Follicular lymphoma B cells exhibit heterogeneous transcriptional states with associated somatic alterations and tumor microenvironments.

Follicular lymphoma (FL) is an indolent non-Hodgkin lymphoma of germinal center origin, which presents with significant biologic and clinical heterogeneity. Using RNA-seq on B cells sorted from 87 FL biopsies, combined with machine-learning approaches, we identify 3 transcriptional states that divide the biological ontology of FL B cells into inflamed, proliferative, and chromatin-modifying states, with relationship to prior GC B cell phenotypes. When integrated with whole-exome sequencing and immune profiling, we find that each state was associated with a combination of mutations in chromatin modifiers, copy-number alterations to TNFAIP3, and T follicular helper cells (Tfh) cell interactions, or primarily by a microenvironment rich in activated T cells. Altogether, these data define FL B cell transcriptional states across a large cohort of patients, contribute to our understanding of FL heterogeneity at the tumor cell level, and provide a foundation for guiding therapeutic intervention.

Multiomic Analysis Identifies a High-Risk Metabolic and TME Depleted Signature that Predicts Early Clinical Failure in DLBCL.

PURPOSE: 60-70% of newly diagnosed diffuse large B-cell lymphoma (DLBCL) patients avoid events within 24 months of diagnosis (EFS24) and the remainder have poor outcomes. Recent genetic and molecular classification of DLBCL has advanced our knowledge of disease biology, yet were not designed to predict early events and guide anticipatory selection of novel therapies. To address this unmet need, we used an integrative multiomic approach to identify a signature at diagnosis that will identify DLBCL at high risk of early clinical failure. PATIENTS AND METHODS: Tumor biopsies from 444 newly diagnosed DLBCL were analyzed by WES and RNAseq. A combination of weighted gene correlation network analysis and differential gene expression analysis followed by integration with clinical and genomic data was used to identify a multiomic signature associated with high risk of early clinical failure. RESULTS: Current DLBCL classifiers are unable to discriminate cases who fail EFS24. We identified a high risk RNA signature that had a hazard ratio (HR, 18.46 [95% CI 6.51-52.31] P < .001) in a univariate model, which did not attenuate after adjustment for age, IPI and COO (HR, 20.8 [95% CI, 7.14-61.09] P < .001). Further analysis revealed the signature was associated with metabolic reprogramming and a depleted immune microenvironment. Finally, WES data was integrated into the signature and we found that inclusion of ARID1A mutations resulted in identification of 45% of cases with an early clinical failure which was validated in external DLBCL cohorts. CONCLUSION: This novel and integrative approach is the first to identify a signature at diagnosis that will identify DLBCL at high risk for early clinical failure and may have significant implications for design of therapeutic options.

Metabolic liver cancer: associations of rare and common germline variants in one-carbon metabolism and DNA methylation genes.

Animal studies implicate one-carbon metabolism and DNA methylation genes in hepatocellular carcinoma (HCC) development in the setting of metabolic perturbations. Using human samples, we investigated the associations between common and rare variants in these closely related biochemical pathways and risk for metabolic HCC development in a multicenter international study. We performed targeted exome sequencing of 64 genes among 556 metabolic HCC cases and 643 cancer-free controls with metabolic conditions. Multivariable logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for multiple comparisons. Gene-burden tests were used for rare variant associations. Analyses were performed in the overall sample and among non-Hispanic whites. The results show that among non-Hispanic whites, presence of rare functional variants in ABCC2 was associated with 7-fold higher risk of metabolic HCC (OR = 6.92, 95% CI: 2.38-20.15, P = 0.0004), and this association remained significant when analyses were restricted to functional rare variants observed in ≥2 participants (cases 3.2% versus controls 0.0%, P = 1.02 × 10-5). In the overall multiethnic sample, presence of rare functional variants in ABCC2 was nominally associated with metabolic HCC (OR = 3.60, 95% CI: 1.52-8.58, P = 0.004), with similar nominal association when analyses were restricted to functional rare variants observed in ≥2 participants (cases 2.9% versus controls 0.2%, P = 0.006). A common variant in PNPLA3 (rs738409[G]) was associated with higher HCC risk in the overall sample (P = 6.36 × 10-6) and in non-Hispanic whites (P = 0.0002). Our findings indicate that rare functional variants in ABCC2 are associated with susceptibility to metabolic HCC in non-Hispanic whites. PNPLA3-rs738409 is also associated with metabolic HCC risk.

