Circulating serum miR-362-3p and miR-6721-5p as potential biomarkers for classification patients with adult-type diffuse glioma.

According to the fifth edition of the WHO Classification of Tumours of the Central Nervous System (CNS) published in 2021, grade 4 gliomas classification includes IDH-mutant astrocytomas and wild-type IDH glioblastomas. Unfortunately, despite precision oncology development, the prognosis for patients with grade 4 glioma remains poor, indicating an urgent need for better diagnostic and therapeutic strategies. Circulating miRNAs besides being important regulators of cancer development could serve as promising diagnostic biomarkers for patients with grade 4 glioma. Here, we propose a two-miRNA miR-362-3p and miR-6721-5p screening signature for serum for non-invasive classification of identified glioma cases into the highest-grade 4 and lower-grade gliomas. A total of 102 samples were included in this study, comprising 78 grade 4 glioma cases and 24 grade 2-3 glioma subjects. Using the NanoString platform, seven miRNAs were identified as differentially expressed (DE), which was subsequently confirmed via RT-qPCR analysis. Next, numerous combinations of DE miRNAs were employed to develop classification models. The dual panel of miR-362-3p and miR-6721-5p displayed the highest diagnostic value to differentiate grade 4 patients and lower grade cases with an AUC of 0.867. Additionally, this signature also had a high AUC = 0.854 in the verification cohorts by RT-qPCR and an AUC = 0.842 using external data from the GEO public database. The functional annotation analyses of predicted DE miRNA target genes showed their primary involvement in the STAT3 and HIF-1 signalling pathways and the signalling pathway of pluripotency of stem cells and glioblastoma-related pathways. For additional exploration of miRNA expression patterns correlated with glioma, we performed the Weighted Gene-Co Expression Network Analysis (WGCNA). We showed that the modules most associated with glioma grade contained as many as six DE miRNAs. In conclusion, this study presents the first evidence of serum miRNA expression profiling in adult-type diffuse glioma using a classification based on the WHO 2021 guidelines. We expect that the discovered dual miR-362-3p and miR-6721-5p signatures have the potential to be utilised for grading gliomas in clinical applications.

Identification of MicroRNA Profiles in Fetal Spina Bifida: The Role in Pathomechanism and Diagnostic Significance.

Distinct miRNA expression patterns may reflect anomalies related to fetal congenital malformations such as spinal bifida (SB). The aim of this preliminary study was to determine the maternal miRNA expression profile of women carrying fetuses with SB. Therefore, six women carrying fetuses with SB and twenty women with euploid healthy fetuses were enrolled in this study. Using NanoString technology, we evaluated the expression level of 798 miRNAs in both plasma and amniotic fluid samples. A downregulation of miR-1253, miR-1290, miR-194-5p, miR-302d-3p, miR-3144-3p, miR-4536-5p, miR-548aa + miR-548t-3p, miR-548ar-5p, miR-548n, miR-590-5p, miR-612, miR-627-5p, miR-644a, and miR-122-5p, and an upregulation of miR-320e, let-7b-5p, miR-23a-3p, miR-873-3p, and miR-30d-5p were identified in maternal amniotic fluid samples in SB when compared to the control group. The target genes of these miRNAs play a predominant role in regulating the synthesis of several biological compounds related to signaling pathways such as those regulating the pluripotency of stem cells. Moreover, the maternal plasma expression of miR-320e was increased in pregnancies with SB, and this marker could serve as a valuable non-invasive screening tool. Our results highlight the SB-specific miRNA signature and the differentially expressed miRNAs that may be involved in SB pathogenesis. Our findings emphasize the role of miRNA as a predictive factor that could potentially be useful in prenatal genetic screening for SB.

Identification of serum miR-1246 and miR-150-5p as novel diagnostic biomarkers for high-grade serous ovarian cancer.

