Development and validation of a circulating microRNA panel for the early detection of breast cancer.

BACKGROUND: Mammography is widely used for breast cancer screening but suffers from a high false-positive rate. Here, we perform the largest comprehensive, multi-center study to date involving diverse ethnic groups, for the identification of circulating miRNAs for breast cancer screening. METHODS: This study had a discovery phase (n = 289) and two validation phases (n = 374 and n = 379). Quantitative PCR profiling of 324 miRNAs was performed on serum samples from breast cancer (all stages) and healthy subjects to identify miRNA biomarkers. Two-fold cross-validation was used for building and optimising breast cancer-associated miRNA panels. An optimal panel was validated in cohorts with Caucasian and Asian samples. Diagnostic ability was evaluated using area under the curve (AUC) analysis. RESULTS: The study identified and validated 30 miRNAs dysregulated in breast cancer. An optimised eight-miRNA panel showed consistent performance in all cohorts and was successfully validated with AUC, accuracy, sensitivity, and specificity of 0.915, 82.3%, 72.2% and 91.5%, respectively. The prediction model detected breast cancer in both Caucasian and Asian populations with AUCs ranging from 0.880 to 0.973, including pre-malignant lesions (stage 0; AUC of 0.831) and early-stage (stages I-II) cancers (AUC of 0.916). CONCLUSIONS: Our panel can potentially be used for breast cancer screening, in conjunction with mammography.

Circulating microRNA breast cancer biomarker detection in patient sera with surface plasmon resonance imaging biosensor.

In this article, we report for the first time, the detection of circulating miRNA as a breast cancer biomarker in patient sera using surface plasmon resonance imaging biosensor. The advantage of this approach lies in the rapid, label-free and sensitive detection. The sensor excites plasmonic resonance on the gold sensor surface and specific DNA-miRNA molecular bindings elucidate responses in the plasmonic resonance image. Experiments of detecting synthetic miRNA molecules (miR-1249) were performed and the sensor resolution was found to be 63.5 nM. The sensor was further applied to screen 17 patient serum samples from National Cancer Centre Singapore and Tan Tock Seng Hospital. Sensor intensity response was found to differ by 20% between malignant and benign cases and thus forms, a potential and an important metric in distinguishing benignity and malignancy.

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer.

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.

A Circulating miRNA Signature for Stratification of Breast Lesions among Women with Abnormal Screening Mammograms.

Although mammography is the gold standard for breast cancer screening, the high rates of false-positive mammograms remain a concern. Thus, there is an unmet clinical need for a non-invasive and reliable test to differentiate between malignant and benign breast lesions in order to avoid subjecting patients with abnormal mammograms to unnecessary follow-up diagnostic procedures. Serum samples from 116 malignant breast lesions and 64 benign breast lesions were comprehensively profiled for 2,083 microRNAs (miRNAs) using next-generation sequencing. Of the 180 samples profiled, three outliers were removed based on the principal component analysis (PCA), and the remaining samples were divided into training (n = 125) and test (n = 52) sets at a 70:30 ratio for further analysis. In the training set, significantly differentially expressed miRNAs (adjusted p < 0.01) were identified after correcting for multiple testing using a false discovery rate. Subsequently, a predictive classification model using an eight-miRNA signature and a Bayesian logistic regression algorithm was developed. Based on the receiver operating characteristic (ROC) curve analysis in the test set, the model could achieve an area under the curve (AUC) of 0.9542. Together, this study demonstrates the potential use of circulating miRNAs as an adjunct test to stratify breast lesions in patients with abnormal screening mammograms.

Breast cancer in women with neurofibromatosis type 1 (NF1): a comprehensive case series with molecular insights into its aggressive phenotype.

