Distinguish Breast Cancer Patients Research Articles

Aberrant Expression of Cancer-Testis Antigen FBXO39 in Breast Cancer and its Clinical Significance.

Cancer/testis antigen (CTA) is a class of antigen molecules expressed only in the germinal epithelium of testis and some tumor tissues. As an important CTA molecule, the expression of F-box protein 39 (FBXO39) in breast cancer (BC) and its clinical significance remain unclear. The objective of this study is to explore the value of FBXO39 in the diagnosis, efficacy monitoring, and prognostic evaluation of BC. The expression of FBXO39 mRNA in the serum exosomes of patients with BC before and after the initial diagnosis and treatment was detected by qRT-PCR, and the corresponding ROC curve was plotted. The expression of FBXO39 protein in BC cancer tissues was detected by immunohistochemistry, along with the analysis of the correlation between FBXO39 expression and clinical pathological features as well as prognosis of BC cases. The serum-derived exosomes were successfully isolated and identified. The positive rate of FBXO39 mRNA in serum exosomes of patients with BC was up to 86%; there was a correlation between the expression level of serum exosomal FBXO39 and clinical staging, HER2, and Ki-67 expression (all with p < 0.05). The sensitivity of serum exosomal FBXO39 in distinguishing BC patients from healthy controls was 88%, with the specificity as 86%, and AUC as 0.9432. The expression change of FBXO39 in serum-sourced exosomes of patients with BC was related to their treatment situation, indicating that the level of FBXO39 decreased significantly after treatment. The expression of FBXO39 in cancer tissue was related to the clinical stage (p = 0.023) and lymphatic metastasis (p = 0.015) of the BC patients. Survival analysis showed that the expression of FBXO39 was negatively correlated with the prognosis of BC patients, with the high expression of FBXO39 indicating poor prognosis. Serum-derived exosomal FBXO39 could serve as an important indicator of BC diagnosis and efficacy evaluation; FBXO39 could be rated as an important indicator of BC prognosis evaluation.

A novel panel of differentially-expressed microRNAs in breast cancer brain metastasis may predict patient survival

Breast cancer brain metastasis (BCBM) is an area of unmet clinical need. MicroRNAs (miRNAs) have been linked to the metastatic process in breast cancer (BC). In this study, we aim to determine differentially-expressed miRNAs utilising primary BCs that did not relapse (BCNR, n = 12), primaries that relapsed (BCR) and their paired (n = 40 pairs) brain metastases (BM) using the NanoString™ nCounter™ miRNA Expression Assays. Significance analysis of microarrays identified 58 and 11 differentially-expressed miRNAs between BCNR vs BCR and BCR vs BM respectively and pathway analysis revealed enrichment for genes involved in invasion and metastasis. Four miRNAs, miR-132-3p, miR-199a-5p, miR-150-5p and miR-155-5p, were differentially-expressed within both cohorts (BCNR-BCR, BCR-BM) and receiver-operating characteristic curve analysis (p = 0.00137) and Kaplan-Meier survival method (p = 0.0029, brain metastasis-free survival; p = 0.0007, overall survival) demonstrated their potential use as prognostic markers. Ingenuity pathway enrichment linked them to the MET oncogene, and the cMET protein was overexpressed in the BCR (p < 0.0001) and BM (p = 0.0008) cases, compared to the BCNRs. The 4-miRNAs panel identified in this study could be potentially used to distinguish BC patients with an increased risk of developing BCBM and provide potential novel therapeutic targets, whereas cMET-targeting warrants further investigation in the treatment of BCBM.

Differentially expressed microRNAs in exosomes of patients with breast cancer revealed by next‑generation sequencing.

