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. 2015 Dec 10;373(24):2336-2346.
doi: 10.1056/NEJMoa1508054. Epub 2015 Nov 18.

Germline Mutations in Predisposition Genes in Pediatric Cancer

Jinghui Zhang #  1 , Michael F Walsh #  1 , Gang Wu #  1 , Michael N Edmonson  1 , Tanja A Gruber  1 , John Easton  1 , Dale Hedges  1 , Xiaotu Ma  1 , Xin Zhou  1 , Donald A Yergeau  1 , Mark R Wilkinson  1 , Bhavin Vadodaria  1 , Xiang Chen  1 , Rose B McGee  1 , Stacy Hines-Dowell  1 , Regina Nuccio  1 , Emily Quinn  1 , Sheila A Shurtleff  1 , Michael Rusch  1 , Aman Patel  1 , Jared B Becksfort  1 , Shuoguo Wang  1 , Meaghann S Weaver  1 , Li Ding  1 , Elaine R Mardis  1 , Richard K Wilson  1 , Amar Gajjar  1 , David W Ellison  1 , Alberto S Pappo  1 , Ching-Hon Pui  1 , Kim E Nichols #  1 , James R Downing  1
Affiliations

Germline Mutations in Predisposition Genes in Pediatric Cancer

Jinghui Zhang et al. N Engl J Med. .

Abstract

Background: The prevalence and spectrum of predisposing mutations among children and adolescents with cancer are largely unknown. Knowledge of such mutations may improve the understanding of tumorigenesis, direct patient care, and enable genetic counseling of patients and families.

Methods: In 1120 patients younger than 20 years of age, we sequenced the whole genomes (in 595 patients), whole exomes (in 456), or both (in 69). We analyzed the DNA sequences of 565 genes, including 60 that have been associated with autosomal dominant cancer-predisposition syndromes, for the presence of germline mutations. The pathogenicity of the mutations was determined by a panel of medical experts with the use of cancer-specific and locus-specific genetic databases, the medical literature, computational predictions, and second hits identified in the tumor genome. The same approach was used to analyze data from 966 persons who did not have known cancer in the 1000 Genomes Project, and a similar approach was used to analyze data from an autism study (from 515 persons with autism and 208 persons without autism).

Results: Mutations that were deemed to be pathogenic or probably pathogenic were identified in 95 patients with cancer (8.5%), as compared with 1.1% of the persons in the 1000 Genomes Project and 0.6% of the participants in the autism study. The most commonly mutated genes in the affected patients were TP53 (in 50 patients), APC (in 6), BRCA2 (in 6), NF1 (in 4), PMS2 (in 4), RB1 (in 3), and RUNX1 (in 3). A total of 18 additional patients had protein-truncating mutations in tumor-suppressor genes. Of the 58 patients with a predisposing mutation and available information on family history, 23 (40%) had a family history of cancer.

Conclusions: Germline mutations in cancer-predisposing genes were identified in 8.5% of the children and adolescents with cancer. Family history did not predict the presence of an underlying predisposition syndrome in most patients. (Funded by the American Lebanese Syrian Associated Charities and the National Cancer Institute.).

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Figures

Figure 1
Figure 1. Frequency of Pediatric Cancer Types among Patients Younger than 20 Years of Age
Panel A shows the distribution of pediatric cancer types on the basis of data from the Surveillance, Epidemiology, and End Results (SEER) program. Panel B shows the distribution of cancer types analyzed by the Pediatric Cancer Genome Project (PCGP). ACT denotes adrenocortical tumor, CNS central nervous system, and STS soft-tissue sarcoma.
Figure 2
Figure 2. Categories of the 565 Cancer Genes Analyzed for Germline Mutations
The number of genes in each category is shown in parentheses. Genes that have overlapping categories are listed only once. Gene names in the other categories are shown in Figure S9 in Supplementary Appendix 1. RASopathies are genetic syndromes that include the cardiofaciocutaneous syndrome, Costello’s syndrome (also called the faciocutaneoskeletal syndrome), Noonan’s syndrome, and the multiple lentigines syndrome.
Figure 3
Figure 3. Distribution of Germline Mutations in Different Gene Categories and Cancer Subtypes
Panels A and B include only mutations that were deemed to be pathogenic or probably pathogenic and that affect genes that have been associated with autosomal dominant cancer-predisposition syndromes, according to tumor subtype. Panel A shows the distribution of mutations in each gene among patients with various cancers included in the PCGP cohort. Panel B shows the prevalence of the mutations in each cancer subtype. Five patients with melanoma without mutations are not shown, and one patient (HGG027) who had a CNS tumor with biallelic mutation in an autosomal recessive gene (ATM) is not included in the summary. Panel C shows the number of patients who had germline mutations considered to be pathogenic or probably pathogenic in genes that have been associated with autosomal dominant (60 genes) and autosomal recessive (29) cancer susceptibility, according to cancer subtype. Panel D shows the total number of patients who had truncation mutations in tumor-suppressor genes, tyrosine kinase genes, and other cancer genes, according to cancer subtype.
Figure 4
Figure 4. Distinguishing Mosaicism from Tumor Contamination
Panel A shows that in the tumor-contaminated germline sample of Patient 1 (E2A019), most somatic mutations were observed at a lower frequency in the germline than in the tumor. Nine genes were selected to show this point. Panel B shows that in the case of mosaicism in Patient 2 (HYPO055), only one TP53 mutation was observed at a lower frequency in the germline than in the tumor. Other somatic mutations in the tumor were absent in the matched germline sample. Panel C shows that MiSeq sequencing confirmed that the mutant allele fraction (MAF) of TP53 c.C374G (coding for p.T125R) in the germline sample of Patient 2 was still low (0.20; only 487 reads of 2383 reads had the mutation), a finding that is consistent with germline mosaicism. Two minor peaks supporting C and G alleles (arrows) were seen in the Sanger-sequencing chromatograph.
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