Current molecular diagnostics of breast cancer and the potential incorporation of microRNA

In silico designing and expression of novel recombinant construct containing the variable part of CD44 extracellular domain for prediagnostic breast cancer

BACKGROUND

CD44, as a tumor-associated marker, can be used to detect stem cells in breast cancer. While CD44 is expressed in normal epithelial cells, carcinoma cells overexpress CD44.

AIMS

In the current study, we designed a recombinant protein that included the variable component of the CD44 (CD44v) extracellular domain to apply in clinical diagnosis of breast cancer.

METHODS

A total of 100 CD44v amino-acid residues were determined, and the structure was examined using bioinformatics tools. The construct was inserted into the PET28a vector and transformed in E. coli BL21(DE3). A nearly 12 kDa fusion protein was obtained by Ni-NTA affinity metal chromatography. Recombinant CD44v was examined by Western blotting, ELISA, and immunohistochemistry (IHC) assays.

RESULTS

The findings revealed that the structure of rCD44v was stable, and its antigenic domain was exposed. The recombinant CD44v was confirmed by western blotting, and the presence of antibodies against recombinant CD44v protein in the patient's serum was detected by the ELISA. Our data demonstrated a link between CD44v serum levels and the prevalence of breast cancer.

CONCLUSION

Assessments of antiCD44v antibodies with rCD44v could be a useful tool for identifying breast cancer in its early stages, which can lead to better outcomes.

Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements

In the current era of medical revolution, genomic testing has guided the healthcare fraternity to develop predictive, preventive, and personalized medicine. Predictive screening involves sequencing a whole genome to comprehensively deliver patient care via enhanced diagnostic sensitivity and specific therapeutic targeting. The best example is the application of whole-exome sequencing when identifying aberrant fetuses with healthy karyotypes and chromosomal microarray analysis in complicated pregnancies. To fit into today's clinical practice needs, experimental system biology like genomic technologies, and system biology viz., the use of artificial intelligence and machine learning is required to be attuned to the development of preventive and personalized medicine. As diagnostic techniques are advancing, the selection of medical intervention can gradually be influenced by a person's genetic composition or the cellular profiling of the affected tissue. Clinical genetic practitioners can learn a lot about several conditions from their distinct facial traits. Current research indicates that in terms of diagnosing syndromes, facial analysis techniques are on par with those of qualified therapists. Employing deep learning and computer vision techniques, the face image assessment software DeepGestalt measures resemblances to numerous of disorders. Biomarkers are essential for diagnostic, prognostic, and selection systems for developing personalized medicine viz. DNA from chromosome 21 is counted in prenatal blood as part of the Down's syndrome biomarker screening. This review is based on a detailed analysis of the scientific literature via a vigilant approach to highlight the applicability of predictive diagnostics for the development of preventive, targeted, personalized medicine for clinical application in the framework of predictive, preventive, and personalized medicine (PPPM/3 PM). Additionally, targeted prevention has also been elaborated in terms of gene-environment interactions and next-generation DNA sequencing. The application of 3 PM has been highlighted by an in-depth analysis of cancer and cardiovascular diseases. The real-time challenges of genome sequencing and personalized medicine have also been discussed.

Advances in Aptamers-Based Applications in Breast Cancer: Drug Delivery, Therapeutics, and Diagnostics

Aptamers are synthetic single-stranded oligonucleotides (such as RNA and DNA) evolved in vitro using Systematic Evolution of Ligands through Exponential enrichment (SELEX) techniques. Aptamers are evolved to have high affinity and specificity to targets; hence, they have a great potential for use in therapeutics as delivery agents and/or in treatment strategies. Aptamers can be chemically synthesized and modified in a cost-effective manner and are easy to hybridize to a variety of nano-particles and other agents which has paved a way for targeted therapy and diagnostics applications such as in breast tumors. In this review, we systematically explain different aptamer adoption approaches to therapeutic or diagnostic uses when addressing breast tumors. We summarize the current therapeutic techniques to address breast tumors including aptamer-base approaches. We discuss the next aptamer-based therapeutic and diagnostic approaches targeting breast tumors. Finally, we provide a perspective on the future of aptamer-based sensors for breast therapeutics and diagnostics. In this section, the therapeutic applications of aptamers will be discussed for the targeting therapy of breast cancer.

Prognostic Value and Biological Role of miR-126 in Breast Cancer

In eukaryotic organisms such as humans, some noncoding single-stranded RNAs (ncRNAs) contribute to regulating the expression of some genes before and after the transcription process, which in turn controls a number of vital physiological processes, including cell proliferation, differentiation, invasion, angiogenesis, and embryonic development. miR-126 is one of these miRNAs expressed exclusively in endothelial cells such as capillaries and vessels involved in controlling angiogenesis. In recent years, the link between miRs such as miR-126 and the pathology of breast cancer has attracted the attention of many researchers. Numerous studies have shown that miR-126 may be able to suppress tumor tissue metastasis or to increase tumor metastasis through complex molecular mechanisms. There is ample clinical evidence that miR-126 can be used as a biomarker to predict and diagnose breast cancer due to the increased or decreased expression of certain genes in breast cancer tissue. In this review, we discuss the association between the growth and metastasis (tumorigenesis) of breast cancer and miR-126, as well as the relationship between current research advances in the prognosis, diagnosis, and treatment of breast cancer and miR-126.

