Epigenome-Wide Association Studies Identify DNA Methylation Associated With Kidney Function
Chu AY Tin A, Schlosser P, Ko Y A, et al. Nat Commun. 2017;8(1):1286.
Epigenome-wide association studies identify DNA methylation associated with kidney function
Chronic kidney disease (CKD) is often familial. Only a small part of these diseases are classical monogenic, environmental factors and DNA sequence variants play a major role in the development of CKD. Epigenomewide association studies have identified more than 60 genetic loci associated with CKD. Altered transcriptional regulation due to epigenetic changes has a major role in DNA methylation influencing the incidence of CKD and its progression.
Cu and coworkers formulated 3 aims for their study:( i) to use epigenomewide association studies for the discovery and validation of genomewide differences in DNA methylation at CpG sites (CpGs) that is present in patients with CKD; (ii) to characterize these validated CpGs in kidney tissue; and (iii) lastly, to link differential DNA methylation to compromised kidney function.
The authors enrolled 2264 African American patients from the Atherosclerosis Risk in Communities Study and 2595 European ancestry participants form the Framingham Heart Study. DNA methylation at > 440 000 CgGs were examined in whole blood. In the Atherosclerosis Risk in Communities study 16 CpGs were associated with prevalent CKD, while 11 CpGs were associated with prevalent CKD in the Framingham Heart Study. In total, 5 CpGs were associated with a degree of fibrosis in kidney biopsies, a pathological correlation with CKD.
Next, DNA methylation sites were quantified from the cortical tubule portion of 95 microdissected human kidney samples to investigate whether the CpG associations in whole blood translated to kidney tissue. Of the 19 replicated CpGs, 5 showed significant association with renal fibrosis.
This well-powered study has identified important target genes for future mechanistic and therapeutic strategies of CKD.
Patient-Derived Xenografts Undergo Mouse-Specific Tumor Evolution
Uri BD, Ha G, Tseng YY, et al. Nat Genet. 2017;8(1):1286.
Do patient-derived xenografts (PDXs) capture the genomic landscape of primary tumors better than cell lines? The ability to transfer human tumors into mice offers unique opportunities for cancer research and drug discovery. PDXs have become a prominent cancer model system, because they are presumed to faithfully represent the genomic features of primary tumors.
The authors systematically analyzed landscapes of aneuploidy and large copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. The collected data were used to characterize CNA dynamics and to compare PDX genomic stability across cancer types. The authors evaluated whether clonal dynamics observed in PDXs were similar to human patients by identifying 61 recurrent arm-level CNAs across different tumor types and following them in PDXs.
CNA landscapes of PDXs were highly similar to their respective tumor types. Furthermore, CNA acquisition in PDXs correlated with the tissue-specific levels of aneuploidy and genetic heterogeneity observed in primary tumors.
However, the particular CNAs acquired during PDX passaging differed from those acquired during clinical tumor evolution with findings suggesting that the genomic instability of PDXs had been underappreciated before. Several CNAs recurrently observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Notably, the genomic stability of PDXs was associated with their response to chemotherapy and targeted drugs.
These findings have major implications for PDX-based modeling of human cancer.