Van Allen, Eliezer M

PURPOSE Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with a 10% annual risk of progression. Various prognostic models exist for risk stratification; however, those are based on solely clinical metrics. The discovery of genomic alterations that underlie disease progression to MM could improve current risk models. METHODS We used next-generation sequencing to study 214 patients with SMM. We performed whole-exome sequencing on 166 tumors, including 5 with serial samples, and deep targeted sequencing on 48 tumors. RESULTS We observed that most of the genetic alterations necessary for progression have already been acquired by the diagnosis of SMM. Particularly, we found that alterations of the mitogen-activated protein kinase pathway ( KRAS and NRAS single nucleotide variants [SNVs]), the DNA repair pathway (deletion 17p, TP53, and ATM SNVs), and MYC (translocations or copy number variations) were all independent risk factors of progression after accounting for clinical risk staging. We validated these findings in an external SMM cohort by showing that patients who have any of these three features have a higher risk of progressing to MM. Moreover, APOBEC associated mutations were enriched in patients who progressed and were associated with a shorter time to progression in our cohort. CONCLUSION SMM is a genetically mature entity whereby most driver genetic alterations have already occurred, which suggests the existence of a right-skewed model of genetic evolution from monoclonal gammopathy of undetermined significance to MM. We identified and externally validated genomic predictors of progression that could distinguish patients at high risk of progression to MM and, thus, improve on the precision of current clinical models.

Abstract Background . Cell-free DNA (cfDNA) sequencing enables serial temporal sampling, which offers the possibility of following the dynamics of biomarkers and clonal evolution in Multiple Myeloma (MM) over time. The use of cfDNA in clinical practice as a molecular biomarker and for monitoring response/resistance is dependent on a comprehensive profile of matched cfDNA and tumor DNA (tDNA) samples. Here we performed Ultra-Low Pass Whole Genome Sequencing (ULP-WGS) followed by whole-exome sequencing (WES) and targeted deep sequencing of matched cfDNA/tDNA samples from MM patients. Methods. We performed next generation sequencing of matched cfDNA/tDNA samples for 63 patients with newly diagnosed or relapsed MM, SMM, or MGUS. Libraries were constructed using the Kappa Hyper kit and sequenced by ultra-low-pass whole-genome sequencing (ULP-WGS, 0.1x coverage) to quantify tumor fraction within cfDNA. WES was performed on 30 matched samples cfDNA/tDNA/germline DNA from 10 patients with more than 5% of tumor fraction. Libraries were hybridized to the Nextera Rapid Capture Exome kit (Illumina) and then sequenced on HiSeq 4000 (Illumina). Targeted deep sequencing was performed on 32 matched cfDNA/tDNA samples from 16 patients using the HaloPlex HS technology (Agilent), allowing for molecular barcoding. Libraries were constructed according to the manufacturer's instructions and sequenced on HiSeq 2500 (Illumina). Sequencing data were analyzed using the Firehose pipelines, including MuTect, ABSOLUTE, ReCapSeg, GISTIC and MutSig. Results. We first used a cost-effective approach to establish the tumor content of cfDNA in a large-scale manner by ULP-WGS. Among 63 tested samples (53 MM, 6 SMM and 4 MGUS patient samples), the tumor fraction within cfDNA ranged from 0 to 81% with a mean of 10%. About 43% of these samples had tumor fraction greater than 5% within cfDNA. To assess whether cfDNA can capture the genetic diversity of MM and inform clinical management, we performed WES of matched cfDNA/tDNA/germline DNA samples for 10 patients (mean target coverage 194x). Copy number alterations (CNAs) assessed by WES (ReCapSeg) were consistent between cfDNA and tumor DNA. Similarly, focal CNAs assessed by GISTIC were consistent between tDNA and cfDNA. We then examined the overlap of somatic single nucleotide variants (SSNVs) between WES of cfDNA and matched tDNA. We found, on average, 100% of the clonal and 96% of the subclonal (range 54-100%) SSNVs that were detected in the tumor were confirmed to be present in cfDNA. Similarly, for mutations detected in the cfDNA, we found, on average, 100% of the clonal and 99% of the subclonal (range 98-100%) SSNVs were confirmed in the tumor. To assess whether targeted deep sequencing of cfDNA could be a good proxy for tumor biopsy we used a targeted deep sequencing approach of known MM driver genes. Libraries were prepared using unique molecular barcodes to avoid duplication rates, for 32 matched cfDNA/tDNA samples from 16 patients with MM. The mean target coverage was 596x. We found similar frequencies of altered MM driver genes in both cfDNA and tDNA, including KRAS, NRAS, and TP53, indicating that cfDNA can be used for precision medicine. Conclusions. Our study demonstrates that both WES and targeted deep sequencing of cfDNA are consistently representative of tumor DNA alterations in terms of CNAs, focal CNAs and SSNVs. This approach could therefore be used to longitudinally follow clonal evolution across the course of the disease and precision medicine in patients with MM. Disclosures Palumbo: Takeda: Employment, Honoraria; Janssen Cilag: Honoraria. Kumar:Noxxon Pharma: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy; BMS: Consultancy; Array BioPharma: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; AbbVie: Research Funding; Onyx: Consultancy, Research Funding. Roccaro:Takeda Pharmaceutical Company Limited: Honoraria. Facon:Amgen: Consultancy, Speakers Bureau; Novartis: Consultancy; Janssen: Consultancy, Speakers Bureau; Bristol: Consultancy; Millenium/Takeda: Consultancy; Celgene: Consultancy, Speakers Bureau; Karyopharm: Consultancy. Ghobrial:Celgene: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Noxxon: Honoraria; Novartis: Honoraria; Takeda: Honoraria; Amgen: Honoraria.

