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The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells in classic Hodgkin lymphoma (cHL) limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Using this approach, we now report the whole-genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events leading to cHL. We identified alterations in driver genes not previously described in cHL, APOBEC mutational activity, and the presence of complex structural variants including chromothripsis. We found that high ploidy in cHL is often acquired through multiple, independent chromosomal gains events including whole-genome duplication. Evolutionary timing analyses revealed that structural variants enriched for RAG motifs, driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID-driven mutagenesis usually preceded large chromosomal gains. This study provides a temporal reconstruction of cHL pathogenesis. Significance: Previous studies in cHL were limited to coding sequences and therefore not able to comprehensively decipher the tumor complexity. Here, leveraging cHL whole-genome characterization, we identify driver events and reconstruct the tumor evolution, finding that structural variants, driver mutations, and AID mutagenesis precede chromosomal gains. This article is highlighted in the In This Issue feature, p. 171

CD19-directed chimeric antigen receptor (CAR-19) T cells are groundbreaking immunotherapies approved for use against large B-cell lymphomas. Although host inflammatory and tumor microenvironmental markers associate with efficacy and resistance, the tumor-intrinsic alterations underlying these phenomena remain undefined. CD19 mutations associate with resistance but are uncommon, and most patients with relapsed disease retain expression of the wild-type receptor, implicating other genomic mechanisms. We therefore leveraged the comprehensive resolution of whole-genome sequencing to assess 51 tumor samples from 49 patients with CAR-19–treated large B-cell lymphoma. We found that the pretreatment presence of complex structural variants, APOBEC mutational signatures, and genomic damage from reactive oxygen species predict CAR-19 resistance. In addition, the recurrent 3p21.31 chromosomal deletion containing the RHOA tumor suppressor was strongly enriched in patients for whom CAR T-cell therapy failed. Pretreatment reduced expression or monoallelic loss of CD19 did not affect responses, suggesting CAR-19 therapy success and resistance are related to multiple mechanisms. Our study showed that tumor-intrinsic genomic alterations are key among the complex interplay of factors that underlie CAR-19 efficacy and resistance for large B-cell lymphomas.

R code of our analysis clock like mutational signatures in Hodgkin lymphoma WGS and WES.

The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells in classic Hodgkin lymphoma (cHL) limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Using this approach, we now report the whole-genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events leading to cHL. We identified alterations in driver genes not previously described in cHL, APOBEC mutational activity, and the presence of complex structural variants including chromothripsis. We found that high ploidy in cHL is often acquired through multiple, independent chromosomal gains events including whole-genome duplication. Evolutionary timing analyses revealed that structural variants enriched for RAG motifs, driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID-driven mutagenesis usually preceded large chromosomal gains. This study provides a temporal reconstruction of cHL pathogenesis.Significance:Previous studies in cHL were limited to coding sequences and therefore not able to comprehensively decipher the tumor complexity. Here, leveraging cHL whole-genome characterization, we identify driver events and reconstruct the tumor evolution, finding that structural variants, driver mutations, and AID mutagenesis precede chromosomal gains.This article is highlighted in the In This Issue feature, p. 171

All supplementary figures S1-S17

R code of our analysis for driver mutation discovery in Hodgkin lymphoma WGS and WES.

Supplementary Tables S1-S20

Purpose:Duration of first remission is important for the survival of patients with multiple myeloma.Experimental Design:From the CoMMpass study (NCT01454297), 926 patients with newly diagnosed multiple myeloma, characterized by next-generation sequencing, were analyzed to evaluate those who experienced early progressive disease (PD; time to progression, TTP ≤18 months).Results:After a median follow-up of 39 months, early PD was detected in 191/926 (20.6%) patients, 228/926 (24.6%) patients had late PD (TTP >18 months), while 507/926 (54.8%) did not have PD at the current follow-up. Compared with patients with late PD, patients with early PD had a lower at least very good partial response rate (47% vs. 82%, P < 0.001) and more frequently acquired double refractoriness to immunomodulatory drugs (IMiD) and proteasome inhibitors (PI; 21% vs. 8%, P < 0.001). Patients with early PD were at higher risk of death compared with patients with late PD and no PD (HR, 3.65; 95% CI, 2.7–4.93; P < 0.001), showing a dismal median overall survival (32.8 months). In a multivariate logistic regression model, independent factors increasing the early PD risk were TP53 mutation (OR, 3.78, P < 0.001), high lactate dehydrogenase levels (OR, 3.15, P = 0.006), λ-chain translocation (OR, 2.25, P = 0.033), and IGLL5 mutation (OR, 2.15, P = 0.007). Carfilzomib-based induction (OR, 0.15, P = 0.014), autologous stem-cell transplantation (OR, 0.27, P < 0.001), and continuous therapy with PIs and IMiDs (OR, 0.34, P = 0.024) mitigated the risk of early PD.Conclusions:Early PD identifies a high-risk multiple myeloma population. Further research is needed to better identify baseline features predicting early PD and the optimal treatment approaches for patients at risk.

Supplementary Appendix: Additional methods. Carfilzomib-treated patients - Trial design; Table S1. List and classification method of the analyzed variables; Table S2. Induction treatment classification; Table S3. List of the 21 genes analyzed and mutation frequency; Table S4. Distribution of upfront treatment and ASCT in CT subgroups; Table S5. Distribution of variables in Early PD vs reference population; Figure S1. Multivariate logistic regression model evaluating risk factors associated with death within 24 months; Figure S2. Sub-analysis on patients with or without baseline del(17p) and/or TP53 mutation; Figure S3. TP53 and IGLL5 mutations at diagnosis and at first relapse in available longitudinal samples; Figure S4. Epanechnikov kernel-smoothed estimated hazard rates of progressive disease (PD) over time; Figure S5. Comparison of Seq-FISH and conventional FISH in a subgroup of patients enrolled in clinical trials and analyzed in the same centralized laboratory.

B cell maturation antigen (BCMA) target loss is considered to be a rare event that mediates multiple myeloma (MM) resistance to anti-BCMA chimeric antigen receptor T cell (CAR T) or bispecific T cell engager (TCE) therapies. Emerging data report that downregulation of G protein coupled receptor family C group 5 member D (GPRC5D) protein often occurs at relapse after anti-GPRC5D CAR T. To examine the tumor intrinsic factors that promote MM antigen escape, we performed combined bulk and single cell whole genome sequencing/ copy number variation analysis of 25 patients treated with anti-BCMA and/ or -GPRC5D CAR T/ TCE. In two cases, MM relapse post TCE/CAR T was driven by BCMA negative clones harboring focal biallelic deletions at the TNFRSF17 locus at relapse or by selective expansion of pre-existing subclones with biallelic TNFRSF17 loss. In another three cases of MM relapse, we identified non-truncating missense mutations or in-frame deletions in the extracellular domain of BCMA which negates the efficacies of anti-BCMA TCEs, despite detectable surface BCMA protein expression. With respect to GPRC5D, we report the first four cases of MM relapse with biallelic mutations of GPRC5D following anti-GPRC5D TCE, including two cases with convergent evolution where multiple subclones lost GPRC5D through different somatic events. Our data support that immunoselection of BCMA or GPRC5D negative or mutant clones post CAR T/ TCE therapies may be more prevalent than currently perceived. The engineering and selection of immunotherapies in MM should account for target antigen structural and extracellular domain mutations.

