Potential Biomarker For Breast Cancer Research Articles

Integrated Analysis of Circular RNA-Associated ceRNA Network Reveals Potential circRNA Biomarkers in Human Breast Cancer.

Circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. Yet, the roles of cancer-specific circRNAs in the circRNA-related ceRNA network of breast cancer (BRCA) remain unclear. The aim of this study was to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer. We downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Gene ontology and pathway enrichment analyses were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. A total of 72 DEcircRNAs, 158 DEmiRNAs, and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA–miRNA pairs and 140 miRNA–mRNA pairs, including 40 circRNAs, 30 miRNAs, and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in the PI3K-Akt signaling pathway, microRNAs in cancer, and proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA–mRNA interaction pairs had a significant negative correlation. A PPI network was established, and 21 hub genes were determined from the network. This study provides an effective bioinformatics basis for further understanding of the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.

Single-Nucleotide Polymorphisms Promote Dysregulation Activation by Essential Gene Mediated Bio-Molecular Interaction in Breast Cancer.

BackgroundBreast cancer (BRCA) is a malignant tumor with a high mortality rate and poor prognosis in patients. However, understanding the molecular mechanism of breast cancer is still a challenge.Materials and MethodsIn this study, we constructed co-expression networks by weighted gene co-expression network analysis (WGCNA). Gene-expression profiles and clinical data were integrated to detect breast cancer survival modules and the leading genes related to prognostic risk. Finally, we introduced machine learning algorithms to build a predictive model aiming to discover potential key biomarkers.ResultsA total of 42 prognostic modules for breast cancer were identified. The nomogram analysis showed that 42 modules had good risk assessment performance. Compared to clinical characteristics, the risk values carried by genes in these modules could be used to classify the high-risk and low-risk groups of patients. Further, we found that 16 genes with significant differential expressions and obvious bridging effects might be considered biological markers related to breast cancer. Single-nucleotide polymorphisms on the CYP24A1 transcript induced RNA structural heterogeneity, which affects the molecular regulation of BRCA. In addition, we found for the first time that ABHD11-AS1 was significantly highly expressed in breast cancer.ConclusionWe integrated clinical prognosis information, RNA sequencing data, and drug targets to construct a breast cancer–related risk module. Through bridging effect measurement and machine learning modeling, we evaluated the risk values of the genes in the modules and identified potential biomarkers for breast cancer. The protocol provides new insight into deciphering the molecular mechanism and theoretical basis of BRCA.

Cytochrome b561 Serves as a Potential Prognostic Biomarker and Target for Breast Cancer.

PurposeCytochrome b561 (CYB561) is a transmembrane protein and participates in ascorbate recycling and iron homeostasis. However, its role in breast cancer remains unclear.Patients and MethodsIn this study, we explored the expression pattern and prognostic value of CYB561 in breast cancer through The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), PrognoScan and Kaplan–Meier Plotter and confirmed its mRNA expression in human breast cell lines. LinkedOmics, Metascape and Gene Expression Profiling Interactive Analysis (GEPIA2) databases were applied to investigate the co-expression genes and construct microRNA (miRNA) networks associated with CYB561. The correlations between CYB561 and immune infiltration cells and genes were also illustrated.ResultsThe CYB561 expression was upregulated in breast cancer tissues and cell lines and significantly correlated with the clinical features of breast cancer patients. High CYB561 expression was associated with poor survival and was an independent risk factor for overall and disease-specific survival. Functional enrichment analysis showed that CYB561 and its co-expressed genes were mainly enriched in lipid biosynthetic process, Wnt signaling pathway, Hippo signaling pathway, etc. The miRNA network analysis suggested that hsa-miR-497 was negatively correlated with CYB561 expression and was predicted to direct target CYB561. CYB561 expression was positively correlated with infiltrating levels of CD4+ T cells, neutrophils and dendritic cells in breast cancer. Subsequent analysis found that B cells could predict the outcome of breast cancer. Also, CYB561 showed strong correlations with diverse immune marker sets in breast cancer.ConclusionCYB561 may serve as a potential prognostic biomarker and target for breast cancer. Our findings laid foundation for future research on molecular mechanisms of CYB561 in breast cancer.

