Abstract Background: Post-transplant lymphoproliferative disorder (PTLD) occurs in up to 30% of high-risk solid organ transplant recipients and is strongly associated with the intensity and duration of immunosuppression. While Epstein-Barr virus (EBV)-positive monomorphic PTLD and diffuse large B-cell lymphoma (DLBCL) share overlapping morphologic features and expression of canonical B-cell markers, they exhibit distinct EBV transcriptional programs. Immunosuppressive regimens, essential for preventing graft rejection, impair EBV-specific cytotoxic T lymphocyte (CTL) responses, thereby promoting EBV-driven lymphomagenesis. We hypothesized that these differences in viral transcription and immune evasion reflect fundamentally distinct immune microenvironments and host responses in EBV-positive PTLD compared to DLBCL. Methods This prospective, non-interventional study has been conducted at Moffitt Cancer Center since 2019. To characterize tumor-specific T-cell responses in EBV-positive PTLD versus DLBCL, peripheral blood mononuclear cells (PBMCs) from enrolled patients were infected with EBV (ATCC VR-1492) to generate autologous, immortalized lymphoblastoid B-cell lines (LCLs). EBV antigen-specific immune responses were quantified using an IFN-γ ELISpot assay targeting EBNA1, LAMP1, LAMP2A, BARF1, and a CEF peptide pool as a control. To optimize cell viability and functional readout post-thaw, we implemented an overnight resting protocol for PBMCs, which demonstrated superior IFN-γ release compared to the conventional 1-hour rest. Results We present pilot data from 11 consecutive patients (55% male; median age 63.4 years), including 3 with PTLD (2 EBV-positive; 2 monomorphic) and 8 with EBV-negative DLBCL. A total of 12 evaluable PBMC samples were analyzed: 7 pre-treatment, 1 mid-treatment, and 4 post-treatment. Successful generation of autologous LCLs was predominantly achieved using pre-treatment samples, whereas samples collected after B-cell–targeted therapy (Rituximab ± CHOP) showed reduced transformation efficiency. Notably, early pre-treatment samples exhibited a relative enrichment of CD27⁺ memory B cells. Baseline flow cytometric profiling of B cells undergoing LCL transformation revealed low CD19 expression (range <1%–15%). Repeat immunophenotyping at 3 weeks identified residual T cells within cultures, suggesting ongoing B-cell clearance. In matched flow cytometry and ELISpot assays from 7 evaluable patients with pre-treatment samples, EBV-positive PTLD cases demonstrated pronounced overexpression of PD-1 and TIM-3, but not LAG-3, alongside markedly diminished T-cell responses to EBV antigens. This distinct immunophenotypic and functional signature suggests T-cell exhaustion or dysfunction, likely driven by prior immunosuppression, which may impair immune surveillance and facilitate EBV-driven lymphomagenesis. Conclusions Our findings reveal distinct immunologic profiles in EBV-positive monomorphic PTLD compared to EBV-negative DLBCL, characterized by immune exhaustion and impaired T-cell functionality. Specifically, overexpression of PD-1 and TIM-3—but not LAG-3—in EBV-positive PTLD correlated with diminished antigen-specific T-cell responses, as measured by ELISpot, underscoring the role of prior immunosuppression in shaping ineffective tumor-specific immunity. Successful generation of autologous LCLs was predominantly achieved from pre-treatment PBMCs, highlighting the impact of B-cell–depleting therapies (Rituximab ± CHOP) on downstream immune profiling feasibility. The persistence of residual T cells in long-term LCL cultures suggests ongoing B-cell clearance and may reflect previously unrecognized immune dynamics in PTLD. Collectively, these data provide novel insights into the immune landscape of EBV-driven PTLD and support the rationale for therapeutic strategies aimed at reversing T-cell exhaustion—such as immune checkpoint blockade or adoptive T-cell therapies—to restore anti-EBV immunity in transplant recipients.
Interim Results of the CMML scrna-seq atlas: GMP skewing is independently associated with overall survival in CMML.
