Cancer-Causative Mutations Occurring in Early Embryogenesis

Abstract

Mosaic mutations in normal tissues can occur early in embryogenesis and be associated with hereditary cancer syndromes when affecting cancer susceptibility genes (CSG). Their contribution to apparently sporadic cancers is currently unknown. Analysis of paired tumor/blood sequencing data of 35,310 patients with cancer revealed 36 pathogenic mosaic variants affecting CSGs, most of which were not detected by prior clinical genetic testing. These CSG mosaic variants were consistently detected at varying variant allelic fractions in microdissected normal tissues (n = 48) from distinct embryonic lineages in all individuals tested, indicating their early embryonic origin, likely prior to gastrulation, and likely asymmetrical propagation. Tumor-specific biallelic inactivation of the CSG affected by a mosaic variant was observed in 91.7% (33/36) of cases, and tumors displayed the hallmark pathologic and/or genomic features of inactivation of the respective CSGs, establishing a causal link between CSG mosaic variants arising in early embryogenesis and the development of apparently sporadic cancers.

Significance: Here, we demonstrate that mosaic variants in CSGs arising in early embryogenesis contribute to the oncogenesis of seemingly sporadic cancers. These variants can be systematically detected through the analysis of tumor/normal sequencing data, and their detection may affect therapeutic decisions as well as prophylactic measures for patients and their offspring. See related commentary by Liggett and Sankaran, p. 889. This article is highlighted in the In This Issue feature, p. 873.

Figure 1.. Identification of cancer patients with candidate early mosaic variants.

A, Schematic representation of the methodology for selection of patients with candidate mosaic variants in CSGs, sequencing methods, selection algorithm, filtering and exclusion criteria and selected variants. B, Variant allele fraction (VAF), sequencing depth and variant type of the candidate pathogenic/likely pathogenic (P/LP) mosaic variants identified by the set of filters in blood and tumor. C, Tumor type and germ layer derivation, CSG affected, variant type, biallelic inactivation of P/LP candidate mosaic variants (n=36). Phenobars (right) depict clinical characteristics. CSG, cancer susceptibility gene, PANET, pancreatic neuroendocrine tumor; MPNST, malignant peripheral nerve sheet tumor; SCCOHT, small cell carcinoma of the ovary hypercalcemic type.

Figure 2.. Validation of candidate mosaic variants affecting mismatch repair genes by targeted sequencing.

A, Schematic representation of the validation method of candidate mosaic variants and representative micrographs of hematoxylin and eosin (H&E)-stained tumors and normal tissues of case MOS14. Scale bars, 1 mm. B, Variant allele fraction (VAF) of the mosaic variants and tumor-derived non-synonymous somatic mutations in microdissected tumors and normal tissues according to germ layer. C-D, VAF of the mosaic variants affecting mismatch repair genes (red) and of tumor-derived non-synonymous somatic mutations (gray) in tumor and normal tissues and tumor mutational signatures. Error bars,95% CI. Representative photomicrographs of H&E-stained slides and immunohistochemistry analysis of mismatch repair proteins are depicted. Scale bars,50 μm. AP, appendix; C1, histologic component 1; C2, histologic component 2; CO, colon; EM, endometrium; FT, fallopian tube epithelium; MSI, microsatellite instability; N, normal; SMM, smooth muscle; SNV, single nucleotide variation; T, tumor; VAF, variant allele fraction.

Figure 3.. Validation of candidate mosaic variants affecting homologous recombination deficiency genes by targeted sequencing.

A-B, Variant allele fraction (VAF) of the mosaic variants affecting BRCA2 (red) and of tumor-derived non-synonymous somatic mutations (gray) in tumor and normal tissues and tumor mutational signatures. Copy number plots depicting segmented Log₂ ratios (y-axis) according to genomic position (x-axis). C, Number of state transitions according to segment size. Each line corresponds to a tumor (n=15) of the 10 individuals in the validation cohort. DCIS, breast ductal carcinoma in situ; HRD, homologous recombination deficiency; IDC, breast invasive ductal carcinoma; SNV, single nucleotide variation; VAF, variant allele fraction.

Figure 4.. Timing of occurrence and mutational processes of mosaic variants.

A, Schematic representation of the first cell divisions of embryogenesis along with the expected variant allele fraction (VAF) of mosaic variants per cell generation in adult normal tissues assuming a symmetrical cell contribution. B, VAF distribution of the 36 CSG mosaic variants. Expected VAF distribution from symmetric cell contribution (red line) and best fitting cell contribution mixture model (blue line). C, Contour plots depicting the Log likelihoods of symmetric and asymmetric cell contributions. The x axis and y axis display the expected VAFs of the first and second cell divisions, respectively (left), and of the third and fourth cell divisions, respectively (right), given different cell contribution asymmetry levels (right x and top y axes). The dotted lines represent the expected VAFs of the respective cell divisions as per a symmetric cell contribution model. (X), symmetric model; (+), best fitting asymmetric model. D, Assignment of the 36 mosaic variants to the VAF clusters of the best fitting mixture model. The means of four VAF clusters are shown in red (cluster 1), blue (cluster 2), green (cluster 3) and orange (cluster 4). The expected VAF of mosaic variants occurring in the first five cell generations assuming a symmetric cell contribution are shown as black dotted lines. Error bars, 95 CI. E, Posterior probabilities of the 36 mosaic variants to belong to each of the four VAF clusters identified using the Beta-Binomial mixture model. F, Single nucleotide variant (SNV) and indels mutational signatures of the 36 mosaic variants identified.