Biomarker For Diagnosis Of Breast Cancer Research Articles

Serum Long Non-Coding RNAs PVT1, HOTAIR, and NEAT1 as Potential Biomarkers in Egyptian Women with Breast Cancer.

Long non-coding RNAs play an important role in tumor growth, angiogenesis, and metastasis in several types of cancer. However, the clinical significance of using lncRNAs as biomarkers for breast cancer diagnosis and prognosis is still poorly investigated. In this study, we analyzed the serum expression levels of lncRNAs PVT1, HOTAIR, NEAT1, and MALAT1, and their associated proteins, PAI-1, and OPN, in breast cancer patients compared to fibroadenoma patients and healthy subjects. Using quantitative real-time PCR (qRT-PCR), we compared the serum expression levels of the four circulating lncRNAs in patients with breast cancer (n = 50), fibroadenoma (n = 25), and healthy controls (n = 25). The serum levels of PAI-1 and OPN were measured using ELISA. Receiveroperating-characteristic (ROC) analysis and multivariate logistic regression were used to evaluate the diagnostic value of the selected parameters. The serum levels of HOTAIR, PAI-1, and OPN were significantly higher in breast cancer patients compared to controls and fibroadenoma patients. The serum level of PVT1 was significantly higher in breast cancer patients than in the controls, while that of NEAT1 was significantly lower in breast cancer patients compared to controls and fibroadenoma patients. Both ROC and multivariate logistic regression analyses revealed that PAI-1 has the greatest power in discriminating breast cancer from the control, whereas HOTAIR, PAI-1, and OPN have the greatest power in discriminating breast cancer from fibroadenoma patients. In conclusion, our data suggest that the serum levels of PVT1, HOTAIR, NEAT1, PAI-1, and OPN could serve as promising diagnostic biomarkers for breast cancer.

Mitochondria-related core genes and TF-miRNA-hub mrDEGs network in breast cancer.

Background: Mitochondria-nuclear cross-talk and mitochondrial retrograde regulation are involved in the genesis and development of breast cancer (BC). Therefore, mitochondria can be regarded as a promising target for BC therapeutic strategies. The present study aimed to construct regulatory network and seek the potential biomarkers of BC diagnosis and prognosis as well as the molecular therapeutic targets from the perspective of mitochondrial dysfunction. Methods: The microarray data of mitochondria-related encoding genes in BC cell lines were downloaded from GEO including GSE128610 and GSE72319. GSE128610 was treated as test set and validation sets consisted of GSE72319 and TCGA tissue samples, intending to identify mitochondria-related differentially expressed genes (mrDEGs). We performed enrichment analysis, PPI network, hub mrDEGs and overall survival analysis and constructed transcription factor (TF)-miRNA-hub mrDEGs network. Results: A total of 23 up-regulated and 71 down-regulated mrDEGs were identified and validated in BC cell lines and tissues. Enrichment analyses indicated that mrDEGs were associated with several cancer-related biological processes. Moreover, 9 hub mrDEGs were identified and validated in BC cell lines and tissues. Finally, 5 hub coregulated mrDEGs, 21 miRNAs and 117 TFs were used to construct TF-miRNA-hub mrDEGs network. MYC associated zinc finger protein (MAZ), heparin binding growth factor (HDGF) and Sp2 transcription factor (SP2) regulated 3 hub mrDEGs. Hsa-mir-21-5p, hsa-mir-1-3p, hsa-mir-218-5p, hsa-mir-26a-5p and hsa-mir-335-5p regulated 2 hub mrDEGs. Overall survival analysis suggested that the up-regulation of fibronectin 1 (FN1), as well as the down-regulation of discoidin domain receptor tyrosine kinase 2 (DDR2) correlated with unfavorable prognosis in BC. Conclusion: TF-miRNA-hub mrDEGs had instruction significance for the exploration of BC etiology. The hub mrDEGs such as FN1 and DDR2 were likely to regulate mitochondrial function and be novel biomarkers for BC diagnosis and prognosis as well as the therapeutic targets.

