Survival of early-stage hormone receptor (HR)-positive and human epidermal receptor
2 (HER2)-negative breast cancer has significantly improved over the last three decades.
Adjuvant chemotherapy plays an important role in this advancement.[1] However, we have also learnt that the benefit of chemotherapy is not for all patients.[2] Some patients may be overtreated with chemotherapy resulting in avoidable toxicity.
Some may be undertreated resulting in lack of cure. Therefore, a predictive biomarker
is of great demand. Such a biomarker will help the oncologist in deciding treatment
course, whether to give or not to give adjuvant chemotherapy.
Over several decades of clinical trials, the field of breast oncology has finessed
the art and science of medicine by individualizing therapeutic decision-making based
on various clinicopathologic tumor-level factors like tumor size, nodal status, grade,
HR and HER2 status along with patient factors like age, menopausal status, and comorbidities.
But these parameters have limitations. For instance, an N1 disease may have an indolent
biology and poor chemosensitivity. A small N0 disease may have an aggressive biology
and be highly chemosensitive.
A paradigm shift in this field happened when RNA-based gene microarray assays involving
21 genes were shown to be both prognostic for outcomes and predictive for chemotherapy.[3]
[4] Suddenly, oncologists woke up to the possibility that the decision-making can be
well-defined based on the degree of expression of a panel of genes in a patient's
tumor tissue.
There are now several types of products in the market—Oncotype DX (21-gene assay),
MammaPrint (70-gene assay), Prosigna (50-gene assay), Endopredict (12-gene assay).
Oncotype Dx and MammaPrint are the more commonly used tests globally. Both these assays
are validated in large prospective, multicentric, independent, phase 3 randomized
controlled trials involving thousands of patients with more than 8 years of follow-up
(TAILORX, RxPonder, MINDACT trials).
However, for patients living in low-and-middle-income countries (LMIC), the alley
is still dark. Very few patients have access to these genomic assays due to the exorbitant
cost. As a matter of fact, it is far more cost-effective for patients to complete
the full schedule of dose-dense chemotherapy than opt for biomarker-driven decision-making.
Another concern with these tests is the relatively low representation of non-Caucasian
patients in the development and validation studies for these tests. In fact, a retrospective,
population-based cohort study showed that Oncotype DX had lower prognostic accuracy
in Black patients with early-stage breast cancer.[5] None of the genomic assays currently recommended in international guidelines are
validated for use in Indians. Therefore, the prognostic and predictive accuracy of
these tests in Indians give some cause for concern.
In this context, Parikh et al. have proposed practical consensus recommendations to
optimize treatment decision for chemotherapy use in patients with HR-positive and
HER2-negative early-stage breast cancer in India.[6] The consensus was achieved with the help of review of published evidence, practical
experience, discussion among the authors, and an online poll among oncologists, 64%
of whom were medical oncologists (119 out of 185).
They suggest the use of CanAssist Breast test in treatment decision algorithm.
CanAssist Breast is an immunohistochemistry-based (IHC) test that quantifies protein
expression levels of a combination of five unique nonproliferative biomarkers (CD44,
Pan-Cadherin, N-Cadherin, ABCC4, and ABCC11). The data from the biomarker IHC testing
are combined with three clinical parameters—tumor size (T), nodal status (N), and
tumor grade—to generate a score for every patient. There are two risk categories—low
and high.
The authors suggest that the test is developed and validated in Indians. They make
a strong assertion that the CanAssist Breast is predictive for chemotherapy response.
However, we were unable to find any study using CanAssist Breast that validated the
predictive potential of the test in ascertaining with confidence that omitting chemotherapy
for a patient with low-risk score would not impact the survival outcomes for the patient.
Among all the various biomarker tests currently available, Oncotype DX and MammaPrint
are found to be predictive for chemotherapy. All other tests including CanAssist Breast
are prognostic tests that unravel the natural history of the disease.
We reviewed some of the published studies for CanAssist Breast that were referenced
in the consensus document.[7]
[8]
[9]
[10] These studies showed the test being prognostic for distant recurrences. However,
all of these studies are retrospective in design. For now, we were unable to find
any prospective phase 3 clinical trials for the test. It would also be ideal to have
an independent group conduct such a study.
We also wish to highlight few other concerns regarding CanAssist Breast. First, unlike
Oncotype DX and MammaPrint, CanAssist Breast is not an RNA-based assay. An IHC-based
assay can be inferior to RNA-based assay in terms of reliability. For instance, Ki67
testing by IHC is generally considered prognostic and predictive. But it is also widely
recognized that the test lacks reliability. There is substantial risk for interobserver
variability. Second, it is also unclear if more weightage is given to the three clinical
parameters (which is obtained from histopathological reporting) or the protein expression
of five genes. If the former is the key factor, then how much does the test add value
to the standard histopathological report. If the latter is the key factor, then the
issue of reliability of IHC testing becomes crucial. Third, the cost of this assay
is lower than the currently available predictive biomarker tests, but is still very
much out of reach for the vast majority of patients in India.
Another limitation of the study pertains to the use of an online poll to develop consensus
guidelines. It is certainly a good method for generating data in short duration. The
small sample size, lack of an avenue for a discussion on pertinent questions, and
the potential bias of selective framing of questions are some of them. In fact, in
the study, almost 47% of oncologists were not convinced about the CanAssist Breast
test and 41% stated that they will not avoid chemotherapy based on a low-risk score
on the CanAssist Breast test. We believe that such an online survey-based study needs
to be utilized as a template for further studies and discussions. Such studies could
serve to highlight areas of need for research—including the one that is highlighted
in this study—the need for a reliable, indigenous predictive biomarker test for chemotherapy
use in early-stage breast cancer.
In summary, while we wish there existed a biomarker test that is validated among Indians
for predicting benefit or lack of benefit of adjuvant chemotherapy and was cost-effective,
the available data suggest that CanAssist Breast is not there yet. We strongly feel
that assisting the developers of this test platform to validate it in the context
of a large prospectively and independently conducted phase 3 clinical trial must be
a high priority for oncologists practicing in India.
As for practicing community oncologists in India and other LMICs, clinical judgement
based upon patient and tumor-related factors still remains the best tool for decision-making.
Shared decision-making with the patient and their family (where it matters)—which
includes an assessment of the risk of recurrence, functional status, risk for chemotherapy
and financial toxicity from therapy or testing—will probably go a long way in improving
overall outcomes of our patients.
