Outpacing Resistance

Drug developers have created cancer therapies that can target specific cancer types, often defined down to a single genetic mutation or protein biomarker. These can be incredibly effective against the right cancer – but matching the right therapy to the right patient continues to present a challenge. Single markers and data points cannot fully identify the broad dynamics of cancer and, for a significant number of patients, these precision treatments often fall short in their promise to deliver a positive outcome.

Surgery to remove tumors is often the first-line treatment for patients, but one in five patients experience complications during the surgery that can diminish its benefits (1). Additionally, patients may undergo chemotherapy – a standby of cancer treatment since the end of World War II – to kill remaining disease in the body. However, chemotherapy is unlikely to succeed in patients with late-stage cancer (2).

Oncologists try to tailor treatments based on the results of genetic tests performed on tumor samples, but tumors are heterogeneous; nine times out of 10, cancer evolves to resist the effects of chemotherapy (2). Tissue biopsies only capture cells from one part of a tumor – so cells in other parts may have different genetic profiles, including ones that are resistant to the oncologist’s chosen treatment. Subsequently, cancer cells that resist chemotherapy survive to proliferate and mutate.

Furthermore, because tumor biopsies are invasive, they are often performed only once. As a result, oncologists routinely make treatment decisions based on a single snapshot in time, so it is difficult to predict if and when patients will start displaying signs of resistance, making timely and appropriate cancer treatment difficult. Fighting cancer can be reduced to a strategy of trial and error as tumors evolve and adapt to different drug therapies.

Another factor that affects the accuracy of tissue biopsy results is the choice of protein biomarker used. One of the most important markers used in precision cancer treatments – PD-L1 – is also one of the least reliable. Tests for expression of this biomarker, a common target of immunotherapy, are not standardized. Different labs often use different antibodies and detection methods, all of which can yield different results. This lab-to-lab variability makes it challenging for oncologists to make treatment decisions with certainty.

Proactively treating cancer

Oncologists have adopted many approaches that enable them to routinely monitor patients’ responsiveness to cancer treatments. Imaging techniques, such as computerized tomography (CT) and magnetic resonance imaging (MRI), allow doctors to monitor a tumor’s size and location. These techniques can serve as rough proxies for whether a treatment is working, but don’t provide any direct information about treatment resistance and are prone to false positives. For example, a working immunotherapy may appear to be failing because the treatment causes inflammation that makes tumors temporarily appear larger.

For decades, oncologists have employed blood tests to detect protein markers associated with cancer – like carcinoembryonic antigen (CEA) – as a means to track cancer progression. Although these tests can be administered on a serial basis, they do not directly measure genetic changes. Consequently, they are not as specific as genetic tests and are prone to false positive and false negative results.

To solve that problem, clinicians can employ molecular diagnostic tests like next-generation sequencing (NGS) to monitor the genetic profiles of tumors based on variants found in ctDNA. Collected via a simple blood draw, nucleic acid strands floating in the bloodstream carry the same genetic information as the tumor. Clinicians can use this information to create targeted therapies based on the tumor’s genetic profile. NGS is comprehensive, highly sensitive, and invaluable for identifying novel mutations that impact the trajectory of a tumor and its responsiveness to treatment. But although NGS yields a comprehensive list of genetic variants in a tumor, it has significant drawbacks: the technique is costly, labor-intensive, and complex, and results often take weeks to receive. Results are also subject to significant variability among different panels and laboratories.

An alternative approach

To monitor for tumor progression more quickly and efficiently, clinicians can add droplet digital PCR (ddPCR) technology to their toolkit. This liquid biopsy technique can complement NGS by providing highly sensitive and reproducible biomarker information about a tumor. Many laboratories already use ddPCR to validate NGS results due to the methodologies’ complementary benefits and the lack of need for library construction prior to performing ddPCR analysis. Research from several recent phase III clinical trials shows that ddPCR can provide oncologists with a rapid, reliable, and cost-effective method to both predict and track the effectiveness of therapy.

Data from one such trial shows that quantifying ctDNAs in a liquid biopsy using ddPCR technology is a more accurate method for tracking treatment resistance than quantifying DNA derived from tissue biopsies (3). Sara Tolaney and colleagues at the Dana Farber Cancer Institute looked at two endocrine therapy resistance genes, PIK3CA and ESR1, in patients with HR+ metastatic breast cancer.

To compare the performance of tissue and liquid biopsies, the researchers assayed 334 plasma samples and 434 formalin-fixed, paraffin-embedded (FFPE) samples, respectively, from a total of 669 patients treated with fulvestrant or fulvestrant and abermaciclib in combination. They found that the concentration of PIK3CA and ESR1 among ctDNAs in plasma correlated with resistance to abermaciclib, but did not find this correlation among FFPE samples (3). These data suggest that ctDNA from liquid biopsy may provide more reliable detection of resistance to endocrine therapy in HR+ metastatic breast cancer.

In a different phase III clinical trial for endocrine therapy in patients with ER+ breast cancer, Francois-Clement Bidard used ddPCR technology to track the onset of ESR1 mutations to inform the design of the trial (4). Using liquid biopsy tests prior to treatment, after one month after treatment, and every two months thereafter, Bidard observed the emergence of ESR1 mutations as patients showed signs of treatment resistance. Based on his real-time monitoring, he was able to randomize these resistant patients to a new group for whom alternative treatment may provide better patient outcomes.  This interventional study addresses one of the most pressing questions concerning the clinical utility of blood monitoring: does it benefit the patient to act on molecular changes before clinical symptoms are evident?

Liquid biopsies using ddPCR technology can also assist in predicting whether or not patients with malignant pleural mesothelioma will benefit from cancer surgery. This cancer is especially common in the elderly; according to the American Cancer Society, two-thirds of patients are 65 or older (5). Consequently, surgery carries heightened risks associated with age – such as arrhythmias, pneumonia, and loss of lung function – that can diminish or cancel out surgical benefits (6). Knowing whether or not surgery might provide a significant benefit can help patients avoid pointless and risky operations.

One indicator for this is plasma ctDNA concentration as measured using ddPCR technology. To test this, Luke Martinson and colleagues at the University of Leicester, in a proof-of-principle study, designed a ddPCR liquid biopsy for mesothelioma patients based on mutations found in tumor tissue using whole exome sequencing (7). Using pre-surgical blood, the investigators examined patients’ ctDNA concentrations to predict the outcome of their surgeries. They discovered that patients survived for a significantly shorter duration following surgery if they had detectable ctDNA in their blood beforehand. This study suggested that ddPCR technology may be used to assess the risk-benefit ratio of subjecting a patient to cancer surgery.

ddPCR’s potential clinical role

Liquid biopsy has already found its place in the clinic, employing tools such as DNA sequencing to provide a noninvasive view of the genetic and phenotypic nature of a patient’s cancer. These tools provide additional context to tissue biopsy and imaging, which are standard of care in cancer detection and monitoring.

ddPCR technology complements these techniques by enabling a physician to capture genotypic and phenotypic cancer information through DNA (or RNA) biomarkers found in blood. After identifying actionable mutations using NGS, an oncologist can reliably track a patient’s ctDNA levels using droplet digital PCR technology to monitor disease status and response to treatment. These data can help oncologists adjust their patients’ treatments over time, increasing the patients’ survival and quality of life.