Molecular classification and identification of an aggressive signature in low-grade B-cell lymphomas.

Non-follicular low-grade B-cell lymphomas (LGBCL) are biologically diverse entities that share clinical and histologic features that make definitive pathologic categorization challenging. While most patients with LGBCL have an indolent course, some experience aggressive disease, highlighting additional heterogeneity across these subtypes. To investigate the potential for shared biology across subtypes, we performed RNA sequencing and applied machine learning approaches that identified five clusters of patients that grouped independently of subtype. One cluster was characterized by inferior outcome, upregulation of cell cycle genes, and increased tumor immune cell content. Integration of whole exome sequencing identified novel LGBCL mutations and enrichment of TNFAIP3 and BCL2 alterations in the poor survival cluster. Building on this, we further refined a transcriptomic signature associated with early clinical failure in two independent cohorts. Taken together, this study identifies unique clusters of LGBCL defined by novel gene expression signatures and immune profiles associated with outcome across diagnostic subtypes.

Molecular Clusters and Tumor-Immune Drivers of IgM Monoclonal Gammopathies.

PURPOSE: IgM monoclonal gammopathy of undetermined significance (MGUS) and Waldenström macroglobulinemia (WM) represent a disease spectrum with highly varied therapeutic management, ranging from observation to chemoimmunotherapy. The current classification relies solely on clinical features and does not explain the heterogeneity that exists within each of these conditions. Further investigation is warranted to shed light on the biology that may account for the clinical differences. EXPERIMENTAL DESIGN: We used bone marrow (BM) clonal CD19+ and/or CD138+ sorted cells, matched BM supernatant, and peripheral blood serum from 32 patients (7 MGUS, 25 WM) to perform the first multi-omics approach including whole-exome sequencing, RNA sequencing, proteomics, metabolomics, and mass cytometry. RESULTS: We identified three clusters with distinct pathway activation, immune content, metabolomic, and clinical features. Cluster 1 included only patients with WM and was characterized by transcriptional silencing of genes involved in cell cycle and immune response, enrichment of mitochondrial metabolism, infiltration of senescent T effector memory cells, and aggressive clinical behavior. Genetic/structural alterations of TNFAIP3 were distinct events of this cluster. Cluster 2 comprised both MGUS and WM patients with upregulation of inflammatory response, senescence and glycolysis signatures, increased activated T follicular helper and T regulatory cells, and indolent clinical behavior. Cluster 3 also included both MGUS and WM patients and exhibited intermediate features, including proliferative and inflammatory signaling, as well as glycolysis and mitochondrial metabolism. CONCLUSIONS: We have identified three distinct molecular clusters, suggesting a potential biologic classification that may have therapeutic implications.

Correction: All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons.

[This corrects the article DOI: 10.1371/journal.pcbi.1009487.].

ACE2 and TMPRSS2 SARS-CoV-2 infectivity genes: deep mutational scanning and characterization of missense variants.

The human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) proteins play key roles in the cellular internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus responsible for the coronavirus disease of 2019 (COVID-19) pandemic. We set out to functionally characterize the ACE2 and TMPRSS2 protein abundance for variant alleles encoding these proteins that contained non-synonymous single-nucleotide polymorphisms (nsSNPs) in their open reading frames (ORFs). Specifically, a high-throughput assay, deep mutational scanning (DMS), was employed to test the functional implications of nsSNPs, which are variants of uncertain significance in these two genes. Specifically, we used a 'landing pad' system designed to quantify the protein expression for 433 nsSNPs that have been observed in the ACE2 and TMPRSS2 ORFs and found that 8 of 127 ACE2, 19 of 157 TMPRSS2 isoform 1 and 13 of 149 TMPRSS2 isoform 2 variant proteins displayed less than ~25% of the wild-type protein expression, whereas 4 ACE2 variants displayed 25% or greater increases in protein expression. As a result, we concluded that nsSNPs in genes encoding ACE2 and TMPRSS2 might potentially influence SARS-CoV-2 infectivity. These results can now be applied to DNA sequence data for patients infected with SARS-CoV-2 to determine the possible impact of patient-based DNA sequence variation on the clinical course of SARS-CoV-2 infection.

All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons.

Accurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing a cell's genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All2, which enables accurate filtering of mutations in a cell without the need for data from bulk(s). It is based on pair-wise comparisons of all cells to each other where every call for base pair substitution and indel is classified as either a germline variant, mosaic mutation, or false positive. As All2 allows for considering dropped-out regions, it is applicable to whole genome and exome analysis of cloned and amplified cells. By applying the approach to a variety of available data, we showed that its application reduces false positives, enables sensitive discovery of high frequency mutations, and is indispensable for conducting high resolution cell lineage tracing.

Frequent POLE-driven hypermutation in ovarian endometrioid cancer revealed by mutational signatures in RNA sequencing.

BACKGROUND: DNA polymerase epsilon (POLE) is encoded by the POLE gene, and POLE-driven tumors are characterized by high mutational rates. POLE-driven tumors are relatively common in endometrial and colorectal cancer, and their presence is increasingly recognized in ovarian cancer (OC) of endometrioid type. POLE-driven cases possess an abundance of TCT > TAT and TCG > TTG somatic mutations characterized by mutational signature 10 from the Catalog of Somatic Mutations in Cancer (COSMIC). By quantifying the contribution of COSMIC mutational signature 10 in RNA sequencing (RNA-seq) we set out to identify POLE-driven tumors in a set of unselected Mayo Clinic OC. METHODS: Mutational profiles were calculated using expressed single-nucleotide variants (eSNV) in the Mayo Clinic OC tumors (n = 195), The Cancer Genome Atlas (TCGA) OC tumors (n = 419), and the Genotype-Tissue Expression (GTEx) normal ovarian tissues (n = 84). Non-negative Matrix Factorization (NMF) of the mutational profiles inferred the contribution per sample of four distinct mutational signatures, one of which corresponds to COSMIC mutational signature 10. RESULTS: In the Mayo Clinic OC cohort we identified six tumors with a predicted contribution from COSMIC mutational signature 10 of over five mutations per megabase. These six cases harbored known POLE hotspot mutations (P286R, S297F, V411L, and A456P) and were of endometrioid histotype (P = 5e-04). These six tumors had an early onset (average age of patients at onset, 48.33 years) when compared to non-POLE endometrioid OC cohort (average age at onset, 60.13 years; P = .008). Samples from TCGA and GTEx had a low COSMIC signature 10 contribution (median 0.16 mutations per megabase; maximum 1.78 mutations per megabase) and carried no POLE hotspot mutations. CONCLUSIONS: From the largest cohort of RNA-seq from endometrioid OC to date (n = 53), we identified six hypermutated samples likely driven by POLE (frequency, 11%). Our result suggests the clinical need to screen for POLE driver mutations in endometrioid OC, which can guide enrollment in immunotherapy clinical trials.

Impact of variant-level batch effects on identification of genetic risk factors in large sequencing studies.

Genetic studies have shifted to sequencing-based rare variants discovery after decades of success in identifying common disease variants by Genome-Wide Association Studies using Single Nucleotide Polymorphism chips. Sequencing-based studies require large sample sizes for statistical power and therefore often inadvertently introduce batch effects because samples are typically collected, processed, and sequenced at multiple centers. Conventionally, batch effects are first detected and visualized using Principal Components Analysis and then controlled by including batch covariates in the disease association models. For sequencing-based genetic studies, because all variants included in the association analyses have passed sequencing-related quality control measures, this conventional approach treats every variant as equal and ignores the substantial differences still remaining in variant qualities and characteristics such as genotype quality scores, alternative allele fractions (fraction of reads supporting alternative allele at a variant position) and sequencing depths. In the Alzheimer's Disease Sequencing Project (ADSP) exome dataset of 9,904 cases and controls, we discovered hidden variant-level differences between sample batches of three sequencing centers and two exome capture kits. Although sequencing centers were included as a covariate in our association models, we observed differences at the variant level in genotype quality and alternative allele fraction between samples processed by different exome capture kits that significantly impacted both the confidence of variant detection and the identification of disease-associated variants. Furthermore, we found that a subset of top disease-risk variants came exclusively from samples processed by one exome capture kit that was more effective at capturing the alternative alleles compared to the other kit. Our findings highlight the importance of additional variant-level quality control for large sequencing-based genetic studies. More importantly, we demonstrate that automatically filtering out variants with batch differences may lead to false negatives if the batch discordances come largely from quality differences and if the batch-specific variants have better quality.

SLCO1B1: Application and Limitations of Deep Mutational Scanning for Genomic Missense Variant Function.

