Agilent has published a white paper on best practices for breast cancer diagnosis. The paper, “Breast Cancer Diagnosis: Past, Present and Future,” is authored by doctors from the U.S. and Belgium.
Breast cancer is the leading cancer among women worldwide, causing more than 522,000 deaths a year. But breast cancer deaths have declined over the past several decades, due in part to public education, better understanding of tumor biology, and therapeutic advances.
Historically, breast cancer was thought to be a single disease, leading doctors to take a “one size fits all” approach to treatment. We now know that “breast cancer” actually encompasses a heterogeneous group of different tumor types. They have different biological structures and respond differently to various therapies.
Immunohistochemistry (IHC) has evolved as a critical tool to aid in the diagnosis and treatment of breast cancer. IHC is based on the principle that antibodies will bind to specific antigens in biological tissues. (An antigen is anything that triggers the body’s immune system). By applying specific antibodies to a tumor, medical professionals can better determine what type of tumor it is.
Next-generation sequencing permits the simultaneous analysis of entire panels of cancer genes at high speed and low cost. More than 1,2000 primary breast tumors have been sequenced, enabling researchers to identify specific gene mutations associated with breast cancer.
The authors admit that our current ability to predict breast cancer recurrence remains “at best, limited.” But these new molecular technologies have led to an overwhelming amount of new data about genetic and molecular alterations present in tumor samples. As doctors learn more about the underlying biology of each patient’s tumor, they will better be able to guide individual treatment.
As the authors conclude, “These exciting developments have led us closer to realizing and being able to provide personalized or ‘precision’ cancer therapy for patients with breast cancer.”
The 52-page white paper can be downloaded here. (Note: it is a 10.6 MB PDF.)
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