Ragini Adams

Introduction: The scarcity of malignant Reed-Sternberg cells has hampered comprehensive genomic profiling of classic Hodgkin lymphoma (cHL) as might inform personalized therapeutic strategies. Given that profiling of circulating tumor DNA (ctDNA) has shown utility in non-Hodgkin lymphoma genotyping and risk stratification, we employed a noninvasive approach in cHL to overcome challenges imposed by low tumor fraction and improve risk stratification. Patients & Methods: We profiled 478 plasma and 26 tumor samples from 304 patients diagnosed with cHL, 98% of whom were enrolled prior to anti-lymphoma therapy. Median age was 29 (range 4-86), 37% had advanced stage (III/IV) disease, and among the subset with early stage (I/II) disease (63%), 91% had unfavorable GHSG risk. We applied CAPP-Seq and Whole Exome Sequencing (WES) to genotype plasma and tumor samples and used 'phased variant enrichment and detection sequencing' (PhasED-Seq) for detection of measurable residual disease (MRD). Whole exome genotypes were generated using a novel gradient boosting model from mutation and cell-free DNA fragmentomic features. We combined mutation calls with genome-wide copy number profiles to define distinct cHL genetic subtypes by lexical clustering through Latent Dirichlet Allocation. To functionally characterize truncating interleukin 4 receptor (IL4R) mutations, we generated a set of recombinant mutant constructs by site directed mutagenesis, and measured phosphorylation levels of IL4R's proximal downstream target STAT6 following ligand stimulation using flow cytometry. Results: Among 16 patients evaluable for paired tumor and blood specimens, analysis of shared mutations detected in both analytes revealed plasma variant allele fractions (AF) to exceed tumor AFs in 75% of cases (Fig A). The average enrichment exceeded 6-fold, demonstrating noninvasive genotyping to be superior to bulk tumor tissue genotyping for most patients. When compared to patients with diffuse large B-cell lymphoma (DLBCL), median plasma AF in cHL were significantly higher (2.3% vs 1.2%, P=0.03), and cHL tumors shed ~2.75x more ctDNA per mL malignant tumor volume (13.8 vs 5.0 haploid genome equivalents (hGE), P<0.0001). We nominate a candidate mechanism driving this striking variation in ctDNA shedding. To comprehensively profile the coding genomic landscape of cHL, we performed plasma WES (360x median coverage) of 119 pretreatment samples with sufficiently high AF allowing us to identify several novel recurrent lesions and to noninvasively define genetically distinct cHL clusters. Among these newly identified recurrent somatic lesions, we identified a novel class of truncating IL4R mutations in ~10% of cHL patients. These IL4R mutations were distinct from those observed in primary mediastinal B-cell lymphoma (PMBL), with cHL mutations typically disrupting IL4R's intracellular immunoreceptor tyrosine-based inhibitory motif (ITIM) domain and conferring cytokine dependent gain of function phenotypes in vitro through enhancement of IL13, but not IL4 signaling (n=48, P<0.05). Strikingly, IL13 expression was substantially higher in cHL tumors than non-Hodgkin lymphomas, and IL13 amplifications (5q31.1) were enriched in IL4R mutant cases (P<0.001), suggesting an underlying autocrine loop. Finally, unlike hotspot IL4R mutations in PMBL, gain-of-function phenotypes of cHL mutations were blockable by antibodies targeting surface IL4R (n=5, P<0.01), which may therefore serve as a precision therapy target. Among 244 treatment-naïve adult patients, pretreatment ctDNA levels predicted progression-free survival (PFS) both as a continuous (HR 2.1, P=0.02) or a dichotomous variable (HR 3.3, P=0.003). Importantly, associations of pretreatment ctDNA levels and outcomes were independent of stage-based and unfavorable risk groups (both P<0.05). Among patients evaluable for MRD, we observed rapid molecular response to therapy, including after ABVD or Bv-AVD. Specifically, MRD negativity rates at C(ycle)1 D(ay)15 and C3D1 were 38% and 90%, respectively. Importantly, ctDNA detection at both C1D15 and C3D1 were prognostic for PFS (P=0.03 and P=0.002, Fig B). Conclusions: Using a noninvasive approach, we overcome known challenges in cHL profiling and describe several molecularly distinct HL subtypes as defined by genotypes, ctDNA levels, and MRD with diagnostic, prognostic, and therapeutic potential. