Molecular data can predict recurrence of breast cancer | Information Center


Molecular data obtained from breast cancer cells can be used to predict which patients have a high risk of recurrence even decades after their diagnosis, according to a new study jointly conducted by researchers at the Faculty of Medicine of the United States. Stanford University and Cancer Research UK Cambridge Institute. , as well as several other institutions.

In particular, some patients whose tumors express the estrogen receptor but not another receptor called HER2 have a persistent risk of relapse over time. Until now, there was no way to identify these women among their peers.

The study also identifies a subgroup of women with so-called triple-negative breast tumors whose cancers are unlikely to recur after five years. Researchers have also learned where and in the body where certain breast cancers are likely to metastasize.

The findings provide researchers and clinicians with a powerful new tool with which to predict a patient's prognosis and potentially make direct clinical decisions.

"For the first time, we have been able to study breast cancer rates and pathways with unprecedented resolution," said Christina Curtis, PhD, assistant professor of medicine and genetics at Stanford and co-director of the Molecular Tumor Board. at the Stanford Cancer Institute. Curtis first defined the distinct subgroups of patients in a study published in Nature in 2012.

"Once we compiled the rich clinical monitoring data, it became striking that distinct relapse trajectories characterized patients in each of the genomic subgroups we had previously defined," Curtis said.

In particular, about 25% of women with estrogen receptor-positive or ER-positive tumors have a 42 to 55% chance of seeing their cancer recur within the next 20 years, the researchers found.

"We found that about 25% of women whose tumors express the estrogen receptor and not HER2 are at an extremely high risk of late relapse and are the cause of the vast majority of these events," he said. said Curtis. "It's the women who seem cured but then have a systemic disease many years later. Until now, there was no effective way to identify this subgroup of women likely to benefit from ongoing screening or treatment. "

The new study was published online on March 13 in Nature. Curtis shares the lead author role with Carlos Caldas, MD, director of the Breast Cancer Research Unit at Cambridge and a professor of cancer medicine at Cambridge University. Oscar Rueda, PhD, Senior Research Associate at the University of Cambridge, is the lead author.

"A clinical challenge in managing breast cancer has been to distinguish tumors that pose the greatest risk of late recurrence," said Harold Burstein, MD, PhD, associate professor of medicine at Harvard Medical School, who n & # 39; 39, did not participate in the research. "This important scientific article identifies the molecular features that determine the timing of cancer recurrence. In the future, this type of genomic classification should help us separate patients who remain at risk – and may require additional or ongoing treatment – from those who do not. "

"Unprecedented resolution"

It is important to note that in many cases, the study also identified probable genomic factors for specific tumors, which, according to the researchers, could serve as targets for drug development.

Traditionally, physicians relied primarily on clinical variables – such as the size and grade of the tumor at the time of diagnosis, the degree of lymph node involvement, and the age of the patient – in making therapeutic and therapeutic decisions. the prognosis. More recently, genomic tests have been used to determine which molecules, if any, are expressed by the cancer cells. They have been used to sub-categorize breast cancer and guide treatment decisions.

Until now, there was no effective way to identify this subgroup of women likely to benefit from ongoing screening or treatment.

For example, a tumor that expresses high levels of estrogen receptor on its surface, indicating that it relies on the growth of estrogens, could be successfully treated with drugs blocking the binding of the estrogen. Hormone to cancer. The presence or absence of HER2 is also commonly used to categorize breast cancers and plan a treatment.

Curtis and colleagues studied the long-term medical history of more than 3,000 women diagnosed with breast cancer in the UK and Canada between 1977 and 2005 to determine if, when and when specific types breast cancer were likely to spread after an initial success. treatment. For 1,980 of these women, the database also contained molecular details about their cancers, including information on the estrogen receptor and HER2 expression, the expression levels of others. specific genes associated with cancer and the presence or absence of specific acquired genetic aberrations, known as copying variations in number. Incorporating all this information, they have developed a computer model identifying four subgroups of estrogen-receptor but non-HER2-expressing tumors with a high risk of recurrence, as well as other subtypes of ER-positive breast cancer. HER2-negative less likely to reproduce.

The researchers were also able to identify a subgroup of women with triple-negative breast cancer – considered an aggressive and more difficult form to treat – who are unlikely to have their cancer reappear after five years.

Distinct patterns of metastasis

Curtis and colleagues found that they could predict the course of the disease at different points in the patient's clinical follow-up. They also found that the subgroups have distinct patterns of recurrence in terms of timing and sites of metastasis.

"Our model uniquely takes into account the chronology of a patient's disease and is based on a genome-based classification scheme that can inform personalized therapeutic approaches," Curtis said.

An unavoidable limitation of a retrospective study spanning decades like this means that researchers study patients diagnosed and treated many years ago.

"This is a cohort of retrospective observation," said Curtis. "Since then, treatment paradigms have changed for some subgroups of patients. Trastuzumab – which specifically targets the HER2 receptor, has dramatically improved outcomes for patients with HER2-positive breast cancer since its approval in 2006 in early-stage breast cancer – did not not been an option for many women in this study. . It will be important to take what we have learned here and determine if we can similarly improve the outcomes of these subgroups of patients at high risk for recurrence with new treatments targeting their specific genomics. "

Curtis and his colleagues are currently planning clinical trials for this purpose. They have also developed a web-based research tool that could potentially help clinicians more accurately predict a person's risk of relapse and guide treatment decisions.

"We have shown that the molecular nature of a woman's breast cancer determines the progression of her disease, not just for the first five years, but also later, even if it reappears," Rueda said. "We hope that our research tool can be turned into a test that doctors can easily use to guide treatment recommendations."

This work is an example of Stanford Medicine's focus on precision health, with the goal of anticipating and preventing disease in healthy people and accurately diagnosing and treating the illnesses of sick people.

Curtis is a member of the Stanford Cancer Institute and Stanford Bio-X.

The other co-authors of the Stanford study are medical instructors, Jose Seoane, PhD, and Jennifer Caswell-Jin, MD. Researchers at the British Columbia Cancer Research Center; the Oncology and Hematology Research Institute in Winnipeg, Canada; the University of Nottingham; King's College London; and the University of Valladolid in Spain also contributed to the work.

The research was funded by Cancer Research UK, the Experimental Cancer Medicine Center, the UK National Institute for Health Research, the Breast Cancer Research Foundation, the American Association for Research on Cancer, cancer and an award from the NIH Pioneer Director (grant DP1CA238296).

A patent application covering certain aspects of the results of the research conducted by Curtis, Caldas, Rueda and Seoane has been filed.

Stanford's Departments of Medicine and Genetics also supported the work.

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