expression profiling
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... Introduction -- 1 Introduction: Present and Potential Impact of Expression Profiling Studies of Human ... ... and its Clinical Implications -- Masayuki Takahashi and Bin Lean Teh 235 -- 14 Expression Profiling ... ... West, and Matt van de Rijn 305 -- 18 Gene Expression Profiling in Lymphoid Malignancies -- Wing C. ... ... Staudt 329 -- 19 Gene Expression Profiling of Brain Tumors -- Meena K. Tanwar and Eric C. ... ... Holland 345 -- 20 Expression Profiling of Bone Tumors -- Deborah Schofield, Daniel Wai, and Timothy J ...
x, 399 stran : ilustrováno ; 26 cm
- MeSH
- diagnostické techniky molekulární MeSH
- nádory * diagnóza genetika MeSH
- stanovení celkové genové exprese MeSH
- Konspekt
- Biochemie. Molekulární biologie. Biofyzika
- NLK Obory
- molekulární biologie, molekulární medicína
- onkologie
- NLK Publikační typ
- kolektivní monografie
- MeSH
- časná diagnóza MeSH
- diagnostické techniky molekulární MeSH
- exprese genu MeSH
- genom lidský MeSH
- lidé MeSH
- messenger RNA analýza MeSH
- mikro RNA analýza MeSH
- polymerázová řetězová reakce MeSH
- sekvenční analýza hybridizací s uspořádaným souborem oligonukleotidů MeSH
- stanovení celkové genové exprese MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- recenze MeSH
Methods in molecular biology, ISSN 1064-3745 822 Springer protocols
xi, 341 stran : ilustrace
V našem sdělení chceme informovat o použití dvou metodik ke studiu molekulární genetické problematiky mnohočetného myelomu (MM). První zmíníme využití DNA čipů (microarrays) a ve druhé části se zaměříme na chromatinovou imunoprecipitaci v analýzách epigenetických změn genů. Obě metodiky náš výzkumný tým používá, a proto představíme i první výstupy. Využití obou metodik je u MM stejné jako u všech ostatních nádorů. Představují možnost studia patogeneze maligních onemocnění na molekulární úrovni, klasifikaci jinak neodlišitelných prognostických skupin choroby, predikci léčebné odpovědi na daný terapeutický zásah a identifikaci možných molekulárních cílů protinádorové terapie.
This review informs about utilization of two methods used in molecular examination in multiple myeloma on genomic level: DNA microarrays and chromatin immunoprecipitation. The profit of both methods is very similar in myeloma as well as in other cancers. They allow to study disease pathogenesis, generate new disease classification, and try to predict effect of therapy. Also, they are used to find the new potential target of therapy in multiple myeloma.
- MeSH
- chromatinová imunoprecipitace metody využití MeSH
- DNA fingerprinting metody využití MeSH
- exprese genu genetika MeSH
- financování organizované MeSH
- hematologické nádory diagnóza etiologie genetika MeSH
- lékařská onkologie metody trendy MeSH
- lékové transportní systémy metody využití MeSH
- lidé MeSH
- mnohočetný myelom diagnóza etiologie genetika MeSH
- sekvenční analýza hybridizací s uspořádaným souborem oligonukleotidů metody využití MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to meet this demand. This review focuses on comparing the two most useful methods for whole transcriptome gene expression profiling. Microarrays are reliable and more cost effective than RNA-Seq for gene expression profiling in model organisms. RNA-Seq will eventually be used more routinely than microarray, but right now the techniques can be complementary to each other. Microarrays will not become obsolete but might be relegated to only a few uses. RNA-Seq clearly has a bright future in bioinformatic data collection.
Gene expression microarrays are being used to develop new prognostic and predictive tests for breast cancer, and might be used at the same time to confirm oestrogen-receptor status and ERBB2 status. Our goal was to establish a new method to assign oestrogen receptor and ERBB2-receptor status to breast carcinoma based on mRNA expression measured using Affymetrix U133A gene-expression profiling. METHODS: We used gene expression data of 495 breast cancer samples to assess the correlation between oestrogen receptor (ESR1) and ERBB2 mRNA and clinical status of these genes (as established by immunohistochemical [IHC] or fluorescence in-situ hybridisation [FISH], or both). Data from 195 fine-needle aspiration (FNA) samples were used to define mRNA cutoff values that assign receptor status. We assessed the accuracy of these cutoffs in two independent datasets: 123 FNA samples and 177 tissue samples (ie, resected or core-needle biopsied tissues). Profiling was done at two institutions by use of the same platform (Affymetrix U133A GeneChip). All data were uniformly normalised with dCHIP software. FINDINGS: ESR1 and ERBB2 mRNA levels correlated closely with routine measurements for receptor status in all three datasets. Spearman's correlation coefficients ranged from 0.62 to 0.77. An ESR1 mRNA cutoff value of 500 identified oestrogen-receptor-positive status with an overall accuracy of 90% (training set), 88% (first validation set), and 96% (second validation set). An ERBB2 mRNA threshold of 1150 identified ERBB2-positive status with the overall accuracy of 93% (training set), 89% (first validation set), and 90% (second validation set). Reproducibility of mRNA measurements in 34 replicate experiments was high (correlation coefficient 0.975 for ESR1, 0.984 for ERBB2). INTERPRETATION: Amounts of ESR1 and ERBB2 mRNA as measured by the Affymetrix GeneChip reliably and reproducibly establish oestrogen-receptor status and ERBB2 status, respectively.
