Novel Molecular Tests In The Clinic

Breast cancer is a clinically heterogeneous disease and it is generally accepted that the different clinical course of patients with histo-logically similar tumors is due to molecular differences among cancers. Therefore, detailed molecular analysis of the cancer could yield information that may improve clinical outcome prediction. It is also increasingly recognized that molecules which determine the behavior of neoplastic cells act in concert and form complex regulatory networks. Any individual gene may only contain limited information about the activity of the entire network. It is reasonable to hypothesize that examining many genes simultaneously will

Table 11.2 Examples of emerging molecular diagnostic tests to aid decision-making in breast cancer

Function

Test

Commercial availability for <

Prognostic tests

Mammaprintâ„¢ 5,6

No, FDA cleared in 2007

76-gene signature7,8

No

5-antibody, Mammostratâ„¢ 13

No

Probability of benefit

Oncotype DxTM 9-11

Yes

from endocrine therapy

200-gene signature13

No

Probability of benefit

30-gene signature17

No

from chemotherapy from chemotherapy yield more accurate information about the biological behavior of the tumor. High-throughput genomic technologies, including multiplex reverse transcriptave-polymerase chain reaction (RT-PCR) and DNA microar-rays, allow investigators to directly test this hypothesis.4

Recently, several novel multigene molecular diagnostic tests became commercially available, or are near to commercial introduction, in the USA and Europe (Table 11.2). The routine adoption of these tests would be straightforward and ubiquitous if they had perfect sensitivity, specificity and 100% positive and negative predictive values. Naturally, no test ever meets such high performance standards; therefore, the pressing question is, in what clinical situations do these tests provide added value? For many patients with newly diagnosed breast cancer, existing clinical and pathologic markers may provide sufficient information to make an appropriate treatment recommendation. For example, most patients with positive lymph nodes represent a high enough risk for recurrence that recommendations for adjuvant chemotherapy are appropriate. However, some of these individuals are frail, have multiple comorbid conditions, and may have ER-positive disease. So, a more precise prediction of sensitivity to chemotherapy and endocrine therapy could help to make the best treatment recommendation. Similarly, a substantial minority of lymph node-negative patients relapse despite adequate locoregional therapy, and better prognostic predictions could help to identify those who could benefit from systemic chemotherapy. It would be helpful in this situation as well to understand endocrine and chemotherapy sensitivity separately in order to recommend the most appropriate treatment.

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