MicroRNAs (miRNAs/miRs) in exosomes play crucial roles in the onset, progression and metastasis of cancer by regulating the stability of target mRNAs or by inhibiting translation. In the present study, differentially expressed miRNAs were identified in exosomes of 27 breast cancer patients and 3 healthy controls using RNA sequencing. The differentially expressed microRNAs were selected by bioinformatic analysis. Subjects were followed up for 2 years and exosomal miRNA profiles were compared between patients with and without recurrence of breast cancer. A total of 30 complementary DNA libraries were constructed and sequenced and 1,835 miRNAs were detected. There were no significant differences in the expression of miRNAs between the basal-like, human epidermal growth factor receptor-2+, luminal A, luminal B and healthy control (HC) groups. A total of 54 differentially expressed miRNAs were identified in triple-negative breast cancer (TNBC) patients vs. HCs, including 20 upregulated and 34 downregulated miRNAs. The results of the reverse transcription-quantitative PCR were consistent with this. Receiver operating characteristic curve analyses indicated that miR-150-5p [area under the curve (AUC)=0.705, upregulated], miR-576-3p (AUC=0.691, upregulated), miR-4665-5p (AUC=0.681, upregulated) were able to distinguish breast cancer patients with recurrence from those without recurrence. In conclusion, the present results indicated differences in miRNA expression profiles between patients with TNBC and healthy controls. Certain exosomal miRNAs were indicated to have promising predictive value as biomarkers for distinguishing breast cancer with recurrence from non-recurrence, which may be utilized for preventive strategies.

Integrative transcriptome data mining for identification of core lncRNAs in breast cancer.

BackgroundCumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening.MethodsFirst, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA).ResultsSeven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer.ConclusionOur study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

A specific gene expression signature for visceral organ metastasis in breast cancer

BackgroundVisceral organ metastasis is associated with poor survival outcomes in terms of metastasis free- and overall survival in breast carcinomas. Identification of a gene expression profile in tumours that selects a subpopulation of patients that is more likely to develop visceral organ metastases will help elucidate mechanisms for the development of distant metastases and could be of clinical value. With this study we aimed to determine genomic predictors that would help to distinguish breast cancer patients with more likelihood to develop visceral metastasis.MethodsGene expression profiling data of 157 primary tumours from breast cancer patients who developed distant metastases were analyzed and differentially expressed genes between the group of tumours with visceral metastasis and the those without visceral metastases were identified. Published data were used to validate our findings. Multivariate logistic regression tests were applied to further investigate the association between the gene-expression-signature and clinical variables. Survival analyses were performed by the Kaplan-Meier method.ResultsFourteen differentially expressed genes (WDR6, CDYL, ATP6V0A4, CHAD, IDUA, MYL5, PREP, RTN4IP1, BTG2, TPRG1, ABHD14A, KIF18A, S100PBP and BEND3) were identified between the group of tumours with and without visceral metastatic disease. Five of these genes (CDYL, ATP6V0A4, PREP, RTN4IP1 and KIF18A) were up-regulated and the other genes were down-regulated. This gene expression signature was validated in the training and in the independent data set (p 2.13e− 08 and p 9.68e− 06, respectively). Multivariate analyses revealed that the 14-gene-expression-signature was associated with visceral metastatic disease (p 0.001, 95% CI 1.43–4.27), independent of other clinicopathologic features. This signature has been also found to be associated with survival status of the patients (p < .001).ConclusionWe have identified an unique gene expression signature which is specific to visceral metastasis. This 14-gene-expression-signature may play a role in identifying the subgroup of patients with potential to develop visceral metastasis.

Potential value of circulatory microRNA122 gene expression as a prognostic and metastatic prediction marker for breast cancer.

Despite progress in terms of management, breast cancer still constitutes a major threat to health worldwide. Various microRNAs have been shown to play a fundamental role in tumor biology during development and progression. Therefore, our study was focused on investigating the role of circulating microRNA122 (miR-122) in breast cancer and its clinical utility as a potential easily accessible biomarker for use in the diagnostic and prognostic assessment of breast cancer. Determination of the serum CA15-3 and carcinoembryonic antigen levels was conducted using an enzyme-linked immunosorbent assay. The expression level of miR-122 was determined using real time PCR in 90 breast cancer patients and 60 healthy controls. Higher circulating miR-122 levels were found in breast cancer patients than in controls and higher miR-122 levels were observed in patients who experienced metastasis. Additionally, miR-122, at a cutoff > 2.2, had a sensitivity of 93.33% and a specificity of 90% when used to distinguish breast cancer patients from controls and was able to predict metastasis at a cutoff > 10.9 with a sensitivity of 95.83% and a specificity of 65.15%. Kaplan-Meier survival analysis revealed that high miR-122 expression is significantly associated with decreased overall survival and progression-free survival. This study concludes that circulatory miR-122 could be utilized as a diagnostic and prognostic biomarker in breast cancer patients.

