Citations

663 Background: GI malignancies continue to be a major cause of cancer related deaths, despite advances in therapy options. In pancreatic cancer, the presence of homologous recombination mutations (HRM) has been shown to confer increased sensitivity to platinum chemotherapy. However, the role of HRM mutations in other GI cancers remains to be determined. The focus of this study is to evaluate the prognostic nature of core and noncore HRM in nonpancreatic GI cancers. Additionally, we aim to understand the predictive nature of these mutations related to platinum exposure. Methods: This was a retrospective review of patients at Moffitt Cancer Center with a primary stage IV nonpancreatic GI cancer treated with platinum therapy. All patients had next generation sequencing and were in the Clinical Genomics Action Committee database between 1/1/2013 and 11/1/2020. All patients had either a core HRM (BRCA1, BRCA2, PALB2) or noncore HRM (such as ATM, ATR, BARD1, BRIP1, FANCA, NBN, and RAD51). Patients were grouped into core HRM vs. noncore HRM. Response was stratified between responders (complete response and partial response) vs. non responders (stable disease and progressive disease), based on RECIST criteria. Progression free survival and overall survival were estimated using Kaplan-Meier method, and the log-rank test was used to assess the difference in progression free survival (PFS) and overall survival (OS) by HRM status and type of platinum therapy used. Results: There were 72 patients included in the study: the majority of patients were male (65.3%) and Caucasian (87.5%). Twenty-one (29.2%) patients had a core HRM and 51 (70.8%) had a noncore HRM. There was no significant difference in response rate between patients with core HRM and patients with noncore HRM for evaluable patients (n = 66): 20.0% of patients with core HRM vs. 21.7% of patients with noncore HRM demonstrated a response to platinum therapy (p = 0.41). An improved OS was noted for patients with core HRM vs. those with noncore HRM at 68.9 vs. 24.3 months (p = 0.019). An improved PFS was also seen in patients with core HRM at 10.4 months vs. 6.3 months with noncore HRM (p = 0.027). There was no difference in PFS based on type of platinum therapy used (oxaliplatin vs. carboplatin vs. cisplatin), while an improved OS was noted for patients treated with oxaliplatin vs. carboplatin vs. cisplatin at 43.1 vs. 28.2 vs. 16.0 months (p = 0.011). Conclusions: Our study demonstrated that in stage IV nonpancreatic GI malignancies treated with platinum therapy, patients with core HRM had a greater OS and PFS compared to those with noncore HRM, suggesting a potential prognostic and predictive role of these mutations. Further studies are needed to confirm our findings.

174 Background: Colorectal cancer (CRC), while one of the most common cancer diagnoses, can behave heterogeneously based on molecular characteristics. A subset of patients (pts) with CRC are characterized with mismatch repair deficiency (MMR-d), these pts exhibit encouraging responses to immunotherapy. The predictive nature of various factors, such as BRAF status, age, and MMR-D protein loss type, have been investigated in pts with MMR-d CRC. However, the prognostic role of these factors has not been well established. The purpose of this study was to identify characteristics that influence survival in MMR-d mCRC. Methods: This study evaluated pts with MMR-d mCRC in the Flatiron database. Overall survival (OS) was determined from date of diagnosis of stage IV disease to date of death and stratified based on age greater than or less than 50 years, BRAF mutation status, RAS mutation status, and type of MMR gene loss. For statistical analysis, the Chi-Square test was implemented to determine the prognostic significance of clinical and molecular features. Univariate and multivariate analyses were determined through the Cox regression model. Results: There were 1,101 pts in the study. The majority of pts were older than 50 (79.7%), Caucasian (75%), and had ECOG 0-1 (83.4%). Among the 803 pts with known BRAF status, 44.3% (n=356) had BRAF V600E mutation and 55.7% (n=447) were BRAF wildtype. Pts with BRAF V600E mutation had OS of 18.9 months vs. 33.2 months for pts with wild type BRAF (HR 1.52, 95% CI: 1.25-1.86, p<0.001). Pts older than 50 had a lower median OS vs. those who were ≤50 at 21.4 months vs. 38.7 months (HR 1.66, 95% CI: 1.33-2.07, p<0.001). When comparing MSH2/MSH6 mutations to MLH1/PMS2, a trend towards improved OS was seen with median survival of 35.2 months vs. 22.7 months, respectively (HR 0.79, 95% CI: 0.61-1.02, p=0.067). On multivariate analysis, BRAF mutation and older age continued to be associated with differences in survival, while KRAS mutation and specific MMR gene loss did not. Conclusions: BRAF V600E mutation and age greater than 50 are associated with decreased survival for pts with MMR-D mCRC. KRAS mutations and specific MMR alterations are not associated with differences in survival.

