Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Background: Tumor heterogeneity in breast cancer tumors is today widely recognized. Most of the available knowledge in genetic variation however, relates to the primary tumor while metastatic lesions are much less studied. Many studies have revealed marked alterations of standard prognostic and predictive factors during tumor progression. Characterization of paired primary- and metastatic tissues should therefore be fundamental in order to understand mechanisms of tumor progression, clonal relationship to tumor evolution as well as the therapeutic aspects of systemic disease. Methods: We performed full exome sequencing of primary breast cancers and their metastases in a cohort of ten patients and further confirmed our findings in an additional cohort of 20 patients with paired primary and metastatic tumors. Furthermore, we used gene expression from the metastatic lesions and a primary breast cancer data set to study the gene expression of the AKAP gene family. Results: We report that somatic mutations in A-kinase anchoring proteins are enriched in metastatic lesions. The frequency of mutation in the AKAP gene family was 10% in the primary tumors and 40% in metastatic lesions. Several copy number variations, including deletions in regions containing AKAP genes were detected and showed consistent patterns in both investigated cohorts. In a second cohort containing 20 patients with paired primary and metastatic lesions, AKAP mutations showed an increasing variant allele frequency after multiple relapses. Furthermore, gene expression profiles from the metastatic lesions (n = 120) revealed differential expression patterns of AKAPs relative to the tumor PAM50 intrinsic subtype, which were most apparent in the basal-like subtype. This pattern was confirmed in primary tumors from TCGA (n = 522) and in a third independent cohort (n = 182). Conclusion: Several studies from primary cancers have reported individual AKAP genes to be associated with cancer risk and metastatic relapses as well as direct involvement in cellular invasion and migration processes. Our findings reveal an enrichment of mutations in AKAP genes in metastatic breast cancers and suggest the involvement of AKAPs in the metastatic process. In addition, we report an AKAP gene expression pattern that consistently follows the tumor intrinsic subtype, further suggesting AKAP family members as relevant players in breast cancer biology.Peer reviewe

Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Abstract Background Tumor heterogeneity in breast cancer tumors is today widely recognized. Most of the available knowledge in genetic variation however, relates to the primary tumor while metastatic lesions are much less studied. Many studies have revealed marked alterations of standard prognostic and predictive factors during tumor progression. Characterization of paired primary- and metastatic tissues should therefore be fundamental in order to understand mechanisms of tumor progression, clonal relationship to tumor evolution as well as the therapeutic aspects of systemic disease. Methods We performed full exome sequencing of primary breast cancers and their metastases in a cohort of ten patients and further confirmed our findings in an additional cohort of 20 patients with paired primary and metastatic tumors. Furthermore, we used gene expression from the metastatic lesions and a primary breast cancer data set to study the gene expression of the AKAP gene family. Results We report that somatic mutations in A-kinase anchoring proteins are enriched in metastatic lesions. The frequency of mutation in the AKAP gene family was 10% in the primary tumors and 40% in metastatic lesions. Several copy number variations, including deletions in regions containing AKAP genes were detected and showed consistent patterns in both investigated cohorts. In a second cohort containing 20 patients with paired primary and metastatic lesions, AKAP mutations showed an increasing variant allele frequency after multiple relapses. Furthermore, gene expression profiles from the metastatic lesions (n = 120) revealed differential expression patterns of AKAPs relative to the tumor PAM50 intrinsic subtype, which were most apparent in the basal-like subtype. This pattern was confirmed in primary tumors from TCGA (n = 522) and in a third independent cohort (n = 182). Conclusion Several studies from primary cancers have reported individual AKAP genes to be associated with cancer risk and metastatic relapses as well as direct involvement in cellular invasion and migration processes. Our findings reveal an enrichment of mutations in AKAP genes in metastatic breast cancers and suggest the involvement of AKAPs in the metastatic process. In addition, we report an AKAP gene expression pattern that consistently follows the tumor intrinsic subtype, further suggesting AKAP family members as relevant players in breast cancer biology

Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq

Our understanding of the development and maintenance of tissues has been greatly aided by large-scale gene expression analysis. However, tissues are invariably complex, and expression analysis of a tissue confounds the true expression patterns of its constituent cell types. Here we describe a novel strategy to access such complex samples. Single-cell RNA-seq expression profiles were generated, and clustered to form a two-dimensional cell map onto which expression data were projected. The resulting cell map integrates three levels of organization: the whole population of cells, the functionally distinct subpopulations it contains, and the single cells themselves—all without need for known markers to classify cell types. The feasibility of the strategy was demonstrated by analyzing the transcriptomes of 85 single cells of two distinct types. We believe this strategy will enable the unbiased discovery and analysis of naturally occurring cell types during development, adult physiology, and disease

Additional file 5: of Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Figures S3a and S3b. Estimation of LOH fraction and tumor content. Estimation of LOH fraction and tumor content using a Beta-Normal mixture model. Histograms show the distribution of major allele frequencies (range: 50–100%) and red curves show the mixture model estimated from the data. The set of SNPs called in the germline sample was considered in the tumor sample (primary and metastasis independently). When genomes contain regions of LOH, the distribution will be bimodal, as illustrated in the inset (top right). The first component (closer to 50%; red in inset) represents heterozygous SNPs in regions without LOH and was modeled as a normal distribution with a mean close to 50% in a perfect sample, but will increase towards 100% as allelic dropout increases. The second component (closer to 100%; blue in inset) represents homozygous SNPs in regions with LOH, was modeled as a beta distribution with two parameters (the mean of this component should be close to 100% and increase as LOH fraction increases and decrease as with non-cancer cell contamination. The mixture distribution thus had four free parameters plus the mixture proportion, the latter representing the estimated LOH fraction of the sample. Fitting this mixture to the observations yielded estimates for LOH fraction, tumor fraction and allelic dropout rate for each sample (Additional file 3: Figure S2). Model fitting was performed using the EstimatedDistribution function of Mathematica 9.0 (Wolfram Research Inc.). (ZIP 421 kb

Additional file 7: of Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Figure S4. AKAP mutations in TCGA data. a) AKAP mutations across all cancers available through cBioPortal (TCGA, provisional). b) AKAP mutations and gene expression alterations in Breast Invasive Carcinoma, (TCGA, provisional). (PDF 753 kb

Additional file 8: of Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Figure S5. AKAP gene expression. Boxplots showing summed expression of AKAP 8,7,3,1 and AKAPs 5,11,9,10,12 gene expression within each PAM50 molecular subgroup, a-b; TCGA data, c-d; risk cohort, d-e; cohort 1. P-values are indicative of ANOVA followed by post-hoc Tukey for Basal vs. other subtypes individually. ***; p ≤ 0.001, **; p ≤ 0.01. (PDF 586 kb

Additional file 6: of Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Table S3. Control experiment. To investigate the rate of false positive mutations as well as the loss of alleles introduced by the amplification process we designed a control experiment as follows: Genomic DNA from a healthy individual was extracted from whole blood using the PAXgene Blood DNA kit (Qiagen). The DNA was of good quality (> 58 kB fragment length) and of high concentration (> 300 ng/uL). This DNA was diluted 1:100 and 1:1000 and 6 ng respectively 0.6 ng was subjected to WGA, exome enriched, sequenced and analyzed as described in (Fig. 2a) using an unamplified sample as ‘germline’ control. In the control exome experiment with 6 ng input gDNA, we found no (zero) variant positions, indicating that the false discovery rate was negligible when the amount of starting material was in the range of 6 ng or more. In the control exome experiment with 0.6 ng input gDNA, we found 27 amino acid altering mutations that passed our SNV calling criteria. This indicates that false positive SNVs can start to appear as the amount of input material is reduced. We used this higher rate of false positives to estimate the false discovery rate (FDR) in samples with input less than 6 ng. Note that no tumor sample was amplified from less than 1.2 ng DNA. Allelic drop out or loss of heterozygosity due to biased amplification towards one of the alleles will be challenging to distinguish from true LOH. As expected, in the control exomes no LOH was detected. The fraction of called LOH positions was 0.6% and 1% of all variant positions in the 6 ng and 0.6 ng control experiments respectively, and these positions did not form continuous regions. In most tumor samples, we could clearly distinguish regions of true LOH, as blocks of SNPs with LOH calls. Outside these regions, any observed LOH could be assumed to be artefactual. We therefore determined the fraction of LOH calls in regions without signs of true LOH in the tumor samples, as a measure of false negative calls (allelic dropout). In the primary tumor samples we found 1.36% (0.1%- 8.3%) false negatives, whereas in the metastatic samples this fraction was 4.88% (0%–16.25%). However, three of the samples (metastases of patients P1, P4 and P10) were of poor quality showing a very noisy pattern of variant allele frequencies, most likely due to DNA degradation and low concentration. In these three samples the false negative discovery rate could not be calculated but could be approximated by assuming that there were no true LOH calls at all, resulting in a conservative estimate of 43–87% false negative calls in these three samples. We could not identify LOH independently in these samples, but we used the SNP phase test described in (Additional file 4: Figure S1a-b) to confirm or reject the existence of LOH alterations in the metastatic lesion concordant with the primary tumor. Although the median false negative SNV rate was less than 1%, the metastatic samples of three patients (P1, P4 and P10) suffered a rate exceeding 40%, presumably due to allelic dropout during amplification. The median false discovery rate was 1%, and did not exceed 6% for any patient. (PDF 398 kb

