High-throughput Genomic Screening Research Articles

P504: A universal filter enabling high throughput genomic screening

P504: A universal filter enabling high throughput genomic screening

Bitkilerde kuraklığa duyarlı miRNA'lar: derleme

MicroRNAs (miRNAs) are known as single-stranded RNA molecule functional in all steps of plant life including growth, development, and stress responses. Plant genomes harbor hundreds of miRNAs, which have diverse functions in regulating numerous biological processes. After being first discovered in plants by the year 2002, thousands of plant miRNAs have been identified so far. With the help of recent advances in high-throughput sequencing technologies, genome and transcriptome-wide screening of miRNAs in specific conditions and in a variety of plants has been conducted. Among the challenging conditions that inversely affect plants, drought stress is one of the main factors limiting plant growth and productivity worldwide. So far, drought-responsive miRNAs have been uncovered in particular plants. Moreover, functional characterizations of some miRNAs provide insights into their role in drought regulatory mechanisms. This review summarizes the most recent findings on miRNA-based drought stress regulation of plants. The study provides insights about role of miRNAs in drought stress response of plant.

Understanding the cellular origin and progression of esophageal cancer using esophageal organoids.

Three-dimensional (3D) organoids are a novel tool to model epithelial cell biology and human diseases of the esophagus. 3D organoid culture systems have been utilized to investigate the pathobiology of esophageal cancer, including both squamous cell carcinoma and adenocarcinoma. Additional organoid-based approaches for study of esophageal development and benign esophageal diseases have provided key insights into esophageal keratinocyte differentiation and mucosal regeneration. These investigations have implications for the identification of esophageal cancer stem cells, as well as the potential to halt malignant progression through induction of differentiation pathways. Patient-derived organoids (PDOs) from human tissue samples allow for unique and faithful in vitro modeling of esophageal cancers, and provide an exciting platform for investigation into personalized medicine and targeted treatment approaches, as well as new models for understanding therapy resistance and recurrent disease. Future directions include high-throughput genomic screening using PDOs, and study of tumor-microenvironmental interactions through co-culture with immune and stromal cells and novel extracellular matrix complexes.

Genetic control of retinal ganglion cell genesis

Retinal ganglion cells (RGCs) are the only projection neurons in the neural retina. They receive and integrate visual signals from upstream retinal neurons in the visual circuitry and transmit them to the brain. The function of RGCs is performed by the approximately 40 RGC types projecting to various central brain targets. RGCs are the first cell type to form during retinogenesis. The specification and differentiation of the RGC lineage is a stepwise process; a hierarchical gene regulatory network controlling the RGC lineage has been identified and continues to be elaborated. Recent studies with single-cell transcriptomics have led to unprecedented new insights into their types and developmental trajectory. In this review, we summarize our current understanding of the functions and relationships of the many regulators of the specification and differentiation of the RGC lineage. We emphasize the roles of these key transcription factors and pathways in different developmental steps, including the transition from retinal progenitor cells (RPCs) to RGCs, RGC differentiation, generation of diverse RGC types, and central projection of the RGC axons. We discuss critical issues that remain to be addressed for a comprehensive understanding of these different aspects of RGC genesis and emerging technologies, including single-cell techniques, novel genetic tools and resources, and high-throughput genome editing and screening assays, which can be leveraged in future studies.

Genetic Approaches to Uncover Gene Products Involved in Iron-Sulfur Protein Maturation: High-Throughput Genomic Screening Using Transposon Sequencing.

Iron-sulfur (Fe-S) clusters are one of the most ubiquitous and versatile prosthetic groups exploited by nature. Fe-S clusters aid in conducting redox reactions, carbon activation, and environmental sensing. This chapter presents an overview of the genetic approaches that have been useful for identifying and characterizing bacterial factors involved in Fe-S protein assembly. Traditional genetic screens that assess viability or conditional auxotrophies and bioinformatic approaches have identified the majority of the described genes utilized for Fe-S protein assembly. Herein, we expand upon this list of genetic methods by detailing the use of transposon sequencing (TnSeq) to identify gene products that are necessary for the proper function of metabolic pathways that require Fe-S enzymes. TnSeq utilizes the power of genomics and massively parallel DNA sequencing to allow researchers to quantify the necessity of individual gene products for a specific growth condition. This allows for the identification of gene products or gene networks that have a role in a given metabolic process but are not essential for the process. An advantage of this approach is that it allows researchers to identify mutants that have partial phenotypes that are often missed using traditional plate-based selections. Applying TnSeq to address questions of Fe-S protein maturation will result in a more comprehensive understanding of genetic interactions and factors utilized in Fe-S biogenesis and Fe-S protein assembly.

