Washington: Scientists have developed a new mathematical model to predict how a patient’s tumour is likely to behave and which of several possible treatments is most likely to be effective. The model was developed by Polyak and Franziska Michor, a computational biologist at Dana-Farber.
Researchers at Dana-Farber Cancer Institute combined several types of data from pre- and post-treatment biopsies of breast tumours to obtain a molecular picture of how the cancer evolved as a result of chemotherapy.
The study analyzed breast cancer samples from 47 patients who underwent pre-operative chemotherapy to shrink the tumour so it could be removed more easily. The biopsy samples, representing the major types of breast cancer, included specimens taken at diagnosis and again after the chemotherapy was completed.
As has been increasingly recognized, a tumour contains a varied mix of cancer cells and the mix is constantly changing. This is known as tumour heterogeneity. The cells may have different sets of genes turned on and off – phenotypic heterogeneity – or have different numbers of genes and chromosomes – genetic heterogeneity.
The computer model cranked out some general findings. For one, the genetic diversity within a tumour, such as differences in how many copies of a DNA segment are present – didn’t change much in cancers that had no response or only a partial response to treatment.
Tumours with less genetic diversity among their cells are more likely to completely respond to treatment than are tumours with more genetic complexity.
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