Epithelial ovarian cancer (EOC) is one of the leading cancers in women, with high-grade serous ovarian cancer (HGSOC) being the most common and lethal subtype of this disease. A vast majority of HGSOC are diagnosed at the late stage of the disease when the treatment and total recovery chances are low. Thus, there is an urgent need for novel, more sensitive and specific methods for early and routine HGSOC clinical diagnosis. In this study, we performed miRNA expression profiling using the NanoString miRNA assay in 34 serum samples from patients with HGSOC and 36 healthy women. We identified 13 miRNAs that were differentially expressed (DE). For additional exploration of expression patterns correlated with HGSOC, we performed weighted gene co-expression network analysis (WGCNA). As a result, we showed that the module most correlated with tumour size, nodule and metastasis contained 8 DE miRNAs. The panel including miR-1246 and miR-150-5p was identified as a signature that could discriminate HGSOC patients with AUCs of 0.98 and 1 for the training and test sets, respectively. Furthermore, the above two-miRNA panel had an AUC = 0.946 in the verification cohorts of RT-qPCR data and an AUC = 0.895 using external data from the GEO public database. Thus, the model we developed has the potential to markedly improve the diagnosis of ovarian cancer.

BCOR expression in paediatric pineoblastoma.

BCOR is expressed in a new brain tumour entity, i.e. 'CNS tumour with BCOR internal tandem duplication' (HGNET BCOR) but not in several other high grade paediatric brain tumours investigated. Immunohistochemical detection of BCOR expression may therefore serve as a potential diagnostic marker. Nevertheless, in rare paediatric glioma cases recurrent EP300-BCOR fusions were detected, which resulted in strong BCOR immunopositivity. We have therefore examined other, not analysed so far, types of central nervous system (CNS) tumours, pineoblastoma and germinoma, to assess a potential involvement of BCOR in these tumours. Levels of BCOR RNA expression were investigated by NanoString nCounter system analysis in a series of altogether 66 high grade paediatric tumours, including four pineoblastoma cases. Immunohistological detection of BCOR was performed in eight pineoblastoma, five germinoma and four atypical teratoid rhabdoid tumours (ATRTs), all located in the pineal region. We detected BCOR expression in all pineoblastomas, at the RNA and protein levels, but not in germinomas and ATRTs. Further analysis of pineoblastoma samples did not reveal the presence of either BCOR internal tandem duplication or BCOR fusion involvement. Positive immunohistological BCOR nuclear reaction in pineoblastoma may therefore differentiate this type of tumour from other high grade tumours located in the pineal region.

Identification and subsequent validation of transcriptomic signature associated with metabolic status in endometrial cancer.

Aberrant metabolism has been identified as a main driver of cancer. Profiling of metabolism-related pathways in cancer furthers the understanding of tumor plasticity and identification of potential metabolic vulnerabilities. In this prospective controlled study, we established transcriptomic profiles of metabolism-related pathways in endometrial cancer (EC) using a novel method, NanoString nCounter Technology. Fifty-seven ECs and 30 normal endometrial specimens were studied using the NanoString Metabolic Panel, further validated by qRT-PCR with a very high similarity. Statistical analyses were by GraphPad PRISM and Weka software. The analysis identified 11 deregulated genes (FDR ≤ 0.05; |FC|≥ 1.5) in EC: SLC7A11; SLC7A5; RUNX1; LAMA4; COL6A3; PDK1; CCNA1; ENO1; PKM; NR2F1; and NAALAD2. Gene ontology showed direct association of these genes with 'central carbon metabolism (CCM) in cancer'. Thus, 'CCM in cancer' appears to create one of the main metabolic axes in EC. Further, transcriptomic data were functionally validated with drug repurposing on three EC cell lines, with several drug candidates suggested. These results lay the foundation for personalized therapeutic strategies in this cancer. Metabolic plasticity represents a promising diagnostic and therapeutic option in EC.

Extracellular circulating miRNAs as potential non-invasive biomarkers in non-small cell lung cancer patients.

Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancers and is a malignant condition resistant to advanced-stage treatment. Despite the advancement in detection and treatment techniques, the disease is taking a deadly toll worldwide, being the leading cause of cancer death every year. Current diagnostic methods do not ensure the detection of the disease at an early stage, nor can they predict the risk of its development. There is an urgent need to identify biomarkers that can help predict an individual's risk of developing NSCLC, distinguish NSCLC subtype, allow monitor disease and treatment progression which can improve patient survival. Micro RNAs (miRNAs) represent the class of small and non-coding RNAs involved in gene expression regulation, influencing many biological processes such as proliferation, differentiation, and carcinogenesis. Research reports significant differences in miRNA profiles between healthy and neoplastic tissues in NSCLC. Its abundant presence in biofluids, such as serum, blood, urine, and saliva, makes them easily detectable and does not require invasive collection techniques. Many studies support miRNAs' importance in detecting, predicting, and prognosis of NSCLC, indicating their utility as a promising biomarker. In this work, we reviewed up-to-date research focusing on biofluid miRNAs' role as a diagnostic tool in NSCLC cases. We also discussed the limitations of applying miRNAs as biomarkers and highlighted future areas of interest.

Pharmacovariome scanning using whole pharmacogene resequencing coupled with deep computational analysis and machine learning for clinical pharmacogenomics.

BACKGROUND: This pilot study aims to identify and functionally assess pharmacovariants in whole exome sequencing data. While detection of known variants has benefited from pharmacogenomic-dedicated bioinformatics tools before, in this paper we have tested novel deep computational analysis in addition to artificial intelligence as possible approaches for functional analysis of unknown markers within less studied drug-related genes. METHODS: Pharmacovariants from 1800 drug-related genes from 100 WES data files underwent (a) deep computational analysis by eight bioinformatic algorithms (overall containing 23 tools) and (b) random forest (RF) classifier as the machine learning (ML) approach separately. ML model efficiency was calculated by internal and external cross-validation during recursive feature elimination. Protein modelling was also performed for predicted highly damaging variants with lower frequencies. Genotype-phenotype correlations were implemented for top selected variants in terms of highest possibility of being damaging. RESULTS: Five deleterious pharmacovariants in the RYR1, POLG, ANXA11, CCNH, and CDH23 genes identified in step (a) and subsequent analysis displayed high impact on drug-related phenotypes. Also, the utilization of recursive feature elimination achieved a subset of 175 malfunction pharmacovariants in 135 drug-related genes that were used by the RF model with fivefold internal cross-validation, resulting in an area under the curve of 0.9736842 with an average accuracy of 0.9818 (95% CI: 0.89, 0.99) on predicting whether a carrying individuals will develop adverse drug reactions or not. However, the external cross-validation of the same model indicated a possible false positive result when dealing with a low number of observations, as only 60 important variants in 49 genes were displayed, giving an AUC of 0.5384848 with an average accuracy of 0.9512 (95% CI: 0.83, 0.99). CONCLUSION: While there are some technologies for functionally assess not-interpreted pharmacovariants, there is still an essential need for the development of tools, methods, and algorithms which are able to provide a functional prediction for every single pharmacovariant in both large-scale datasets and small cohorts. Our approaches may bring new insights for choosing the right computational assessment algorithms out of high throughput DNA sequencing data from small cohorts to be used for personalized drug therapy implementation.

Human Gut Microbiota in Coronary Artery Disease: A Systematic Review and Meta-Analysis.

In recent years, the importance of the gut microbiome in human health and disease has increased. Growing evidence suggests that gut dysbiosis might be a crucial risk factor for coronary artery disease (CAD). Therefore, we conducted a systematic review and meta-analysis to determine whether or not CAD is associated with specific changes in the gut microbiome. The V3-V4 regions of the 16S rDNA from fecal samples were analyzed to compare the gut microbiome composition between CAD patients and controls. Our search yielded 1181 articles, of which 21 met inclusion criteria for systematic review and 7 for meta-analysis. The alpha-diversity, including observed OTUs, Shannon and Simpson indices, was significantly decreased in CAD, indicating the reduced richness of the gut microbiome. The most consistent results in a systematic review and meta-analysis pointed out the reduced abundance of Bacteroidetes and Lachnospiraceae in CAD patients. Moreover, Enterobacteriaceae, Lactobacillus, and Streptococcus taxa demonstrated an increased trend in CAD patients. The alterations in the gut microbiota composition are associated with qualitative and quantitative changes in bacterial metabolites, many of which have pro-atherogenic effects on endothelial cells, increasing the risk of developing and progressing CAD.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

The short-term and long-term effects of intranasal mesenchymal stem cell administration to noninflamed mice lung.