Genome wide association studies for treatment-related adverse effects of pediatric acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is the most common pediatric hematological malignancy; notwithstanding the success of ALL therapy, severe adverse drugs effects represent a serious issue in pediatric oncology, because they could be both an additional life threatening condition for ALL patients per se and a reason to therapy delay or discontinuation with important fallouts on final outcome. Cancer treatment-related toxicities have generated a significant need of finding predictive pharmacogenomic markers for the a priori identification of at risk patients. In the era of precision medicine, high throughput genomic screening such as genome wide association studies (GWAS) might provide useful markers to tailor therapy intensity on patients' genetic profile. Furthermore, these findings could be useful in basic research for better understanding the mechanistic and regulatory pathways of the biological functions associated with ALL treatment toxicities. The purpose of this review is to give an overview of high throughput genomic screening of the last 10 years that had investigated the landscape of ALL treatment-associated toxicities. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics.

A high-throughput genomic screen identifies a role for the plasmid-borne type II secretion system of Escherichia coli O157:H7 (Sakai) in plant-microbe interactions

Shiga-toxigenic Escherichia coli (STEC) is often transmitted into food via fresh produce plants, where it can cause disease. To identify early interaction factors for STEC on spinach, a high-throughput positive-selection system was used. A bacterial artificial chromosome (BAC) clone library for isolate Sakai was screened in four successive rounds of short-term (2 h) interaction with spinach roots, and enriched loci identified by microarray. A Bayesian hierarchical model produced 115 CDS credible candidates, comprising seven contiguous genomic regions. Of the two candidate regions selected for functional assessment, the pO157 plasmid-encoded type two secretion system (T2SS) promoted interactions, while a chaperone-usher fimbrial gene cluster (loc6) did not. The T2SS promoted bacterial binding to spinach and appeared to involve the EtpD secretin protein. Furthermore, the T2SS genes, etpD and etpC, were expressed at a plant-relevant temperature of 18 °C, and etpD was expressed in planta by E. coli Sakai on spinach plants.

Mantis-ml: Disease-Agnostic Gene Prioritization from High-Throughput Genomic Screens by Stochastic Semi-supervised Learning

Access to large-scale genomics datasets has increased the utility of hypothesis-free genome-wide analyses. However, gene signals are often insufficiently powered to reach experiment-wide significance, triggering a process of laborious triaging of genomic-association-study results. We introduce mantis-ml, a multi-dimensional, multi-step machine-learning framework that allows objective assessment of the biological relevance of genes to disease studies. Mantis-ml is an automated machine-learning framework that follows a multi-model approach of stochastic semi-supervised learning to rank disease-associated genes through iterative learning sessions on random balanced datasets across the protein-coding exome. When applied to a range of human diseases, including chronic kidney disease (CKD), epilepsy, and amyotrophic lateral sclerosis (ALS), mantis-ml achieved an average area under curve (AUC) prediction performance of 0.81–0.89. Critically, to prove its value as a tool that can be used to interpret exome-wide association studies, we overlapped mantis-ml predictions with data from published cohort-level association studies. We found a statistically significant enrichment of high mantis-ml predictions among the highest-ranked genes from hypothesis-free cohort-level statistics, indicating a substantial improvement over the performance of current state-of-the-art methods and pointing to the capture of true prioritization signals for disease-associated genes. Finally, we introduce a generic mantis-ml score (GMS) trained with over 1,200 features as a generic-disease-likelihood estimator, outperforming published gene-level scores. In addition to our tool, we provide a gene prioritization atlas that includes mantis-ml’s predictions across ten disease areas and empowers researchers to interactively navigate through the gene-triaging framework. Mantis-ml is an intuitive tool that supports the objective triaging of large-scale genomic discovery studies and enhances our understanding of complex genotype-phenotype associations.

