Cancer Cell: Lack of diversity in cancer biomarker data

The researchers reported in the journal Cancer Cell on September 29 that high tumor mutation load — the number of mutations found within cancer cells — may not be able to generalize
as an accurate biomarker in different groups of cancer patients.
The findings may be important
for clinical decision-making in the treatment of immune checkpoint inhibitors, an immunotherapy.

Alexander Gusev of the Dana-Farber Cancer Institute and Harvard Medical School said: "This study has uncovered potential technical issues with high tumor mutation burden (TMB) as a biomarker in different populations that have not been taken seriously
before.
" "Biomarker studies of underrepresented populations are critical to ensuring that differences are minimized in the age of precision medicine
.
"

Recently, ICI pembrolizumab was approved by the U.
S.
Food and Drug Administration (FDA) for the treatment of solid tumors
with high TMB.
As TMB is used for clinical decision-making, its promotion to different real-world environments is a prerequisite for its effectiveness and practicality as a biomarker
.
Leaving aside the question of accurate estimation of TMB, it is critical to understand the prevalence of TMB as a biomarker in different patient cohorts, as TMB high thresholds were largely established in studies of
white patients of European ancestry.
However, to what extent the tmb high classification is generalized as an accurate biomarker in different patient populations
is largely unknown.

To address this knowledge gap, Gusev and Jian Carrot-Zhang, a co-senior study author at the Sloan-Kettering Cancer Memorial Center, analyzed the genetic ancestry
of more than 2,000 patients with common solid tumor types who have undergone ci treatment.
They assessed clinical outcomes such as overall survival and time to
ICI failure.
Gusev said: "As far as we know, this is the largest analysis
of the interaction between gene ancestry, TMB and immunotherapy results.
"

In two separate clinical cohorts, TMB estimates from the commonly used tumor sequencing group greatly overclassified individuals as TMB high, especially in non-Europeans
.
This bias is particularly pronounced
in patients of Asian or African ancestry.
Based on the results, a high misclassification of tmb was expected to affect 21 percent of patients of European ancestry, compared with 37 percent and 44 percent
of patients of Asian or African ancestry, respectively.

Gusev said: "If this holds true in the general patient population, it will have a significant impact on
the treatment options of many patients.
" "It's important to note that this is purely a technical bias
.
The study proposes a calculation method for correcting tumor TMB estimates, as well as a modified calculation method
that should be widely applicable.
”

As a proof of concept, the authors next applied their TMB recalibration method to PCI-treated non-small cell lung cancer patients
.
The tmb high classification is significantly associated with improved prognosis only in European ancestry and is therefore validated
in people of non-European ancestry.
Gusev said: "This does not mean that TMB should not be used as a biomarker for individuals of non-European ancestry, but it does mean that more research and data collection is needed to determine the precise threshold
used to optimize treatment outcomes.
" "We also hope this underscores the broader importance of assessing the accuracy of biomarkers in different populations
.
"

Further analysis showed that alterations in the MGA gene were associated with longer overall survival and ICI failure times in Europeans, not with outcomes in Africans, and with worse outcomes in
Asians.
Gusev said: "We observed ancestor-specific effects of some individual-driven genes, suggesting that this phenomenon may not be unique to TMB, but also applies to individual mutations and has implications
for other targeted therapies.
"

An important limitation of the study was that the sample sizes of non-Europeans in both groups of studies were small
.
Gusev said: "It is critical to accelerate the collection of data and results from these populations so that we can better understand how TMB and other biomarkers can be effectively generalized to all patients
.
" "Sample sizes limit our ability to study more cancer types, individual genomic changes, and more population-specific particle effects — all of which could yield important additional insights
.
"

Ancestor-driven recalibration of tumor mutation burden and different clinical outcomes for immune checkpoint inhibitors