Mesenchymal stem cells (mesenchymal stromal cells; MSC)-based therapies remain a promising approach to treat degenerative and inflammatory diseases. Their beneficial effects were confirmed in numerous experimental models and clinical trials. However, safety issues concerning MSCs' stability and their long-term effects limit their implementation in clinical practice, including treatment of respiratory diseases such as asthma, chronic obstructive pulmonary disease, and COVID-19. Here, we aimed to investigate the safety of intranasal application of human adipose tissue-derived MSCs in a preclinical experimental mice model and elucidate their effects on the lungs. We assessed short-term (two days) and long-term (nine days) effects of MSCs administration on lung morphology, immune responses, epithelial barrier function, and transcriptomic profiles. We observed an increased frequency of IFNγ- producing T cells and a decrease in occludin and claudin 3 as a long-term effect of MSCs administration. We also found changes in the lung transcriptomic profiles, reflecting redox imbalance and hypoxia signaling pathway. Additionally, we found dysregulation in genes clustered in pattern recognition receptors, macrophage activation, oxidative stress, and phagocytosis. Our results suggest that i.n. MSCs administration to noninflamed healthy lungs induces, in the late stages, low-grade inflammatory responses aiming at the clearance of MSCs graft.

Serum miRNA Profile in Diabetic Patients With Ischemic Heart Disease as a Promising Non-Invasive Biomarker.

The increasing morbidity and mortality of type 2 diabetic mellitus (T2DM) patients with ischemic heart disease (IHD) highlight an urgent need to identify early biomarkers, which would help to predict individual risk of development of IHD. Here, we postulate that circulating serum-derived micro RNAs (miRNAs) may serve as potential biomarkers for early IHD diagnosis and support the identification of diabetic individuals with a predisposition to undergo IHD. We obtained serum samples from T2DM patients either with IHD or IHD-free and analysed the expression levels of 798 miRNAs using the NanoString nCounter technology platform. The prediction of the putative miRNAs targets was performed using the Ingenuity Pathway Analysis (IPA) software. Gene Ontology (GO) analysis was used to identify the biological function and signalling pathways associated with miRNA target genes. Hub genes of protein-protein interaction (PPI) network were identified by STRING database and Cytotoscape tool. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic value of identified miRNAs. Real-time quantitative polymerase chain reaction (qRT-PCR) was used for nCounter platform data validation. Our data showed that six miRNAs (miR-615-3p, miR-3147, miR-1224-5p, miR-5196-3p, miR-6732-3p, and miR-548b-3p) were significantly upregulated in T2DM IHD patients compared to T2DM patients without IHD. Further analysis indicated that 489 putative target genes mainly affected the endothelin-1 signalling pathway, glucocorticoid biosynthesis, and apelin cardiomyocyte signalling pathway. All tested miRNAs showed high diagnostic value (AUC = 0.779 - 0.877). Taken together, our research suggests that circulating miRNAs might have a crucial role in the development of IHD in diabetic patients and may be used as a potential biomarker for early diagnosis.

Expression Profile and Diagnostic Significance of MicroRNAs in Papillary Thyroid Cancer.