Rapid Detection of MCR-Mediated Colistin Resistance in Escherichia coli

Colistin is one of the last-resort antibiotics for infections caused by multidrug-resistant Gram-negative bacteria. However, the wide spread of novel plasmid-carrying colistin resistance genes mcr-1 and its variants substantially compromise colistin's therapeutic effectiveness and pose a severe danger to public health. To detect colistin-resistant microorganisms induced by mcr genes, rapid and reliable antibiotic susceptibility testing (AST) is imminently needed. In this study, we identified an RNA-based AST (RBAST) to discriminate between colistin-susceptible and mcr-1-mediated colistin-resistant bacteria. After short-time colistin treatment, RBAST can detect differentially expressed RNA biomarkers in bacteria. Those candidate mRNA biomarkers were successfully verified within colistin exposure temporal shifts, concentration shifts, and other mcr-1 variants. Furthermore, a group of clinical strains were effectively distinguished by using the RBAST approach during the 3-h test duration with over 93% accuracy. Taken together, our findings imply that certain mRNA transcripts produced in response to colistin treatment might be useful indicators for the development of fast AST for mcr-positive bacteria.

IMPORTANCE The emergence and prevalence of mcr-1 and its variants in humans, animals, and the environment pose a global public health threat. There is a pressing urgency to develop rapid and accurate methods to identify MCR-positive colistin-resistant bacteria in the clinical samples, providing a basis for subsequent effective antibiotic treatment. Using the specific mRNA signatures, we develop an RNA-based antibiotic susceptibility testing (RBAST) for effectively distinguishing colistin-susceptible and mcr-1-mediated colistin-resistant strains. Meanwhile, the detection efficiency of these RNA biomarkers was evidenced in other mcr variants-carrying strains. By comparing with the traditional AST method, the RBAST method was verified to successfully characterize a set of clinical isolates during 3 h assay time with over 93% accuracy. Our study provides a feasible method for the rapid detection of colistin-resistant strains in clinical practice.

Rapid and Accurate Antibiotic Susceptibility Determination of tet(X)-Positive E. coli Using RNA Biomarkers

The emergence and prevalence of novel plasmid-mediated tigecycline resistance genes, namely, tet(X) and their variants, pose a serious threat to public health worldwide. Rapid and accurate antibiotic susceptibility testing (AST) that can simultaneously detect the genotype and phenotype of tet(X)-positive bacteria may contribute to the deployment of an effective antibiotic arsenal, mortality reduction, and a decrease in the use of broad-spectrum antimicrobial agents. However, current bacterial growth-based AST methods, such as broth microdilution, are time consuming and delay the prompt treatment of infectious diseases. Here, we developed a rapid RNA-based AST (RBAST) assay to effectively distinguish tet(X)-positive and -negative strains. RBAST works by detecting specific mRNA expression signatures in bacteria after short-term tigecycline exposure. As a proof of concept, a panel of clinical isolates was characterized successfully by using the RBAST method, with a 3-h assay time and 87.9% accuracy (95% confidence interval [CI], 71.8% to 96.6%). Altogether, our findings suggest that RNA signatures upon antibiotic exposure are promising biomarkers for the development of rapid AST, which could inform early antibiotic choices.

IMPORTANCE Infections caused by multidrug-resistant (MDR) Gram-negative pathogens are an increasing threat to global health. Tigecycline is one of the last-resort antibiotics for the treatment of these complicated infections; however, the emergence of plasmid-encoded tigecycline resistance genes, namely, tet(X), severely diminishes its clinical efficacy. Currently, there is a lack of rapid and accurate antibiotic susceptibility testing (AST) for the detection of tet(X)-positive bacteria. In this study, we developed a rapid and robust RNA-based antibiotic susceptibility determination (RBAST) assay to effectively distinguish tet(X)-negative and -positive strains using specific RNA biomarkers in bacteria after tigecycline exposure. Using this RBAST method, we successfully characterized a set of clinical strains in 3 h. Our data indicate that the RBAST assay is useful for identifying tet(X)-positive Escherichia coli.

MicroRNAs in Molecular Classification and Pathogenesis of Breast Tumors

The current clinical practice of breast tumor classification relies on the routine immunohistochemistry-based expression analysis of hormone receptors, which is inadequate in addressing breast tumor heterogeneity and drug resistance. MicroRNA expression profiling in tumor tissue and in the circulation is an efficient alternative to intrinsic molecular subtyping that enables precise molecular classification of breast tumor variants, the prediction of tumor progression, risk stratification and also identifies critical regulators of the tumor microenvironment. This review integrates data from protein, gene and miRNA expression studies to elaborate on a unique miRNA-based 10-subtype taxonomy, which we propose as the current gold standard to allow appropriate classification and separation of breast cancer into a targetable strategy for therapy.

Real-world Evidence of Diagnostic Testing and Treatment Patterns in US Patients With Breast Cancer With Implications for Treatment Biomarkers From RNA Sequencing Data

OBJECTIVE/BACKGROUND

We performed a retrospective analysis of longitudinal real-world data (RWD) from patients with breast cancer to replicate results from clinical studies and demonstrate the feasibility of generating real-world evidence. We also assessed the value of transcriptome profiling as a complementary tool for determining molecular subtypes.

METHODS

De-identified, longitudinal data were analyzed after abstraction from records of patients with breast cancer in the United States (US) structured and stored in the Tempus database. Demographics, clinical characteristics, molecular subtype, treatment history, and survival outcomes were assessed according to strict qualitative criteria. RNA sequencing and clinical data were used to predict molecular subtypes and signaling pathway enrichment.

RESULTS

The clinical abstraction cohort (n = 4000) mirrored the demographics and clinical characteristics of patients with breast cancer in the US, indicating feasibility for RWE generation. Among patients who were human epidermal growth factor receptor 2-positive (HER2+), 74.2% received anti-HER2 therapy, with ∼70% starting within 3 months of a positive test result. Most non-treated patients were early stage. In this RWD set, 31.7% of patients with HER2+ immunohistochemistry (IHC) had discordant fluorescence in situ hybridization results recorded. Among patients with multiple HER2 IHC results at diagnosis, 18.6% exhibited intra-test discordance. Through development of a whole-transcriptome model to predict IHC receptor status in the molecular sequenced cohort (n = 400), molecular subtypes were resolved for all patients (n = 36) with equivocal HER2 statuses from abstracted test results. Receptor-related signaling pathways were differentially enriched between clinical molecular subtypes.

