Disease evolution and heterogeneity in bilateral breast cancer

Abstract

Bilateral breast cancers (BBC) are currently treated as independent tumors arising in the same patient. Herein, we investigated whether BBC indeed evolve independently at the genomic level. We examined paired targeted next generation sequencing genotypes from 155 paraffin tumors corresponding to 76 BBC patients (75 women and one man; 52 concurrent and 24 metachronous), for coding mutations (amino acid changing, minor allele frequency <0.1%) and single nucleotide polymorphism (SNP) zygosity. Germline genotypes were available for 29 patients. Mutations were present in 80 tumors (54/76 patients; 71%), were mostly tumor-private (90%), more frequent in TP53 (19%), PIK3CA (14%), CDH1, GATA3, MLL3. TP53 mutations were more frequent in metachronous tumors (P<0.001); hormone receptor negative (P<0.001); with higher Ki-67 (P=0.002); and, in younger patients (P=0.01). Hypermutated tumors, all TP53 mutated, were diagnosed as the first incidence in 5 patients; their metachronous counterparts were mutation poor without TP53 involvement. Paired tumors shared common mutations at intratumoral frequency >20% in 10/54 comparable BBC (18.5%), 8/10 concurrent. SNP zygosity status was less preserved in metachronous, compared to concurrent disease. Pathogenic germline mutations were present in 10/29 patients, 9 in BRCA1 and one in TP53 (p.Phe341Val, first report in the germline). BBC demonstrated extensive inter- and intra-patient heterogeneity in the present thus far largest series of corresponding paired genotypes. The majority evolve independently and unpredictably, supporting current clinical practice. A considerable minority though, retains clonal origin and may be regarded as a distinct group for therapeutic interventions among concurrent BBC.

Keywords: Bilateral; breast cancer; clonality; coding mutations; concurrent; contralateral; hypermutation; metachronous; targeted next generation sequencing.

Figure 1

Study outline (REMARK).

Figure 2

Distribution of NGS variants in BBC. A. Distribution of variants of any type in the study cases. All variants, SNPs and coding mutations are shown per case. For similar sequencing efficiency metrics (total reads, on target reads, uniformity of reads), 5-214 variants were identified per case (mean ± SD: 23 ± 30; median: 22), up to 54 in the same gene (mean ± SD: 15 ± 7; median: 12). Asterisks: truncated Y-axis for cases with >50 variants. B. Distribution of variants per gene. Grey bars: total number of variants of any type. Coding mutations were identified in 41 out of 61 genes in the MPS panel (red bars). The total number of mutations per gene varied from 1 to 49 (median: 3 mutations per gene). In additional 10 genes, only SNPs were present (blue bars). The number of SNPs per sample ranged from 10-20. Asterisks: >100 variants for these genes. C. Common and private SNPs and coding mutations. SNPs were preserved at 94% in both sides (922/983 comparable SNPs); by contrast, only 4.9% common coding mutations were observed (10/202 comparable mutations). The remaining 192 comparable mutations were present unilaterally, as shown. D. Distribution of gene coding mutations on either side; common, private A and private B mutations represented by blue, green and orange bars, respectively.

Figure 3

Mutation patterns in concurrent and metachronous BBC. (A) Distribution of mutations and mutated genes in tumors of both sides. SNP numbers are shown for comparison of sequencing performance of the samples; these did not differ for samples in side 1 vs. side 2 (Mann-Whitney P=0.5656) and showed a good correlation upon bivariate comparisons (Spearman’s rho 0.641; P<0.0001). The matched tumor was not available in one of the hypermutated cases (arrow). (B and C) mutation maps in concurrent (B) and metachronous (C) cases. The number of mutations per gene is indicated on the color scale. Indicated are germline mutations; hypermutated tumors; tumors with shared mutations. Most frequently mutated gene in concurrent samples is PIK3CA, followed by TP53 and GATA3. Metachronous tumors carry more frequently mutations in TP53, followed by PIK3CA and CDH1.

Figure 4

Bilateral comparisons of Variant Allele Frequencies (VAFs). A. VAF distribution for coding mutations and SNPs in both sides and in the germline. Germline variants as identified with the tissue panel. VAF distribution for coding mutations was skewed towards 0, with mean (median) values of 21% (14%) in side 1 and 30% (21%) in side 2. Most mutation VAFs were <25%, particularly in Side 1. B. Coding mutation VAFs are significantly lower in hypermutated as compared to non-hypermutated tumors (Mann-Whitney P<0.001). Numbers in parentheses: mean values for VAFs. N: number of mutations. Note that the contralateral tumors paired to hypermutated ones exhibited only one mutation in 3 out of 4 comparable cases, although they were diagnosed years later after the hypermutated tumors. C. Bilateral correlations of SNP VAFs in matched samples. Tumors in side 1 (T1) and in side 2 (T2) were compared with each other and with germline. SNPs were identified with the tissue panel. Triangles and circles: altered zygosity for these SNPs. Spearman’s rho values yielded P’s <0.0001 in all comparisons.

Figure 5

Example bilateral breast cancer (BBC) genotypes with corresponding histology. Three different cases are shown: BIL-041 (A), BIL-073 (B), BIL-078 (C), with case IDs as in Table S1. (A and C) Concurrent; (B) Metachronous. Note the different bilateral tumor genotypes in all cases; different mutations in hyperplastic lesions (ADH) in (A); shared mutations in the in situ carcinoma (DCIS) and in the unilateral tumor in (B), which were also morphologically consistent; shared TP53 mutation in the bilateral normal samples in the male BBC case in (C). SNPs were consistently shared among samples in (B) and (C) but less so in the case in (A). NST: non-specific type.