Highly expressed SLCO1B3 inhibits the occurrence and development of breast cancer and can be used as a clinical indicator of prognosis

The role of organic anion transporting polypeptide 1B3 (SLCO1B3) in breast cancer is still controversial. The clinical immunohistochemical results showed that a greater proportion of patients with negative lymph nodes, AJCC stage I, and histological grade 1 (P < 0.05) was positively correlated with stronger expression of SLCO1B3, and DFS and OS were also increased significantly in these patients (P = 0.041, P = 0.001). Further subgroup analysis showed that DFS and OS were significantly enhanced with the increased expression of SLCO1B3 in the ER positive subgroup. The cellular function assay showed that the ability of cell proliferation, migration and invasion was significantly enhanced after knockdown of SLCO1B3 expression in breast cancer cell lines. In contrast, the ability of cell proliferation, migration and invasion was significantly reduced after overexpress the SLCO1B3 in breast cancer cell lines (P < 0.05). Overexpression or knockdown of SLCO1B3 had no effect on the apoptotic ability of breast cancer cells. High level of SLCO1B3 expression can inhibit the proliferation, invasion and migration of breast cancer cells, leading to better prognosis of patients. The role of SLCO1B3 in breast cancer may be related to estrogen. SLCO1B3 will become a potential biomarker for breast cancer diagnosis and prognosis assessment.

Unravelling Structure, Localization, and Genetic Crosstalk of KLF3 in Human Breast Cancer.

Breast cancer is the most prevailing disease among women. It actually develops from breast tissue and has heterogeneous and complex nature that constitutes multiple tumor quiddities. These features are associated with different histological forms, distinctive biological characteristics, and clinical patterns. The predisposition of breast cancer has been attributed to a number of genetic factors, associated with the worst outcomes. Unfortunately, their behavior with relevance to clinical significance remained poorly understood. So, there is a need to further explore the nature of the disease at the transcriptome level. The focus of this study was to explore the influence of Krüppel-like factor 3 (KLF3), tumor protein D52 (TPD52), microRNA 124 (miR-124), and protein kinase C epsilon (PKCε) expression on breast cancer. Moreover, this study was also aimed at predicting the tertiary structure of KLF3 protein. Expression of genes was analyzed through real-time PCR using the delta cycle threshold method, and statistical significance was calculated by two-way ANOVA in Graphpad Prism. For the construction of a 3D model, various bioinformatics software programs, Swiss Model and UCSF Chimera, were employed. The expression of KLF3, miR-124, and PKCε genes was decreased (fold change: 0.076443, 0.06969, and 0.011597, respectively). However, there was 2-fold increased expression of TPD52 with p value < 0.001 relative to control. Tertiary structure of KLF3 exhibited 80.72% structure conservation with its template KLF4 and was 95.06% structurally favored by a Ramachandran plot. These genes might be predictors of stage, metastasis, receptor, and treatment status and used as new biomarkers for breast cancer diagnosis. However, extensive investigations at the tissue level and in in vivo are required to further strengthen their role as a potential biomarker for prognosis of breast cancer.

The long non coding RNA H19 as a biomarker for breast cancer diagnosis in Lebanese women

Breast cancer is the most common cancer in women worldwide. Minimally invasive percutaneous image-guided biopsies are the current cornerstone in the diagnosis of breast lesions detected on mammography/ultrasonography/MRI or palpable clinically. However, apparently benign breast disease seen on benign biopsies is a limiting factor for diagnosis and a risk factor of breast cancer especially in the high-risk category patients. Hypothesizing that molecular changes often occur before morphological variations, the levels of the LncRNA H19 were measured in anonymous tissues obtained from 79 women’s image guided breast biopsies, and correlated with cancer progression and aggressiveness. Using a double-blinded approach, H19 might be attributed an interesting role of a more sensitive biomarker in core breast biopsies, independently of the radiological/clinical classification and distant from the clinical management. We established different thresholds for H19 levels in normal versus proliferative, versus malignant tissues. Additionnally, H19 could act as an intra-group risk marker categorizing the biopsies in normal versus benign, versus precancerous breast tissue, and as a prognostic factor in cancerous lesions discriminating aggressive versus nonaggressive lesions. Our study suggests that the lncRNA H19 could be a potential marker for breast cancer diagnosis, prognosis and risk management.