CONCLUSIONS

RWD in the Tempus database mirrors the overall population of patients with breast cancer in the US. These results suggest that real-time, RWD analyses are feasible in a large, highly heterogeneous database. Furthermore, molecular data may aid deficiencies and discrepancies observed from breast cancer RWD.

MicroRNA Expression Changes and Integrated Pathways Associated With Poor Outcome in Canine Osteosarcoma

MicroRNAs (miRNA) are small non-coding RNA molecules involved in post-transcriptional gene regulation. Deregulation of miRNA expression occurs in cancer, and miRNA expression profiles have been associated with diagnosis and prognosis in many cancers. Osteosarcoma (OS), an aggressive primary tumor of bone, affects ~10,000 dogs each year. Though survival has improved with the addition of chemotherapy, up to 80% of canine patients will succumb to metastatic disease. Reliable prognostic markers are lacking for this disease. miRNAs are attractive targets of biomarker discovery efforts due to their increased stability in easily obtained body fluids as well as within fixed tissue. Previous studies in our laboratory demonstrated that dysregulation of genes in aggressive canine OS tumors that participate in miRNA regulatory networks is reportedly disrupted in OS or other cancers. We utilized RT-qPCR in a 384-well-plate system to measure the relative expression of 190 miRNAs in 14 canine tumors from two cohorts of dogs with good or poor outcome (disease-free interval >300 or <100 days, respectively). Differential expression analysis in this subset guided the selection of candidate miRNAs in tumors and serum samples from larger groups of dogs. We ultimately identified a tumor-based three-miR Cox proportional hazards regression model and a serum-based two-miR model, each being able to distinguish patients with good and poor prognosis via Kaplan-Meier analysis with log rank test. Additionally, we integrated miRNA and gene expression data to identify potentially important miRNA-mRNA interactions that are disrupted in canine OS. Integrated analyses of miRNAs in the three-miR predictive model and disrupted genes from previous expression studies suggest the contribution of the primary tumor microenvironment to the metastatic phenotype of aggressive tumors.

Targeting triple-negative breast cancer with an aptamer-functionalized nanoformulation: a synergistic treatment that combines photodynamic and bioreductive therapies

Background

Areas of hypoxia are often found in triple-negative breast cancer (TNBC), it is thus more difficult to treat than other types of breast cancer, and may require combination therapies. A new strategy that combined bioreductive therapy with photodynamic therapy (PDT) was developed herein to improve the efficacy of cancer treatment. Our design utilized the characteristics of protoporphyrin IX (PpIX) molecules that reacted and consumed O₂ at the tumor site, which led to the production of cytotoxic reactive oxygen species (ROS). The low microenvironmental oxygen levels enabled activation of a bioreductive prodrug, tirapazamine (TPZ), to become a toxic radical. The TPZ radical not only eradicated hypoxic tumor cells, but it also promoted therapeutic efficacy of PDT.

Results

To achieve the co-delivery of PpIX and TPZ for advanced breast cancer therapy, thin-shell hollow mesoporous Ia3d silica nanoparticles, designated as MMT-2, was employed herein. This nanocarrier designed to target the human breast cancer cell MDA-MB-231 was functionalized with PpIX and DNA aptamer (LXL-1), and loaded with TPZ, resulting in the formation of TPZ@LXL-1-PpIX-MMT-2 nanoVector. A series of studies confirmed that our nanoVectors (TPZ@LXL-1-PpIX-MMT-2) facilitated in vitro and in vivo targeting, and significantly reduced tumor volume in a xenograft mouse model. Histological analysis also revealed that this nanoVector killed tumor cells in hypoxic regions efficiently.

Conclusions

Taken together, the synergism and efficacy of this new therapeutic design was confirmed. Therefore, we concluded that this new therapeutic strategy, which exploited a complementary combination of PpIX and TPZ, functioned well in both normoxia and hypoxia, and is a promising medical procedure for effective treatment of TNBC.

Overexpression of miR-1225 promotes the progression of breast cancer, resulting in poor prognosis

Breast cancer is the most common cancer among women, with metastasis as the principal cause of mortality. MiR-1225 has been reported to play roles in the progression of various cancers, but its role in breast cancer was unclear. The expression of miR-1225 was investigated in breast cancer tissues and cells by quantitative real-time PCR. The role of miR-1225 in the cell process of OS was analyzed by CCK-8 assay and Transwell assay. The prognostic value of miR-1225 was evaluated by Kaplan-Meier survival curves and Cox regression analysis. miR-1225 was significantly upregulated in breast cancer tissues, which was associated with the TNM stage of breast cancer patients. The prognosis of patients with high miR-1225 expression was worse than that of patients with low miR-1225 expression, which indicated that miR-1225 acted as an independent factor for the prognosis of breast cancer. Additionally, the upregulation of miR-1225 promoted cell proliferation, migration, and invasion of breast cancer, which suggested miR-1225 might be involved in the progression of breast cancer. JAK1 was identified as the direct target of miR-1225, which was also involved in cell proliferation, migration, and invasion of breast cancer. The overexpression of miR-1225 in breast cancer indicates a poor prognosis of patients and promotes the progression of breast cancer by targeting JAK1. miR-1225 may be a biomarker and therapeutic target for the treatment of breast cancer.

Transmembrane protein 92 performs a tumor-promoting function in breast carcinoma by contributing to the cell growth, invasion, migration and epithelial-mesenchymal transition

OBJECTIVE

We try to examine the role of transmembrane protein 92 (TMEM92) in the progression of breast carcinoma (BC) and assess its prognostic value. Moreover, the effects of TMEM92 on BC cell phenotypes was explored.

