophic factor (BDNF), FKBP5, and cytokines, that could improve diagnostic accuracy. Preliminary data suggest these biomarkers may offer superior diagnostic power. Using PLCO data and Luminex Multianalyte Profiling (LabMAP) technology, capable of detecting up to 100 biomarkers in 25–50 µL of serum, we aim to validate these biomarkers. We hypothesize that depression influences the survival in prostate cancer patients and that a multi-marker panel can improve diagnostic sensitivity and specificity. Specific Aims:
1. To verify the relationship between biomarkers and depression in cancer patients;
2. To profile depression across cancer types and linking biomarkers to patient outcomes;
3. To examine the dynamic relationship between biomarkers and depression across the cancer spectrum;
4. To investigate gene-environment interactions in depression, focusing on biomarkers, demographics, and patient outcomes. This study seeks to develop objective diagnostic tools for depression in cancer, enabling timely interventions to improve patient outcomes, QOL, and survival rates.
Collaborators
Xianzhang Hu (USUHS)