Genetic testing is already common practice for a large number of tumors, especially when - as in the case of breast cancer - the genetic make-up is therapy-determining. But which of these genes also have predictive value and thus indicate an increased cancer risk?
A recent British study has now addressed this question and examined a gene panel comprising 34 putative risk genes for breast carcinoma. The necessary samples came from 60,446 breast cancer patients and 53,461 controls. Using this data, the researchers were able to deduce associations between defined genes and breast cancer risk.
The results showed that changes in five genes (ATM, BRCA1, BRCA2, CHEK2, PALB2), which are associated with a shortened protein variant, significantly increased the risk of breast cancer (p < 0.0001). In addition, women with protein variants of the BARD1, RAD51C, RAD51D and TP53 genes have a significantly increased risk (p < 0.05) of developing breast cancer.
Likewise, these gene alterations appear to have an influence on the hormone dependence of breast carcinoma. For example, the researchers described that ATM and CHEK2 gene variants conferred a higher risk of estrogen receptor (ER)-positive breast carcinoma. BARD-1, BRCA1, BRCA2, PALB2 RAD51C and RAD51D, on the other hand, are more likely to be associated with ER-negative breast cancer.
So-called high-risk aggregations of rare missense mutations in the ATM, CHEK2 and TP53 genes were also associated with a generally increased risk of breast cancer (p < 0.001).
Breast cancer is still a major challenge in clinical practice, despite some advances in therapy. Gene variations and receptor-positive as well as receptor-negative tumor entities determine the choice of therapy approach and often also the prognosis of tumor treatment.
Until now, it was known that in some patients with familial risk, certain genes, such as BRCA1/2, can promote the risk of developing breast carcinoma. However, the possible association between tumor development and other genes is often less clear.
The results of this current work are therefore of practical relevance for oncology in two respects. On the one hand, they provide initial insights into which risk genes and gene constellations should be used in prognostic gene panels for breast carcinoma. With the help of such genetic predictors, women's breast cancer risk can be assessed individually, which not least improves preventive diagnostics.
On the other hand, the approach described here makes it possible to assess the risk of individual gene and resulting protein variants for the aetiology of breast carcinoma. This information is in turn important for the genetic risk counselling of women.