METHODS

The levels of TMEM92 in BC tissues were evaluated using bioinformatics analysis according to the Oncomine and The Cancer Genome Atlas databases. mRNA levels of TMEM92 in BC cells were measured by qRT-PCR. Kaplan-Meier methods together with log-rank tests were used to conduct survival analysis, and chi-square tests were employed to assess the relationship between TMEM92 levels and clinicopathological parameters. Cox regression analysis was carried out to identify the independent prognosticators. Small interference RNA targeted to TMEM92 and plasmid vectors pcDNA3.1-TMEM92 were respectively used to silence and over-express TMEM92. Protein levels of molecules in this study were tested by western blot. Cell viability, invasiveness and motility of BC cells were determined by cell counting kit 8, clone formation assay and Transwell assay, appropriately.

RESULTS

The data showed that TMEM92 was upregulated in BC tissues or cells in comparison with control. High expression of TMEM92 was notably correlated with stage and metastasis, and led to a poor overall survival. Moreover, cox multivariate analysis model demonstrated that TMEM92 can be seen as an independent prognostic factor. Functional experiments demonstrated that downregulation of TMEM92 showed a significantly inhibitory effect on MDA-MB-231 cell viability, invasiveness and motility, whereas overexpression of TMEM92 could promote the changes of these phenotypes. Furthermore, western blot analysis revealed that depletion of TMEM92 inactivated the epithelial-mesenchymal transition (EMT) process with raised E-cadherin protein levels, while declined N-cadherin, Vimentin and Snail levels. However, enhancement of TMEM92 showed the opposite outcomes on these EMT-related markers.

CONCLUSION

TMEM92 had an independent prognostic value for BC patients, and might act as an oncogene to facilitate tumor cells growth, invasiveness and motility by modulating the EMT relative proteins.

MicroRNA-138 is a Prognostic Biomarker for Triple-Negative Breast Cancer and Promotes Tumorigenesis via TUSC2 repression

Breast cancer manifests as a spectrum of subtypes with distinct molecular signatures, and different responses to treatment. Of these subtypes, triple-negative breast cancer (TNBC) has the worst prognoses and limited therapeutic options. Here we report aberrant expression of microRNA-138 (miR-138) in TNBC. Increased miR-138 expression is highly specific to this subtype, correlates with poor prognosis in patients, and is functionally relevant to cancer progression. Our findings establish miR-138 as a specific diagnostic and prognostic biomarker for TNBC. OncomiR-138 is pro-survival; sequence-specific miR-138 inhibition blocks proliferation, promotes apoptosis and inhibits tumour growth in-vivo. miR-138 directly targets a suite of pro-apoptotic and tumour suppressive genes, including tumour suppressor candidate 2 (TUSC2). miR-138 silences TUSC2 by binding to a unique 5′-UTR target-site, which overlaps with the translation start-site of the transcript. Over-expression of TUSC2 mimics the phenotype of miR-138 knockdown and functional rescue experiments confirm that TUSC2 is a direct downstream target of miR-138. Our report of miR-138 as an oncogenic driver in TNBC, positions it as a viable target for oligonucleotide therapeutics and we envision the potential value of using antimiR-138 as an adjuvant therapy to alleviate this therapeutically intractable cancer.

Application of a Neural Network Whole Transcriptome-Based Pan-Cancer Method for Diagnosis of Primary and Metastatic Cancers

IMPORTANCE

A molecular diagnostic method that incorporates information about the transcriptional status of all genes across multiple tissue types can strengthen confidence in cancer diagnosis.

OBJECTIVE

To determine the practical use of a whole transcriptome-based pan-cancer method in diagnosing primary and metastatic cancers and resolving complex diagnoses.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional diagnostic study assessed Supervised Cancer Origin Prediction Using Expression (SCOPE), a machine learning method using whole-transcriptome RNA sequencing data. Training was performed on publicly available primary cancer data sets, including The Cancer Genome Atlas. Testing was performed retrospectively on untreated primary cancers and treated metastases from volunteer adult patients at BC Cancer in Vancouver, British Columbia, from January 1, 2013, to March 31, 2016, and testing spanned 10 822 samples and 66 output classes representing untreated primary cancers (n = 40) and adjacent normal tissues (n = 26). SCOPE's performance was demonstrated on 211 untreated primary mesothelioma cancers and 201 treatment-resistant metastatic cancers. Finally, SCOPE was used to identify the putative site of origin in 15 cases with initial presentation as cancers with unknown primary of origin.

RESULTS

A total of 10 688 adult patient samples representing 40 untreated primary tumor types and 26 adjacent-normal tissues were used for training. Demographic data were not available for all data sets. Among the training data set, 5157 of 10 244 (50.3%) were male and the mean (SD) age was 58.9 (14.5) years. Testing was performed on 211 patients with untreated primary mesothelioma (173 [82.0%] male; mean [SD] age, 64.5 [11.3] years); 201 patients with treatment-resistant cancers (141 [70.1%] female; mean [SD] age, 55.6 [12.9] years); and 15 patients with cancers of unknown primary of origin; among the treatment-resistant cancers, 168 were metastatic, and 33 were the primary presentation. An accuracy rate of 99% was obtained for primary epithelioid mesotheliomas tested (125 of 126). The remaining 85 mesotheliomas had a mixed etiology (sarcomatoid mesotheliomas) and were correctly identified as a mixture of their primary components, with potential implications in resolving subtypes and incidences of mixed histology. SCOPE achieved an overall mean (SD) accuracy rate of 86% (11%) and F1 score of 0.79 (0.12) on the 201 treatment-resistant cancers and matched 12 of 15 of the putative diagnoses for cancers with indeterminate diagnosis from conventional pathology.

CONCLUSIONS AND RELEVANCE

These results suggest that machine learning approaches incorporating multiple tumor profiles can more accurately identify the cancerous state and discriminate it from normal cells. SCOPE uses the whole transcriptomes from normal and tumor tissues, and results of this study suggest that it performs well for rare cancer types, primary cancers, treatment-resistant metastatic cancers, and cancers of unknown primary of origin. Genes most relevant in SCOPE's decision making were examined, and several are known biological markers of respective cancers. SCOPE may be applied as an orthogonal diagnostic method in cases where the site of origin of a cancer is unknown, or when standard pathology assessment is inconclusive.

