Biobehavioral Factors Predict an Exosome Biomarker of Ovarian Carcinoma Disease Progression

Authors

Susan K Lutgendorf
Premal H Thaker
Michael J Goodheart
Jesusa M G Arevalo
Mamur A Chowdhury
Alyssa E Noble
Laila Dahmoush
George M Slavich
Frank J Penedo
Anil K Sood
Steven W Cole

Publication Date

12-1-2022

Journal

Cancer

Abstract

BACKGROUND: Biobehavioral factors such as social isolation and depression have been associated with disease progression in ovarian and other cancers. Here, the authors developed a noninvasive, exosomal RNA profile for predicting ovarian cancer disease progression and subsequently tested whether it increased in association with biobehavioral risk factors.

METHODS: Exosomes were isolated from plasma samples from 100 women taken before primary surgical resection or neoadjuvant (NACT) treatment of ovarian carcinoma and 6 and 12 months later. Biobehavioral measures were sampled at all time points. Plasma from 76 patients was allocated to discovery analyses in which morning presurgical/NACT exosomal RNA profiles were analyzed by elastic net machine learning to identify a biomarker predicting rapid (≤6 months) versus more extended disease-free intervals following initial treatment. Samples from a second subgroup of 24 patients were analyzed by mixed-effects linear models to determine whether the progression-predictive biomarker varied longitudinally as a function of biobehavioral risk factors (social isolation and depressive symptoms).

RESULTS: An RNA-based molecular signature was identified that discriminated between individuals who had disease progression in ≤6 months versus >6 months, independent of clinical variables (age, disease stage, and grade). In a second group of patients analyzed longitudinally, social isolation and depressive symptoms were associated with upregulated expression of the disease progression propensity biomarker, adjusting for covariates.

CONCLUSION: These data identified a novel exosome-derived biomarker indicating propensity of ovarian cancer progression that is sensitive to biobehavioral variables. This derived biomarker may be potentially useful for risk assessment, intervention targeting, and treatment monitoring.

Keywords

Humans, Female, Exosomes, Carcinoma, Ovarian Epithelial, Ovarian Neoplasms, Carcinoma, Biomarkers, RNA, Disease Progression, Ovarian cancer, exosome, social support, transcriptome, progression, biobehavioral

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Associated Data

PMID: 36251340