A Diagnostic Tool That Finds Breast Cancer Patients Who Can Skip Chemo!

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Maybe you don’t need Chemo!

Highlighting latest results (published August 25, 2016) on the use of the 70-gene test (MammaPrint, Agendia, The Netherlands) in identifying women with breast cancer who can skip chemotherapy. 
Chemotherapy vials Credit: Bill Branson, National Cancer Institute; WikimediaCommons
Chemotherapy vials Credit: Bill Branson, National Cancer Institute; WikimediaCommons
First some basics of breast cancer incidence, heterogeneity, and the available diagnostic tests.

Breast cancer incidence

With an estimated 1.7 million newly diagnosed cases in 2012 alone, breast cancer is the leading cause of cancer-related deaths among women globally. Since the 2008 census, a 20% increase in cancer incidence and a 14% increase in mortality have been recorded, indicating a sharp rise in breast cancer cases in recent years. Historically, breast cancer was perceived as a single disease with varying histopathological features and responses to systemic treatment.

However, the advent of high-throughput platforms for gene-expression profiling and whole-genome and whole-exome sequencing have enabled studies that have challenged this view and brought to the fore the concept that breast cancer consists of a collection of different diseases that affect the same organ site but have different risk factors, clinical presentation, histopathological features, survival outcomes and responses to systemic therapies.

This heterogeneity poses a severe challenge for accurate diagnosis of patients for optimal dosage and extent of treatment and to estimate risk factors associated with their disease.

For example, a study analysing breast cancer cases in the US reported between 1976 and 2008 estimated that about 1.3 million women were over-diagnosed and over-treated as a result of regular mammogram screening during this thirty-year period; the long-term side-effects of the treatments among survivors may be significant. 

Histological grading of breast cancer

Very simply, histological grade is the description of the tumour based on the abnormality of tumour cells relative to normal cells when observed under a microscope. Typically a numerical grade (1, 2, 3 or 4) is assigned to the tumour depending on the extent of this abnormality. Grade-1 tumour cells appear highly similar to normal cells and these tumours tend to spread slowly. In contrast, cells of Grade 3 and 4 tumours appear highly dissimilar from normal cells, and these tumours grow rapidly and spread faster than lower-grade tumours.

The histological grading system which is the most widely adopted in breast cancer is the Nottingham system, and is included as part of prognostic indices such as the Nottingham Prognostic Index (NPI). This index, combines tumour grade and lymph node stage of the TNM system (discussed next) for determining the treatment for breast cancer patients in the UK.

Classification of breast cancer based on tumour size, lymph-node invasion and metastatic spread

In the TNM system, T appended with a number (0 to 4) is used to describe the size and location of the tumour: T0 – no evidence of tumour; T1 – the invasive part of the tumour has size £20 millimetres (mm) and is carcinoma in situ (CIS), confined within the ducts (DCIS) or lobules (LCIS) of breast tissue; T2 – the invasive part of the tumour is 20-50 mm; T3 – the invasive part > 50 mm; and T4 – the tumour has grown into the chest wall and skin with signs of inflammation.

Four stages are likewise recognised for lymph-node invasion: N0 – no cancer cells are found in the lymph nodes; N1 – the cancer has spread to 3 nodes; N2 – the cancer has spread to 4-9 nodes; and N3 – the cancer has spread to ≥ 10 nodes.

The spread is measured as distant metastasis with the following stages: M0 – the cancer has not metastasized; and M1 – there is evidence of metastasis to another body part. The cancer is staged by combining these T, N and M classifications. In breast cancer, there are five stages 0 to 4, of which stage 0 corresponds to non-invasive ductal carcinoma in situ (DCIS) and stages 1 through 4 are used for invasive breast cancer.

Classification of breast cancer using gene expression profiling

Molecular biology studies such as gene-expression profiling have shown that response to treatment, and therefore clinical decision-making, is not determined by anatomical factors (such as tumour size or lymph nodal status) alone, but also by intrinsic molecular characteristics of the tumours.

Consequently, a number of landmark studies uncovered multi-gene expression markers which are independent of classical anatomical markers, from the compendia of genome-wide mRNA profiles of patients. These clinically motivated markers, also called gene signatures, correlate with the molecular characteristics of tumours (molecular subtypes) aggressiveness markers such as proliferation or grade, survival outcomes (prognosis) and response to therapy.

Molecular or “intrinsic” subtyping

One of the first applications of microarray-based gene expression analysis to the study of breast cancer was in the assessment of diversity at a molecular level.

Starting with an initial set of 8102 genes from 65 tumour expression samples, 456 “intrinsic” genes (those that varied more in expression between tumours than between repeated samples of the same tumour) were identified that hierarchically clustered the samples based on molecular characteristic. Subsequent validation on an independent dataset of 78 breast cancers confirmed the robustness of this classification.

These seminal studies revealed that ER-positive and ER-negative tumours (ER: oestrogen receptor) are molecularly different, and the intrinsic genes identified at least four distinct subtypes (luminal, HER2-enriched, basal-like and normal-like).

