Underwriting breast cancer in 2017 will require an understanding of the current and growing role of genomics in the assessment of its mortality risk. This is not to lessen the importance of well-known prognosticators such as tumor/node/metastasis (TNM) staging, estrogen receptor/progesterone receptor (ER/PR) and human epidermal receptor growth factor 2 (HER2) receptor status, grade, or the mitotic activity index (MAI). Rather, it is to keep abreast of additional genomics-based prognostic tools that can be used to further stratify breast cancer and its risks.
The importance of genomics today is being seen in precision medicine: the increasing ability to predict the biological behavior of particular subclasses of diseases and then directly target treatments and hopefully influence favorable outcomes. Genomic-based treatments can also potentially reduce the use of ineffective therapies thereby avoiding the oft-used phrase “The treatment was a success, but the patient died.”
This article will focus on current trends and advances in breast cancer genomics and prognostication and how they are enabling better assessments of individual mortality risk. Microarray studies, for example, that can distinguish breast cancer subtypes into luminal, basal and HER2-enriched, are enabling genetic profiling of breast cancers with validated recurrence scores using typing tests such as Oncotype DX and MammaPrint. The scores generated by these tests in combination with other prognosticators can be used to assess with greater precision the likelihood of long-term disease-free survival for these individuals.
Breast cancer is the most common cancer in women worldwide. Nearly 1.7 million new cases were diagnosed in 2016 according to World Cancer Research Fund International, representing 12% of all new cancer cases and 25% of all cancers in women1. Breast cancer also ranks as the fifth most common cause of death from all cancers. While it is the most common cause of cancer death in women in less-developed regions, it is the second most common cause of cancer death in developed regions1.
According to Globoscan, a project of the International Agency for Research on Cancer (IARC) that provides estimates by cancer site and sex for 184 countries, the highest breast cancer rates are found in Belgium, Denmark, France and the Netherlands, and the lowest in Asia and Africa.
With the emergence of genomics has come a surge of information that can help clinicians differentiate and predict the biological behavior of individual breast cancer types. Just as no two individuals have the exact combination of genes, no two breast cancer genomes are exactly alike. Making sense of these genetic variations to find usefulness in underwriting is the current goal.
Microarray studies and genome sequencing have yielded advances which are substantially altering how breast cancer subtypes are risk-stratified. Insurers, in turn, would be well advised to adjust underwriting risk guidelines as information evolves, providing additional biomarkers to assess mortality risk including response to treatment and assessment of recurrence. Essentially, given the widening variety of prognostic tools, breast cancer might eventually be underwritten on a case-by-case basis, for what might appear to be the same assessment on the basis of TNM and grade could, in actuality, be far different in terms of biological behavior when comparing the DNA of one cancer tissue to another.
In order to appreciate the progress in research, it is prudent to review prognosticators used since the 1980s. Many are still valid today and remain the primary basis for the current guidelines used by insurers to assess mortality. Valid, in this usage, means having analytical and clinical validity as well as clinical utility.2
These prognosticators fall into three distinct groups.
- Age. Older-age breast cancer patients have more estrogen/progesterone (ER/PR) positive hormone receptors than do younger patients. This correlates with better prognoses for postmenopausal women with early-stage breast cancer.3
- Pathologic factors. Valid factors include: tumor size, nodal involvement, metastasis, tumor morphology, histological grade, and degree of peritumoral lymphovascular invasion (PLVI). (Adverse pathologic factors associated with PLVI specifically for breast cancer include: large tumor size; high grade, positive nodal status; tubular, papillary, mucinous, medullary and adenoid cystic histology [as opposed to micropapillary and metaplastic carcinomas]; and estrogen-receptor negativity.)4
- Tissue markers. Receptor status, especially of hormone receptors such as estrogen and progesterone, as well as evidence of HER2 overexpression are important prognosticators.
Microarray studies of breast cancer subtypes show good correlation with these three groups, further supporting the validity of these prognosticators. These subtypes correlate most closely with hormone tissue markers and HER2 status.
Microarray studies were first introduced in 1983 as a means to assess antibodies. It was not, however, until 1995 that microarrays were first used to assess DNA. Since then, the utility of microarray studies has grown significantly, paving the way for genomic profiling.
Microarray studies enabled the categorization of breast cancer tissue into four distinct subtypes.5
- Luminal A. This subtype comprises 40% of all breast cancers. It is associated with high expression of ER/PR positive receptors, low expression of HER2, and low proliferation clusters. It carries the best prognosis of all breast cancer subtypes. Luminal A expressed genes are associated with epithelial cells of normal breast tissue. They are characterized by the expression of luminal cytokeratins (8 and 18).
- Luminal B. This subtype is associated with low expression of ER/PR, variable expressions of HER2, and with high-proliferation gene clusters, comprising 25% to 35% of breast cancers. The prognosis for the B subtype is not as favorable as for the A subtype and those individuals will have higher Oncotype DX and MammaPrint recurrence scores.
- HER2-enriched. This subtype, 10% to 15% of breast cancers, is characterized by
high expression of HER2, low expression of ER/PR, and low expression of luminal and basal clusters. Most are ER/PR negative and HER2 positive, but about 30% of HER2-enriched subtype are HER2 negative. This discordance likely represents HER2 mutations, producing a similar expression phenotype without the HER2 amplification or protein overexpression.
- ER-negative. These subtypes include multiple basal-like carcinoma subtypes. Basal-like types have similar gene expression to that of basal epithelial cells and make up 15% to 20% of breast cancers. These tumors are characterized by low expression of ER/PR and HER2 and are known as “triple-negative breast cancers” (TNBC). TNBC is associated with the poorest prognosis and highest recurrence rates. Most of these tumors are infiltrating ductal tumors and are characterized by high nuclear grade, presence of central necrosis, and high mitotic activity indices. These tend to have aggressive clinical behavior and high rates of metastasis to brain and lung5.
Although an applicant may be ER/PR positive and HER2 negative, that does not confirm the best prognosis, nor does being TNBC automatically equate to a grim prognosis. Additional information on the subtype classifications can provide much more accurate prediction of mortality risk and if available should be used in the risk assessment.