Introduction
Breast cancer treatment often involves complex decisions regarding the use of chemotherapy. An innovative and cost-effective testing method developed by an Indian scientist now offers a more accessible way to guide these decisions. This advancement holds promise for patients seeking accurate risk assessment without the financial burden of expensive tests.
Understanding the Oncotype DX Test
The Oncotype DX test analyses breast cancer tumour tissue samples to predict the likelihood of cancer recurrence following treatment. This information assists oncologists in determining whether chemotherapy is necessary for a patient. However, the high cost—amounting to several lakhs of rupees—limits accessibility for many individuals.
A More Affordable Alternative: CanAssist Breast (CAB)
Dr. Manjiri Bakre, a PhD graduate from the Indian Institute of Science (IISc), founded OncoStem and developed CanAssist Breast (CAB), an Indian equivalent of the Oncotype DX test. Offered at approximately Rs 65,000, CAB is about 4.5 times more affordable than international counterparts.
Since its inception in 2011, OncoStem’s mission has been to create a test that is affordable, accurate, and user-friendly, aimed at identifying early-stage breast cancer patients who truly require chemotherapy versus those who can safely avoid it.
How the CAB Test Works
The CAB test utilizes an artificial intelligence (AI) algorithm that assigns a score between 1 and 100, indicating the risk of cancer recurrence within five years. Patients are classified into low-risk or high-risk groups based on this score.
Approximately 70% of patients fall into the low-risk category, for whom chemotherapy generally provides minimal benefit and can therefore be avoided. This reduces exposure to adverse side effects and alleviates financial strain. High-risk patients receive clear guidance to proceed with chemotherapy and supplementary treatments.
“The CAB test clearly stratifies patients into risk categories, enabling personalized treatment plans that minimize unnecessary chemotherapy and its associated burdens.”
Personal Experience Inspiring Innovation
Dr. Bakre’s motivation to develop CAB stemmed from a personal tragedy during her PhD studies. A close friend diagnosed with breast cancer experienced aggressive disease progression despite surgery and treatment. This loss fueled the pursuit of a predictive test capable of assessing tumour aggressiveness at an early stage.
Expert Support for CAB’s Effectiveness
Dr. Garima Daga, a breast cancer surgeon, has applied the CAB test in over 300 cases. Previously relying on the costly Oncotype DX and other foreign tests, which many patients could not afford, she endorses CAB for its accuracy and applicability to both premenopausal and postmenopausal women.
Dr. Daga emphasizes that CAB offers decisive low-risk and high-risk classification, reducing uncertainty in treatment planning. Low-risk patients can safely avoid chemotherapy, while those at high risk are advised to proceed accordingly.
The Science Behind CAB
Studies indicate that 10 to 40 percent of cancer patients may receive unnecessary chemotherapy, especially toward end-of-life care. The decision-making process following tumour removal remains challenging for clinicians.
Recognizing artificial intelligence’s potential, OncoStem developed their AI-based algorithm between 2014 and 2016, employing high-quality data to enhance prediction accuracy at a time when AI was not mainstream.
Unique Approach to Biomarker Analysis
Unlike tests focusing on gene expression, CAB evaluates protein interactions within tumour cells. Proteins engage in complex networks with multiple partners rather than isolated functions, and the algorithm accounts for these dynamics.
The test is performed on tissue removed during surgery, targeting early-stage breast cancer patients with tumours less than five centimetres in size.
Key Biomarkers and Eligibility
Standard pathology evaluates three biomarkers: estrogen receptor (ER), progesterone receptor (PR), and HER2/neu receptor. CAB testing is available only for patients whose tumours are ER and PR positive and HER2/neu negative.
When ER and PR receptors are present, endocrine therapy, typically administered orally, can be offered. HER2/neu negativity signifies a less aggressive tumour, whereas positivity indicates aggressive disease requiring anti-HER2 therapy combined with chemotherapy.
Five Important Proteins Examined
OncoStem assesses five critical proteins through immunohistochemical staining, which influence the tumour’s ability to spread. Oncopathologists evaluate the staining intensity and grade the tissue accordingly.
These data, along with tumour size, grade, and lymph node status, are input into the AI algorithm to generate a comprehensive risk assessment.
Risk Scoring and Treatment Recommendations
The AI algorithm produces a risk score ranging from 0 to 100. A score of 15.5 or below indicates a low risk for cancer recurrence within five years, while scores above 15.6 indicate high risk.
Based on this classification, low-risk patients are advised against chemotherapy, whereas high-risk patients receive recommendations to proceed with the treatment.
Global Validation and Growing Usage
The combination of biomarker selection and AI methodology employed by CAB is patented internationally. Validation studies have been conducted across multiple countries, including India, the United States, Spain, Germany, Italy, Austria, the Netherlands, and Turkey.
Currently, over 800 doctors utilize CAB regularly. The test is accessible in India, Sri Lanka, Bangladesh, Turkey, and the United Arab Emirates.
Positive Feedback from Practitioners
Dr. Praveen Kumar Dadireddy, chief breast onco-surgeon at Continental Hospitals, has employed CAB since 2019. He describes it as a major advancement in reducing reliance on expensive foreign diagnostics and genomic tests.
Previously, sample processing abroad required 8 to 10 weeks for results. CAB dramatically shortens this turnaround time to approximately 20 days.
Looking Ahead
Dr. Bakre envisions CAB and forthcoming innovations by OncoStem transforming cancer remission management in India. These developments aim to make cancer treatment more precise, cost-effective, and accessible to a broader patient population.
All images courtesy of Manjiri Bakre.
Sources
- A taxonomy of the factors contributing to the overtreatment of cancer patients at the end of life, ESMO Open, January 2025.
Author: Krystelle Dsouza