Current and Future Molecular Targets for Acute Myeloid Leukemia Therapy.

Acute myeloid leukemia (AML) disease prognosis is poor and there is a high risk of chemo-resistant relapse for both young and old patients. Thus, there is a demand for alternative and target-specific drugs to improve the 5-year survival rate. Current treatment mainstays include chemotherapy, or mutation-specific targeting molecules including FLT3 inhibitors, IDH inhibitors, and monoclonal antibodies. Efforts to devise new, targeted therapy have included recent advances in methods for high-throughput genomic screening and the availability of computer-assisted techniques for the design of novel agents predicted to specifically inhibit mutant molecules involved in leukemogenesis. Crosstalk between the leukemia cells and the bone marrow microenvironment through cell surface molecules, such as the integrins αvβ3 and αvβ5, might influence drug response and AML progression. This review article focuses on current AML treatment options, new AML targeted therapies, the role of integrins in AML progression, and a potential therapeutic agent-integrin αvβ3 antagonist.

Abstract 3097: Investigating an aggressive molecular subtype of stage I lung adenocarcinoma: Evidences for the acquirement of stem-like and immune evasion phenotype

Abstract Lung cancer early diagnosis is effective in reducing the risk of metastatic disease and improve overall survival. However, a significant fraction of patients (~20%) with early stage disease (Stage I) experience tumor recurrence and metastatic disease. Recent advances in high-throughput genomic screening allowed an in-depth molecular profile analyses of lung cancer, with particular emphasis for the identification of prognostic gene expression signatures. Indeed, we recently described the existence of an aggressive lung adenocarcinoma (LUAD) molecular subtype (Stage I), namely C1-LUAD, with a peculiar expression and mutational profile more resembling advanced metastatic cancer. Using an integrative approach relying on computational biology and lung cancer experimental models, we now discovered that this C1-subtype is characterized by stem-like and immune evading phenotype. In particular, gene-set enrichment analysis (GSEA) revealed that ‘C1-LUAD’ tumors are enriched in stem cell (SC) expression signatures (q-value<0.05). Notably, the gene network characterizing the C1-LUAD subtype was downstream to known transcriptional modulators involved in SC biology. In line with this, we found several iPS/Stem and EMT biomarkers overexpressed in C1-LUAD and in a panel of C1-LUAD-like lung cancer cells. Furthermore, forced overexpression of HOXB7 gene, a biomarker of C1-LUAD and a member of the Antp homeobox family, promotes the expansion of lung sphere-forming cells and reprogramming into iPS cells. Lastly, we performed an analysis of the Immune Subtypes and ImmunoPhenoScore in C1-LUAD tumors coupled with tumor mutational burden (TMB) and intra-tumor genetic heterogeneity (ITH) profile, which revealed: i) a predominance of the tumor permissive ‘C1 wound healing' subtype (i.e. high Th2/TAMs, low CD8+Tc); ii) a reduction of the ‘C3 inflammatory' subtype; iii) an increased ITH; and iv) a reduction of neoantigen burden. These are hallmarks of cancer immunoediting process which ultimately favor tumor cell escape. In conclusion, we identified an aggressive subtype of LUAD characterized by a stem-like and immune evasion phenotype. C1-LUAD can be identified by qPCR analysis using a panel of 10 genes, previously validated in a large cohort of FFPE samples. Our findings can contribute to improve survival of lung cancer patients by anticipating diagnosis of aggressive Stage I tumors and may pave the way for developing more effective therapeutic strategies. Citation Format: Valentina Melocchi, Elisa Dama, Roberto Cuttano, Tommaso Colangelo, Paolo Graziano, Fabrizio Bianchi. Investigating an aggressive molecular subtype of stage I lung adenocarcinoma: Evidences for the acquirement of stem-like and immune evasion phenotype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3097.

Distinct seasonal infectious agent profiles in life-history variants of juvenile Fraser River Chinook salmon: An application of high-throughput genomic screening.

