Expression data from short-time cultured primary cells derived from colorectal adenocarcinoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE13059 | GEO | 2008/10/07
SECONDARY ACCESSION(S): PRJNA109979
REPOSITORIES: GEO
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Project description:Time course comparison to tissue origin and with control cell line HT29 derived from colorectal adenocarcinoma. Status of expression pattern is different in adenocarcinoma of each patient. Human tumor cells extensively changes their gene- and protein expression patterns during their cultivation, clonal selection and expansion, thereby loosing many of the characteristics of their primary origin. In this study we analyzed if these expression changes could be circumvented by using short-term primary cell culture models derived from colorectal cancer patients. We compared several primary cells from tumor tissues using a standardized protocol which yielded similar cell populations. For monitoring the gene expression changes induced by cell preparation and cultivation we collected the tissues immediately after resection and isolated cells before seeding, and after 24 and 72 hours of cultivation from each patient. Experiment Overall Design: Reference tissue, viable primary cells, and cells of cell line HT29 were selected at indicated times, total RNA's were preparated and amplified to biotinylated cRNA for microarray analysis using high-density HG-U133plus 2.0 GeneChips® from Affymetrix.
2008-10-26 | E-GEOD-13059 | biostudies-arrayexpress
Project description:Despite advances in contemporary chemotherapeutic strategies, long term survival still remains elusive for patients with metastatic colorectal cancer. A better understanding of the molecular markers of drug sensitivity to match therapy with patient is needed to improve clinical outcomes. In this study, we used in vitro drug sensitivity data from the NCI-60 cell lines together with their Affymetrix microarray data to develop a gene expression signature to predict sensitivity to oxaliplatin. In order to validate our oxaliplatin sensitivity signature, Patient-Derived Colorectal Cancer Explants (PDCCEs) were developed in NOD-SCID mice from resected human colorectal tumors. Analysis of gene expression profiles found similarities between the PDCCEs and their parental human tumors, suggesting their utility to study drug sensitivity in vivo. The oxaliplatin sensitivity signature was then validated in vivo with response data from 14 PDCCEs treated with oxaliplatin and was found to have an accuracy of 92.9% (Sensitivity=87.5%; Specificity=100%). Our findings suggest that PDCCEs can be a novel source to study drug sensitivity in colorectal cancer. Furthermore, genomic-based analysis has the potential to be incorporated into future strategies to optimize individual therapy for patients with metastatic colorectal cancer. Fourty-two human tumors and murine explants of colorectal origin, both primary colon and of various metastatic sites, were processed for total RNA. The samples included RNA from 14 patient samples in addition to RNA from Patient-Derived Colorectal Cancer Explant (PDCCEs) generated from these 14 patient samples. The PDCCEs were processed as fresh frozen whole tumor in addition to formalin-fixed paraffin-embedded (FFPE) tumors.
2012-02-17 | E-GEOD-28691 | biostudies-arrayexpress
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Project description:Pulmonary enteric adenocarcinoma (PEAD) is a rare non-small cell lung cancer subtype. It is poorly characterized and cannot be distinguished from metastatic colorectal or upper gastrointestinal adenocarcinomas (ADCs) by means of routine pathological methods. As DNA methylation patterns are known to be highly tissue specific, we aimed to develop a methylation-based algorithm to differentiate these entities. To this end, genome wide methylation profiles of 600 primary pulmonary, colorectal and upper gastrointestinal ADCs obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database were used as a reference cohort to train a machine learning algorithm. The resulting classifier correctly classified all samples from a validation cohort consisting of 680 primary pulmonary, colorectal and upper gastrointestinal ADCs from TCGA and the GEO database, demonstrating the ability of the algorithm to reliably distinguish these three entities. We then analyzed DNA methylation data of 15 PEADs as well as four pulmonary metastases and four primary colorectal ADCs with the algorithm. All 15 PEADs were reliably classified as primary pulmonary tumors and all four metastases as well as all four primary colorectal ADC samples were identified as primary colorectal ADCs. In a t-distributed stochastic neighbor embedding analysis, the PEAD samples did not form a separate methylation subclass but rather diffusely intermixed with other pulmonary ADCs. Additional characterization of the PEAD series using fluorescence in-situ hybridization, next generation sequencing and copy number analysis revealed KRAS mutations in nine of 15 samples (60%) and a high number of structural chromosomal changes. Except for an unusually high rate of chromosome 20 gain (66.7%) the molecular data was mostly reminiscent of standard pulmonary ADCs. In conclusion, we provide sound evidence of the pulmonary origin of PEAD and in addition provide a publicly available machine learning based algorithm to reliably distinguish PEAD from metastatic colorectal cancer and upper gastrointestinal adenocarcinomas.
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Project description:Altered chromatin structure is a hallmark of cancer, and inappropriate regulation of chromatin structure may represent the origin of transformation. Several important studies have mapped human nucleosome distributions genome wide, but the genome-wide role of chromatin structure in cancer progression has not been addressed. We developed a MNase-Sequence Capture method, mTSS-seq, to map genome-wide nucleosome distribution in primary human lung and colon adenocarcinoma tissue. Here, we confirm that nucleosome redistribution is an early, widespread event in lung (LAC) and colon (CRC) adenocarcinoma. These altered nucleosome architectures are consistent between LAC and CRC patient samples indicating that they may serve as important early adenocarcinoma markers. We demonstrate that the nucleosome alterations are driven by the underlying DNA sequence and potentiate transcription factor binding. We conclude that DNA-directed nucleosome redistributions are widespread early in cancer progression. We have proposed an entirely new hierarchical model for chromatin-mediated genome regulation. â Nucleosome distribution mapping in primary patient tissue at all transcription start sites in the human genome Please note that two processed data files '4137N_ALLcombined.bed' and '4137T_ALLcombined.bed' (linked as Series supplementary file) are processed bed files combined from three 4137N_*_hiseq samples (total 6 raw data files) and three 4137T_*_hiseq samples (total 6 raw data files), respectively.
