Implementing Next-Generation Sequencing Process Changes to Increase Capacity and Improve Timeliness of Molecular Biomarker Profiling for Lung Cancer Patients.

BACKGROUND: Faced with expansion of molecular tumor biomarker profiling, the molecular genetics laboratory at Kingston Health Science Centre experienced significant pressures to maintain the provincially mandated 2-week turnaround time (TAT) for lung cancer (LC) patients. We used quality improvement methodology to identify opportunities for improved efficiencies and report the impact of the initiative. METHODS: We set a target of reducing average TAT from accessioning to clinical molecular lab report for LC patients. Process measures included percentage of cases reaching TAT within target and number of cases. We developed a value stream map and used lean methodology to identify baseline inefficiencies. Plan-Do-Study-Act cycles were implemented to streamline, standardize, and automate laboratory workflows. Statistical process control (SPC) charts assessed for significance by special cause variation. RESULTS: A total of 257 LC cases were included (39 baseline January-May 2021; 218 post-expansion of testing June 2021). The average time for baseline TAT was 12.8 days, peaking at 23.4 days after expansion of testing, and improved to 13.9 days following improvement interventions, demonstrating statistical significance by special cause variation (nonrandom variation) on SPC charts. CONCLUSIONS: The implementation of standardized manual and automated laboratory processes improved timeliness of biomarker reporting despite the increasing volume of testing at our center.

Optimizing the delivery of genetic and advanced diagnostic testing in the province of Ontario: challenges and implications for laboratory technology assessment and management in decentralized healthcare systems.

AIMS: The Canadian province of Ontario provides full coverage for its residents (pop.14.8 M) for hospital-based diagnostic testing. Historical governance of the healthcare system and a legacy scheme of health technology assessment (HTA) and financing has led to a suboptimal approach of adopting advanced diagnostic technology (i.e. protein expression, cytogenetic, and molecular/genetic) for guiding therapeutic decisions. The aim of this research is to explore systemic barriers and provide guidance to improve patient and care provider experiences by reducing delays and inequity of access to testing, while benefitting laboratory innovators and maximizing system efficiency. MATERIALS AND METHODS: A mixed-methods approach including literature review, semi-structured interviews, and a multi-stakeholder forum involving patient representatives (n = 1), laboratory leaders (n = 6), physicians (n = 5), Ministry personnel (n = 4), administrators (n = 3), extra-provincial experts, and researchers (n = 7), as well as pharmaceutical (n = 5) and diagnostic companies (n = 2). The forum considered evidence of good practices in adoption, implementation, and financing laboratory services and identified barriers as well as feasible options for improving advanced diagnostic testing in Ontario. RESULTS: Overarching challenges identified included: barriers to define what is needed; need for a clear approach to adoption; and the need for more oversight and coordination. Recommendations to address these included a shift to an anticipatory system of test adoption, creating a fit-for-purpose system of health technology management that consolidates existing evaluation processes, and modernizing the governance and financing of testing so that it is managed at a care-delivery level. CONCLUSIONS: The proposals for change in Ontario highlight the role that HTA, governance, and financing of health technology play along the continuum of a health technology life cycle within a healthcare system where decision-making is highly decentralized. Resource availability and capacity were not a concern - instead, solutions require higher levels of coordination and system integration along with innovative approaches to HTA.

BRCA1 Variant Assessment Using a Simple Analytic Assay.

BACKGROUND: We previously developed a biological assay to accurately predict BRCA1 (BRCA1 DNA repair associated) mutation status, based on gene expression profiles of Epstein-Barr virus-transformed lymphoblastoid cell lines. The original work was done using whole genome expression microarrays, and nearest shrunken centroids analysis. While these approaches are appropriate for model building, they are difficult to implement clinically, where more targeted testing and analysis are required for time and cost savings. METHODS: Here, we describe adaptation of the original predictor to use the NanoString nCounter platform for testing, with analysis based on the k-top scoring pairs (k-TSP) method. RESULTS: Assessing gene expression using the nCounter platform on a set of lymphoblastoid cell lines yielded 93.8% agreement with the microarray-derived data, and 87.5% overall correct classification of BRCA1 carriers and controls. Using the original gene expression microarray data used to develop our predictor with nearest shrunken centroids, we rebuilt a classifier based on the k-TSP method. This classifier relies on the relative expression of 10 pairs of genes, compared to the original 43 identified by nearest shrunken centroids (NSC), and was 96.2% concordant with the original training set prediction, with a 94.3% overall correct classification of BRCA1 carriers and controls. CONCLUSIONS: The k-TSP classifier was shown to accurately predict BRCA1 status using data generated on the nCounter platform and is feasible for initiating a clinical validation.

Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository.

BACKGROUND: This study aimed to identify and resolve discordant variant interpretations across clinical molecular genetic laboratories through the Canadian Open Genetics Repository (COGR), an online collaborative effort for variant sharing and interpretation. METHODS: Laboratories uploaded variant data to the Franklin Genoox platform. Reports were issued to each laboratory, summarising variants where conflicting classifications with another laboratory were noted. Laboratories could then reassess variants to resolve discordances. Discordance was calculated using a five-tier model (pathogenic (P), likely pathogenic (LP), variant of uncertain significance (VUS), likely benign (LB), benign (B)), a three-tier model (LP/P are positive, VUS are inconclusive, LB/B are negative) and a two-tier model (LP/P are clinically actionable, VUS/LB/B are not). We compared the COGR classifications to automated classifications generated by Franklin. RESULTS: Twelve laboratories submitted classifications for 44 510 unique variants. 2419 variants (5.4%) were classified by two or more laboratories. From baseline to after reassessment, the number of discordant variants decreased from 833 (34.4% of variants reported by two or more laboratories) to 723 (29.9%) based on the five-tier model, 403 (16.7%) to 279 (11.5%) based on the three-tier model and 77 (3.2%) to 37 (1.5%) based on the two-tier model. Compared with the COGR classification, the automated Franklin classifications had 94.5% sensitivity and 96.6% specificity for identifying actionable (P or LP) variants. CONCLUSIONS: The COGR provides a standardised mechanism for laboratories to identify discordant variant interpretations and reduce discordance in genetic test result delivery. Such quality assurance programmes are important as genetic testing is implemented more widely in clinical care.

Validation, Implementation, and Clinical Impact of the Oncomine Myeloid Targeted-Amplicon DNA and RNA Ion Semiconductor Sequencing Assay.

The identification of clinically significant genes recurrently mutated in myeloid malignancies necessitates expanding diagnostic testing with higher throughput, such as targeted next-generation sequencing. We present validation of the Thermo Fisher Oncomine Myeloid Next-Generation Sequencing Panel (OMP), targeting 40 genes and 29 fusion drivers recurrently mutated in myeloid malignancies. The study includes data from a sample exchange between two Canadian hospitals demonstrating high concordance for detection of DNA and RNA aberrations. Clinical validation demonstrates high accuracy, sensitivity, and specificity of the OMP, with a lower limit of detection of 5% for single-nucleotide variants and 10% for insertions/deletions. Prospective sequencing was performed for 187 samples from 168 unique patients presenting with suspected or confirmed myeloid malignancy and other hematological conditions to assess clinical impact of identifying variants. Of detected variants, 48% facilitated or clarified diagnoses, 29% affected prognoses, and 25% had the potential to influence clinical management. Of note, OMP was essential to identifying patients with premalignant clonal states likely contributing to cytopenias. We also found that the detection of even a single variant by the OMP assay, versus 0 variants, was predictive of overall survival, independent of age, sex, or diagnosis (P = 0.03). This study demonstrates that molecular profiling of myeloid malignancies with the OMP represents a promising strategy to advance molecular diagnostics.

Simultaneous detection of lung fusions using a multiplex RT-PCR next generation sequencing-based approach: a multi-institutional research study.

BACKGROUND: Gene fusion events resulting from chromosomal rearrangements play an important role in initiation of lung adenocarcinoma. The recent association of four oncogenic driver genes, ALK, ROS1, RET, and NTRK1, as lung tumor predictive biomarkers has increased the need for development of up-to-date technologies for detection of these biomarkers in limited amounts of material. METHODS: We describe here a multi-institutional study using the Ion AmpliSeq™ RNA Fusion Lung Cancer Research Panel to interrogate previously characterized lung tumor samples. RESULTS: Reproducibility between laboratories using diluted fusion-positive cell lines was 100%. A cohort of lung clinical research samples from different origins (tissue biopsies, tissue resections, lymph nodes and pleural fluid samples) were used to evaluate the panel. We observed 97% concordance for ALK (28/30 positive; 71/70 negative samples), 95% for ROS1 (3/4 positive; 19/18 negative samples), and 93% for RET (2/1 positive; 13/14 negative samples) between the AmpliSeq assay and other methodologies. CONCLUSION: This methodology enables simultaneous detection of multiple ALK, ROS1, RET, and NTRK1 gene fusion transcripts in a single panel, enhanced by an integrated analysis solution. The assay performs well on limited amounts of input RNA (10 ng) and offers an integrated single assay solution for detection of actionable fusions in lung adenocarcinoma, with potential savings in both cost and turn-around-time compared to the combination of all four assays by other methods.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

BACKGROUND: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. METHODS: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. DISCUSSION: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.