Exosomal miRNA profile as complementary tool in the diagnostic and prediction of treatment response in localized breast cancer under neoadjuvant chemotherapy

BACKGROUND

Breast cancer patients under neoadjuvant chemotherapy includes a heterogeneous group of patients who eventually develop distal disease, not detectable by current methods. We propose the use of exosomal miRNAs and circulating tumor cells as diagnostic and predictive biomarkers in these patients.

METHODS

Fifty-three breast cancer women initially diagnosed with localized breast cancer under neoadjuvant chemotherapy were prospectively enrolled in this study. However, six of them were later re-evaluated and diagnosed as metastatic breast cancer patients by PET-CT scan. Additionally, eight healthy donors were included. Circulating tumor cells and serum exosomal miRNAs were isolated from blood samples before and at the middle of neoadjuvant therapy and exosomal miRNA levels analyzed by qPCR.

RESULTS

Before neoadjuvant therapy, exosomal miRNA-21 and 105 expression levels were higher in metastatic versus non-metastatic patients and healthy donors. Likewise, higher levels of miRNA-222 were observed in basal-like (p = 0.037) and in luminal B versus luminal A (p = 0.0145) tumor subtypes. Exosomal miRNA-222 levels correlated with clinical and pathological variables such as progesterone receptor status (p = 0.017) and Ki67 (p = 0.05). During neoadjuvant treatment, exosomal miRNA-21 expression levels directly correlated with tumor size (p = 0.039) and inversely with Ki67 expression (p = 0.031). Finally, higher levels of exosomal miRNA-21, miRNA-222, and miRNA-155 were significantly associated with the presence of circulating tumor cells.

CONCLUSION

Liquid biopsies based on exosomal miRNAs and circulating tumor cells can be a complementary clinical tool for improving breast cancer diagnosis and prognosis.

Reduced RKIP Expression is Associated With Breast Neoplastic Progression and is Correlated With Poor Outcomes and Aberrant Methylation in Breast Carcinoma

Raf kinase inhibitor protein's (RKIP) downregulation can predict poor outcome in patients with various types of malignancy. In this study, we aimed to assess the potential involvement of RKIP in breast carcinogenesis and to evaluate its association with outcome variables and aberrant promoter methylation in breast carcinoma (BC). Tissue microarray sections were immunostained for RKIP in 26 normal breasts, 25 usual ductal hyperplasia, 76 ductal carcinoma in situ, and 198 BC specimens. The methylation status of RKIP was also determined in BC. In addition, the mRNA and protein level of RKIP was analyzed in 8 pairs of BC tissues and surrounding normal tissues by quantitative real-time polymerase chain reaction and Western blot analysis, respectively. RKIP mRNA and protein expression was significantly downregulated in BC tissues compared with the surrounding normal tissues (P<0.05 and P<0.01, respectively). Reduced RKIP expression seemed to increase progressively from normal breast to BC (P<0.001). Reduced RKIP expression was significantly associated with metastatic relapse (P<0.001) and was identified as an independent adverse prognostic indicator for disease-free survival (P=0.003). Reduced RKIP expression in BC was significantly correlated with its aberrant promoter methylation (P<0.05). In conclusion, downregulation of RKIP plays an important role in the breast neoplastic progression and correlates with poor prognosis in patients with BC. Aberrant RKIP methylation is one of the mechanisms that lead to downregulation of RKIP in BC.

Prediction Potential of Serum miR-155 and miR-24 for Relapsing Early Breast Cancer

Oncogenic microRNAs (oncomiRs) accumulate in serum due to their increased stability and thus serve as biomarkers in breast cancer (BC) pathogenesis. Four oncogenic microRNAs (miR-155, miR-19a, miR-181b, and miR-24) and one tumor suppressor microRNA (let-7a) were shown to differentiate between high- and low-risk early breast cancer (EBC) and reflect the surgical tumor removal and adjuvant therapy. Here we applied the longitudinal multivariate data analyses to stochastically model the serum levels of each of the oncomiRs using the RT-PCR measurements in the EBC patients (N = 133) that were followed up 4 years after diagnosis. This study identifies that two of the studied oncomiRs, miR-155 and miR-24, are highly predictive of EBC relapse. Furthermore, combining the oncomiR level with Ki-67 expression further specifies the relapse probability. Our data move further the notion that oncomiRs in serum enable not only monitoring of EBC but also are a very useful tool for predicting relapse independently of any other currently analyzed characteristics in EBC patients. Our approach can be translated into medical practice to estimate individual relapse risk of EBC patients.

Identification of microRNA biomarkers in the blood of breast cancer patients based on microRNA profiling

Accumulating evidence indicates that human circulating microRNAs (miRNAs) could serve as diagnostic and prognostic biomarkers in various cancers. We aimed to explore novel miRNA biomarkers in the blood of breast cancer patients based on miRNA profiling. A miRCURY™ LNA Array was used to identify differentially altered miRNAs in the whole blood of breast cancer patients (n=6) and healthy controls (n=6). Levels of candidate miRNAs were quantified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in whole blood specimens of 15 breast cancer patients and 13 age-matched healthy control individuals. The miRWalk database was used to predict miRNA targets and the DAVID tool was used to identify significant enrichment pathways. A total of 171 differentially expressed miRNAs were identified by microarray, including 169 upregulated and 2 downregulated miRNAs in breast cancer. Five upregulated miRNAs (miR-30b-5p, miR-96-5p, miR-182-5p, miR-374b-5p, and miR-942-5p) were confirmed by qRT-PCR. The areas under the receiver operating characteristic curve of miR-30b-5p, miR-96-5p, miR-182-5p, miR-374b-5p, and miR-942-5p were 0.9333, 0.7692, 0.7590, 0.8256, and 0.8128, respectively. Importantly, upregulation of these five miRNAs was observed even in patients with very early-stage breast cancer. A total of 855 genes were predicted to be targeted by the five miRNAs, and the one cut domain family member 2 gene (ONECUT2) was a shared target of the five miRNAs. Analysis of publicly available data revealed that these dysregulated miRNAs and the target genes were associated with the survival of breast cancer patients. Furthermore, the five miRNAs were significantly enriched in numerous cancer-related pathways, including "MicroRNAs in cancer", "Pathways in cancer", "FoxO signaling pathway", "Ras signaling pathway", "Rap1 signaling pathway", "MAPK signaling pathway", and "PI3K-Akt signaling pathway". Our data support the potential of the five identified miRNAs as novel biomarkers for the detection of breast cancer, and indicate that they may be involved in breast cancer development and progression.