Patients treated with cytotoxic therapies, including autologous stem cell transplantation, are at risk for developing therapy-related myeloid neoplasms (tMN). Pre-leukemic clones (i.e., clonal hematopoiesis; CH) are detectable years before the development of these aggressive malignancies, though the genomic events leading to transformation and expansion are not well-defined. Here, leveraging distinctive chemotherapy-associated mutational signatures from whole-genome sequencing data and targeted sequencing of pre-chemotherapy samples, we reconstruct the evolutionary life-history of 39 therapy-related myeloid malignancies. A dichotomy is revealed, in which neoplasms with evidence of chemotherapy-induced mutagenesis from platinum and melphalan are hypermutated and enriched for complex structural variants (i.e., chromothripsis) while neoplasms with non-mutagenic chemotherapy exposures are genomically similar to de novo acute myeloid leukemia. Using chemotherapy-associated mutational signatures as temporal barcodes linked to a discrete clinical exposure in each patient's life, we estimate that several complex events and genomic drivers are acquired after chemotherapy is administered. For patients with prior multiple myeloma who were treated with high-dose melphalan and autologous stem cell transplantation, we demonstrate that tMN can develop from either a reinfused CH clone that escapes melphalan exposure and is selected following reinfusion, or from TP53-mutant CH that survives direct myeloablative conditioning and acquires melphalan-induced DNA-damage. Overall, we reveal a novel mode of tMN progression that is not reliant on direct mutagenesis or even exposure to chemotherapy. Conversely, for tMN that evolve under the influence of chemotherapy-induced mutagenesis, distinct chemotherapies not only select pre-existing CH, but also promote the acquisition of recurrent genomic drivers.

Whole genome sequencing (WGS) of newly diagnosed multiple myeloma patients (NDMM) has shown recurrent structural variant (SV) involvement in distinct regions of the genome (i.e. hotspots) and causing recurrent copy number alterations. Together with canonical immunoglobulin translocations, these SVs are recognized as “recurrent SVs”. More than half SVs were not involved in recurrent events. The significance of these “rare SVs” has not been previously examined. In this study, we utilize 752 WGS and 591 RNA-seq data from NDMM patients to determine the role of rare SVs in myeloma pathogenesis. 94% of patients harbored at least one rare SV event. Rare SVs showed an SV-class specific enrichment within genes and superenhancers associated with outlier gene expression. Furthermore, known myeloma driver genes recurrently impacted by point mutations were dysregulated by rare SVs. Overall, we demonstrate the association of rare SVs with aberrant gene expression supporting a driver role in myeloma pathogenesis.SIGNIFICANCECharacterization of multiple myeloma genome revealed that more than half structural variants are not involved in recurrent events. Here, we demonstrate that these rare SVs hold potential for myeloma pathogenesis through their gene expression impact. Rare SVs contribute to MM heterogeneity and have implications for development of individualized treatment.

Alterations in KRAS have been identified as the most recurring somatic variants in the multiple myeloma (MM) mutational landscape. Combining DNA and RNA sequencing, we studied 756 patients and observed KRAS as the most frequently mutated gene in patients at diagnosis; in addition, we demonstrated the persistence or de novo occurrence of the KRAS aberration at disease relapse. Small-molecule inhibitors targeting KRAS have been developed; however, they are selective for tumors carrying the KRASG12C mutation. Therefore, there is still a need to develop novel therapeutic approaches to target the KRAS mutational events found in other tumor types, including MM. We used AZD4785, a potent and selective antisense oligonucleotide that selectively targets and downregulates all KRAS isoforms, as a tool to dissect the functional sequelae secondary to KRAS silencing in MM within the context of the bone marrow niche and demonstrated its ability to significantly silence KRAS, leading to inhibition of MM tumor growth, both in vitro and in vivo, and confirming KRAS as a driver and therapeutic target in MM.

Mutational signatures have emerged as powerful biomarkers in cancer patients, with prognostic and therapeutic implications. Wider clinical utility requires access to reproducible algorithms, which allow characterization of mutational signatures in a given tumor sample. Here, we show how mutational signature fitting can be applied to hematological cancer genomes to identify biologically and clinically important mutational processes, highlighting the importance of careful interpretation in light of biological knowledge. Our newly released R package mmsig comes with a dynamic error-suppression procedure that improves specificity in important clinical and biological settings. In particular, mmsig allows accurate detection of mutational signatures with low abundance, such as those introduced by APOBEC cytidine deaminases. This is particularly important in the most recent mutational signature reference (COSMIC v3.1) where each signature is more clearly defined. Our mutational signature fitting algorithm mmsig is a robust tool that can be implemented immediately in the clinic., Rustad et al. present a software package for the R statistical environment for the accurately quantify of somatic mutational signatures in hematological malignancies

Background: Structural variants (SV) are known to play a critical role in the pathogenesis of multiple cancer types. Using whole genome sequencing (WGS), we recently characterized the SV landscape of 752 newly diagnosed multiple myeloma (MM) patients, identifying 68 SV hotspots and 152 recurrent copy number aberrations (CNA; Rustad et al. Blood Cancer Discovery 2020). Despite comprehensive annotation, more than half of SVs were not linked to any known MM genomic driver. The biological impact of these SV events, here defined as rare SV, occurring in 93% (702/752) of patients, is unknown. Methods: To study the biological impact of rare SVs, we interrogated WGS (n=752) and RNAseq (n=591) in the CoMMpass trial. Recurrent SVs identified by involvement in canonical Ig translocations, recurrent CNAs, or SV hotspots were excluded. All SVs within an event must not involve a recurrent region to be defined rare. To determine SV class-specific gene relationships, breakpoint enrichment was compared against a permuted background model for each SV class and gene expression direction, up to 1 Mb. Genes were considered affected if expression was above a gene specific outlier Z-score of +/- 2. Lastly, we modeled breakpoint density to the nearest MM superenhancer up to 10 MB, and compared to permuted background rates. Results: Of the total 8,942 SVs, 4,959 (55%) were identified as rare. 201 (34%) patients had at least 1 enriched rare SV event associated with gene expression outliers. Amongst over-expressed gene outliers, rare templated insertions and duplications were enriched within the gene body and up to 1 MB away. Rare inversions were enriched in genes 100kb and 1MB away, and rare translocations were associated with outliers 1 MB away. Amongst under-expressed gene outliers, rare complex SVs were enriched within the gene body, while deletion SVs were enriched in the gene body and up to 1 MB away. Rare duplications, translocations and templated insertions were enriched up to 1 MB of superenhancers. Rare templated insertions were significantly enriched against the background model (p < 0.001, Fisher Exact). Overall, 82% (104/126) of gene outliers affected by rare templated insertions were associated with superenhancers, (95 over-expressed, e.g. IRF6 and 9 under-expressed), 54% (130/237) by rare translocations, (105 overexpressed, e.g. FAM46A and 25 under-expressed), and 55% (96/172) by rare duplication events, (93 overexpressed, e.g. MAPK13, and 7 under-expressed). In addition, among the 853 outlier genes affected by enriched rare SVs, at least 15 are involved with B-cell development, suggesting a potential driver role in myeloma pathogenesis. Conclusion: In summary, leveraging WGS and RNA-seq of clinical samples, we demonstrate that rare SVs are frequently associated with aberrant gene expression, expanding our understanding of their potential role in heterogenous clinical response in patients diagnosed with MM. Citation Format: Monika Chojnacka, Benjamin Diamond, Bachisio Ziccheddu, Even Rustad, Kylee Maclachlan, Marios Papadimitriou, Eileen Boyle, Patrick Blaney, Saad Usmani, Gareth Morgan, Ola Landgren, Francesco Maura. Characterizing the landscape of rare structural variant events in newly diagnosed multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6067.