Effects of Aerobic Exercise Training on MyomiRs Expression in Cachectic and Non-Cachectic Cancer Mice.

Simple SummaryMuscle wasting is a symptom of the cancer cachexia closely related to the imbalance between protein synthesis and degradation. MyomiRs are small RNA molecules that do not encode proteins and have the function of regulating protein-coding genes, and in this way, myomiRs can regulate the homeostasis of skeletal muscle cells submitted to physiological or pathological stimulus. Aerobic exercise training (AET) is a nonpharmacological adjuvant treatment to prevent cancer cachexia, improving the patient’s quality of life. MyomiRs are modulated by cancer and AET, as well. Thus, we propose to investigate the effects promoted by AET on circulating and skeletal muscle myomiRs in cachectic and non-cachectic cancer mice. Exercise is a promising therapy for cancer-associated muscle wasting, revealing the importance to understand the molecular mechanisms involved to preserve muscle mass.We investigated the effects of AET on myomiRs expression in the skeletal muscle and serum of colon cachectic (CT26) and breast non-cachectic (MMTV-PyMT) cancer mice models. Colon cancer decreased microRNA-486 expression, increasing PTEN in tibialis anterior muscle (TA), decreasing the PI3K/mTOR protein pathway, body and muscle wasting, fibers’ cross-sectional area and muscle dysfunction, that were not preserved by AET. In contrast, breast cancer decreased those muscle functions, but were preserved by AET. In circulation, the downregulation of microRNA-486 and -206 in colon cancer, and the downregulation of microRNA-486 and upregulation of microRNA-206 expression in breast cancer might be good cancer serum biomarkers. Since the microRNA-206 is skeletal muscle specific, their expression was increased in the TA, serum and tumor in MMTV, suggesting a communication among these three compartments. The AET prevents these effects on microRNA-206, but not on microRNA-486 in MMTV. In conclusion, cancer induced a downregulation of microRNA-486 expression in TA and serum of CT26 and MMTV mice and these effects were not prevented by AET; however, to MMTV, the trained muscle function was preserved, probably sustained by the downregulation of microRNA-206 expression. Serum microRNA-206 is a potential biomarker for colon (decreased) and breast (increased) cancer to monitor the disease evolution and the effects promoted by the AET.

The role of ferroptosis-related genes for overall survival prediction in breast cancer.

BackgroundFerroptosis is a novel iron‐dependent form of cell death, which is implicated in various diseases including cancers. However, the influence of ferroptosis‐related genes on the prognosis of breast cancer remains unclear.MethodsRNA sequencing data of 1053 breast cancer tissue samples and 111 normal tissue samples from The Cancer Genome Atlas (TCGA) were analyzed. Expression levels of 259 ferroptosis‐related genes were compared. Gene Ontology (GO) and the Kyoto Gene and Genomic Encyclopedia (KEGG) analyses were conducted on differentially expressed genes. Cox univariate analysis was conducted to explore the potential prognostic biomarkers of breast cancer. Infiltrating immune cell status was assessed.ResultsA total of 66 ferroptosis‐related genes were differentially expressed in breast cancer tissues. The enriched GO terms included Biological Process (mainly included response to oxidative stress, cellular response to chemical stress, multicellular organismal homeostasis, cofactor metabolic process, response to metal ion, response to steroid hormone, cellular response to oxidative stress, transition metal ion homeostasis, iron ion homeostasis, and cellular iron ion homeostasis), Cellular Component (mainly included apical plasma membrane, early endosome, apical part of cell, lipid droplet, basolateral plasma membrane, blood microparticle, clathrin‐coated pit, caveola, astrocyte projection, and pronucleus) and Molecular Function (mainly included iron ion binding, ubiquitin protein ligase binding, oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen, oxidoreductase activity, acting on the CH−OH group of donors, NAD or NADP as acceptor, ferric iron binding, aldo−keto reductase (NADP) activity, oxidoreductase activity, acting on single donors with incorporation of molecular oxygen, steroid dehydrogenase activity, alditol:NADP+1−oxidoreductase activity, and alcohol dehydrogenase (NADP+) activity). The enriched KEGG pathway mainly included the HIF‐1 signaling pathway, NOD‐like receptor signaling pathway, ferroptosis, IL‐17 signaling pathway, central carbon metabolism in cancer, PPAR signaling pathway, PD‐L1 expression, and PD‐1 checkpoint pathway in cancer. Among them, 38 ferroptosis‐related genes were significantly associated with the prognosis of breast cancer. The prognostic model was constructed, and breast cancer patients in low‐risk group had a better prognosis. In addition, risk score of ferroptosis prognostic model was negatively correlated with B cells (r = −0.063, p = 0.049), CD8+ T cells (r = −0.083, p = 0.010), CD4+ T cells (r = −0.097, p = 0.002), neutrophils (r = −0.068, p = 0.033), and dendritic cells (r = 0.088, p = 0.006).ConclusionsThe ferroptosis pathway plays a key role in breast cancer. Some differentially expressed ferroptosis‐related genes can be used as prognostic biomarkers for breast cancer.

