Sanja Rogic

Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations. Genes with roles in histone modification were frequent targets of somatic mutation. For example, 32% of DLBCL and 89% of FL cases had somatic mutations in MLL2, which encodes a histone methyltransferase, and 11.4% and 13.4% of DLBCL and FL cases, respectively, had mutations in MEF2B, a calcium-regulated gene that cooperates with CREBBP and EP300 in acetylating histones. Our analysis suggests a previously unappreciated disruption of chromatin biology in lymphomagenesis.

Concurrent expression of MYC and BCL2 in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone

PURPOSE Diffuse large B-cell lymphoma (DLBCL) is curable in 60% of patients treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). MYC translocations, with or without BCL2 translocations, have been associated with inferior survival in DLBCL. We investigated whether expression of MYC protein, with or without BCL2 protein expression, could risk-stratify patients at diagnosis. PATIENTS AND METHODS We determined the correlation between presence of MYC and BCL2 proteins by immunohistochemistry (IHC) with survival in two independent cohorts of patients with DLBCL treated with R-CHOP. We further determined if MYC protein expression correlated with high MYC mRNA and/or presence of MYC translocation. RESULTS In the training cohort (n = 167), MYC and BCL2 proteins were detected in 29% and 44% of patients, respectively. Concurrent expression (MYC positive/BCL2 positive) was present in 21% of patients. MYC protein correlated with presence of high MYC mRNA and MYC translocation (both P < .001), but the latter was less frequent (both 11%). MYC protein expression was only associated with inferior overall and progression-free survival when BCL2 protein was coexpressed (P < .001). Importantly, the poor prognostic effect of MYC positive/BCL2 positive was validated in an independent cohort of 140 patients with DLBCL and remained significant (P < .05) after adjusting for presence of high-risk features in a multivariable model that included elevated international prognostic index score, activated B-cell molecular subtype, and presence of concurrent MYC and BCL2 translocations. CONCLUSION Assessment of MYC and BCL2 expression by IHC represents a robust, rapid, and inexpensive approach to risk-stratify patients with DLBCL at diagnosis.

Whole transcriptome sequencing reveals recurrent NOTCH1 mutations in mantle cell lymphoma

Mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma, is characterized by the hallmark translocation t(11;14)(q13;q32) and the resulting overexpression of cyclin D1 (CCND1). Our current knowledge of this disease encompasses frequent secondary cytogenetic aberrations and the recurrent mutation of a handful of genes, such as TP53, ATM, and CCND1. However, these findings insufficiently explain the biologic underpinnings of MCL. Here, we performed whole transcriptome sequencing on a discovery cohort of 18 primary tissue MCL samples and 2 cell lines. We found recurrent mutations in NOTCH1, a finding that we confirmed in an extension cohort of 108 clinical samples and 8 cell lines. In total, 12% of clinical samples and 20% of cell lines harbored somatic NOTCH1 coding sequence mutations that clustered in the PEST domain and predominantly consisted of truncating mutations or small frame-shifting indels. NOTCH1 mutations were associated with poor overall survival (P = .003). Furthermore, we showed that inhibition of the NOTCH pathway reduced proliferation and induced apoptosis in 2 MCL cell lines. In summary, we have identified recurrent NOTCH1 mutations that provide the preclinical rationale for therapeutic inhibition of the NOTCH pathway in a subset of patients with MCL.

Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing

Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous cancer composed of at least 2 molecular subtypes that differ in gene expression and distribution of mutations. Recently, application of genome/exome sequencing and RNA-seq to DLBCL has revealed numerous genes that are recurrent targets of somatic point mutation in this disease. Here we provide a whole-genome-sequencing-based perspective of DLBCL mutational complexity by characterizing 40 de novo DLBCL cases and 13 DLBCL cell lines and combining these data with DNA copy number analysis and RNA-seq from an extended cohort of 96 cases. Our analysis identified widespread genomic rearrangements including evidence for chromothripsis as well as the presence of known and novel fusion transcripts. We uncovered new gene targets of recurrent somatic point mutations and genes that are targeted by focal somatic deletions in this disease. We highlight the recurrence of germinal center B-cell-restricted mutations affecting genes that encode the S1P receptor and 2 small GTPases (GNA13 and GNAI2) that together converge on regulation of B-cell homing. We further analyzed our data to approximate the relative temporal order in which some recurrent mutations were acquired and demonstrate that ongoing acquisition of mutations and intratumoral clonal heterogeneity are common features of DLBCL. This study further improves our understanding of the processes and pathways involved in lymphomagenesis, and some of the pathways mutated here may indicate new avenues for therapeutic intervention.

