12444 results for "cancer studies using rna-seq"

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• Genomic and epigenomic characterization of juvenile myelomonocytic leukemia (JMML)

  Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative disorder of early childhood. While some cases show spontaneous remission, allogeneic hematopoietic stem cell transplantation (HSCT) remains the only curative treatment option for the majority of patients, however, the 5-year event-free survival reaches only about 50%. Hyperactive RAS signaling is assumed to be the main driving event in JMML. It is caused by genetic alterations in CBL, KRAS, NF1, NRAS, or PTPN11 in about 90% of patients. So far, there is no clear understanding of how RAS pathway mutations relate to the heterogeneous disease biology and variable clinical outcome seen in JMML patients. As a consequence, established clinical and genetic markers fail to fully represent the observed disease heterogeneity. We hypothesized that DNA methylation profiling, either alone or in combination with genetic alterations, might provide a molecular basis for disease classification. Genome wide DNA methylation analysis using the HumanMethylation450 Bead Chip array was performed in a discovery cohort of 20 patients (19 JMML, 1 Noonan syndrome). The clinical relevance of our findings was assessed in an unselected sample set consisting of 147 consecutive patients with JMML (n=129) or Noonan syndrome (n=18) associated myeloproliferative disorder (n=18) registered in the EWOG-MDS 1998 & 2006 trials. Data integration was performed in a subset of patients with available exome sequencing (n=50) and expression profiling (n=15) data. This integrated approach identified three JMML subgroups characterized by distinct clinical and biological features. This analysis further suggested a molecular mechanism by which additional genetic events, presumably further activating the RAS-RAF-MEK-ERK pathway, mediate DNA hypermethylation via up-regulation of DNMTs in more aggressive JMML cases.

  Study EGAS00001002511

• MiR expression profiles of paired primary colorectal cancerand metastases by next-generation sequencing

  MicroRNAs (miRs) have been recognized as promising biomarkers. It is unknown to what extent tumor-derived miRs aredifferentially expressed between primary colorectal cancers (pCRCs) and metastatic lesions, and to what extent the expressionprofiles of tumor tissue differ from the surrounding normal tissue. Next-generation sequencing (NGS) of 220 fresh-frozen samples,including paired primary and metastatic tumor tissue and non-tumorous tissue from 38 patients, revealed expression of 2245known unique mature miRs and 515 novel candidate miRs. Unsupervised clustering of miR expression profiles of pCRC tissue withpaired metastases did not separate the two entities, whereas unsupervised clustering of miR expression profiles of pCRC withnormal colorectal mucosa demonstrated complete separation of the tumor samples from their paired normal mucosa. Twohundred and twenty-two miRs differentiated both pCRC and metastases from normal tissue samples (false discovery rate (FDR)o0.05). The highest expressed tumor-specific miRs were miR-21 and miR-92a, both previously described to be involved in CRC withpotential as circulating biomarker for early detection. Only eight miRs, 0.5% of the analysed miR transcriptome, were differentiallyexpressed between pCRC and the corresponding metastases (FDR o0.1), consisting of five known miRs (miR-320b, miR-320d,miR-3117, miR-1246 and miR-663b) and three novel candidate miRs (chr 1-2552-5p, chr 8-20656-5p and chr 10-25333-3p). Theseresults indicate that previously unrecognized candidate miRs expressed in advanced CRC were identified using NGS. In addition,miR expression profiles of pCRC and metastatic lesions are highly comparable and may be of similar predictive value for prognosisor response to treatment in patients with advanced CRC

  Study EGAS00001001127

• Genome wide association study on coronary heart disease in patients with familial hypercholesterolemia