Knockdown of Oligosaccharyltransferase Subunit Ribophorin 1 Induces Endoplasmic-Reticulum-Stress-Dependent Cell Apoptosis in Breast Cancer.

Ribophorin 1 (RPN1) is a major part of Oligosaccharyltransferase (OST) complex, which is vital for the N-linked glycosylation. Though it has been verified that the abnormal glycosylation is closely related to the development of breast cancer, the detail role of RPN1 in breast cancer remains unknown. In this study, we explored the public databases to investigate the relationship between the expression levels of OST subunits and the prognosis of breast cancer. Then, we focused on the function of RPN1 in breast cancer and its potential mechanisms. Our study showed that the expression of several OST subunits including RPN1, RPN2, STT3A STT3B, and DDOST were upregulated in breast cancer samples. The protein expression level of RPN1 was also upregulated in breast cancer. Higher expression of RPN1 was correlated with worse clinical features and poorer prognosis. Furthermore, knockdown of RPN1 suppressed the proliferation and invasion of breast cancer cells in vitro and induced cell apoptosis triggered by endoplasmic reticulum stress. Our results identified the oncogenic function of RPN1 in breast cancer, implying that RPN1 might be a potential biomarker and therapeutic target for breast cancer.

The Pseudokinase TRIB3 Negatively Regulates the HER2 Receptor Pathway and Is a Biomarker of Good Prognosis in Luminal Breast Cancer.

Simple SummaryBreast cancer is the most frequent type of cancer in women. More than 70% of these tumors belong to the so-called luminal subtype which has, in general, a good prognosis. However, a fraction of patients with luminal breast cancer progress to an advanced or metastatic disease, which remains a major clinical and social problem. Therefore, it is crucial to identify novel biomarkers that help to predict the progression of the disease and to develop more efficacious therapeutic approaches to fight advanced luminal breast cancer. In this work we found that the increased expression of the protein tribbles pseudokinase 3 (TRIB3) is associated with a good prognosis and a better response to therapy in luminal breast cancer patients. We also found that this effect is at least in part due to the ability of TRIB3 to inhibit the activity of the oncogene HER2.Background: Tribbles pseudokinase 3 (TRIB3) has been proposed to both promote and restrict cancer generation and progression. However, the precise mechanisms that determine this dual role of TRIB3 in cancer remain to be understood. In this study we aimed to investigate the role of TRIB3 in luminal breast cancer, the most frequent subtype of this malignancy. Methods: We genetically manipulated TRIB3 expression in a panel of luminal breast cancer cell lines and analyzed its impact on cell proliferation, and the phosphorylation, levels, or subcellular localization of TRIB3 and other protein regulators of key signaling pathways in luminal breast cancer. We also analyzed TRIB3 protein expression in samples from luminal breast cancer patients and performed bioinformatic analyses in public datasets. Results: TRIB3 enhanced the proliferation and AKT phosphorylation in luminal A (HER2-) but decreased them in luminal B (HER2+) breast cancer cell lines. TRIB3 negatively regulated the stability of HER2 in luminal B breast cancer cell lines. TRIB3 expression was associated with increased disease-free survival and a better response to therapy in luminal breast cancer patients. Conclusions: Our findings support the exploration of TRIB3 as a potential biomarker and therapeutic target in luminal breast cancer.