Gene Expression–Based Model Using Formalin-Fixed Paraffin-Embedded Biopsies Predicts Overall Survival in Advanced-Stage Classical Hodgkin Lymphoma

PURPOSE Our aim was to reliably identify patients with advanced-stage classical Hodgkin lymphoma (cHL) at increased risk of death by developing a robust predictor of overall survival (OS) using gene expression measured in routinely available formalin-fixed paraffin-embedded tissue (FFPET). METHODS Expression levels of 259 genes, including those previously reported to be associated with outcome in cHL, were determined by digital expression profiling of pretreatment FFPET biopsies from 290 patients enrolled onto the E2496 Intergroup trial comparing doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) and Stanford V regimens in locally extensive and advanced-stage cHL. A model for OS separating patients into low- and high-risk groups was produced using penalized Cox regression. The model was tested in an independent cohort of 78 patients enriched for treatment failure but otherwise similar to patients in a population-based registry of patients treated with ABVD. Weighted analysis methods generated unbiased estimates of predictor performance in the population-based registry. RESULTS A 23-gene outcome predictor was generated. The model identified a population at increased risk of death in the validation cohort. There was a 29% absolute difference in 5-year OS between the high- and low-risk groups (63% v 92%, respectively; log-rank P < .001; hazard ratio, 6.7; 95% CI, 2.6 to 17.4). The predictor was superior to the International Prognostic Score and CD68 immunohistochemistry in multivariate analyses. CONCLUSION A gene expression-based predictor, developed in and applicable to routinely available FFPET biopsies, identifies patients with advanced-stage cHL at increased risk of death when treated with standard-intensity up-front regimens.

Recurrent somatic mutations of PTPN1 in primary mediastinal B cell lymphoma and Hodgkin lymphoma

Classical Hodgkin lymphoma and primary mediastinal B cell lymphoma (PMBCL) are related lymphomas sharing pathological, molecular and clinical characteristics. Here we discovered by whole-genome and whole-transcriptome sequencing recurrent somatic coding-sequence mutations in the PTPN1 gene. Mutations were found in 6 of 30 (20%) Hodgkin lymphoma cases, in 6 of 9 (67%) Hodgkin lymphoma–derived cell lines, in 17 of 77 (22%) PMBCL cases and in 1 of 3 (33%) PMBCL-derived cell lines, consisting of nonsense, missense and frameshift mutations. We demonstrate that PTPN1 mutations lead to reduced phosphatase activity and increased phosphorylation of JAK-STAT pathway members. Moreover, silencing of PTPN1 by RNA interference in Hodgkin lymphoma cell line KM-H2 resulted in hyperphosphorylation and overexpression of downstream oncogenic targets. Our data establish PTPN1 mutations as new drivers in lymphomagenesis.

The E3 ubiquitin ligase UBR5 is recurrently mutated in mantle cell lymphoma

We have recently reported the application of RNAseq to mantle cell lymphoma (MCL) transcriptomes revealing recurrent mutations in NOTCH1. Here we describe the targeted resequencing of 18 genes mutated in this discovery cohort using a larger cohort of MCL tumors. In addition to frequent mutations in ATM, CCND1, TP53, and NOTCH1, mutations were also observed recurrently in MEF2B, TRAF2, and TET2. Interestingly, the third most frequently mutated gene was UBR5, a gene encoding a 2799aa protein, with multiple functions, including E3 ligase activity based on a conserved cysteine residue at the C-terminus. Nonsynonymous mutations were detected in 18% (18/102) of tumors, with 61% of the mutations resulting in frameshifts in, or around, exon 58, predicted to result in the loss of this conserved cysteine residue. The recurrence and clustering of deleterious mutations implicate UBR5 mutations as a critical pathogenic event in a subgroup of MCL.

