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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

Background: β-thalassemia, a monogenic autosomal recessive disorder, is prevalent in Middle East, particularly in Iran. In Iran, near to 20 mutations in the β-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.

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.

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.