Bioinformatics analysis revealing prognostic significance of TIMP2 gene in breast cancer.

Tissue inhibitor of metalloproteinases 2 (TIMP2) is a member of the TIMP gene family. Accumulated evidence indicates that TIMP2 plays a significant role in various tumor processes including cell growth, apoptosis, invasion, and metastasis. However, the expression patterns and exact roles of TIMP2 had not been elucidated in breast cancer. In our research, we evaluated the expression and prognostic value of TIMP2 in breast cancer through analyzing various databases including Oncomine, bc-GenExMiner, PrognoScan, UCSC Xena, Kaplan–Meier Plotter, and PPI network. The results showed that TIMP2 was down-regulated in various breast cancer subtypes. Additionally, TIMP2 was significantly associated with age, estrogen receptor status, basal-like group, triple-negative breast cancer, PAM50 subtypes, and RSSPC subtypes. Also, the expression of TIMP2 was related to overall survival with different clinical characteristics. We analyzed the co-expressed genes with TIMP2 and interaction information with other proteins. These results disclosed that TIMP2 might serve as a potential target and prognostic biomarker in breast cancer. However, additional research is required to demonstrate our findings and motivate the clinical importance of TIMP2 in breast cancer.

Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis

Breast cancer is the most common cancer and the leading cause of cancer-related deaths in women. Increasing molecular targets have been discovered for breast cancer prognosis and therapy. However, there is still an urgent need to identify new biomarkers. Therefore, we evaluated biomarkers that may aid the diagnosis and treatment of breast cancer. We searched three mRNA microarray datasets (GSE134359, GSE31448 and GSE42568) and identified differentially expressed genes (DEGs) by comparing tumor and non-tumor tissues using GEO2R. Functional and pathway enrichment analyses of the DEGs were performed using the DAVID database. The protein–protein interaction (PPI) network was plotted with STRING and visualized using Cytoscape. Module analysis of the PPI network was done using MCODE. The associations between the identified genes and overall survival (OS) were analyzed using an online Kaplan–Meier tool. The redundancy analysis was conducted by DepMap. Finally, we verified the screened HUB gene at the protein level. A total of 268 DEGs were identified, which were mostly enriched in cell division, cell proliferation, and signal transduction. The PPI network comprised 236 nodes and 2132 edges. Two significant modules were identified in the PPI network. Elevated expression of the genes Discs large-associated protein 5 (DLGAP5), aurora kinase A (AURKA), ubiquitin-conjugating enzyme E2 C (UBE2C), ribonucleotide reductase regulatory subunit M2(RRM2), kinesin family member 23(KIF23), kinesin family member 11(KIF11), non-structural maintenance of chromosome condensin 1 complex subunit G (NCAPG), ZW10 interactor (ZWINT), and denticleless E3 ubiquitin protein ligase homolog(DTL) are associated with poor OS of breast cancer patients. The enriched functions and pathways included cell cycle, oocyte meiosis and the p53 signaling pathway. The DEGs in breast cancer have the potential to become useful targets for the diagnosis and treatment of breast cancer.

Identification and Validation of m6A-Related lncRNA Signature as Potential Predictive Biomarkers in Breast Cancer.

