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Background: Multiple myeloma (MM) remains an incurable plasma cell (PC) malignancy. Despite improvements in clinical outcomes, variability in treatment response exists. Some patients experience innate resistance, while others develop resistance over the course of treatment. Identifying signatures of treatment response and resistance is essential to predicting effective treatment strategies. Given the phenotypic clonal heterogeneity observed in MM, we hypothesize that resistant and sensitive subpopulations have unique phenotypic signatures. We used mass cytometry (CyTOF) to characterize primary MM samples and correlated their phenotypic signatures with treatment response. Methods: We characterized 102 primary MM samples by CyTOF using 37 antibodies (see figure). Frozen whole BM specimens were thawed, stained with antibodies, barcoded, and analyzed on a Helios mass cytometer. Data was processed using Cytobank or Pathsetter and analyzed using t-distributed stochastic neighbor embedding (t-SNE) algorithm. T-SNE plots for CD45+ cells were created using lineage defining markers. T-SNE plots of neoplastic PCs (CD138+,CD3-,CD16-,CD19-,cytoplasmic kappa or lambda+) were created using all remaining markers. A differential analysis of each sample's clusters was performed against all other events. Z-score values, representing marker changes from the differential analysis, for each cluster were used to group similar clusters across all samples, allowing us to compare sub populations of PCs between patients (see figure). From these groups of clusters with similar changes in markers, we calculated the proportion of cells with increases or decreases in markers for each sample. Results were compared to IMWG 90-day response criteria using a random forest model. Results: We performed mass cytometry on 102 samples from 68 unique MM patients. Median age was 66 years (range 34-95) with a 1.5:1 male:female ratio. 37 (36%) had NDMM, 55 (54%) had RRMM, 2 (2%) had SMM and 8 cases (8%) had unknown status. FISH studies revealed 47 (46%) had hyperdiploidy without a recurrent primary IgH rearrangement, 31 (30%) had t(11;14), 13 (13%) had t(4;14), 5 (5%) had 14;16 or 14;20, 3 (3%) had hyperhaploidy and 3 (3%) had an undefined primary. 54 (53%) had 1q gain/amp, 22 (22%) had TP53 deletion, 22 (22%) had a MYC rearrangement and 71% had high mSMART risk. Nearly all patients received an immunomodulatory compound, a proteasome inhibitor and dexamethasone. 2 (2%) had complete response (CR), 10 (9.8%) very good partial response (VGPR), 36 (35%) had partial response (PR), 14 (14%) had minimal response (MR), 13 (13%) had stable disease (SD) and 17 (17%) had progressive disease (PD). Characterization of CD45+ cells identified a relatively conserved and reproducible map from each patient. Notable differences included an ~2-fold reduction in the percentage of total B cells (CD45+,CD3-,CD19+)/total CD45+ cells in cases with high risk mSMART, RRMM and TP53 deletion compared to cases with standard risk, NDMM or normal TP53 status. Similar B-cell reductions were found in RRMM vs. NDMM samples from matched-patients. In contrast to the conserved t-SNE structure of the CD45+ population, the neoplastic PC population displayed dramatically reduced t-SNE structural consistency. Heterogeneity between patient samples and between the same patient samples over time was observed. We focused our analysis on 22 patients with serial samples. The proportion of each t-SNE group present in each patient sample was calculated and then correlated to the 90-day response metric. We identified a phenotypic group whose proportion increased in relation to disease progression (R2=0.85). This group had elevated BCL-2, pSTAT3, CD56 levels and reduced CD45 and CD81 levels. Evaluating individual markers, we found an increase in the proportion of cells with elevated BCL-2, pS6, Ki67, and IKZF1 levels in relation to disease progression. We also observed an increase in the proportion of cells with reduced pCREB levels and a reduction in the proportion of cells with reduced CD147 levels in relation to disease progression. Conclusions: We have utilized CyTOF to characterize phenotypic and functional markers in MM cells on a single cell level and can identify unique subgroups that change in relation to disease progression. Future analysis will correlate phenotypic signatures with ISS stage, mSMART risk, cytogenetic abnormality and type of treatment. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Karyopharm: Consultancy; Merck: Consultancy, Research Funding; Carsgen: Other, Research Funding; Cellectar: Other; Novartis: Research Funding; Adaptive Biotechnologies: Consultancy; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genecentrix: Consultancy; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Dr. Reddy's Laboratories: Honoraria.