Presence of Circulating miR-145, miR-155, and miR-382 in Exosomes Isolated from Serum of Breast Cancer Patients and Healthy Donors.

miR-145, miR-155, and miR-382 have been proposed as noninvasive biomarkers to distinguish breast cancer patients from healthy individuals. However, it is unknown if these three miRNAs are secreted by exosomes. Thus, we hypothesized that miR-145, miR-155, and miR-382 in breast cancer patients are present in exosomes. We isolated exosomes from serum of breast cancer patients and healthy donors, then we characterized them according to their shape, size, and exosome markers by scanning electron microscopy, atomic force microscopy, nanoparticle tracking analysis (NTA), and Western blot and determined the exosome concentration in all samples by NTA. Later, exosomal small RNA extraction was done to determine the expression levels of miR-145, miR-155, and miR-382 by qRT-PCR. We observed a round shape of exosomes with a mean size of 119.84 nm in breast cancer patients and 115.4 nm in healthy donors. All exosomes present the proteins CD63, Alix, Tsg, CD9, and CD81 commonly used as markers. Moreover, we found a significantly high concentration of exosomes in breast cancer patients with stages I, III, and IV compared to healthy donors. We detected miR-145, miR-155, and miR-382 in the exosomes isolated from serum of breast cancer patients and healthy donors. Our results show that the exosomes isolated from the serum of breast cancer patients and healthy donors contains miR-145, miR-155, and miR-382 but not in a selective manner in breast cancer patients. Moreover, our data support the association between exosome concentration and the presence of breast cancer, opening the possibility to study how miRNAs packaged into exosomes play a role in BC progression.

Plasma Peptidome Pattern of Breast Cancer Using Magnetic Beads-Based Plasma Fractionation and MALDI-TOF MS: A Case Control Study in Egypt

Objective:The present study aimed to determine peptidome patterns in breast cancer (BC).Methods:We analyzed the plasma proteomic profiling of 80 BC patients and 50 healthy controls, using hydrophobic interaction chromatography magnetic beads (MB-HIC8) separation followed by Matrix assisted laser desorption ionization/ time of flight mass spectrometry (MALDI-TOF MS).Results:ClinProTools software identified 92 peaks that differed among the analyzed groups, 33 peaks were significantly different (P < 0.05). Of those, 22 peaks were up-regulated while 11 peaks were down-regulated in BC patients compared with the healthy controls. Three peptide ion signatures (m/z 1,570.31, 1,897.4 and 2,568.17) were provided by the Quick Classifier model to discriminate BC patients from healthy control subjects with 96.4% accuracy. External validation was performed by an independent group and this achieved a sensitivity of 100% and a specificity of 76.9%.Conclusion:MALDI-TOF MS has good analytical performance in distinguishing BC patients from healthy controls.

Aberrant Expression of miR-142-3p and its Target Gene HMGA1 and FZD7 in Breast Cancer and its Clinical Significance.

Breast cancer is the second leading cause of cancer-related death among women worldwide. The aim of this study is to investigate the role of miR-142-3p in breast cancer cells and the related mechanism. Sixty paired breast cancer tissues were collected and 60 breast tissues from patients with mammary hyperplasia served as the control group. The expression of miR-142-3p was examined using RT-qPCR methods; moreover, we also performed receiver operating characteristic (ROC) curve analysis to determine whether miR142-3p can distinguish breast cancer patients from the controls. Next, HMGA1 and FZD7 have been predicted as target genes of miR-142-3p, and the expressions of HMGA1 and FZD7 in breast cancer tissue and the control group were examined using RT-qPCR and western blot methods. miR-142-3p was significantly down-regulated in breast cancer tissue compared with the controls, and the levels of miR-142-3p was negatively correlated with the tumor size, degree of differentiation, and metastasis (p < 0.01). Moreover, results of ROC curve analysis indicated that the expression of miR-142-3p can distinguish between patients with breast cancer and the control group (AUC = 0.819, 95% CI, 0.756 - 0.881). Furthermore, the expressions of HMGA1 and FZD7 were significantly up-regulated in patients with breast cancer compared with the controls. The level of miR-142-3p was negatively correlated with expressions of HMGA1 (r = -0.3507, p = 0.006) and FZD7 (r = -0.3410, p = 0.0077) in patients with breast cancer. Our results proved that miR-142-3p may serve as a tumor suppressor in breast cancer by suppressing the expression of oncogene HMGA1 and FZD7, suggesting that miR-142-3p has the potential to become a diagnostic marker and therapeutic target for the early diagnosis and treatment of breast cancer.