The metastasis and poor prognosis are still regarded as the main challenge in the clinical treatment of breast cancer (BC). Both N6-methyladenosine (m6A) modification and lncRNAs play vital roles in the carcinogenesis and evolvement of BC. Considering the unknown association of m6A and lncRNAs in BC, this study therefore aims to discern m6A-related lncRNAs and explore their prognostic value in BC patients. Firstly, a total of 6 m6A-related lncRNAs were screened from TCGA database and accordingly constructed a prognostic-predicting model. The BC patients were then divided into high-risk and low-risk groups dependent on the median cutoff of risk score based on this model. Then, the predictive value of this model was validated by the analyses of cox regression, Kaplan-Meier curve, ROC curve, and the biological differences in the two groups were validated by PCA, KEGG, GSEA, immune status as well as in vitro assay. Finally, we accordingly constructed a risk prognostic model based on the 6 identified m6A-related lncRNAs, including Z68871.1, AL122010.1, OTUD6B-AS1, AC090948.3, AL138724.1, EGOT. Interestingly, the BC patients were divided into the low-risk and high-risk groups with different prognoses according to the risk score. Notably, the risk score of the model was an excellent independent prognostic factor. In the clinical sample validation, m6A regulatory proteins were differentially expressed in patients with different risks, and the markers of tumor-associated macrophages and m6A regulators were co-localized in high-risk BC tissues. This well-validated risk assessment tool based on the repertoire of these m6A-related genes and m6A-related lncRNAs, is of highly prognosis-predicting ability, and might provide a supplemental screening method for precisely judging BC prognosis.

Differential Expression of Serum Exosomal miRNAs in Breast Cancer Patients and Healthy Controls.

Purpose: Breast cancer has become as a serious public health concern worldwide. Breast cancer cells release exosomes into the circulatory system, which are easily accessible for further analysis like cancer diagnosis. In this study, we aimed to investigate expression of circulating exosomal miRNAs (miRs) in the serum of individuals with breast cancer and healthy controls. Methods: Exosomes were collected from serum samples using a commercial kit and characterized by scanning electron microscopy (SEM) and flow cytometry analysis. Expression of miRs such as miR-21, miR-155, miR-182, miR-373, and miR-126 were evaluated by real-time PCR. Results: The result showed that the expression level of exosomal miR-21, miR-155, miR-182, and miR-373 in the serum of breast cancer patients was higher than of those controls (P<0.05). However, expression of miR-126 did not change between breast cancer and control individuals (P > 0.05). Conclusion: Our results showed a different miRs expression pattern between breast cancer and healthy samples, supposing potential biomarkers for breast cancer. Further studies focusing on these miRs are required to confirm our findings.

Extraction and isolation of histones from paraffin-embedded tissues and quantitative analysis of post-translational modifications

组蛋白翻译后修饰(HPTMs)参与基因转录调控,其异常与肿瘤等重大疾病的发生发展密切相关。石蜡包埋组织是当前疾病研究的重要样本资源,对肿瘤机制和标志物研究具有重要意义。目前基于质谱的蛋白质组学技术已成为HPTMs分析的有力工具,而针对福尔马林固定石蜡包埋(FFPE)组织样品的HPTMs分析还十分有限。该研究发展了一种基于高效液相色谱-串联质谱的FFPE组织样本HPTMs分离分析新方法。通过研究并优化组蛋白的提取策略,建立了FFPE组织样本脱蜡水化处理、蛋白质提取与聚丙烯酰胺凝胶电泳分离相结合的组蛋白提取和分离方法。通过研究FFPE切片数量、组蛋白化学衍生化方法等对组蛋白鉴定的影响,确定了组蛋白处理的具体步骤。通过HPLC分离结合非依赖性采集模式的质谱分析,鉴定了组蛋白修饰的类型、位点和丰度。最后,将优化的实验方法应用于FFPE临床样本的HPTMs分析,鉴定了2例人乳腺浸润性癌和癌旁正常组织的HPTMs图谱,均获得了100种以上的不同组蛋白修饰形式的多肽。定量分析了他们的差异性水平,通过主成分降维分析,发现浸润性癌和癌旁正常组织之间组蛋白修饰丰度存在明显的差异,且差异性具有一定的规律,特别是涉及转录调控的组蛋白修饰与乳腺癌的预后和治疗靶点具有相关性,进而探讨了乳腺癌中异常HPTMs的生物学意义。该研究对临床石蜡样本中组蛋白修饰的分离分析以及肿瘤表观遗传标志物的检测进行了有益的探索。

