Systematic immune cell dysregulation and molecular subtypes revealed by single-cell RNA-seq of subjects with type 1 diabetes.

BACKGROUND: Type 1 diabetes mellitus (T1DM) is a prototypic endocrine autoimmune disease resulting from an immune-mediated destruction of pancreatic insulin-secreting ß  cells. A comprehensive immune cell phenotype evaluation in T1DM has not been performed thus far at the single-cell level. METHODS: In this cross-sectional analysis, we generated a single-cell transcriptomic dataset of peripheral blood mononuclear cells (PBMCs) from 46 manifest T1DM (stage 3) cases and 31 matched controls. RESULTS: We surprisingly detected profound alterations in circulatory immune cells (1784 dysregulated genes in 13 immune cell types), far exceeding the count in the comparator systemic autoimmune disease SLE. Genes upregulated in T1DM were involved in WNT signaling, interferon signaling and migration of T/NK cells, antigen presentation by B cells, and monocyte activation. A significant fraction of these differentially expressed genes were also altered in T1DM pancreatic islets. We used the single-cell data to construct a T1DM metagene z-score (TMZ score) that distinguished cases and controls and classified patients into molecular subtypes. This score correlated with known prognostic immune markers of T1DM, as well as with drug response in clinical trials. CONCLUSIONS: Our study reveals a surprisingly strong systemic dimension at the level of immune cell network in T1DM, defines disease-relevant molecular subtypes, and has the potential to guide non-invasive test development and patient stratification.

Deciphering the immune landscape of head and neck squamous cell carcinoma: A single-cell transcriptomic analysis of regulatory T cell responses to PD-1 blockade therapy.

Immunotherapy is changing the Head and Neck Squamous Cell Carcinoma (HNSCC) landscape and improving outcomes for patients with recurrent or metastatic HNSCC. A deeper understanding of the tumor microenvironment (TME) is required in light of the limitations of patients' responses to immunotherapy. Here, we aimed to examine how Nivolumab affects infiltrating Tregs in the HNSCC TME. We used single-cell RNA sequencing data from eight tissues isolated from four HNSCC donors before and after Nivolumab treatment. Interestingly, the study found that Treg counts and suppressive activity increased following Nivolumab therapy. We also discovered that changes in the CD44-SSP1 axis, NKG2C/D-HLA-E axis, and KRAS signaling may have contributed to the increase in Treg numbers. Furthermore, our study suggests that decreasing the activity of the KRAS and Notch signaling pathways, and increasing FOXP3, CTLA-4, LAG-3, and GZMA expression, may be mechanisms that enhance the killing and suppressive capacity of Tregs. Additionally, the result of pseudo-temporal analysis of the HNSCC TME indicated that after Nivolumab therapy, the expression of certain inhibitory immune checkpoints including TIGIT, ENTPD1, and CD276 and LY9, were decreased in Tregs, while LAG-3 showed an increased expression level. The study also found that Tregs had a dense communication network with cluster two, and that certain ligand-receptor pairs, including SPP1/CD44, HLA-E/KLRC2, HLA-E/KLRK1, ANXA1/FPR3, and CXCL9/FCGR2A, had notable changes after the therapy. These changes in gene expression and cell interactions may have implications for the role of Tregs in the TME and in response to Nivolumab therapy.

ESRG, LINC00518 and PWRN1 are newly-identified deregulated lncRNAs in colorectal cancer.

Colorectal cancer is the 2nd leading cause of death in humans because of cancer. This rank of death could be due to the high rate of incidence from one hand, and the lack of sufficient diagnostic and therapeutic approaches from the other hand. Thus, molecular tools have been emerging as the potential biomarker to improve the early diagnosis and therapeutic management that subsequently could lead to the heightened survival rate of colorectal cancer patients. Long non-coding RNA (lncRNAs) have shown promising capabilities to be used in clinics. The profiling methods could identify novel aberrantly expressed lncRNAs in colorectal cancer. We, thus, performed a comprehensive and unbiased approach to shortlist the dysregulated lncRNAs based on the colon adenocarcinoma TCGA data. An unbiased in silico method was used to rank the yet to profiled lncRNAs in colorectal cancer. qPCR was used to measure the expression level of selected lncRNAs. Our results nominated ESRG, LINC00518, PWRN1, and TTTY14 lncRNAs as the top-hit novel lncRNAs with aberrant expression in colon cancer. The qPCR method was used to profile these lncRNAs that showed the up-regulation of ESRG and LINC00518, and down-regulation of TTTY14 in thirty paired colorectal cancer specimens. The statistical analyses demonstrated that ESRG, LINC00518 and PWRN1 could distinguish the tumor from normal samples. Moreover, ESRG showed a negative correlation with the overall survival of patients. These diagnostic and prognostic results suggest that profiling ESRG, LINC00518 and PWRN1 s may have implications in clinics.

DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data.

Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. Existing feature selection methods perform inconsistently across datasets, occasionally even resulting in poorer clustering accuracy than without feature selection. Moreover, existing methods ignore information contained in gene-gene correlations. Here, we introduce DUBStepR (Determining the Underlying Basis using Stepwise Regression), a feature selection algorithm that leverages gene-gene correlations with a novel measure of inhomogeneity in feature space, termed the Density Index (DI). Despite selecting a relatively small number of genes, DUBStepR substantially outperformed existing single-cell feature selection methods across diverse clustering benchmarks. Additionally, DUBStepR was the only method to robustly deconvolve T and NK heterogeneity by identifying disease-associated common and rare cell types and subtypes in PBMCs from rheumatoid arthritis patients. DUBStepR is scalable to over a million cells, and can be straightforwardly applied to other data types such as single-cell ATAC-seq. We propose DUBStepR as a general-purpose feature selection solution for accurately clustering single-cell data.

Highly expressed TLX1NB and NPSR1-AS1 lncRNAs could serve as diagnostic tools in colorectal cancer.

Colorectal cancer is the main cause of human death due to cancer. This fact could be due to the insufficiency of early diagnosis or poor therapeutic strategies. Various molecular tools have been utilized in studies to assess their potentials as diagnostic biomarkers or determining factors in precision medicine. Among these molecules, long non-coding RNAs (lncRNA) have been emerging as accurate and potent transcripts to improve the detection of cancer. The overexpressed lncRNAs could also be deeply studied as the molecules for the targeted therapy in different malignancies, in particular colorectal cancer. Thus, we utilized an unbiased approach to select the up-regulated lncRNAs in colon adenocarcinoma via analyzing the TCGA dataset. Then, we validated the overexpression of two first-ranked lncRNAs, i.e., NPSR1-AS1 and TLX1NB, in our in-house colorectal cancer samples as compared to the paired adjacent normal tissues. The analyses revealed that these lncRNAs could significantly distinguish the tumor against the normal samples. The results may have implications in the early diagnosis and targeted therapy of colorectal cancer.

RCA2: a scalable supervised clustering algorithm that reduces batch effects in scRNA-seq data.

The transcriptomic diversity of cell types in the human body can be analysed in unprecedented detail using single cell (SC) technologies. Unsupervised clustering of SC transcriptomes, which is the default technique for defining cell types, is prone to group cells by technical, rather than biological, variation. Compared to de-novo (unsupervised) clustering, we demonstrate using multiple benchmarks that supervised clustering, which uses reference transcriptomes as a guide, is robust to batch effects and data quality artifacts. Here, we present RCA2, the first algorithm to combine reference projection (batch effect robustness) with graph-based clustering (scalability). In addition, RCA2 provides a user-friendly framework incorporating multiple commonly used downstream analysis modules. RCA2 also provides new reference panels for human and mouse and supports generation of custom panels. Furthermore, RCA2 facilitates cell type-specific QC, which is essential for accurate clustering of data from heterogeneous tissues. We demonstrate the advantages of RCA2 on SC data from human bone marrow, healthy PBMCs and PBMCs from COVID-19 patients. Scalable supervised clustering methods such as RCA2 will facilitate unified analysis of cohort-scale SC datasets.

scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data.

