Microdissected Pancreatic Cancer Whole Exome Sequencing
Ontology highlight
ABSTRACT: 109 micro-dissected pancreatic cancer cases and normal control tissue were subjected to whole-exome sequencing. Microdissection enriches tumor cellularity and enhances mutation calling.
SECONDARY ACCESSION(S): PRJNA289550PRJNA289549
REPOSITORIES: dbGaP
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Project description:Whole Exome Sequencing of Microdissected Pancreatic Cancer
| PRJNA289549 | ENA
Project description:Flow-sorted pancreatic acinar and ductal cells from fresh human pancreatic exocrine tissue were subjected to molecular characterization to identify lineage-specific expression and epigenetic properties. Cells of both lineages were cultured and transformed via lentiviral mutation to form pancreatic ductal adenocarcinoma.
2023-11-27 | GSE222990 | GEO
Project description:Flow-sorted pancreatic acinar and ductal cells from fresh human pancreatic exocrine tissue were subjected to molecular characterization to identify lineage-specific expression and epigenetic properties. Cells of both lineages were cultured and transformed via lentiviral mutation to form pancreatic ductal adenocarcinoma.
2023-11-27 | GSE223153 | GEO
Project description:Gene expression analyses of pancreatic adenocarcinoma and adjacent ductal epithelia from the same patient using bulk vs LCM dissected samples. Our results indicate that laser capture microdissection (LCM) is necessary to identify differentially expressed genes that discriminate between PDAC and healthy pancreatic ductal tissue.
2014-12-31 | GSE27890 | GEO
Project description:Gene expression analyses of pancreatic adenocarcinoma and adjacent ductal epithelia from the same patient using bulk vs LCM dissected samples. Our results indicate that laser capture microdissection (LCM) is necessary to identify differentially expressed genes that discriminate between PDAC and healthy pancreatic ductal tissue. Pancreatic tissues were collected at time of surgery and snap frozen in liquid nitrogen for RNA extraction and Affymetrix GeneChip Expression analyses.
2014-12-31 | E-GEOD-27890 | biostudies-arrayexpress
Project description:Background: Whole exome sequencing (WES) has been proven to serve as a valuable basis for various applications such as variant calling and copy number variation (CNV) analyses. For those analyses the read coverage should be optimally balanced throughout protein coding regions at sufficient read depth. Unfortunately, WES is known for its uneven coverage within coding regions due to GC-rich regions or off-target enrichment. Results: In order to examine the irregularities of WES within genes, we applied Agilent SureSelectXT exome capture on human samples and sequenced these via Illumina in 2x101 paired-end mode. As we suspected the sequenced insert length to be crucial in the uneven coverage of exome captured samples, we sheared 12 genomic DNA samples to two different DNA insert size lengths, namely 130 and 170 bp. Interestingly, although mean coverages of target regions were clearly higher in samples of 130 bp insert length, the level of evenness was more pronounced in 170 bp samples. Moreover, merging overlapping paired-end reads revealed a positive effect on evenness indicating overlapping reads as another reason for the unevenness. In addition, mutation analysis on a subset of the samples was performed. In these isogenic subclones almost twofold mutations were failed in the 130 bp samples when compared to the 170 bp samples. Visual inspection of the discarded mutation sites exposed low coverages at the sites embedded in high amplitudes of coverage depth in the affected region. Conclusions: Producing longer insert reads could be a good strategy to achieve better uniform read coverage in coding regions and hereby enhancing the effective sequencing yield to provide an improved basis for further variant calling and CNV analyses.
2016-07-28 | E-MTAB-4527 | biostudies-arrayexpress
Project description:<p>Pancreatic neuroendocrine tumors (PNETs), often referred to as "islet cell tumors", are neuroendocrine neoplasms that arise from cells of the endocrine and nervous system within the pancreas. These rare tumors which originate from the pancreatic islet are divided into many categories and are often classified by the hormone most strongly secreted. With the collaboration of the Elkins Pancreatic Center, the Human Genome Sequencing Center (HGSC) at Baylor College of Medicine had access to approximately 30 untreated tumor specimens and matched normal blood samples. Since the onset and progression of cancer is driven by extensive mutation of the genome, we are combining enrichment of exonic DNA with next generation sequencing to detect and characterize the somatic mutation profile of patients with pancreatic neuroendocrine cancer.</p> <p>This work was done at the Human Genome Sequencing Center (HGSC) in collaboration with the Elkins Pancreatic Center at Baylor College of Medicine in Houston, TX and was supported by grant number 5U54HG003273 from National Human Genome Research Institute (NHGRI).</p>
| phs000871 | dbGaP
Project description:Pancreatic ductal adenocarcinoma (PDA) has a dismal prognosis and insights into both disease etiology and targeted intervention are needed. A total of 109 micro-dissected PDA cases were subjected to whole-exome sequencing. Microdissection enriches tumour cellularity and enhances mutation calling. Here we show that environmental stress and alterations in DNA repair genes associate with distinct mutation spectra. Copy number alterations target multiple tumour suppressive/oncogenic loci; however, amplification of MYC is uniquely associated with poor outcome and adenosquamous subtype. We identify multiple novel mutated genes in PDA, with select genes harbouring prognostic significance. RBM10 mutations associate with longer survival in spite of histological features of aggressive disease. KRAS mutations are observed in >90% of cases, but codon Q61 alleles are selectively associated with improved survival. Oncogenic BRAF mutations are mutually exclusive with KRAS and define sensitivity to vemurafenib in PDA models. High-frequency alterations in Wnt signalling, chromatin remodelling, Hedgehog signalling, DNA repair and cell cycle processes are observed. Together, these data delineate new genetic diversity of PDA and provide insights into prognostic determinants and therapeutic targets.
| S-EPMC4403382 | biostudies-literature
Project description:Objectives: The aim of this study was to investigate the prognostic significance of thirteen anticancer drug-relevant solute carrier transporters (SLCs) in pancreatic cancer in the context of clinical-pathological characteristics and the KRAS mutation status of tumors. Methods: Tumors and non-neoplastic pancreatic tissues were obtained from 32 histologically verified patients with pancreatic ductal adenocarcinoma. The transcript profile of SLCs was assessed using quantitative real-time PCR. KRAS mutations in exon 2 were assessed by high resolution melting analysis and confirmed by sequencing. Results: SLC22A3 was upregulated and SLC22A1, SLC22A2, SLC22A11, SLC28A1, SLC28A3 and SLC29A1 were downregulated when compared with non-neoplastic pancreatic tissues. Moreover, significantly lower levels of SLC22A1, SLC22A11 and SLC29A1 were found in tumors with angioinvasion. There was also a significantly higher transcript level of SLC28A1 in tumors with regional lymph nodes affected by metastasis. The study found that a high expression of SLC22A1 or SLC28A1was significantly associated with poor overall survival in unselected patients. In contrast, a high expression of SLC22A3 or SLC29A3 was significantly associated with longer overall survival in patients treated with nucleoside analogs. Finally, SLC levels were not found to be associated with KRAS mutation status in exon 2. Conclusions: This study identified a number of associations of SLCs with prognosis of pancreatic cancer patients. Transcript levels of thirteen anticancer drug-relevant solute carrier transporters (SLCs) were determined by qPCR in pancreatic ductal adenocarcinomas and non-neoplastic tissue samples from 32 pancreatic cancer patients. MRPL19, ELF1 and POLR2A were used as reference genes for data normalization.
2013-06-30 | E-GEOD-47368 | biostudies-arrayexpress