Abstract Background: Somatic EGFR mutations define a subset of non–small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. Methods: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. Results: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74–0.77) in the training and 0.77 (95% CI, 0.74–0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. Conclusions: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. Impact: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

AbstractAmyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease, is an aggressive motor neuron degenerative disease characterized by selective loss of both upper and lower motor neurons. The mechanisms underlying disease initiation and progression are poorly understood. The involvement of nonmotor neuraxis emphasizes the contribution of glial cells in disease progress. Microglia comprise a unique subset of glial cells and are the principal immune cells in the central nervous system (CNS). Triggering receptor expressed on myeloid cell 2 (TREM2) is a surface receptor that, within the CNS, is exclusively expressed on microglia and plays crucial roles in microglial proliferation, migration, activation, metabolism, and phagocytosis. Genetic evidence has linked TREM2 to neurodegenerative diseases including ALS, but its function in ALS pathogenesis is largely unknown. In this review, we summarize how microglial activation, with a specific focus on TREM2 function, affects ALS progression clinically and experimentally. Understanding microglial TREM2 function will help pinpoint the molecular target for ALS treatment.

Background Acute changes in GFR can occur after initiation of interventions targeting progression of CKD. These acute changes complicate the interpretation of long-term treatment effects. Methods To assess the magnitude and consistency of acute effects in randomized clinical trials and explore factors that might affect them, we performed a meta-analysis of 53 randomized clinical trials for CKD progression, enrolling 56,413 participants with at least one estimated GFR measurement by 6 months after randomization. We defined acute treatment effects as the mean difference in GFR slope from baseline to 3 months between randomized groups. We performed univariable and multivariable metaregression to assess the effect of intervention type, disease state, baseline GFR, and albuminuria on the magnitude of acute effects. Results The mean acute effect across all studies was −0.21 ml/min per 1.73 m 2 (95% confidence interval, −0.63 to 0.22) over 3 months, with substantial heterogeneity across interventions (95% coverage interval across studies, −2.50 to +2.08 ml/min per 1.73 m 2 ). We observed negative average acute effects in renin angiotensin system blockade, BP lowering, and sodium-glucose cotransporter 2 inhibitor trials, and positive acute effects in trials of immunosuppressive agents. Larger negative acute effects were observed in trials with a higher mean baseline GFR. Conclusion The magnitude and consistency of acute GFR effects vary across different interventions, and are larger at higher baseline GFR. Understanding the nature and magnitude of acute effects can help inform the optimal design of randomized clinical trials evaluating disease progression in CKD.

R47H- TREM2 mutation enhances AKT signaling in human AD microglia and mediates proinflammatory and synaptic toxicity in a tauopathy mouse model.