Patients treated with cytotoxic therapies, including autologous stem cell transplantation, are at risk for developing therapy-related myeloid neoplasms1, 2. Pre-leukemic clones (i.e., clonal hematopoiesis) are detectable years before the development of these aggressive malignancies3-5, though the genomic events leading to transformation and expansion are not well-defined. Here, leveraging distinctive chemotherapy-associated mutational signatures6-12 from whole-genome sequencing data and targeted sequencing of pre-chemotherapy samples, we reconstruct the evolutionary life-history of 39 therapy-related myeloid malignancies. A dichotomy is revealed, in which neoplasms with evidence of chemotherapy-induced mutagenesis from platinum and melphalan are relatively hypermutated and enriched for complex structural variants (i.e., chromothripsis), while neoplasms with alternative exposures bear a similar profile to de novo acute myeloid leukemia. Using chemotherapy-associated mutational signatures as a temporal barcode in each patient’s life, we estimate that several complex events and genomic drivers are acquired after chemotherapy exposure. In the case of treatment with high-dose melphalan and autologous stem cell transplantation, we demonstrate that the procedure allows clonal hematopoiesis to escape chemotherapy exposure entirely, and to be reinfused to expand to malignancy. This information reveals a novel mode of malignant progression for therapy-related malignancies that is not reliant on direct mutagenesis or even exposure to chemotherapy, itself, and prompts further investigation into leukemia-permissive effects of cytotoxic drugs.

The rarity of malignant Hodgkin and Reed Sternberg (HRS) cells within a classic Hodgkin lymphoma (cHL) biopsy limits the ability to study the genomics of cHL. To circumvent this, our group has previously optimized fluorescence-activated cell sorting to purify HRS cells. Here we leveraged this method to report the first whole genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events prior to the clinical diagnosis of cHL. We identified alterations in driver genes not previously described in cHL, a high activity of the APOBEC mutational signature, and the presence complex structural variants including chromothripsis. We found that the high ploidy observed in cHL is often acquired through multiple, independent large chromosomal gain events including whole genome duplication. The first of these likely occurs several years prior to the diagnosis of cHL, and the last gains typically occur very close to the time of diagnosis. Evolutionary timing analyses revealed that driver mutations in B2M, BCL7A, GNA13, and PTPN1, and the onset of AID driven mutagenesis usually preceded large chromosomal gains. The study provides the first temporal reconstruction of cHL pathogenesis and suggests a relatively long time course between the first pathogenic event and the clinical diagnosis.

Introduction: Anti-CD-19 chimeric antigen receptor-reprogrammed autologous T cells are breakthrough immunotherapies for heavily pretreated patients with aggressive B-cell lymphomas; however, across CAR-19 products, ~60% of patients do not achieve remission or relapse and unfortunately typically progress and rapidly die. Factors associated with impaired response to CAR-19 include inflammatory markers such as interferon signaling and clinical factors such as the need for bridging therapy and high pre-CAR-19 tumor burden, but cell-intrinsic driver of CAR-19 resistance remain largely undefined. Methods: To characterize the genomic mechanisms involved in diffuse large B cell lymphoma (DLBCL) resistance to CAR-19, we interrogated whole genome sequencing (WGS) from 28 relapsed/refractory (r/r) aggressive lymphoma patients treated with axicabtagene ciloleucel (axi-cel). The median coverage was 44.8X. To increase statistical power of analyses, we included also 50 newly diagnosed DLBCL patients from the Pan-Cancer Analysis of Whole Genomes (PCAWG). Results: As reported in other series, neither double hit cytogenetics nor MYC-BCL2 double expression associated with CAR-19 resistance, despite their negative predictive power for newly diagnosed DLBCL patients. Chapuy and LymphGen classification algorithms also demonstrated no prognostic significance. Among known mutated driver genes, only TP53 was significantly enriched in our cohort in comparison to the PCAWG cohort (p=0.002), but it did not predict poor CAR-19 outcome. Among other genes known to be involved in DLBCL pathogenesis, only mutations in NFKBIA or MYC, associated with worse PFS (p=0.04, p=0.025 respectively). Next, we identified 12 single base substitution (SBS) mutational signatures detected in our cohort of r/r lymphomas, four of which are caused by exposure to distinct chemotherapies (Landau et al., 2020, Nat Comm). The melphalan-related signature (SBS-MM1) was identified in 4 out 5 patients who received high dose melphalan followed by autologous stem cell transplant, and 75% of patients exposed to platinum had evidence of one of the three known platinum signatures. Across different SBS signatures, only presence of APOBEC (SBS2 and SBS13) associated with worse PFS with 4/5 patients progressing (p=0.03). We compared newly diagnosed and r/r DLBCL by GISTIC2.0 copy number variation (CNV) analysis, revealing three gene deletions significantly enriched in our r/r cohort: TP53, RHOA and RB1. Interestingly, the deletions involving RHOA and RB1 both independently predicted poor outcome (p=0.0007 and p=0.05 respectively) with 5/5 and 6/8 patients progressing respectively. The third, involving TP53 (46.4% of patients), had no prognostic impact but reflected the high-risk nature of the heavily pretreated tumors. WGS allows detailed identification of structural variants and complex events. Indeed, we found evidence of chromothripsis, a catastrophic event in which one or more chromosomes are shattered and aberrantly reassembles generating multiple aneuploidies, in 39.3% of r/r DLBCL. This strongly associated with poor CAR-19 outcome, with 9/11 affected cases experiencing early progression (p=0.041). Finally, reduced expression (n=3) or genomic alteration (n=3) of CD19 did not associate with poor outcome. We found one case, with durable response, containing a sub-clonal mutation in CD19 (L174V) at baseline, previously reported as associated with CAR-19 resistance. In line with recent evidence, these findings indicate that antigen-mediated tumor killing is not the only mechanism of tumor eradication, and CD19-independent resistance mechanisms predominate. Conclusions: Leveraging the high resolution of WGS, we observed that markers of genomic complexity (chromothripsis and APOBEC) and specific genomic alterations (RHOA and RB1 deletion) associate with resistance to CAR-19 immunotherapy for aggressive B-cell lymphomas. Fifteen out of sixteen patients (93.8%) who relapsed on CAR-19 contained at least one of the described genomic alterations. Recent data demonstrate that an immunosuppressed TME leads to CAR-19 failure in patients, and animal studies show activation of host T cells by CAR-T cells. Combining these findings with these genomics findings, successful CAR-19 therapy must overcome the immune-exhausted tumor microenvironment to mobilize the host immune system and eliminate the tumor. Figure 1 Figure 1. Disclosures Jain: Takeda: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Kite/Gilead: Consultancy, Honoraria. Faramand: Novartis: Research Funding; Kite/Gilead: Research Funding. Landgren: Amgen: Research Funding; Janssen: Research Funding; Amgen: Honoraria; Celgene: Research Funding; Janssen: Other: IDMC; Janssen: Honoraria; Takeda: Other: IDMC; GSK: Honoraria. Locke: Iovance Biotherapeutics: Consultancy, Other: Scientific Advisory Role; Gerson Lehrman Group: Consultancy; Calibr: Consultancy, Other: Scientific Advisory Role; Janssen: Consultancy, Other: Scientific Advisory Role; Umoja: Consultancy, Other; Novartis: Consultancy, Other, Research Funding; Bluebird Bio: Consultancy, Other: Scientific Advisory Role; Allogene Therapeutics: Consultancy, Other: Scientific Advisory Role, Research Funding; Kite, a Gilead Company: Consultancy, Other: Scientific Advisory Role, Research Funding; Takeda: Consultancy, Other; Emerging Therapy Solutions: Consultancy; EcoR1: Consultancy; Cowen: Consultancy; Wugen: Consultancy, Other; Legend Biotech: Consultancy, Other; GammaDelta Therapeutics: Consultancy, Other: Scientific Advisory Role; Cellular Biomedicine Group: Consultancy, Other: Scientific Advisory Role; BMS/Celgene: Consultancy, Other: Scientific Advisory Role; Amgen: Consultancy, Other: Scientific Advisory Role; Moffitt Cancer Center: Patents & Royalties: field of cellular immunotherapy. Maura: Medscape: Consultancy, Honoraria; OncLive: Honoraria. Davila: Precigen: Research Funding.

