儿童癌症
流行病学
癌症
小儿癌症
医学
癌症流行病学
入射(几何)
分子流行病学
儿童白血病
遗传学
基因组学
生物
种系突变
突变
癌症发病率
肿瘤科
生物信息学
梅德林
体细胞
癌症遗传学
病因学
机制(生物学)
作者
Logan G Spector,Cassandra J. Clark,Zhanni Lu,Nathan Anderson,Erin L. Marcotte,Adam James de Smith
标识
DOI:10.1093/clinchem/hvaf154
摘要
Abstract Background Childhood cancers comprise a variety of liquid and solid tumors that display different patterns of incidence than adult cancers. Most have distinct molecular subtypes characterized by specific genomic driver events. The mutational processes that influence the somatic landscape of cancers also generate distinctive mutational signatures (mutSig). While these signatures are often inert, they do represent a fingerprint of the insult(s) present during mutagenesis. Associating mutSig with putatively causal exposures for pediatric cancer could inform future etiologic studies and elucidate the exposure pathways underlying risk. Content Here we review the epidemiology of pediatric cancers. We then summarize the knowledge around mutSig seen in pediatric cancer to date, discuss observed geographic and subtype-related variability, and discuss future efforts to characterize mutSig with unknown etiologies. Summary The diversity of childhood cancers and their molecular subtypes suggest etiologic heterogeneity. Detection of mutSig in childhood cancers has promoted hypothesis generation; e.g., the enrichment of UV-related signatures in aneuploid B-acute lymphoblastic leukemia has inspired new studies. Although the Mutographs projects were developed to investigate geographical variation in incidence, mutational epidemiology studies should also be employed to understand why certain mutSig are enriched in particular childhood cancers or subtypes. As pediatric cancers have lower mutational burdens than adult cancers, studying childhood cancer may also help determine the causes of mutSig with unknown etiologies. Given persistent differences in pediatric cancer risk by ancestry and socioeconomics, as well as the shifting global burden of childhood cancer, there is a need for studies with patients from diverse populations.
科研通智能强力驱动
Strongly Powered by AbleSci AI