In a study published recently in Cell, researchers at the University of São Paulo's Ribeirão Preto Medical School (FMRP - USP) in Brazil and collaborators in several other countries describe a method that objectively measures the degree of similarity
between tumor samples and pluripotent stem cells (cells that can differentiate into nearly any type of tissue in the body).
NYGC computational biologists and members of the Simon Laboratory at The Rockefeller University discussed the possibility of using a series of computer algorithms to search for sequence differences
between the tumor samples and samples of healthy liver tissue.
Not exact matches
In blood
samples from 1005 patients with eight types of
tumors that had evidently not yet metastasized, the test detected
between 33 % and 98 % of cases, depending on the
tumor type (see graph, above).
A tissue slice, a
tumor biopsy, or a
sample of a bacterial culture yields a sequence representing the average of all of the cells within it, even though researchers know there can be tremendous variation
between those cells.
The model, called COXEN (CO-eXpression gENe analysis), sorts through the massive genetic data of thousands of
tumor samples to discover differences
between tumors that responded and
tumors that did not.
«Without the integrated characterization of so many
tumor samples, correlations
between histology and genomic data may not have been observed or potential clinical outcomes identified.»
For analysis of the normal -
tumor paired HCC
samples, the staining intensity was compared directly
between the
tumor part and the normal part.
Data delivered includes the full data set for each genome within the
Sample Group as well as results from paired analysis
between the
tumor and the matched normal genome
samples.