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Ovarian cancer biomarkers may enable personalized treatment, say Stanford scientists

skittlesUpdated 7-15-13: Several changes were made for clarification.


The concept of "divide and conquer" can apply as much to cancer therapies as to warfare. Separating tumors from one organ into several subtypes based on molecular parameters (What molecules do the cancer cells express on their surface? What drives their growth?) is an important first step to devising an appropriate plan of attack. But it's not always been easy to categorize tumor types based on these kinds of biomarkers, particularly in the case of ovarian cancer. That's because most clinical trials have treated ovarian cancer as just one disease.

Now Stanford epidemiologist Weiva Sieh, MD, PhD, hasĀ published an international study in The Lancet Oncology that describes how expression patterns of the progesterone receptor (PR) and estrogen receptor (ER) on the surface of the five main subtypes of ovarian cancer relate to patient survival. They conclude:

PR and ER are prognostic biomarkers for endometrioid and high-grade serous ovarian cancers. Clinical trials, stratified by subtype and biomarker status, are needed to establish whether hormone-receptor status predicts response to endocrine treatment, and whether it could guide personalised treatment for ovarian cancer.

The research may help clinicians decide how best to treat patients with each subtype. According to an accompanying commentary by Charlie Gourley, MD, PhD, from the Edinburgh Cancer Research UK Centre:

Sieh and colleagues' data should help clinicians when considering issues such as prognosis and hormonal treatment in the setting of relapsed disease, or whether hormone replacement therapy is appropriate in a young disease-free patient after oophorectomy.

Previously: Making high-tech "maps" of cancer, Stanford expert weighs in on ovarian-cancer screening recommendation and Ovarian cancer tests flawed
Photo by Andrew Gray

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