Background: Multiple myeloma (MM) is an incurable plasma cell malignancy and genetic abnormalities contribute to disease heterogeneity and outcome. Primary abnormalities, namely recurrent immunoglobulin (Ig) heavy chain translocations and hyperdiploidy, occur early in disease course. Secondary events, such as MYC abnormalities occur upon progression. Earlier studies showed MYC abnormalities detected by FISH or by capture sequencing were independently associated with poor outcome (Walker, et al., BCJ, 2014), while recent studies using WGS did not support this finding (excluding MYC/IGL) (Mikulasova, et al. Haematologica, 2020; Misund, et al. Leukemia, 2020). We hypothesize these discrepancies are due to differences in methods and sensitivities of detection of MYC abnormalities by FISH vs. WGS. Given that MYC abnormalities often display remarkable genomic heterogeneity with numerous gene partners, reduced detection of MYC abnormalities by FISH is not unexpected. This hypothesis is supported by lower frequencies of MYC abnormalities found by FISH (15%) vs. NGS (30-35%) consistent with ~50% false-negative rate of the MYC FISH probe (Smadbeck, et al. BCJ, 2019). To better understand the role of MYC in myeloma disease outcome, we compared the MYC abnormality subtype identified by FISH or NGS vs. MYC gene expression levels and overall survival. Methods: We performed a retrospective study of newly diagnosed MM patients seen at Mayo Clinic or enrolled in the MMRF CoMMpass trial. For Mayo cases, MYC FISH results (breakapart probe, Abbott) were obtained from the Mayo Clinic Genomics database (N=1342) and mate pair sequencing (MPseq) was performed on 140 cases. For CoMMpass cases, we obtained tumor long-insert whole genome sequencing (WGS), RNA sequencing (RNAseq) for gene expression and clinical outcome data. Overall survival (OS) was defined as time from diagnosis to death from any cause or to last follow up. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical analyses performed using SPSS and JMP with significance determined when P <0.05. Results: We first evaluated the impact of MYC abnormalities on OS when detected by FISH or NGS. In Mayo cases, OS was significantly shorter in patients with MYC abnormalities compared to patients without MYC abnormalities using FISH (5.3 vs. 8.0 years, P<0.001, N=1342). In contrast, there was no significant difference in OS between patients with or without MYC or abnormalities using MPseq or WGS in both the Mayo and CoMMpass cohorts (Mayo: 6.4 vs. and 6.9 years P=0.78, N=140; CoMMpass: 4.9 vs. and 5.1 years P=0.74, N=546). Since FISH-detected MYC abnormalities were associated with poor outcome, we evaluated differences in the types of MYC abnormalities identified FISH and genome sequencing; 270 of 658 CoMMpass cases had a MYC abnormality and 12 abnormality subgroups were identified. In the Mayo cases, FISH preferentially detected translocations and complex abnormalities and missed insertions with flanking duplicating sequences or terminal tandem duplications (TTD) that occur telomeric to MYC. Since the level of MYC expression should be a consequence of the various genomic abnormalities altering the MYC gene region, we compared MYC expression levels in relation to MYC abnormality subgroups. Highest expression was seen with MYC amplification, followed by Ig abnormalities, non-Ig abnormalities, complex deletion/duplications, proximal deletions, non-Ig insertions, terminal deletions, TTD, trisomy 8, no MYC structural variation, monosomy 8 and cases with MAX mutations had the lowest expression. Abnormalities identified by FISH had higher MYC expression (83.5 TPM) compared to cases predicted to be missed by FISH (63.2 TPM). We tested if high MYC expression, irrespective of MYC structural abnormality, was associated with differences in OS. Boxplot analysis was used to categorize MYC expression in 631 CoMMpass patients as top quartile/high MYC expression (Q4≥ 75 TPM, n=159) and bottom quartile/low MYC expression (Q1≤ 16.5 TPM, n= 158) (see Figure). OS was significantly shorter in patients with high MYC expression compared to patients with low MYC expression (4.6 vs. 5.3 years, P <0.038). Conclusion: We show that FISH detects only a subset of the MYC abnormalities detected by genome sequencing, and that FISH-detected MYC abnormalities are associated with higher MYC gene expression and decreased survival. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Dr. Reddy's Laboratories: Honoraria; Cellectar: Other; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Tenebio: Other, Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Genecentrix: Consultancy; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy.

