Breast cancer has variability from the many different cell types with different patterns of gene expression in breast cancer, but a new study found that [WU1] that variability should not be a barrier to using gene expression tests to help tailor cancer treatments to individual patients. These findings were presented at the 5th IMPAKT Breast Cancer Conference in Brussels, Belgium.

Breast cancer is now known to contain a variety of different cell types. Different biopsy specimens from a single breast cancer tumor can exhibit significant variability in the expression of genes. This is a major concern when doctors try to understand which patients are likely to benefit from drugs that are designed to be effective against tumor cells with particular genetic characteristics.

In this study, Dr. Michal Jarzab and his colleagues at the Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Poland took a total of 78 different biopsies from 26 individual tumors. They assessed the degree of genomic variation and how that impacted a set of 32 different prognostic and predictive multigene signatures.

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“Some genomic tests have proven very useful in breast cancer, but in other important areas we have not achieved optimal results,” explained Jarzab. “One of these areas where we haven’t done so well is in deciding whether a particular patient would benefit from certain type of chemotherapy or not, based on the material from presurgical needle biopsies. We hypothesized that some genomic tests may be prone to the heterogeneity of starting material and provide not reliable results.”

The researchers performed gene expression profiling on their 78 samples using oligonucleotide microarrays. Overall, they found that the gene expression profiles of the cores were variable, and in at least five patients this heterogeneity was substantial.

However, when they analyzed a number of multigene signatures selected from previous studies, this heterogeneity was considerably less significant.

The gene sets differed in their variance between biopsies, the authors found. The most pronounced heterogeneity was observed in immune response-related genes, while the least heterogeneous were the classifiers based on genes selected by advanced bioinformatical methods from both cell culture experiments and patient tissues.

“Overall, the heterogeneity among the potentially predictive genes was small enough and we conclude that this factor should not prohibit their effective use in clinical practice,” said Jarzab.

“Our study confirms that it is possible to address tumor heterogeneity when carrying out routine diagnostic procedures in patients. Our results may help to introduce the better tailoring of preoperative treatment.”