Recent Advances in Experimental Models of Breast Cancer Exosome Secretion, Characterization and Function.

Breast cancer (BC) is responsible for 15% of all the cancer deaths among women in the USA. The tumor microenvironment (TME) has the potential to act as a driver of breast cancer progression and metastasis. The TME is composed of stromal cells within an extracellular matrix and soluble cytokines, chemokines and extracellular vesicles and nanoparticles that actively influence cell behavior. Extracellular vesicles include exosomes, microvesicles and large oncosomes that orchestrate fundamental processes during tumor progression through direct interaction with target cells. Long before tumor cell spread to future metastatic sites, tumor-secreted exosomes enter the circulation and establish distant pre-metastatic niches, hospitable and permissive milieus for metastatic colonization. Emerging evidence suggests that breast cancer exosomes promote tumor progression and metastasis by inducing vascular leakiness, angiogenesis, invasion, immunomodulation and chemoresistance. Exosomes are found in almost all physiological fluids including plasma, urine, saliva, and breast milk, providing a valuable resource for the development of non-invasive cancer biomarkers. Here, we review work on the role of exosomes in breast cancer progression and metastasis, and describe the most recent advances in models of exosome secretion, isolation, characterization and functional analysis. We highlight the potential applications of plasma-derived exosomes as predictive biomarkers for breast cancer diagnosis, prognosis and therapy monitoring. We finally describe the therapeutic approaches of exosomes in breast cancer.

Investigation of the content differences of arachidonic acid metabolites in a mouse model of breast cancer by using LC–MS/MS

Arachidonic acid (AA) is closely associated with breast cancer. In addition to the two metabolic pathways regulated by cyclooxygenase and lipoxygenase, AA has a third metabolic pathway through which cytochrome P450 (CYP) enzymes produce hydroxyeicosatetraenoic acids (HETEs) and epoxyeicosatrienoic acids (EETs). The targeted CYP-mediated pathway of AA can not only kill cancer cells but also inhibit the interstitial microenvironment around a tumor. Therefore, it makes sense to identify potential biomarkers from the AA metabolome for the diagnosis and treatment of breast cancer. This study established a liquid chromatography-tandem mass spectrometry (LC–MS/MS) method for the analysis of AA and its main metabolites, EETs and HETEs, in MMTV-PyMT mice, a spontaneous breast cancer mouse model. The results showed that there were significant differences in the concentrations of AA, 12-HETE, 19-HETE and 8,9-EET in plasma and tumor tissues between normal and MMTV-PyMT mice. Therefore, the eicosanoids mentioned above may be used as new biomarkers for breast cancer diagnosis. This study provides a new perspective for the recognition and diagnosis of breast cancer.

Long non-coding RNA IGF2-AS represses breast cancer tumorigenesis by epigenetically regulating IGF2.

Long non-coding RNAs are a kind of endogenous ncRNAs with a length of more than 200 bp. Accumulating evidence suggests that long non-coding RNAs function as pivotal regulators in tumorigenesis and progression. However, their biological roles in breast cancer remain largely unknown. Here, we found that IGF2 antisense RNA (IGF2-AS) was significantly decreased in breast cancer tissues, cell lines, and plasma. Patients with low IGF2-AS were more likely to develop larger tumor size and later clinical stage. Overexpression of IGF2-AS evidently inhibited the proliferation and induced apoptosis of MCF-7 and T47D cells in vitro, as well as retarded tumor growth in vivo. Further investigation revealed that IGF2-AS inhibited the expression of its sense-cognate gene IGF2 in an epigenetic DNMT1-dependent manner, resulting in the inactivation of downstream oncogenic PI3K/AKT/mTOR signaling pathway. Enforced expression of IGF2 could significantly block the tumor inhibitory effect of IGF2-AS. Importantly, we found that IGF2-AS could be used as an effective biomarker for breast cancer diagnosis and prognosis. Taken together, our study indicates that IGF2-AS is a tumor suppressor in breast cancer, restoration of IGF2-AS may be a promising treatment for this fatal disease.