Disease-causing infectious agents are natural components of ecosystems and considered a major selective force driving the evolution of host species. However, knowledge of the presence and abundance of suites of infectious agents in wild populations has been constrained by our ability to easily screen for them. Using salmon as a model, we contrasted seasonal pathogenic infectious agents in life history variants of juvenile Chinook salmon from the Fraser River system (N = 655), British Columbia (BC), through the application of a novel high-throughput quantitative PCR monitoring platform. This included freshwater hatchery origin fish and samples taken at sea between ocean entry in spring and over-winter residence in coastal waters. These variants currently display opposite trends in productivity, with yearling stocks generally in decline and sub-yearling stocks doing comparatively well. We detected the presence of 32 agents, 21 of which were at >1% prevalence. Variants carried a different infectious agent profile in terms of (1) diversity, (2) origin or transmission environment of infectious agents, and (3) prevalence and abundance of individual agents. Differences in profiles tended to reflect differential timing and residence patterns through freshwater, estuarine and marine habitats. Over all seasons, individual salmon carried an average of 3.7 agents. Diversity changed significantly, increasing upon saltwater entrance, increasing through the fall and decreasing slightly in winter. Diversity varied between life history types with yearling individuals carrying 1.3-times more agents on average. Shifts in prevalence and load over time were examined to identify agents with the greatest potential for impact at the stock level; those displaying concurrent decrease in prevalence and load truncation with time. Of those six that had similar patterns in both variants, five reached higher prevalence in yearling fish while only one reached higher prevalence in sub-yearling fish; this pattern was present for an additional five agents in yearling fish only.

Abstract B66: An integrated immuno-oncology platform using high-throughput cell based assays, gene editing and genomic screens in immune cells

Abstract Horizon is establishing a powerful in vitro immuno-oncology platform with the capability to identify combinations of agents that will synergise with checkpoint inhibitors, determine methods for making safer and more effective cell therapies and find novel targets for immuno-therapy. Horizon previously reported the establishment of a platform consisting of a suite of high-throughput cell-based assays modelling a variety of oncology relevant immune reactions. The platform includes primary human immune-cell based assays for T cell activation, Mixed lymphocyte reaction (MLR), Tumor cell lysis, Antibody-dependent cellular cytotoxicity (ADCC), Complement-dependent cytotoxicity (CDC) and Natural killer cell cytotoxicity assays that have been validated with appropriate clinically approved antibodies (e.g. nivolumab, blinotumamab, & rituximab). Miniaturized to a 384-well format and supported by automation at each experimental step the platform is highly customizable in terms of testing agents that either enhance or inhibit immune cell functions. We will present ongoing efforts to identify synergistic activities with other relevant therapeutics likely to bring benefits to patients. In addition to the continued development of our high throughput immuno-oncology cell based assays, we have expanded our cell engineering know how combined with CRISPR-Cas9 gene editing technology to build new models to understand better the immune response and its subversion in tumorigenesis. By modifying specific genes of interest in immune cells we aim to robustly identify and validate new targets for the clinic. For example, we have used high efficiency gene editing with CRISPR-Cas9 in human primary T cells to knock out and knock in genes using Neon transfection systems. Using this methodology we can rapidly generate primary T cell models lacking specific checkpoint proteins (such as PD-1) to better understand how T-cell signalling pathways interact and to nominate novel targets suitable for ex vivo gene editing. We have also employed pooled CRISPR-Cas9 screens to investigate the effects of metabolic changes on T cell biology. CD3+ T cells have been infected with a one vector lentiviral system that delivers both Cas9 and sgRNAs targeting genes involved in cellular metabolism. Results from these screens should identify potential targets involved in T cell metabolism that affect their capacity to respond to proliferative stimuli in the form of anti-CD3 and anti-CD28 antibodies. We anticipate that these and other data generated using libraries targeting essential genes will be invaluable for the design of more complex immuno-oncology screens. Overall, Horizon's integrated immuno-oncology platform will enable large scale interrogation of prospective immunotherapies, either alone or in combination, and could be useful for the discovery of novel checkpoint components, for deciphering the underlying mechanisms promoting an immunosuppressive tumor microenvironment and for the understanding of how pathways crucial for an anti-tumor immune response interact. Thus, this platform could contribute substantially to the discovery and development of future immunotherapies. Citation Format: An Frank, Sujatha Kumar, Christina Ghirelli, Kim Hoenderdos, Tabasum Huseni, Lauren Thibault, Lydia Kifle, Nava Almog, Felicia Zhao, Simon Scrace, Anatoly Myaskovsky, Chris Lowe, Janine Steiger, Nicola McCarthy, Jonathan Moore. An integrated immuno-oncology platform using high-throughput cell based assays, gene editing and genomic screens in immune cells. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr B66.

