Bone structure in two adult subjects with impaired minor spliceosome function resulting from RNU4ATAC mutations causing microcephalic osteodysplastic primordial dwarfism type 1 (MOPD1)

AbstractMicrocephalic osteodysplastic primordial dwarfism type 1 (MOPD1), or Taybi-Linder syndrome is characterized by distinctive skeletal dysplasia, severe intrauterine and postnatal growth retardation, microcephaly, dysmorphic features, and neurological malformations. It is an autosomal recessive disorder caused by homozygous or compound heterozygous mutations in the RNU4ATAC gene resulting in impaired function of the minor spliceosome. Here, we present the first report on bone morphology, bone density and bone microstructure in two adult MOPD1 patients and applied radiographs, dual energy X-ray absorptiometry, high-resolution peripheral quantitative computed tomography and biochemical evaluation.The MOPD1 patients presented with short stature, low BMI but normal macroscopic bone configuration. Bone mineral density was low. Compared to Danish reference data, total bone area, cortical bone area, cortical thickness, total bone density, cortical bone density, trabecular bone density and trabecular bone volume per tissue volume (BV/TV) were all low. These findings may correlate to the short stature and low body weight of the MOPD1 patients. Our findings suggest that minor spliceosome malfunction may be associated with altered bone modelling

Clonal expansion and linear genome evolution through breast cancer progression from pre-invasive stages to asynchronous metastasis

Evolution of the breast cancer genome from pre-invasive stages to asynchronous metastasis is complex and mostly unexplored, but highly demanded as it may provide novel markers for and mechanistic insights in cancer progression. The increasing use of personalized therapy of breast cancer necessitates knowledge of the degree of genomic concordance between different steps of malignant progression as primary tumors often are used as surrogates of systemic disease. Based on exome sequencing we performed copy number profiling and point mutation detection on successive steps of breast cancer progression from one breast cancer patient, including two different regions of Ductal Carcinoma In Situ (DCIS), primary tumor and an asynchronous metastasis. We identify a remarkable landscape of somatic mutations, retained throughout breast cancer progression and with new mutational events emerging at each step. Our data, contrary to the proposed model of early dissemination of metastatic cells and parallel progression of primary tumors and metastases, provide evidence of linear progression of breast cancer with relatively late dissemination from the primary tumor. The genomic discordance between the different stages of tumor evolution in this patient emphasizes the importance of molecular profiling of metastatic tissue directing molecularly targeted therapy at recurrence

Genomic Analyses of Breast Cancer Progression Reveal Distinct Routes of Metastasis Emergence

A main controversy in cancer research is whether metastatic abilities are present in the most advanced clone of the primary tumor or result from independently acquired aberrations in early disseminated cancer cells as suggested by the linear and the parallel progression models, respectively. The genetic concordance between different steps of malignant progression is mostly unexplored as very few studies have included cancer samples separated by both space and time. We applied whole exome sequencing and targeted deep sequencing to 26 successive samples from six patients with metastatic estrogen receptor (ER)-positive breast cancer. Our data provide support for both linear and parallel progression towards metastasis. We report for the first time evidence of metastasis-to-metastasis seeding in breast cancer. Our results point to three distinct routes of metastasis emergence. This may have profound clinical implications and provides substantial novel molecular insights into the timing and mutational evolution of breast cancer metastasis

Evaluation of Nine Somatic Variant Callers for Detection of Somatic Mutations in Exome and Targeted Deep Sequencing Data.

Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths

Total number of somatic mutations called by nine somatic variant caller tools in the exome sequencing data of five breast cancer samples.

<p>SNV and indel calls in left and right panels, respectively.</p

Calling patterns of the somatic variant callers.

<p>Hierarchical cluster analysis of mutations called by the somatic variant callers in exome and deep sequencing data in left and right panel, respectively. Each red line represents a called somatic mutation.</p

Inter-caller agreement.

<p>Pairwise comparisons of the nine studied variant callers in exome sequencing of five breast cancer samples in exome sequencing and deep sequencing data in upper and lower panels, respectively. The matrix depicts the agreement among the studied variant callers. In each horizontal line, the number reflects the fraction of calls found by the caller that are also reported by the other callers. For instance, looking at EBCall in the first line, Mutect reports 51% of the calls reported by EBCall. Deep sequencing data includes only data covered by 200 x at minimum in both tumor and normal sample. The color reflects the degree of agreement, with the highest color intensity depicting high agreement between the two callers.</p