Although ten years of genetic profiling has had an enormous impact on the understanding of breast cancer, progress on individualizing therapy has been rather limited, researchers from the UK and USA reported in The Lancet this week. Specifically, the authors refer to the prognostic and predictive factors associated with personalized medicine, even though genetic profiling offers enormous potential for better prediction of outcomes and optimizing individual patients' treatments.
At this moment there are no commercially available molecular tests that can predict benefit from a specific therapeutic agent, despite of many prognostic and predictive signatures having been developed. Scientists are still unable to accurately determine prognosis or chemotherapy success in some disease subsets, such as ER-negative and triple negative disease.
Jorge Reis-Filho from The Breakthrough Breast Cancer Research Centre at The Institute of Cancer Research in London, UK and Lajos Pusztai from the MD Anderson Cancer Center in Texas, USA, set out to determine what progress, if any, had been made over the last ten years regarding microarray analysis (expression profiling) of breast cancers.
Treatment decisions have usually been based on several clinical factors, such as tumor size and its location, estrogen receptor (ER) status, and whether the cancer has spread to lymph nodes or distant sites in the body.
The researchers explain: "With these approaches, about 60% of all patients with early-stage breast cancer still receive adjuvant chemotherapy, of which only a small proportion, 2-15% of patients, will ultimately derive benefit, while all remain at risk of toxic side-effects."
In addition to information provided by clinicopathological features, the introduction of first generation prognostic gene signatures has offered clinically useful prognostics.
At present, several genomic tests are being used in women with ER-positive disease to help determine the likelihood of cancer recurrence, and which patients' outcome has been sufficiently successful in order to deem chemotherapy unnecessary.
However, the researchers comment: "Increasingly clear is that the prognostic information offered by these [first generation prognostic] signatures in addition to the information provided by semi-quantitaive analysis of ER, PR, HER2, and Ki67 is limited...and the continued importance of standardized histo-pathological analysis of tumors should be emphasized."
Using gene signatures to predict which patients may benefit from specific therapies has been less successful, and even though scientists have developed many predictive signatures, some have been based on unreliable data; their usefulness in patients continues to be controversial.
This could be due to the fact that resistance to chemotherapy is a complex mechanism, as it can be caused by changes in just one or a small number of genes? The likelihood of diverse and often subtle changes resulting in resistance to chemotherapy being reliably identified by standard gene expression profiling is extremely small.
In a concluding statement the researchers say: "The theoretical knowledge and logistical lessons learned from gene expression profiling studies, however, will prove useful for research aiming to develop the next generation of prognostic and predictive biomarkers."
References: Prof Jorge S Reis-Filho FRCPath and Prof Lajos Pusztai MD "Gene expression profiling in breast cancer: classification, prognostication, and prediction" The Lancet, Volume 378, Issue 9805, Pages 1812 - 1823, 19 November 2011. doi:10.1016/S0140-6736(11)61539-0
http://www.thelancet.com/journals/la...539-0/abstract
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