Sookiasian, Danielle

Abstract The detection of genetic abnormalities is required during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this relies on invasive bone marrow (BM) biopsies, severely limiting early detection, frequent longitudinal monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. To address these needs, we recently launched GenoPredicta, a CLIA-approved LDT that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively characterizing MM genomes with whole genome sequencing (WGS) from as few as 50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Briefly, tumor cells are isolated from samples using fluorescence-activated cell sorting and subjected to WGS, from which copy number alterations, structural variants, and short variants (SNVs/indels) are identified using a fully automated pipeline generating physician-ready clinical reports from raw sequencing data in ∼6h. Analytical validation of GenoPredicta showed complete concordance with FISH results. Identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding MM immunotherapies is becoming increasingly important. Here, we describe GenoPredicta results from relapsed/refractory MM patients, highlighting resistance-conferring alterations that can only be detected by WGS, such as deletions in the kilo- to megabase scales that are observed in conjunction with SNVs and indels, leading to biallelic loss/inactivation of the gene, including at subclonal levels. In addition to biallelic loss of BCMA and GPRC5D in response to CAR T or T cell engager therapies, we observed similar resistance mechanisms for targets of immunomodulatory drugs, e.g., CRBN. The observation of these resistance mechanisms was consistent with patients’ clinical histories. In summary, we demonstrate that low input WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with CTC-based measurements enabling comprehensive profiling of the MM genome. Crucially, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection and guidance of therapy. The dramatically improved variant calling ability from WGS, especially in low-input CTC applications, extends to other malignancies and will gain wider adoption as sequencing costs continue to decrease. Citation Format: Bruno Paiva, Peter Voorhees, Patricia T. Greipp, Danielle Sookiasian, Julian Hess, Marisa DeMeo, Vicki Pounder, Sarah Calkins, Reid Meyer, Linda B. Baughn, Christine-Ivy Liacos, Meletios-Athanasios Dimopoulos, Alexandra Papadimou, Taouxi Konstantina, Efstathios Kastritis, Jesus Berdeja, Daniel Auclair, Valentina Nardi, Thomas Mullen, Francois Aguet, Shaji Kunnathu Kumar. Whole genome sequencing of multiple myeloma genomes with a novel clinical assay enables identification of genetic alterations underlying immunotherapy resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1067.

Abstract Introduction Detecting genetic abnormalities is mandatory during diagnostic workup and for potential individualization of therapy selection in multiple myeloma (MM) and its precursor conditions. At present, this requires invasive bone marrow (BM) biopsies, severely limiting early detection, patient monitoring, and the precise selection of therapy. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect point mutations and other clinically relevant alterations. Consequently, the IMS-IMWG guidelines were recently updated to require next-generation sequencing for the classification of high-risk MM. Moreover, the importance of identifying alterations in therapeutic targets (e.g., BCMA, GPRC5D) for guiding immunotherapies is becoming increasingly recognized. To address this need, we recently launched GenoPredicta, a CLIA-approved Laboratory Developed Test that enables routine monitoring, informing diagnosis, and treatment selection by comprehensively and robustly characterizing MM genomes with whole genome sequencing (WGS) from a minimum of ~50 circulating tumor cells (CTCs) isolated from peripheral blood (PB) or tumor cells from BM. Here, we describe the characterization of clinical and research samples with GenoPredicta, highlighting resistance-conferring genetic alterations that can only be detected by sequencing and that are consistent with patients' clinical histories, while further demonstrating the complete concordance of GenoPredicta with prior FISH results. Methods Tumor cells were isolated from BM and/or PB samples using fluorescence-activated cell sorting (FACS) (after CD138+ enrichment for PB) and subjected to whole genome sequencing (WGS), from which we identified copy number alterations, structural variants, and single nucleotide variants and indels. For a subset of samples, the BM was also characterized by FISH, using a standard clinical panel for characterizing MM; for other samples prior FISH results were available from patients' clinical records. Results The analytical validation of GenoPredicta, conducted on a retrospective cohort of >60 viably frozen samples from >30 patients, showed complete concordance between BM and PB for detected genomic abnormalities, with all clinically relevant events (11 translocations and 125 CNVs) observed in BM recapitulated in PB (100% recall). All events identified by FISH in 14 samples (8 translocations and 30 CNVs) were also identified in the BM (100% recall), with 50 translocations and 30 CNVs not detected by FISH also absent in the WGS data (100% precision). The abnormalities detected in these samples also included multiple high-risk events not assayed by FISH, including biallelic TP53 loss (Del 17p coupled with a deleterious TP53 mutation, observed in 4 patients) and MYC::IGL translocations (2 patients). Moreover, for all fresh peripheral blood clinical samples with FISH results available from patients' histories, GenoPredicta recalled 100% of reported events. Among these clinical samples, we notably observed a case with both a biallelic GPRC5D deletion and a TNFRSF17 (BCMA) deletion combined with a truncating mutation on the remaining allele. This was consistent with the patient's clinical history showing progression after therapy with talquetamab (anti-GPRC5D bispecific), and previous nonresponse to teclistamab (anti-BCMA bispecific) after prior therapy with Cilta-cel (BCMA-directed CAR T). GenoPredicta also detected other mutations likely to confer resistance to immunotherapies, including loss-of-function mutations in IKZF3 and deletions of FCRL5 in frozen peripheral blood research samples. Conclusion We demonstrate that WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis and monitoring, with blood-based measurements enabling comprehensive profiling of the myeloma cancer genome. Importantly, this includes genetic alterations that confer resistance to therapy, allowing for both early detection of such alterations and more precise selection of therapy.