PURPOSE: The purpose of the study was to improve the understanding of NF1-associated breast cancer, given the increased risk of breast cancer in this tumour predisposition syndrome and the limited data. METHODS: We identified 18 women with NF1 and breast cancer at our institution. Clinical and pathologic characteristics of NF1-associated breast cancers were compared with 7132 breast cancers in patients without NF1 from our institutional database. Next generation sequencing was performed on DNA from blood and breast cancer specimens available. Blood specimens negative for NF1 mutation were subjected to multiplex ligation-dependent probe amplification (MLPA) to identify complete/partial deletions or duplications. Expression of neurofibromin in the NF1-associated breast cancers was evaluated using immunohistochemistry. RESULTS: There was a higher frequency of grade 3 (83.3% vs 45.4%, p = 0.005), oestrogen receptor (ER) negative (66.7% vs 26.3%, p < 0.001) and human epidermal growth factor receptor 2 (HER2)-positive (66.7% vs 23.4%, p < 0.001) tumours among NF1 patients compared to non-NF1 breast cancers. Overall survival was inferior in NF1 patients in multivariable analysis (hazard ratio 2.25, 95% CI 1.11-4.60; p = 0.025). Apart from germline NF1 mutations (11/16; 69%), somatic mutations in TP53 (8/10; 80%), second-hit NF1 (2/10; 20%), KMT2C (4/10; 40%), KMT2D (2/10; 20%), and PIK3CA (2/10; 20%) were observed. Immunohistochemical expression of neurofibromin was seen in the nuclei and/or cytoplasm of all specimens, but without any consistent pattern in the intensity or extent. CONCLUSIONS: This comprehensive series of NF1-associated breast cancers suggests that their aggressive features are related to germline NF1 mutations in cooperation with somatic mutations in TP53, KMT2C and other genes.

Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese.

Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157-3.100), 2.013 (95% CI = 1.227-3.302) and 1.751 (95% CI = 1.073-2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.

The future of blood-based biomarkers for the early detection of breast cancer.

Breast cancer (BC) is the most frequently diagnosed cancer and the most common cause of cancer-related mortality among women worldwide. Despite the extensive use of mammography as the gold standard for BC screening, the occurrences of false-positive and false-negative mammograms, as well as overdiagnosis, remain a concern in breast oncology. Thus, there is a need to identify reliable biomarkers from an easily accessible source that could generate cost-effective assays feasible for routine screening. Blood-based biomarkers may offer an alternative non-invasive strategy to improve cancer screening. Although none of the currently used blood-based biomarkers are sensitive enough for the early detection of BC, a plethora of significant findings pertaining to the development of screening tools using blood-based biomarkers have emerged in recent years. Promising candidate biomarkers such as proteins, autoantibodies, miRNAs, nucleic acid methylation, metabolites and lipids have shown great potential for detecting BC, including detection at the pre-invasive and early stages of the disease. Nevertheless, blood-based biomarkers for BC screening are still at the early phases of development, and various clinical and preclinical issues need to be addressed before these biomarkers can be used clinically. This review summarises the latest discoveries for harnessing blood-based biomarkers as novel BC screening tools, as well as discusses the limitations and challenges that need to be overcome before the translation of their use from the bench to the bedside.

Identification of Novel Breast Cancer Risk Loci.

It has been estimated that >1,000 genetic loci have yet to be identified for breast cancer risk. Here we report the first study utilizing targeted next-generation sequencing to identify single-nucleotide polymorphisms (SNP) associated with breast cancer risk. Targeted sequencing of 283 genes was performed in 240 women with early-onset breast cancer (≤40 years) or a family history of breast and/or ovarian cancer. Common coding variants with minor allele frequencies (MAF) >1% that were identified were presumed initially to be SNPs, but further database inspections revealed variants had MAF of ≤1% in the general population. Through prioritization and stringent selection criteria, we selected 24 SNPs for further genotyping in 1,516 breast cancer cases and 1,189 noncancer controls. Overall, we identified the JAK2 SNP rs56118985 to be significantly associated with overall breast cancer risk. Subtype analysis performed for patient subgroups defined by ER, PR, and HER2 status suggested additional associations of the NOTCH3 SNP rs200504060 and the HIF1A SNP rs142179458 with breast cancer risk. In silico analysis indicated that coding amino acids encoded at these three SNP sites were conserved evolutionarily and associated with decreased protein stability, suggesting a likely impact on protein function. Our results offer proof of concept for identifying novel cancer risk loci from next-generation sequencing data, with iterative data analysis from targeted, whole-exome, or whole-genome sequencing a wellspring to identify new SNPs associated with cancer risk. Cancer Res; 77(19); 5428-37. ©2017 AACR.

Global gene expression changes in the prefrontal cortex of rabbits with hypercholesterolemia and/or hypertension.

