<p>PDF file - 179KB, Sequence of oligonucleotides used in this study.</p>

<p>PDF file - 2673KB, MiR-30s target BCL9 in MM cells.</p>

PDF file - 141KB

PDF file - 2071KB, MiR-30s treatment does not have a negative impact on bone disease in MM1S-Luc-Neo bearing mice.

<p>PDF file - 2673KB, MiR-30s target BCL9 in MM cells.</p>

<p>PDF file - 1007KB, Knockdown expression of miR-30s enhances BCL9 expression in MM cells.</p>

<p>PDF file - 1392KB, BMSCs decrease miR-30s levels, and enforced expression of miR-30s inhibits CAM-DR in MM cells.</p>

<p>PDF file - 1007KB, Knockdown expression of miR-30s enhances BCL9 expression in MM cells.</p>

PDF file - 179KB, Sequence of oligonucleotides used in this study.

EDITORIAL article Front. Immunol., 18 March 2022Sec. Autoimmune and Autoinflammatory Disorders Volume 13 - 2022 | https://doi.org/10.3389/fimmu.2022.725090

MicroRNA-200 (miR-200) family is highly expressed in ovarian cancer. We evaluated the levels of family members relative to the internal control miR-103a in ovarian cancer and control blood specimens collected from American and Hong Kong Chinese institutions, as well as from a laying hen spontaneous ovarian cancer model. The levels of miR-200a, miR-200b and miR-200c were significantly elevated in all human cancer versus all control blood samples. Further analyses showed significantly higher miR-200 levels in Chinese control (except miR-429) and cancer (except miR-200a and miR141) samples than their respective American counterparts. Subtype-specific analysis showed that miR-200b had an overall elevated level in serous cancer compared with controls, whereas miR-429 was significantly elevated in clear cell and endometrioid cancer versus controls. MiR-429 was also significantly elevated in cancer versus control in laying hen plasma samples, consistent with the fact that endometrioid tumor is the prevalent type in this species. A neural network model consisting of miR-200a/200b/429/141 showed an area under the curve (AUC) value of 0.904 for American ovarian cancer prediction, whereas a model consisting of miR-200b/200c/429/141 showed an AUC value of 0.901 for Chinese women. Hence, miR-200 is informative as blood biomarkers for both human and laying hen ovarian cancer.

INTRODUCTION:In general, mice develop chronic and nonhealing periapical lesions after endodontic infection. Surprisingly, we recently found that toll-like receptor 2 (TLR2)/interleukin 10 (IL-10) double-knockout (dKO) mice exhibited acute but resolving osteomyelitislike inflammation. In this study, we examined the kinetics of endodontic infection-induced inflammation in TLR2/IL-10 dKO mice and explored a potential mechanism of periapical wound healing mediated by the hypoxia-inducible factor 1 alpha (HIF-1α) subunit and arginase 1. METHODS:TLR2/IL-10 dKO and wild-type C57BL/6J mice were subjected to endodontic infection in the mandibular first molars. Mice were sacrificed on days 0 (noninfected), 10, and 21 postinfection. The extent of bone destruction, inflammation, bone deposition, and gene expression were determined by micro-computed tomographic imaging, histology, bone polychrome labeling, and microarray analysis. In addition, the effect of blocking endogenous HIF-1α was tested in infected TLR2/IL-10 dKO mice using the specific inhibitor YC-1. RESULTS:Infected TLR2/IL-10 dKO mice exhibited extensive bone destruction and inflammation on day 10 followed by spontaneous periapical wound healing including bone formation and resolution of inflammation by day 21 postinfection. In contrast, WT mice developed increasing chronic periapical inflammation over the 21-day observation period. Gene expression analyses and immunohistochemistry revealed that HIF-1α and arginase 1 were up-regulated in spontaneous wound healing in TLR2/IL-10 dKO mice. Blocking of HIF-1α in TLR2/IL-10 dKO mice using YC-1 resulted in significant inhibition of regenerative bone formation. CONCLUSIONS:The TLR2/IL-10 dKO mouse is a novel model resembling osteomyelitis of the jaws in which HIF-1α and arginase 1 appear to be crucial factors in spontaneous wound healing and bone repair.

