Citations

Abstract Background: Fusion genes, transcripts, and proteins are key drivers of hematopoietic oncogenesis and can serve as effective therapeutic targets. Among peripheral T-cell lymphomas (PTCLs), little is known about fusion genes except for those involving ALK. Discovery of fusion genes may provide therapeutic targets for PTCLs, which have poor outcomes with conventional therapy. We have developed methods for detecting candidate fusions using (1) mate-pair DNA sequencing (MPseq), an approach that spans the entire genome at a fraction of the cost of traditional whole-genome sequencing, and (2) RNA sequencing (RNAseq). Each technique has strengths, limitations, and false discovery rates. Here, we integrated results of both methods to discover and orthogonally validate expressed fusion genes in PTCLs. Methods: DNA and RNA were extracted from 49 frozen, OCT-embedded clinical PTCL specimens, including 25 anaplastic large cell lymphomas; 16 PTCLs, not otherwise specified; and 8 other PTCLs. MPseq and RNAseq were performed using Illumina library protocols and a HiSeq 2000. Detection of fusion genes and transcripts followed our published methods (Blood 2012;120:2280 and Nucleic Acids Res 2011;39:e100, respectively). Functional annotation of genes involved in fusions was performed using DAVID. Results: Of 2818 candidate chromosomal rearrangements identified by MPseq and 90 candidate fusion transcripts identified by RNAseq, 45 events were present in both datasets (mean/case, 0.9; range, 0-7). Fusions were inter-chromosomal in 16 and intra-chromosomal in 29. Annotation clusters with the highest enrichment scores related to SH2 domain-containing proteins and tyrosine kinases (including FER and MAP2K3). Seven genes were recurrently involved in fusions, including known fusion partners such as ALK and previously unreported fusion partners such as PPP1R8, a phosphatase inhibitor important for the activity of Polycomb group proteins such as EZH2. Detection of candidate events only by MPseq could be explained in part by breakpoints mapping to non-genic regions (79% of events). Detection only by RNAseq could be explained in part by unannotated transcripts spanning neighboring named genes (median intra-chromosomal distance, 0.09 MB vs. 12.7 MB for intra-chromosomal candidates identified by MPseq; p<0.0001, Wilcoxon test). Conclusions: Integrated DNA/RNA sequencing is an effective, clinically feasible tool for simultaneous discovery and orthogonal validation of expressed fusion genes. This approach yielded fusions in PTCLs involving genes with key functions in lymphocytes, including novel and recurrent fusions, some of which might be targetable with compounds currently in clinical trial. Candidate intra-chromosomal fusion transcripts not identified by MPseq may represent unrecognized isoforms or the results of novel read-through mechanisms, and merit further study. Citation Format: Andrew L. Feldman, George Vasmatzis, Yan W. Asmann, Sarah H. Johnson, Bruce W. Eckloff, Sumit Middha, Jaime I. Davila, Paul J. Kurtin, Brian K. Link, Stephen M. Ansell, James R. Cerhan. Integrated DNA/RNA sequencing for discovery and orthogonal validation of expressed fusion genes in peripheral T-cell lymphomas. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5585. doi:10.1158/1538-7445.AM2014-5585