Assessment of circulating HISLA as a potential biomarker for breast cancer diagnosis and prognosis.

Breast cancer (BC) is the most frequently encountered and aggressive type of malignant tumor and affects the health of females across the globe. Approximately 30% of patients that are newly diagnosed have a high risk of subsequent metastasis and relapse. HIF-1α-stabilizing long noncoding RNA (HISLA) packaged in exosome has been recently identified and revealed as an important oncogenic gene in promoting BC progress. Thus, we sought to investigate whether serum circulating HISLA was involved in dynamics underlying its applicability for the diagnosis and prognosis of BC. We assessed serum HISLA expression in 40 patients with BC and 20 healthy controls to investigate its roles in BC using quantitative real-time polymerase chain reaction (qRT-PCR). We also assessed measures of correlation of clinical and pathological parameters with prognoses of BC patients. Our findings suggested that serum HISLA expression in BC patients was significantly higher than in healthy controls. Furthermore, high expression of serum HISLA was positively associated with advanced stage lymph node metastasis. Expression of HISLA was reduced in postoperative BC patients' serum samples, compared with preoperative serum samples. Pearson correlation assessments indicated significant correlation between serum HISLA expression and the tissue sample HISLA expression in BC patients. Our findings suggested that serum HISLA may serve as newfound biomarker which could help to improve diagnoses and prognoses for BC-afflicted patients.

Ectopic Expression of the Meiotic Protein SYCP2 in Breast Cancer Promotes Homologous Recombination and Endows Broad Resistance to DNA Repair-Targeted Drugs

Drugs targeting the DNA damage response (DDR) pathway are widely used in cancer therapy, but resistance to these drugs remains a major clinical challenge. Here, we show that SYCP2, a component of the meiotic synaptonemal complex, is ectopically expressed in breast cancer and associates with broad resistance to DDR-targeted drugs including Cisplatin, inhibitors for PARP, topoisomerase II and topoisomerase I. SYCP2 overexpression correlates with poor prognosis in breast cancer patients and with decreased survival in a clinical trial of antibody-conjugated topoisomerase I inhibitor. SYCP2 overexpression is sufficient to enhance homologous recombination (HR) and confer DDR-targeted drugresistance. Mechanistically, SYCP2 responds to DNA double strand breaks via its lysine/arginine residues and promotes RAD51 localization to DNA breaks by interacting with RAD51. SYCP2 promotes HR independently of BRCA1, suggesting that SYCP2 is a BRCA-independent determinant of DNA damage sensitivity. Thus, SYCP2, which enhances HR, is potentially a biomarker for breast cancer diagnosis, a predictor of DDR-targeted drug response, a prognostic marker for patient outcome, and a target in breast cancer therapy.

Upregulation of the long noncoding RNAs DSCAM-AS1 and MANCR is a potential diagnostic marker for breast carcinoma.

Breast cancer (BC) is one of the most common malignancies among women in the world. There is a global attempt to diagnose BC as early as possible. Long noncoding RNAs (lncRNAs) are emerging as novel targets and biomarkers for BC diagnosis and prognosis. Aberrant expression of lncRNAs is associated with BC development, making them a potential tumor marker for BC. To investigate this possibility, we determined the expression levels of Down syndrome cell adhesion molecule-antisense RNA-1 (DSCAM-AS1) and mitotically-associated long non-coding RNA (MANCR) lncRNAs in BC tissues. This case-control study included 50 paired tumor and adjacent nontumor tissues from female BC patients. The total RNA was isolated and the expression levels of MANCR and DSCAM-AS1 lncRNAs were assessed using quantitative real-time reverse transcription-PCR. Potential correlations between lncRNA levels and clinicopathological characteristics were also analyzed. DSCAM-AS1 and MANCR lncRNAs were significantly upregulated in BC tumor tissues compared with the adjacent nontumor tissues. We also found the significant upregulation of DSCAM-AS1 in advanced tumor-node-metastasis stage (TNM III) of BC tumor tissues. Furthermore, the expression of DSCAM-AS1 and MANCR in HER-2 positive patients was significantly higher than HER-2 negative affected individuals. Receiver operating characteristic curve analysis showed a satisfactory diagnostic efficacy (P value<0.0001), which means that DSCAM-AS1 and MANCR lncRNAs can potentially serve as a biomarker. The present study might provide further approval for the clinical diagnostic significance of DSCAM-AS1 and MANCR lncRNAs that their high expressions were associated with aggressive clinical parameters of BC.

