Investigation of common genetic risk factors between thyroid traits and breast cancer.

Breast cancer (BC) risk is suspected to be linked to thyroid disorders, however observational studies exploring the association between BC and thyroid disorders gave conflicting results. We proposed an alternative approach by investigating the shared genetic risk factors between BC and several thyroid traits. We report a positive genetic correlation between BC and thyroxine (FT4) levels (corr = 0.13, p-value = 2.0 × 10-4) and a negative genetic correlation between BC and thyroid-stimulating hormone (TSH) levels (corr = -0.09, p-value = 0.03). These associations are more striking when restricting the analysis to estrogen receptor-positive BC. Moreover, the polygenic risk scores (PRS) for FT4 and hyperthyroidism are positively associated to BC risk (OR = 1.07, 95%CI: 1.00-1.13, p-value = 2.8 × 10-2 and OR = 1.04, 95%CI: 1.00-1.08, p-value = 3.8 × 10-2, respectively), while the PRS for TSH is inversely associated to BC risk (OR = 0.93, 95%CI: 0.89-0.97, p-value = 2.0 × 10-3). Using the PLACO method, we detected 49 loci associated to both BC and thyroid traits (p-value < 5 × 10-8), in the vicinity of 130 genes. An additional colocalization and gene-set enrichment analyses showed a convincing causal role for a known pleiotropic locus at 2q35 and revealed an additional one at 8q22.1 associated to both BC and thyroid cancer. We also found two new pleiotropic loci at 14q32.33 and 17q21.31 that were associated to both TSH levels and BC risk. Enrichment analyses and evidence of regulatory signals also highlighted brain tissues and immune system as candidates for obtaining associations between BC and TSH levels. Overall, our study sheds light on the complex interplay between BC and thyroid traits and provides evidence of shared genetic risk between those conditions.

Screening of candidate genes associated with high titer production of oncolytic measles virus based on systems biology approach.

The number of viral particles required for oncolytic activity of measles virus (MV) can be more than a million times greater than the reported amount for vaccination. The aim of the current study is to find potential genes and signaling pathways that may be involved in the high-titer production of MV. In this study, a systems biology approach was considered including collection of gene expression profiles from the Gene Expression Omnibus (GEO) database, obtaining differentially expressed genes (DEGs), performing gene ontology, functional enrichment analyses, and topological analyses on the protein-protein interaction (PPI) network. Then, to validate the in-silico data, total RNA was isolated from five cell lines, and full-length cDNA from template RNA was synthesized. Subsequently, quantitative reverse transcription-PCR (RT-qPCR) was employed. We identified five hub genes, including RAC1, HSP90AA1, DNM1, LTBP1, and FSTL1 associated with the enhancement in MV titer. Pathway analysis indicated enrichment in PI3K-Akt signaling pathway, axon guidance, proteoglycans in cancer, regulation of actin cytoskeleton, focal adhesion, and calcium signaling pathways. Upon verification by RT-qPCR, the relative expression of candidate genes was generally consistent with our bioinformatics analysis. Hub genes and signaling pathways may be involved in understanding the pathological mechanisms by which measles virus manipulates host factors in order to facilitate its replication. RAC1, HSP90AA1, DNM1, LTBP1, and FSTL1 genes, in combination with genetic engineering techniques, will allow the direct design of high-throughput cell lines to answer the required amounts for the oncolytic activity of MV.

MGL_3741 gene contributes to pathogenicity of Malassezia globosa in pityriasis versicolor.

Dihydroxyacid dehydratase (DHAD) is a key enzyme in biosynthetic pathway of isoleucine and valine. This pathway is absent in human but exists in various organisms such as fungi. Using RNA-seq analysis in this study, we identified MGL_3741gene which encodes DHAD protein in Malassezia globosa (M. globosa). Furthermore, we found that mentioned gene is homologous to the Ustilago maydis, Saccharomyces cerevisiae, Aspergillus flavus, and Aspergillus fumigatus ILV3P. For understanding the probable role of this gene in pathogenicity of M. globosa, we applied Real-time PCR to investigate the differentially expressed of the MGL_3741 gene in healthy and pathogenic states. Our results indicate a significant difference between two mentioned stats. These results revealed that ILV3-like gene in M. globosa can be related to the pathogenicity of this yeast.

Metabolic cancer biology: structural-based analysis of cancer as a metabolic disease, new sights and opportunities for disease treatment.