Advancing Crop Transformation in the Era of Genome Editing.

Plant transformation has enabled fundamental insights into plant biology and revolutionized commercial agriculture. Unfortunately, for most crops, transformation and regeneration remain arduous even after more than 30 years of technological advances. Genome editing provides novel opportunities to enhance crop productivity but relies on genetic transformation and plant regeneration, which are bottlenecks in the process. Here, we review the state of plant transformation and point to innovations needed to enable genome editing in crops. Plant tissue culture methods need optimization and simplification for efficiency and minimization of time in culture. Currently, specialized facilities exist for crop transformation. Single-cell and robotic techniques should be developed for high-throughput genomic screens. Plant genes involved in developmental reprogramming, wound response, and/or homologous recombination should be used to boost the recovery of transformed plants. Engineering universal Agrobacterium tumefaciens strains and recruiting other microbes, such as Ensifer or Rhizobium, could facilitate delivery of DNA and proteins into plant cells. Synthetic biology should be employed for de novo design of transformation systems. Genome editing is a potential game-changer in crop genetics when plant transformation systems are optimized.

Genome-Engineering Tools to Establish Accurate Reporter Cell Lines That Enable Identification of Therapeutic Strategies to Treat Friedreich’s Ataxia

Friedreich’s ataxia is a neurodegenerative disease caused by deficiency of the mitochondrial protein frataxin. This deficiency results from expansion of a trinucleotide repeat in the first intron of the frataxin gene. Because this repeat expansion resides in an intron and hence does not alter the amino acid sequence of the frataxin protein, gene reactivation could be of therapeutic benefit. High-throughput screening for frataxin activators has so far met with limited success because current cellular models may not accurately assess endogenous frataxin gene regulation. Here we report the design and validation of genome-engineering tools that enable the generation of human cell lines that express the frataxin gene fused to a luciferase reporter gene from its endogenous locus. Performing a pilot high-throughput genomic screen in a newly established reporter cell line, we uncovered novel negative regulators of frataxin expression. Rational design of small-molecule inhibitors of the identified frataxin repressors and/or high-throughput screening of large siRNA or compound libraries with our system may yield treatments for Friedreich’s ataxia.

An epidemiological perspective of personalized medicine: the Estonian experience.

Milani L, Leitsalu L, Metspalu A (University of Tartu). An epidemiological perspective of personalized medicine: the Estonian experience (Review). J Intern Med 2015; 277: 188–200.The Estonian Biobank and several other biobanks established over a decade ago are now starting to yield valuable longitudinal follow-up data for large numbers of individuals. These samples have been used in hundreds of different genome-wide association studies, resulting in the identification of reliable disease-associated variants. The focus of genomic research has started to shift from identifying genetic and nongenetic risk factors associated with common complex diseases to understanding the underlying mechanisms of the diseases and suggesting novel targets for therapy. However, translation of findings from genomic research into medical practice is still lagging, mainly due to insufficient evidence of clinical validity and utility. In this review, we examine the different elements required for the implementation of personalized medicine based on genomic information. First, biobanks and genome centres are required and have been established for the high-throughput genomic screening of large numbers of samples. Secondly, the combination of susceptibility alleles into polygenic risk scores has improved risk prediction of cardiovascular disease, breast cancer and several other diseases. Finally, national health information systems are being developed internationally, to combine data from electronic medical records from different sources, and also to gradually incorporate genomic information. We focus on the experience in Estonia, one of several countries with national goals towards more personalized health care based on genomic information, where the unique combination of elements required to accomplish this goal are already in place.

PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets.