Non-Invasive Biomarkers for Early Detection of Breast Cancer.

Simple SummaryEarly diagnosis of breast cancer greatly increases the chance of cure and survival from the disease. The mammogram is widely used for early detection of breast cancer, but its effectiveness and accuracy have been a concern for a long time as well as its inability in detecting small cancers, especially in women with dense breast tissues. Therefore, it is an unmet clinical need to develop a simple, convenient test to overcome the shortcomings of mammography. Liquid biopsy, which is based on the analysis of body fluids, has attracted much attention in the search for cancer biomarkers. Recent advances in analytical techniques have gradually made it possible to detect breast cancer early through a biomarker analysis of blood, nipple aspirate fluid, sweat, urine, tears, or the breath. We envision that a simple blood or breath test holds great promise as a biomarker for early detection of breast cancer in the near future.Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of “omics” strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.

Clinical Evaluation of the Diagnostic Role of MicroRNA-155 in Breast Cancer.

Aim Biochemical markers, including microRNAs (miRs), may facilitate the diagnosis and prognosis of breast cancer. This study was aimed at assessing serum miR-155 expression in patients with breast cancer and receptors. Methods This case-control study was conducted on 36 patients with breast cancer and 36 healthy individuals. After RNA extraction from the patient's serum, cDNA was synthesized. The expression of miR-155 was measured using RT-qPCR. Demographic and histochemical data were extracted from patient documents. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) software. Results The mean age of subjects in breast cancer and control groups was 47.64 ± 8.19 and 47.36 ± 7.52 years, respectively. The serum miR-155 expression was higher in the cancer group (1.68 ± 0.66) compared to the control group (p < 0.0001). There was a significant relationship between serum miR-155 expression and the tumor grade (p < 0.001), tumor stage (p < 0.001), and tumor size (p < 0.001) of the patients. However, no relationship between miR-155 expression and the presence of lymph node involvement (p = 0.15), HER2 (p = 0.79), Ki-67 (p = 0.9), progesterone receptor (p = 0.54), and estrogen receptors (p = 0.84) was found. The ROC curve analysis showed that the AUC was 0.89 (77.78% sensitivity and 88.89% specificity), and the cutoff was 1.4 (Youden index: 0.6667) for detecting breast cancer. Conclusion The findings of this study revealed that serum miR-155 may serve as a potential noninvasive molecular biomarker for breast cancer diagnosis and can help predict the grade of the disease.

Computational studies on bacterial secondary metabolites against breast cancer

Microbes exist in the human body provide more benefits by modulating metabolic processes, immunity, and signal transduction. However, microbial dysbiosis with harmful bacterial species can cause chronic inflammation and cancers. Hence human probiotics were recently paid more attention to immune responses, therapy, and diagnosis. Breast cancer is the second leading cancer worldwide and causes more death in women. The role of breast microbiome secondary metabolites in breast cancer is poorly studied. Research shows that breast has a specific microbiome inhabited with particular bacterial species. More significantly probiotics produced from breast microbiomes may act as a potential biomarker for breast cancer diagnosis. Hence this computational research aimed at the effect of chosen metabolites on breast cancer cell receptor G-protein-coupled bile acid receptor, Gpbar1 (TGR5). The current research suggested that cadaverine, succinate, p-cresol, and its derivatives could be used as a molecular marker in the diagnosis of breast cancer.

Identifying potential serum biomarkers of breast cancer through targeted free fatty acid profiles screening based on a GC-MS platform.

