Reading Time: 3 minutes
Researchers describe a new method to identify tumor-promoting genes and how it was used to discover potential drug targets for breast cancer treatment.
Oncogenes are genes whose expression promote tumor development. The discovery of oncogenes associated with breast cancer has led to an increased understanding of the disease and to the classification of breast cancer tumors into five subtypes based on their oncogene expression profile.
Clinically, these subtypes are used to classify patients, which is particularly useful since each tumor subtype presents characteristic risk factors, prognosis predictors, and sensitivity to different treatment options. This classification is therefore critical to select a patient’s treatment and inclusion in clinical trials.
Despite the fact that breast cancer is one of the best-characterized types of cancer and this knowledge has reduced breast cancer mortality, many breast cancer patients still do not respond or develop resistance to current treatments. Researchers think that this is because we still do not fully know the diversity of tumor types.
There have been great efforts to find better methods that can dive deeper into cancer patient’s genomic data to identify oncogenes. These “hard-to-find” oncogenes could be used as new drug targets and refine the classification of tumors into subtypes.
New access to gene expression data across the entire genome
In a recent study published in the British Journal of Cancer, a group of American and Australian researchers describes a new statistical approach to identify oncogenes that takes advantage of recently available genome-wide gene expression data from tumor and adjacent healthy tissue from hundreds of patients.
The particular problem this new method solves has been best described by one of the authors of the study, Associate Professor Jess Mar, in a press release: “If an oncogene is over-active in one group of patients but inactive in another group, that’s statistically harder to see using the tools that we had available. If you only look at the average activity of a gene across the two groups, you’d never see the high activity in the first group.”
Discovery of a potential breast cancer oncogene
The efficacy of this new method, called oncomix, was put to test with a dataset from The Cancer Genome Atlas containing gene expression data from 110 Caucasian women with breast cancer. Excitingly, the method identified five new potential oncogenes. One in particular, CBX2, is a gene associated with the regulation of cell proliferation that is barely expressed in healthy tissues and over-expressed in aggressive tumors. The researchers switched off CBX2 in a breast cancer cell line and found that this slowed down the growth of the cells, suggesting that CBX2 might promote tumor growth.
The ability of CBX2 to promote cancer cell growth, combined with the fact that CBX2 is expressed at very low levels in healthy tissues, makes CBX2 a very attractive candidate to develop new drugs against aggressive types of breast cancer.
In summary, the results of the study are very exciting. They share with the scientific community a new method to identify “hard to find” oncogenes in any type of cancer where gene expression data is available from tumors and their surrounding healthy tissues. Moreover, the method has identified CBX2 as an oncogene candidate in aggressive breast carcinoma that has the potential to become a new target for breast cancer treatment.
Written by Maria Isabel Acosta Lopez, PhD, Medical Writer
- Piqué, D. G., Montagna, C., Greally, J. M., & Mar, J. C. (2019). A novel approach to modelling transcriptional heterogeneity identifies the oncogene candidate CBX2 in invasive breast carcinoma. British Journal of Cancer.
- University of Queensland. (2019, March 8). New gene hunt reveals potential breast cancer treatment target. EurekAlert!. Retrieved March 12, 2019 from https://www.eurekalert.org/pub_releases/2019-03/uoq-ngh030819.php
- Clinical implications of the intrinsic molecular subtypes of breast cancer. (2015). Clinical implications of the intrinsic molecular subtypes of breast cancer., 24 Suppl 2, S26–35. http://doi.org/10.1016/j.breast.2015.07.008