Improving gene recognition accuracy by combining predictions from two gene-finding programs

MOTIVATION Despite constant improvements in prediction accuracy, gene-finding programs are still unable to provide automatic gene discovery with desired correctness. The current programs can identify up to 75% of exons correctly and less than 50% of predicted gene structures correspond to actual genes. New approaches to computational gene-finding are clearly needed. RESULTS In this paper we have explored the benefits of combining predictions from already existing gene prediction programs. We have introduced three novel methods for combining predictions from programs Genscan and HMMgene. The methods primarily aim to improve exon level accuracy of gene-finding by identifying more probable exon boundaries and by eliminating false positive exon predictions. This approach results in improved accuracy at both the nucleotide and exon level, especially the latter, where the average improvement on the newly assembled dataset is 7.9% compared to the best result obtained by Genscan and HMMgene. When tested on a long genomic multi-gene sequence, our method that maintains reading frame consistency improved nucleotide level specificity by 21.0% and exon level specificity by 32.5% compared to the best result obtained by either of the two programs individually. AVAILABILITY The scripts implementing our methods are available from http://www.cs.ubc.ca/labs/beta/genefinding/

GeneComber: combining outputs of gene prediction programs for improved results

UNLABELLED We recently demonstrated that combining the output from Genscan and HMMgene can provide increased accuracy of gene predictions. We have created a robust software system that runs algorithms previously described on DNA sequences and provides a public web interface to the system for use by the biological community worldwide. The GeneComber system performs ab initio gene prediction by first taking a user inputted DNA sequence and running Genscan and HMMgene. The outputs of Genscan and HMMgene are then integrated using the EUI, GI and EUI_frame algorithms. All results are then stored into a relational database management system (RDBMS) and can then be retrieved through a web interface. The web interface provides a unified view of the GeneComber predictions by graphically overlaying outputs from Genscan, HMMgene, EUI, GI and EUI_frame. Outputs can also be retrieved in general feature format (GFF) or FASTA format. The software is written in the Perl programming language and is both dependent on and interoperable with the Bioperl toolkit. It includes high-level application programming interfaces (APIs) to run Genscan, HMMgene and a database API to insert prediction results into an RDBMS. The APIs are assembled into the genecomber script which is executed by the web interface or can be run directly from the Unix command line. The web interface is written in PHP and is structured so as to be easily modified for viewing data from any database that stores gene structures. AVAILABILITY The GeneComber public web interface and supplementary information is located at http://bioinformatics.ubc.ca/genecomber The source code is released under the GNU General Public License and is available at ftp://ftp.bioinformatics.ubc.ca/pub/genecomber/software.

Meta-Analysis of Gene Expression in Autism Spectrum Disorder.

Autism spectrum disorders (ASD) are clinically heterogeneous and biologically complex. In general it remains unclear, what biological factors lead to changes in the brains of autistic individuals. A considerable number of transcriptome analyses have been performed in attempts to address this question, but their findings lack a clear consensus. As a result, each of these individual studies has not led to any significant advance in understanding the autistic phenotype as a whole. Here, we report a meta‐analysis of more than 1000 microarrays across twelve independent studies on expression changes in ASD compared to unaffected individuals, in both blood and brain tissues. We identified a number of known and novel genes that are consistently differentially expressed across three studies of the brain (71 samples in total). A subset of the highly ranked genes is suggestive of effects on mitochondrial function. In blood, consistent changes were more difficult to identify, despite individual studies tending to exhibit larger effects than the brain studies. Our results are the strongest evidence to date of a common transcriptome signature in the brains of individuals with ASD. Autism Res 2015, 8: 593–608.