Precision medicine has emerged as an approach to tailor therapies for an individual at the time of diagnosis and/or treatment. This emergence has been fueled by the ability to profile nucleic acids, along with proteins and lipids isolated from biofluids, a method called “liquid biopsy,” either by or in combination of one of the following components: circulating tumor cells (CTCs), cell-free DNA (cfDNA), and/or extracellular vesicles (EVs). EVs are membrane-surrounded structures released by cells in an evolutionarily conserved manner. EVs have gained much attention from both the basic and clinical research areas, as EVs appear to play a role in many diseases; however, the well-known case is cancer. The hallmark of EVs in cancer is their role as mediators of communication between cells both at physiological and pathophysiological levels; hence, EVs are thought to contribute to the creation of a microenvironmental niche that promotes cancer cell survival, as well as reprogramming distant tissue for invasion. It is important to understand the mechanistic and functional aspects at the basic science level of EVs to get a better grasp on their role in healthy and disease states. EVs range from 30–1000 nm membrane-enclosed vesicles that are released by many mammalian cell types and present in a variety of biofluids. EVs have emerged as an area of clinical interest in the era of Precision Medicine, from their role in liquid biopsy (tissue biopsy free) approach for screening, assessing tumor heterogeneity, monitoring therapeutic responses, and minimal residual disease detection to EV-based therapeutics. EVs’ diagnostic and therapeutic exploitation is under intense investigation in various indications. This chapter highlights EV biogenesis, composition of EVs, and their potential role in liquid biopsy diagnostics and therapeutics in the area of cancer.

Extracellular vesicles (EVs), including exosomes and microvesicles, are present in a variety of bodily fluids, and the concentration of these sub-cellular vesicles and their associated biomarkers (proteins, nucleic acids, and lipids) can be used to aid clinical diagnosis. Although ultracentrifugation is commonly used for isolation of EVs, it is highly time-consuming, labor-intensive and instrument-dependent for both research laboratories and clinical settings. Here, we developed an integrated double-filtration microfluidic device that isolated and enriched EVs with a size range of 30–200 nm from urine, and subsequently quantified the EVs via a microchip ELISA. Our results showed that the concentration of urinary EVs was significantly elevated in bladder cancer patients (n = 16) compared to healthy controls (n = 8). Receiver operating characteristic (ROC) analysis demonstrated that this integrated EV double-filtration device had a sensitivity of 81.3% at a specificity of 90% (16 bladder cancer patients and 8 healthy controls). Thus, this integrated device has great potential to be used in conjunction with urine cytology and cystoscopy to improve clinical diagnosis of bladder cancer in clinics and at point-of-care (POC) settings.

During their lifetime, like all other cell types, red blood cells (RBCs) release both exosomes and plasma membrane derived EVs (ectosomes). RBC exosomes are formed only during the development of RBCs in bone marrow, and are released following the fusion of microvesicular bodies (MVB) with the plasma membrane. On the other hand, RBC EVs are generated during normal aging of RBCs in circulation by budding of the plasma membrane due to complement-mediated calcium influx, followed by vesicle shedding. This makes red blood cells and stored red cells a reliable source of EVs for basic and clinical research.

Precision medicine has emerged as an approach to tailor therapies for an individual at the time of diagnosis and/or treatment. This emergence has been fueled by the ability to profile nucleic acids, along with proteins and lipids isolated from biofluids, a method called "liquid biopsy," either by or in combination of one of the following components: circulating tumor cells (CTCs), cell-free DNA (cfDNA), and/or extracellular vesicles (EVs). EVs are membrane-surrounded structures released by cells in an evolutionarily conserved manner. EVs have gained much attention from both the basic and clinical research areas, as EVs appear to play a role in many diseases; however, the well-known case is cancer. The hallmark of EVs in cancer is their role as mediators of communication between cells both at physiological and pathophysiological levels; hence, EVs are thought to contribute to the creation of a microenvironmental niche that promotes cancer cell survival, as well as reprogramming distant tissue for invasion. It is important to understand the mechanistic and functional aspects at the basic science level of EVs to get a better grasp on their role in healthy and disease states. EVs range from 30-1000 nm membrane-enclosed vesicles that are released by many mammalian cell types and present in a variety of biofluids. EVs have emerged as an area of clinical interest in the era of Precision Medicine, from their role in liquid biopsy (tissue biopsy free) approach for screening, assessing tumor heterogeneity, monitoring therapeutic responses, and minimal residual disease detection to EV-based therapeutics. EVs' diagnostic and therapeutic exploitation is under intense investigation in various indications. This chapter highlights EV biogenesis, composition of EVs, and their potential role in liquid biopsy diagnostics and therapeutics in the area of cancer.

The management of cancer relies on a combination of imaging and tissue biopsy for diagnosis, monitoring, and molecular classification-based patient stratification to ensure appropriate treatment. Conventional tissue biopsy harvests tumor samples with invasive procedures, which are often difficult for patients with advanced disease. Given the well-recognized intratumor genetic heterogeneity [1], the biopsy of small tumor fragments does not necessarily represent all the genetic aberrations in the tumor, but sampling the entire tumor in each patient is not realistic. Moreover, tumors evolve all the time from local to advanced disease and by adapting to selective pressure from treatment.