Pattern recognition for predictive, preventive, and personalized medicine in cancer

Predictive, preventive, and personalized medicine (PPPM) is the hot spot and future direction in the field of cancer. Cancer is a complex, whole-body disease that involved multi-factors, multi-processes, and multi-consequences. A series of molecular alterations at different levels of genes (genome), RNAs (transcriptome), proteins (proteome), peptides (peptidome), metabolites (metabolome), and imaging characteristics (radiome) that resulted from exogenous and endogenous carcinogens are involved in tumorigenesis and mutually associate and function in a network system, thus determines the difficulty in the use of a single molecule as biomarker for personalized prediction, prevention, diagnosis, and treatment for cancer. A key molecule-panel is necessary for accurate PPPM practice. Pattern recognition is an effective methodology to discover key molecule-panel for cancer. The modern omics, computation biology, and systems biology technologies lead to the possibility in recognizing really reliable molecular pattern for PPPM practice in cancer. The present article reviewed the pathophysiological basis, methodology, and perspective usages of pattern recognition for PPPM in cancer so that our previous opinion on multi-parameter strategies for PPPM in cancer is translated into real research and development of PPPM or precision medicine (PM) in cancer.

A novel semi-robotized device for high-precision 18F-FDG-guided breast cancer biopsy

PURPOSE

To assess the 3D geometric sampling accuracy of a new PET-guided system for breast cancer biopsy (BCB) from areas within the tumour with high ¹⁸F-FDG uptake.

MATERIALS AND METHODS

In the context of the European Union project MammoCare, a prototype semi-robotic stereotactic prototype BCB-device was incorporated into a dedicated high resolution PET-detector for breast imaging. The system consists of 2 stacked rings, each containing 12 plane detectors, forming a dodecagon with a 186mm aperture for 3D reconstruction (1mm³ voxel). A vacuum-assisted biopsy needle attached to a robot-controlled arm was used. To test the accuracy of needle placement, the needle tip was labelled with ¹⁸F-FDG and positioned at 78 target coordinates distributed over a 35mm×24mm×28mm volume within the PET-detector field-of-view. At each position images were acquired from which the needle positioning accuracy was calculated. Additionally, phantom-based biopsy proofs, as well as MammoCare images of 5 breast cancer patients, were evaluated for the 3D automated locating of ¹⁸F-FDG uptake areas within the tumour.

RESULTS

Needle positioning tests revealed an average accuracy of 0.5mm (range 0-1mm), 0.6mm (range 0-2mm), and 0.4mm (range 0-2mm) for the x/y/z-axes, respectively. Furthermore, the MammoCare system was able to visualize and locate small (<10mm) regions with high ¹⁸F-FDG uptake within the tumour suitable for PET-guided biopsy after being located by the 3D automated application.

CONCLUSIONS

Accuracy testing demonstrated high-precision of this semi-automatic 3D PET-guided system for breast cancer core needle biopsy. Its clinical feasibility evaluation in breast cancer patients scheduled for neo-adjuvant chemotherapy will follow.

MicroRNAs in breast cancer: oncogene and tumor suppressors with clinical potential

MicroRNAs (miRs) are small single-stranded RNA molecules, which function as key negative regulators of post-transcriptional modulation in almost all biological processes. Abnormal expression of microRNAs has been observed in various types of cancer including breast cancer. Great efforts have been made to identify an association between microRNA expression profiles and breast cancer, and to understand the functional role and molecular mechanism of aberrant-expressed microRNAs. As research progressed, 'oncogenic microRNAs' and 'tumor suppressive microRNAs' became a focus of interest. The potential of candidate microRNAs from both intercellular (tissue) and extracellular (serum) sources for clinical diagnosis and prognosis was revealed, and treatments involving microRNA achieved some amazing curative effects in cancer disease models. In this review, advances from the most recent studies of microRNAs in one of the most common cancers, breast cancer, are highlighted, especially the functions of specifically selected microRNAs. We also assess the potential value of these microRNAs as diagnostic and prognostic markers, and discuss the possible development of microRNA-based therapies.

Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential

BACKGROUND

Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics.

RESULTS

These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses.

CONCLUSION

This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches.

Rapid and fully automated bacterial pathogen detection on a centrifugal-microfluidic LabDisk using highly sensitive nested PCR with integrated sample preparation

Diagnosis of infectious diseases suffers from long turnaround times for gold standard culture-based identification of bacterial pathogens, therefore impeding timely specific antimicrobial treatment based on laboratory evidence. Rapid molecular diagnostics-based technologies enable detection of microorganisms within hours however cumbersome workflows and complex equipment still prevent their widespread use in the routine clinical microbiology setting. We developed a centrifugal-microfluidic "LabDisk" system for rapid and highly-sensitive pathogen detection on a point-of-care analyser. The unit-use LabDisk with pre-stored reagents features fully automated and integrated DNA extraction, consensus multiplex PCR pre-amplification and geometrically-multiplexed species-specific real-time PCR. Processing merely requires loading of the sample and DNA extraction reagents with minimal hands-on time of approximately 5 min. We demonstrate detection of as few as 3 colony-forming-units (cfu) of Staphylococcus warneri, 200 cfu of Streptococcus agalactiae, 5 cfu of Escherichia coli and 2 cfu of Haemophilus influenzae in a 200 μL serum sample. The turnaround time of the complete analysis from "sample-to-result" was 3 h and 45 min. The LabDisk consequently provides an easy-to-use molecular diagnostic platform for rapid and highly-sensitive detection of bacterial pathogens without requiring major hands-on time and complex laboratory instrumentation.

