The ‘one-size-fits-all’ approach in medicine is slowly giving way to personalized treatment strategies as scientists discover how and why individuals with the same disease can have very different outcomes in response to treatment. Understanding the characteristics of patients down to the gene level can make diagnosis more accurate and treatments more effective.
For example, ethnicity appears to play a major role in the prevalence of lung adenocarcinoma (LUAD), the most common type of lung cancer in the world. “In Asians, we commonly see the never-smoker phenotype associated with the EGFR mutation,” explained Daniel Tan, a Senior Clinician Scientist at A*STAR’s Genome Institute of Singapore (GIS) and Senior Consultant in the Division of Medical Oncology at National Cancer Centre Singapore. This is in contrast to LUAD in Europeans, which tends to occur in male smokers without the EGFR mutation.
However, because previous studies only examined small populations, they were unable to comprehensively characterize the unique features of East Asian LUAD patients. A study published in Nature Genetics led by first author Jianbin Chen, a Research Associate at GIS, has overcome this issue by combining new data from Chinese patients from Singapore with existing data from other Chinese patients.
The researchers conducted whole-exome and transcriptome sequencing—techniques that look at regions of the DNA that encode proteins—in their large group of LUAD samples from East Asian patients and compared these results to available data from patients of European ancestry.
They found that East Asian patients had more stable genomes, a trait that may influence cancer progression and the development of resistance, said Tan. This genome stability may explain why survival predictions were more accurate for East Asian patients over European patients.
By using an unsupervised algorithm—which searches for previously unknown patterns with minimum input from humans—to cluster their sequencing data, the researchers identified a unique subgroup of tumors in the East Asian population with high levels of inflammation-related genes and immune cells.
“This may represent a unique feature of the tumor microenvironment in lung cancer in Asians,” said Tan. “With the burgeoning pipeline of new immune targets, our analysis could shed light on novel immunotherapy strategies.”
The study highlights the usefulness of genetic features for predicting patient prognosis. The researchers are now exploring the deeper clinical relevance in relation to other features, including pathology reports, immune markers and clinical outcomes such as response to therapy. “In the near future we hope to deploy these selection features in the clinic prospectively,” Tan said.
The A*STAR-affiliated researchers contributing to this research are from the Genome Institute of Singapore (GIS).
