Dataset Information

Clonal Analysis for Identification of Molecular Pathways with Potential Therapeutic Implications in of Rare Gastrointestinal and Endocrine Cancers

ABSTRACT: Genomic analysis of many cancers has led to the identification of novel targets and the development of personalized, targeted therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. Clinical specimens typically contain variable degrees of non-tumor cells that can mask a potentially critical genomic signature, leaving important clinically relevant events undetected. When analysis is limited to a smaller number of specimens, the effects of heterogeneity within each sample is magnified. In light of these challenges, we used DNA content based flow cytometry to isolate clonal tumor populations from a series of rare cancers for genomic analysis: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. These purified clonal populations are then subject to high definition measurement of copy number aberrations by objectively measuring the height and boundaries of amplicons and by discriminating homozygous from partial deletions. Ranking of these events by copy number facilitates the identification of highly selected aberrations. This approach can garner useful information from a single biopsy. In the cases we describe, several potential therapeutic targets were identified and genomic aberrations correlated with the phenotypic behavior. We propose that clonal genomic analysis can generate unique hypotheses and guide the development of clinical advances for these and other rare tumors.

ORGANISM(S): Homo sapiens

PROVIDER: GSE34063 | GEO | 2012/04/01

SECONDARY ACCESSION(S): PRJNA150007

REPOSITORIES: GEO

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Project description:Genomic analysis of many cancers has led to the identification of novel targets and the development of personalized, targeted therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. Clinical specimens typically contain variable degrees of non-tumor cells that can mask a potentially critical genomic signature, leaving important clinically relevant events undetected. When analysis is limited to a smaller number of specimens, the effects of heterogeneity within each sample is magnified. In light of these challenges, we used DNA content based flow cytometry to isolate clonal tumor populations from a series of rare cancers for genomic analysis: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. These purified clonal populations are then subject to high definition measurement of copy number aberrations by objectively measuring the height and boundaries of amplicons and by discriminating homozygous from partial deletions. Ranking of these events by copy number facilitates the identification of highly selected aberrations. This approach can garner useful information from a single biopsy. In the cases we describe, several potential therapeutic targets were identified and genomic aberrations correlated with the phenotypic behavior. We propose that clonal genomic analysis can generate unique hypotheses and guide the development of clinical advances for these and other rare tumors. We applied DNA content based flow sorting to isolate the nuclei of clonal populations from tumor biopsies. We coupled this strategy with oligonucleotide array CGH (aCGH) thereby obtaining high definition genomic profiles of clonal populations from different rare tumors including pancreatic neuroendocrine cancers, adrenal leiomyosarcoma, anal carcinoma, and cholangiocarcinoma.

Project description:Background & Aims: The metastatic process is complex and remains a major obstacle in the management of colorectal cancer (CRC). To gain a better insight into the biologic events driving the metastatic process we investigated genomic aberrations in a large cohort of matched CRC primaries and distant metastases from various sites. Methods: In total, 62 primary colorectal cancers, 62 matched normal specimens, and 68 matched metastases (from liver, lung, ovary, omentum, and distant lymph nodes) were analyzed by high resolution array comparative genomic hybridization (array CGH) for DNA copy number changes. Findings were validated using a publicly available dataset consisting of 21 primary tumors and matched liver metastases. Fluorescence in situ hybridization (FISH) was used to confirm some of the DNA copy number changes observed. Results: Overall patterns of DNA copy number aberrations were highly similar between primary tumors and their metastases, confirming clonality. Additional copy number aberrations in metastasis are rare and rather than recurrent they were sporadic for individual patients. The only recurrent differences between primary tumors and their metastases were two chromosomal regions, 6q21 and 8q24.21 encompassing the MYC oncogene, that coamplified in three metastases of two patients (3.2%). FISH analysis confirmed the high level co-amplification in the metastasis, which were not detected in their primary tumors. Conclusions: Primary CRC and their metastases show highly similar patterns of DNA copy number changes, additional copy number aberrations in metastasis are rare and recurrences exceptional. These observations are consistent with the hypothesis that the metastatic potential is predestined early in the development of the primary tumor. In total, 62 primary colorectal cancers, 62 matched normal specimens, and 68 matched metastases (liver, lung, ovarian, omentum and distant lymph nodes) were analyzed by high resolution array comparative genomic hybridization (array CGH).

Dataset Information

Clonal Analysis for Identification of Molecular Pathways with Potential Therapeutic Implications in of Rare Gastrointestinal and Endocrine Cancers

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