Roles for miR-375 in Neuroendocrine Differentiation and Tumor Suppression via Notch Pathway Suppression in Merkel Cell Carcinoma.

Dysfunction of key miRNA pathways regulating basic cellular processes is a common driver of many cancers. However, the biological roles and/or clinical applications of such pathways in Merkel cell carcinoma (MCC), a rare but lethal cutaneous neuroendocrine (NE) malignancy, have yet to be determined. Previous work has established that miR-375 is highly expressed in MCC tumors, but its biological role in MCC remains unknown. Herein, we show that elevated miR-375 expression is a specific feature of well-differentiated MCC cell lines that express NE markers. In contrast, miR-375 is strikingly down-regulated in highly aggressive, undifferentiated MCC cell lines. Enforced miR-375 expression in these cells induced NE differentiation, and opposed cancer cell viability, migration, invasion, and survival, pointing to tumor-suppressive roles for miR-375. Mechanistically, miR-375-driven phenotypes were caused by the direct post-transcriptional repression of multiple Notch pathway proteins (Notch2 and RBPJ) linked to cancer and regulation of cell fate. Thus, we detail a novel molecular axis linking tumor-suppressive miR-375 and Notch with NE differentiation and cancer cell behavior in MCC. Our findings identify miR-375 as a putative regulator of NE differentiation, provide insight into the cell of origin of MCC, and suggest that miR-375 silencing may promote aggressive cancer cell behavior through Notch disinhibition.

ATM gene mutations in sporadic breast cancer patients from Brazil.

PURPOSE: The Ataxia-telangiectasia mutated (ATM) gene encodes a multifunctional kinase, which is linked to important cellular functions. Women heterozygous for ATM mutations have an estimated relative risk of developing breast cancer of 3.8. However, the pattern of ATM mutations and their role in breast cancer etiology has been controversial and remains unclear. In the present study, we investigated the frequency and spectrum of ATM mutations in a series of sporadic breast cancers and controls from the Brazilian population. METHODS: Using PCR-Single Strand Conformation Polymorphism (SSCP) analysis and direct DNA sequencing, we screened a panel of 100 consecutive, unselected sporadic breast tumors and 100 matched controls for all 62 coding exons and flanking introns of the ATM gene. RESULTS: Several polymorphisms were detected in 12 of the 62 coding exons of the ATM gene. These polymorphisms were observed in both breast cancer patients and the control population. In addition, evidence of potential ATM mutations was observed in 7 of the 100 breast cancer cases analyzed. These potential mutations included six missense variants found in exon 13 (p.L546V), exon 14 (p.P604S), exon 20 (p.T935R), exon 42 (p.G2023R), exon 49 (p.L2307F), and exon 50 (p.L2332P) and one nonsense mutation in exon 39 (p.R1882X), which was predicted to generate a truncated protein. CONCLUSIONS: Our results corroborate the hypothesis that sporadic breast tumors may occur in carriers of low penetrance ATM mutant alleles and these mutations confer different levels of breast cancer risk.

BRCA1 haploinsufficiency leads to altered expression of genes involved in cellular proliferation and development.

The assessment of BRCA1 and BRCA2 coding sequences to identify pathogenic mutations associated with inherited breast/ovarian cancer syndrome has provided a method to identify high-risk individuals, allowing them to seek preventative treatments and strategies. However, the current test is expensive, and cannot differentiate between pathogenic variants and those that may be benign. Focusing only on one of the two BRCA partners, we have developed a biological assay for haploinsufficiency of BRCA1. Using a series of EBV-transformed cell lines, we explored gene expression patterns in cells that were BRCA1 wildtype compared to those that carried (heterozygous) BRCA1 pathogenic mutations. We identified a subset of 43 genes whose combined expression pattern is a sensitive predictor of BRCA1 status. The gene set was disproportionately made up of genes involved in cellular differentiation, lending credence to the hypothesis that single copy loss of BRCA1 function may impact differentiation, rendering cells more susceptible to undergoing malignant processes.

Inactivation of the CDKN2A tumor-suppressor gene by deletion or methylation is common at diagnosis in follicular lymphoma and associated with poor clinical outcome.