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2010-07-07 | E-GEOD-10179 | biostudies-arrayexpress
Project description:Most cancer deaths are caused by metastasis but understanding how metastatic cancers adapt from their origin tissues to their target tissues remains a fundamental challenge. Here, we ask if the gene expression of primary and metastatic tumors is more similar to their tissue of origin or to their target tissue. We analyzed the gene expression profiles of both paired and unpaired primary and metastatic tumor patient cohorts across multiple cancer types, studying single-cell and bulk RNA-seq data. To quantify the similarities between tumor samples and their normal, noncancerous origin and targeted tissues, we computed the Euclidean distance between their expression profiles, termed their transcriptomic distances, at the whole-genome and pathway levels. While the expression of most primary tumors is more similar to origin than to their target tissues, the expression patterns of metastases shift towards their target tissue. In specific cases, we chart the alterations occurring at the pathway level, pointing to key adaptive transcriptomic changes. Notably, our analysis indicates that primary cancers across several cancer types are primed for metastasis before the process begins. We further reproduce our findings using a new, unpublished RNA-seq data from colorectal cancer patients with liver metastases This first of its kind systematic analysis of the expression landscape of primary tumors and metastases with respect to their normal origin and target tissues provides a transcriptomic-wide view of cancer tumors adaptations to their metastatic niches
2024-10-21 | GSE245351 | GEO
Project description:Barrett's esophagus transcriptome was analysed and compared with Barrett's esophagus primary cell culture and esophageal adenocarcinoma. Keywords: SAGE analysis to compare tissues Barrett's esophagus biopsy was taken from 1 male metaplastic Barrett's esophagus patient. Barrett's esophagus primary cell culture was cultures from a biopsy taken from a Barrett's esophagus patient and cultured for about 4 to 5 weeks. Esophageal adenocarcinoma was taken from a patient known to have cancer and previously Barrett's esophagus
2006-06-28 | E-GEOD-5155 | biostudies-arrayexpress
Project description:Background: Fatal cancer is often the result of spread, or metastasis, of a cancer cell from the site of its origin to a distant anatomic site. While the metastatic process and the foreign environment of the metastatic site impact a tumorâ??s biology, we continue to determine therapy for patients based upon their cancerâ??s site of origin. We have performed an unbiased analysis across metastatic solid tumors from common primary sites to determine the molecular impact of the metastatic process on site-specific biology and to identify novel therapeutic strategies. Methods: Global gene expression was used as a biological phenotype to perform a top-down analysis of 96 metastatic human tumors. Laser capture microdissection, RNA amplification, and microarray analysis were used to measure the transcription patterns of malignant epithelial cells. Genes, multi-gene expression â??signaturesâ??, and pathways associated with site of origin (SOO) and site of metastases (SOM) were identified using established computational approaches. SOO and SOM expression signatures were validated on multiple, independent datasets comprising 1217 samples (1104 samples from GSE2109 (Expression Project for Oncology) and 113 samples from GSE12630 (Monzon FA, Lyons-Weiler M, Buturovic LJ, Rigl CT et al. Multicenter validation of a 1,550-gene expression profile for identification of tumor tissue of origin. J Clin Oncol 2009 May 20;27(15):2503-8. PMID: 19332734). Reverse phase proteomics and in vitro tissue culture were used to validate associations between biological pathways, site of primary, and implicated therapeutic combinations. Findings: SOO has the dominant influence on solid tumor biology as samples segregate based upon their primary site during unsupervised hierarchical clustering. In addition, statistically significant associations are identified between single genes and pathways and each primary site investigated and SOO signatures for colon, breast, ovary, lung, and prostate cancers accurately identify primary site for independent samples of both local and metastatic tumors independent of degree of histological differentiation. The impact of SOM on tumor biology is evident as genes and pathways are significantly associated with metastatic site and SOM signatures can be generated but they are not strongly predictive when applied to localized tumors. Pathway analysis identified relatively increased expression of MYC, beta-catenin, and SRC gene sets in metastatic colorectal cancers which was confirmed with proteomic analysis of a sub-set of the original tumors. Within colorectal cancers, high SRC expression also correlates with predicted oxaliplatin sensitivity and the combination of an SRC inhibitor with oxaliplatin demonstrated synergy in three independent colorectal cancer cell lines. Interpretation: Our findings suggest that the complex alterations required for metastasis do not obscure the impact of a cancer cellâ??s origin. SOO signatures have the potential to be highly accurate diagnostic tools and the underlying site-specific biology can be used to identify novel therapeutic targets for advanced cancers. Keywords: Gene expression analysis Ninety-six laser capture microdissected adenocarcinoma patient tumor samples of various primary and metastatic sites were processed for Total RNA. Our 96-sample datatset was enriched by inclusion of previously deposited microarray data in GEO (reprocessed for this study): A total of 1217 samples (1104 samples from GSE2109, 113 samples from GSE12630) were reprocessed from the CEL files using RMA. Supplementary files: The reprocessed data matrices. A list of the 1217 Samples' GSM accession numbers and the corresponding reprocessed sample IDs.
2016-02-13 | E-GEOD-18549 | biostudies-arrayexpress