Abstract In multiple myeloma (MM), despite well-characterized precursor states such as monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM), there is a lack of sufficient biomarkers to predict disease progression. Most genomic analyses have studied the malignant plasma cells, however, cancers form a complex ecosystem with the immune and stromal microenvironment. To characterize the cellular composition and transcriptional programs of each component of the tumor and microenvironment at different stages of MM progression, we employed single-cell RNA sequencing on 48K plasma and 40.8K immune microenvironmental cells from a cohort of 22 patients with varying stages of disease progression and 9 healthy donors. Expression profiles of plasma cells revealed clear tumor-specific differences in known oncogenic drivers in MM (MMSET/FGFR3, CCND1 and MAFB) as well as other clonally expressed genes (LAMP5, HIST1H1C, and AREG), distinguishing them from healthy plasma cells. We identified a subset of cycling plasma cells in malignant samples, observing a range of proliferative capacity across disease stages. Furthermore, our approach allowed a unique head-to-head comparison of gene expression changes in normal and malignant plasma cells from the same individual, revealing early alterations in genes related to immune modulation (NKBIA) or controlling transcription and differentiation (EID1). Some alterations were patient-specific, while others, such as MHC I overexpression and CD27 loss, were recurrently observed across subsets of the cohort. Analysis of the BM microenvironment demonstrated significant infiltration of natural killer cells, non-classical monocytes/macrophages, and T cells, even in the earliest stages of the disease. Further investigation revealed upregulation of MHC II expression at the mRNA level in CD14+ monocytes/macrophages and yet, intriguingly, analysis by CyTOF and immunohistochemistry revealed a shift towards intracellular localization of MHC II in these cells. Co-culture with MM cell lines was sufficient to induce the decrease of extracellular MHC II, providing strong evidence for MM-induced compromised antigen presentation by macrophages, and hinting at a mechanism of immune evasion. Together, our results provide a comprehensive view at the complex interplay of the immune and malignant cells in different stages of the disease. We demonstrate the immune response beginning in premalignant conditions to be heterogeneous, including compromised antigen presentation as well as alterations in cellular composition and signaling. Consideration of the type of immunological response may prove valuable in determination of progression risk, as well as open up potential strategies for therapy. Citation Format: Nicholas J. Haradhvala, Oksana Zavidij, Tarek H. Mouhieddine, Romanos Sklavenitis-Pistofidis, Jihye Park, Mairead Reidy, Abdallah Flaifel, Benjamin Ferland, Salomon Manier, Mark Bustoros, Daisy Huynh, Marzia Capelletti, Brianna Berrios, Mahshid Rahmat, Chia-Jen Liu, Meng Xiao He, Esteban Braggio, Rafael Fonseca, Yosef Maruvka, Jennifer Guerriero, Melissa Goldman, Eliezer Van Allen, Steven McCarroll, Jamil Azzi, Gad Getz, Irene M. Ghobrial. Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 139.