SERUM LONG NON-CODING RNA MALAT1 AS POTENTIAL BIOMARKER FOR BREAST CANCER IN EGYPTIAN FEMALE PATIENTS

Breast cancer (BC) is the most frequent type of tumors among females.Until a palpable or visible lump develops within the breast, there are no symptoms or indicators correlated with BC.The main issue with serum markers in BC is finding one that is both specific and sensitive for women with tiny or early lesions. Techniques based on lncRNAs are expected to have great sensitivity making them useful in therapeutic settings. As a result, MALAT-1 could be investigated as a novel biomarker in the diagnosis, prognosis, metastasis, and the prediction of treatment responses in solid tumours. Also many trace elements such as selenium has been shown to play a substantial role in a variety of biological processes.As a consequence, it is reasonable to expect that these trace elements will have an effect on carcinogenic development.Aim of the work:Evaluate the possible significance of circulating MALAT1 as potential biomarker for BC in Egyptian female patients.Assess the possible relation of serum selenium concentration and MALAT1 expression in BC patients.

Identifying GPSM Family Members as Potential Biomarkers in Breast Cancer: A Comprehensive Bioinformatics Analysis

G-protein signaling modulators (GPSMs) are a class of proteins involved in the regulation of G protein-coupled receptors, the most abundant family of cell-surface receptors that are crucial in the development of various tumors, including breast cancer. This study aims to identify the potential therapeutic and prognostic roles of GPSMs in breast cancer. Oncomine and UALCAN databases were queried to determine GPSM expression levels in breast cancer tissues compared to normal samples. Survival analysis was conducted to reveal the prognostic significance of GPSMs in individuals with breast cancer. Functional enrichment analysis was performed using cBioPortal and MetaCore platforms. Finally, the association between GPSMs and immune infiltration cells in breast cancer was identified using the TIMER server. The experimental results then showed that all GPSM family members were significantly differentially expressed in breast cancer according to Oncomine and UALCAN data. Their expression levels were also associated with advanced tumor stages, and GPSM2 was found to be related to worse distant metastasis-free survival in patients with breast cancer. Functional enrichment analysis indicated that GPSMs were largely involved in cell division and cell cycle pathways. Finally, GPSM3 expression was correlated with the infiltration of several immune cells. Members of the GPSM class were differentially expressed in breast cancer. In conclusion, expression of GPSM2 was linked with worse distant metastasis-free outcomes, and hence could potentially serve as a prognostic biomarker. Furthermore, GPSM3 has potential to be a possible target for immunotherapy for breast cancer.

Long Non-Coding RNAs as Potential Diagnostic and Prognostic Biomarkers in Breast Cancer: Progress and Prospects.

Breast cancer is the most common malignancy among women worldwide, excluding non-melanoma skin cancer. It is now well understood that breast cancer is a heterogeneous entity that exhibits distinctive histological and biological features, treatment responses and prognostic patterns. Therefore, the identification of novel ideal diagnostic and prognostic biomarkers is of utmost importance. Long non-coding RNAs (lncRNAs) are commonly defined as transcripts longer than 200 nucleotides that lack coding potential. Extensive research has shown that lncRNAs are involved in multiple human cancers, including breast cancer. LncRNAs with dysregulated expression can act as oncogenes or tumor-suppressor genes to regulate malignant transformation processes, such as proliferation, invasion, migration and drug resistance. Intriguingly, the expression profiles of lncRNAs tend to be highly cell-type-specific, tissue-specific, disease-specific or developmental stage-specific, which makes them suitable biomarkers for breast cancer diagnosis and prognosis.