Patients treated with chemotherapy (CT) and/or autologous stem-cell transplantation (ASCT) are at risk for therapy-related myeloid neoplasms (tMN). Certain cytotoxic agents introduce mutations within distinct trinucleotide contexts resulting in a unique barcode for each exposed cell. We leveraged mutational signatures to investigate the role of CT in the genomic landscape of tMN with respect to antecedent clonal hematopoiesis (CH). We analyzed 32 tMN and 2 tALL from 33 patients and interrogated for copy number abnormalities (CNA), structural variants (SV), single nucleotide variants (SNV), and mutational signatures. For 7 patients with tMN post-melphalan/ASCT, we investigated antecedent CH using targeted sequencing on pre-melphalan samples, including autograft products. CH variants that became clonal in tumor were seen in 5/7 pre-melphalan/ASCT samples (TP53, RUNX1, NCOR1, NF1, CREBBP, DNMT3A, and PPM1D). Complex SV were seen in 7 tMNs; including chromothripsis in 6 (19.4%). In 4 cases, chromothripsis involved chromosome 19 with hyper-amplification of the SMARCA4 locus (≥5 copies). Mutational signature analysis revealed 6 known single base substitution (SBS) signatures in tMN including melphalan (SBS-MM1) and platinum signatures (SBS31, SBS35, and E-SBS37). TMNs with CT signatures had higher mutation burden than those without (p = 0.004). 17 patients with exposure to agents other than melphalan/platinum did not have increased mutational burden with respect to de novo AML (TCGA; NEJM, 2013). All patients with prior platinum exposure (including tALL, n=9) had platinum SBS signatures while only 2 of 7 patients with prior melphalan/ASCT had a melphalan signature (SBS-MM1). Detection of CT signatures in bulk sequencing relies on one cell, with its barcode of mutations, to expand to clonal dominance. Given pre-existent CH, including in 3/3 autograft products, absence of a CT signature despite melphalan exposure implies progression by a clone that escaped CT exposure with stem-cell collection and reinfusion. Conversely, all platinum-exposed tAML had signature evidence of exposure confirming existence of CH prior to exposure and supporting post-CT single-cell expansion. TMNs from 3 patients exposed to sequential platinum and melphalan/ASCT had platinum but not melphalan signatures confirming single-cell expansion of the pre-tMN CH clone post-platinum but with escape from exposure to melphalan via leukapheresis. Chromothripsis events bore only non-duplicated CT-induced mutations, indicative of acquisition prior to, and not directly caused by, CT exposure. These disparities suggest that ASCT provides a mechanism for CH clones to escape CT and re-engraft with transplant. Coupled with driver events accrued prior to CT, this suggest that CT-induced mutagenesis may be less important than other factors, such as CT-induced immunosuppression, in the expansion of pre-TMN CH clones. Citation Format: Benjamin Diamond, Bachisio Ziccheddu, Eileen M. Boyle, Kylee Maclachlan, Justin Taylor, Justin M. Watts, Sydney X. Lu, David G. Coffey, Niccolo Bolli, Elli Papaemmanuil, Kelly Bolton, Jae H. Park, Heather Landau, Karuna Ganesh, Mikkael A. Sekeres, Stephen Nimer, David J. Chung, Caleb H. Ho, Mikhail Roshal, Alexander Lesokhin, Gareth Morgan, Ola Landgren, Francesco Maura. Chemotherapy-related mutational signatures reveal the origins of therapy-related myeloid neoplasms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5747.

Purpose: Multiple myeloma is a biologically heterogenous plasma-cell disorder. In this study, we aimed at dissecting the functional impact on transcriptome of gene mutations, copy-number abnormalities (CNA), and chromosomal rearrangements (CR). Moreover, we applied a geno-transcriptomic approach to identify specific biomarkers for personalized treatments. Experimental Design: We analyzed 514 newly diagnosed patients from the IA12 release of the CoMMpass study, accounting for mutations in multiple myeloma driver genes, structural variants, copy-number segments, and raw-transcript counts. We performed an in silico drug sensitivity screen (DSS), interrogating the Cancer Dependency Map (DepMap) dataset after anchoring cell lines to primary tumor samples using the Celligner algorithm. Results: Immunoglobulin translocations, hyperdiploidy and chr(1q)gain/amps were associated with the highest number of deregulated genes. Other CNAs and specific gene mutations had a lower but very distinct impact affecting specific pathways. Many recurrent genes showed a hotspot (HS)-specific effect. The clinical relevance of double-hit multiple myeloma found strong biological bases in our analysis. Biallelic deletions of tumor suppressors and chr(1q)-amplifications showed the greatest impact on gene expression, deregulating pathways related to cell cycle, proliferation, and expression of immunotherapy targets. Moreover, our in silico DSS showed that not only t(11;14) but also chr(1q)gain/amps and CYLD inactivation predicted differential expression of transcripts of the BCL2 axis and response to venetoclax. Conclusions: The multiple myeloma genomic architecture and transcriptome have a strict connection, led by CNAs and CRs. Gene mutations impacted especially with HS-mutations of oncogenes and biallelic tumor suppressor gene inactivation. Finally, a comprehensive geno-transcriptomic analysis allows the identification of specific deregulated pathways and candidate biomarkers for personalized treatments in multiple myeloma.