The cancer cell metabolism or the Warburg effect discovery goes back to 1924 when, for the first time Otto Warburg observed, in contrast to the normal cells, cancer cells have different metabolism. With the initiation of high throughput technologies and computational systems biology, cancer cell metabolism renaissances and many attempts were performed to revise the Warburg effect. The development of experimental and analytical tools which generate high-throughput biological data including lots of information could lead to application of computational models in biological discovery and clinical medicine especially for cancer. Due to the recent availability of tissue-specific reconstructed models, new opportunities in studying metabolic alteration in various kinds of cancers open up. Structural approaches at genome-scale levels seem to be suitable for developing diagnostic and prognostic molecular signatures, as well as in identifying new drug targets. In this review, we have considered these recent advances in structural-based analysis of cancer as a metabolic disease view. Two different structural approaches have been described here: topological and constraint-based methods. The ultimate goal of this type of systems analysis is not only the discovery of novel drug targets but also the development of new systems-based therapy strategies.

Alterations in cancer cell metabolism: the Warburg effect and metabolic adaptation.

The Warburg effect means higher glucose uptake of cancer cells compared to normal tissues, whereas a smaller fraction of this glucose is employed for oxidative phosphorylation. With the advent of high throughput technologies and computational systems biology, cancer cell metabolism has been reinvestigated over the last decades toward identifying various events underlying "how" and "why" a cancer cell employs aerobic glycolysis. Significant progress has been shaped to revise the Warburg effect. In this study, we have integrated the gene expression of 13 different cancer cells with the genome-scale metabolic network of human (Recon1) based on the E-Flux method, and analyzed them based on constraint-based modeling. Results show that regardless of significant up- and down-regulated metabolic genes, the distribution of metabolic changes is similar in different cancer types. These findings support the theory that the Warburg effect is a consequence of metabolic adaptation in cancer cells.

Targeted expression of a designed fusion protein containing BMP2 into the lumen of exosomes.

BACKGROUND: Exosomes are 30-150 nm membrane vesicles, originating from the endocytic pathway. By acting as natural carriers of biomolecules, they can transfer various materials to recipient cells. Therefore, discovering novel strategies for cargo packaging into exosomes is crucial. METHODS: The fusion constructs, consisting of protein of interest (BMP2) along with the targeting motif, linkers, tracking proteins, and enzyme cleavage sites, were computationally designed. Following the homology modeling, the best structure was selected and subjected to molecular dynamics (MD) simulation and docking analyses. The fusion protein gene was expressed in the HEK-293LTV cell line. The high-efficiency transfected and transduced cells were screened and their exosomes were isolated. Finally, cell and exosome lysates were evaluated for expression of the fusion protein. RESULTS: A total of 12 constructs with lengths ranging from 483 to 496 were designed. The top three templates, 1REW, 2H5Q, and 2MOF were screened. MD simulation and docking analyses of the structures revealed their stability and functionality. In the protein expression analyses, three bands at sizes of approximately 60, 25, and 12.5 kDa were observed, consistent with the sizes of the complete fusion protein, dimeric, and monomeric BMP2 protein. The presence of a 12.5 kDa band at exosome lysate analysis might suggest that it was loaded and cleaved inside exosomes. CONCLUSION: In summary, these findings revealed that the proposed idea for cargo sorting within the exosome lumen through incorporating an appropriate cleavage site was effective, thus providing further insight into the potential of exosomes as nano-shuttles bearing therapeutic biomolecules.

Competitive Effect of Overexpressed C-terminal of Snail-1 (CSnail) in Control of the Growth and Metastasis of Melanoma Cells.

