All in a blood draw: breast cancer monitoring in the age of genetic medicine

Aug. 17, 2013

Breast cancer is a disease that has received significant public and research attention over the last 20 years. Despite this, it accounts for more cancer deaths in women than all but lung cancer. Of the 1.5 million people diagnosed annually, almost 250,000 cases will present as invasive breast cancer. Overall, almost one in four patients will recur within 10 years of treatment. The recurrence numbers are significantly higher for patients diagnosed with invasive or locally advanced disease, where five-year survival rates can range from 30% to 75%.1 Recognizing and treating these recurrent events present a series of particular challenges for patients and doctors.

The arguments in favor of more aggressive monitoring for breast cancer recurrence stem from the positive effect on overall survival when primary disease is identified while the patient still has asymptomatic disease.2 This positive impact of early detection in primary disease can be extrapolated to recurrent disease. Second, early detection can afford the opportunity to delay or mitigate cancer-related symptoms. Third, recurrence monitoring provides peace of mind to patients.

This notwithstanding, the American Society of Clinical Oncology (ASCO) and National Comprehensive Cancer Network (NCCN) guidelines continue to recommend that after primary treatment, asymptomatic patients receive standard breast imaging for detection of recurrence but no aggressive recurrence monitoring.3 This recommendation is based on a pair of prospective trials conducted in Europe in the 1980s. These trials used available biomarkers and imaging technologies to compare the effect of routine follow-up with that of more aggressive protocols. Neither demonstrated any benefit when balanced against specificity, cost, and the effects of radiation exposure. True to the practice of evidence-based medicine, these trials still inform the monitoring recommendations today, almost 30 years later. A new approach to recurrence monitoring would leverage three major technological breakthroughs from the last 20 years: a better understanding of the molecular biology of breast cancer; rapid and cost-effective tools to evaluate this molecular biology in patients; and simple, longitudinal access to tumor cells.

Molecular pathology of breast cancer

There have been a number of significant changes in our understanding of the molecular pathology of breast cancer. Organ-based classifications of cancer used to lead practitioners to approach and treat all breast cancers similarly. Increasingly, using tools to profile expression signatures, breast cancer has been sub-classified into expression-based subgroups that  reflect the clinically predictive utility of defining whether a tumor expresses the estrogen receptor (ER), progesterone receptor (PR), HER2neu (Her2), or none of the above (triple negative).4

Ultimately, the aberrant growth behaviors in breast cancer arise due to changes in the genomic material of the cancer cells. These somatic changes accumulate in a sequential fashion and can have several different impacts on carcinogenesis, ranging from activating constitutive growth signals, to inhibiting the function of a tumor suppressor, to altering the sensitivity to selective pressures such as nutrient deprivation. All these changes, both small and large, are accumulated and selected as the tumor grows. This ontogeny makes it very unlikely any two cancers are identical. Even within one patient there is variability among cancer cells found at a single tumor site, as well as those found at distant sites in a metastatic setting.5 This complexity predicts that the molecular fingerprint of a cancer has to be evaluated from as many sites as possible to capture the functional heterogeneity of the disease. It also suggests that treatment decisions will be best made in the context of an understanding of the current state of disease.6

High throughput sequencing tools

The pace of the molecular definition of the biomarkers in breast cancer has been significantly increased by new massively parallel sequencing technologies that have become available during the last 10 years. Not only do these technologies generate, as the name suggests, vast amounts of data; they have reduced the cost of evaluating extensive regions of the genome. These next generation sequencing (NGS) technologies can interrogate tens of thousands of somatic mutation sites in a single day.7 Access to these data has enabled two changes in the way we interrogate breast cancer. First, rather than looking only for well-defined drug targetable mutations, NGS allows evaluation of thousands of different mutations that contribute to carcinogenesis and treatment decisions.8 Second, because this approach sequences in parallel, it is much more sensitive to heterogeneous mutations. Properly executed, NGS can detect mutations in as few as 1% of the genome templates being sequenced. These tools are therefore significantly more sensitive to samples that have small numbers of mutation-bearing tumor cells. Last, and most important, observing a mutation in the genome of a single tumor cell is not a qualitative evaluation of disease on its own. Rather, disease-associated mutations are defined by the cumulative history of oncology research and are curated in databases such as Catalogue of Somatic Mutations in Cancer (COSMIC).9