Chromothripsis is detectable in 20–30% of newly diagnosed multiple myeloma (NDMM) patients and is emerging as a new independent adverse prognostic factor. In this study we interrogate 752 NDMM patients using whole genome sequencing (WGS) to investigate the relationship of copy number (CN) signatures to chromothripsis and show they are highly associated. CN signatures are highly predictive of the presence of chromothripsis (AUC = 0.90) and can be used identify its adverse prognostic impact. The ability of CN signatures to predict the presence of chromothripsis is confirmed in a validation series of WGS comprised of 235 hematological cancers (AUC = 0.97) and an independent series of 34 NDMM (AUC = 0.87). We show that CN signatures can also be derived from whole exome data (WES) and using 677 cases from the same series of NDMM, we are able to predict both the presence of chromothripsis (AUC = 0.82) and its adverse prognostic impact. CN signatures constitute a flexible tool to identify the presence of chromothripsis and is applicable to WES and WGS data., Chromothripsis is associated with unfavourable outcomes in multiple myeloma (MM), but its detection usually requires whole genome sequencing. Here the authors develop an approach to detect chromothripsis in MM based on copy-number signatures that also works with whole exome sequencing data.

Chromothripsis is detectable in 20-30% of newly diagnosed multiple myeloma (NDMM) patients and is emerging as a new independent adverse prognostic factor. In this study, we interrogate 752 NDMM patients using whole genome sequencing (WGS) to study the relationship of copy number (CN) signatures to chromothripsis and show they are highly associated. CN signatures are highly predictive of the presence of chromothripsis (AUC=0.90) and can be used to identify its adverse prognostic impact. The ability of CN signatures to predict the presence of chromothripsis was confirmed in a validation series of WGS comprised of 235 hematological cancers (AUC=0.97) and an independent series of 34 NDMM (AUC=0.87). We show that CN signatures can also be derived from whole exome data (WES) and using 677 cases from the same series of NDMM, we were able to predict both the presence of chromothripsis (AUC=0.82) and its adverse prognostic impact. CN signatures constitute a flexible tool to identify the presence of chromothripsis and is applicable to WES and WGS data.

The knowledge of cancer origin and the subsequent tracking of disease evolution represent unmet needs that will soon be within clinical reach. This will provide the opportunity to improve patient's stratification and to personalize treatments based on cancer biology along its life history. In this review, we focus on the molecular pathogenesis of multiple myeloma (MM), a hematologic malignancy with a well-known multi-stage disease course, where such approach can sooner translate into a clinical benefit. We describe novel insights into modes and timing of disease initiation. We dissect the biology of the preclinical and pre-malignant phases, elucidating how knowledge of the genomics of the disease and the composition of the microenvironment allow stratification of patients based on risk of disease progression. Then, we explore cell-intrinsic and cell-extrinsic drivers of MM evolution to symptomatic disease. Finally, we discuss how this may relate to the development of refractory disease after treatment. By integrating an evolutionary view of myeloma biology with the recent acquisitions on its clonal heterogeneity, we envision a way to drive the clinical management of the disease based on its detailed biological features more than surrogates of disease burden.

Genomic analysis could contribute to a better understanding of the biological determinants of the evolution of multiple myeloma (MM) precursor disease and an improved definition of high-risk patients. To assess the feasibility and value of next-generation sequencing approaches in an asymptomatic setting, we performed a targeted gene mutation analysis and a genome-wide assessment of copy number alterations (CNAs) by ultra-low-pass whole genome sequencing (ULP-WGS) in six patients with monoclonal gammopathy of undetermined significance and 25 patients with smoldering MM (SMM). Our comprehensive genomic characterization highlighted heterogeneous but substantial values of the tumor fraction, especially in SMM, a rather high degree of genomic complexity, in terms of both mutations and CNAs, and inter-patient variability, a higher incidence of gene mutations and CNAs in SMM, confirming ongoing evolution, intraclonal heterogeneity, and instances of convergent evolution. ULP-WGS of these patients proved effective in revealing the marked genome-wide level of their CNAs, most of which are not routinely investigated. Finally, the analysis of our small SMM cohort suggested that chr(8p) deletions, the DNA tumor fraction, and the number of alterations may have clinical relevance in the progression to overt MM. Although validation in larger series is mandatory, these findings highlight the promising impact of genomic approaches in the clinical management of SMM.

In multiple myeloma, novel treatments with proteasome inhibitors (PIs) and immunomodulatory agents (IMiDs) have prolonged survival but the disease remains incurable. At relapse, next-generation sequencing has shown occasional mutations of drug targets but has failed to identify unifying features that underlie chemotherapy resistance. We studied 42 patients refractory to both PIs and IMiDs. Whole-exome sequencing was performed in 40 patients, and RNA sequencing (RNA-seq) was performed in 27. We found more mutations than were reported at diagnosis and more subclonal mutations, which implies ongoing evolution of the genome of myeloma cells during treatment. The mutational landscape was different from that described in published studies on samples taken at diagnosis. The TP53 pathway was the most frequently inactivated (in 45% of patients). Conversely, point mutations of genes associated with resistance to IMiDs were rare and were always subclonal. Refractory patients were uniquely characterized by having a mutational signature linked to exposure to alkylating agents, whose role in chemotherapy resistance and disease progression remains to be elucidated. RNA-seq analysis showed that treatment or mutations had no influence on clustering, which was instead influenced by karyotypic events. We describe a cluster with both amp(1q) and del(13) characterized by CCND2 upregulation and also overexpression of MCL1, which represents a novel target for experimental treatments. Overall, high-risk features were found in 65% of patients. However, only amp(1q) predicted survival. Gene mutations of IMiD and PI targets are not a preferred mode of drug resistance in myeloma. Chemotherapy resistance of the bulk tumor population is likely attained through differential, yet converging evolution of subclones that are overall variable from patient to patient and within the same patient.

Purpose: Duration of first remission is important for the survival of patients with multiple myeloma. Experimental Design: From the CoMMpass study (NCT01454297), 926 patients with newly diagnosed multiple myeloma, characterized by next-generation sequencing, were analyzed to evaluate those who experienced early progressive disease (PD; time to progression, TTP ≤18 months). Results: After a median follow-up of 39 months, early PD was detected in 191/926 (20.6%) patients, 228/926 (24.6%) patients had late PD (TTP >18 months), while 507/926 (54.8%) did not have PD at the current follow-up. Compared with patients with late PD, patients with early PD had a lower at least very good partial response rate (47% vs. 82%, P < 0.001) and more frequently acquired double refractoriness to immunomodulatory drugs (IMiD) and proteasome inhibitors (PI; 21% vs. 8%, P < 0.001). Patients with early PD were at higher risk of death compared with patients with late PD and no PD (HR, 3.65; 95% CI, 2.7–4.93; P < 0.001), showing a dismal median overall survival (32.8 months). In a multivariate logistic regression model, independent factors increasing the early PD risk were TP53 mutation (OR, 3.78, P < 0.001), high lactate dehydrogenase levels (OR, 3.15, P = 0.006), λ-chain translocation (OR, 2.25, P = 0.033), and IGLL5 mutation (OR, 2.15, P = 0.007). Carfilzomib-based induction (OR, 0.15, P = 0.014), autologous stem-cell transplantation (OR, 0.27, P < 0.001), and continuous therapy with PIs and IMiDs (OR, 0.34, P = 0.024) mitigated the risk of early PD. Conclusions: Early PD identifies a high-risk multiple myeloma population. Further research is needed to better identify baseline features predicting early PD and the optimal treatment approaches for patients at risk.