  Mutations in the low-density lipoprotein receptor (LDLR) gene cause familial hypercholesterolemia (FH), a disorder characterized by coronary heart disease (CHD) at young age. We aimed to apply an extreme sampling method to enhance the statistical power to identify novel genetic risk variants for CHD in individuals with FH. We selected cases and controls with an extreme contrast in CHD risk from 17 000 FH patients from the Netherlands, whose functional LDLR mutation was unequivocally established. The genome-wide association (GWA) study was performed on 249 very young FH cases with CHD and 217 old FH controls without CHD (above 65 years for males and 70 years of age for females) using the Illumina HumanHap 550K chip. In the next stage, two independent samples (one from the Netherlands and one from Italy, Norway, Spain, and the United Kingdom) of FH patients were used as replication samples. In the initial GWA analysis we identified 29 independent single nucleotide polymorphisms (SNPs) with suggestive associations with premature CHD (p<1×10-4). We examined the association of these SNPs with CHD risk in the replication samples. After Bonferroni correction, none of the SNPs either replicated or reached genome-wide significance after combining the discovery and replication samples. Therefore, we conclude that the genetics of CHD risk in FH is complex and even applying an ‘extreme genetics’ approach we did not identify new genetic risk variants. Most likely, this method is not as effective in leveraging effect size as anticipated, and may therefore not lead to significant gains in statistical power. (NB submitten and conditionally accepted at European Journal of Human Genetics-please use abstract only for internal review until submission complete)

  Study EGAS00001000734

• Genesis of Two Most Prevalent Variants Causing Combined Pituitary Hormone Deficiency in 21 Populations

  Two variants (c.[301_302delAG];[301_302delAG] and c.[150delA];[150delA]) in the PROP1 gene are the most common genetic causes of recessively inherited combined pituitary hormones deficiency (CPHD). Our objective was to analyze in detail the origin of the two most prevalent variants. In the multicentric study were included 237 patients with CPHD and their 15 relatives carrying c.[301_302delAG];[301_302delAG] or c.[150delA];[150delA] or c.[301_302delAG];[ 150delA]. They originated from 21 different countries worldwide. We genotyped 21 single nucleotide variant markers flanking the 9.6Mb region around the PROP1 gene that are not in mutual linkage disequilibrium in the general populations - a finding of a common haplotype would be indicative of ancestral origin of the variant. Haplotypes were reconstructed by Phase and Haploview software, and the variant age was estimated using an allelic association method. We demonstrated ancestral origin of both variants: c.[301_302delAG] was carried on 0.2Mb-long haplotype in a majority of European patients arising approximately 101 generations ago (confidence interval 90.1-116.4). Patients from the Iberian Peninsula displayed a different haplotype which was estimated to have emerged 23.3 (20.1-29.1) generations ago. Subsequently, the data indicated that both haplotypes were transmitted to Latin American patients approximately 13.8 (12.2-17.0) and 16.4 (14.4-20.1) generations ago, respectively. The c.[150delA] variant that was carried on a haplotype spanning about 0.3Mb was estimated to appear 43.7 (38.4-52.7) generations ago. We present strong evidence that the most frequent variants in the PROP1 gene are not a consequence of variant hot-spots as previously assumed, but are founder variants.

  Study EGAS00001001165

• An integrative model of pathway convergence in genetically heterogeneous blast crisis chronic myeloid leukemia (CML)

  Targeted therapies against the BCR-ABL1 kinase have revolutionized treatment of chronic phase (CP) chronic myeloid leukemia (CML). In contrast, management of blast crisis (BC) CML remains challenging because BC cells acquire complex molecular alterations that confer stemness features to progenitor populations and resistance to BCR-ABL1 tyrosine kinase inhibitors. Comprehensive models of BC transformation have proved elusive because of the rarity and genetic heterogeneity of BC, but are important for developing biomarkers predicting BC progression and effective therapies. To better understand BC, we performed an integrated multiomics analysis of 74 CP and BC samples using whole-genome and exome sequencing, transcriptome and methylome profiling, and chromatin immunoprecipitation followed by high-throughput sequencing. Employing pathway-based analysis, we found the BC genome was significantly enriched for mutations affecting components of the polycomb repressive complex (PRC) pathway. While transcriptomically, BC progenitors were enriched and depleted for PRC1- and PRC2-related gene sets respectively. By integrating our data sets, we determined that BC progenitors undergo PRC-driven epigenetic reprogramming toward a convergent transcriptomic state. Specifically, PRC2 directs BC DNA hypermethylation, which in turn silences key genes involved in myeloid differentiation and tumor suppressor function via so-called epigenetic switching, whereas PRC1 represses an overlapping and distinct set of genes, including novel BC tumor suppressors. On the basis of these observations, we developed an integrated model of BC that facilitated the identification of combinatorial therapies capable of reversing BC reprogramming (decitabine+PRC1 inhibitors), novel PRC-silenced tumor suppressor genes (NR4A2), and gene expression signatures predictive of disease progression and drug resistance in CP.