PURPOSE: Follicular lymphoma, the most common indolent lymphoma, is clinically heterogeneous. CDKN2A encodes the tumor suppressors p16(INK4a) and p14(ARF) and frequently suffers deleterious alterations in cancer. We investigated the hypothesis that deletion or hypermethylation of CDKN2A might identify follicular lymphoma cases with distinct clinical or pathologic features potentially amenable to tailored clinical management. EXPERIMENTAL DESIGN: Deletion of CDKN2A was detected in pretreatment biopsy specimens using a single nucleotide polymorphism-based approach or endpoint PCR, and methylation of CpG elements in CDKN2A was quantified by methylation-specific PCR. Correlations between CDKN2A status and pathologic or clinical characteristics, including overall survival (OS), were investigated in 106 cases using standard statistical methods. RESULTS: Deletion of CDKN2A was detected in 9 of 111 samples (8%) and methylation was detectable in 22 of 113 (19%). CDKN2A was either deleted or methylated in 29 of 106 cases (27%) and this status was associated with inferior OS especially among patients treated with rituximab (P = 0.004). CDKN2A deletion or methylation was associated with more advanced age (P = 0.012) and normal hemoglobin (P = 0.05) but not with sex, FLIPI score, ECOG stage, LDH, performance status, number of involved nodal sites, B symptoms, histologic grade, the presence of a component of diffuse large B-cell lymphoma, proliferation index, or other pathologic factors. CONCLUSIONS: Our results show that deletion or methylation of CDKN2A is relatively common in pretreatment follicular lymphoma biopsy specimens and defines a group of cases associated with reduced survival in the rituximab era presumably on the basis of more aggressive disease biology.

Exploring high dimensional data with Butterfly: a novel classification algorithm based on discrete dynamical systems.

MOTIVATION: We introduce a novel method for visualizing high dimensional data via a discrete dynamical system. This method provides a 2D representation of the relationship between subjects according to a set of variables without geometric projections, transformed axes or principal components. The algorithm exploits a memory-type mechanism inherent in a certain class of discrete dynamical systems collectively referred to as the chaos game that are closely related to iterative function systems. The goal of the algorithm was to create a human readable representation of high dimensional patient data that was capable of detecting unrevealed subclusters of patients from within anticipated classifications. This provides a mechanism to further pursue a more personalized exploration of pathology when used with medical data. For clustering and classification protocols, the dynamical system portion of the algorithm is designed to come after some feature selection filter and before some model evaluation (e.g. clustering accuracy) protocol. In the version given here, a univariate features selection step is performed (in practice more complex feature selection methods are used), a discrete dynamical system is driven by this reduced set of variables (which results in a set of 2D cluster models), these models are evaluated for their accuracy (according to a user-defined binary classification) and finally a visual representation of the top classification models are returned. Thus, in addition to the visualization component, this methodology can be used for both supervised and unsupervised machine learning as the top performing models are returned in the protocol we describe here. RESULTS: Butterfly, the algorithm we introduce and provide working code for, uses a discrete dynamical system to classify high dimensional data and provide a 2D representation of the relationship between subjects. We report results on three datasets (two in the article; one in the appendix) including a public lung cancer dataset that comes along with the included Butterfly R package. In the included R script, a univariate feature selection method is used for the dimension reduction step, but in the future we wish to use a more powerful multivariate feature reduction method based on neural networks (Kriesel, 2007). AVAILABILITY AND IMPLEMENTATION: A script written in R (designed to run on R studio) accompanies this article that implements this algorithm and is available at http://butterflygeraci.codeplex.com/. For details on the R package or for help installing the software refer to the accompanying document, Supporting Material and Appendix.

Identification of the IGF1/PI3K/NF κB/ERK gene signalling networks associated with chemotherapy resistance and treatment response in high-grade serous epithelial ovarian cancer.