Abstract Background: Extranodal follicular dendritic cell sarcoma (FDCS) is an exceedingly rare tumor type that is limited to few cases in the literature. Given the rarity of this tumor, there is a lack of genetic understanding of this disease resulting in a non-individualized plan of care for patients with this disease. Herein, we are the first to describe extensively molecularly the DNA and RNA of this tumor. Methods: Under an IRB approved protocol, the patient's tumor and whole blood was freshly frozen for molecular analysis. We performed Next Generation Sequencing (NGS) genomic profiling including exome capture, mate pair and mRNA sequencing on this tumor. Exome and mRNA data were processed through Mayo's Bioinformatics Core standard pipelines, GENOME GPS 1.2.1 and MAPRSeq v1.2.1. Mutations and indels were prioritized depending on whether or not they belonged to known cancer associated genes. Copy number variations (CNVs) in Exome and Mate Pair data was found through PatternCNV v 1.0.1 and fusion transcripts were found using SNOWSHOES-FTD and Tophat-Fusion 2.0.6. Results: At the genomic level large scale genomic rearrangements were detected, including chr19 and chr20 trisomy, chr15q and chr17q segmental duplications result in two intra-chromosomal fusion genes, and translocations leading to four inter-chromosomal fusion genes between chr15 and chr17. Of particular interest is a stop codon gain in the CLTC1 (chr22) gene, which is involved in the mitotic spindle organization which has been associated with meningiomas and breast tumorigenesis. The new stop codon is before the site required for the recruitment of the proteins to the spindle. The large scale genomic rearrangement described above is consistent with this defective spindle assembly hypothesis. Another intriguing mutation detected in the VEGFR1 (chr13) gene leads to a 45% mis-spliced transcript. VEGFR1 is thought to modulate VEGFR2 which plays an essential role in angiogenesis, by acting as a decoy receptor. Therefore the loss of function of VEGFR1 might lead to hyper-activity of VEGFR2 pathway and a potential therapeutic strategy is to directly inhibit the VEGFR2 pathway. Furthermore missense mutations in the ATM (chr11) and TP53 (chr17) genes were found. PARP inhibitors have been used with success for cancer with defects in the ATM gene. Finally a novel fusion transcript of HDGRFP3 (chr15) and SHC4 (chr15) was identified. Such fusion results in an overexpressed SHC4 gene which has been associated with metastatic melanomas. Conclusions: In summary, genomic profiling of a rare thyroid FDCS identified drug targetable genes as well as changes related to tumor etiology. Future work is necessary to determine the functional significance of these molecular findings and whether they will predict benefit to targeted therapies. Citation Format: Jaime I. Davila, Jason Starr, Steven Attia, Chen Wang, Xue Wang, Brian Necela, Casler John, David Menke, Vivek Sarangi, Gavin Oliver, Richard Joseph, John Copland, Alexander Parker, E. Aubrey Thompson, Robert Smallridge, Yan W. Asmann. Extensive genomic profiling of a rare extranodal-follicular dendritic cell sarcoma: Implications for future individualized therapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1894. doi:10.1158/1538-7445.AM2014-1894

Abstract Objectives and Rationale: Structural variants (SV) including large copy number aberrations (CNV), translocations, inversions, and large insertions and deletions (INDEL) play a critical role in tumorigenesis and progression. In fact, we now know that tumors can be categorized according to the size of mutations harbored. In several cancers, including ovarian and breast cancer, the large structural mutations, rather than single site mutations, play a dominate role in tumor etiology. Therefore, it's critical to implement reliable algorithm for the detection of structural variants in DNA sequencing data. Mate-pair sequencing is a protocol specifically implemented for detection of the whole-genome level structural variants. It requires less sequencing depth therefor is cost effective, and enables the detection of CNVs, translocations, and inversions simultaneously. However, so far there has been no reliable bioinformatics pipeline for the analyses of the mate-pair sequencing data. Methods: Our novel algorithm, the SnowShoes-SV, is an exhaustive search algorithm designed specifically for mate-pair DNA sequencing data analyses. It calls the SVs based on disconcordant read pairs. The false SVs are filtered according to the following criteria: (i) the number of the supporting read pairs; (ii) the lack of reads from control data that implicate SV at the same region; (iii) the mappability and uniqueness of the region based on data from the ENCODE project; (iv) consistencies of the mapping orientations of the supporting read pairs; (v) the similar sizes between sequencing library and the two end read clusters. Results: Using a set of samples previously genotyped by aCGH, the SnowShoes-SV successfully detected all known CNVs and other SVs. It also identified copy number neutral translocations and inversions previously not identified by aCGH. In addition, the algorithm nominated novel SVs which are to be validated by PCR. Conclusions: SnowShoes-SV is a highly sensitive and specific algorithm for SV detection from the mate-pair DNA sequencing data. Citation Format: Yan W Asmann, Chen Wang, Brian M Necela, Xianfeng Chen, Jean-Pierre A Kocher, Matthew J Maurer, Thomas M Habermann, Susan L Slager, Andrew L Feldman, Anne J Novak, James R Cerhan, Edith A Perez, E Aubrey Thompson. An exhaustive algorithm for detecting copy number aberrations and large structural variants in whole-genome mate-pair sequencing data [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-07-03.