BACKGROUND: Epithelial-to-mesenchymal transition (EMT) plays a role in the invasion and metastasis of cancer cells. During this phenomenon, Snail can promote tumor progression by upregulating mesenchymal factors and downregulating the expression of pro-apoptotic proteins. OBJECTIVE: Therefore, interventions on the expression rate of Snails may show beneficial therapeutic applications. METHODS: In this study, the C-terminal region of Snail1, capable of binding to E-box genomic sequences, was subcloned into the pAAV-IRES-EGFP backbone to make complete AAV-CSnail viral particles. B16F10 as a metastatic melanoma cell line, with a null expression of wild type TP53 was transduced by AAV-CSnail. Moreover, the transduced cells were analyzed for in vitro expression of apoptosis, migration, and EMT-related genes, and in vivo inhibition of metastasis. RESULTS: In more than 80% of the AAV-CSnail transduced cells, the CSnail gene expression competitively reduced the wild-type Snail functionality and consequently lowered the mRNA expression level of EMT-related genes. Furthermore, the transcription level of cell cycle inhibitory factor p21 and pro-apoptotic factors were promoted. The scratch test showed a decrease in the migration ability of AAV-CSnail transduced group compared to control. Finally, metastasis of cancer cells to lung tissue in the AAV-CSnail-treated B16F10 melanoma mouse model was significantly reduced, pointing out to prevention of EMT by the competitive inhibitory effect of CSnail on Snail1 and increased apoptosis of B16F10 cells. CONCLUSION: The capability of this successful competition in reducing the growth, invasion, and metastasis of melanoma cells indicates that gene therapy is a promising strategy for the control of the growth and metastasis of cancer cells.

Identification of Hub Genes Associated with Resistance to Prednisolone in Acute Lymphoblastic Leukemia Based on Weighted Gene Co-expression Network Analysis.

Resistance against glucocorticoids which are used to reduce inflammation and treatment of a number of diseases, including leukemia, is known as the first stage of treatment failure in acute lymphoblastic leukemia. Since these drugs are the essential components of chemotherapy regimens for ALL and play an important role in stop of cell growth and induction of apoptosis, it is important to identify genes and the molecular mechanism that may affect glucocorticoid resistance. In this study, we used the GSE66705 dataset and weighted gene co-expression network analysis (WGCNA) to identify modules that correlated more strongly with prednisolone resistance in type B lymphoblastic leukemia patients. The PPI network was built using the DEGs key modules and the STRING database. Finally, we used the overlapping data to identify hub genes. out of a total of 12 identified modules by WGCNA, the blue module was find to have the most statistically significant correlation with prednisolone resistance and Nine genes including SOD1, CD82, FLT3, GART, HPRT1, ITSN1, TIAM1, MRPS6, MYC were recognized as hub genes Whose expression changes can be associated with prednisolone resistance. Enrichment analysis based on the MsigDB repository showed that the altered expressed genes of the blue module were mainly enriched in IL2_STAT5, KRAS, MTORC1, and IL6-JAK-STAT3 pathways, and their expression changes can be related to cell proliferation and survival. The analysis performed by the WGCNA method introduced new genes. The role of some of these genes was previously reported in the resistance to chemotherapy in other diseases. This can be used as clues to detect treatment-resistant (drug-resistant) cases in the early stages of diseases.

Evaluation of hippocampal arylalkylamine N-acetyltransferase activity in amyloid-ß neurotoxicity.

Arylalkylamine N-acetyltransferase (AANAT), a rate-limiting enzyme in melatonin synthesis, is present in extra-pineal tissues such as the hippocampus. The hippocampal AANAT activity in amyloid ß (Aß) neurotoxicity has not been exactly defined. Adult male rats received bilateral intra-CA1 Aß administration. The hippocampus tissue sampling was performed 2, 12, and 24 h after Aß injection in the morning and night. The inflammation was monitored using tumor necrosis factor-alpha (TNF-α) immunohistochemistry. The AANAT enzyme activity and melatonin levels were measured using western blotting and high-performance liquid chromatography. The sampling in the morning vs night showed no significant differences in the AANAT activity. The Aß increased the area of TNF-α positive staining 24 h after injection, which indicated the induction of an inflammatory context. It was accompanied by a significant reduction in AANAT activity and hippocampal melatonin. A reverse correlation was also detected between TNF-α and AANAT activity in the 24-h group. The TNF-α positive area was significantly increased in the 24-h group as compared to the 12-h group. Data showed that inflammatory processes began 12 h after the Aß injection and augmented 24 h later. In the second experiment, the impact of Aß injection on hippocampus AANAT activity was examined in the pinealectomized (PIN×) animals. The PIN× per se did not affect the hippocampal AANAT and melatonin levels. However, there was a significant decrease in hippocampal melatonin in the PIN×+Aß group. The findings suggest the accompanying hippocampal inflammatory context and AANAT enzyme activity reduction in early stages after Aß administration. Understanding the underlying mechanism of the decreased AANAT activity may suggest new treatment strategies.