Longitudinal access to tumor cells

In a recurrence setting, there is an additional restriction: we have no way to predict where the disease will return. Current monitoring protocols are focused on identifying events at the same site as the original cancer. Furthermore, even reliable detection at local sites misses the ability to survey the whole body. Ideally, a monitoring tool should be able to evaluate all sites and be more accessible than repeated tissue biopsy, a procedure that is expensive, painful, and challenging to repeat frequently.10 There are tools to identify tumor cells in a blood sample that have been used for nearly 10 years to provide prognostic feedback on first-line therapy in metastatic disease. These have been valuable to demonstrate that there is a population of cells that can be found in blood that are directly associated with the disease process.11 These tools have been found to be as strong, if not stronger, than standard imaging approaches. Furthermore, this population of cells could also be found in early stage breast cancer.12 However, to date, there have been no high throughput means of sufficiently purifying these cells so that they can be evaluated using the NGS tools. With the emergence of just that capability, the loop on productive molecular monitoring of breast cancer recurrence can be closed.

With the advent of tools to recover tumor cells from blood that have the sensitivity and specificity sufficient for sequence analysis, recurrence monitoring is no longer plagued by the specificity issues surrounding previous biomarker readouts. Not only does sequence analysis of tumor cells recovered from blood address the concern that the biomarker was unrelated to the disease process; it reveals predictive information about the molecular aspects of the diseased cells that are in circulation. This is significant and useful information that a physician can use in the context of each individual patient. With this approach, a patient can be monitored regularly by the simple recovery of a blood sample to detect whether these tumor cells are present. If such cells are found in levels that raise concern, they can be sequenced to identify the genetic lesions that are present. This information can then be interpreted in the context of the individual patient’s clinical history to open a completely new window into remission monitoring applications.

Paul W. Dempsey, PhD, is the Chief Science Officer at Cynvenio Biosystems, Inc., a cancer diagnostics company focused on the molecular analysis of tumor biomarkers derived from whole blood.

References

  1. Karam AK. Breast cancer posttreatment surveillance: diagnosis and management of recurrent disease. Clin Obstet Gynecol. 2011;54:157–163.
  2. Etzioni R, et al. Early detection: the case for early detection. Nat Rev Cancer. 2003;3:243–252 .
  3. Jochelson M, Haye DF, Ganz P. Surveillance and monitoring in breast cancer survivors: maximizing benefit and minimizing harm. Am Sci Clin Oncol Educ Book. 2013:13-18.
  4. Ellis MJ, Perou CM. The genomic landscape of breast cancer as a therapeutic roadmap. Cancer Discov.  2013;3:27–34.
  5. Ogino S, Fuchs CS, Giovannucci E. How many molecular subtypes? Implications of the unique tumor principle in personalized medicine. Expert Rev Mol Diag. 2012;12:621–628.
  6. Murugaesu, Chew SK, Swanton C. Adapting clinical paradigms to the challenges of cancer clonal evolution. Am J Pathol. 2013;182:1962–1971.
  7. Loman NJ, Misra RV, Dallman TJ, et al. Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol. 2012;30(5):434-439.
  8. Desmedt C, Voet T, Sotiriou C, Campbell PJ. Next-generation sequencing in breast cancer: first take home messages. Curr Opin Oncol. 2012;24:597–604.
  9. The Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2013;490:61–71.
  10. Martin KJ, Fournier MV, Reddy GPV, Pardee AB. A need for basic research on fluid-based early detection biomarkers. Cancer Res. 2010;70;5203–5206.
  11. Cristofanilli M, Budd GT,  Ellis MJ, et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004;351:781–791.
  12. Fehm T, Hoffman O, Aktas B, et al. Detection and characterization of circulating tumor cells in blood of primary breast cancer patients by RT-PCR and comparison to status of bone marrow disseminated cells. Breast Cancer Res. 2009;11:R59.

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