BACKGROUND: Clustering is a crucial step in the analysis of single-cell data. Clusters identified in an unsupervised manner are typically annotated to cell types based on differentially expressed genes. In contrast, supervised methods use a reference panel of labelled transcriptomes to guide both clustering and cell type identification. Supervised and unsupervised clustering approaches have their distinct advantages and limitations. Therefore, they can lead to different but often complementary clustering results. Hence, a consensus approach leveraging the merits of both clustering paradigms could result in a more accurate clustering and a more precise cell type annotation. RESULTS: We present SCCONSENSUS, an [Formula: see text] framework for generating a consensus clustering by (1) integrating results from both unsupervised and supervised approaches and (2) refining the consensus clusters using differentially expressed genes. The value of our approach is demonstrated on several existing single-cell RNA sequencing datasets, including data from sorted PBMC sub-populations. CONCLUSIONS: SCCONSENSUS combines the merits of unsupervised and supervised approaches to partition cells with better cluster separation and homogeneity, thereby increasing our confidence in detecting distinct cell types. SCCONSENSUS is implemented in [Formula: see text] and is freely available on GitHub at https://github.com/prabhakarlab/scConsensus .

Fluctuating expression of miR-584 in primary and high-grade gastric cancer.

BACKGROUND: Gastric cancer is the fifth most common cancer worldwide. Along with environmental factors, such as Helicobacter pylori (H. pylori) infection, genetic changes play important roles in gastric tumor formations. miR-584 is a less well-characterized microRNA (miRNA), with apparent activity in human cancers. However, miR-584 expression pattern in gastric cancer development has remained unclear. This study aims to analyze the expression of miR-584 in gastric cancer samples and investigates the associations between this miRNA and H. pylori infection and clinical characteristics. METHODS: The expression level of miR-584 was studied in primary gastric cancers versus healthy control gastric mucosa samples using the RT-qPCR method. The clinical data were analyzed statistically in terms of miR-584 expression. In silico studies were employed to study miR-584 more broadly in order to assess its expression and find new potential target genes. RESULTS: Both experimental and in silico studies showed up-regulation of miR-584 in patients with gastric cancer. This up-regulation seems to be induced by H. pylori infection since the infected samples showed increased levels of miR-584 expression. Deeper analyses revealed that miR-584 undergoes a dramatic down-regulation in late stages, invasive and lymph node-metastatic gastric tumors. Bioinformatics studies demonstrated that miR-584 has a substantial role in cancer pathways and has the potential to target STAT1 transcripts. Consistent with the inverse correlation between TCGA RNA-seq data of miR-584 and STAT1 transcripts, the qPCR analysis showed a significant negative correlation between these two RNAs in a set of clinical samples. CONCLUSION: miR-584 undergoes up-regulation in the stage of primary tumor formation; however, becomes down-regulated upon the progression of gastric cancer. These findings suggest the potential of miR-584 as a diagnostic or prognostic biomarker in gastric cancer.

Bioinformatics prediction and experimental validation of a novel microRNA: hsa-miR-B43 within human CDH4 gene with a potential metastasis-related function in breast cancer.

As a class of short noncoding RNAs, microRNAs (miRNAs) play a key role in the modulation of gene expression. Although, the regulatory roles of currently identified miRNAs in various cancer types including breast cancer have been well documented, there are many as yet undiscovered miRNAs. The aim of the current study was to bioinformatically reanalyze a list of 189 potentially new miRNAs introduced in a previously published paper (PMID: 21346806) and experimentally explore the existence and function of a candidate one: hsa-miR-B43 in breast cancer cells. The sequences of 189 potential miRNAs were re-checked in the miRbase database. Genomic location and conservation of them were assessed with the University of California Santa Cruz (UCSC) genome browser. SSC profiler, RNAfold, miRNAFold, MiPred, and FOMmiR bioinformatics tools were furthermore utilized to explore potential hairpin structures and differentiate real miRNA precursors from pseudo ones. hsa-miR-B43 was finally selected as one of the best candidates for laboratory verification. The expression and function of hsa-miR-B43 were examined by real-time polymerase chain reaction, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, and wound-healing assays. DIANA-microT, RNAhybrid and Enrichr tools were used to predict the miRNA target genes and for further enrichment analysis. We could detect the exogenous and endogenous expression of hsa-miR-B43, as a real novel miRNA, in cancer cell lines. Gene Ontology enrichment, pathway analysis and wound-healing assay results furthermore confirmed that a metastasis-related function may be assigned to hsa-miR-B43. Our results introduced hsa-miR-B43, as a novel functional miRNA, which might play a role in the metastatic process. Further studies will be necessary to completely survey the existence and function of hsa-miR-B43 in other cancer types.