Reversing T Cell Exhaustion by Converting Membrane PD-1 to Its Soluble form in Jurkat Cells; Applying The CRISPR/Cas9 Exon Skipping Strategy.

OBJECTIVE: T-cells express two functional forms of the programmed cell death protein 1 (PD-1): membrane (mPD-1) and soluble (sPD-1). The binding of mPD-1 and its ligand (PD-L1) on tumor cells could lead activated lymphocytes toward exhaustion. Selective deletion of the transmembrane domain via alternative splicing of exon-3 in PD-1 mRNA could generate sPD-1. Overexpression of sPD-1 could disrupt the mPD-1/PD-L1 interaction in tumor-specific T cells. We investigated the effect of secreted sPD-1 from pooled engineered and non-engineered T cell supernatant on survival and proliferation of lymphocytes in the tumor microenvironment (TME). MATERIALS AND METHODS: In this experimental study, we designed two sgRNA sequences upstream and downstream of exon-3 in the PDCD1 gene. The lentiCRISPRv2 puro vector was used to clone the dual sgRNAs and produce lentiviral particles to transduce Jurkat T cells. Analysis assays were used to clarify the change in PD-1 expression pattern in the pooled (engineered and non-engineered) Jurkat cells. Co-culture conditions were established with PD-L1+ cancer cells and lymphocytes. RESULTS: CRISPR/Cas9 could delete exon-3 of the PDCD1 gene in the engineered cells based on the tracking of indels by decomposition (TIDE) and interference of CRISPR edit (ICE) sequencing analysis reports. Our results showed a 12% reduction in mPD-1 positive cell population after CRISPR manipulation and increment in sPD-1 concentration in the supernatant. The increased sPD-1 confirmed its positive effect on proliferation of lymphocytes co-cultured with PDL1+ cancer cells. The survival percent of lymphocytes co-cultured with the pooled cells supernatant was 12.5% more than the control. CONCLUSION: The CRISPR/Cas9 exon skipping approach could be used in adoptive cell immunotherapies to change PD-1 expression patterns and overcome exhaustion.

Design of a dual-function agent by fusing a designed anti-VEGF-A binder and CPG-2 enzyme.

Anti-VEGF therapies are common for the treatment of cancer. Carboxypeptidase G (CPG-2) enzyme is a zinc-dependent metalloenzyme that metabolizes non-toxic synthetic 'benzoic mustard prodrugs' to cytotoxic moieties in tumor cells. In this study, we designed a dual-activity agent by combining a designed anti-VEGF- and CPG-2 enzyme to convert methotrexate (MTX). VEGF-A was docked against a set of scaffolds, and suitable inverse rotamers were made. Rosetta design was used for the interface design. The top 1200 binders were chosen by flow cytometry and displayed in yeast. The activity of CPG-2 enzyme was analyzed at different temperature conditions and in the presence of the substrate, MTX. Optimal binders were selected and protein was eluted using immobilized metal affinity chromatography and size-exclusion chromatography. Both, native PAGE and on-yeast flow cytometry confirmed the binding of the binder to VEGF-A. The activity of truncated enzymes was slightly lower than that of full-length enzymes linked to VEGF-A. The method should be generally useful as a dual-activity agent for targeting VEGF-A and combination therapy with the enzyme CPG-2 for metabolizing non-toxic prodrugs to cytotoxic moieties.Communicated by Ramaswamy H. Sarma.

The immunostimulant effects of the rice ragged stunt virus genome on the growth and metastasis of breast cancer in mouse model.

There are multiple treatment strategies that have been reported for breast cancer, while new and effective therapies against it are still necessary. Stimulating the immune system and its components against cancer cells is one of the unique treatment strategies of immunotherapy and long dsRNAs are immunostimulant in this regard. Based on bioinformatics approaches, a fragment of the Rice ragged stunt RNA virus genome was selected and synthesized according to its immunogenicity. Based on the in vitro transcription technique, dsRNA was synthesized and its binding ability to the PEI/PEI-Ac Polyethylenimine (PEI) or Acetylated polyethylenimine (PEI-Ac) was verified by the gel retardation assay. Then, the PEI-Ac was synthesized by adding acetyl groups to the PEI, and the results of the 1H NMR method indicated its successful synthesis. After cancer induction by 4 T1 cells in Balb/C mice, intraperitoneal (IP) and intratumoral (IT) treatment by the PEI/PEI-Ac-dsRNA were performed and the tumor growth inhibition was evaluated. Results demonstrated that PEI/PEI-Ac-dsRNA can lead to a decrease in tumor weight and volume in both the IP and IT routes. Also, by using macro-metastatic nodule counting and hematoxylin and eosin (H&E) staining we showed that PEI/PEI-Ac-dsRNA can prevent micro and macro-metastasis in the lung. Therefore, the PEI/PEI-Ac-dsRNA acts as an effective inhibitor of growth and metastasis of the breast cancer models. We showed that viral dsRNA can exert its antitumor properties by stimulating TNF-α and IFN-γ. In general, our results revealed that dsRNA derived from the plant virus genome stimulates the intrinsic immune system and can be a potential immune stimulant drug for cancer treatment.