The incidence of papillary thyroid cancer (PTC) has increased in recent years. To improve the diagnostic management of PTC, we propose the use of microRNAs (miRNAs) as a biomarker. Our aim in this study was to evaluate the miRNA expression pattern in PTC using NanoString technology. We identified ten miRNAs deregulated in PTC compared with reference tissue: miR-146b-5p, miR-221-3p, miR-221-5p, miR-34-5p, miR-551b-3p, miR-152-3p, miR-15a-5p, miR-31-5p, and miR-7-5p (FDR < 0.05; |fold change (FC)| ≥ 1.5). The gene ontology (GO) analysis of differentially expressed miRNA (DEM) target genes identified the predominant involvement of epidermal growth factor receptor (EGFR), tyrosine kinase inhibitor resistance, and pathways in cancer in PTC. The highest area under the receiver operating characteristic (ROC) curve (AUC) for DEMs was found for miR-146-5p (AUC = 0.770) expression, indicating possible clinical applicability in PTC diagnosis. The combination of four miRNAs (miR-152-3p, miR-221-3p, miR-551b-3p, and miR-7-5p) showed an AUC of 0.841. Validation by real-time quantitative polymerase chain reactions (qRT-PCRs) confirmed our findings. The introduction of an miRNA diagnostic panel based on the results of our study may help to improve therapeutic decision making for questionable cases. The use of miRNAs as biomarkers of PTC may become an aspect of personalized medicine.

Alpha-smooth muscle actin-positive cancer-associated fibroblasts secreting osteopontin promote growth of luminal breast cancer.

BACKGROUND: Cancer-associated fibroblasts (CAFs) have been shown to support tumor development in a variety of cancers. Different markers were applied to classify CAFs in order to elucidate their impact on tumor progression. However, the exact mechanism by which CAFs enhance cancer development and metastasis is yet unknown. METHODS: Alpha-smooth muscle actin (α-SMA) was examined immunohistochemically in intratumoral CAFs of nonmetastatic breast cancers and correlated with clinicopathological data. Four CAF cell lines were isolated from patients with luminal breast cancer (lumBC) and classified according to the presence of α-SMA protein. Conditioned medium (CM) from CAF cultures was used to assess the influence of CAFs on lumBC cell lines: MCF7 and T47D cells using Matrigel 3D culture assay. To identify potential factors accounting for promotion of tumor growth by α-SMAhigh CAFs, nCounter PanCancer Immune Profiling Panel (NanoString) was used. RESULTS: In luminal breast cancer, presence of intratumoral CAFs expressing high level of α-SMA (13% of lumBC group) correlated with poor prognosis (p = 0.019). In in vitro conditions, conditioned medium obtained from primary cultures of α-SMA-positive CAFs isolated from luminal tumors was observed to enhance growth of lumBC cell line colonies in 3D Matrigel, in contrast to CM derived from α-SMA-negative CAFs. Multigene expression analysis indicated that osteopontin (OPN) was overexpressed in α-SMA-positive CAFs in both clinical samples and in vitro models. OPN expression was associated with higher percentage of Ki67-positive cells in clinical material (p = 0.012), while OPN blocking in α-SMA-positive CAF-derived CM attenuated growth of lumBC cell line colonies in 3D Matrigel. CONCLUSIONS: Our findings demonstrate that α-SMA-positive CAFs might enhance tumor growth via secretion of OPN.

ERα36-High Cancer-Associated Fibroblasts as an Unfavorable Factor in Triple-Negative Breast Cancer.

Background: Cancer-associated fibroblasts (CAFs) are the most abundant cell type in the tumor microenvironment (TME). Estrogen receptor alpha 36 (ERα36), the alternatively spliced variant of ERα, is described as an unfavorable factor when expressed in cancer cells. ERα can be expressed also in CAFs; however, the role of ERα36 in CAFs is unknown. Methods: Four CAF cultures were isolated from chemotherapy-naïve BC patients and characterized for ERα36 expression and the NanoString gene expression panel using isolated RNA. Conditioned media from CAF cultures were used to assess the influence of CAFs on triple-negative breast cancer (TNBC) cells using a matrigel 3D culture assay. Results: We found that ERα36high CAFs significantly induced the branching of TNBC cells in vitro (p < 0.001). They also produced a set of pro-tumorigenic cytokines compared to ERα36low CAFs, among which hepatocyte growth factor (HGF) was the main inducer of TNBC cell invasive phenotype in vitro (p < 0.001). Tumor stroma rich in ERα36high CAFs was correlated with high Ki67 expression (p = 0.041) and tumor-associated macrophages markers (CD68 and CD163, p = 0.041 for both). HGF was found to be an unfavorable prognostic factor in TCGA database analysis (p = 0.03 for DFS and p = 0.04 for OS). Conclusions: Breast cancer-associated fibroblasts represent distinct subtypes based on ERα36 expression. We propose that ERα36high CAFs could account for an unfavorable prognosis for TNBC patients.