Aberrant expression of PlncRNA-1 and TUG1: potential biomarkers for gastric cancer diagnosis and clinically monitoring cancer progression.

AIM: To evaluate PlncRNA-1, TUG1 and FAM83H-AS1 gene expression and their possible role as a biomarker in gastric cancer (GC) progression. PATIENTS & METHODS: Long noncoding RNA expressions and clinicopathological characteristics were assessed in 70 paired GC tissues. Furthermore, corresponding data from 318 GC patients were downloaded from The Cancer Genome Atlas database. RESULTS: Expression of PlncRNA-1 and TUG1 were significantly upregulated in GC tumoral tissues, and significantly correlated with clinicopathological characters. However, FAM83H-AS1 showed no consistently differential expression. The expression of these three long noncoding RNAs was significantly higher in The Cancer Genome Atlas tumoral tissues. CONCLUSION: In conclusion, PlncRNA-1 and TUG1 genes may play a critical role in GC progression and may serve as potential diagnostic biomarkers in GC patients.

Lower expression of miR-218 in human breast cancer is associated with lymph node metastases, higher grades, and poorer prognosis.

Breast cancer is considered as the most prevalent malignancy in women worldwide. Despite emergence of several prognosticators for better management of patients, there are still limitations for their clinical application due to the complexity of breast tumors, and therefore, new biomarkers for better prognosis of clinical outcomes would be of the great essence. MicroRNAs are highly conserved small non-coding regulatory RNAs involved in post-transcriptional regulating of gene expression during different cellular mechanisms. Accumulating studies suggest that miR-218 plays a multifunctional role in various cancer types and different stages. Here, to address prognostic significance of miR-218 in breast cancer, we investigate the expression profile of miR-218 and B-cell-specific Moloney murine leukemia virus integration site 1 ( BMI1) gene, as one of the putative targets of miR-218, in 33 paired breast tumors and their adjacent normal tissues with respect to the clinicopathological features of patients using quantitative real-time polymerase chain reaction. The correlation of both miR-218 and BMI1 gene expression with overall survival of breast cancer patients was also examined recruiting OncoLNC data portal. Finally, to better understand biological function of miR-218 in breast cancer, we performed in silico Gene Ontology and signaling pathway enrichment analysis on miR-218 targetome. According to our data, significant elevation of the expression of miR-218 and downregulation of BMI1 were observed in clinical breast cancer specimens compared with normal tissues ( p < 0.0001). The lower expression of miR-218 was associated with lymph node metastases, higher grades, and poorer prognosis (logrank p = 0.00988), whereas no significant difference in overall survival was observed between patients with higher and lower expression of BMI1 (logrank p = 0.254). These findings suggest that miR-218 expression profiling might be clinically applicable as a prognostic biomarker in breast cancer. In addition, our in silico enrichment analyses revealed that the association of miR-218 expression with breast cancer prognosis might be through its involvement in endocytosis and gap junction biological pathways.

Integrative computational in-depth analysis of dysregulated miRNA-mRNA interactions in drug-resistant pediatric acute lymphoblastic leukemia cells: an attempt to obtain new potential gene-miRNA pathways involved in response to treatment.