GCPBayes pipeline: a tool for exploring pleiotropy at the gene level.

Cross-phenotype association using gene-set analysis can help to detect pleiotropic genes and inform about common mechanisms between diseases. Although there are an increasing number of statistical methods for exploring pleiotropy, there is a lack of proper pipelines to apply gene-set analysis in this context and using genome-scale data in a reasonable running time. We designed a user-friendly pipeline to perform cross-phenotype gene-set analysis between two traits using GCPBayes, a method developed by our team. All analyses could be performed automatically by calling for different scripts in a simple way (using a Shiny app, Bash or R script). A Shiny application was also developed to create different plots to visualize outputs from GCPBayes. Finally, a comprehensive and step-by-step tutorial on how to use the pipeline is provided in our group's GitHub page. We illustrated the application on publicly available GWAS (genome-wide association studies) summary statistics data to identify breast cancer and ovarian cancer susceptibility genes. We have shown that the GCPBayes pipeline could extract pleiotropic genes previously mentioned in the literature, while it also provided new pleiotropic genes and regions that are worthwhile for further investigation. We have also provided some recommendations about parameter selection for decreasing computational time of GCPBayes on genome-scale data.

The Potential of Circulating miR-193b, miR-146b-3p and miR-483-3p as Noninvasive Biomarkers in Cutaneous Melanoma Patients.

Melanoma is a destructive skin disease with few therapeutic options in the developed stage and therefore there is a critical need for reliable biomarkers for early diagnosis. In this context, microRNAs could play an important role as diagnostic biomarkers. Three datasets with accession numbers GSE31568, GSE61741 and GSE20994 were downloaded from the Gene Expression Omnibus (GEO) database. MATLAB software was used to analyze differentially expressed miRNAs between cutaneous melanoma plasma samples and normal plasma samples (control). Plasma levels of miR-193b, miR-146b-3p and miR-483-3p were evaluated by the RT-PCR method. Furthermore, linear regression followed by receiver operating characteristic analyses was performed to estimate whether selected plasma miRNAs were able to distinguish between cases and controls. Finally, the data were analyzed by unpaired Mann-Whitney U test using Graph pad prism 8 computer software. Specifically, miR-193b and miR-146b-3p were downregulated in the plasma of melanoma patients compared with control groups which were decreased 5 × [Formula: see text]-fold in miR-193b and 58-fold in miR-146b-3p, while miR-483-3p was upregulated 3.5-fold. After receiver operating characteristic (ROC) curve analysis, miR-193b with the most area under the curve (AUC: 1.00, 95% confidence interval 1.00-1.00, p < 0.0001) had the best discriminatory power, and miR-146b-3p had the large area under the curve (AUC: 0.96, 95% confidence interval 0.96-1.00, p < 0.0001) and consequently the high discriminatory power. Between these three miRNAs, miR-193b and miR-146b-3p had a high capacity to distinguish between melanoma patients and control groups that are appropriate to be applied in melanoma diagnosis as an early and noninvasive method.

On the possibility of oscillating in the Ebola virus dynamics and investigating the effect of the lifetime of T lymphocytes.

Ebola virus (EBOV) targets immune cells and tries to inactivate dendritic cells and interferon molecules to continue its replication process. Since EBOV detailed mechanism has not been identified so far, it would be useful to understand the growth and spread of EBOV dynamics based on mathematical methods and simulation approaches. Computational approaches such as Cellular Automata (CA) have the advantage of simplicity over solving complicated differential equations. The spread of Ebola virus in lymph nodes is studied using a simplified Cellular Automata model with only four parameters. In addition to considering healthy and infected cells, this paper also considers T lymphocytes as well as cell movement ability during the simulation in order to investigate different scenarios in the dynamics of an EBOV system. It is shown that the value of the probability of death of T cells affects the number of infected cells significantly in the steady-state. For a special case of parameters set, the system shows oscillating dynamics. The results were in good agreement with an ordinary differential equation-based model which indicated CA method in combination with experimental discoveries could help biologists find out more about the EBOV mechanism and hopefully to control the disease.