miRNAs as Predictive Factors in Early Diagnosis of Gestational Diabetes Mellitus.

Introduction: Circulating miRNAs are important mediators in epigenetic changes. These non-coding molecules regulate post-transcriptional gene expression by binding to mRNA. As a result, they influence the development of many diseases, such as gestational diabetes mellitus (GDM). Therefore, this study investigates the changes in the miRNA profile in GDM patients before hyperglycemia appears. Materials and Methods: The study group consisted of 24 patients with GDM, and the control group was 24 normoglycemic pregnant women who were matched for body mass index (BMI), age, and gestational age. GDM was diagnosed with an oral glucose tolerance test between the 24th and 26th weeks of pregnancy. The study had a prospective design, and serum for analysis was obtained in the first trimester of pregnancy. Circulating miRNAs were measured using the NanoString quantitative assay platform. Validation with real time-polymerase chain reaction (RT-PCR) was performed on the same group of patients. Mann-Whitney U-test and Spearman correlation were done to assess the significance of the results. Results: Among the 800 miRNAs, 221 miRNAs were not detected, and 439 were close to background noise. The remaining miRNAs were carefully investigated for their average counts, fold changes, p-values, and false discovery rate (FDR) scores. We selected four miRNAs for further validation: miR-16-5p, miR-142-3p, miR-144-3p, and miR-320e, which showed the most prominent changes between the studied groups. The validation showed up-regulation of miR-16-5p (p<0.0001), miR-142-3p (p=0.001), and miR-144-3p (p=0.003). Conclusion: We present changes in miRNA profile in the serum of GDM women, which may indicate significance in the pathophysiology of GDM. These findings emphasize the role of miRNAs as a predictive factor that could potentially be useful in early diagnosis.

MicroRNA Profile Alterations in Parathyroid Carcinoma: Latest Updates and Perspectives.

Parathyroid tumors are a genetically heterogenous group with a significant variability in clinical features. Due to a lack of specific signs and symptoms and uncertain histopathological criteria, parathyroid carcinomas (PCs) are challenging to diagnose, both before and after surgery. There is a great interest in searching for accurate molecular biomarkers for early detection, disease monitoring, and clinical management. Due to improvements in molecular pathology, the latest studies have reported that PC tumorigenesis is strongly linked to the epigenetic regulation of gene expression. MicroRNA (miRNA) profiling may serve as a helpful adjunct in distinguishing parathyroid adenoma (PAd) from PC and provide further insight into regulatory pathways involved in PTH release and parathyroid tumorigenesis. So far, only a few studies have attempted to show the miRNA signature for PC, and very few overlaps could be found between these relatively similar studies. A global miRNA downregulation was detected in PC compared with normal glands among differentially expressed miRNAs. This review summarizes changes in miRNA expression in PC and discusses the future research directions in this area.

The Role of Androgen Receptor and microRNA Interactions in Androgen-Dependent Diseases.