  Study EGAS00001001751

• A reference map of potential determinants for the human serum metabolome

  The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

  Study EGAS00001004512

• Immune microenvironment and lineage tracing help deciphering Rosette-forming GlioNeuronal Tumors: a multi-omic analysis of 9 cases

  Rosette-forming GlioNeuronal Tumor (RGNT) is a rare central nervous system neoplasm containing two components, glial and neuronal. The delineation of histological diagnosis of RGNT from similar low-grade tumors such as pilocytic astrocytoma (PA) and ganglioglioma (GG) may be challenging. We performed here a comprehensive molecular analysis of a cohort of tumors with same histology features to identify molecular characteristics of RGNT. A cohort of 9 rosette-forming tumors histologically-diagnosed were analyzed at molecular level using multimodal approaches as Whole Exome Sequencing (WES), RNAseq and methylome. In our cohort, 3 tumors were plotted within the Methylation Class-RGNT (MC-RGNT) characterized by FGFR1 mutation associated with PIK3CA or NF1 mutations. Transcriptome analysis was performed in 7 cases. RNAseq identified a “Hot” and a “Cold” transcriptomic group; the latter includes the 3 MC-RGNT and 1 MC-Pilocytic Astrocytoma and exhibited a “Cold” immune tumor microenvironment in comparison with the “Hot” group. The distinct immune cell content of both groups was confirmed by quantitative immunostainings. Get Set Enrichment Analysis showed that the “Cold” group had upregulated NOTCH pathway and mainly oligodendrocyte precursor cell and neuronal phenotypes while the “Hot” group exhibited predominantly astrocytic and neural stem cell phenotypes. In silico deconvolution identified the cerebellar granule cell lineage as a putative origin and as the cell context to understand the effects of genetic alterations and NOTCH signaling. Histological diagnosis of rosette-forming tumors encompasses heterogeneous tumor entities. Our study identified distinct tumor cell contexts and microenvironments as key features to better understand and manage these neoplasms.

  Study EGAS00001006502

• Genetic heritage of the Baphuthi highlights an over-ethnicised notion of 'Bushman' in the Maloti-Drakensberg, southern Africa

  Using contemporary people as proxies for ancient communities is a contentious but necessary practice in anthropology. In southern Africa, the distinction between the Cape KhoeSan and eastern KhoeSan remains unclear as ethnicity labels have been changed through time and most communities were decimated if not extirpated. The eastern KhoeSan may have had genetic distinctions from neighbouring communities who speak Bantu languages and KhoeSan further away, alternatively the identity may not have been tied to any notion of biology, instead denoting communities with a nomadic 'lifeway' distinct from African agro-pastoralism. The Baphuthi of the 1800s in the Maloti-Drakensberg, southern Africa had a substantial KhoeSan constituency and a lifeway of nomadism, cattle raiding, and horticulture. Baphuthi heritage could provide insights into the history of the eastern KhoeSan. We examine genetic affinities of 23 Baphuthi to discern whether the narrative of KhoeSan descent reflects distinct genetic ancestry. Genome-wide SNP data (Illumina GSA) were merged with 52 global populations, for 160K SNPs. Genetic analyses show no support for a unique eastern KhoeSan ancestry distinct from other KhoeSan or southern Bantu-speakers. The Baphuthi have strong affinities with early-arriving southern Bantu-speaking (Nguni) communities, as the later-arriving non-Nguni show strong evidence of recent African admixture possibly related to Late-Iron Age migrations. The references to communities as 'San',and 'Bushman' in historic literature has often been misconstrued as notions of ethnic/biological distinctions. The terms may have reflected ambiguous references to non-sedentary polities instead, as seems to be the case for the eastern ‘Bushman’ heritage of the Baphuthi.