Binder design for targeting SARS-CoV-2 spike protein: An in silico perspective.

INTRODUCTION: The COVID-19 pandemic is now affecting all people around the world and getting worse. New antiviral medications are desperately needed other than the few approved medications that have shown no promising efficacy so far. METHODS: Here we report three blocking binders for targeting SARS-CoV-2 spike protein to block the interaction between the spike protein on the SARS-CoV-2 and the angiotensin-converting enzyme 2 (ACE2) receptors, responsible for viral homing into the alveolar epithelium type II cells (AECII). RESULTS: The design process is based on the collected natural scaffolds and using Rosetta interface for designing the binders. CONCLUSION: Based on the structural analysis, three binders were selected, and the results showed that they might be promising as new therapeutic targets for blocking COVID-19.

Identification of lncRNAs associated with the progression of acute lymphoblastic leukemia using a competing endogenous RNAs network.

Acute lymphoblastic leukemia (ALL) is a malignancy of bone marrow lymphoid precursors. Despite effective treatments, the causes of its progression or recurrence are still unknown. Finding prognostic biomarkers is needed for early diagnosis and more effective treatment. This study was performed to identify long non-coding RNAs (lncRNAs) involved in ALL progression by constructing a competitive endogenous RNA (ceRNA) network. These lncRNAs may serve as potential new biomarkers in the development of ALL. The GSE67684 dataset identified changes in lncRNAs and mRNAs involved in ALL progression. Data from this study were re-analyzed, and probes related to lncRNAs were retrieved. Targetscan, miRTarBase, and miRcode databases were used to identify microRNAs (miRNAs) related to the discovered genes and lncRNAs. The ceRNA network was constructed, and the candidate lncRNAs were selected. Finally, the results were validated with reverse transcription quantitative real-time PCR (RT-qPCR). The ceRNA network outcomes demonstrated that the top lncRNAs associated with altered mRNAs in ALL are IRF1-AS1, MCM3AP-AS1, TRAF3IP2-AS1, HOTAIRM1, CRNDE, and TUG1. Investigations of the subnets linked to MCM3AP-AS1, TRAF3IP2-AS1, and IRF1-AS1 indicated that these lncRNAs were considerably related to pathways associated with inflammation, metastasis, and proliferation. Higher expression levels of IRF1-AS1, MCM3AP-AS1, TRAF3IP2-AS1, CRNDE, and TUG1 were found in ALL samples compared to controls. The expression of MCM3AP-AS1, TRAF3IP2-AS1, and IRF1-AS1 is significantly elevated during the progression of ALL, playing an oncogenic role. Due to their role in the main cancer pathways, lncRNAs could be suitable therapeutic and diagnostic targets in ALL.

A systematic review of long non-coding RNAs with a potential role in breast cancer.

The human transcriptome contains many non-coding RNAs (ncRNAs), which play important roles in gene regulation. Long noncoding RNAs (lncRNAs) are an important class of ncRNAs with lengths between 200 and 200,000 bases. Unlike mRNA, lncRNA lacks protein-coding features, specifically, open-reading frames, and start and stop codons. LncRNAs have been reported to play a role in the pathogenesis and progression of many cancers, including breast cancer (BC), acting as tumor suppressors or oncogenes. In this review, we systematically mined the literature to identify 65 BC-related lncRNAs. We then perform an integrative bioinformatics analysis to identify 14 lncRNAs with a potential regulatory role in BC. The biological function of these 14 lncRNAs, their regulatory mechanisms, and roles in the initiation and progression of BC are discussed in this review. Additionally, we elaborate on the current and future applications of lncRNAs as diagnostic and/or therapeutic biomarkers in BC.

Expression Analysis of Long Non-Coding RNAs Related With FOXM1, GATA3, FOXA1 and ESR1 in Breast Tissues.

