166 research outputs found

    When Should One Substract Background Fluorescence in Two Color Microarrays?

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    Two color microarrays are a powerful tool for genomic analysis, but have noise components that make inferences regarding gene expression inefficient and potentially misleading. Background fluorescence,whether attributable to non-specific binding or other sources,is an important component of noise. The decision to subtract fluorescence surrounding spots of hybridization from spot fluorescence has been controversial, with no clear criteria for determining circumstances that may favor, or disfavor, background subtraction. While it is generally accepted that subtracting background reduces bias but increases variance in the estimates of the ratios of interest, no formal analysis of the bias-variance trade off of background subtraction has been undertaken. In this paper, we use simulation to systematically examine the bias-variance trade off under a variety of possible experimental conditions. Our simulation is based on data obtained from two self versus self microarray experiments and is free of distributional assumptions. Our results identify factors that are important for determining whether to background subtract, including the correlation of foreground to background intensity ratios. Using these results we develop recommendations for diagnostic visualizations that can help decisions about background subtraction

    Cronkhite-Canada Syndrome: Gastric Involvement Diagnosed by MDCT

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    Chronkhite-Canada is a rare nonfamilial polyposis syndrome that usually presents as chronic malabsorption in adults. We present a case of a-73-year old woman with chronic gastrointestinal bleeding and malnutrition. On CT imaging she was found to have massive gastric polyps, which on biopsy was most consistent with Cronkhite-Canada syndrome

    Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma

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    Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease with a 5-year survival of 4%. A key hallmark of PDAC is extensive stromal involvement, which makes capturing precise tumor-specific molecular information difficult. Here, we have overcome this problem by applying blind source separation to a diverse collection of PDAC gene expression microarray data, which includes primary, metastatic, and normal samples. By digitally separating tumor, stroma, and normal gene expression, we have identified and validated two tumor-specific subtypes including a “basal-like” subtype which has worse outcome, and is molecularly similar to basal tumors in bladder and breast cancer. Furthermore, we define “normal” and “activated” stromal subtypes which are independently prognostic. Our results provide new insight into the molecular composition of PDAC which may be used to tailor therapies or provide decision support in a clinical setting where the choice and timing of therapies is critical

    Cross-platform Comparison of Two Pancreatic Cancer Phenotypes

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    Model-based approaches for combining gene expression data from multiple high throughput platforms can be sensitive to technological artifacts when the number of samples in each platform is small. This paper proposes simple tools for quantifying concordance in a small study of pancreatic cancer cells lines with an emphasis on visualizations that uncover intra- and inter-platform variation. Using this approach, we identify several transcripts from the integrative analysis whose over-or under-expression in pancreatic cancer cell lines was validated by qPCR

    Widespread somatic L1 retrotransposition occurs early during gastrointestinal cancer evolution

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    Somatic L1 retrotransposition events have been shown to occur in epithelial cancers. Here, we attempted to determine how early somatic L1 insertions occurred during the development of gastrointestinal (GI) cancers. Using L1-targeted resequencing (L1-seq), we studied different stages of four colorectal cancers arising from colonic polyps, seven pancreatic carcinomas, as well as seven gastric cancers. Surprisingly, we found somatic L1 insertions not only in all cancer types and metastases but also in colonic adenomas, well-known cancer precursors. Some insertions were also present in low quantities in normal GI tissues, occasionally caught in the act of being clonally fixed in the adjacent tumors. Insertions in adenomas and cancers numbered in the hundreds, and many were present in multiple tumor sections, implying clonal distribution. Our results demonstrate that extensive somatic insertional mutagenesis occurs very early during the development of GI tumors, probably before dysplastic growth

    Genotype tunes pancreatic ductal adenocarcinoma tissue tension to induce matricellular fibrosis and tumor progression