SLCO1B1 (solute carrier organic anion transporter family member 1B1) is an important transmembrane hepatic uptake transporter. Genetic variants in the SLCO1B1 gene have been associated with altered protein folding, resulting in protein degradation and decreased transporter activity. Next-generation sequencing (NGS) of pharmacogenes is being applied increasingly to associate variation in drug response with genetic sequence variants. However, it is difficult to link variants of unknown significance with functional phenotypes using "one-at-a-time" functional systems. Deep mutational scanning (DMS) using a "landing pad cell-based system" is a high-throughput technique designed to analyze hundreds of gene open reading frame (ORF) missense variants in a parallel and scalable fashion. We have applied DMS to analyze 137 missense variants in the SLCO1B1 ORF obtained from the Exome Aggregation Consortium project. ORFs containing these variants were fused to green fluorescent protein and were integrated into "landing pad" cells. Florescence-activated cell sorting was performed to separate the cells into four groups based on fluorescence readout indicating protein expression at the single cell level. NGS was then performed and SLCO1B1 variant frequencies were used to determine protein abundance. We found that six variants not previously characterized functionally displayed less than 25% and another 12 displayed approximately 50% of wild-type protein expression. These results were then functionally validated by transporter studies. Severely damaging variants identified by DMS may have clinical relevance for SLCO1B1-dependent drug transport, but we need to exercise caution since the relatively small number of severely damaging variants identified raise questions with regard to the application of DMS to intrinsic membrane proteins such as organic anion transporter protein 1B1. SIGNIFICANCE STATEMENT: The functional implications of a large numbers of open reading frame (ORF) "variants of unknown significance" (VUS) in transporter genes have not been characterized. This study applied deep mutational scanning to determine the functional effects of VUS that have been observed in the ORF of SLCO1B1(s olute carrier organic anion transporter family member 1B1). Several severely damaging variants were identified, studied, and validated. These observations have implications for both the application of deep mutational scanning to intrinsic membrane proteins and for the clinical effect of drugs and endogenous compounds transported by SLCO1B1.

Early developmental asymmetries in cell lineage trees in living individuals.

Mosaic mutations can be used to track cell lineages in humans. We used cell cloning to analyze embryonic cell lineages in two living individuals and a postmortem human specimen. Of 10 reconstructed postzygotic divisions, none resulted in balanced contributions of daughter lineages to tissues. In both living individuals, one of two lineages from the first cleavage was dominant across tissues, with 90% frequency in blood. We propose that the efficiency of DNA repair contributes to lineage imbalance. Allocation of lineages in postmortem brain correlated with anterior-posterior axis, associating lineage history with cell fate choices in embryos. We establish a minimally invasive framework for defining cell lineages in any living individual, which paves the way for studying their relevance in health and disease.

Fine-mapping of the non-coding variation driving the Caucasian LRRK2 GWAS signal in Parkinson's disease.

INTRODUCTION: Genome-wide association studies (GWAS) have confirmed the leucine-rich repeat kinase 2 (LRRK2) gene as a susceptibility locus for idiopathic Parkinson's disease (PD) in Caucasians. Though the rs1491942 and rs76904798 variants have shown the strongest associations, the causal variant(s) remains unresolved. Therefore, the aim of this study was to identify variants that may be driving the LRRK2 GWAS signal by sequencing the entire LRRK2 gene in Caucasian PD patients and controls. METHODS: A discovery series (287 PD patients, 294 controls) and replication series (362 PD patients, 168 controls) were included. The entire LRRK2 gene as well as 10 Kb upstream/downstream was sequenced. Candidate potential causal variants were considered to be those that (a) were in at least weak linkage disequilibrium with the two GWAS-nominated variants (rs1491942 and rs76904798), and (b) displayed an association odds ratio (OR) that is stronger than the two GWAS variants. RESULTS: Thirty-four candidate variants (all intronic/intergenic) that may drive the LRRK2 PD GWAS signal were identified in the discovery series. However, examination of the replication series for these variants did not reveal any with a consistently stronger OR than both PD GWAS variants. Evaluation of public databases to determine which candidate variants are most likely to have a direct functional effect on LRRK2 expression was inconclusive. CONCLUSION: Though our findings provide novel insights into the LRRK2 GWAS association, a clear causal variant was not identified. The identified candidate variants can form the basis for future experiments and functional studies that can more definitively assess causal LRRK2 variants.

