Hitesh Goswami, CEO and Co-Founder, 4baseCare stresses that precision oncology, which integrates genomic biomarkers into the treatment paradigm, has rapidly emerged as a pillar of contemporary cancer care. However, the major challenge to precision oncology is that it is mostly based on genomics research and data on caucasian population which puts our and other non caucasian populations at a disadvantage
Over the last decade or so, cancer treatment has significantly changed. From a ‘one size fits all’ approach to a more targeted and precise method, cancer treatment has become much more personalised. Every cancer is different, so should be the treatment. There is a paradigm shift in the way advanced stage cancer patients are being treated today. This shift allows us to tailor treatment on the basis of unique molecular alterations in each patient’s tumor and aligning them with targeted therapies for better treatment outcomes.
Most of these treatment outcomes are predicted on the basis of clinical trials and genomic data primarily from caucasian population. There are many scientific publications which indicate that the response for a specific type of treatment does not work the same way in all the populations and it significantly varies due to genetic diversity. This highlights the need for more population-specific data.
Precision oncology, which integrates genomic biomarkers into the treatment paradigm, has rapidly emerged as a pillar of contemporary cancer care. However, the major challenge to precision oncology is that it is mostly based on genomics research and data on caucasian population which puts our and other non caucasian populations at a disadvantage.
Striking data imbalance in global cancer genomics
There is a glaring gap and disparity that exists when it comes to global cancer genomics data. Individuals of European descent are disproportionately represented in widely-used resources like The Cancer Genome Atlas (TCGA). This imbalance poses challenges in developing truly inclusive cancer treatments and personalised therapies.
According to TCGA data, approximately 77-81 per cent of samples are from individuals of European descent. In comparison, only 12-13 per cent of samples represent African Americans, 3-5 per cent Asians, and just 1-3 per cent Hispanic/Latino populations. Other or unspecified ethnic groups make up less than 2 per cent of the data.
Furthermore, many other researchers from organizations such as National Institute of Health and Partners Healthcare/Harvard Medical School have highlighted similar disparities in the Genome-Wide Association Study Catalog (GWAS) and the database of Genotypes and Phenotypes (dbGaP). In most of these studies, populations of African, Latin American, and Asian descent are underrepresented compared to their European counterparts.
This data gap indicates that we definitely require more extensive and diverse genomic research and need for more inclusive studies to improve the effectiveness of precision medicine for all ethnicities.
Closing the genomic data gap – Why is it important?
Let us discuss a widely used biomarker for Immunotherapy treatment called Tumour Mutation Burden (TMB). As per FDA guidelines, any solid cancer patient with a tumour mutation burden of greater than 10 may respond better to Immunotherapy drugs and are more likely to benefit from the treatment. However, as per an article in ‘Science Journal’ written by Rodrigo Pérez Ortega, TMB score misclassification occurs in 37 per cent of Asian and 44 per cent of African patients. This indicates that doctors could be prescribing expensive immunotherapy drugs, such as pembrolizumab, which costs between $2,000 and $4,000 per dose, to patients who may not even benefit from the treatment.
The above has also been corroborated through our inhouse research data. As per data generated through internal research, we found that in Indian pancreatic cancer patients, TMB score falls at approximately 60th percentile which means that more than 40 per cent of the patients have a TMB score more than 10. In Gastric cancers, it falls at 50th percentile which means every second gastric cancer patient may have a TMB score above 10. In Thyroid cancers, TMB score 10 falls at 95th percentile which means very few thyroid patients will have TMB score =>10 making the score extremely significant. Our research also suggests that a universal TMB score of 10 might not be the best way for classification of cancer patients for treatment with Immunotherapy drugs. The most ideal way would be to look at population specific data and calculate the TMB score based on individual cancer types across different populations.
The way forward
The current genomic data gap that currently exists significantly impacts the development of targeted therapies and diagnostic tools, as treatments may not be as effective or applicable across diverse genetic backgrounds. Closing this data gap is essential to achieving equitable precision medicine, where treatments are tailored to the unique genetic profiles of individuals globally. Increased genomic research in underrepresented populations is critical for this progress.
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