Osteoblastic differentiation is a multistep process characterized by osteogenic induction of mesenchymal stem cells, which then differentiate into proliferative pre-osteoblasts that produce copious amounts of extracellular matrix, followed by stiffening of the extracellular matrix, and matrix mineralization by hydroxylapatite deposition. Although these processes have been well characterized biologically, a detailed transcriptional analysis of murine primary calvaria osteoblast differentiation based on RNA sequencing (RNA-seq) analyses has not previously been reported. Here, we used RNA-seq to obtain expression values of 29,148 genes at four time points as murine primary calvaria osteoblasts differentiate in vitro until onset of mineralization was clearly detectable by microscopic inspection. Expression of marker genes confirmed osteogenic differentiation. We explored differential expression of 1386 protein-coding genes using unsupervised clustering and GO analyses. 100 differentially expressed lncRNAs were investigated by co-expression with protein-coding genes that are localized within the same topologically associated domain. Additionally, we monitored expression of 237 genes that are silent or active at distinct time points and compared differential exon usage. Our data represent an in-depth profiling of murine primary calvaria osteoblast differentiation by RNA-seq and contribute to our understanding of genetic regulation of this key process in osteoblast biology.
- MeSH
- alternativní sestřih MeSH
- buněčná diferenciace genetika MeSH
- kultivované buňky MeSH
- lebka fyziologie MeSH
- myši inbrední C57BL MeSH
- myši MeSH
- osteoblasty fyziologie MeSH
- osteogeneze genetika MeSH
- RNA analýza MeSH
- stanovení celkové genové exprese MeSH
- transkriptom genetika MeSH
- zvířata MeSH
- Check Tag
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Yeast infections are often connected with formation of biofilms that are extremely difficult to eradicate. An excellent model system for deciphering multifactorial determinants of yeast biofilm development is the colony biofilm, composed of surface ("aerial") and invasive ("root") cells. While surface cells have been partially analyzed before, we know little about invasive root cells. In particular, information on the metabolic, chemical and morphogenetic properties of invasive versus surface cells is lacking. In this study, we used a new strategy to isolate invasive cells from agar and extracellular matrix, and employed it to perform genome wide expression profiling and biochemical analyses of surface and invasive cells. RESULTS: RNA sequencing revealed expression differences in 1245 genes with high statistical significance, indicating large genetically regulated metabolic differences between surface and invasive cells. Functional annotation analyses implicated genes involved in stress defense, peroxisomal fatty acid β-oxidation, autophagy, protein degradation, storage compound metabolism and meiosis as being important in surface cells. In contrast, numerous genes with functions in nutrient transport and diverse synthetic metabolic reactions, including genes involved in ribosome biogenesis, biosynthesis and translation, were found to be important in invasive cells. Variation in gene expression correlated significantly with cell-type specific processes such as autophagy and storage compound accumulation as identified by microscopic and biochemical analyses. Expression profiling also provided indications of cell-specific regulations. Subsequent knockout strain analyses identified Gip2p, a regulatory subunit of type 1 protein phosphatase Glc7p, to be essential for glycogen accumulation in surface cells. CONCLUSIONS: This is the first study reporting genome wide differences between surface and invasive cells of yeast colony biofilms. New findings show that surface and invasive cells display very different physiology, adapting to different conditions in different colony areas and contributing to development and survival of the colony biofilm as a whole. Notably, surface and invasive cells of colony biofilms differ significantly from upper and lower cells of smooth colonies adapted to plentiful laboratory conditions.
... Tumor staging and grading: A primer -- Clinical trial design in the age of molecular profiling -- Personalized ... ... clinical trials -- Reduction of preanalytical variability in specimen procurement for molecular profiling ... ... -- The human side of cancer biobanking -- Introduction to genomics -- Genomic profiling: cDNA arrays ... ... and oligoarrays -- Genome-wide methylation profiling in archival formalin-fixed paraffin-embedded tissue ... ... samples -- An overview of microRNA methods: expression profiling and target identification -- Antibody ...
