Chromosome Instability Patterns Predict Tumor Drug Response
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By LabMedica International staff writers Posted on 16 Jun 2022 |
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Image: Computer-generated three dimensional drawing of a chromosome mutation (Photo courtesy of 123rf.com)
By analyzing the differences in the number of repetitions of sequences of DNA within cancerous tumors, genomic researchers characterized 17 different types of chromosomal instability, which could be used to predict tumor drug response and to aid in the identifying future drug targets.
Chromosomal instability (CIN) is a type of genomic instability in which chromosomes are unstable, such that either whole chromosomes or parts of chromosomes are duplicated or deleted. Chromosomal instability is a common feature of cancer, occurring in around 80% of tumors, researchers are only now beginning to understand exactly what types or patterns of instability are present in any given tumor.
To increase this understanding, investigators at the University of Cambridge (United Kingdom) and colleagues at the Spanish National Cancer Research Center (Madrid, Spain) evaluated the extent, diversity, and origin of CIN across 7,880 tumors representing 33 cancer types.
Results of this evaluation revealed 17 different types of chromosomal instability. These chromosomal instability signatures could be used to predict how tumors might respond to drugs, as well as aiding in the identification of future drug targets.
Senior author Dr. Florian Markowetz, senior group leader at the Cancer Research UK Cambridge Institute of the University of Cambridge, said, "The more complex the genetic changes that underlie a cancer, the more difficult they are to interpret and the more challenging it is to treat the tumor. This is tragically clear from the very low survival rates for cancers that arise as a result of chromosomal instability. Our discovery offers hope that we can turn things around, providing much more sophisticated and accurate treatments. We are now working hard to bring our technology to patients and develop it to a level where it can transform patients' lives."
The CIN study was published in the June 15, 2022, online edition of the journal Nature.
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University of Cambridge
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