Grayson, Susan C
(2024)
Psychoneurological Symptoms and their Association with Markers of Genomic Instability from Circulating Tumor DNA in Metastatic Breast Cancer.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Among the 3.8 million breast cancer survivors in the United States, many will experience the psychoneurological (PN) symptom cluster of fatigue, sleep disturbance, anxiety, pain, depressive symptoms, and changes in cognitive function. A variety of patient social, treatment, and biological factors have been associated with this symptom cluster. Genomic instability in cancer cells may be associated with the variability in psychoneurological symptom development, given that markers of systemic inflammation have been associated with both genomic instability and psychoneurological symptoms. Genomic instability can be measured through an emerging technology that sequences circulating tumor DNA in the blood of patients with breast cancer. Individual factors and social determinants of health (SDoH) have also been linked to inflammatory processes and may impact symptoms as well. However, no studies to date have linked genomic instability in cancer cells to variability in the psychoneurological symptom cluster experience. The overall goal of this study was to develop understanding of how genomic instability in breast cancer is associated with the psychoneurological symptom cluster and enable future development of precision health interventions for symptoms based on cancer characteristics. The specific aims of the proposed research were to (1) phenotype patterns and severity of PN symptoms in individuals with metastatic breast cancer (2) investigate the association of PN symptom phenotypes with markers of cancer genomic instability from circulating tumor DNA analysis. This was accomplished through analysis of data from (1) a parent study focused on the circulating tumor DNA in patients with metastatic breast cancer and (2) measures of patient-reported symptoms concurrent with measures collection of biological samples abstracted from the electronic medical record. Factor analysis identified a single factor underlying all six measures PN symptoms. Hierarchical clustering identified three distinct symptom phenotypes: mild symptoms, moderate symptoms, and severe mood related symptoms. Deletion of TP53 in circulating tumor DNA was predictive of a more severe symptom phenotype. Prediction of symptoms from cancer biological factors is a novel approach that could improve predictive value of cancer genomic profiling, that is increasingly becoming the standard of care in breast cancer treatment. Additionally, uncovering cancer characteristics associated with PN symptoms could guide future research elucidating the underlying pathways of symptom development.
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Details
| Item Type: |
University of Pittsburgh ETD
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| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
30 July 2024 |
| Date Type: |
Publication |
| Defense Date: |
21 March 2024 |
| Approval Date: |
30 July 2024 |
| Submission Date: |
23 May 2024 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
116 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Nursing > Nursing |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
breast cancer, symptom science, genomic instability, liquid biopsies |
| Date Deposited: |
30 Jul 2024 19:27 |
| Last Modified: |
30 Jul 2024 19:47 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/46075 |
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