Acute lymphoblastic leukemia (ALL) is the major neoplasia type among children. Despite the tremendous success of current treatment strategies, drug resistance still remains a major cause of chemotherapy failure and relapse in pediatric patients. Overwhelming evidence illustrates that microRNAs (miRNAs) act as post-transcriptional regulators of drug-resistance-related genes. The current study was aimed at how dysregulated miRNA-mRNA-signaling pathway interaction networks mediate resistance to four commonly used chemotherapy agents in pediatric ALL, including asparaginase, daunorubicin, prednisolone, and vincristine. Using public expression microarray datasets, a holistic in silico approach was utilized to investigate candidate drug resistance miRNA-mRNA-signaling pathway interaction networks in pediatric ALL. Our systems biology approach nominated significant drug resistance and cross-resistance miRNAs, mRNAs, and cell signaling pathways based on anti-correlative relationship between miRNA and mRNA expression pattern. To sum up, our systemic analysis disclosed either a new potential role of miRNAs, or a possible mechanism of cellular drug resistance, in chemotherapy resistance of pediatric ALL. The current study may shed light on predicting drug response and overcoming drug resistance in childhood ALL for subsequent generations of chemotherapies.

Integrative computational mRNA-miRNA interaction analyses of the autoimmune-deregulated miRNAs and well-known Th17 differentiation regulators: An attempt to discover new potential miRNAs involved in Th17 differentiation.

Th17 cells are a lineage of CD4(+) T helper cells in immune system which differentiate from naïve CD4(+) T cells and have demonstrated to play a critical role in the pathogenesis of different autoimmune disorders. miRNAs are a novel group of non-coding RNAs which participate in post-transcriptional regulation of gene expression mostly by pairing with 3'UTR of their mRNA targets and inhibition of its translation. It has been demonstrated that miRNAs function in various cellular processes such as differentiation, proliferation, and apoptosis. By now, several signaling pathways and their downstream positive and negative regulators involve in Th17 differentiation have been discovered. Several studies have reported the aberrant miRNA expression profile in patients with autoimmune disease called autoimmune-deregulated miRNAs. Here, using integrative miRwalk database which assembles the data gathered from ten different bioinformatics databases designed to predict miRNA-target interaction, we analyzed possible targeting effect of "autoimmune-deregulated miRNAs" on prominent positive and negative regulators of Th17 differentiation. Our resulting mRNA-miRNA network simply nominated several miRNAs with strong possibility which probably may have inducing (miR-27b, miR-27a, miR-30c, miR-1, and miR-141) or inhibitory (miR-20b, miR-93, miR-20a, miR-152, miR-21, and miR-106a) role in Th17 differentiation by targeting negative or positive regulators of Th17 differentiation, respectively.

Tetra-Primer ARMS PCR Optimization for Detection of IVS-II-I (G-A) and FSC 8/9 InsG Mutations in ß-Thalassemia Major Patients in Isfahan Population.

BACKGROUND: ß-thalassemia, a monogenic autosomal recessive disorder, is prevalent in Middle East, particularly in Iran. In Iran, near to 20 mutations in the ß-globin gene are introduced as common mutations with varying incidence frequencies in each city. Therefore, detection and screening for couples at high risk can help to solve the problems of this disease. In this study, optimized genotyping of two common mutations in Isfahan Province, IVSII-I (G-A) and FSC-8/9 insG, was performed using the T-ARMS method. METHODS: In this case-control study, 10 healthy individuals and 30 patients affected by ß-thalassemia major with a mean 24.76 ± 4.5 years were selected from Omid Hospital in Isfahan Province. After designing tetra primers for two prevalent mutations IVSII-I (G-A) and FSC-8/9 insG, samples were genotyped using tetra-primers ARMS PCR technique. RESULTS: We have developed a sensitive single tube tetra-primers PCR assay to detect both IVSII-1 (G-A) and FS8-9 insG mutations. Moreover, we have distinguished homozygous and heterozygous forms of these mutations successfully. The frequency of IVSII-1 (G-A) mutation from 30 patients in Isfahan was 86.6% (33.3% heterozygote, and 53.3% mutant homozygote) and for FS8-9 insG mutation was 16.6% (13.3% heterozygote, and 3.3% mutant homozygote). CONCLUSION: Tetra-primers ARMS PCR could be a reliable, accurate and simple technique for genotyping SNP and different mutations. So far, no study was done on optimization methods for genotyping mutations in ß-thalassemia by T-ARMS. Here, we successfully adjusted and enhanced this method for recognizing two common mutations (FSC-8/9 insG and IVSII-I (G-A)) of ß-thalassemia in Isfahan population.