Additional file 4: of Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Figures S1a and S1b. Exome-wide view of mutations in metastatic breast cancer. Each panel (numbered by patient ID) shows whole-exome data from one patient in several aligned tracks, as indicated on the right. SNV: single-nucleotide variations, shown as tick marks for COSMIC recurrent cancer genes (outer tracks) and as density for all mutations (inner tracks). The central colored density gradient shows major allele concordance P value between primary and metastasis (50 SNP moving windows; blue: concordant; red: discordant), indicating the presence of concordant loss of heterozygosity. CNV: copy-number variation (red: deletion, blue: amplification); LOH: loss-of-heterozygosity. The Tumorscape track shows known hotspots for copy-number variation in breast cancer using data from Tumorscape Copy Number Alterations Across Multiple Cancer Types Release 1.6 (Broad Institute). CNV was determined by calculating the normalized read coverage at each SNP position for paired tumor and germline samples, then taking the log2 of the ratio of these numbers and recentering to zero. In Fig. 1, these measures were plotted as a moving average across ten adjacent SNPs. LOH: loss of heterozygousity) as major allele frequency for heterozygous SNPs on the vertical axis, with manually called LOH regions indicated by horizontal lines (vertical axis range 50–100%; red: significant SNP phase concordance with the paired sample, p < 0.01 by the binomial distribution; black: not significant (see also Additional file 3: Figure S2 a-b). Note that LOH could not be called for some samples (metastases of P1, P2, P4 and P10) because of low data quality. SNP phase concordance was determined using all SNPs in the LOH region in A and recorded the major allele of each (i.e. the ‘phase’ of the LOH region). We then tested the null hypothesis that the alleles of the corresponding SNPs in sample B was randomly distributed relative to A, with a 50% chance of concordance at each position. This would be expected if there were in fact no LOH in B, as the major allele would then be determined by the random fluctuations of read coverage. Under this model, the probability of observing k concordant calls among n SNPs is distributed according to the Binomial distribution (k; n, p) with p = 0.5. Thus we calculated the P value as the cumulative density of this distribution from k to n (that is, the probability of observing as many as k concordant calls, or more). A low P value (e.g. P < 0.01) on this test suggest that the LOH region in A was in fact also present on B, whereas a high P (e.g. P > 0.99) value suggests that there was LOH in B, but it was derived from the opposite allele compared with A. Intermediate values are expected whenever there was no LOH in sample B. The central track for each patient in Additional file 4: Figure S1 shows this P value. (ZIP 1670 kb

Additional file 1: of Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs)

Table S1. Patient table cohort 2. The study material includes 20 patients and was collected at Karolinska University Hospital between the years 2000 and 2011. The following inclusion criteria were applied; metastatic adenocarcinoma; detailed clinical data available; axillary and distant metastasis available; required amount of paraffin embedded tissue. The study was approved by the Ethics committee at the Karolinska Institute. (PDF 637 kb