Lisle E. Mose

ABRA: improved coding indel detection via assembly-based realignment

Motivation: Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read mappers have difficulty accurately mapping short reads containing complex variation (i.e. more than a single base change), thus making identification of such variants difficult or impossible. Insertions and deletions (indels) in particular have been an area of great difficulty. Indels are frequent and can have substantial impact on function, which makes their detection all the more imperative. Results: We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads. This results in enhanced performance for indel detection as well as improved accuracy in variant allele frequency estimation. Availability and implementation: ABRA is implemented in a combination of Java and C/C++ and is freely available for download at https://github.com/mozack/abra. Contact: lmose@unc.edu; parkerjs@email.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Integrated RNA and DNA sequencing improves mutation detection in low purity tumors

Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors.

Claudin-low bladder tumors are immune infiltrated and actively immune suppressed

We report the discovery of a claudin-low molecular subtype of high-grade bladder cancer that shares characteristics with the homonymous subtype of breast cancer. Claudin-low bladder tumors were enriched for multiple genetic features including increased rates of RB1, EP300, and NCOR1 mutations; increased frequency of EGFR amplification; decreased rates of FGFR3, ELF3, and KDM6A mutations; and decreased frequency of PPARG amplification. While claudin-low tumors showed the highest expression of immune gene signatures, they also demonstrated gene expression patterns consistent with those observed in active immunosuppression. This did not appear to be due to differences in predicted neoantigen burden, but rather was associated with broad upregulation of cytokine and chemokine levels from low PPARG activity, allowing unopposed NFKB activity. Taken together, these results define a molecular subtype of bladder cancer with distinct molecular features and an immunologic profile that would, in theory, be primed for immunotherapeutic response.

Germline Analysis from Tumor-Germline Sequencing Dyads to identify clinically actionable secondary findings

Purpose: To evaluate germline variants in hereditary cancer susceptibility genes among unselected cancer patients undergoing tumor–germline sequencing. Experimental Design: Germline sequence data from 439 individuals undergoing tumor–germline dyad sequencing through the LCCC1108/UNCseq™ (NCT01457196) study were analyzed for genetic variants in 36 hereditary cancer susceptibility genes. These variants were analyzed as an exploratory research study to determine whether pathogenic variants exist within the germline of patients undergoing tumor–germline sequencing. Patients were unselected with respect to indicators of hereditary cancer predisposition. Results: Variants indicative of hereditary cancer predisposition were identified in 19 (4.3%) patients. For about half (10/19), these findings represent new diagnostic information with potentially important implications for the patient and their family. The others were previously identified through clinical genetic evaluation secondary to suspicion of a hereditary cancer predisposition. Genes with pathogenic variants included ATM, BRCA1, BRCA2, CDKN2A, and CHEK2. In contrast, a substantial proportion of patients (178, 40.5%) had Variants of Uncertain Significance (VUS), 24 of which had VUS in genes pertinent to the presenting cancer. Another 143 had VUS in other hereditary cancer genes, and 11 had VUS in both pertinent and nonpertinent genes. Conclusions: Germline analysis in tumor–germline sequencing dyads will occasionally reveal significant germline findings that were clinically occult, which could be beneficial for patients and their families. However, given the low yield for unexpected germline variation and the large proportion of patients with VUS results, analysis and return of germline results should adhere to guidelines for secondary findings rather than diagnostic hereditary cancer testing. Clin Cancer Res; 22(16); 4087–94. ©2016 AACR. See related commentary by Mandelker, p. 3987

Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V'DJer.

Motivation: B-cell receptor (BCR) repertoire profiling is an important tool for understanding the biology of diverse immunologic processes. Current methods for analyzing adaptive immune receptor repertoires depend upon PCR amplification of VDJ rearrangements followed by long read amplicon sequencing spanning the VDJ junctions. While this approach has proven to be effective, it is frequently not feasible due to cost or limited sample material. Additionally, there are many existing datasets where short-read RNA sequencing data are available but PCR amplified BCR data are not. Results: We present here V’DJer, an assembly-based method that reconstructs adaptive immune receptor repertoires from short-read RNA sequencing data. This method captures expressed BCR loci from a standard RNA-seq assay. We applied this method to 473 Melanoma samples from The Cancer Genome Atlas and demonstrate V’DJer’s ability to accurately reconstruct BCR repertoires from short read mRNA-seq data. Availability and Implementation: V’DJer is implemented in C/C ++, freely available for academic use and can be downloaded from Github: https://github.com/mozack/vdjer Contact: benjamin_vincent@med.unc.edu or parkerjs@email.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling

Changes in the quantity of genetic material, known as somatic copy number alterations (CNAs), can drive tumorigenesis. Many methods exist for assessing CNAs using microarrays, but considerable technical issues limit current CNA calling based upon DNA sequencing. We present SynthEx, a novel tool for detecting CNAs from whole exome and genome sequencing. SynthEx utilizes a “synthetic-normal” strategy to overcome technical and financial issues. In terms of accuracy and precision, SynthEx is highly comparable to array-based methods and outperforms sequencing-based CNA detection tools. SynthEx robustly identifies CNAs using sequencing data without the additional costs associated with matched normal specimens.