BACKGROUND: Resistance to platinum-based chemotherapy remains a major impediment in the treatment of serous epithelial ovarian cancer. The objective of this study was to use gene expression profiling to delineate major deregulated pathways and biomarkers associated with the development of intrinsic chemotherapy resistance upon exposure to standard first-line therapy for ovarian cancer. METHODS: The study cohort comprised 28 patients divided into two groups based on their varying sensitivity to first-line chemotherapy using progression free survival (PFS) as a surrogate of response. All 28 patients had advanced stage, high-grade serous ovarian cancer, and were treated with standard platinum-based chemotherapy. Twelve patient tumours demonstrating relative resistance to platinum chemotherapy corresponding to shorter PFS (< eight months) were compared to sixteen tumours from platinum-sensitive patients (PFS > eighteen months). Whole transcriptome profiling was performed using an Affymetrix high-resolution microarray platform to permit global comparisons of gene expression profiles between tumours from the resistant group and the sensitive group. RESULTS: Microarray data analysis revealed a set of 204 discriminating genes possessing expression levels which could influence differential chemotherapy response between the two groups. Robust statistical testing was then performed which eliminated a dependence on the normalization algorithm employed, producing a restricted list of differentially regulated genes, and which found IGF1 to be the most strongly differentially expressed gene. Pathway analysis, based on the list of 204 genes, revealed enrichment in genes primarily involved in the IGF1/PI3K/NF κB/ERK gene signalling networks. CONCLUSIONS: This study has identified pathway specific prognostic biomarkers possibly underlying a differential chemotherapy response in patients undergoing standard platinum-based treatment of serous epithelial ovarian cancer. In addition, our results provide a pathway context for further experimental validations, and the findings are a significant step towards future therapeutic interventions.

Multicolor microRNA FISH effectively differentiates tumor types.

MicroRNAs (miRNAs) are excellent tumor biomarkers because of their cell-type specificity and abundance. However, many miRNA detection methods, such as real-time PCR, obliterate valuable visuospatial information in tissue samples. To enable miRNA visualization in formalin-fixed paraffin-embedded (FFPE) tissues, we developed multicolor miRNA FISH. As a proof of concept, we used this method to differentiate two skin tumors, basal cell carcinoma (BCC) and Merkel cell carcinoma (MCC), with overlapping histologic features but distinct cellular origins. Using sequencing-based miRNA profiling and discriminant analysis, we identified the tumor-specific miRNAs miR-205 and miR-375 in BCC and MCC, respectively. We addressed three major shortcomings in miRNA FISH, identifying optimal conditions for miRNA fixation and ribosomal RNA (rRNA) retention using model compounds and high-pressure liquid chromatography (HPLC) analyses, enhancing signal amplification and detection by increasing probe-hapten linker lengths, and improving probe specificity using shortened probes with minimal rRNA sequence complementarity. We validated our method on 4 BCC and 12 MCC tumors. Amplified miR-205 and miR-375 signals were normalized against directly detectable reference rRNA signals. Tumors were classified using predefined cutoff values, and all were correctly identified in blinded analysis. Our study establishes a reliable miRNA FISH technique for parallel visualization of differentially expressed miRNAs in FFPE tumor tissues.

miR-193b Regulates Mcl-1 in Melanoma.

MicroRNAs play important roles in gene regulation, and their expression is frequently dysregulated in cancer cells. In a previous study, we reported that miR-193b represses cell proliferation and regulates cyclin D1 in melanoma cells, suggesting that miR-193b could act as a tumor suppressor. Herein, we demonstrate that miR-193b also down-regulates myeloid cell leukemia sequence 1 (Mcl-1) in melanoma cells. MicroRNA microarray profiling revealed that miR-193b is expressed at a significantly lower level in malignant melanoma than in benign nevi. Consistent with this, Mcl-1 is detected at a higher level in malignant melanoma than in benign nevi. In a survey of melanoma samples, the level of Mcl-1 is inversely correlated with the level of miR-193b. Overexpression of miR-193b in melanoma cells represses Mcl-1 expression. Previous studies showed that Mcl-1 knockdown cells are hypersensitive to ABT-737, a small-molecule inhibitor of Bcl-2, Bcl-X(L), and Bcl-w. Similarly, overexpression of miR-193b restores ABT-737 sensitivity to ABT-737-resistant cells. Furthermore, the effect of miR-193b on the expression of Mcl-1 seems to be mediated by direct interaction between miR-193b and seed and seedless pairing sequences in the 3' untranslated region of Mcl-1 mRNA. Thus, this study provides evidence that miR-193b directly regulates Mcl-1 and that down-regulation of miR-193b in vivo could be an early event in melanoma progression.

Differential expression of cell-cycle regulatory proteins defines distinct classes of follicular lymphoma.