Identification of CCNB2 as A Potential Non-Invasive Breast Cancer Biomarker in Peripheral Blood Mononuclear Cells Using The Systems Biology Approach.

Objective Breast cancer (BC) still remains an imperative clinical issue, despite advances in the diagnosis, prognosis and treatment modalities of this malignancy. Hence, progress has been made to identify non-invasive, high sensitive and specific biomarkers. Since immune system affects development of breast cancer, peripheral blood mononuclear cells (PBMCs) -a subpopulation of immune cells- can be considered as a promising tool in the field of BC biomarker research. In the current study, we initially attempted to use concept of the present shared biomarkers in solid tumors and systemic immune profile and then evaluate correlation of these biomarkers to clinical use in cancer research. Materials and Methods In this experimental study, available microarray gene expression datasets of BC as well as the related PBMCs were retrieved and downloaded from the Gene Expression Omnibus (GEO) database, followed by analysis using GEO2R along with affylmGUI, a R-based package, to obtain differentially expressed genes (DEGs). Signature genes from 20 types of cancer were also applied to validate DEGs. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was carried out to assess mRNA level of CCNB2 in PBMC of the BC patients and healthy subjects. ResultsDEGs analysis for the transcription profile of BC cells and PBMCs showed two shared targets, CCNB2 and PGK1. Validation with systems biology using reweighted 20 types of cancer signature genes revealed that CCNB2 is the only common target in BC and its related PBMCs, which was further validated by qRT-PCR implying a significant increase in the level of CCNB2 in the BC patients.ConclusionResults of this study demonstrated that PBMCs are affected by BC cells and CCNB2 may be of value as a diagnostic biomarker for breast cancer. However, verification would require future detailed experimental plans.

Multi-omics analysis of the expression and prognostic value of the butyrophilins in breast cancer.

Butyrophilins (BTNs) belong to the immunoglobulin superfamily of transmembrane proteins and play a role in the regulation of lymphocyte activation, several autoimmune diseases, and the progression of human cancers. However, the associated clinicopathologic characteristics and prognostic value of BTNs in breast cancer remain unknown. This study aimed to discover potential key related BTN genes and signaling pathways in breast cancer, which could provide new insights for immune-based strategies. In the present study, the mRNA expression level and prognostic value of BTN2A1, BTN3A1, BTN3A2, BTN3A3, BTNL2, BTNL9, ERMAP, and MOG were measured. Up-regulation of these genes was significantly correlated with improved overall and relapse-free survival. We then analyzed the prognostic outcomes of breast cancer subtypes, genetic alterations, interaction networks, and the functional enrichment of eight BTN family genes. Our results showed that these eight genes played essential roles in tumor progression. Furthermore, an immune infiltration analysis indicated that most candidate BTN family members were associated with intratumoral immune cell infiltration, especially that of γδ T cells. Finally, gene set enrichment analysis for a single hub gene revealed that each BTN gene played a vital role in tumor progression through immune signaling pathways. These findings provided new insights into breast cancer pathogenesis and identified eight potential biomarkers for breast cancer.

Salivary miRNA-21 expression as a potential non-invasive diagnostic biomarker in breast cancer

IntroductionBreast cancer (BC) is the most common neoplasm and the most important cause of mortality in women worldwide. microRNAs (miRNAs) are single-stranded RNA molecules with approximately 22 nucleotides in length and act as regulators of eukaryotic gene expression by targeting various mRNAs. In the present study, we evaluated the expression level of miR-21 in saliva samples of BC patients compared to controls to introduce as a novel diagnostic biomarker. Materials and methodsSalivary samples were collected from 41 patients with BC and 39 healthy individuals. The salivary expression of miR-21 was investigated using quantitative reverse-transcription polymerase chain reaction (RT-qPCR). The receiver operating characteristic (ROC) curve analysis was applied to evaluate the potential role of salivary miR-21 as a diagnostic biomarker in BC patients. Further, to predict the possible molecular mechanisms of miR-21 during BC development, in silico analysis was applied to enrich the signaling pathways in which miR-21 may be involved. ResultsIt was shown that the miR-21 expression level in the BC group's saliva samples was significantly upregulated relative to the control group. Also, 100% sensitivity and 100% specificity were shown for this potential biomarker, according to which the area under the curve is equal to one, which indicates the high diagnostic value of this biomarker. Finally, MAPK signaling pathway was suggested as a potential pathway involved in BC development. DiscussionAccording to the results, the expression level of miR-21 in BC patients' saliva samples could be considered a novel diagnostic biomarker in BC patients.