Rapid and Sensitive Detection of Breast Cancer Cells in Patient Blood with Nuclease-Activated Probe Technology.

A challenge for circulating tumor cell (CTC)-based diagnostics is the development of simple and inexpensive methods that reliably detect the diverse cells that make up CTCs. CTC-derived nucleases are one category of proteins that could be exploited to meet this challenge. Advantages of nucleases as CTC biomarkers include: (1) their elevated expression in many cancer cells, including cells implicated in metastasis that have undergone epithelial-to-mesenchymal transition; and (2) their enzymatic activity, which can be exploited for signal amplification in detection methods. Here, we describe a diagnostic assay based on quenched fluorescent nucleic acid probes that detect breast cancer CTCs via their nuclease activity. This assay exhibited robust performance in distinguishing breast cancer patients from healthy controls, and it is rapid, inexpensive, and easy to implement in most clinical labs. Given its broad applicability, this technology has the potential to have a substantive impact on the diagnosis and treatment of many cancers.

Abstract 5706: Gene expression profile of peripheral blood mononuclear cells in breast cancer patients may be contribute to the identification and the immunological classification of breast cancer patients by blood test

Abstract It is reported that gene expression profile of peripheral blood mononuclear cells (PBMCs) exhibits unique gene expression signature in cancer patients including renal cell carcinoma, pancreatic cancer and lung cancer. Since pancreatic cancer diagnosis is difficult in not only early detection of the disease but also in the diagnosis itself, development of novel diagnostic tools in addition to conventional diagnostic strategy has been awaited. On the other hand, in breast cancer, because early diagnosis by mammography and ultra sound examination on breast is established successfully, exploration of gene expression profile of PBMCs may be important in terms of insight to host antitumor immune response aspects. In the current study, we performed RNA sequencing (RNA-seq) analysis on RNA of PBMCs from 3 healthy volunteers, 6 early and 7 metastatic breast cancer patients including all phenotypes defined by ER, PgR and HER2. Genes that showed FDR&amp;lt;0.05 and fold change of &amp;lt;0.5 and 2.0&amp;lt; in comparison of healthy volunteers and breast cancer patients were applied to clustering analysis by Ward method. We found significant unique gene expression signature between healthy volunteers and breast cancer patients. Furthermore, it was shown that HER2 overexpressing breast cancer patients, which breast cancer patients were divided into 3 clusters including HER2 type and other 2 different groups, seemed to be classified into healthy group different from other phenotypes of breast cancer patients. These findings suggested that evaluation of gene expression patterns of PBMCs of breast cancer patients might distinguish breast cancer patients from healthy subjects and the gene expression signature of PBMCs which divided breast cancer patients into 3 groups might reveal immunologically important biologic properties such as response prediction of cancer immunotherapy including immune checkpoint inhibition treatment. Citation Format: Eiji Suzuki, Kosuke Kawaguchi, Masahiro Sugimoto, Fengling Pu, Ryuji Uozumi, Ayane Yamaguchi, Mariko Nishie, Moe Tsuda, Takeshi Kotake, Satoshi Morita, Masakazu Toi. Gene expression profile of peripheral blood mononuclear cells in breast cancer patients may be contribute to the identification and the immunological classification of breast cancer patients by blood test [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5706. doi:10.1158/1538-7445.AM2017-5706

Value of circulating cell-free DNA analysis as a diagnostic tool for breast cancer: a meta-analysis.

ObjectivesThe aim of this study was to systematically evaluate the diagnostic value of cell free DNA (cfDNA) for breast cancer.ResultsAmong 308 candidate articles, 25 with relevant diagnostic screening qualified for final analysis. The mean sensitivity, specificity and area under the curve (AUC) of SROC plots for 24 studies that distinguished breast cancer patients from healthy controls were 0.70, 0.87, and 0.9314, yielding a DOR of 32.31. When analyzed in subgroups, the 14 quantitative studies produced sensitivity, specificity, AUC, and a DOR of 0.78, 0.83, 0.9116, and 24.40. The 10 qualitative studies produced 0.50, 0.98, 0.9919, and 68.45. For 8 studies that distinguished malignant breast cancer from benign diseases, the specificity, sensitivity, AUC and DOR were 0.75, 0.79, 0.8213, and 9.49. No covariate factors had a significant correlation with relative DOR. Deek's funnel plots indicated an absence of publication bias.Materials and MethodsDatabases were searched for studies involving the use of cfDNA to diagnose breast cancer. The studies were analyzed to determine sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC). Covariates were evaluated for effect on relative DOR. Deek's Funnel plots were generated to measure publication bias.ConclusionsOur analysis suggests a promising diagnostic potential of using cfDNA for breast cancer screening, but this diagnostic method is not yet independently sufficient. Further work refining qualitative cfDNA assays will improve the correct diagnosis of breast cancers.