Although many studies have identified a link between hypercholesterolemia or hypertension and cognitive deficits, till date, comprehensive gene expression analyses of the brain under these conditions is still lacking. The present study was carried out to elucidate differential gene expression changes in the prefrontal cortex (PFC) of New Zealand white rabbits exposed to hypercholesterolemia and/or hypertension with a view of identifying gene networks at risk. Microarray analyses of the PFC of hypercholesterolemic rabbits showed 850 differentially expressed genes (DEGs) in the cortex of hypercholesterolemic rabbits compared to controls, but only 5 DEGs in hypertensive rabbits compared to controls. Up-regulated genes in the PFC of hypercholesterolemic rabbits included CIDEC, ODF2, RNASEL, FSHR, CES3 and MAB21L3, and down-regulated genes included FAM184B, CUL3, LOC100351029, TMEM109, LOC100357097 and PFDN5. Comparison with our previous study on the middle cerebral artery (MCA) of the same rabbits showed many differentially expressed genes in common between the PFC and MCA, during hypercholesterolemia. Moreover, these genes tended to fall into the same functional networks, as revealed by IPA analyses, with many identical node molecules. These include: proteasome, insulin, Akt, ERK1/2, histone, IL12, interferon alpha and NFκB. Of these, PSMB4, PSMD4, PSMG1 were chosen as representatives of genes related to the proteasome for verification by quantitative RT-PCR. Results indicate significant downregulation of all three proteasome associated genes in the PFC. Immunostaining showed significantly increased number of Aß labelled cells in layers III and V of the cortex after hypercholesterolemia and hypertension, which may be due to decreased proteasome activity and/or increased ß- or γ-secretase activity. Knowledge of altered gene networks during hypercholesterolemia and/or hypertension could inform our understanding of the link between these conditions and cognitive deficits in vascular dementia or Alzheimer's disease.

Comprehensive gene expression profiling reveals synergistic functional networks in cerebral vessels after hypertension or hypercholesterolemia.

Atherosclerotic stenosis of cerebral arteries or intracranial large artery disease (ICLAD) is a major cause of stroke especially in Asians, Hispanics and Africans, but relatively little is known about gene expression changes in vessels at risk. This study compares comprehensive gene expression profiles in the middle cerebral artery (MCA) of New Zealand White rabbits exposed to two stroke risk factors i.e. hypertension and/or hypercholesterolemia, by the 2-Kidney-1-Clip method, or dietary supplementation with cholesterol. Microarray and Ingenuity Pathway Analyses of the MCA of the hypertensive rabbits showed up-regulated genes in networks containing the node molecules: UBC (ubiquitin), P38 MAPK, ERK, NFkB, SERPINB2, MMP1 and APP (amyloid precursor protein); and down-regulated genes related to MAPK, ERK 1/2, Akt, 26 s proteasome, histone H3 and UBC. The MCA of hypercholesterolemic rabbits showed differentially expressed genes that are surprisingly, linked to almost the same node molecules as the hypertensive rabbits, despite a relatively low percentage of 'common genes' (21 and 7%) between the two conditions. Up-regulated common genes were related to: UBC, SERPINB2, TNF, HNF4A (hepatocyte nuclear factor 4A) and APP, and down-regulated genes, related to UBC. Increased HNF4A message and protein were verified in the aorta. Together, these findings reveal similar nodal molecules and gene pathways in cerebral vessels affected by hypertension or hypercholesterolemia, which could be a basis for synergistic action of risk factors in the pathogenesis of ICLAD.

Comprehensive gene expression analyses of the rat prefrontal cortex after oxysterol treatment.

Oxysterols such as 7ß-hydroxycholesterol (7ß-HC) and 7-ketocholesterol (7-KC) have been linked to the pathophysiology of neurodegenerative diseases. This study was carried out to examine the effect of oxysterols on global gene expression in the rat prefrontal cortex (PFC). 7ß-HC, 7-KC, or cholesterol was injected into the rat PFC and RNA was extracted from this brain region at 24-h post-injection and analyzed. Microarray analyses identified 1365 genes, whose expressions were affected by both 7ß-HC and 7-KC. Among these, down-regulated genes outnumbered up-regulated genes. Pathway analysis showed that down-regulated genes had roles in carbohydrate metabolism, cell signaling and nucleic acid metabolism; and the majority of these encode G-protein coupled receptors (GPCRs). Expression of selected genes were validated by quantitative real-time PCR. Western blots confirmed down-regulation of oxytocin receptor (Oxtr) at 1 day post-7ß-HC treatment. Immunohistochemical analysis showed localization of Oxtr in neurons of the PFC. Electron microscopy identified the presence of Oxtr-immunoreactivity in axon terminals. Together, these findings provide insights into molecular mechanisms through which oxysterols could exert their pathophysiological effects, and suggest that increased oxysterols may affect synaptic function by transcriptional repression of GPCRs.