The genomic landscape of Waldenström Macroglobulinemia (WM) is characterized by recurrent somatic mutations in MYD88, with a lower incidence of mutations affecting CXCR4, ARID1A, CD79B and the NFKB signaling pathway (Hunter et. al. Blood 2014). We aimed to characterize the relationship between single base substitutions (SBS), mutational signatures, copy number aberrations (CNA) and structural variants (SV) in WM. We performed whole genome sequencing (WGS) on 14 primary samples from WM patients at various clinical stages, including IgM monoclonal gammopathy (n=1), smoldering (n=5), newly diagnosed (n=7) and relapsed WM (n=1). We identified a median of 2806 clonal SBS per sample (IQR 1870-3079), and 12/14 (85%) samples harbored MYD88 mutations. To investigate which mutational processes are involved in shaping the genomic landscape of WM we performed a mutational signature analysis. Four previously reported SBS signatures were detected: SBS1 and SBS5 (aging), SBS9 (germinal center; GC) and SBS8, with the contribution of age-related signatures SBS1/SBS5 being directly correlated with age at presentation (R 2=0.44, p=0.014). The GC signature SBS9 demonstrated sustained GC activity, as evidenced by the same proportion of mutations attributable to SBS9 at both the clonal and subclonal level (24%). At the immunoglobulin loci, we observed evidence of clustered SBS84 (AID), reflecting somatic hypermutation, with SBS84 accounting for 30% of signature contribution from subclonal mutations. Overall, these data suggest that, similarly to MM and other hematological malignancies, the interaction between WM and the GC is sustained over time. We have previously demonstrated that SV and complex events are critical in the pathogenesis and clinical outcomes of multiple myeloma. In contrast, in this WM WGS cohort, we found a low prevalence of complex SV, with no chromothripsis detected, and a single chromoplexy event found in 3 patients (21%), all of whom had progressed to symptomatic WM. To explore WM CNA features in a larger cohort, we examined the WGS data together with 38 MYD88-mutated WM samples for which targeted sequencing was available (MSK-IMPACT-Heme 400 gene panel). In this combined dataset (n=52), GISTIC analysis identified significantly deleted regions at 6q16.1, 7q34, 17p13.1 (TP53) and 21q22.2, along with significant amplification at 6p22.1 (HLA-A). To better characterize the HLA loci using the loss of heterozygosity in human leukocyte antigen (LOHHLA) tool (McGranahan et. al. Cell 2017) we found the presence of HLA-specific loss of heterozygosity in 1 sample, while 4 samples had HLA CN >2.5 (all from patients who progressed to symptomatic WM). CNA analysis demonstrated that while some samples harbored typical CNA features, others had minimal changes, with MGUS / smoldering WM samples having less CNA compared with those who progressed to symptomatic WM. The 2 MYD88 wild type WGS contained a clonal gain affecting chromosome 12, which is typically an early event in chronic lymphocytic leukemia. Molecular time analysis (the corrected ratio between duplicated and non-duplicated clonal mutations within large chromosomal gains [Maura et al. Nat Comm 2019]) demonstrated that these 2 chromosomal gain events occurred early in cancer development (relative timing 0.5) and tended to be subclonal. This data suggests that, while MYD88-mutations are central to WM clone establishment and can be observed in precursor disease, CNA may contribute to later phases and disease progression. In summary, WGS in WM allows the demonstration that germinal center activity is sustained over time. CNA in WM are not random in distribution, with specific loci being significantly amplified or deleted, and a potential role for HLA CNA. In contrast to MYD88 mutations, which are carried by stable precursor patients, the subclonal status and late molecular time of most CNA changes suggest a late role in cancer progression. Disclosures Kastritis: Pfizer: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Amgen: Consultancy, Honoraria, Research Funding. Diamond: Sanofi: Honoraria; Medscape: Honoraria. Kazandjian: Arcellx: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees. Papaemmanuil: Isabl Technologies: Divested equity in a private or publicly-traded company in the past 24 months; Kyowa Hakko Kirin Pharma: Consultancy. Dogan: Roche: Consultancy, Research Funding; Seattle Genetics: Consultancy; EUSA Pharma: Consultancy; Peer View: Honoraria; Takeda: Consultancy, Research Funding; Physicians' Education Resource: Honoraria. Lesokhin: Trillium Therapeutics: Consultancy; Serametrix, Inc: Patents & Royalties; Genetech: Research Funding; Iteos: Consultancy; bristol myers squibb: Research Funding; Behringer Ingelheim: Honoraria; pfizer: Consultancy, Research Funding; Janssen: Honoraria, Research Funding. Landgren: Janssen: Other: IDMC; Janssen: Honoraria; Celgene: Research Funding; Amgen: Honoraria; Janssen: Research Funding; Amgen: Research Funding; Takeda: Other: IDMC; GSK: Honoraria. Palomba: Rheos: Honoraria; Pluto: Honoraria; Lygenesis: Honoraria; Ceramedix: Honoraria; Seres: Honoraria, Other: Stock, Patents & Royalties, Research Funding; Nektar: Honoraria; PCYC: Consultancy; Wolters Kluwer: Patents & Royalties; Notch: Honoraria, Other: Stock; Priothera: Honoraria; Kite: Consultancy; Novartis: Consultancy; Magenta: Honoraria; WindMIL: Honoraria; BeiGene: Consultancy; Juno: Patents & Royalties. Maura: OncLive: Honoraria; Medscape: Consultancy, Honoraria. Dimopoulos: Amgen: Honoraria; BMS: Honoraria; Janssen: Honoraria; Takeda: Honoraria; BeiGene: Honoraria.