Circulating cell-free DNA-based epigenetic assay can detect early breast cancer.

BackgroundCirculating cell-free DNA (cfDNA) has recently been recognized as a resource for biomarkers of cancer progression, treatment response, and drug resistance. However, few have demonstrated the usefulness of cfDNA for early detection of cancer. Although aberrant DNA methylation in cfDNA has been reported for more than a decade, its diagnostic accuracy remains unsatisfactory for cancer screening. Thus, the aim of the present study was to develop a highly sensitive cfDNA-based system for detection of primary breast cancer (BC) using epigenetic biomarkers and digital PCR technology.MethodsArray-based genome-wide DNA methylation analysis was performed using 56 microdissected breast tissue specimens, 34 cell lines, and 29 blood samples from healthy volunteers (HVs). Epigenetic markers for BC detection were selected, and a droplet digital methylation-specific PCR (ddMSP) panel with the selected markers was established. The detection model was constructed by support vector machine and evaluated using cfDNA samples.ResultsThe methylation array analysis identified 12 novel epigenetic markers (JAK3, RASGRF1, CPXM1, SHF, DNM3, CAV2, HOXA10, B3GNT5, ST3GAL6, DACH1, P2RX3, and chr8:23572595) for detecting BC. We also selected four internal control markers (CREM, GLYATL3, ELMOD3, and KLF9) that were identified as infrequently altered genes using a public database. A ddMSP panel using these 16 markers was developed and detection models were constructed with a training dataset containing cfDNA samples from 80 HVs and 87 cancer patients. The best detection model adopted four methylation markers (RASGRF1, CPXM1, HOXA10, and DACH1) and two parameters (cfDNA concentration and the mean of 12 methylation markers), and, and was validated in an independent dataset of 53 HVs and 58 BC patients. The area under the receiver operating characteristic curve for cancer-normal discrimination was 0.916 and 0.876 in the training and validation dataset, respectively. The sensitivity and the specificity of the model was 0.862 (stages 0-I 0.846, IIA 0.862, IIB-III 0.818, metastatic BC 0.935) and 0.827, respectively.ConclusionOur epigenetic-marker-based system distinguished BC patients from HVs with high accuracy. As detection of early BC using this system was comparable with that of mammography screening, this system would be beneficial as an optional method of screening for BC.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-016-0788-z) contains supplementary material, which is available to authorized users.

Serum immunoglobulin G Fc region N-glycosylation profiling by matrix-assisted laser desorption/ionization mass spectrometry can distinguish breast cancer patients from cancer-free controls

Herein, we report that breast cancer (BC) patients can be distinguished from cancer-free (NC) controls by serum immunoglobulin G (IgG) crystallizable fragment (Fc) region N-glycosylation profiling using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Recently, there has been much progress in the field of tumor immunology. However, to date, the role and biomarker potential of IgG Fc region N-glycosylation, which affects the function of antibodies, have not been examined in BC. In the present study, we profiled serum IgG Fc region N-glycans in BC patients (N = 90) and NC controls (N = 54) using MALDI-MS. An IgG Fc region N-glycan-based multiple logistic regression model was produced which could distinguish BC patients from NC controls (area under the receiver operative characteristic curve = 0.874). Furthermore, stage 0 patients could also be distinguished using this model. These results suggest that an unknown humoral factor or soluble mediator affects IgGs from the earliest stage of breast cancer, and also suggests that IgG Fc region N-glycosylation may play a role in tumor biology. Although further investigation is required, our findings are the evidence that IgG N-glycan profiling has the potential to be used as a breast cancer biomarker and may provide the insights into tumor immunology.

A circulating miRNA signature as a diagnostic biomarker for non-invasive early detection of breast cancer.