Introduction The discovery of MAPK/ERK pathway mutations has revolutionized the care for patients with histiocytic neoplasms. However, mutational analysis on biopsy specimens is often limited by low tumor cellularity leading to testing failure or disease involvement of difficult-to-reach sites (e.g., central nervous system). Recently, molecular analysis of cell-free DNA (cfDNA) has shown promise as a viable tool for discovering driver mutations in multiple cancers. A recent study of mainly BRAF-mutated non-Langerhans cell histiocytosis (LCH) showed 50% concordance between tumor and plasma cfDNA analysis for BRAF-V600E. However, it is unknown whether cfDNA has a role in the evaluation of cases that harbor mutations beyond BRAF-V600E. We conducted this study to address this unanswered question using a large cohort of individuals with diverse histiocytic neoplasms from a tertiary-care institution. Methods We included 40 cases with histiocytic neoplasms with stored plasma and germline DNA in this study. Tissue molecular analysis was conducted using a targeted next generation sequencing (NGS) using commercial assays or whole exome sequencing (WES) using an in-house assay. A custom panel of 226 genes, including exonic and intronic regions, was used for the cfDNA assay in this study. To avoid cfDNA false positives, germline mutations identified from normal DNA sequencing were filtered using a BostonGene ®-developed error reduction algorithm.The total length of the analyzed genomic regions was 1.56 MB. For samples with an input greater than 30 ng, a 0.2% variant allele frequency (VAF) limit of detection (LOD) was used; a 0.4% VAF LOD was used for samples less than 30 ng. Results The final analysis cohort included 38 patients with histiocytic neoplasms after exclusion of 2 cases (failure of germline DNA library preparation and mismatch of germline and somatic DNA, respectively). Disease types included Erdheim-Chester disease (ECD; n=13, 34%), Langerhans cell histiocytosis (LCH; n=13, 34%), and Rosai-Dorfman disease (RDD; n=12, 32%). 24 cases were multisystem (63%), and the remaining were single-system. Commonly involved organs included bone (n=25, 66%), kidney (n=12, 32%), skin (n=8, 21%), central nervous system (n=7, 18%), and pituitary (n=7, 18%). Most cases (n=31, 82%) underwent plasma collection pre-treatment, 5 cases underwent collection after histiocytosis-directed therapy, and 2 while on treatment. Tissue NGS/WES data were available for 28 (74%) cases; 5 cases (13%) had insufficient tissue cellularity, and 5 (13%) did not undergo any tissue sequencing. Among those who underwent successful tissue sequencing assays, the most common common driver alterations was BRAF V600E (n=5, 26%). Other alterations included those in MAP2K1 (n=4, 21%), BRAF-fusions (n=3, 10%; partners UBDT2, RNF11, and LMTK2, respectively), and single cases of KRAS, NRAS and BRAF indel, respectively. cfDNA analysis showed at least one variant in 23 cases (60%). Correlation between tissue and cfDNA for known driver mutations was poor and concordant findings were only seen in one case with ECD harboring BRAF V600E in tissue as well as plasma (VAF 0.5%). Among the 5 cases where tissue mutational analysis had failed, cfDNA showed mutations in MUTYH, PTCH2, NOTCH3 SDHD, and TMEM127, respectively (Figure 1). Among the 5 cases where tissue molecular assessment could not be undertaken due to various reasons, cfDNA showed alterations in 4 cases, encompassing NOTCH1, TET2, BRCA1, MSH6, PIK3CD, and FUS genes. Conclusions In a large cohort of adults with diverse histiocytic neoplasms, we found poor correlation between tumor and plasma cfDNA molecular findings. The reason for the lack of correlation may be related to low tumor shedding especially among non- BRAF V600E cases. cfDNA analysis may have a role to identify potential drivers of pathogenesis among cases that are unable to successfully undergo tissue molecular analysis. Further studies are underway to characterize other novel alterations that were discovered in the cfDNA analysis.