Genome Analysis of Osteosarcoma Progression Samples Identifies FGFR1 Overexpression as a Potential Treatment Target and CHM as a Candidate Tumor Suppressor Gene.

Osteosarcoma (OS) is the most common primary malignant tumor of bone, showing complex chromosomal rearrangements but with few known consistent changes. Deeper biological understanding is crucial to find new therapies to improve patient survival. We have sequenced the whole exome of two primary tumors (before and after chemotherapy), one metastatic tumor and a matched normal sample from two OS patients, to identify mutations involved in cancer biology. The metastatic samples were also RNA sequenced. By RNA sequencing we identified dysregulated expression levels of drug resistance- and apoptosis-related genes. Two fusion transcripts were identified in one patient (OS111); the first resulted in p53 inactivation by fusing the first exon of TP53 to the fifth exon of FAM45A. The second fusion joined the two first exons of FGFR1 to the second exon of ZNF343. Furthermore, FGFR1 was amplified and highly expressed, representing a potential treatment target in this patient. Whole exome sequencing revealed large intertumor heterogeneity, with surprisingly few shared mutations. Careful evaluation and validation of the data sets revealed a number of artefacts, but one recurrent mutation was validated, a nonsense mutation in CHM (patient OS106), which also was the mutation with the highest expression frequency (53%). The second patient (OS111) had wild-type CHM, but a downregulated expression level. In a panel of 71 clinical samples, we confirmed significant low expression of CHM compared to the controls (p = 0.003). Furthermore, by analyzing public datasets, we identified a significant association between low expression and poor survival in two other cancer types. Together, these results suggest CHM as a candidate tumor suppressor gene that warrants further investigation.

Unscrambling the genomic chaos of osteosarcoma reveals extensive transcript fusion, recurrent rearrangements and frequent novel TP53 aberrations.

In contrast to many other sarcoma subtypes, the chaotic karyotypes of osteosarcoma have precluded the identification of pathognomonic translocations. We here report hundreds of genomic rearrangements in osteosarcoma cell lines, showing clear characteristics of microhomology-mediated break-induced replication (MMBIR) and end-joining repair (MMEJ) mechanisms. However, at RNA level, the majority of the fused transcripts did not correspond to genomic rearrangements, suggesting the involvement of trans-splicing, which was further supported by typical trans-splicing characteristics. By combining genomic and transcriptomic analysis, certain recurrent rearrangements were identified and further validated in patient biopsies, including a PMP22-ELOVL5 gene fusion, genomic structural variations affecting RB1, MTAP/CDKN2A and MDM2, and, most frequently, rearrangements involving TP53. Most cell lines (7/11) and a large fraction of tumor samples (10/25) showed TP53 rearrangements, in addition to somatic point mutations (6 patient samples, 1 cell line) and MDM2 amplifications (2 patient samples, 2 cell lines). The resulting inactivation of p53 was demonstrated by a deficiency of the radiation-induced DNA damage response. Thus, TP53 rearrangements are the major mechanism of p53 inactivation in osteosarcoma. Together with active MMBIR and MMEJ, this inactivation probably contributes to the exceptional chromosomal instability in these tumors. Although rampant rearrangements appear to be a phenotype of osteosarcomas, we demonstrate that among the huge number of probable passenger rearrangements, specific recurrent, possibly oncogenic, events are present. For the first time the genomic chaos of osteosarcoma is characterized so thoroughly and delivered new insights in mechanisms involved in osteosarcoma development and may contribute to new diagnostic and therapeutic strategies.

The regulatory landscape of osteogenic differentiation.

Differentiation of osteoblasts from mesenchymal stem cells (MSCs) is an integral part of bone development and homeostasis, and may when improperly regulated cause disease such as bone cancer or osteoporosis. Using unbiased high-throughput methods we here characterize the landscape of global changes in gene expression, histone modifications, and DNA methylation upon differentiation of human MSCs to the osteogenic lineage. Furthermore, we provide a first genome-wide characterization of DNA binding sites of the bone master regulatory transcription factor Runt-related transcription factor 2 (RUNX2) in human osteoblasts, revealing target genes associated with regulation of proliferation, migration, apoptosis, and with a significant overlap with p53 regulated genes. These findings expand on emerging evidence of a role for RUNX2 in cancer, including bone metastases, and the p53 regulatory network. We further demonstrate that RUNX2 binds to distant regulatory elements, promoters, and with high frequency to gene 3' ends. Finally, we identify TEAD2 and GTF2I as novel regulators of osteogenesis.