Breast cancer is the most common neoplasm among females. Estrogen receptor (ESR) signaling has a prominent impact in the pathogenesis of breast cancer. Among the transcription factors associated with ESR signaling, FOXM1, GATA3, FOXA1 and ESR1 have been suggested as a candidate in the pathogenesis of this neoplasm. In the current project, we have designed an in silico approach to find long non-coding RNAs (lncRNAs) that regulate these transcription factors. Then, we used clinical samples to carry out validation of our in silico findings. Our systems biology method led to the identification of APTR, AC144450.1, linc00663, ZNF337.AS1, and RAMP2.AS1 lncRNAs. Subsequently, we assessed the expression of these genes in breast cancer tissues compared with the adjacent non-cancerous tissues (ANCTs). Expression of GATA3 was significantly higher in breast cancer tissues compared with ANCTs (Ratio of mean expressions (RME) = 4.99, P value = 3.12E-04). Moreover, expression levels of APTR, AC144450.1, and ZNF337.AS1 were elevated in breast cancer tissues compared with control tissues (RME = 2.27, P value = 5.40E-03; Ratio of mean expressions = 615.95, P value = 7.39E-19 and RME = 1.78, P value = 3.40E-02, respectively). On the other hand, the expression of RAMP2.AS1 was lower in breast cancer tissues than controls (RME = 0.31, P value = 1.87E-03). Expression levels of FOXA1, ESR1, and FOXM1 and linc00663 were not significantly different between the two sets of samples. Expression of GATA3 was significantly associated with stage (P value = 4.77E-02). Moreover, expressions of FOXA1 and RAMP2.AS1 were associated with the mitotic rate (P values = 2.18E-02 and 1.77E-02, respectively). Finally, expressions of FOXM1 and ZNF337.AS1 were associated with breastfeeding duration (P values = 3.88E-02 and 4.33E-02, respectively). Based on the area under receiver operating characteristics curves, AC144450.1 had the optimal diagnostic power in differentiating between cancerous and non-cancerous tissues (AUC = 0.95, Sensitivity = 0.90, Specificity = 0.96). The combination of expression levels of all genes slightly increased the diagnostic power (AUC = 0.96). While there were several significant pairwise correlations between expression levels of genes in non-tumoral tissues, the most robust correlation was identified between linc00663 and RAMP2.AS1 (r = 0.61, P value = 3.08E-8). In the breast cancer tissues, the strongest correlations were reported between FOXM1/ZNF337.AS1 and FOXM1/RAMP2.AS1 pairs (r = 0.51, P value = 4.79E-5 and r = 0.51, P value = 6.39E-5, respectively). The current investigation suggests future assessment of the functional role of APTR, AC144450.1 and ZNF337.AS1 in the development of breast neoplasms.

New Biomarkers Based on Smoking-Related Phenotypes for Smoking Cessation Outcomes of Nicotine Replacement Therapy: A Prospective Study.

INTRODUCTION: Identifying a potent biomarker for smoking cessation can play a key role in predicting prognosis and improving treatment outcomes. This study aimed to evaluate the contribution of new biomarkers based on the levels of Cotinine (Cot) and carbon monoxide (CO) to the short- and long-term quit rates of nicotine replacement therapies (Nicotine Patch [NP] and Nicotine Lozenge [NL]). METHODS: In this prospective interventional study, 124 smokers under treatment with the 5A's method were selected from an outpatient smoking cessation center in district 18 of Tehran City, Iran. The study was conducted from April 2016 to December 2018. They were divided into NP (n=56) and NL (n=61) intervention groups. The levels of Cot and CO were measured using ELISA and breath analysis at the beginning of the study. Three markers were calculated: Cot/CO, Cot to cigarette per day ratio (Cot/CPD), and CO/CPD. Binary logistic regression models and generalized estimating equations models were analyzed by SPSS software, version 21 to determine the chances of quitting smoking. RESULTS: Of the NP participants, 30.4% and 19.6% were abstinent after 2 and 6 months, respectively, while NL was found less effective with 19.7% for 2-month follow-up and 13.1% for 6-month follow-up. The 6-month success of quitting attempts was significantly different for the NP participants at the second half of Cot/CO (P=0.029). Of the NL participants, CO/CPD would be a superior predictor for smoking cessation success (P>0.05). CONCLUSION: The findings of this study suggested two markers of Cot/CO and CO/CPD in this order for the optimum treatment outcomes of NP and NL.