Precision Oncology Data Registry May Perpetuate Health Disparities

Researchers from Massachusetts General Hospital (MGH) revealed in a study published in npj Precision Oncology that the American Association of Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE), a publicly available, international cancer registry, lacks sufficient representation of cancer distribution among racial and ethnic minorities.

According to the press release, biorepositories like GENIE are designed to support precision oncology research by providing large amounts of genomic data. However, these data registries have historically included mostly white patients, which can limit t   generalizability of study findings to other patient groups.

“The need is greater than ever for diversity to be a mission-critical priority for precision medicine so that breakthroughs or new findings from biorepositories can broadly apply to and be safe for diverse cancer populations,” said senior study author Sophia Kamran, MD, radiation oncologist with the MGH Department of Radiation Oncology, and director of Diversity, Equity, and Inclusion for the department, in the press release.

In the study, the researchers evaluated GENIE’s representation of various patient populations since the registry is widely used in clinical research to describe novel genomic variations between racial categories of different tumors. But the findings among studies using the tool often conflict.

To evaluate GENIE’s representation compared to the broader cancer populations, the research team leveraged the Centers for Disease Control and Prevention’s Wide-Ranging Online Data for Epidemiologic Research (CDC-WONDER), which defines the proportion of cancer patients expected from each racial and ethnic group for a given cancer type.

By comparing the two, the researchers found that White patients were adequately or overly represented with GENIE for all cancer types except lung cancer and melanoma. Similarly, Asian patients had significant overrepresentation across several tumor types, including breast, lung, and colorectal cancers.

However, other groups had little to no representation. Black patients were found to be underrepresented for most cancers, except melanoma and cervical cancer, and Hispanic patients were consistently underrepresented among all cancers. Likewise, Native American and Pacific Islander patients had zero representation for many cancer types.

“Our findings suggest that these data registries do not reflect the true landscape of cancer patients in the U.S., and may therefore misrepresent the disease burden in many racial/ethnic minority populations,” said Kamran, adding that “GENIE is not sufficiently powered to detect small yet potentially clinically meaningful differences between White and non-White patients in even the most common cancer types.”

The reasons for low representation in some groups and overrepresentation in others vary, the press release stated. Some of this phenomenon is likely explained by mistrust of clinical research agendas by minority patients and ingrained institutional exclusion and bias.

These findings may also indicate limited generalizability of biomarker discoveries to all patient populations, which could perpetuate health disparities.

Despite this, the researchers noted that bringing recognition to this problem may lead to some improvements.

“Even basic changes in methodology and recruitment for future biorepositories can dramatically improve their ability to address health disparities,” said Kamran. “For instance, standardized methods to obtain demographic information of participants should be implemented by all institutions, and self-identified ethnicities should have more options than the binary ‘Hispanic’ or ‘Non-Hispanic’ present in the current GENIE database.”

This study is part of a larger trend to leverage and improve biobanks and data registries to bolster precision medicine.

In September, researchers at UCLA found that the genomic data from the UCLA ATLAS Precision Health Biobank is highly diverse. Thus, they plan to use the biobank to support precision medicine efforts for underrepresented populations.

The research team discovered that the biobank’s data mirrors the diversity of Los Angeles, which they noted is one of the most ethnically diverse cities in the world. The data represent genetic ancestry but also take into account self-identified race and identity, which are tied to social constructs and shared values, cultural norms, and behaviors within their subgroups. These can provide insights into systemic issues impacting the health of these groups, such as clinical care disparities and care access.

By analyzing these data, the researchers hope to explore the relationship between them as it relates to population health and precision medicine. To date, they have analyzed the genomes of 30,000 patients with ancestries from almost every continent.