Luminal tumours are mostly ER-positive, and are further classified into luminal-A, which are histologically low-grade, and luminal-B, which express lower levels of hormone receptors and are mostly high-grade. HER2-positive tumours show amplification and over-expression of the ERBB2 gene, and are mostly high-grade. On the other hand, basal-like tumours are ER-negative, PR-negative (PR: progesterone receptor) and HER2-negative (hence “triple-negative”). These subgroups correspond reasonably well to clinical characterization on the basis of ER and HER2 status, as well as proliferation markers or histological grade.

Although these intrinsic subtypes have been adopted to build breast cancer prognostic and therapeutic-response prediction models such as the PAM50 signature, the classification is limited by its close correspondence to ER, PR and HER2 status, and analyses have suggested that these do not have sufficient prognostic or predictive value.

Over the last decade, several groups have pursued the development of multi-gene prognostic signatures that classify patients with good prognosis, who hence can forgo chemotherapy, and those with poor prognosis and metastasis risk. Here, I highlight two widely adopted signatures in the clinic- MammaPrint and OncotypeDX.

The 70-gene signature MammaPrint

MammaPrint (Agendia, Amsterdam, Netherlands) was the first successful prognostic gene signature, and is a microarray test approved by the US Food and Drug Administration (FDA) for prognosis of patients with TNM stage 1 or 2, node-negative, invasive breast cancer of tumour size ≤50 mm.

This signature was constructed from an empirical microarray analysis of 78 breast cancers from patients younger than 55 years with node-negative tumours ≤50 mm. A supervised analysis of 25,000 genes from the expression profiles of these patients identified a set of 70 genes that accurately predicted poor prognosis disease (development of distant metastasis within 5 years) on an independent cohort of 295 invasive breast cancers. Subsequent studies confirmed the test’s prognostic potential in node-positive and HER2-positive tumours, and its correlation with chemotherapy sensitivity. However, the discriminatory power of the signature for ER-negative cancers was noted to be very low.

The 21-gene signature OncotypeDX

In parallel with microarray-based signatures, OncotypeDX (Genomic Health, USA) was developed using qRT-PCR-based expression profiles, and is widely adopted for clinical practice in the USA. A mathematical function (recurrence score [RS]) in OncotypeDX uses a 21-gene expression profile to predict the risk of distant relapse at 10 years for patients with ER-positive, lymph-node-negative cancers. The association between RS and distant relapse was examined retrospectively in 668 patients treated with tamoxifen, and RS predicted 10-year distant recurrence rates as 7%, 14%, and 30% for the low-risk, intermediate-risk, and high-risk categories of patients, respectively. In addition, the association of RS with benefit from adjuvant chemotherapy in ER-positive, node-negative, tamoxifen-treated patients was examined in 651 patients. Higher scores were associated with greater benefit from adjuvant chemotherapy, and more critically, lower scores were associated with a lack of even marginal benefit from chemotherapy.

Latest news on the use of MammaPrint for identifying women who can skip chemotherapy

Summarizing results from a phase-3 randomized clinical trial called the Microarray in Node-Negative and 1 to 3 Positive Lymph Node Disease May Avoid Chemotherapy (EORTC 10041/BIG 3-04 MINDACT) study involving 11,228 breast cancer patients enrolled at 112 institutions across Europe between 2007 and 2011, between the ages 18 and 70 years, with up to three three positive axillary nodes, and histologically confirmed to be primary invasive breast cancer (T1, T2 or operable T3):

The break up:

  • 4595 patients (40.7%) not analysed due to unsuitability of tumour material;
  • Of the remaining, 2,745 patients (41%) classified as low clinical risk and low genomic risk;
  • 592 patients (8.8%) classified as low clinical risk and high genomic risk;
  • 1,550 patients (23.2%) classified as high clinical risk and low genomic risk; and
  • 1,806 patients (27%) classified high clinical risk and high genomic risk.

The trial examined whether the 70-gene signature (MammaPrint) would enable a reduction in the use of chemotherapy by focusing on the results in the patients with high clinical risk for whom chemotherapy was advised but for whom the 70-gene signature identified low risk. The investigators asked whether this group would have a 5-year rate of metastasis-free survival of more than 92%, which was identified as the cutoff for the benefit of chemotherapy.

Primary outcome:

  • At 5 years post diagnosis, patients who were at high clinical risk and low genomic risk who did not receive adjuvant chemotherapy had a rate of survival without distant metastasis of 94.7%, which was higher than the 92% cut-off.

To chemo or not to chemo:

  • At 5 years, patients who underwent chemotherapy had a survival without distant metastasis of 95.9%;
  • at 5 years, patients who did not undergo chemotherapy had a survival without distant metastasis of 94.4%;
  • Therefore, only an 1.5 percentage points lower than the group who underwent chemotherapy.
  • The 70-gene signature was significantly associated with survival without distant metastasis after adjustment for chemotherapy use, clinical risk, and patient and tumour characteristics.
  • Therefore, the addition of the 70-gene signature to traditional clinical and pathological factors provides valuable information for considering which patients might benefit from adjuvant chemotherapy.
  • However, the study was not powered to determine significance between the groups, but the magnitude of chemotherapy benefit appeared modest in consideration of its inconvenience, risks, and costs.

“However, a difference of 1.5 percentage points, if real, might mean more to one patient than to another. Thus, the stated difference does not precisely exclude a benefit that clinicians and patients might find meaningful.”

Source: Medscape, Labiotech.eu, NEJM