Involvement of microRNA-198 overexpression in the poor prognosis of esophageal cancer

OBJECTIVE

This study aimed to investigate whether the miR-198 expression level is related to clinicopathological factors and prognosis of esophageal cancer.

METHODS

MicroRNA was extracted from esophageal cancer patients who underwent surgery for assessment using the Taqman@ MicroRNA assay. The correlation between miR-198 expression and clinicopathological features was analyzed, and the significance of miR-198 as a prognostic factor and its relationship with survival was determined.

RESULTS

MicroRNA-198 (miR-198) expression was higher in patients with poor prognosis than those with good prognosis (P < 0.05). Kaplan-Meier analysis results showed that the miR-198 expression level had a significant correlation with survival time (P = 0.030) and that patients with a higher expression of miR-198 had a shorter survival time. Cox multi-factor model analysis showed that patient prognosis (P = 0.014), tumor length (P = 0.040) and expression (P = 0.012), and survival time had a significant correlation; the corresponding risks were 7.268, 1.246, and 3.524, respectively.

CONCLUSION

miR- 198 overexpression is involved in the poor prognosis of esophageal cancer and can be used as a biomarker for selection of cases requiring especial attention.

Circulating miR-148b and miR-133a as biomarkers for breast cancer detection

Circulating microRNAs have drawn a great deal of attention as promising novel biomarkers for breast cancer. However, to date, the results are mixed. Here, we performed a three-stage microRNA analysis using plasma samples from breast cancer patients and healthy controls, with efforts taken to address several pitfalls in detection techniques and study design observed in previous studies. In the discovery phase with 122 Caucasian study subjects, we identified 43 microRNAs differentially expressed between breast cancer cases and healthy controls. When those microRNAs were compared with published data from other studies, we identified three microRNAs, including miR-148b, miR-133a and miR-409-3p, whose plasma levels were significantly higher in breast cancer cases than healthy controls and were also significant in previous independent studies. In the validation phase with 50 breast cancer cases and 50 healthy controls, we validated the associations with breast cancer detection for miR-148b and miR-133a (P = 1.5×10-6 and 1.3×10-10, respectively). In the in-vitro study phase, we found that both miR-148b and miR-133a were secreted from breast cancer cell lines, showing their secretory potential and possible tumor origin. Thus, our data suggest that both miR-148b and miR-133a have potential use as biomarkers for breast cancer detection.

MicroRNAs in the diagnosis and prognosis of breast cancer and their therapeutic potential (review)

MicroRNAs (miRNAs) are non-coding single-stranded RNAs in eukaryotes and are involved in the regulation of the post-transcriptional expression of specific genes. Studies have demonstrated that miRNAs play important roles in regulating diverse physiological events such as cell proliferation, differentiation and embryo development. In recent decades, considerable attention has been given to the relationship between miRNA and the pathology of cancers, particularly breast cancer. A large number of miRNAs have been shown to be involved in the pathophysiology of breast cancer. Studies have revealed that some miRNAs might regulate the oncogenesis and growth of breast cancer by acting on breast tumor-initiating cells or other downstream targets. Studies have also demonstrated that some miRNAs act as suppressors of metastasis or promoters of breast cancer. Additionally, certain miRNAs are involved in cancer tissue angiogenesis (one of the most important mechanisms of tumor growth and metastasis). Clinical evidence indicates that some miRNAs can be used as diagnostic and prognostic biomarkers for breast cancer due to their significantly increased or decreased expression in cancer tissue. Moreover, certain miRNAs may have therapeutic potential for targeting ER-α/HER, breast tumor-initiating cells and metastasis as well as multidrug resistance. In this review, we discuss the relationship between miRNAs and the pathogenesis of breast cancer as well as the progress of current research on the miRNA-specific diagnosis, prognosis and treatment of breast cancer.

Steroid receptor coactivator-1: a versatile regulator and promising therapeutic target for breast cancer

Breast cancer is the leading cause of cancer death for women worldwide. Various therapeutic approaches have been proposed, among which endocrine therapy has recently become popular due to the high sensitivity of breast tissues to steroids such as estrogens and progesterone. The underlying mechanisms of steroid regulation in breast cancer cell proliferation, invasiveness, metastasis and endocrine resistance, however, remain largely unknown. Steroid receptor coactivator-1 (SRC-1) has attracted much attention because it is an important co-regulator and plays a pivotal role in modulating the transcriptional activities of steroid nuclear receptors. Accumulated research has established a strong correlation between SRC-1 and the pathological progression or disease-related features of breast cancer, which supports its potential as a target for specific therapeutic intervention in the clinical management of breast cancer. In addition, a diverse group of downstream molecules have also been shown to participate in various functional pathways related to SRC-1-associated regulation of breast cancer. These downstream molecules are also considered promising therapeutic targets, providing additional options for targeted treatments. In this review, the expression of SRC-1 in breast cancer and the close relationships between SRC-1 and the cell proliferation, invasiveness, metastasis and endocrine resistance of breast cancer will be discussed, followed by a brief summary of its putative functional mechanisms with an emphasis on the potential therapeutic role of SRC-1.