Abstract Background The expansion of hematopoietic stem and progenitor cells (HSPCs) in the bone marrow is universally associated with adverse outcomes and disease progression in all chronic myeloid neoplasms, to include chronic myelomonocytic leukemia (CMML). However, HSPCs are a heterogeneous cellular compartment and the impact of its composition on clinical outcomes remains poorly defined. Single cell RNA-sequencing (scRNA-seq) represents an optimal strategy to annotate cellular composition but no large clinically annotated scRNA-seq datasets are currently available. To address this, we have embarked to generate a clinically annotated 500 patient CMML scRNA-seq atlas from CD34+ enriched BMNCs to establish among the largest clinically and genetically annotated single cell references for any chronic myeloid malignancy. Here we report the interim analysis of 113 clinically annotated cases that demonstrates massive reshaping of HSPC composition that is independently a predictor of overall survival. Methods Single-cell RNA expression profiling was performed on 113 CD34-enriched CMML BMNC samples using 10x Genomics GEM-X Universal 3' Gene Expression v4 (4-plex) chemistry. Libraries were sequenced on NovaSeq S4 flow cells in two runs, and data were processed using Cell Ranger to generate gene expression matrices. A total of 502,659 single cells from 113 samples were processed using Seurat. The upper threshold for gene count was defined as the mean number of detected genes plus two standard deviations data normalization was performed using the log-normalization method. Batch correction and integration were conducted with Harmony to mitigate technical variation across pools. Descriptive statistics were used to tabulate clinical and genetic parameters. KM curves, log-rank test, and cox regression were used to calculate survival, test for statistical differences, and perform multivariate analysis, respectively. Results To derive high resolution cell annotations, we employed the SingleR algorithm using a large hematopoietic reference of over 300,000 single cells (Zhang, X. Nature Immunology, 2024). Using this approach a diverse set of cell types were identified that included HSCs, 23 myeloid progenitors, 18 erythroid progenitors, and 18 lymphoid progenitors. This diverse cellular repertoire displayed massive reshaping relative to the normal CD34 enriched reference including a >53x expansion of multilineage GMPs and a >100x depletion of B-cell progenitors consistent with the known myeloid skewing seen in this disease. To understand whether expansion of specific progenitors was associated with outcomes we iteratively evaluated key progenitor populations and observed that expansions of HSC (HR 0.468 p<0.005) and MEP (HR 0.485, p<0.005) were associated with improved survival while GMP (HR 1.729, p=0.029) expansions were associated with inferior survival when using a cut point derived with a maximally selected ranks statistics approach. To achieve a more comprehensive metric of HSPC composition we explored GMP ratios to include GMP/HSC ratios and GMP/MEP ratios and observed that both were associated with inferior survival in univariate and multivariate when considering clinical and genetic features such as the CPSS-molecular prognostic score and FAB classification. When considering both GMP/HSC and GMP/MEP ratios in a multivariate model only GMP/MEP ratios and CPSS molecular remained independently prognostic. As an orthogonal approach, pseudotime projections were carried out using a reference map from Setty et al., 2019 to calculate differentiation potential and branch probabilities. This approach enabled both cell identity assignment and placement of cells along the hematopoietic differentiation trajectory. Samples were classified as monocyte-biased, MEP-biased, or normal-like, as previously described (Ferrall-Fairbanks et al. 2022) and demonstrated that increased GMP ratios are associated with a monocytic biased trajectory and that this trajectory is also associated with overall survival. Conclusion This study represents an interim analysis of among the largest scRNA-seq cohorts generated in chronic myeloid malignancies. This enabled us, for the first time, to demonstrate that HSPC composition is independently prognostic even when considering modern CMML prognostic models. As this cohort continues to increase, validation of these findings and examining the impact of therapy on HPSC composition in serial samples will be prioritized.
