Extracellular Vesicle Molecular Signatures Characterize Metastatic Dynamicity in Ovarian Cancer

Simultaneously targeting extracellular vesicle trafficking and TGF-β receptor kinase activity blocks signaling hyperactivation and metastasis

Metastasis is the leading cause of cancer-related deaths. Transforming growth factor beta (TGF-β) signaling drives metastasis and is strongly enhanced during cancer progression. Yet, the use of on-target TGF-β signaling inhibitors in the treatment of cancer patients remains unsuccessful, highlighting a gap in the understanding of TGF-β biology that limits the establishment of efficient anti-metastatic therapies. Here, we show that TGF-β signaling hyperactivation in breast cancer cells is required for metastasis and relies on increased small extracellular vesicle (sEV) secretion. Demonstrating sEV's unique role, TGF-β signaling levels induced by sEVs exceed the activity of matching concentrations of soluble ligand TGF-β. Further, genetic disruption of sEV secretion in highly-metastatic breast cancer cells impairs cancer cell aggressiveness by reducing TGF-β signaling to nearly-normal levels. Otherwise, TGF-β signaling activity in non-invasive breast cancer cells is inherently low, but can be amplified by sEVs, enabling invasion and metastasis of poorly-metastatic breast cancer cells. Underscoring the translational potential of inhibiting sEV trafficking in advanced breast cancers, treatment with dimethyl amiloride (DMA) decreases sEV secretion, TGF-β signaling activity, and breast cancer progression in vivo. Targeting both the sEV trafficking and TGF-β signaling by combining DMA and SB431542 at suboptimal doses potentiated this effect, normalizing the TGF-β signaling in primary tumors to potently reduce circulating tumor cells, metastasis, and tumor self-seeding. Collectively, this study establishes sEVs as critical elements in TGF-β biology, demonstrating the feasibility of inhibiting sEV trafficking as a new therapeutic approach to impair metastasis by normalizing TGF-β signaling levels in breast cancer cells.

Extracellular vesicle small RNA cargo discriminates non-cancer donors from pediatric B-lymphoblastic leukemia patients

Pediatric B-acute lymphoblastic leukemia (B-ALL) is a disease of abnormally growing B lymphoblasts. Here we hypothesized that extracellular vesicles (EVs), which are nanosized particles released by all cells (including cancer cells), could be used to monitor B-ALL severity and progression by sampling plasma instead of bone marrow. EVs are especially attractive as they are present throughout the circulation regardless of the location of the originating cell. First, we used nanoparticle tracking analysis to compare EVs between non-cancer donor (NCD) and B-ALL blood plasma; we found that B-ALL plasma contains more EVs than NCD plasma. We then isolated EVs from NCD and pediatric B-ALL peripheral blood plasma using a synthetic peptide-based isolation technique (Vn96), which is clinically amenable and isolates a broad spectrum of EVs. RNA-seq analysis of small RNAs contained within the isolated EVs revealed a signature of differentially packaged and exclusively packaged RNAs that distinguish NCD from B-ALL. The plasma EVs contain a heterogenous mixture of miRNAs and fragments of long non-coding RNA (lncRNA) and messenger RNA (mRNA). Transcripts packaged in B-ALL EVs include those involved in negative cell cycle regulation, potentially suggesting that B-ALL cells may use EVs to discard gene sequences that control growth. In contrast, NCD EVs carry sequences representative of multiple organs, including brain, muscle, and epithelial cells. This signature could potentially be used to monitor B-ALL disease burden in pediatric B-ALL patients via blood draws instead of invasive bone marrow aspirates.

Extracellular Vesicles-ceRNAs as Ovarian Cancer Biomarkers: Looking into circRNA-miRNA-mRNA Code

Simple Summary

Patients with ovarian cancer have a very poor chance of long-term survival, usually due to advanced disease at the time of diagnosis. Emerging evidence suggests that extracellular vesicles contain noncoding RNAs such as microRNAs, piwiRNAs, circular RNAs, and long noncoding RNAs, with regulatory effects on ovarian cancer. In this review, we focus on ovarian cancer-associated circular RNA shuttled by extracellular vesicles as mediators of cancer progression and novel biomarkers in liquid biopsy. We propose a circular-RNA–microRNA-mRNA code that can reveal the regulatory network created by extracellular vesicles, noncoding RNAs, and mRNAs in ovarian cancer. Future research in this field will help to identify novel diagnostic biomarkers and druggable therapeutic targets, which will ultimately benefit patients.

Abstract

Ovarian cancer (OC) is one of the most lethal gynecologic malignancies in females worldwide. OC is frequently diagnosed at an advanced stage due to a lack of specific symptoms and effective screening tests, resulting in a poor prognosis for patients. Age, genetic alterations, and family history are the major risk factors for OC pathogenesis. Understanding the molecular mechanisms underlying OC progression, identifying new biomarkers for early detection, and discovering potential targets for new drugs are urgent needs. Liquid biopsy (LB), used for cancer detection and management, consists of a minimally invasive approach and practical alternative source to investigate tumor alterations by testing extracellular vesicles (EVs), circulating tumor cells, tumor-educated platelets, and cell-free nucleic acids. EVs are nanosize vesicles shuttling proteins, lipids, and nucleic acids, such as DNA, RNA, and non-coding RNAs (ncRNAs), that can induce phenotypic reprogramming of target cells. EVs are natural intercellular shuttles for ncRNAs, such as microRNAs (miRNAs) and circular-RNAs (circRNAs), known to have regulatory effects in OC. Here we focus on the involvement of circRNAs and miRNAs in OC cancer progression. The circRNA-microRNA-mRNA axis has been investigated with Circbank and miRwalk analysis, unraveling the intricate and detailed regulatory network created by EVs, ncRNAs, and mRNAs in OC.