Regulation of breast cancer and bone metastasis by microRNAs

Breast cancer progression including bone metastasis is a complex process involving numerous changes in gene expression and function. MicroRNAs (miRNAs) are small endogenous noncoding RNAs that regulate gene expression by targeting protein-coding mRNAs posttranscriptionally, often affecting a number of gene targets simultaneously. Alteration in expression of miRNAs is common in human breast cancer, possessing with either oncogenic or tumor suppressive activity. The expression and the functional role of several miRNAs (miR-206, miR-31, miR-27a/b, miR-21, miR-92a, miR-205, miR-125a/b, miR-10b, miR-155, miR-146a/b, miR-335, miR-204, miR-211, miR-7, miR-22, miR-126, and miR-17) in breast cancer has been identified. In this review we summarize the experimentally validated targets of up- and downregulated miRNAs and their regulation in breast cancer and bone metastasis for diagnostic and therapeutic purposes.

Improving breast cancer survival analysis through competition-based multidimensional modeling

Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

MicroRNA-mediated posttranscriptional mechanisms of gene expression in proliferating and quiescent cancer cells

MicroRNAs are small non-coding RNA regulators of gene expression that play important roles in critical biological processes, including cell division, self-renewal and cell state maintenance. Their deregulation leads to extensive clinical consequences in tumorigenesis. Cancers demonstrate heterogeneity in their cell states implicated in their resistance and resurgence. Apart from proliferating cells, cancers harbor a small proportion of assorted quiescent cells that resist conventional therapeutics and contribute to cancer recurrence. MicroRNA expression, targets, microRNPs (microRNA-protein complexes) and their functions have been demonstrated to be regulated in distinct tumor cell states and as an adaptive response to stress signals in tumor-unfavorable environments. In turn, altered microRNPs and their modified post-transcriptional mechanisms of gene expression may contribute to tumor resistance and influence tumor progression. An understanding of distinct microRNA mechanisms in cancer cells would provide extensive insights into the versatile roles of microRNAs in the perpetuation of tumors and indicate potential therapeutic avenues.

RNA signatures allow rapid identification of pathogens and antibiotic susceptibilities

With rising rates of drug-resistant infections, there is a need for diagnostic methods that rapidly can detect the presence of pathogens and reveal their susceptibility to antibiotics. Here we propose an approach to diagnosing the presence and drug-susceptibility of infectious diseases based on direct detection of RNA from clinical samples. We demonstrate that species-specific RNA signatures can be used to identify a broad spectrum of infectious agents, including bacteria, viruses, yeast, and parasites. Moreover, we show that the behavior of a small set of bacterial transcripts after a brief antibiotic pulse can rapidly differentiate drug-susceptible and -resistant organisms and that these measurements can be made directly from clinical materials. Thus, transcriptional signatures could form the basis of a uniform diagnostic platform applicable across a broad range of infectious agents.

Prognostic Implications of MicroRNA-21 Overexpression in Invasive Ductal Carcinomas of the Breast

PURPOSE

Among more than 500 microRNAs, microRNA-21 (miR-21) is known to act as an oncogene. The aim of this study was to investigate the significance of miR-21 expression level in relation with clinicopathological factors and prognosis in breast cancer.

METHODS

MicroRNA was extracted from cancer and normal breast tissue of 109 breast cancer patients who underwent surgery from 2002 to 2004 using the Taqman® MicroRNA Assay. The correlation between miR-21 expression and clinicopathologic features was analyzed and the significance of miR-21 as a prognostic factor and its relationship with survival was determined.

RESULTS

MiR-21 expression was higher in cancer tissues than in normal tissues (p<0.0001). High miR-21 expression was associated with mastectomy, larger tumor size, higher stage, higher grade, estrogen receptor (ER) negative, human epidermal growth factor receptor 2 (HER2) positive, HER2 positive breast cancer subtype, high Ki-67 expression, and death. On multivariate analysis, prognostic factors for overall survival were ER and miR-21. High miR-21 expression was significantly related to lower overall survival (p=0.031).

CONCLUSION

This study supports the role of miR-21 as an oncogene and a biomarker for breast cancer with its high expression in cancer tissues and its relationship with other prognostic factors and survival.

Breast cancer genomics: normal tissue and cancer markers

Mammography is a powerful screening tool for early detection of breast cancer, but it has limitations in terms of both specificity and sensitivity. Imaging tools such as MRI that complement mammography are too costly to serve as first-line screens. Recently, progress has been made on blood markers, particularly microRNAs and proteins. There are new methods for protein marker discovery directly in blood, but they are limited in the number of patients that can be examined. An alternative is to discover markers as transcripts in tissues, followed by development of blood protein tests for those that perform best. To identify genes that are overexpressed in malignancy it is paramount to include normal control tissues from healthy individuals. Here we report the identification of potential breast cancer markers, including some that are overexpressed in aggressive disease.

MicroRNAs as biomarkers in rheumatic diseases

MicroRNAs (miRNAs) are endogenous, noncoding, single-stranded RNAs of 19-25 nucleotides in length. They regulate gene expression and are important in a wide range of physiological and pathological processes. MiRNAs are attractive as potential biomarkers because their expression pattern is reflective of underlying pathophysiologic processes and they are specific to various disease states. Moreover, miRNAs can be detected in a variety of sources, including tissue, blood and body fluids; they are reasonably stable and appear to be resistant to differences in sample handling, which increases their appeal as practical biomarkers. The clinical utility of miRNAs as diagnostic or prognostic biomarkers has been demonstrated in various malignancies and a few nonmalignant diseases. There is accumulating evidence that miRNAs have an important role in systemic rheumatic diseases and that various diseases or different stages of the same disease are associated with distinct miRNA expression profiles. Preliminary data suggest that miRNAs are promising as candidate biomarkers of diagnosis, prognosis, disease activity and severity in autoimmune diseases. MiRNAs identified as potential biomarkers in pilot studies should be validated in larger studies designed specifically for biomarker validation.