Recent advances suggest that abnormal fatty acid metabolism highly correlates with breast cancer, which provide clues to discover potential biomarkers of breast cancer. This study aims to identify serum free fatty acid (FFA) metabolic profiles and screen potential biomarkers for breast cancer diagnosis. Gas chromatography-mass spectrometry and our in-house fatty acid methyl ester standard substances library were combined to accurately identify FFA profiles in serum samples of breast cancer patients and breast adenosis patients (as controls). Potential biomarkers were screened by applying statistical analysis. A total of 18 FFAs were accurately identified in serum sample. Two groups of patients were correctly discriminated by the orthogonal partial least squares-discriminant analysis model based on FFA profiles. Seven FFA levels were significantly higher in serum from breast cancer patients than that in controls, and exhibited positive correlation with malignant degrees of disease. Furthermore, five candidates (palmitic acid, oleic acid, cis-8,11,14-eicosatrienoic acid, docosanoic acid and the ratio of oleic acid to stearic acid) were selected as potential serum biomarkers for differential diagnosis of breast cancer. Our study will help to reveal the metabolic signature of FFAs in breast cancer patients, and provides valuable information for facilitating clinical noninvasive diagnosis.

MicroRNAs as Biomarker for Breast Cancer.

Regardless of advances in detection and treatment, breast cancer affects about 1.5 million women all over the world. Since the last decade, genome-wide association studies (GWAS) have been extensively conducted for breast cancer to define the role of miRNA as a tool for diagnosis, prognosis and therapeutics. MicroRNAs are small, non-coding RNAs that are associated with the regulation of key cellular processes such as cell multiplication, differentiation, and death. They cause a disturbance in the cell physiology by interfering directly with the translation and stability of a targeted gene transcript. MicroRNAs (miRNAs) constitute a large family of non-coding RNAs, which regulate target gene expression and protein levels that affect several human diseases and are suggested as the novel markers or therapeutic targets, including breast cancer. MicroRNA (miRNA) alterations are not only associated with metastasis, tumor genesis but also used as biomarkers for breast cancer diagnosis or prognosis. These are explained in detail in the following review. This review will also provide an impetus to study the role of microRNAs in breast cancer.

Fluidity and elasticity form a concise set of viscoelastic biomarkers for breast cancer diagnosis based on Kelvin-Voigt fractional derivative modeling.

Cancer progression involves biomechanical changes within transformed cells and the surrounding extracellular matrix (ECM). The viscoelastic features of fluidity and elasticity that are based on a novel Kelvin-Voigt fractional derivative (KVFD) model were found capable of discriminating normal, benign and malignant breast biopsy tissues on the cellular scale. The improved specificity of KVFD model parameters derives from greater accuracy of fitting the entire approaching force-indentation measurement curve ([Formula: see text] > 0.99) compared with traditional elastic models ([Formula: see text] < 0.86). Moreover, model parameters can be interpreted in terms of histopathological features. First, statistical comparisons reveal there are significant differences (p < 0.001) in elasticity E0, fluidity [Formula: see text], and viscosity [Formula: see text] among healthy, benign, and malignant groups. Malignant breast tissues show low-value, broad-distributions in E0 and with high fluidity [Formula: see text] as compared with healthy and benign tissues. Second, histograms of E0 and [Formula: see text] provide distinctive features by fitting to Gaussian mixture (GM) models. The histograms of E0 and [Formula: see text] are best fit by two kernels GM for malignant tissues, indicating that the cells are soft but with high fluidity and the ECM is stiff but with low fluidity. However, the data suggest one-kernel GM model for benign tissue and a patched uniform distribution for healthy tissue. Third, using fluidity [Formula: see text] as the test statistic, the area under the receiver operator characteristiccurve (AUC) is 0.701 ± 0.012 (p < 0.0001) for control versus malignant and 0.706 ± 0.013 (p < 0.0001) for benign versus malignant group. Variations in tissue fluidity and elasticity offer a concise set of viscoelastic biomarkers that correlate well with histopathological features.

Determination of Serum Exosomal H19 as a Noninvasive Biomarker for Breast Cancer Diagnosis.

