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Diagnostics Omics, Precision medicine, Genetics and epigenetics, Oncology

A Tipping Point for Comprehensive Genomic Profiling in Cancer

Precision medicine offers valuable information not just for diagnosis and treatment selection, but also for patient stratification and prognosis. But powerful tools need powerful methods – which is why comprehensive genomic profiling may be the way forward for precision oncology.

Oncology has reached a tipping point and its name is “precision medicine.” No doubt you will have heard of it; in fact, it may well form a substantial part of your daily work. Over the last few years, we have seen tremendous advances in research and in the clinic, thanks, at least in part, to the adoption of comprehensive genomic profiling (CGP), which helps guide treatment decisions based on the molecular drivers of disease. Precision medicine is changing the outlook for many people living with cancer – especially those facing advanced disease.

In breast cancer specifically, we’ve seen an avalanche of research and subsequent progress that spans multiple decades and shapes modern oncology. The progress we’re making for breast cancer patients every day is exciting and provides a glimpse into the potential of CGP and precision medicine not just for breast cancer, but for oncology as a whole.

An age-old decision

True personalization of cancer treatment goes beyond tumor type or stage. Consider, for example, the influence of age in advanced breast cancer – an aggressive disease with a higher mortality rate for younger patients than for older patients (1). For younger women, the need to balance treatment with reproductive health concerns adds a layer of complexity. The rate of breast cancer in younger women has almost doubled in the last 40 years (2), so it’s vital that we better understand the specific drivers of breast cancer in this population. CGP is helping us gain that understanding.

A recent study used CGP to identify and compare genomic drivers in younger and older women and found specific age-related differences that were consistent across histological and molecular breast cancer subtypes (2). For example, the study found markedly lower frequencies of PIK3CA alterations – but higher frequencies of BRCA1/2 alterations – in women under the age of 45 than in those over 45.

In the clinic, this knowledge could help guide treatment decisions or match breast cancer patients with clinical trials. But these results also pose a question: how many other cancers exhibit age-dependent differences in genomic drivers? How many patients are missing testing that could influence treatment decisions and, ultimately, outcomes?

This study strongly reinforces the pivotal role CGP can play in truly personalizing the patient experience. However, we can only harness that potential through widespread and routine access for all patients.

Beyond diagnostics

Emerging research has also shown that CGP may have a role in monitoring disease and predicting recurrence in earlier-stage cancers. This incredibly exciting glimpse into the future shows how the clinical utility of CGP could evolve – from a tool matching advanced cancer patients with appropriate therapy to a technology informing cancer treatment paths throughout the patient’s journey.

Recently, investigators studied triple negative breast cancer (TNBC), another aggressive cancer with high recurrence rates and fewer treatment options than other subtypes (3). Neoadjuvant chemotherapy has become standard treatment in early-stage TNBC, but disease recurrence is still high. Today, decisions around adjuvant treatment after surgery and radiotherapy are based on clinical factors and there is no consistent approach to risk stratification.

In their study, the researchers used CGP to determine whether detection and quantification of the circulating tumor DNA (ctDNA) that remains in patients’ blood after neoadjuvant chemotherapy could help predict the risk of later disease recurrence. The phase II trial tested more than 150 patients and, at 24 months post-treatment, the results demonstrated a significant association between disease recurrence and the detection of ctDNA. Furthermore, the higher the quantity of ctDNA detected, the higher the risk of recurrence.

The ability to better predict outcomes and more accurately stratify risk at the start of a patient’s TNBC treatment could have big implications for success. And that’s welcome news for such a difficult-to-treat cancer. Using CGP in this setting means that the specific driver mutations can be identified early on, allowing the optimization of adjuvant treatment approaches for those with a high risk of recurrence. We are among the researchers now looking at potential designs for new basket trials that would do just that and generate further evidence for this approach.

Moving forward with CGP

Although CGP is currently used to help match patients with advanced disease to targeted treatment and clinical trial options, the results highlight the promise of CGP from a much wider perspective at every stage of cancer treatment. To move toward a truly personalized approach, we need to look beyond tumor type or stage to understand the genomic drivers that could inform treatment decisions and patient outcomes.

Using new technologies to develop monitoring tools means we also have great potential to evolve and adjust treatment strategies in real-time.

The ability to accurately predict recurrence risk alongside identification of specific mutational drivers for a patient’s cancer also gives us a much more complete picture of a patient’s likely cancer experience. It means we can strategically plan our approach to treatment, assessing different combinations and strategies based on our knowledge of how the cancer is likely to respond, and choose the best possible treatment pathway. Using new technologies to develop monitoring tools means we also have great potential to evolve and adjust treatment strategies in real-time.

I’m proud to play a role in the tremendous advancements in cancer care, but I also recognize that there is still a lot of work to do to make precision medicine a reality for everyone. To progress, the entire precision medicine community will need to focus on the same objective: enabling better outcomes for all patients living with cancer. And by sharing insights, our expanding community can deliver more impactful advancements. This collaborative community includes researchers, physicians, payers, advocates, patients, and the investment of many innovative diagnostic and biopharmaceutical organizations. Together, we can help advance and enable personalized medicine for more patients.

 

Cindy Perettie is Chief Executive Officer of Foundation Medicine, Cambridge, Massachusetts, USA.

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  1. AH Partridge et al., “Subtype-dependent relationship between young age at diagnosis and breast cancer survival”, J Clin Oncol, 34, 3308 (2016). PMID: 27480155.
  2. ES Sokol, “Advanced breast cancer (ABC) in young women (YW): a comprehensive genomic profiling (CGP) study” (2019). Available at: bit.ly/35ccgER.
  3. M Radovich et al., “Detection of circulating tumor DNA (ctDNA) after neoadjuvant chemotherapy is significantly associated with disease recurrence in early-stage triple-negative breast cancer (TNBC): Preplanned correlative results from clinical trial BRE12-158” (2020). Available at: bit.ly/3eWVhLb.

About the Author

Cindy Perettie

Chief Executive Officer of Foundation Medicine, Cambridge, Massachusetts, USA.

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