Angelina Jolie’s 2013 op-ed sparked a global conversation on genetic cancer risks. Today, in silico tools like CancerMate advance personalised oncology, improving breast cancer treatment predictions.
On Tuesday, May 14, 2013, an opinion piece destined to spark controversy and discussion appeared in The New York Times. The author was not a politician, a renowned writer, or a business tycoon, as one might expect. It was an actress at the peak of her fame—Angelina Jolie.
The article, titled "My Medical Choice," opened with a powerful line: "My mother fought cancer for almost a decade and died at 56." In a few simple words, Jolie set the stage for what would become a landmark moment in science communication. She explained the risks associated with mutations in the BRCA genes (BRCA1 and BRCA2), which play a crucial role in preventing cancer.
Jolie’s mother had a mutated BRCA1 gene, a mutation she had inherited herself. Normally, BRCA and other tumor suppressor genes prevent uncontrolled cell growth and division. However, mutations can deactivate these genes, dramatically increasing the risk of developing certain cancers.
In Jolie’s case, the BRCA1 mutation translated into an 87% risk of developing breast cancer and a 50% risk of ovarian cancer. Even more concerning, such mutations are linked to triple-negative breast cancer, a rare and aggressive disease known for its rapid progression and limited treatment options. Despite intensive therapies, prognosis remains poor, with many patients facing relapse or death by cancer.
As a result, significant efforts have been devoted in recent years to developing new and more effective treatments. One of the standard approaches today is neoadjuvant therapy—one or more drugs administered to shrink the tumor and reduce its metabolic activity, easing or even avoiding surgical removal procedures. A successful neoadjuvant phase not only improves surgical outcomes but is also associated with a better prognosis.
In this sense, a key buzzword in modern oncology is personalisation. Tailoring treatment to an individual’s unique genetic and biological profile could reduce therapy duration and minimize the burden of chemotherapy’s side effects. However, achieving truly personalised and effective treatments remains a work in progress.
Much hope is now placed on in silico medicine, which leverages computational models to personalise neoadjuvant treatments for triple-negative breast cancer, leading to significant breakthroughs. One recent innovation is CancerMate, a tool developed by iBMB (Initiative for Bio-Materials Behavior), a spin-off of the University of Basilicata, Italy.
CancerMate employs a mathematical model for predictive oncology, enabling it to simulate tumor behavior, forecast disease progression, and test various treatment scenarios. In a 2023 study published in Nature Scientific Reports, the tool was retrospectively tested on 17 triple-negative breast cancer patients who had undergone three weeks of neoadjuvant therapy with olaparib. Remarkably, CancerMate successfully predicted individual tumor dynamics in response to treatment, aligning closely with real-world clinical outcomes.
This innovation could greatly assist oncologists in predicting treatment outcomes and refining therapies to enhance effectiveness while minimising side effects. Additionally, the CancerMate team is investigating how gut microbiota—the diverse community of microbes in our intestines—affects therapy response in another type of breast cancer. In collaboration with multiple hospitals, their research aims to bridge the gap between microbiota science and cancer treatment. The findings could pave the way for dietary strategies that shape microbiota composition to improve responses to cancer immunotherapy.
Coming back to the now-legendary New York Times article, Angelina Jolie shared her decision to undergo a preventive double mastectomy. At the time, it was almost scandalous—a high-profile actress voluntarily undergoing such a drastic procedure without an actual cancer diagnosis. But her choice paid off, reducing her risk of developing breast cancer from 87% to less than 5%.
What followed was a phenomenon dubbed by Time magazine as The Angelina Effect. Her article led to a surge in internet searches about breast cancer, a spike in genetic testing rates, and an increase in preventive mastectomies. More importantly, it ignited conversations about genetic risk, proactive health choices, and the importance of advancing cancer research.
Thanks to that article, there is now greater awareness of breast cancer and a stronger push for more effective, truly personalised therapies. In the near future, tools like CancerMate and in silico predictive oncology could drastically transform breast—and other—cancer treatments, offering hope for a future where medicine is not just reactive but anticipatory and individualised.
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