Dataset Information

Global comparative gene expression analysis of melanoma patient samples, derived cell lines and corresponding tumor xenografts.

ABSTRACT: Various in vitro and in vivo experimental models have been used for the discovery of genes and pathways involved in melanoma and other types of cancer. However, in many cases, the results from various tumor models failed to be validated successfully in clinical studies. Limited information is available on how closely these models reflect the in vivo physiological conditions. In this study, a comprehensive genomics approach was used to systematically compare the expression patterns of snap frozen samples obtained from patients with primary melanoma, lymph node metastasis, and distant metastases, and compare these patterns to those of their corresponding cell lines and tumor xenografts in nude mice. The GE Healthcare 20k human genome array was used and the expression data was normalized and analyzed using GeneSpring 7.2 software. Based on the expression analysis, the correlation rate between the snap frozen primary patient samples vs. derived cell lines was 66%, with 1687 differentially expressed genes. The correlation rate between the snap frozen primary patient samples and the tumor xenografts was 75%, with 1,374 differentially expressed genes, and the correlation rate comparing tumor xenografts to derived cell lines ranged between 58% and 84%. These results demonstrated significant gene expression differences between tumor materials with different in vitro and in vivo growth microenvironments. Such studies can help us to distinguish between genes up- or down-regulated as a result of the microenvironment and those stably expressed independently of the tumor milieu. With the extensive use of cell lines and xenografts in cancer research, the information obtained using our approach may help to better interpret results generated from different tumor models by understanding common differences, as well as similarities at the gene expression level, information that may have important practical and biological implications.

SUBMITTER: Xi Y

PROVIDER: S-EPMC3226839 | biostudies-literature | 2008 Jan-Feb

REPOSITORIES: biostudies-literature

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Global comparative gene expression analysis of melanoma patient samples, derived cell lines and corresponding tumor xenografts.

Xi Yaguang Y Riker Adam A Shevde-Samant Lalita L Samant Rajeev R Morris Christopher C Gavin Elaine E Fodstad Oystein O Ju Jingfang J

Cancer genomics & proteomics 20080101 1

Various in vitro and in vivo experimental models have been used for the discovery of genes and pathways involved in melanoma and other types of cancer. However, in many cases, the results from various tumor models failed to be validated successfully in clinical studies. Limited information is available on how closely these models reflect the in vivo physiological conditions. In this study, a comprehensive genomics approach was used to systematically compare the expression patterns of snap frozen ...[more]

PMID: 18359977

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Project description:Patient-derived xenograft (PDX) models have been recognized as being more suitable for predicting therapeutic efficacy than cell-culture models. However, there are several limitations in applying PDX models in preclinical studies, including their availability-especially for cancers such as gastric cancer-that are not frequently encountered in Western countries. In addition, the differences in morphology between primary, PDX, and tumor cell line-derived xenograft (CDX) models have not been well established. In this study, we aimed to establish a series of gastric cancer PDXs and cell-lines from a relatively large number of gastric cancer patients. We also investigated the clinicopathological factors associated with the establishment of PDX and CDX models, and compared the histology between the primary tumor, PDX, and CDX that originated from the same patient. We engrafted 232 gastric cancer tissues into immune-deficient mice subcutaneously and successfully established 35 gastric cancer PDX models (15.1% success rate). Differentiated type adenocarcinomas (DAs, 19.4%) were more effectively established than poorly differentiated type adenocarcinomas (PDAs, 10.8%). For establishing CDXs, the success rate was less influenced by histological differentiation grade (DA vs. PDA, 12.1% vs. 9.8%). In addition, concordance of histological differentiation grade between primary tumors and PDXs was significant (p < 0.01), while concordance between primary tumors and CDXs was not. Among clinicopathological factors investigated, pathological nodal metastasis status (pN) was significantly associated with the success rate of PDX establishment. Although establishing cell lines from ascites fluid was more efficient (41.2%, 7/17) than resected tissues, it should be noted that all CDXs from ascites fluid had the PDA phenotype. In conclusion, we established 35 PDX and 32 CDX models from 249 gastric cancer patients; among them, 21 PDX/CDX models were established from the same patients. Our findings may provide helpful insights for establishing PDX and CDX models not only from gastric but from other cancer types, as well as select preclinical models for developing new therapeutics.

Project description:Esophageal Squamous Cell Carcinoma (ESCC) is the predominant type of Esophageal Cancer (EC), accounting for nearly 88% of EC incidents worldwide. Importantly, it is also a life-threatening cancer for patients diagnosed in advanced stages, with only a 20% 5-year survival rate due to a limited number of actionable targets and therapeutic options. Increasing evidence has shown that inter-tumor and intra-tumor heterogeneity are widely distributed across ESCC tumor tissues. In our work, multi-omics data from ESCC cell lines, tumor tissue, normal tissue and Patient-Derived Xenograft (PDX) tissues were analyzed to investigate the heterogeneity among ESCC samples at the DNA, RNA, and protein level. We identified enrichment of ECM-receptor interaction and Focal adhesion pathways from the subset of protein-coding genes with non-silent mutations in ESCC patients. We also found that TP53, TTN, KMT2D, CSMD3, DNAH5, MUC16 and DST are the most frequently mutated genes in ESCC patient samples. Out of the identified genes, TP53 is the most frequently mutated, with 84 distinct non-silent mutation variants. We observed that p.R248Q, p.R175G/H, and p.R273C/H are the most common TP53 mutation variants. The diversity of TP53 mutations reveal its importance in ESCC progression and may also provide promising targets for precision therapeutics. Additionally, we identified the Olfactory transduction as the top signaling pathway, enriched from genes uniquely expressed in The Cancer Genome Atlas (TCGA)-ESCC patient tumor tissues, which may provide implications for the exact roles of the corresponding genes in ESCC. Cyclic nucleotide-gated channel subunit beta 1(CNGB1), a gene belonging to the Olfactory transduction pathway, was found exclusively overexpressed in ESCC. Expression of CNGB1 could serve as a marker, indicating potential diagnostic or therapeutic value. Finally, we investigated heterogeneity in the context of the ESCC PDX model, which is an emerging tool used to predict drug response and recapitulate tumor behavior in vivo. We observed trans-species heterogeneity in as high as 75% of the identified proteins, indicating that the ambiguity of proteins should be addressed by specific strategies to avoid drawing false conclusions. The identification and characterization of gene mutation and expression heterogeneity across different ESCC datasets, including various novel TP53 mutations, ECM-receptor interaction, Focal adhesion, and Olfactory transduction pathways (CNGB1), provide researchers with evidence and implications for accurate research and precision therapeutic development.

Dataset Information

Global comparative gene expression analysis of melanoma patient samples, derived cell lines and corresponding tumor xenografts.

Publications

Global comparative gene expression analysis of melanoma patient samples, derived cell lines and corresponding tumor xenografts.

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