Racial diversity of actionable mutations in non-small cell lung cancer

Abstract

Introduction: Lung cancer is the leading cause of cancer-related deaths in the US. The reasons for higher incidence and poorer survival rates among black compared with white lung cancer patients have not been defined. We hypothesized that differential incidence of somatic cancer gene mutations may be a contributing factor. Previous genomic studies of non-small cell lung cancer (NSCLC) have not adequately represented black patients.

Methods: A matrix-assisted laser desorption/ionization and time-of-flight mass spectrometry approach was used to analyze tumor DNA for 214 coding mutations in 26 cancer genes previously identified in NSCLC. The samples included NSCLC from 335 white patients and 137 black patients. For 299 of these, normal matched DNA was available and analyzed.

Results: Epidermal growth factor receptor (EGFR) exon 19 deletions were only detected in women cases, with increased odds for black women compared with white women (odds ratio = 3.914, 95% confidence interval: 1.014-15.099, p = 0.048). Beyond race, variations in mutation frequencies were seen by histology. DDR2 alterations, previously described as somatic mutations, were identified as constitutional variants.

Conclusions: This study is among the largest comparing somatic mutations in black and white patients. The results point to the molecular diversity of NSCLC and raise new questions as to the importance of inherited alleles. Genomic tumor testing will benefit both populations, although the mutation spectrum appears to vary by sex, race, and histology.

Figure 1

Overall rates of detection & patterns of multi-mutations by race. The percentages of specimens where a single mutation or multiple mutations were discovered are presented in the pie graphs (left). The frequencies for the co-occurrence of mutated genes are displayed in the charts (right).

Figure 2

Overall rates of detection & patterns of multi-mutations by histology. The percentages of specimens where a single mutation or multiple mutations were discovered are presented in the pie graphs (left). The frequencies for the co-occurrence of mutated genes are displayed in the charts (right).