Novel, non-invasive biomarkers to diagnose breast cancer with high sensitivity and specificity are greatly desired. Circulating microRNAs (miRNAs) show potential for breast cancer detection, but the existing results appear to be mixed. Using microscale serum, we established a novel serum-direct multiplex detection assay based on RT-PCR (SdM-RT-PCR). Ninety-three miRNAs dysregulated or with functions in breast cancer were selected as candidates, and additional 3 miRNAs were chosen as endogenous controls. We first conducted miRNA profiling of these 96 miRNAs by SdM-RT-PCR using the sera of 25 breast cancer patients at diagnosis prior to treatment and 20 age-matched healthy controls. miRNAs showing significantly different expression levels between patients and controls were further analyzed using a logistic regression model. A miRNA signature was validated in an independent set of 128 serum samples composed of 76 breast cancer patients and 52 healthy controls. In the discovery stage, we identified 23 miRNAs as significantly dysregulated in breast cancer patients compared with healthy controls. Of these, 10 miRNAs were previously identified as dysregulated in breast cancer; 14 miRNAs remained significant after P-values were adjusted by both correction methods. Principal component analysis and hierarchical clustering of these miRNAs separated patients from controls. Furthermore, the 3-miRNA signature (miR-199a, miR-29c, and miR-424) with the highest diagnostic accuracy for distinguishing breast cancer patients from controls by ROC curve analysis (AUC=0.888) was successfully confirmed in the validation set (AUC=0.901). Our data demonstrate that the SdM-RT-PCR assay is an effective breast cancer profiling method that utilizes very small volumes and is compatible with Biobank. Furthermore, the identified 3-miRNA signature is a promising circulating biomarker for breast cancer diagnosis.

Circulating DNA of HOTAIR in serum is a novel biomarker for breast cancer.

Long non-coding HOX transcript antisense intergenic RNA (HOTAIR) plays an important role in breast cancer. The purpose of this study was to determine whether circulating HOTAIR can be used for breast cancer diagnosis. HOTAIR in serum was measured by PCR-based direct detection. Reverse transcriptase and DNase I treatment were used to distinguish the DNA and RNA forms of HOTAIR. To determine whether circulating HOTAIR is a biomarker for breast cancer, the DNA of HOTAIR from breast cancer patients and healthy controls was measured at both the discovery stage (48 individuals) and an independent validation stage (156 individuals). The diagnostic accuracy was assessed by the receiver operating characteristic curve (ROC) and the area under the curve (AUC). We showed that the major form of HOTAIR-derived fragment in serum is DNA rather than RNA in our study, the same as for MALAT-1, another well-described lincRNA. A higher circulating DNA level of HOTAIR was found in patients at the discovery stage (P = 0.0008). ROC analysis revealed that the circulating HOTAIR DNA distinguished breast cancer patients from healthy individuals (AUC = 0.799). This finding was confirmed at the validation stage. Though circulating MALAT-1 DNA was altered in the discovery stage, it showed no significant difference in the validation stage. In the entire set of 204 samples, the circulating HOTAIR DNA showed a 2.15-fold change in patients compared with healthy controls (P < 0.0001, AUC = 0.786). The optimal cutoff value for diagnosis was 0.30 with sensitivity of 80.0 % and specificity of 68.3 %. Moreover, a correlation between the DNA level of circulating HOTAIR and the progress of breast cancer was established. We have demonstrated that the circulating DNA of HOTAIR is a potential biomarker for breast cancer.

Reduced expression levels of let-7c in human breast cancer patients.

Circulating microRNAs (miRNAs) are important in the diagnosis of a number of diseases, since serum or plasma miRNAs are more stable compared with miRNA isolated from blood samples. The aim of the present study was to investigate the association between the expression levels of serum let-7c miRNA and the clinical diagnosis of breast cancer (BC). The circulating let-7c levels of 90 BC patients and 64 healthy controls were determined by performing a reverse transcription-quantitative polymerase chain reaction assay. The results demonstrated that let-7c expression was downregulated in the BC tissues compared with the paracarcinoma control tissues. In addition, the let-7c expression in the serum of BC patients was significantly lower compared with the healthy controls (P<0.01). Using a cutoff value of 0.374×103 copies/ml, the serum expression levels of let-7c exhibited 87.5% sensitivity and 78.9% specificity for distinguishing BC patients from healthy controls (area under the receiver operating characteristic curve, 0.848; 95% confidence interval, 0.785–0.911). Furthermore, the results demonstrated that the serum expression levels of let-7c were significantly higher in premenopausal compared with postmenopausal patients (P<0.05), supporting the hypothesis that postmenopausal status may affect the serum expression levels of let-7c. However, no statistically significant differences were detected in the serum levels of let-7c between ER (or PR)-positive and -negative patients. Therefore, the current study hypothesized that serum let-7c may be used as a novel and valuable biomarker for the diagnosis of BC.