Methods in molecular biology, ISSN 1064-3745 vol 823
xiii, 447 s. : il. ; 27 cm
- MeSH
- molekulární biologie MeSH
- Publikační typ
- laboratorní příručky MeSH
- příručky MeSH
- Konspekt
- Biochemie. Molekulární biologie. Biofyzika
- NLK Obory
- biologie
Východiska: Meduloblastom (MB) je nejčastější maligní nádor centrálního nervového systému u dětí. V ČR ročně onemocní tímto nádorem přibližně 10–12 dětí. MB jsou považovány za vysoce rizikové nádory se sklonem k metastazování. Současné pokroky v molekulární diagnostice pomáhají ve zpřesnění diagnózy a předpovědi klinického průběhu onemocnění. V současné době jsou MB rozdělovány do podskupin, a to na základě molekulárních drah řídících jejich vznik, na WNT aktivované, SHH aktivované, skupinu 3 a 4. Jednotlivé podskupiny se liší svou histologií, klinickým průběhem, genomickými změnami a profily genové exprese. Cílem naší studie je klasifikace pacientů s MB do čtyř základních molekulárních skupin a porovnání získaných výsledků s literaturou. Materiál a metody: U pacientů s MB je v rámci naší studie prováděno profilování genových expresí pomocí Affymetrix GeneChip Human Gene 1.0. ST Array (Thermo Fisher Scientific, MA, USA). Vstupním materiálem je celková RNA izolovaná ze zamražené nádorové tkáně. Samotná klasifikace je založena na metodě vyvinuté P. Northcottem v roce 2011. Výsledky: Od dubna 2015 do února 2019 bylo do naší studie zařazeno celkem 21 pacientů s MB. Medián věku pacienta v době diagnózy byl 6 let, zařazeno bylo 14 chlapců a 7 dívek. U pacientů bylo provedeno profilování genové exprese a následná molekulární klasifikace MB. Zjistili jsme, že nejčastěji zastoupená skupina MB byla skupina 4 (9 pacientů, 43 %), následovala skupina 3 (5 pacientů, 24 %), SHH aktivovaný MB (4 pacienti, 19 %) a nejméně zastoupenou skupinou byl WNT aktivovaný MB (3 pacienti, 14 %). Výsledky stanovení podskupiny MB byly úspěšně korelovány s histopatologickým nálezem a dalšími molekulárně genetickými vyšetřeními. Závěr: Molekulární klasifikace pacientů s MB, která byla zavedena na našem pracovišti, umožňuje lépe porozumět tomuto heterogennímu charakteru onemocnění a pomáhá v terapeutickém plánování.
Background: Medulloblastoma (MB) is the most common malignant tumour of the central nervous system in children. MB is considered to be high risk tumour propensity to metastasize. In the Czech Republic, approximately 10-12 children are affected annually by this tumour. Recent progress in molecular diagnostics helps to refine the diagnosis and estimate clinical prognosis of the disease. Currently, MBs are subclassified into WNT-activated, SHH-activated, group 3, and 4 based on molecular pathways that drive their tumorigenesis. Each subtype differs in its histopathology, clinical features, genomic changes and gene expressions. The aim of our study is to classify patient‘s MBs into four basic molecular groups and compare our results with published data. Material and methods: In our study we analysed expression profiles using Affymetrix GeneChip Human Gene 1.0. ST Array (Thermo Fisher Scientific, MA, USA). As input material RNA extracted from the fresh frozen tissue was used. Molecular classification based on the method established by P. Northcott in 2011 was performed. Results: From April 2015 to February 2019, 21 patients with MBs were included in our study. Median age of the patients at the time of diagnosis was 6 years, 14 boys and 7 girls were enrolled. Gene expression profiling and molecular classification of MBs was performed. Based on this methodology, we found the most frequently represented subgroup of MB was group 4 (9 patients, 43%), followed by group 3 (5 patients, 24%), SHH-activated MB (4 patients, 19%) and the least represented subgroup was WNT-activated MB (3 patients, 14%). Results of molecular subgroup classification of MBs were successfully correlated with histopathological findings and other molecular-genetic examinations. Conclusion: Molecular classification of MBs has been established in our institution allowing better understanding of this heterogeneous disease and helping clinicians in therapeutic planning in affected patients.
- MeSH
- dítě MeSH
- dospělí MeSH
- exprese genu MeSH
- individualizovaná medicína MeSH
- kojenec MeSH
- lidé MeSH
- meduloblastom diagnóza genetika MeSH
- mladiství MeSH
- předškolní dítě MeSH
- Check Tag
- dítě MeSH
- dospělí MeSH
- kojenec MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- předškolní dítě MeSH
- ženské pohlaví MeSH
- Publikační typ
- práce podpořená grantem MeSH