  Study EGAS00001007080

• IL7-receptor expression is frequent in T-cell acute lymphoblastic leukemia and predicts sensitivity to JAK-inhibition

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy with a dismal prognosis related to refractory/relapsing diseases, raising the need for new targeted-therapies. Activating mutations of the IL7-receptor pathway genes (IL7Rp) play a proven leukemia-supportive role in T-ALL. JAK-inhibitors such as ruxolitinib have recently demonstrated preclinical efficacy. However, prediction markers for sensitivity to JAK-inhibitors are still lacking. Herein, we show that IL7R (CD127) expression is more frequent (~70%) than IL7Rp-mutations in T-ALL (~30%). We compared the so-called non-expressers (no IL7R-expression/IL7Rp-mutation), expressers (IL7R-expression without IL7Rp-mutation) and mutants (IL7Rp-mutations). Integrative multi-omics analysis outlined IL7R-deregulation in virtually all T-ALL subtypes, at the epigenetic-level in non-expressers, genetic-level in mutants, and post-transcriptional level in expressers. Ex-vivo data using primary-derived xenografts support that IL7Rp is functional whenever the IL7R is expressed, regardless of the IL7Rp mutational status. Consequently, ruxolitinib impaired T-ALL survival in both expressers and mutants. Interestingly, we show that expressers displayed ectopic IL7R-expression and IL7Rp-addiction conferring a deeper sensitivity to ruxolitinib. Conversely, mutants were more sensitive to venetoclax than expressers. Overall, combination of ruxolitinib and venetoclax resulted in synergistic effects in both groups. We illustrate the clinical relevance of this association by reporting achievement of complete remission in two patients with refractory/relapsed-T-ALL. This provides proof of concept for translation of this strategy into clinics as bridge to transplant. Altogether, IL7R-expression can be used as a biomarker for sensitivity to JAK-inhibition, thereby expanding the fraction of T-ALL patients eligible to ruxolitinib up to nearly ~70% of T-ALL.

  Study EGAS00001007144

• Ultra-fast deep-learned pediatric CNS tumor classification.

  The primary treatment of CNS tumors starts with a neurosurgical resection in order to obtain tumor tissue for diagnosis and to reduce tumor load and mass effect. The neurosurgeon has to decide between radical resection versus a more conservative strategy to prevent surgical morbidity. The prognostic impact of a radical resection varies between tumor types. However due to a lack of pre-operative tissue-based diagnostics, limited knowledge of the precise tumor type is available at the time of surgery. Current standard practice includes preoperative imaging and intraoperative histological analysis, but these are not always conclusive. After surgery, histopathological and molecular tests are performed to diagnose the precise tumor type. The results may indicate that an additional surgery is needed or that the initial surgery could have been less radical. Using rapid Nanopore sequencing, a sparse methylation profile can be directly obtained during surgery, making it ideally suited to enable intraoperative diagnostics. We developed a state-of-the-art neural-network approach called Sturgeon, to deliver trained models that are lightweight and universally applicable across patients and sequencing depths. We demonstrate our method to be accurate and fast enough to provide a correct diagnosis with as little as 20 to 40 minutes of sequencing data in 45 out of 49 pediatric samples, and inconclusive results in the other four. In four intraoperative cases we achieved a turnaround time of 60-90 minutes from sample biopsy to result; well in time to impact surgical decision making. We conclude that machine-learned diagnosis based on intraoperative sequencing can assist neurosurgical decision making, allowing neurological comorbidity to be avoided or preventing additional surgeries.

  Study EGAS00001007475