Evaluating the Radiation Sensitivity Index and 12-Chemokine Gene Expression Signature for Clinical Use in a CLIA Laboratory
Abstract The radiation sensitivity index (RSI) and 12-chemokine gene expression signature (12CK GES) are two gene expression signatures (GES) that were previously developed to predict tumor radiation sensitivity or identify the presence of tertiary lymphoid structures in tumors, respectively. To advance the use of these GESs into clinical trial evaluation, their assays must be assessed within the context of the Clinical Laboratory Improvement Amendments (CLIA) process. Using HG-U133Plus2.0 arrays, we first established CLIA laboratory proficiency. Then the accuracy (limit of detection and macrodissection impact), precision (variability by time and operator), sample type (surgery vs. biopsy), and concordance with a reference laboratory were evaluated. RSI and 12CK GES were reproducible (RSI: 0.01 mean difference, 12CK GES: 0.17 mean difference) and precise with respect to time and operator. Taken together, the reproducibility analysis of the scores indicated a median RSI difference of 0.06 (6.47% of range) across samples and a median 12CK GES difference of 0.92 (12.29% of range). Experiments indicated that the lower limit of input RNA is 5 ng. Reproducibility with a second CLIA laboratory demonstrated reliability with the median RSI score difference of 0.065 (6% of full range) and 12CK GES difference of 0.93 (12% of observed range). Overall, under CLIA, RSI and 12CK GES were demonstrated by the Moffitt Cancer Center Advanced Diagnostic Laboratory to be reproducible GESs for clinical usage. Significance: The RSI and 12CK GES are two GESs that predict tumor radiation sensitivity or the presence of tertiary lymphoid structures in tumors, respectively. These GESs were assessed within the CLIA process for future clinical use. We established proficiency, reproducibility, and reliability characteristics for both signatures in a controlled setting, indicating these GESs are suitable for validation within future clinical trials.
Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus
Abstract Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. Significance: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. See related commentary by Choi and Brown, p. 439
Abstract 420: Targeted deep sequencing of mitochondrial DNA in epithelial ovarian carcinomas
Abstract Introduction: Mitochondria are intracellular organelles that play an important role in energy metabolism, reactive oxygen species generation, and apoptosis. They possess their own haploid genome distinct from nuclear DNA, and mutations in mitochondrial DNA (mtDNA) have previously been linked to cancer risk, disease progression, and treatment response for multiple tumor types. However, the spectrum of mtDNA variation in epithelial ovarian carcinoma (EOC) and associations with clinical characteristics have not been fully explored. Methods: We extracted mtDNA from fresh frozen EOC tumors of women diagnosed with primary invasive epithelial ovarian, fallopian tube, or peritoneal carcinoma, and performed targeted sequencing using the Illumina MiSeq Reporter mtDNA workflow. Homoplasmic and heteroplasmic SNVs and indels were called using an in-house bioinformatics pipeline. We estimated mtDNA haplogroup using Haplogrep and compared to results from available germline mtDNA SNP genotyping. We derived regional weighted variant burden scores based on mtDNA functional domains, accounting for underlying haplogroup, heteroplasmic fraction, and predicted functional impact. To assess potential differences in variant burden by histotype, we compared burden scores using Kruskal-Wallis testing. Among high-grade serous tubo-ovarian cases, we explored associations with overall survival (OS) using Cox proportional hazards regression. After quality control filtering, 389 mitochondrial genomes were analyzed, including those from 320 tubo-ovarian high-grade serous tumors, 42 endometrioid tumors, and 18 clear cell tumors. Results: Accounting for predicted haplogroup, we identified a median count of two global private heteroplasmies per tumor (range: 0-9). Elevated mutation rates were identified in the regulatory control region as well as among the various mt-tRNAs (>3 per 10kb per sample) relative to the remainder of the mtDNA. The majority of recurrent variants across tumors were also identified in the mtDNA control region. We did not observe an association with overall mtDNA variant burden and patient age at diagnosis. Regional mtDNA burden scores revealed a significant association with histotype (P<0.001) for the oxidative phosphorylation complex IV genes, with higher burden in tubo-ovarian high-grade serous and clear-cell tumors relative to endometrioid tumors. For patients with tubo-ovarian high-grade serous tumors, increased variant burden in MT-CO1 (cytochrome C oxidase I) was associated with improved OS (HR = 0.32; 95% CI = [0.14,0.70], LRT P = 0.001) after adjustment for age, stage, and debulking status. Conclusions: We demonstrate a wide range of tumor mtDNA variant patterns in the largest known collection of EOC patients. This work provides the first extensive evaluation of mtDNA variation in these diseases and highlights the potential prognostic relevance of mitochondrial dysfunction. Citation Format: Nicholas B. Larson, Stacey J. Winham, Chen Wang, Jared M. Evans, Sebastian M. Armasu, Bryan M. McCauley, Sean J. Yoder, Lan Min Zhang, Catherine M. Phelan, Ellen L. Goode. Targeted deep sequencing of mitochondrial DNA in epithelial ovarian carcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 420.