Peripheral blood cells inform on the presence of breast cancer: A population‐based case–control study

Tumor–host interactions extend beyond the local microenvironment and cancer development largely depends on the ability of malignant cells to hijack and exploit the normal physiological processes of the host. Here, we established that many genes within peripheral blood cells show differential expression when an untreated breast cancer (BC) is present, and harnessed this fact to construct a 50-gene signature that distinguish BC patients from population-based controls. Our results were derived from a series of large datasets within our unique population-based Norwegian Women and Cancer cohort that allowed us to investigate the influence of medications and tumor characteristics on our blood-based test, and were further tested in two external datasets. Our 50-gene signature contained cytostatic signals including the specific suppression of the immune response and medications influencing transcription involved in those processes were identified as confounders. Through analysis of the biological processes differentially expressed in blood, we were able to provide a rationale as to why the systemic response of the host may be a reliable marker of BC, characterized by the underexpression of both immune-specific pathways and “universal” cell programs driven by MYC (i.e., metabolism, growth and cell cycle). In conclusion, gene expression of peripheral blood cells is markedly perturbed by the specific presence of carcinoma in the breast and these changes simultaneously engage a number of systemic cytostatic signals emerging connections with immune escape of BC.What's new?Blood cells are dynamic warehouses of information. In the case of cancer, studies have indicated that blood cells house genetic signatures related to solid tumors. In the present study, genes in peripheral blood cells were found to be differentially expressed in women with untreated breast cancer, enabling the development of a 50-gene signature capable of identifying women with the disease. The gene signature included signals specific to immunosuppression. The association of breast cancer with the underexpression of immune-specific pathways and with MYC-driven “universal” cell programs may explain the systemic response of the host.

Volatile organic metabolites identify patients with breast cancer, cyclomastopathy, and mammary gland fibroma.

The association between cancer and volatile organic metabolites in exhaled breaths has attracted increasing attention from researchers. The present study reports on a systematic study of gas profiles of metabolites in human exhaled breath by pattern recognition methods. Exhaled breath was collected from 85 patients with histologically confirmed breast disease (including 39 individuals with infiltrating ductal carcinoma, 25 individuals with cyclomastopathy and from 21 individuals with mammary gland fibroma) and 45 healthy volunteers. Principal component analysis and partial least squares discriminant analysis were used to process the final data. The volatile organic metabolites exhibited significant differences between breast cancer and normal controls, breast cancer and cyclomastopathy, and breast cancer and mammary gland fibroma; 21, 6, and 8 characteristic metabolites played decisive roles in sample classification, respectively (P < 0.05). Three volatile organic metabolites in the exhaled air, 2,5,6-trimethyloctane, 1,4-dimethoxy-2,3-butanediol, and cyclohexanone, distinguished breast cancer patients from healthy individuals, mammary gland fibroma patients, and patients with cyclomastopathy (P < 0.05). The identified three volatile organic metabolites associated with breast cancer may serve as novel diagnostic biomarkers.

Construction and investigation of breast‐cancer‐specific ceRNA network based on the mRNA and miRNA expression data

It has been proved and widely acknowledged that messenger RNAs can talk to each other by competing for a limited pool of miRNAs. The competing endogenous RNAs are called as ceRNAs. Although some researchers have recently used ceRNAs to do biological function annotations, few of them have investigated the ceRNA network on specific disease systematically. In this work, using both miRNA expression data and mRNA expression data of breast cancer patient as well as the miRNA target relations, the authors proposed a computational method to construct a breast-cancer-specific ceRNA network by checking whether the shared miRNA sponges between the gene pairs are significant. The ceRNA network is shown to be scale-free, thus the topological characters such as hub nodes and communities may provide important clues for the biological mechanism. Through investigation on the communities (the dense clusters) in the network, it was found that they are related to cancer hallmarks. In addition, through function annotation of the hub genes in the network, it was found that they are related to breast cancer. Moreover, classifiers based on the discriminative hubs can significantly distinguish breast cancer patients' risks of distant metastasis in all the three independent data sets.