Quality control and read preprocessing are critical steps in the analysis of data sets generated from high-throughput genomic screens. In the most extreme cases, improper preprocessing can negatively affect downstream analyses and may lead to incorrect biological conclusions. Here, we present PathoQC, a streamlined toolkit that seamlessly combines the benefits of several popular quality control software approaches for preprocessing next-generation sequencing data. PathoQC provides a variety of quality control options appropriate for most high-throughput sequencing applications. PathoQC is primarily developed as a module in the PathoScope software suite for metagenomic analysis. However, PathoQC is also available as an open-source Python module that can run as a stand-alone application or can be easily integrated into any bioinformatics workflow. PathoQC achieves high performance by supporting parallel computation and is an effective tool that removes technical sequencing artifacts and facilitates robust downstream analysis. The PathoQC software package is available at http://sourceforge.net/projects/PathoScope/.

Abstract A103: High-throughput genomic and chemical screening in glioblastoma cell lines.

Abstract Introduction: Glioblastoma is the most malignant and deleterious brain tumor. Average patient survival is less than 14 months and there is no effective cure. Glioma cell lines, grown in serum, have been used to explore new therapeutic approaches, but they are poor representatives of primary tumors. At the genomic level, they exhibit many allelic imbalances and mutations that are likely associated with long-term passages and selective pressure to fit an artificial environment. At the gene expression level, they do not clearly recapitulate expression patterns seen in human glioblastomas. Finally, when these cell lines are injected in animal models tend to form “ball”-like masses rather than infiltrating tumors. Recently, it has been found that “neurosphere” cells derived from glioblastomas cultured in cytokines without serum more closely mirror the phenotype and genotype of primary tumors. Experimental procedures: We are therefore pursuing a systematic analysis of genetic and non-genetic features that correlate with sensitivity to each of 480 small molecules in 40 neurosphere cell lines grown in the absence of serum. Here we present initial results from 12 neurospheres and nine traditional glioblastoma cell lines. We considered mutations, copy number alterations, and gene expression. In order to determine the representation of cancer stem cells in these populations, we also interrogated the cell surface markers CD44, CD15, and CD133 by flow citometry and the neural stem cell markers Nestin, Olig2, Sox2 and lineage differentiation markers GFAP, Tuj1, and O4 by Western blots. Summary: We find that copy number profiles of the neurosphere lines resemble glioblastomas more closely than do established cells lines growing in serum. Gene expression profiles denoted that cell lines don't recapitulate accurately molecular signatures previously defined in GBMs. Neurospheres were classified mainly as Proneuronal or Mesenchymal subtypes, in change cell lines growing in serum displayed more heterogeneous profiles being difficult assign to previously defined subtypes. We also find that neurosphere lines are more sensitive to a variety of small molecules than are traditional cell lines. Among the neurospheres, those lines that grow in suspension or as sphereoids tend to exhibit heterogeneity in expression of CD44/CD133/CD15, whereas neurospheres that grow attached to the plate tend to homogenously express CD44 alone. The suspension lines are also more sensitive to a variety of small molecules. Statement: These results indicate the feasibility of large-scale small molecule screening in neurosphere cell lines, and allowed us correlate with genomic and non-genomic determinants in a more accurate glioblastoma cell line model. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A103. Citation Format: Ruben Ferrer-Luna, Shakti Ramkissoon, Jaime Cheah, Rebecca Lamothe, Steven Schumacher, Alykhan Shamji, Paul Clemons, David Reardon, Patrick Wen, Stuart Schreiber, Keith Ligon, Rameen Beroukhim. High-throughput genomic and chemical screening in glioblastoma cell lines. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A103.

Identification of unique somatic mutations with functional relevance through genetic characterization of gallbladder cancer (GB ca).