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    Fibrosis compromises pancreatic ductal carcinoma (PDAC) treatment and contributes to patient mortality yet anti-stromal therapies are controversial. We found that human PDACs with impaired epithelial transforming growth factor β (TGF-β) signaling have elevated epithelial Stat3 activity and develop a stiffer, matricellular-enriched fibrosis associated with high epithelial tension and shorter patient survival. In several Kras-driven mouse models, both the loss of TGF-β signaling and elevated β1-integrin mechanosignaling engaged a positive feedback loop whereby Stat3 signaling promotes tumor progression by increasing matricellular fibrosis and tissue tension. In contrast, epithelial Stat3 ablation attenuated tumor progression by reducing the stromal stiffening and epithelial contractility induced by loss of TGF-β signaling. In PDAC patient biopsies, higher matricellular protein and activated Stat3 associated with SMAD4 mutation and shorter survival. The findings implicate epithelial tension and matricellular fibrosis in the aggressiveness of SMAD4 mutant pancreatic tumors, and highlight Stat3 and mechanics as key drivers of this phenotype

    HMGA1 Induces Intestinal Polyposis in Transgenic Mice and Drives Tumor Progression and Stem Cell Properties in Colon Cancer Cells

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    Although metastatic colon cancer is a leading cause of cancer death worldwide, the molecular mechanisms that enable colon cancer cells to metastasize remain unclear. Emerging evidence suggests that metastatic cells develop by usurping transcriptional networks from embryonic stem (ES) cells to facilitate an epithelial-mesenchymal transition (EMT), invasion, and metastatic progression. Previous studies identified HMGA1 as a key transcription factor enriched in ES cells, colon cancer, and other aggressive tumors, although its role in these settings is poorly understood.To determine how HMGA1 functions in metastatic colon cancer, we manipulated HMGA1 expression in transgenic mice and colon cancer cells. We discovered that HMGA1 drives proliferative changes, aberrant crypt formation, and intestinal polyposis in transgenic mice. In colon cancer cell lines from poorly differentiated, metastatic tumors, knock-down of HMGA1 blocks anchorage-independent cell growth, migration, invasion, xenograft tumorigenesis and three-dimensional colonosphere formation. Inhibiting HMGA1 expression blocks tumorigenesis at limiting dilutions, consistent with depletion of tumor-initiator cells in the knock-down cells. Knock-down of HMGA1 also inhibits metastatic progression to the liver in vivo. In metastatic colon cancer cells, HMGA1 induces expression of Twist1, a gene involved in embryogenesis, EMT, and tumor progression, while HMGA1 represses E-cadherin, a gene that is down-regulated during EMT and metastatic progression. In addition, HMGA1 is among the most enriched genes in colon cancer compared to normal mucosa.Our findings demonstrate for the first time that HMGA1 drives proliferative changes and polyp formation in the intestines of transgenic mice and induces metastatic progression and stem-like properties in colon cancer cells. These findings indicate that HMGA1 is a key regulator, both in metastatic progression and in the maintenance of a stem-like state. Our results also suggest that HMGA1 or downstream pathways could be rational therapeutic targets in metastatic, poorly differentiated colon cancer

    Processed pseudogenes acquired somatically during cancer development.

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    Cancer evolves by mutation, with somatic reactivation of retrotransposons being one such mutational process. Germline retrotransposition can cause processed pseudogenes, but whether this occurs somatically has not been evaluated. Here we screen sequencing data from 660 cancer samples for somatically acquired pseudogenes. We find 42 events in 17 samples, especially non-small cell lung cancer (5/27) and colorectal cancer (2/11). Genomic features mirror those of germline LINE element retrotranspositions, with frequent target-site duplications (67%), consensus TTTTAA sites at insertion points, inverted rearrangements (21%), 5' truncation (74%) and polyA tails (88%). Transcriptional consequences include expression of pseudogenes from UTRs or introns of target genes. In addition, a somatic pseudogene that integrated into the promoter and first exon of the tumour suppressor gene, MGA, abrogated expression from that allele. Thus, formation of processed pseudogenes represents a new class of mutation occurring during cancer development, with potentially diverse functional consequences depending on genomic context
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