Targeting of inflammatory pathways with R2CHOP in high-risk DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma, and front line therapies have not improved overall outcomes since the advent of immunochemotherapy. By pairing DNA and gene expression data with clinical response data, we identified a high-risk subset of non-GCB DLBCL patients characterized by genomic alterations and expression signatures capable of sustaining an inflammatory environment. These mutational alterations (PIM1, SPEN, and MYD88 [L265P]) and expression signatures (NF-κB, IRF4, and JAK-STAT engagement) were associated with proliferative signaling, and were found to be enriched in patients treated with RCHOP that experienced unfavorable outcomes. However, patients with these high-risk mutations had more favorable outcomes when the immunomodulatory agent lenalidomide was added to RCHOP (R2CHOP). We are the first to report the genomic validation of a high-risk phenotype with a preferential response towards R2CHOP therapy in non-GCB DLBCL patients. These conclusions could be translated to a clinical setting to identify the ~38% of non-GCB patients that could be considered high-risk, and would benefit from alternative therapies to standard RCHOP based on personalized genomic data.

SCELLECTOR: ranking amplification bias in single cells using shallow sequencing.

BACKGROUND: The study of mosaic mutation is important since it has been linked to cancer and various disorders. Single cell sequencing has become a powerful tool to study the genome of individual cells for the detection of mosaic mutations. The amount of DNA in a single cell needs to be amplified before sequencing and multiple displacement amplification (MDA) is widely used owing to its low error rate and long fragment length of amplified DNA. However, the phi29 polymerase used in MDA is sensitive to template fragmentation and presence of sites with DNA damage that can lead to biases such as allelic imbalance, uneven coverage and over representation of C to T mutations. It is therefore important to select cells with uniform amplification to decrease false positives and increase sensitivity for mosaic mutation detection. RESULTS: We propose a method, Scellector (single cell selector), which uses haplotype information to detect amplification quality in shallow coverage sequencing data. We tested Scellector on single human neuronal cells, obtained in vitro and amplified by MDA. Qualities were estimated from shallow sequencing with coverage as low as 0.3× per cell and then confirmed using 30× deep coverage sequencing. The high concordance between shallow and high coverage data validated the method. CONCLUSION: Scellector can potentially be used to rank amplifications obtained from single cell platforms relying on a MDA-like amplification step, such as Chromium Single Cell profiling solution.

Somatic copy number gains in MYC, BCL2, and BCL6 identifies a subset of aggressive alternative-DH/TH DLBCL patients.

Double/triple hit lymphoma (DH/TH), known as high-grade B-cell lymphoma (HGBL), is an aggressive diffuse large B cell lymphoma (DLBCL), defined as having concurrent MYC, BCL2, and/or BCL6 gene rearrangements. While gene rearrangements represent significant genetic events in cancer, copy number alterations (CNAs) also play an important role, and their contributions to rearrangements have yet to be fully elucidated. Using FISH and high-resolution CNA data, we defined the landscape of concurrent gene rearrangements and copy gains in MYC, BCL2, and BCL6, in a cohort of 479 newly diagnosed DLBCL. We also show that concurrent translocations and copy number alterations, in combinations similar to DH/TH, identify a unique subset of DLBCL, alternative DH/TH, that have survival outcomes similar to DH/TH DLBCL patients.

HLA class-I and class-II restricted neoantigen loads predict overall survival in breast cancer.

Tumors acquire numerous mutations during development and progression. When translated into proteins, these mutations give rise to neoantigens that can be recognized by T cells and generate antibodies, representing an exciting direction of cancer immunotherapy. While neoantigens have been reported in many cancer types, the profiling of neoantigens often focused on the class-I subtype that are presented to CD8 + T cells, and the relationship between neoantigen load and clinical outcomes was often inconsistent among cancer types. In this study, we described an informatics workflow, REAL-neo, for identification, quality control (QC), and prioritization of both class-I and class-II human leukocyte antigen (HLA) bound neoantigens that arise from somatic single nucleotide mutations (SNM), small insertions and deletions (INDEL), and gene fusions. We applied REAL-neo to 835 primary breast tumors in the Cancer Genome Atlas (TCGA) and performed comprehensive profiling and characterization of the detected neoantigens. We found recurrent HLA class-I and class-II restricted neoantigens across breast cancer cases, and uncovered associations between neoantigen load and clinical traits. Both class-I and class-II neoantigen loads from SNM and INDEL were found to predict overall survival independent of tumor mutational burden (TMB), breast cancer subtypes, tumor-infiltrating lymphocyte (TIL) levels, tumor stage, and age at diagnosis. Our study highlighted the importance of accurate and comprehensive neoantigen profiling and QC, and is the first to report the predictive value of neoantigen load for overall survival in breast cancer.

