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Metastatic potential in clonal melanomal cells is driven by a rare, early-invading subpopulation [RNA-Seq]

ABSTRACT: Metastatic potential in clonal melanomal cells is driven by a rare, early-invading subpopulation [RNA-Seq]

PROVIDER: PRJNA934527 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR23386700.fastq.gz	Fastqsanger.gz
	SRR23386800.fastq.gz	Fastqsanger.gz
	SRR23386900.fastq.gz	Fastqsanger.gz
	SRR23387000.fastq.gz	Fastqsanger.gz
	SRR23386701.fastq.gz	Fastqsanger.gz

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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.

Dataset Information

Metastatic potential in clonal melanomal cells is driven by a rare, early-invading subpopulation [RNA-Seq]

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