Biobehavioral modulation of the exosome transcriptome in ovarian carcinoma

Social factors in the patient macroenvironment have been shown to influence molecular events in the tumor microenvironment and thereby influence cancer progression. However, biomarkers providing a window into the longitudinal effects of biobehavioral factors on tumor biology over time are lacking. Exosome analysis is a novel strategy for in vivo monitoring of dynamic changes in tumor cells. This study examined exosomal profiles from patients with low or high levels of social support for epithelial-mesenchymal transition (EMT) polarization and gene expression related to inflammation and β-adrenergic signaling.

Exosomes were isolated from plasma sampled from a series of 40 women before primary surgical resection of advanced-stage, high-grade ovarian carcinoma. Samples were selected for analysis on the basis of extremes of low and high levels of social support. After exosomal isolation and RNA extraction, a microarray analysis of the transcriptome was performed.

Primary analyses identified significant upregulation of 67 mesenchymal-characteristic gene transcripts and downregulation of 63 epithelial-characteristic transcripts in patients with low social support; this demonstrated increased EMT polarization (P = .0002). Secondary analyses using promoter sequence bioinformatics supported a priori hypotheses linking low social support to 1) increased activity of cyclic adenosine monophosphate response element binding protein (CREB)/activating transcription factor (ATF) family transcription factors that mediate the β-adrenergic response to catecholamines via the cyclic adenosine monophosphate/protein kinase A signaling pathway (mean fold change for CREB: 2.24 ± 0.65; P = .0019; mean fold change for ATF: 2.00 ± 0.55; P = .0049) and 2) increased activity of the proinflammatory nuclear factor κB/Rel family of transcription factors (mean fold change: 2.10 ± 0.70; P = .0109).

These findings suggest the possibility of leveraging exosomes as a noninvasive assessment of biobehavioral factors to help to direct personalized treatment approaches. Cancer 2018;124:580-6. © 2017 American Cancer Society.