PurposeThere is an urgent need for new biomarkers for the diagnosis of breast cancer. Exosomes can communicate with cells through transport molecules, including long-chain noncoding RNA (lncRNA), which is considered as a promising noninvasive biomarker. Here, we aimed to determine the potential of long noncoding RNA (lncRNA) H19 in the circulating exosomes for the diagnosis of breast cancer (BC).Materials and MethodsWe measured the levels of lncRNA H19 in serum-derived exosomes from patients with breast cancer (BC) or benign breast disease (BBD) and healthy subjects, using quantitative real-time PCR. H19 levels were also measured for pre-operative and post-operative patients. Receiver operating characteristic curve was constructed, and the area under the curve (AUC) was calculated to determine the applicability of exosomal H19 levels as biomarkers in BC. The relationship between H19 relative expression and clinical features of BC patients was also analyzed.ResultsExosomal H19 expression levels were upregulated in patients with BC compared to that in patients with BBD and healthy controls (BC vs BBD, P < 0.001; BC vs healthy subjects, P < 0.001). The median serum exosomal H19 levels were significantly lower in post-operative than that in the pre-operative patients (P < 0.001). The AUC for exosomal H19 analysis was 0.870 (95% CI: 0.774–0.966) with a sensitivity of 87.0% and specificity of 70.6%, which was higher than the AUCs for CA15-3 and CEA, ie, 0.822 and 0.811, respectively. Moreover, exosomal H19 expression levels were associated with lymph node metastasis (P = 0.039), distant metastasis (P = 0.008), TNM stages (P = 0.022), ER (P=0.009), PR (P = 0.018), and Her-2 (P = 0.021).ConclusionOur results indicated that serum exosomal H19 acts as a novel biomarker for the diagnosis of BC.

Multimodal plasmonic optical fiber grating aptasensor.

Tilted fiber Bragg gratings (TFBGs) are now a well-established technology in the scientific literature, bringing numerous advantages, especially for biodetection. Significant sensitivity improvements are achieved by exciting plasmon waves on their metal-coated surface. Nowadays, a large part of advances in this topic relies on new strategies aimed at providing sensitivity enhancements. In this work, TFBGs are produced in both single-mode and multimode telecommunication-grade optical fibers, and their relative performances are evaluated for refractometry and biosensing purposes. TFBGs are biofunctionalized with aptamers oriented against HER2 (Human Epidermal Growth Factor Receptor-2), a relevant protein biomarker for breast cancer diagnosis. In vitro assays confirm that the sensing performances of TFBGs in multimode fiber are higher or identical to those of their counterparts in single-mode fiber, respectively, when bulk refractometry or surface biosensing is considered. These observations are confirmed by numerical simulations. TFBGs in multimode fiber bring valuable practical assets, featuring a reduced spectral bandwidth for improved multiplexing possibilities enabling the detection of several biomarkers.

Survival analysis for long noncoding RNAs identifies TP53TG1 as an antioncogenic target for the breast cancer.

Breast carcinoma is one of the most commonly diagnosed tumors and also one of the deadliest cancers in the female. Long noncoding RNAs (lncRNAs) are emerging as novel targets and biomarkers for breast cancer diagnosis and treatment. In this study, we aimed to study the lncRNAs associated with the outcomes in patients using the breast invasive carcinoma datasets from The Cancer Genome Atlas. The Cox proportional hazards regression model was fitted to each lncRNA. Hierarchy clustering was carried out using these survival-related lncRNAs and the log-rank test was carried out for the clustered groups. DNA methylation status was utilized to identify the lncRNAs regulated by epigenetics. Finally, the coexpressed messenger RNA with the potential lncRNAs were utilized to study the possible functions and mechanisms of lncRNAs. In total, 182 lncRNAs had an impact on the survival time of the patients with a cutoff <0.01. The patients were clustered into three groups using these survival-related genes, which performed significantly different prognosis. Two lncRNAs, which were significantly correlated with the outcomes of breast cancer and were regulated by methylation status, were obtained. These two lncRNAs were TP53TG1 and RP5-1061H20.4. We proposed that TP53TG1 was activated by the wild-type TP53 and performed an impact on the PI3Ks family by binding YBX2 in breast cancer.