The androgen receptor (AR) is a member of the steroid hormone receptor family of nuclear transcription factors. It is present in the primary/secondary sexual organs, kidneys, skeletal muscles, adrenal glands, skin, nervous system, and breast. Abnormal AR functioning has been identified in numerous diseases, specifically in prostate cancer (PCa). Interestingly, recent studies have indicated a relationship between the AR and microRNA (miRNA) crosstalk and cancer progression. MiRNAs are small, endogenous, non-coding molecules that are involved in crucial cellular processes, such as proliferation, apoptosis, or differentiation. On the one hand, AR may be responsible for the downregulation or upregulation of specific miRNA, while on the other hand, AR is often a target of miRNAs due to their regulatory function on AR gene expression. A deeper understanding of the AR-miRNA interactions may contribute to the development of better diagnostic tools as well as to providing new therapeutic approaches. While most studies usually focus on the role of miRNAs and AR in PCa, in this review, we go beyond PCa and provide insight into the most recent discoveries about the interplay between AR and miRNAs, as well as about other AR-associated and AR-independent diseases.

Exploring microRNAs as predictive biomarkers for type 2 diabetes mellitus remission after sleeve gastrectomy: A pilot study.

OBJECTIVE: This study aimed to evaluate microRNAs (miRNAs) as predictive biomarkers for type 2 diabetes (T2D) remission 12 months after sleeve gastrectomy (SG). METHODS: A total of 179 serum miRNAs were profiled, and 26 clinical variables were collected from 46 patients. Two patients were later excluded because of hemolysis, and six patients with unclear remission status were set aside to evaluate the prediction models. The remaining 38 patients were included for model building. Variable selection was done using different approaches, including Least Absolute Shrinkage and Selection Operator (LASSO). Prediction models were then developed using LASSO and assessed in the validation set. RESULTS: A total of 26 out of 38 patients achieved T2D remission 12 months after SG. The prediction model with only clinical variables misclassified two patients, which were correctly classified using miRNAs. Two miRNA-only models achieved an accuracy of one but performed poorly for the validation set. The best miRNA model was a mixed model (accuracy: 0.974) containing four miRNAs (hsa-miR-32-5p, hsa-miR-382-5p, hsa-miR-1-3p, and hsa-miR-21-5p) and four clinical variables (T2D medication, sex, age, and fasting blood glucose). These miRNAs are involved in pathways related to obesity and insulin resistance. CONCLUSIONS: This study suggests that four serum miRNAs might be predictive biomarkers for T2D remission 12 months after SG, but further validation studies are needed.

Low Tumor-to-Stroma Ratio Reflects Protective Role of Stroma against Prostate Cancer Progression.

Tumor-to-stroma ratio (TSR) is a prognostic factor that expresses the relative amounts of tumor and intratumoral stroma. In this study, its clinical and molecular relevance was evaluated in prostate cancer (PCa). The feasibility of automated quantification was tested in digital scans of tissue microarrays containing 128 primary tumors from 72 PCa patients stained immunohistochemically for epithelial cell adhesion molecule (EpCAM), followed by validation in a cohort of 310 primary tumors from 209 PCa patients. In order to investigate the gene expression differences between tumors with low and high TSR, we applied multigene expression analysis (nCounter® PanCancer Progression Panel, NanoString) of 42 tissue samples. TSR scores were categorized into low (<1 TSR) and high (≥1 TSR). In the pilot cohort, 31 patients (43.1%) were categorized as low and 41 (56.9%) as high TSR score, whereas 48 (23.0%) patients from the validation cohort were classified as low TSR and 161 (77.0%) as high. In both cohorts, high TSR appeared to indicate the shorter time to biochemical recurrence in PCa patients (Log-rank test, p = 0.04 and p = 0.01 for the pilot and validation cohort, respectively). Additionally, in the multivariate analysis of the validation cohort, TSR predicted BR independent of other factors, i.e., pT, pN, and age (p = 0.04, HR 2.75, 95%CI 1.07-7.03). Our data revealed that tumors categorized into low and high TSR score show differential expression of various genes; the genes upregulated in tumors with low TSR score were mostly associated with extracellular matrix and cell adhesion regulation. Taken together, this study shows that high stroma content can play a protective role in PCa. Automatic EpCAM-based quantification of TSR might improve prognostication in personalized medicine for PCa.