Introduction: Treatment combinations involving CD38 targeted monoclonal antibodies have significantly prolonged the median duration and depth of response in myeloma (MM), reflected in minimal residual disease-negativity (MRD-) rates of over 70% in newly diagnosed patients (Landgren et al. JAMA Onc 2021). Key to improving our understanding of treatment failures is the combined use of single cell analysis of the microenvironment with genome wide assessment of tumor genetics to decipher the mechanisms of disease resistance. Methods: We isolated malignant plasma cells from bone marrow (BM) samples using CD138+magnetic or flow (CD38, CD138, and CD45) sorting from 60 newly diagnosed MM patients treated with KRd with daratumumab (D-KRd n=46; NCT03290950) and without daratumumab combination therapy (KRd, n=14; NCT01402284). Fifty-five baseline samples underwent whole genome sequencing (WGS), median coverage of 80x using somatic DNA as a normal comparator. The BM cellular content of 22 patients (44 samples-5 failed) treated with D-KRd (10 MRD+ and 12 MRD-) underwent 5'single cell RNA-sequencing with an additional capture of the TCR and surface protein markers (CITEseq) to interrogate the single cell composition of the immune microenvironment at baseline (T1, n=20) and at the end of induction (T2, n=19). Paired (T1/T2) single-cell data were obtained in 17 patients and paired WGS and single cell data (T1) were available in 15 patients. MRD-, sustained MRD- (defined as two MRD- results, the first at the end of the induction (T2) and the subsequent at the first year of follow-up (T3)) and progression/loss of MRD- were used as clinical endpoints for this study. Results: After a median follow up of 29 months, 36 (54%) patients achieved MRD-; 34 (51%) had sustained MRD- >1 year after completion of combination therapy. Overall, 10 (15%) patients had clinical progression and two conversions from MRD- to MRD+. A comprehensive catalogue of MM-genomic events associated with these three clinical endpoints was defined. Deletion (del) 13, biallelic loss CYLD, del XBP1, del 20q13.12 (CD40), and 8q gains were associated with MRD+ and failure to achieve sustained MRD-. Presence of del RPL5 and multiple chromothripsis events significantly correlated with early progression and loss of MRD-. Interestingly, structural variants (SV) involving IKFZ3 were seen in all three negative clinical endpoints (p We interrogated the BM microenvironment at baseline and correlated its composition with the tumor genomic architecture. Across 15 evaluable patients, del XBP1 were associated with fewer memory B-cells (p=0.03), naïve B-cell (p=0.01) and dendritic cells (p=0.03) compared to the wild type. Also, low dendritic cell at baseline cases were observed in patients with del 20q13.12 (CD40) (p=0.03). Interestingly, low level of plasmacytoid dendritic cells at baseline was associated with failure to achieve MRD- and sustained MRD-. Patients with 6p24 amplification showed a reduced number of CD8 effectors 1 and 2 (p When comparing baseline (T1) and end of induction (T2), significant differences were seen between sustained MRD+ and MRD-. We identified significantly depleted NK, and naïve and memory B-cell after D-KRd MRD- patients had significantly more CD14+ monocytes both at T1 and T2 than their MRD+ counterparts (Fig. 1). Differential expression suggests that inflammatory response genes including IL1B are upregulated in the absence of sustained MRD- whereas genes implicated in IL2, IL6, and IFNα response as well as adipocyte differentiation are associated with sustained MRD response. Conclusion: We show, for the first time, evidence of complex interplay between MM tumor genetics and the microenvironment in the context of D-KRd treated patients. Our results highlight the importance of genomic-based mechanisms in the persistence of disease (IKZF3, XBP1) as well as heterogeneity in the composition of the BM microenvironment, with the monocytes pointing towards the importance of inflammation. Figure 1 Figure 1. Disclosures Maura: OncLive: Honoraria; Medscape: Consultancy, Honoraria. Hassoun: Celgene, Takeda, Janssen: Research Funding. Mailankody: Jansen Oncology: Research Funding; Allogene Therapeutics: Research Funding; Bristol Myers Squibb/Juno: Research Funding; Legend Biotech: Consultancy; Takeda Oncology: Research Funding; Fate Therapeutics: Research Funding; Physician Education Resource: Honoraria; Plexus Communications: Honoraria; Evicore: Consultancy. Hultcrantz: Intellisphere LLC: Consultancy; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees, Research Funding; Curio Science LLC: Consultancy; Amgen: Research Funding; Daiichi Sankyo: Research Funding. Scordo: Omeros Corporation: Consultancy; i3 Health: Other: Speaker; Kite - A Gilead Company: Membership on an entity's Board of Directors or advisory committees; Angiocrine Bioscience: Consultancy, Research Funding; McKinsey & Company: Consultancy. Kazandjian: Arcellx: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees. Shah: Janssen Pharmaceutica: Research Funding; Amgen: Research Funding. Landau: Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Genzyme: Honoraria. Giralt: SANOFI: Membership on an entity's Board of Directors or advisory committees; PFIZER: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; JAZZ: Membership on an entity's Board of Directors or advisory committees; JANSENN: Membership on an entity's Board of Directors or advisory committees; AMGEN: Membership on an entity's Board of Directors or advisory committees; Actinnum: Membership on an entity's Board of Directors or advisory committees; CELGENE: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Dogan: Physicians' Education Resource: Honoraria; Seattle Genetics: Consultancy; EUSA Pharma: Consultancy; Roche: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Peer View: Honoraria. Lesokhin: Behringer Ingelheim: Honoraria; pfizer: Consultancy, Research Funding; Janssen: Honoraria, Research Funding; Iteos: Consultancy; Genetech: Research Funding; bristol myers squibb: Research Funding; Trillium Therapeutics: Consultancy; Serametrix, Inc: Patents & Royalties. Davies: Janssen: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Roche: Consultancy, Honoraria. Korde: Amgen: Research Funding; Medimmune: Membership on an entity's Board of Directors or advisory committees. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees. Landgren: Janssen: Other: IDMC; Celgene: Research Funding; Amgen: Honoraria; Janssen: Research Funding; Janssen: Honoraria; Amgen: Research Funding; Takeda: Other: IDMC; GSK: Honoraria.

