September 2014 Edition Vol.11, Issue 9

Oncotype DX® Colon Cancer Assay Improves Recurrence Risk Stratification in Stage II Colon Cancer Patients

Oncotype DX® Colon Cancer Assay Improves Recurrence Risk Stratification in Stage II Colon Cancer Patients

 

 

This edutorial is brought to you by Genomic Health.

 

We are now in an era where cancer is recognized as not one disease, but as many diseases as there are cancer patients. Cancer treatment has evolved in the age of personalized medicine as well and needs to be tailored to each individual patient. Molecular alterations in DNA, RNA, and proteins within every individual tumor are the driving sources of therapeutic resistance and cancer recurrence.1 Therefore, molecular-based assays, which detect specific, disease-associated biomarkers, are valuable tools for treatment strategies based on the individual cancer patient’s unique tumor biology.

Traditionally, treatment decisions relied on morphological characteristics of the tumor (type, grade, and stage) and measurement of a limited number of tumor biomarkers.2 However, the large variance observed in treatment responses and toxicities among patients with similar disease states indicates that a more accurate method is needed to determine whether patients would benefit from receiving a particular therapy and to personalize care.

Several molecular-based assays have been developed and clinically validated in cancer patients. The application of these assays to cancer diagnostics has shown remarkable effects on treatment decisions. These novel diagnostic approaches became available as a result of significant advances in new technologies, including whole genome sequencing, single nucleotide polymorphism (SNP) and microarray analyses, proteomics using mass spectrometry, real-time PCR gene expression analysis, and genome-wide association studies.2 From the introduction of the predictive single gene HercepTest® in 1998 to newer prognostic multi-gene diagnostics such as Oncotype DX® assay and MammaPrint™, doctors (in this example breast cancer oncologists) are turning more often to the use of molecular diagnostics to guide treatment decisions. The “one size fits all” model is no longer viable in cancer treatment. Instead, treatment decisions are based on informed, molecular diagnostic-guided principles.

One of the advantages of utilizing molecular-based assays is the ability to determine the prognosis of an individual patient and then plan treatment, such as observation alone or administering a specific chemotherapy regimen based on the specific information provided by the assay result. This approach stratifies cancer patients with higher risk of disease recurrence from those with lower risk, which improves treatment response rates because only the patients with a greater likelihood of responding to chemotherapy are receiving it, thus preventing undue exposure and toxicity in patients that have little likelihood of deriving benefit.

What Makes an Assay Clinically Useful?

To be useful in the clinic, an assay must be analytically and clinically validated, practical, and cost-effective. Importantly, it must also provide new information that can be used to direct clinicians’ decisions regarding treatment.

The validation of an assay is critical for its translation into a useful diagnostic tool. This is a multistep process that addresses the analytic and clinical validity, as well as the clinical utility of a test. The assay must first and foremost demonstrate an accurate and reliable measurement of tumor biology, the so-called analytic validity. If multiple markers are measured, there must also be a system (i.e. algorithm) in place to translate the collection of those measurements into a useful scoring system for clinicians.

In addition to analytic validity, the assay must also undergo clinical validation studies, defining the accuracy and reliability of the test to predict a certain patient outcome. The clinical validity of a molecular-based assay is determined by investigating the relationship between gene expression profile and the risk of cancer recurrence and/or cancer-specific survival. Additionally, clinical validity may also be assessed by determining the relationship between gene expression profile and response to adjuvant chemotherapy versus surgery alone.

Clinically validated assays can penetrate the market only if they are practical for clinical use. It is thus necessary that both the specimen collection and the methods used to measure biomarkers are feasible.3 Assays that require elaborate analyses, uncommon instrumentation, or challenging specimen collection protocols, are less likely to attain widespread use.

An important measurement of an assay’s clinical utility is its ability to provide meaningful information that can be used to direct clinicians’ decision-making about treatment. The goal of molecular-based assays is to enhance treatment efficiency for cancer patients by selecting those who would most likely benefit from therapy, while sparing the treatment’s side effects for patients who may not benefit from the therapy. Therefore, a newly developed assay must demonstrate superior predictive or prognostic measurements compared to existing assays for a specific disease state.

Stakeholders, including patients, clinicians and payers, are hesitant to embrace molecular assays that do not show the potential to significantly influence disease outcomes for the patient. Perhaps most important for the uptake of an assay is the clinical utility, or the positive net impact associated with the use of the test in practice. Studies have revealed that failure to demonstrate clinical utility can result in denial of coverage by payers, even when there is evidence of association between genotype and disease risk or drug effectiveness.4

Health economics is a major consideration for the adoption of an assay, from the payers' and often patients' perspective.  For successful adoption, treatment decisions based on incorporation of the assay in clinical practice must result in significant improvement in patient outcomes and cost savings to the healthcare system.

Predictive vs. Prognostic

Considerable research is being performed to identify biomarkers that can predict subpopulations of cancer patients who would respond to a specific therapy.5 These predictive biomarkers are the “Holy Grail” for personalized medicine in oncology and have been extremely beneficial in managing some tumors, e.g. tumors of the breast and lung. However, most cancers do not yet have predictive biomarkers, and therefore, treatment decisions for these cancer patients, including colon cancer patients, are based upon tumor morphology and treatment history.

Prognostic biomarkers are quantifiable traits in an individual’s tumor that provide information on the likely disease outcome.5 By identifying biomarkers that can stratify patients by risk for disease recurrence, better informed decisions can be made concerning therapeutics for patients in distinct risk groups. For example, a low-risk group of colon cancer patients might be recommended for observation while a high-risk group might be recommended to receive adjuvant chemotherapy.

Limitations of Existing Recurrence Risk Markers in Colon Cancer

Currently, decisions regarding whether or not to administer adjuvant chemotherapy to a patient with stage II colon cancer are based upon several qualitative parameters used to determine each patient’s prognosis and risk for recurrence. For example, patients considered high-risk for recurrence exhibit T4 lesions, and have had fewer than 12 lymph nodes removed and examined, a bowel perforation or obstruction, poorly differentiated tumors, and/or lymphatic/venous invasion.6 Because most of these markers are qualitative rather than quantitative, there is high variability associated with classifying patients as low- or high-risk for recurrence.

Traditional markers, such as tumor grade, are also not predictive of recurrence in stage II colon cancer. Unlike many other cancers, high tumor grade in stage II patients does not correlate with high recurrence risk.7 Alan P. Venook, MD, Professor at the Department of Medicine (Hematology/Oncology) at the University of California San Francisco, San Francisco, CA, notes that the traditional approach to risk assessment and treatment planning in stage II colon cancer must be re-considered. ”Most of the conventional clinical and pathologic features in use suffer from lack of standardization, reproducibility, and prospective validation criteria which should apply to any marker, new or old, for clinical decision making.” This is a critical point when deciding on the course of treatment for stage II colon cancer patients, and highlights the need for a quantitative, reliable way to assess recurrence risk in this patient population.

 

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