Investigation of sensitivity, specificity and accuracy of Tetra primer ARMS PCR method in comparison with conventional ARMS PCR, based on sequencing technique outcomes in IVS-II-I genotyping of beta thalassemia patients.

PURPOSE: Beta thalassemia is one of the most important hematic diseases all around the world and solving the problems caused by this abnormality is strongly dependent on precise detection and reliable screening of high-risk couples. The aim of our study was the investigation of sensitivity, specificity and accuracy of Tetra primer ARMS PCR method comparing with conventional ARMS PCR, based on sequencing technique outcomes for genotyping of IVS-II-I mutation in beta thalassemia patients. METHODS: Fifty seven samples including two homozygote, 49 heterozygote and 6 normal specimens were analyzed by Tetra primer ARMS PCR and conventional ARMS PCR methods. DNA was extracted by the standard method of salting out for leukocyte genomic DNA extraction of blood specimens and a high pure PCR template preparation kit was used for DNA purification of CVS samples. The results obtained by Tetra primer ARMS PCR and conventional ARMS PCR methods were compared with gold standard technique, i.e. sequencing. RESULTS: All three parameters including specificity, sensitivity and accuracy were 100% for Tetra primer ARMS PCR method, while they were 100%, 92.45% and 92.7% for conventional ARMS PCR technique respectively. Comparing with Tetra primer ARMS PCR which represented 100% agreement with sequencing method, conventional ARMS PCR technique only showed 47.1% agreement, because of 4 discordant results. CONCLUSION: Tetra primer ARMS PCR method is an almost reliable, sensitive and accurate technique and it is suggested that it can be used as a complementary method for diagnostic cases instead of conventional ARMS PCR method. This suggestion originated with perfect rate of agreement between outcomes of sequencing method, as a gold standard method of detecting the mutations, and Tetra primer ARMS PCR technique comparing with conventional ARMS PCR method.

miR-326 and miR-26a, two potential markers for diagnosis of relapse and remission phases in patient with relapsing-remitting multiple sclerosis.

BACKGROUND: Multiple sclerosis is an inflammatory autoimmune disease widely characterized by myelin destruction of CNS. Th-17 cells, have been demonstrated to play a crucial role in pathogenesis of MS. MicroRNAs are a new class of non-coding RNAs that participate in post-transcriptional regulation of gene expression. Previous studies have reported a potential role of various miRNAs in induction of Th-17 differentiation and progress of autoimmune diseases. In recent years, it has been shown that miR-326 and miR-26a involved in progress of Th-17 and MS disease. OBJECTIVE: To evaluate expression pattern of miR-326 and miR-26a in peripheral blood lymphocytes of relapsing-remitting MS patients during relapsing and remitting phases compared to healthy control subjects. MATERIALS AND METHODS: Forty RR-MS patients of Isfahan population were diagnosed as relapsing (n=20) or remitting phase (n=20) patients according to clinical manifests and expression level of miR-26a and miR-326 was measured in these groups by quantitative real time PCR method compared to 20 healthy controls. In-silico molecular signaling pathway enrichment analysis was also performed on validated and predicted targets (targetome) of miR-26a by DAVID database to explore possible role of miR-26a in Th17 differentiation. RESULTS: We observed up-regulation of both miR-326 and miR-26a in relapsing phase of multiple sclerosis patients compared with remitting phase (p value=0.0001) and healthy controls (p value=0.0091). ROC curve analysis confirmed valuable and precise potential of miR-326 to discriminate between relapsing and remitting phases of multiple sclerosis with specificity and sensitivity of 100% at a proposed optimum cutoff point. Furthermore, in-silico molecular signaling pathway enrichment analysis detected TGF-ß signaling pathway as one of the most statistically relevant pathway with miR-26a targetome. CONCLUSION: Our results confirmed potential of miR-326 as a diagnostic biomarker to discriminate between relapsing and remitting phases of multiple sclerosis disease. Similar expression pattern to miR-326 and in-silico molecular enrichment analysis altogether suggest an inducing role of miR-26a in differentiation of pathogenic Th17 cells during pathogenesis of multiple sclerosis by targeting major components of the TGF-ß signaling pathway (i.e. SMAD4 and SMAD1) and disarrangement of this signaling pathway.