Background: Patients treated with cytotoxic chemotherapies and/or autologous stem-cell transplantation (ASCT) are at risk for therapy-related myeloid neoplasms (tMN). As these agents yield increased mutation burden in relapsed malignancies and leave evidence of exposure via mutational signatures, we studied the genomic and temporal relationship between chemo exposure and progression of clonal hematopoiesis (CH) to tMN. Methods: We analyzed 32 tMN whole genomes (WG) from 31 patients [27 acute myeloid leukemias (AML), 4 myelodysplastic syndromes]. For 7 patients with tMN post-high-dose melphalan/ASCT, we investigated the presence of antecedent CH using targeted sequencing (MSK-IMPACT; Bolton et al. Nat Gen 2020) on pre-melphalan blood mononuclear cells, granulocytes, or CD34+ apheresis samples. Results: TMN was diagnosed a median of 4.2 years (IQR, 2.6-6.6) following primary treatment. When compared to data from 200 de novo AML from TCGA (NEJM, 2013), tMNs had fewer mutations in FLT3 (9.7% v 28.0%; p = 0.028) and NPM1 (3.2% v 27.0%; p = 0.003). TP53 loss was enriched in tMNs (25.8% v 10.5%; p = 0.035 ). Mutational signature analysis revealed 5 known single base substitution (SBS) signatures in tMN: the hematopoietic stem-cell (SBS-HSC), aging (SBS1), melphalan (SBS-MM1), and platinum signatures (E-SBS1, E-SBS20) (Rustad et al. Nat Comm 2020, Pich et al. Nat Gen 2019). Complex structural variants (SV), defined as ≥3 breakpoint pairs involved in simultaneous copy number changes (Rustad et al. Blood Can Disc 2020), were observed in 7 tMNs; including chromothripsis in 6 tumors (19.4%), chromoplexy in 2 (6.5%), templated insertion in 1 (3.2%), and unspecified complex SV in 2 (6.5%). Chromothripsis has not been previously reported in de novo AML and, in 4 cases, involved chromosome 19 with hyper-amplification of the SMARCA4 locus (≥5 copies). CH variants that became clonal in tumor were seen in 5/7 pre-melphalan/ASCT samples and included mutations in TP53, RUNX1, NCOR1, NF1, CREBBP, DNMT3A, and PPM1D. Chemotherapy introduces hundreds of mutations, leaving each exposed cell with a unique catalogue (i.e., barcode). In fact, TMNs with evidence of chemo signatures had a higher mutation burden (median 1574 single nucleotide variants) than those without (median 938; p = 0.004). Detection of chemo signatures in bulk genome sequencing relies on one cell, with its catalogue of mutations, to expand to clonal dominance (Fig 1a, Landau et al. Nat Comm 2020). Given the long latency between exposure and tMN diagnosis, this single-cell expansion model was expected for all samples exposed to melphalan or platinum-based regimens (i.e., agents with a measurable signature). Strikingly, all patients with pre-tMN platinum exposure (n=7) had evidence of platinum SBS signatures whereas only 2 of 7 patients with prior melphalan/ASCT had a melphalan signature (SBS-MM1). As all platinum-exposed tMN had mutational evidence of exposure, a CH clone must have existed prior to exposure, supporting a single-cell expansion model. Absence of a chemo signature for 5/7 post-melphalan/ASCT tumors despite exposure implies tumor progression driven either by multiple clones in parallel (Fig 1b) or by an unexposed clone. As latency largely excludes the former, this suggests pre-tMN CH clones were re-infused during SCT, thus avoiding chemo exposure (Fig 1c). This is supported by two lines of evidence: 1) tMNs from 2 patients exposed to sequential platinum and melphalan/ASCT had platinum but not melphalan signatures confirming single-cell expansion of the pre-tMN CH clone post-platinum but with escape from exposure to melphalan in the ASCT (Fig 1d); 2) targeted sequencing of pre-tMN samples from melphalan/ASCT patients identified tMN genomic mutations at the CH level in 5/7 cases, including in all 3 tested apheresis samples - one of which (TP53) expanded to dominance without a melphalan signature. Conclusion: WG sequencing identified novel features of tMN revealing the key driver role of complex SV. Mutational signature analyses and targeted sequencing of pre-tMN samples can increase our understanding of tMN pathogenesis and demonstrate that tMNs arising post-ASCT are often driven by CH clones that re-engraft after escaping melphalan exposure. This mode of expansion suggests that a permissive, immunosuppressed, post-transplant environment might play a more important role than chemotherapy-induced mutagenesis in tMN pathogenesis. Figure 1 Figure 1. Disclosures Diamond: Sanofi: Honoraria; Medscape: Honoraria. Watts: Rafael Pharmaceuticals: Consultancy; Genentech: Consultancy; Bristol Myers Squibb: Consultancy; Takeda: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy; Aptevo Therapeutices: Research Funding. Kazandjian: Arcellx: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bradley: AbbVie: Consultancy, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Bolli: Amgen: Honoraria; Takeda: Honoraria; Janssen: Consultancy, Honoraria; Celgene/BMS: Consultancy, Honoraria. Papaemmanuil: Isabl Technologies: Divested equity in a private or publicly-traded company in the past 24 months; Kyowa Hakko Kirin Pharma: Consultancy. Scordo: Kite - A Gilead Company: Membership on an entity's Board of Directors or advisory committees; i3 Health: Other: Speaker; Omeros Corporation: Consultancy; Angiocrine Bioscience: Consultancy, Research Funding; McKinsey & Company: Consultancy. Lahoud: MorphoSys: Membership on an entity's Board of Directors or advisory committees. Stein: Jazz Pharmaceuticals: Consultancy; Foghorn Therapeutics: Consultancy; Blueprint Medicines: Consultancy; Gilead Sciences, Inc.: Consultancy; Abbvie: Consultancy; Janssen Pharmaceuticals: Consultancy; Genentech: Consultancy; Celgene: Consultancy; Bristol Myers Squibb: Consultancy; Agios Pharmaceuticals, Inc: Consultancy; Novartis: Consultancy; Astellas: Consultancy; Syndax Pharmaceuticals: Consultancy; PinotBio: Consultancy; Daiichi Sankyo: Consultancy; Syros Pharmaceuticals, Inc.: Consultancy. Sauter: Precision Biosciences: Consultancy; Kite/Gilead: Consultancy; Bristol-Myers Squibb: Research Funding; GSK: Consultancy; Gamida Cell: Consultancy; Celgene: Consultancy, Research Funding; Genmab: Consultancy; Novartis: Consultancy; Spectrum Pharmaceuticals: Consultancy; Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding. Hassoun: Celgene, Takeda, Janssen: Research Funding. Mailankody: Bristol Myers Squibb/Juno: Research Funding; Physician Education Resource: Honoraria; Plexus Communications: Honoraria; Takeda Oncology: Research Funding; Jansen Oncology: Research Funding; Fate Therapeutics: Research Funding; Allogene Therapeutics: Research Funding; Legend Biotech: Consultancy; Evicore: Consultancy. Korde: Medimmune: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding. Hultcrantz: Daiichi Sankyo: Research Funding; Intellisphere LLC: Consultancy; Curio Science LLC: Consultancy; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Research Funding. Shah: Bristol Myers Squibb: Research Funding; Janssen: Research Funding. Shah: Janssen Pharmaceutica: Research Funding; Amgen: Research Funding. Park: Servier: Consultancy; Affyimmune: Consultancy; Autolus: Consultancy; Minerva: Consultancy; PrecisionBio: Consultancy; BMS: Consultancy; Novartis: Consultancy; Kura Oncology: Consultancy; Curocel: Consultancy; Artiva: Consultancy; Innate Pharma: Consultancy; Intellia: Consultancy; Amgen: Consultancy; Kite Pharma: Consultancy. Landau: Genzyme: Honoraria; Takeda, Janssen, Caelum Biosciences, Celgene, Pfizer, Genzyme: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding. Sekeres: BMS: Membership on an entity's Board of Directors or advisory committees; Takeda/Millenium: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Ho: Blueprint Medicine: Membership on an entity's Board of Directors or advisory committees. Roshal: Celgene: Other: Provision of services; Auron Therapeutics: Other: Ownership / Equity interests; Provision of services; Physicians' Education Resource: Other: Provision of services. Lesokhin: pfizer: Consultancy, Research Funding; Janssen: Honoraria, Research Funding; Iteos: Consultancy; Serametrix, Inc: Patents & Royalties; Genetech: Research Funding; Trillium Therapeutics: Consultancy; bristol myers squibb: Research Funding; Behringer Ingelheim: Honoraria. Morgan: BMS: Membership on an entity's Board of Directors or advisory committees; Jansen: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees. Landgren: Janssen: Other: IDMC; Janssen: Research Funding; Amgen: Honoraria; Celgene: Research Funding; Janssen: Honoraria; Amgen: Research Funding; Takeda: Other: IDMC; GSK: Honoraria. Maura: OncLive: Honoraria; Medscape: Consultancy, Honoraria.