SNF'ing out antitumor immunity Immune checkpoint inhibitors induce durable tumor regressions in some, but not all, cancer patients. Understanding the mechanisms that determine tumor sensitivity to these drugs could potentially expand the number of patients who benefit (see the Perspective by Ghorani and Quezada). Pan et al. discovered that tumor cells in which a specific SWI/SNF chromatin remodeling complex had been experimentally inactivated were more sensitive to T cell–mediated killing. The cells were more responsive to interferon-γ, leading to increased secretion of cytokines that promote antitumor immunity. Miao et al. examined the genomic features of tumors from patients with metastatic renal cell carcinoma who had been treated with immune checkpoint inhibitors. Tumors harboring inactivating mutations in PBRM1 , which encodes a subunit of the same SWI/SNF complex, were more likely to respond to the drugs. Science , this issue p. 770 , p. 801 ; see also p. 745

422 Background: There is significant variability in the response to VEGF-TT in mRCC with no validated predictive biomarkers. We hypothesized that whole exome analysis might identify markers of response and resistance to VEGF-TT in mRCC. Methods: mRCC patients who received first-line sunitinib or pazopanib and were in two extreme phenotypes of response were identified. Extreme responders (ER) were defined as PR or CR for ≥3 years (n=10) and primary refractory patients (PRP) were defined as PD within the first 3 months of therapy (n=10). WES was performed in pre-treatment specimens and established Broad Institute analytical pipelines were utilized to identify point mutations and copy number alterations across the exome. ER (n=4) and PRP (n=4) who were part of TCGA project for clear-cell RCC were included in this analysis. Nonsense, missense and indel mutations in established or novel RCC genes were investigated. Results: IMDC prognostic scores were not significantly different between the two groups. VHL mutations were observed at similar frequency in ER and PRP, overall 57%. Mutations in PBRM1 were identified in 7 ER (50%) vs. 1 PRP (7%) (p=0.03). In addition, mutations in TP53 were only found in PRP (p=0.09). No other gene had mutations that were associated with either response or primary refractory disease (Table). Conclusions: In this pilot study, PBRM1 mutations were associated with extreme response to VEGF-TT. However, this was exploratory, and multivariable analysis was not performed. Analysis of additional patient samples is ongoing to confirm or refute this association. If true it suggests that epigenetic effects of PBRM1 mutation may contribute to response to VEGF-TT in mRCC. [Table: see text]

Abstract Purpose: We examined the hypothesis that mutations in mTOR pathway genes are associated with response to rapalogs in metastatic renal cell carcinoma (mRCC). Experimental Design: We studied a cohort of mRCC patients who were treated with mTOR inhibitors with distinct clinical outcomes. Tumor DNA from 79 subjects was successfully analyzed for mutations using targeted next-generation sequencing of 560 cancer genes. Responders were defined as those with partial response (PR) by RECIST v1.0 or stable disease with any tumor shrinkage for 6 months or longer. Nonresponders were defined as those with disease progression during the first 3 months of therapy. Fisher exact test assessed the association between mutation status in mTOR pathway genes and treatment response. Results: Mutations in MTOR, TSC1, or TSC2 were more common in responders, 12 (28%) of 43, than nonresponders, 4 (11%) of 36 (P = 0.06). Mutations in TSC1 or TSC2 alone were also more common in responders, 9 (21%), than nonresponders, 2(6%), (P = 0.05). Furthermore, 5 (42%) of 12 subjects with PR had mutations in MTOR, TSC1, or TSC2 compared with 4 (11%) of 36 nonresponders (P = 0.03). Eight additional non-mTOR pathway genes were found to be mutated in at least 4 of 79 tumors (5%); none were associated positively with response. Conclusions: In this cohort of mRCC patients, mutations in MTOR, TSC1, or TSC2 were more common in patients who experienced clinical benefit from rapalogs than in those who progressed. However, a substantial fraction of responders (24 of 43, 56%) had no mTOR pathway mutation identified. Clin Cancer Res; 22(10); 2445–52. ©2016 AACR. See related commentary by Voss and Hsieh, p. 2320

Abstract Objective Clinicians’ ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS). Materials and Methods The National Institutes of Health (NIH)-sponsored Clinical Sequencing Exploratory Research and Electronic Medical Records & Genomics EHR Working Groups conducted a multiphase, iterative process involving working group discussions and 2 surveys in order to determine how genetic and genomic information are currently displayed in EHRs, envision optimal uses for different types of genetic or genomic information, and prioritize areas for EHR improvement. Results There is substantial heterogeneity in how genetic information enters and is documented in EHR systems. Most institutions indicated that genetic information was displayed in multiple locations in their EHRs. Among surveyed institutions, genetic information enters the EHR through multiple laboratory sources and through clinician notes. For laboratory-based data, the source laboratory was the main determinant of the location of genetic information in the EHR. The highest priority recommendation was to address the need to implement CDS mechanisms and content for decision support for medically actionable genetic information. Conclusion Heterogeneity of genetic information flow and importance of source laboratory, rather than clinical content, as a determinant of information representation are major barriers to using genetic information optimally in patient care. Greater effort to develop interoperable systems to receive and consistently display genetic and/or genomic information and alert clinicians to genomic-dependent improvements to clinical care is recommended.