Breast Cancer’s Genetic Relationship to Other Cancers
Posted: Tuesday, April 30, 2019
Utilizing the latest sophisticated statistical models and wide-ranging genetic data, a research team’s study results reveal that numerous “solid tumors arising across tissues share in part a common germline genetic basis,” wrote Xia Jiang, PhD, of the Harvard T.H. Chan School of Public Health, Boston, and colleagues. Among the significant associations they found were between breast and ovarian cancers, breast and lung cancers, and breast and colorectal cancers.
The team accessed the database of summary statistics from the largest-to-date European ancestry genome-wide association study (GWAS) of breast, colorectal, head/neck, lung, ovarian, and prostate cancers. The average sample size was 49,369 cases and 50,219 controls per cancer. The work was published in Nature Communications.
The significant GWAS loci for a particular cancer, such as breast cancer, explained most of its heritability. However, in some cancers, significant GWAS loci of other cancers also contributed a nontrivial part of its heritability. Significant breast cancer GWAS loci explained 10%, 15%, and 22% heritability of colorectal, ovarian, and prostate cancers, respectively, and the significant prostate cancer GWAS loci explained 11% and 15% heritability of breast and ovarian cancers, respectively.
In addition, Dr. Jiang and co-investigators sought to find genetic correlations that might exist between noncancer traits and cancer. They discovered, among others, a weak negative correlation between body mass index and breast cancer; a positive genetic correlation between breast cancer and schizophrenia; and no significant correlation between breast cancer and either age at menarche or natural menopause.
Dr. Jiang and colleagues believe their results provide direction for future cross-cancer studies to generate insights into the biologic mechanisms underlying cancer development and etiology. Further work that continues to identify new susceptibility loci “could help our understanding of disease development, improve [the] prediction power of genetic risk scores, and hence contribute to screening and personalized risk prediction,” they wrote.
Disclosure: The study authors reported no conflicts of interest.