Androgen receptor expression and prognosis in Hispanic/Latino women with triple negative breast cancer

Introduction and objectiveTriple-negative breast cancer (TNBC) is an aggressive subtype that has no available molecular targets. It occurs most often in premenopausal African-American and Hispanic/Latino women. In Colombia, its prevalence has been reported to be 20.6%. Androgen receptor (AR) belongs to the steroid nuclear receptor family and has been recently considered a potential biomarker for breast cancer. Considering the high prevalence of TNBC in Colombian women and the lack of knowledge of AR expression, our aim was to determine the frequency of AR expression and its association with pathological variables. Materials and methods149 women diagnosed with TNBC between 2011 and 2014 were included. Clinical and pathological data were obtained from medical and pathology reports. Information on hormone receptor status, Ki67 expression and HER2 was reevaluated by a pathologist. AR expression was considered positive when it exceeded 1% of nuclear staining in tumor cells. ResultsAR expression was detected in 41.6% of the samples. Although we did not find statistically significant differences in clinic-pathological variables according to AR expression, patients with AR expression over 50% were younger (53.92 years vs. 60.78 years, p=0.027) and presented higher Ki67 expression (64.06% vs. 47.32%, p=0.05), compared to patients with a low AR expression. The median overall survival in our sample of TNBC patients was 2.45 years. ConclusionsThe expression of AR in our sample was similar to the expression in populations of European descent. We found statistically significant differences in age at diagnosis and Ki67 expression according to AR expression.

An integrative approach based on GC-qMS and NMR metabolomics data as a comprehensive strategy to search potential breast cancer biomarkers.

Globally, breast cancer (BC) is leading at the top of women's diseases and, as a multifactorial disease, there is the need for the development of new approaches to aid clinicians on monitoring BC treatments. In this sense, metabolomic studies have become an essential tool allowing the establishment of interdependency among metabolites in biological samples. The combination of nuclear magnetic resonance (NMR) and gas chromatography-quadrupole mass spectrometry (GC-qMS) based metabolomic analyses of urine and breast tissue samples from BC patients and cancer-free individuals was used. Multivariate statistical tools were used in order to obtain a panel of metabolites that could discriminate malignant from healthy status assisting in the diagnostic field. Urine samples (n = 30), cancer tissues (n = 30) were collected from BC patients, cancer-free tissues were resected outside the tumor margin from the same donors (n = 30) while cancer-free urine samples (n = 40) where obtained from healthy subjects and analysed by NMR and GC-qMS methodologies. The orthogonal partial least square discriminant analysis model showed a clear separation between BC patients and cancer-free subjects for both classes of samples. Specifically, for urine samples, the goodness of fit (R2Y) and predictive ability (Q2) was 0.946 and 0.910, respectively, whereas for tissue was 0.888 and 0.813, revealing a good predictable accuracy. The discrimination efficiency and accuracy of tissue and urine metabolites was ascertained by receiver operating characteristic curve analysis that allowed the identification of metabolites with high sensitivity and specificity. The metabolomic pathway analysis identified several dysregulated pathways in BC, including those related with lactate, valine, aspartate and glutamine metabolism. Additionally, correlations between urine and tissue metabolites were investigated and five metabolites (e.g. acetone, 3-hexanone, 4-heptanone, 2-methyl-5-(methylthio)-furan and acetate) were found to be significant using a dual platform approach. Overall, this study suggests that an improved metabolic profile combining NMR and GC-qMS may be useful to achieve more insights regarding the mechanisms underlying cancer.