Hidradenocarcinoma is a rare malignancy of the sweat glands with only a few cases reported in literature. The management of these tumors is based on the extent of disease with local disease managed with surgical resection. These can tumors carry a high potential of lymphatic and vascular spread and local and distant metastases are not uncommon. Given the rarity of the tumor and lack of genetic and clinical data about these tumors, there is no consensus on the proper management of metastatic disease. Here in we report the first case of metastatic hidradenocarcinoma with detailed molecular profiling including whole exome sequencing. We identified mutations in multiple genes including two that are potentially targetable: PTCH1 and TCF7L1. Further work is necessary to not only confirm the presence of these mutations but also to confirm the clinical significance.

Polarity protein complexes are crucial for epithelial apical-basal polarity and directed cell migration. Since alterations of these processes are common in cancer, polarity proteins have been proposed to function as tumor suppressors or oncogenic promoters. Here, we review the current understanding of polarity protein functions in epithelial homeostasis, as well as tumor formation and progression. As most previous studies focused on the function of single polarity proteins in simplified model systems, we used a genomics approach to systematically examine and identify the expression profiles of polarity genes in human cancer. The expression profiles of polarity genes were distinct in different human tissues and classified cancer types. Additionally, polarity expression profiles correlated with disease progression and aggressiveness, as well as with identified cancer types, where specific polarity genes were commonly altered. In the case of Scribble, gene expression analysis indicated its common amplification and upregulation in human cancer, suggesting a tumor promoting function.

Purpose To develop a genomic signature that predicts benefit from trastuzumab in human epidermal growth factor receptor 2–positive breast cancer. Patients and Methods DASL technology was used to quantify mRNA in samples from 1,282 patients enrolled onto the Combination Chemotherapy With or Without Trastuzumab in Treating Women With Breast Cancer (North Central Cancer Treatment Group N9831 [NCCTG-N9831]) adjuvant trastuzumab trial. Cox proportional hazard ratios (HRs), adjusted for significant clinicopathologic risk factors, were used to determine the association of each gene with relapse-free survival (RFS) for 433 patients who received chemotherapy alone (arm A) and 849 patients who received chemotherapy plus trastuzumab (arms B and C). Network and pathway analyses were used to identify key biologic processes linked to RFS. The signature was built by using a voting scheme. Results Network and functional ontology analyses suggested that increased RFS was linked to a subset of immune function genes. A voting scheme model was used to define immune gene enrichment based on the expression of any nine or more of 14 immune function genes at or above the 0.40 quantile for the population. This model was used to identify immune gene–enriched tumors in arm A and arms B and C. Immune gene enrichment was linked to increased RFS in arms B and C (HR, 0.35; 95% CI, 0.22 to 0.55; P < .001), whereas arm B and C patients who did not exhibit immune gene enrichment did not benefit from trastuzumab (HR, 0.89; 95% CI, 0.62 to 1.28; P = .53). Enriched immune function gene expression as defined by our predictive signature was not associated with increased RFS in arm A (HR, 0.90; 95% CI, 0.60 to 1.37; P = .64). Conclusion Increased expression of a subset of immune function genes may provide a means of predicting benefit from adjuvant trastuzumab.

Abstract Motivation: RNA-seq has become the method of choice to quantify genes and exons, discover novel transcripts and detect fusion genes. However, reliable variant identification from RNA-seq data remains challenging because of the complexities of the transcriptome, the challenges of accurately mapping exon boundary spanning reads and the bias introduced during the sequencing library preparation. Method: We developed RVboost, a novel method specific for RNA variant prioritization. RVboost uses several attributes unique in the process of RNA library preparation, sequencing and RNA-seq data analyses. It uses a boosting method to train a model of ‘good quality’ variants using common variants from HapMap, and prioritizes and calls the RNA variants based on the trained model. We packaged RVboost in a comprehensive workflow, which integrates tools of variant calling, annotation and filtering. Results: RVboost consistently outperforms the variant quality score recalibration from the Genome Analysis Tool Kit and the RNA-seq variant-calling pipeline SNPiR in 12 RNA-seq samples using ground-truth variants from paired exome sequencing data. Several RNA-seq–specific attributes were identified as critical to differentiate true and false variants, including the distance of the variant positions to exon boundaries, and the percent of the reads supporting the variant in the first six base pairs. The latter identifies false variants introduced by the random hexamer priming during the library construction. Availability and implementation: The RVboost package is implemented to readily run in Mac or Linux environments. The software and user manual are available at http://bioinformaticstools.mayo.edu/research/rvboost/. Supplementary information: Supplementary data are available at Bioinformatics online.