214 Background: GB Ca is the leading cause of cancer mortality in Chilean women and its incidence is high in Southeast Asia. Molecular characterization of this disease is limited to small retrospective studies of prognostic biomarkers. Methods: 54 surgically resected GB Ca cases were selected. DNA was extracted from microdissected tumors; genetic mutations analyzed using two platforms a) Sequenom MassARRAY, a mass spectrometry-based approach for 90 targetable mutations including PIK3CA, KRAS, EGFR, FGFR, CTNNB1, MET, ALK and AKT and b) Exome sequencing using the Illumina HiSeq2000 sequencer for novel genetic variants in the coding regions. Sample preparation followed the standard Agilent SureSelect XT protocol with the 71Mb +UTR capture library. A stepwise filtering approach was used to identify variants by screening for nonsynonymous substitutions, comparison of exomes to matched control and dbSNP database to exclude common variants. Variants not predicted to affect protein function were excluded. KM survival curves and log rank test were used to correlate genotyping results with survival. Results: 46 cases were selected for Sequenom MassARRAY and whole exome sequencing performed on 8 cases and control non-tumor tissue. Sequenom identified mutations in KRAS (3 cases), IDH1 (4), ALK1 (1), MET (1), NRAS (3) and PIK3CA genes (2). Overall survival was poorer in KRAS [24 vs. 75 weeks, p=0.008] and IDH1 [27 vs. 80 weeks, p=0.0008] mutation carriers. Exome sequencing after filtering revealed genetic variants in 6 cases with an overall low mutation rate. There were no overlapping mutations and we identified 45 functional mutations in STK11, CDKN2A, IKZF3, GRM6, TP53 and CTNNB1 genes, known to be prognostic in other cancers. ABCB1 transporter, TP53 and STK11mutations were predicted to have high functional impact. Ingenuity pathway analysis identified p53, WNT/ ß-catenin, GBM and thyroid cancer signaling and cell cycle regulation to be the top hits. Conclusions: This first high-throughput genomic screening of GB Ca using different platforms identifies known and unique variants in cancer genes. Sequencing of additional cases and efforts to develop a GB Ca-specific somatic mutation panel are ongoing.

Homogeneous detection of cyanobacterial DNA via polymerase chain reaction

To design a primer set enabling the identification through PCR of high-quality DNA for routine and high-throughput genomic screening of a diverse range of cyanobacteria. A codon-equivalent multiple alignment of the phycocyanin alpha-subunit coding sequence (cpcA) of 22 cyanobacteria was generated and analysed to produce a single degeneracy primer set with virtually uniform product size. Also, an 18S ribosomal RNA detection set is proposed for rejecting false positives. The primer sets were tested against five diverse cyanobacteria, Chlorella vulgaris, Saccharomyces cerevisiae, and Escherichia coli. All five cyanobacteria showed positive amplification of cpcA product with homogeneous fragment length, and no products were observed for any other organism. Additionally, the only product formation observed for the 18S rRNA set was in C.vulgaris and S.cerevisiae. The newly proposed primer set served as effective check primers for cyanobacteria. Cyanobacteria gDNA had a positive, homogenous result, while other bacteria, eukaryotes and alga tested were negative. These novel, broad-spectrum primers will greatly increase the utility of PCR on newly discovered cyanobacterial species.

Molecular Markers of Early-Stage Mycosis Fungoides

The lack of a specific marker differentiating early mycosis fungoides (eMF) from benign inflammatory dermatitis presents significant difficulties in the assessment and management of suspected MF patients, which often leads to delayed diagnosis and improper medical approaches. To address this, an investigation was carried out to characterize positive identification markers for eMF by comparing eMF lesions with healthy skin and benign inflammatory dermatitis, using high-throughput genomic transcription profiling. A total of 349 genes were differentially expressed in eMF lesions compared with normal skin. These genes belong to pathways associated with inflammation, immune activation, and apoptosis regulation. Most of them (N=330) also demonstrated significant upregulation in chronic dermatitis, making them nonideal markers for eMF. Among them, 19 genes with specific enrichment in eMF lesions were identified that showed no significant upregulation in chronic dermatitis. Two of them, TOX and PDCD1, showed high discrimination power between eMF lesions and biopsies from benign dermatitis by RNA expression. Furthermore, TOX demonstrated highly specific staining of MF cells in eMF skin biopsies in immunohistochemistry and immunofluorescence, including the early epidermotropic cells in Pautrier's microabscesses. This study demonstrates the potential of eMF-enriched genes, especially TOX, as molecular markers for histological diagnosis of eMF, which currently is a major diagnostic challenge.