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Introduction: The scarcity of malignant Hodgkin and Reed-Sternberg (HRS) cells has hampered comprehensive genomic profiling of classic Hodgkin lymphoma (cHL) from tumor tissue. Multiple recent studies have demonstrated that plasma cfDNA profiling facilitates molecular characterization of cHL. Leveraging noninvasive genotypes and Latent Dirichlet Allocation, we recently defined 2 genetic cHL subtypes in a large international cohort comprising 366 patients including pediatric and adult patients of all ages (Alig et al., ASH 2022 and ICML 2023). Cluster H1 comprised ~2/3 of cases and was dominated by a high somatic mutational burden, and non-silent mutations in genes canonically involved in NF-κB, JAK/STAT and PI3K signaling as well as in B2M. Conversely, cluster H2 (~1/3 of cases) was primarily characterized by recurrent somatic copy number aberrations as well as mutations in TP53 and KMT2D. Herein, we validate these previously identified genetic subtypes in external datasets as well as through orthogonal methods including tissue-based and noninvasive transcriptional and immune profiling. Methods: To validate genetic cHL subtypes, we first leveraged public cHL genotypes from 61 patients obtained through whole genome/exome sequencing (WGS/WES) of flow-sorted HRS cells (Maura et al, Blood Cancer Disc. 2023). Using our previously locked down probabilistic classifier, we assigned the H1/H2 subtype, and then correlated cluster assignments with clinical variables. To explore transcriptional differences between genetic subtypes, we profiled baseline plasma samples (n=113) from the larger plasma genotyping cohort (n=293) using EPIC-Seq (Esfahani et al, Nat Biotechnol 2022), which allows for noninvasive gene expression profiling from cfDNA fragmentation patterns at transcription start sites. Further, we used SABER (Sworder, Cancer Cell 2023) to enumerate T-cell receptor (TCR) rearrangements in cfDNA (cfTCR, n=292). Finally, to assess subtype-specific immune infiltrate patterns, we profiled cHL tumor specimens using RNA-Seq (n=64), and applied CIBERSORTx. Results: Similar to observations in our cfDNA discovery cohort, H1 was found to be the more prevalent subtype in the external validation set comprising 56% of tumors, while 44% were classified as H2. Recurrence frequencies of genetic features were comparable to and significantly correlated with those from our plasma discovery cohort ( R S=0.59 [H1] and R S=0.63 [H2], P&amp;lt;0.001 each). Of note, when considering the whole genome space, the higher mutational burden of H1 tumors could be confirmed ( P&amp;lt;0.01), and this association was independent of the tumor EBV status. In agreement with the discovery cohort, the bimodal age distribution and increased EBV positivity of the H2 subtype could also be recapitulated (31% vs 6% EBV+, P&amp;lt;0.01). To explore transcriptional differences between H1/H2 subtypes, we took advantage of the plasma enrichment of HRS cell ctDNA and utilized EPIC-Seq to noninvasively infer expression of 1,676 targeted genes. Tracking signatures derived from scRNA-Sequencing in plasma samples, we found that both HRS cells and the cHL tumor microenvironment can be successfully profiled by EPIC-Seq. Strikingly, we found substantial enrichment of a cytokine response signature in H1 tumors, while T-cell activation was among the top upregulated signatures in H2 tumors ( Fig. A). Importantly, the T-cell signature found in H2 was accompanied by a higher abundance of T-cell clones as quantified by SABER in baseline plasma samples ( P&amp;lt;0.001, Fig. B). Notably, cfTCR fragment length profiles resembled the mutant ctDNA profiles, strongly suggesting a tumor origin of the TCR rearrangements detected in plasma. Lastly, immune cell deconvolution of bulk RNA-Seq specimens indicated a higher abundance of CD8+ T-cells in H2 tumors ( P&amp;lt;0.01), further confirming our prior observations. Conclusions: Collectively, these results serve to validate H1 and H2 as distinct cHL subtypes, to confirm the characteristic genotypes defining them, and recapitulate their distinctive associations with key clinical and pathological variables including age and EBV status. We further validate the subtypes using orthogonal methods revealing dominant cytokine driven signaling in H1. Conversely, H2 tumors, which largely lack B2M mutations, despite their lower mutational burden, are rather immunogenic triggering T-cell responses.