Abstract 3285: Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition
Abstract An ovarian cancer Genome Wide Association Study (GWAS) identified 9p22.2 as a novel susceptibility locus with the most statistically significant single nucleotide polymorphisms (SNPs) located in an intergenic region near the Basonuclin 2 (BNC2) gene, which codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. The minor alleles are protective in terms of ovarian cancer susceptibility. However, the molecular mechanisms by which these SNPs modify susceptibility remain largely unknown. The significant SNPs in the 9p22.2 locus lie in non-coding regions and therefore are hypothesized to affect the activity of regulatory elements and modify the expression of a target gene(s). In order to test this hypothesis we conducted fine mapping for the locus which delimited a ∼74kb region containing SNPs with a p-value less than 10-8. FAIRE-Seq and ChIP-Seq experiments for histone markers conducted in immortalized ovarian surface epithelial cells (IOSE) and fallopian tube epithelial cells (IFTE) were used to prioritize functional SNP candidates which overlap with regulatory elements. Luciferase assays tested the ability of these regulatory elements to activate transcription. Chromosome conformation capture (3C) experiments demonstrate a physical interaction between the BNC2 promoter and candidate regulatory elements containing risk-associated SNPs. Methylation Quantification at Trait Loci (mQTL) revealed an association between decreased methylation at the BNC2 promoter and the protective minor alleles. Expression analysis shows decreased expression of BNC2 in cancer versus normal tissue implicating tumor suppressor function of BNC2. Therefore the protective minor allele likely increases expression of BNC2 which in turn contains tumor suppressing properties that decrease ovarian cancer risk. BNC2 protein is in complex with transcriptional regulatory proteins, in particular the NURD complex components. Moreover, BNC2 acts as a transcriptional repressor in in vitro transfection assays indicating that it functions in transcriptional repression. We then used protein binding microarrays and CHIP-Seq experiments to identify its putative DNA binding motifs and its downstream target genes. Analysis of this data suggests that BNC2 functions in a regulatory transcription network that impacts on genes implicated in ovarian cancer with enrichment for genes in the TGF-beta response pathway. Citation Format: Melissa A. Buckley, Howard C. Shen, Gustavo A. Mendoza-Fandino, Nicholas T. Woods, Anxhela Gjyshi, Juliet French, Kate Lawrenson, Honglin Song, Jonathan Tyrer, Renato S. Carvalho, Alexandra Valle, Ann Chen, Sean Yoder, Gregory Bloom, Ya-Yu Tsai, Ally Yang, Timothy R. Hughes, Xiaotao Qu, Mine Cicek, Melissa Larson, Ellen Goode, Brooke Fridley, Susan Ramus, Georgia Chenevix-Trench, Paul Pharoah, Thomas A. Sellers, Simon Gayther, Alvaro N.A. Monteiro, Ovarian Cancer Association Consortium. Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition. [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 3285. doi:10.1158/1538-7445.AM2014-3285