Background: Relapse is expected when treating patients with follicular lymphoma (FL) and marginal zone lymphoma (MZL), with a shortened response associated with each relapse. Lenalidomide combined with rituximab (R2) has shown enhanced activity, with a recently reported median progression free-survival (PFS) of 39.4 months in patients with relapsed/refractory (R/R) indolent non-Hodgkin lymphoma, including those with FL and MZL (AUGMENT; J Clin Oncol. 2019;37:1188). Methods: MAGNIFY is a multicenter, phase IIIb trial in patients with R/R FL grades 1-3b, transformed FL (tFL), MZL, or mantle cell lymphoma (MCL; NCT01996865) in which optimal lenalidomide duration is being explored. Patients received 12 cycles of R2 (lenalidomide 20 mg/d, d1-21/28 + rituximab 375 mg/m2 weekly in cycle 1 and then on day 1 of cycles 3, 5, 7, 9, and 11) followed by 1:1 randomization in patients with stable disease, partial response, or complete response/complete response unconfirmed (CR/CRu) to R2 versus rituximab maintenance for 18 months. Data presented here focus on induction R2 in efficacy-evaluable MZL patients compared with the overall population of FL grades 1-3a+MZL (not including FL grade 3b, tFL, or MCL) receiving ≥ 1 treatment with baseline/post-baseline assessments. The primary end point is progression-free survival (PFS) by 1999 International Working Group criteria. Results: As of November 30, 2019, 393 patients with FL grades 1-3a and MZL enrolled; 76 (19%) had MZL. The median age of MZL patients was 68 years (range, 46-90), 68 (89%) had stage III/IV disease, and 72 (95%) had prior rituximab-containing therapy. Overall response rate was 68% with 39% CR/CRu, and median duration of response was 38.6 months (95% CI, 29.4-not reached [NR]). The median PFS was 41.2 months (95% CI, 38.4-NR). Efficacy results for MZL subtypes and the overall population (FL grades 1-3a + MZL) are shown in the table. Forty-two patients (55%) have completed 12 cycles of R2, and 41 (54%) have been randomized and entered maintenance. Twenty-eight patients (37%) prematurely discontinued both lenalidomide and rituximab, primarily due to adverse events (AEs; n = 11; 14%) and progressive disease (n = 6; 8%). The most common (≥ 20%) all-grade AEs were neutropenia (49%), diarrhea (37%), anemia (25%), thrombocytopenia (24%), and constipation (24%). Most common (≥ 10%) grade 3/4 AEs were neutropenia (41%; 1 patient [1%] had febrile neutropenia), thrombocytopenia (13%), and leukopenia (11%). Conclusions: R2 is active with a tolerable safety profile in patients with R/R MZL. The efficacy and safety profile of R2 in MZL patients were similar to results observed in the overall MAGNIFY population. Disclosures Coleman: Seattle Genetics: Research Funding; EMD Serono Research and Development Institute Inc.: Research Funding; Innocare: Research Funding; ARCUS Biosciences: Research Funding; AstraZeneca Pharmaceuticals, LP (Acerta Pharma BV Trials): Research Funding; AstraZeneca Pharmaceuticals, LP: Research Funding; BMS (Celgene Corporation): Research Funding; Eli Lilly and Company: Research Funding; Genetech (F. Hoffman-LaRoche Ltd): Research Funding; Hutchinson MediPharma, LTD: Research Funding; Ipsen Group: Research Funding; Karyopharma Therapeutics, Inc.: Research Funding; Klus Pharma, Inc.: Research Funding; MeiPharma, Inc.: Research Funding; Merck Sharp & Dohme Corp.: Research Funding; Novartis Pharmaceuticals: Research Funding; Incyte Corporation: Research Funding; Boston BIoMedical, Inc.: Research Funding; BeiGene: Research Funding; Acerta: Research Funding. Andorsky:CTI: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Research Funding. Yacoub:Roche: Other: Support of parent study and funding of editorial support; Dynavax: Current equity holder in publicly-traded company; Ardelyx: Current equity holder in publicly-traded company; Incyte: Speakers Bureau; Hylapharm: Current equity holder in private company; Cara Therapeutics: Current equity holder in publicly-traded company; Agios: Honoraria, Speakers Bureau; Novartis: Speakers Bureau. Melear:Janssen: Speakers Bureau; AstraZeneca: Speakers Bureau. Fanning:Takeda: Consultancy, Speakers Bureau; Bristol Myers Squibb: Consultancy, Speakers Bureau; TG Therapeautics: Consultancy; Abbvie: Consultancy; Prisma Health: Current Employment; Sanofi Aventis: Speakers Bureau. Kolibaba:Atara Biotech: Consultancy; Compass Oncology: Ended employment in the past 24 months; Verastem: Honoraria; Seattle Genetics: Research Funding; Pharmacyclics: Research Funding; Novartix: Research Funding; Janssen: Research Funding; Gilead: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Acerta: Research Funding; AbbVie: Research Funding; Sumitomo Dainippon Pharma Oncology: Consultancy, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Lansigan:BMS: Consultancy; Seattle Genetics: Consultancy; BMS Steering Committee for MAGNIFY Program: Membership on an entity's Board of Directors or advisory committees; Spectrum Pharma: Consultancy, Research Funding. Reynolds:IHA Hematology/Oncology Consultants: Current Employment. Nowakowski:Kymera: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other; Curis: Consultancy; Kite: Consultancy; MorphoSys: Consultancy, Research Funding; Denovo: Consultancy; Seattle Genetics: Consultancy; Nanostrings: Research Funding; Celgene/BMS: Consultancy, Research Funding; Roche: Consultancy, Research Funding. Gharibo:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company; Bayer: Ended employment in the past 24 months. Ahn:BMS: Current Employment, Current equity holder in publicly-traded company. Li:BMS: Current Employment, Current equity holder in publicly-traded company. Rummel:Roche: Honoraria; Amgen GmbH: Honoraria; Celgene: Consultancy, Honoraria; Janssen: Honoraria; Novartis Pharma GmbH: Honoraria. Sharman:BeiGene: Research Funding; Bristol Meyers Squibb: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; AstraZeneca: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Acerta: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