CYP2C9 and CYP2C19: Deep Mutational Scanning and Functional Characterization of Genomic Missense Variants.

Single nucleotide variants in the open reading frames (ORFs) of pharmacogenes are important causes of interindividual variability in drug response. The functional characterization of variants of unknown significance within ORFs remains a major challenge for pharmacogenomics. Deep mutational scanning (DMS) is a high-throughput technique that makes it possible to analyze the functional effect of hundreds of variants in a parallel and scalable fashion. We adapted a "landing pad" DMS system to study the function of missense variants in the ORFs of cytochrome P450 family 2 subfamily C member 9 (CYP2C9) and cytochrome P450 family 2 subfamily C member 19 (CYP2C19). We studied 230 observed missense variants in the CYP2C9 and CYP2C19 ORFs and found that 19 of 109 CYP2C9 and 36 of 121 CYP2C19 variants displayed less than ~ 25% of the wild-type protein expression, a level that may have clinical relevance. Our results support DMS as an efficient method for the identification of damaging ORF variants that might have potential clinical pharmacogenomic application.

Inherited variants at 3q13.33 and 3p24.1 are associated with risk of diffuse large B-cell lymphoma and implicate immune pathways.

We previously identified five single nucleotide polymorphisms (SNPs) at four susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (GWAS). To further elucidate genetic susceptibility to DLBCL, we sought to validate two loci at 3q13.33 and 3p24.1 that were suggestive in the original GWAS with additional genotyping. In the meta-analysis (5662 cases and 9237 controls) of the four original GWAS discovery scans and three replication studies, the 3q13.33 locus (rs9831894; minor allele frequency [MAF] = 0.40) was associated with DLBCL risk [odds ratio (OR) = 0.83, P = 3.62 × 10-13]. rs9831894 is in linkage disequilibrium (LD) with additional variants that are part of a super-enhancer that physically interacts with promoters of CD86 and ILDR1. In the meta-analysis (5510 cases and 12 817 controls) of the four GWAS discovery scans and four replication studies, the 3p24.1 locus (rs6773363; MAF = 0.45) was also associated with DLBCL risk (OR = 1.20, P = 2.31 × 10-12). This SNP is 29 426-bp upstream of the nearest gene EOMES and in LD with additional SNPs that are part of a highly lineage-specific and tumor-acquired super-enhancer that shows long-range interaction with AZI2 promoter. These loci provide additional evidence for the role of immune function in the etiology of DLBCL, the most common lymphoma subtype.

Amplification of 9p24.1 in diffuse large B-cell lymphoma identifies a unique subset of cases that resemble primary mediastinal large B-cell lymphoma.

Copy number alterations (CNAs) of 9p24.1 occur frequently in Hodgkin lymphoma, primary mediastinal large B-cell lymphoma (PMBCL), primary central nervous system lymphoma, and primary testicular lymphoma, resulting in overexpression of PD-L1 and sensitivity to PD-1 blockade-based immunotherapy. While 9p24.1 CNA was also reported in diffuse large B-cell lymphoma (DLBCL), little is known about its molecular or clinical significance. In this study, we analyzed the prevalence of 9p24.1 CNA in newly diagnosed DLBCL and examined its association with PD-L1, PD-L2, and JAK2 expression, clinical characteristics, and outcome. We found that 10% of DLBCL cases had CNA of 9p24.1, with 6.5% gains, and 3.5% amplifications. Only the cases with a 9p24.1 amplification had high levels of PD-L1, PD-L2, and JAK2 expression. Gains or amplifications of 9p24.1 were associated with a younger age and the ABC/non-GCB subtype. Compared with DLBCL cases without 9p24.1 CNA, the cases with a 9p24.1 amplification had a trend of better event-free survival. Furthermore, the amplification cases had a gene expression and mutation profile similar to those of PMBCL. Our data suggest that amplification of 9p24.1 identifies a unique subset of DLBCL with clinical and molecular features resembling PMBCL that may be amenable to PD-1 blockade-based immunotherapy.