Activating mutations in tyrosine kinase (TK) genes (e.g. FLT3 and KIT) are found in more than 30% of patients with de novo acute myeloid leukemia (AML); many groups have speculated that mutations in other TK genes may be present in the remaining 70%. We performed high-throughput re-sequencing of the kinase domains of 26 TK genes (11 receptor TK and 15 cytoplasmic TK) that are expressed in most AML patients, using genomic DNA from the bone marrow (tumor) and matched skin biopsy samples (germline) from 94 patients with de novo AML; sequence variants were validated in an additional 94 AML tumor samples (14.3 million base pairs of sequence were obtained and analyzed). We identified known somatic mutations in FLT3, KIT, and JAK2 TK genes at the expected frequencies, and found four novel somatic mutations, JAK1V623A, JAK1T478S, DDR1A803V and NTRK1S677N, once each in four respective patients out of 188 tested. We also identified novel germline sequence changes encoding amino acid substitutions (i.e. non-synonymous changes) in 14 TK genes, including TYK2, which had the largest number of non-synonymous sequence variants (11 total detected). Additional studies will be required to define the roles that these somatic and germline TK gene variants play in AML pathogenesis.
Somatic mutations and germline sequence variants in the expressed tyrosine kinase genes of patients with de novo acute myeloid leukemia.
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This SuperSeries is composed of the SubSeries listed below.
Enhancer sequence variants and transcription-factor deregulation synergize to construct pathogenic regulatory circuits in B-cell lymphoma.
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To better understand the pathogenesis of acute promyelocytic leukemia (APL, FAB M3 AML), we identified genes that are expressed differently in APL cells compared to other acute myeloid leukemia subtypes, and to normal promyelocytes. Comparative gene expression analysis of 14 M3, 62 other AML (M0, M1, M2 and M4) and 5 enriched normal promyelocyte samples revealed a signature of 1,121 genes that are specifically dysregulated in M3 samples relative to other AML, and that do not simply represent normal promyelocyte expression (M3-specific signature). We used a novel, high throughput digital platform (Nanostring's nCounter system) to evaluate a subset of the most significantly dysregulated genes in 30 AML samples; 33 of 37 evaluable gene expression patterns were validated. In an additional analysis, we selected only genes that are dysregulated in M3 both compared to other AML subtypes, and to purified normal CD34+ cells, promyelocytes, and/or neutrophils, thereby isolating a 478 gene "composite M3 dysregulome". Surprisingly, the expression of only a few of these genes was significantly altered in PR-9 cells after PML-RARA induction, suggesting that most of these genes are not direct targets of PML-RARA. Comparison of the M3-specific signature to our previously described murine APL dysregulome revealed 33 commonly dysregulated genes, including JUN, EGR1, and TNF. Collectively, these results suggest that PML-RARA initiates a transcriptional cascade which generates a unique downstream expression signature in both primary human and mouse APL cells.
High throughput digital quantification of mRNA abundance in primary human acute myeloid leukemia samples.
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This was a collaborative study to discover somatic mutations in 188 lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are likely to play a role in carcinogenesis. The observed mutational profiles correlate with clinical features, smoking status, and DNA repair defects. These results are complemented by data integration including SNP array data and gene expression array data (deposited here). Our findings shed further light on several key signaling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.
Somatic mutations affect key pathways in lung adenocarcinoma.
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Type 1 diabetes (T1D) is an autoimmune disease triggered by T cell reactivity to protein antigens produced by the -cells. Here we present a chronological compendium of transcriptional profiles from islets of Langerhans isolated from non-obese diabetic (NOD) mice ranging from 2 wks up to diabetes and compared to controls. Parallel analysis was made of cellular components of the islets. Myeloid cells populated the islets early during development in all mouse strains. This was followed by a type I interferon signature detectable at 4-6 wks of age only in diabetes susceptible mice. Concurrently, CD4 T cells were found within islets, many in contact with intra-islet antigen presenting cells. Early cellular signs of islet reactivity were detected by six wks. By 8 wks, NOD islets contained all major leukocytes populations and an inflammatory gene signature. This work establishes the natural transcriptional signature of T1D and provides a resource for future research.
Defining the transcriptional and cellular landscape of type 1 diabetes in the NOD mouse.
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The mechanism(s) for septic cardiomyopathy in humans is not known. To address this, we performed transcriptional profiling of hearts from patients who died from sepsis, in comparison to non-failing human donor hearts that could not be transplanted for technical reasons.
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Objective: To examine the changes in tibial plateau cartilage in relation to body mass index (BMI) in patients with end-stage osteoarthritis (OA). Design: Knees were obtained from 23 OA patients (3 non-obese, 20 obese) at the time of total knee replacement. RNA prepared from cartilage was probed for differentially expressed (DE) gene transcripts using RNA microarrays and validated via real-time PCR. Differences with regard to age, sex, and between medial and lateral compartments were also queried. Results: Microarrays revealed that numerous transcripts were significantly DE between non-obese and obese patients (1.5-fold) using pooled and separate data from medial and lateral compartments. Correlation analyses showed that 706 transcripts (459 positively, 247 negatively) were significantly correlated with BMI. Among these, HS3ST6, HSD17B12, and FAM26F were positively correlated while STAC3, PRSS21, and EDA were negatively correlated. Differentially correlated transcripts represented important biological processes e.g. cellular metabolic processes, anatomical structure morphogenesis and cellular response to growth factors. Although age and sex had some effect on transcript expression, most intriguing results were observed for comparison between medial and lateral compartments. Transcripts (MMP13, CLEC3A, MATN3, EPYC, SCARNA5, COL2A1) elevated in the medial compartment represented skeletal system development, cartilage development, collagen and proteoglycan metabolism, and extracellular matrix organization. Likewise, transcripts (SELE, CTSS, VSIG4, F13A1, and STEAP4) repressed in medial compartment represented host immune response, cell migration, wound healing, cell proliferation and response to cytokines. PCR data confirmed expression of DE transcripts. Conclusions: This study supports molecular interaction between obesity and OA and implies that BMI is an important determinant of transcript-level changes in cartilage.
No associated publication
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Germ free (GF) and conventionalized (CONV-D) wild-type C57Bl/6 male mice in the CARB-fed, 24h fasted, and 30d trained states; plus GF and CONV-D CARB-fed Ppara-/- mice. CARB-fed indicates a standard polysaccharide-rich mouse chow diet.
Regulation of myocardial ketone body metabolism by the gut microbiota during nutrient deprivation.
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Susceptible and Resistant mouse strain, e.g. DBA/2J and C57BL/6J respectively, were inoculated with a highly pathogenic H5N1 influenza A virus (A/Hong Kong/213/2003) for 72 hours.
Host genetic variation affects resistance to infection with a highly pathogenic H5N1 influenza A virus in mice.