Abstract 5120: The novel claudin-low molecular subtype of high-grade urothelial bladder cancer is highly immunogenic yet immunosuppressed

Rationale: High-grade urothelial carcinoma of the bladder is a heterogeneous disease, with molecular subtypes characterized by distinct tumor biologies and prognoses. Our group and others have described the basal and luminal subtypes, and we now report on the discovery of the claudin-low subtype, all of which resemble analogous subtypes in breast cancer. Methods: We analyzed mRNA sequencing and whole exome sequencing data for The Cancer Genome Atlas (TCGA) bladder tumors and tumors collected at UNC. We performed unsupervised hierarchical clustering on relative gene expression values with significance testing using SigClust to identify the claudin-low subtype. Basal, luminal, and claudin-low bladder tumors were compared for enrichment of genetic features (single nucleotide and copy number variation), gene set expression, immune gene signature expression, T cell receptor (TCR) and B cell receptor (BCR) gene segment expression, and number of predicted MHC Class I and Class II neoantigens. We further report on the first use of our VDJician software to reconstruct full-length rearranged BCR sequences from short-read RNA sequencing data in bladder cancer. Results: Claudin-low bladder tumors were defined by low expression of tight junction claudin-proteins, high expression of epithelial-to-mesenchymal transition genes and immune gene signatures, and were associated with reduced overall survival compared to luminal tumors. A minimal gene set classifier to identify claudin-low tumors showed some but not complete overlap with an optimal classifier derived in breast cancer. Claudin-low bladder tumors were enriched for multiple genetic features: increased rates of RB1, EP300, and NCOR1 mutations, increased frequency of EGFR amplification, decreased rates of FGFR3, ELF3, and KDM6A mutations, and decreased frequency of PPARG amplification. Claudin-low tumors showed the highest expression of immune gene signatures (including an immunosuppression signature), however in contrast to basal tumors, increased immune gene signature expression was not associated with prolonged survival. Claudin-low tumors also showed the highest overall expression of rearranged BCR sequences but lowest BCR repertoire diversity. Predicted neoantigen burden did not vary significantly by subtype, however broad cytokine and chemokine expression levels were elevated in claudin-low tumors, potentially related to low PPARG activity driving increased NFKB activity. Conclusions: Claudin-low bladder cancer is a novel molecular subtype with distinct molecular and immunologic features and prognostic significance. Given the presence of dense immune infiltrates, BCR repertoire characteristics consistent with an antigen-driven response, and high expression of immunosuppression genes, claudin-low bladder tumors may be primed to respond to immune checkpoint inhibitor therapy. Citation Format: Benjamin G. Vincent, William Kim, Jordan Kardos, Shengjie Chai, Joel Parker, Lisle Mose, Sara Selitsky, Michael Iglesia, Matthew Milowsky. The novel claudin-low molecular subtype of high-grade urothelial bladder cancer is highly immunogenic yet immunosuppressed. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5120.

Abstract SY12-03: Multi-tumor analysis of TCGA data identifies expression commonalities across tumor types.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC High dimensional assays, such as DNA microarrays for gene expression, have helped delineate the complexity and diversity of most major cancer types. The Cancer Genome Atlas (TCGA), with its goal to comprehensively genomically characterize over twenty different types of tumors, gives us a wealth of data to start looking at similarities across tumor types. Much of the current data is now generated using Massively Parallel Sequencing (MPS) approaches, which yields tens of millions of “reads” per sample. Illumina Hiseq-based mRNA-sequencing data for twelve tumor types representing over 3,500 samples were analyzed for patterns unique to each tumors, and patterns present across multiple tumor types. Tumor types tested included rectal adenocarcinoma, colon adenocarcinoma, lung squamous cell carcinoma and adenocarcinoma, uterine corpus endometrial carcinoma, ovarian serous cystadenocarcinoma, kidney clear cell, breast ductal and lobular carcinoma, glioblastoma multiforme, bladder carcinomas, acute myeloid leukemia, and head and neck squamous cell carcinoma. Tissue-specific expression was the dominant signature; however, there were similarities across sets of tumors including a common “squamous” pattern that was populated by tumors from three distinct anatomic sites. Pathway or Module-based analysis also provided methods to comparisons across tissues. Cross tissue analysis of mRNA-seq data provides interesting observations of common tumor biology with potential insights into treatment. Citation Format: Katherine A. Hoadley, Cheng Fan, Matthew D. Wilkerson, Lisle E. Mose, Stuart R. Jefferys, J. Todd Auman, Joel S. Parker, D. Neil Hayes, Charles M. Perou. Multi-tumor analysis of TCGA data identifies expression commonalities across tumor types. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr SY12-03. doi:10.1158/1538-7445.AM2013-SY12-03