Abstract
Comorbid Type 2 diabetes (T2D), a metabolic complication of obesity, associates with worse cancer outcomes for prostate, breast, head and neck, colorectal and several other solid tumors. However, the molecular mechanisms remain poorly understood. Emerging evidence shows that exosomes carry miRNAs in blood that encode the metabolic status of originating tissues and deliver their cargo to target tissues to modulate expression of critical genes. Exosomal communication potentially connects abnormal metabolism to cancer progression. Here, we hypothesized that T2D plasma exosomes induce epithelial-mesenchymal transition (EMT) and immune checkpoints in prostate cancer cells. We demonstrate that plasma exosomes from subjects with T2D induce EMT features in prostate cancer cells and upregulate the checkpoint genes CD274 and CD155. We demonstrate that specific exosomal miRNAs that are differentially abundant in plasma of T2D adults compared to nondiabetic controls (miR374a-5p, miR-93-5p and let-7b-3p) are delivered to cancer cells, thereby regulating critical target genes. We build on our previous reports showing BRD4 controls migration and dissemination of castration-resistant prostate cancer, and transcription of key EMT genes, to show that T2D exosomes require BRD4 to drive EMT and immune ligand expression. We validate our findings with gene set enrichment analysis of human prostate tumor tissue in TGCA genomic data. These results suggest novel, non-invasive approaches to evaluate and potentially block progression of prostate and other cancers in patients with comorbid T2D.
Competing Interest Statement
G.V.D. and N.J are inventors on U.S. patent 63/171,689 to use exosomes as a cancer diagnostic.
Footnotes
Grant support: This study was supported by grants from the National Institutes of Health (DK090455, U01CA182898, R01CA222170; GV Denis).
The EMT signature has been validated now in 2 additional human prostate cancer cell lines, for a total of four models that now demonstrate responsiveness to exosomal miRNAs from peripheral blood plasma of adults with Type 2 diabetes. We also undertook more detailed analysis of how the cell line EMT signatures correlate with human prostate cancer clinical samples, in which EMT signatures are apparent. We have previously noted that the human cell line reagents available to model the stages of prostate cancer progression are relatively few, and idiosyncratic, not fully capturing the range of cellular and transcriptional heterogeneity or plasticity observed in human primary prostate cancer. Therefore, some sort of in vivo or clinical data are critical to confirm that results actually have relevance and impact for patients with prostate cancer. We address two major hypotheses: 1.Specific plasma exosomal miRNAs could be useful as non-invasive biomarkers, when viewed through the lens of EMT. 2.Specific exosomal miRNAs (miR-374, miR-93, Let-7b) promote tumor aggressiveness in prostate cancer cell lines, when viewed through the lens of EMT. We have good evidence to support these interpretations. In order to highlight these findings, we have included a new Fig 6. The original Fig. 6, which was a schematic of proposed signaling by miRNAs in prostate cancer, has been relabeled Fig. 7. Details of how the three top hit exosomal miRNAs induce EMT as analyzed in two independent prostate cancer cell lines (DU145 and PC3) are shown in a new Fig. S11. In short, we find that the miRNAs on which we focus the mechanistic studies are indeed strongly associated with EMT in genomic databases of primary cancer tissue.
Abbreviations
- ADT
- androgen deprivation therapy
- BET
- Bromodomain and ExtraTerminal
- DAPI
- 4′,6-diamidino-2-phenylindole dihydrochloride
- EMT
- epithelial-to-mesenchymal transition
- FBS
- fetal bovine serum
- FDR
- false discovery rate
- IFN
- interferon
- IPA
- Ingenuity Pathway Analysis
- ND
- non-diabetic
- PCA
- principal components analysis
- PD-L1
- programmed death-ligand 1
- PROTAC
- proteolysis-targeting chimera
- PSA
- prostate specific antigen
- T2D
- Type 2 diabetes
- TGF
- Transforming Growth Factor
- VST
- variance-stabilizing transformation