Performance comparison of four exome capture systems for deep sequencing.

BACKGROUND: Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen's SeqCap EZ v3.0, Agilent's SureSelect v4.0, Illumina's TruSeq Exome, and Illumina's Nextera Exome, all applied to the same human tumor DNA sample. RESULTS: Each capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content. CONCLUSIONS: We show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application.

Common fusion transcripts identified in colorectal cancer cell lines by high-throughput RNA sequencing.

Colorectal cancer (CRC) is the third most common cancer disease in the Western world, and about 40% of the patients die from this disease. The cancer cells are commonly genetically unstable, but only a few low-frequency recurrent fusion genes have so far been reported for this disease. In this study, we present a thorough search for novel fusion transcripts in CRC using high-throughput RNA sequencing. From altogether 220 million paired-end sequence reads from seven CRC cell lines, we identified 3391 candidate fused transcripts. By stringent requirements, we nominated 11 candidate fusion transcripts for further experimental validation, of which 10 were positive by reverse transcription-polymerase chain reaction and Sanger sequencing. Six were intrachromosomal fusion transcripts, and interestingly, three of these, AKAP13-PDE8A, COMMD10-AP3S1, and CTB-35F21.1-PSD2, were present in, respectively, 18, 18, and 20 of 21 analyzed cell lines and in, respectively, 18, 61, and 48 (17%-58%) of 106 primary cancer tissues. These three fusion transcripts were also detected in 2 to 4 of 14 normal colonic mucosa samples (14%-28%). Whole-genome sequencing identified a specific genomic breakpoint in COMMD10-AP3S1 and further indicates that both the COMMD10-AP3S1 and AKAP13-PDE8A fusion transcripts are due to genomic duplications in specific cell lines. In conclusion, we have identified AKAP13-PDE8A, COMMD10-AP3S1, and CTB-35F21.1-PSD2 as novel intrachromosomal fusion transcripts and the most highly recurring chimeric transcripts described for CRC to date. The functional and clinical relevance of these chimeric RNA molecules remains to be elucidated.

Correlation of TP53 and MDM2 genotypes with response to therapy in sarcoma.

BACKGROUND: Relatively few sarcomas harbor TP53 (tumor protein p53) mutations, but in many cases, amplification of MDM2 (murine double minute 2) effectively inactivate p53. The p53 pathway activity can also be affected by normal genetic variation. METHODS: The mutation status of TP53 and expression of MDM2, TP53, and their genetic variants SNP309 and R72P (Arg72Pro) were investigated in 125 sarcoma patient samples and 18 sarcoma cell lines. Association of the different genotypes and gene aberrations with chemotherapy response and survival, as well as response to MDM2 antagonists in vitro was evaluated. RESULTS: Twenty-two percent of the tumors had mutant TP53 and 20% MDM2 gene amplification. Patients with wild-type TP53 (TP53(Wt) ) tumors had improved survival (P < .001) and TP53(Wt) was an independent prognostic factor (hazard ratio = 0.41; 95% confidence interval = 0.23-0.74; P = .03). Interestingly, there was a trend toward longer time to progression after chemotherapy for tumors with the apoptosis-prone p53 variant R72 (P = .07), which was strongest with doxorubicin/ifosfamide-based regimens (P = .01). Liposarcomas had low R72 frequency (33% versus 56%), but increased levels of MDM2 and MDM4 (51% and 11%, P < .001). MDM2 overexpression on a TP53(Wt) background predicted better response to MDM2 antagonist Nutlin-3a, irrespective of R72P or SNP309 status. CONCLUSIONS: Improved survival after chemotherapy was found in patients with TP53(Wt) tumors harboring the R72 variant. MDM2 overexpression in TP53(Wt) tumors predicted good response to MDM2 antagonists, irrespective of R72P or SNP309 status. Thus, detailed TP53 and MDM2 genotype analyses prior to systemic therapy are recommended.