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'Signature' Of Chromosome Instability Predicts Cancer Outcomes

Date:
August 21, 2006
Source:
Children's Hospital Boston
Summary:
Traditional microscopic examination can't always accurately predict a cancer's aggressiveness, leading to increased interest in molecular diagnostic techniques. Now, researchers report in Nature Genetics that a gene-expression profile indicating chromosomal instability -- an increased tendency to develop chromosomal aberrations -- predicts clinical outcome in a broad range of cancer types. Their technique could also aid the search for cancer drugs that reduce chromosomal instability, a key factor in promoting cancer.

Microscopic examination of tumor specimens cannot always predict a cancer's aggressiveness, leading to increased interest in molecular approaches to diagnosis. Now, researchers in the Children's Hospital Informatics Program (CHIP) at the Harvard-MIT Division of Health Sciences and Technology report that a genetic profile indicating chromosomal instability -- an increased tendency to develop chromosomal aberrations, critical in cancer development -- is predictive of clinical outcome in a broad range of cancer types.

Using data on gene expression (activity) from 18 previous studies of cancer, representing six cancer types, they found that this genetic profile, or signature, predicted poor clinical outcome in 12 of the populations studied. The study was published online by the journal Nature Genetics on August 20.

"Chromosomal instability is one of the key mechanisms that keeps malignant cell proliferation going," says Zoltan Szallasi, MD, a CHIP researcher and the study's senior investigator. "We have achieved a relatively easy way to measure the level of chromosomal instability in a given tumor sample."

The technique may help in the search for cancer drugs that reduce chromosomal instability -- an approach of increasing interest to researchers -- by making it possible to screen a large number of drugs for efficacy, Szallasi notes. With further development, the team's work could also form the basis of a diagnostic tool that could be used in the clinic.

The human genome is at constant risk for mutations due to environmental insults, errors in gene replication, and other factors that can cause chromosomes to break and bits of DNA to be lost, duplicated or reshuffled to the wrong chromosomes. Cells have repair mechanisms that constantly fix this damage, but when the repair process breaks down, chromosomes become unstable and cancers are more likely to develop.

Chromosomal instability leads to a condition known as aneuploidy, in which chunks of DNA are either missing or duplicated. The technique developed by Szallasi's team indirectly measures the degree of aneuploidy -- and thus the degree of chromosomal instability -- by looking for abnormal expression levels of genes at the different chromosomal locations.

Next, the researchers identified 25 genes whose activity most strongly predicted chromosomal instability itself. This 25-gene signature was a significant predictor of clinical outcomes in a variety of cancers (breast, lung, medulloblastoma, glioma, mesothelioma and lymphoma). It could also differentiate between primary tumors and tumor metastases, and, in grade 1 and grade 2 breast cancer, distinguished the more aggressive cancers within each grade.

The study was supported by grants from the National Institutes of Health and the Department of Defense.


Story Source:

The above story is based on materials provided by Children's Hospital Boston. Note: Materials may be edited for content and length.


Cite This Page:

Children's Hospital Boston. "'Signature' Of Chromosome Instability Predicts Cancer Outcomes." ScienceDaily. ScienceDaily, 21 August 2006. <www.sciencedaily.com/releases/2006/08/060820191755.htm>.
Children's Hospital Boston. (2006, August 21). 'Signature' Of Chromosome Instability Predicts Cancer Outcomes. ScienceDaily. Retrieved July 23, 2014 from www.sciencedaily.com/releases/2006/08/060820191755.htm
Children's Hospital Boston. "'Signature' Of Chromosome Instability Predicts Cancer Outcomes." ScienceDaily. www.sciencedaily.com/releases/2006/08/060820191755.htm (accessed July 23, 2014).

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