Abstract Antimullerian hormone (AMH) is a promising biomarker for ovarian reserve. In this study, we assessed AMH before and 1 year after initiation of adjuvant chemotherapy on National Surgical Adjuvant Breast and Bowel Project (NSABP)/NRG Oncology B-47 in female participants aged 42 years and younger (median age = 39 years). At baseline, median AMH was 1.2 ng/mL; 13 (4.7%) values were less than 0.1 ng/mL (the threshold for detectable levels, in the perimenopause and menopause range), and 57 values (20.6%) were less than 0.5 ng/mL. At 1 year, 215 (77.6%) were less than 0.1 ng/mL, and 264 (95.3%) were less than 0.5 ng/mL. Postchemotherapy menses were reported by 46.2% of participants. Multivariable logistic regression found that the odds of having postchemotherapy menses increased with younger age, higher body mass index, and higher prechemotherapy AMH, but not by trastuzumab administration or by the choice of chemotherapy (doxorubicin-cyclophosphamide followed by paclitaxel vs docetaxel-cyclophosphamide). We conclude that higher prechemotherapy AMH predicts a lower risk of chemotherapy-induced amenorrhea and that AMH 1 year after chemotherapy initiation is not informative in this setting because it is likely to be very low.

Abstract Scientists debate where, when, and how different visual, orthographic, lexical, and semantic features are involved in visual word recognition. In this study, we investigate intracranial neurophysiology data from 151 patients engaged in reading single words. Using representational similarity analysis, we characterize the neural representation of a hierarchy of word features across the entire cerebral cortex. We find evidence of both feed-forward and feedback processing, with early representation of visual and lexical information in lingual gyrus followed by lexical representation in fusiform gyrus and semantic sensitivity in inferior frontal gyrus, with letter representation emerging later in fusiform gyrus. Furthermore, we observed a variety of anatomically heterogeneous temporal response shapes, and these functional populations had significant feature sensitivity. Taken together, our results demonstrate the early influence of lexical, phonological, and semantic features in visual word recognition and reveal feed-forward, feed-back, and anatomically distributed processing mechanisms that contribute to visual word recognition.

AbstractIn this article, the editors of Clinical Infectious Diseases review some of the most important lessons they have learned about the epidemiology, clinical features, diagnosis, treatment and prevention of SARS-CoV-2 infection and identify essential questions about COVID-19 that remain to be answered.

ObjectivesThe spine is the most common site of bone metastases in differentiated thyroid cancer (DTC). The role of surgery in the management of cervical spine (C‐spine) metastases (CSpM) has not been adequately explored.MethodsThis is a retrospective cohort study at a tertiary referral center from 2002 to 2018. Inclusion criteria were pathologic diagnosis of DTC and imaging/pathologic diagnosis of CSpM. Statistical analysis utilized t tests for continuous variables and χ2 tests for categorical variables. Survival analysis was conducted using Kaplan–Meier curves with univariate and multivariate Cox regressions.ResultsFifty patients with DTC and CSpM were identified. Of those, 16 underwent surgical resection of the C‐spine, whereas 34 did not. The most common presenting symptom was neck pain (N = 37, 74%). Patients in the surgery group were more likely to report a subjective improvement of symptoms (P < .01) and to have local (P < .01) and systemic (P = .04) disease control. Five‐year overall survival was 44.7% for the surgery group (95% confidence interval [CI]: 17.1–69.3) and 11.1% (95% CI: 2.1–28.8) for the nonsurgery group (P = .01). The strongest risk factor for improved overall survival after C‐spine metastasis was local disease control at the C‐spine (multivariate hazard ratio [HR] = 0.32, 95% CI: 0.12–0.85, P = .02). Surgical intervention was significantly associated with improved survival on both univariate (HR = 0. 35, 95% CI: 0.15–0.82, P = .02) and multivariate (HR = 0.37, 95% CI: 0.14–0.98, P = .04) analysis.ConclusionSurgical management of CSpM in differentiated thyroid cancers is associated with significantly improved local disease control and overall survival. Referral to spine surgeons should be considered after diagnosis.Level of EvidenceIV. Laryngoscope, 131:E1741–E1747, 2021