Follicular lymphoma, a relatively common neoplasm of mature B lymphocytes, generally pursues an indolent clinical course. The disease is biologically heterogeneous, however, and aggressive instances associated with short survival are relatively common. Because defects in the regulation of apoptotic cell death are fundamental in follicular lymphoma pathogenesis, we hypothesized that deregulated expression of components of the Rb signaling pathway may promote cell proliferation, thereby complementing antecedent antiapoptotic mutations and producing more aggressive disease. We determined the differential expression of key cell-cycle regulatory proteins in lymphoma cells by incorporating formalin-fixed, paraffin-embedded samples from the initial, diagnostic biopsies from 127 cases of follicular lymphoma into tissue microarrays, histologic sections of which were stained by immunohistochemistry for p53, pRb, p16(INK4a), and cyclin D3. The results were ascertained by visual inspection and then correlated with histopathological and clinical parameters, including overall survival. Our findings show that increased abundance of p53 or p16(INK4a) is associated with reduced overall survival and conventional pathological markers of tumor aggressiveness including high histologic grade. Therefore, subjective quantification of cell-cycle regulatory proteins by immunohistochemistry can identify biologically and clinically distinct subsets of follicular lymphoma cases.

Immunohistochemical Assessment of Expression of Centromere Protein-A (CENPA) in Human Invasive Breast Cancer.

Abnormal cell division leading to the gain or loss of entire chromosomes and consequent genetic instability is a hallmark of cancer. Centromere protein -A (CENPA) is a centromere-specific histone-H3-like variant gene involved in regulating chromosome segregation during cell division. CENPA is one of the genes included in some of the commercially available RNA based prognostic assays for breast cancer (BCa)-the 70 gene signature MammaPrint® and the five gene Molecular Grade Index (MGISM). Our aim was to assess the immunohistochemical (IHC) expression of CENPA in normal and malignant breast tissue. Clinically annotated triplicate core tissue microarrays of 63 invasive BCa and 20 normal breast samples were stained with a monoclonal antibody against CENPA and scored for percentage of visibly stained nuclei. Survival analyses with Kaplan-Meier (KM) estimate and Cox proportional hazards regression models were applied to assess the associations between CENPA expression and disease free survival (DFS). Average percentage of nuclei visibly stained with CENPA antibody was significantly higher (p = 0.02) in BCa than normal tissue. The 3-year DFS in tumors over-expressing CENPA (>50% stained nuclei) was 79% compared to 85% in low expression tumors ( 60.07; p = 0.06) within our small cohort. To the best of our knowledge, this is the first published report evaluating the implications of increased IHC expression of CENPA in paraffin embedded breast tissue samples. Our finding that increased CENPA expression may be associated with shorter DFS in BCa supports its exploration as a potential prognostic biomarker.

MicroRNA-193b represses cell proliferation and regulates cyclin D1 in melanoma.

Cutaneous melanoma is an aggressive form of human skin cancer characterized by high metastatic potential and poor prognosis. To better understand the role of microRNAs (miRNAs) in melanoma, the expression of 470 miRNAs was profiled in tissue samples from benign nevi and metastatic melanomas. We identified 31 miRNAs that were differentially expressed (13 up-regulated and 18 down-regulated) in metastatic melanomas relative to benign nevi. Notably, miR-193b was significantly down-regulated in the melanoma tissues examined. To understand the role of miR-193b in melanoma, functional studies were undertaken. Overexpression of miR-193b in melanoma cell lines repressed cell proliferation. Gene expression profiling identified 314 genes down-regulated by overexpression of miR-193b in Malme-3M cells. Eighteen of these down-regulated genes, including cyclin D1 (CCND1), were also identified as putative miR-193b targets by TargetScan. Overexpression of miR-193b in Malme-3M cells down-regulated CCND1 mRNA and protein by > or = 50%. A luciferase reporter assay confirmed that miR-193b directly regulates CCND1 by binding to the 3'untranslated region of CCND1 mRNA. These studies indicate that miR-193b represses cell proliferation and regulates CCND1 expression and suggest that dysregulation of miR-193b may play an important role in melanoma development.

Microarrays in veterinary diagnostics.

Microarrays have numerous applications in the clinical setting, and these uses are not confined to the study of common human diseases. Indeed, the high-throughput technology affects clinical diagnostics in a variety of contexts, and this is reflected in the increasing use of microarray-based tools in the development of diagnostic and prognostic tests and in the identification of novel therapeutic targets. While much of the value of microarray-based experimentation has been derived from the study of human disease, there is equivalent potential for its role in veterinary medicine. Even though the resources devoted to the study of animal molecular diagnostics may be less than those available for human research, there is nonetheless a growing appreciation of the value of genome-wide information as it applies to animal disease. Therefore, this review focuses on the basics of microarray experimentation, and how this technology lends itself to a variety of diagnostic approaches in veterinary medicine.