Abstract Background: Clonal cytopenia of undetermined significance (CCUS) is defined as persistent unexplained cytopenia with evidence of clonality [myeloid-associated somatic mutations (MTs) or cytogenetic [CG] abnormalities] but without definitive evidence of myeloid neoplasms (MN). The outcomes in CCUS patients (pts) are not well understood. Methods: The CCUS International Study database includes pts from 17 institutions who meet the criteria of CCUS and do not have other causes of cytopenia. Pts with MDS defining CG abnormalities were excluded. We collected baseline clinical data, laboratory parameters, CGs, molecular genetics, treatment, and disease course. Diverse gene panels from different institutions were collated to include a total of 70 myeloid-related somatic genes (30 genes in common). 2018 IWG MDS response criteria were used to determine response rate (RR). Disease progression (DP) is defined by progression to MN. The relationship between independent variables and DP and death was assessed using Cox proportional hazards models. Progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan-Meier method. All statistical analysis was performed using SAS. Results: A total of 258 pts were captured by July 2021. The median age was 71 (IQR 63-77) years, and 66% were male. Among 73 (28%) pts with known malignancy history, 27 (37%) pts received previous chemo- or radiation therapy. 27 (10%) pts had non-malignant hematology comorbidities. 91 (35%) had cardiovascular disease, and 33 (13%) had inflammatory disease. (Table 1) The red blood cell and platelet transfusion-dependent rates were 7.3% and 2.3%, respectively. The median number of MTs was 2 (IQR 1-3), with 221 (86%) pts had ≥1 MT, of which 116 (53%) had ≥ 2 MTs. The most common 5 MTs were TET2 (n=78, 30%), SRSF2 (n=50, 19%), DNMT3A (n=47, 18%), ASXL1 (n=40, 16%), and U2AF1 (n=22, 9%) (Figure 1). The median VAF (mVAF) was 28% (IQR: 9.2%, 43%) with VAF &lt; 10% in 47 (18%) and VAF ≥40% in 78 (30.2%) of the MTs. mVAF of the all genes are shown in Figure 2. Among pts with CG abnormalities (n=62, 24%), trisomy 8 and -Y are the most common karyotypes (n=15 for each, 24%) (Table 2). Eighty one (31%) patients received various treatments for CCUS with modest RR, including growth factors (n=47, 18.2%, RR: 25.5%), supportive care (n=23, 9%, RR: 26%), immunoglobulin/immunosuppressive therapy (n=15, 6%, RR: 40%), and DNMTi (n=8, 3%, RR=13%). The median length of follow-up was 15.6 (IQR 6.9-30.6) months. 24 pts progressed to MN, 14 (58.3%) of which were MDS, 8 (33.3%) CMML, and 2 (8.3%) AML. The 2-year PFS was 86.1% (95% CI: 80-93%) with a median PFS of 16.3 (IQR: 3.7, 21) months. In the multivariable model, positive MT of KRAS (HR: 8.4, 95% CI: 1.9-36.9, p=0.005) and CBL (HR: 16.5, 95% CI: 3.7-73.8, p=0.003) were significantly associated with DP. In the functional pathway analysis, having at least 1 splicing factor MT was significantly associated with DP (HR: 2.6, 95% CI:1.2-5.9, p=0.02). TP53 was not significantly associated with DP (HR: 1.2, 95% CI: 0.2-8.7, p=0.88). Having &gt;1 MT (HR: 3.57, 95% CI: 1.19-10.7, p=0.02) compared to a single MT was significantly associated with DP (Figure 3). Over the follow-up period, 35 pts died. The 2-year OS was 81% (95% CI: 74.9-87.9%). In the multivariable model, MT of KRAS (HR: 6.1, 95% CI: 1.8-20, p=0.003), CBL (HR: 7.3, 95% CI: 1.7-31, p=0.007), and FLT3 (HR: 19.9, 95% CI: 2.5-155, p=0.004) were significantly associated with inferior survival. In the functional pathway analysis, MTs in activated signaling pathway were significantly associated with death (HR: 4.1, 95% CI: 1.8-9, p&lt;0.001). None of the pts with TP53 MT died. Having &gt;1 MT was not statistically significantly associated with higher risk of death (HR: 1.5, 95% CI: 0.7-3.0, p=0.28) (Figure 4). After adjustment for co-MT status and comorbidities, baseline Hb&lt;10 g/dL (HR: 3.7, 95% CI: 1.8-7.9, p&lt;0.001) was significantly associated with greater mortality. Conclusion: This large retrospective study summarizes the CCUS pts' characteristics, with different MT patterns and VAF. We confirmed the impact of having &gt;1 MT on DP, but not OS. Genes involved in activated signaling had a significant impact on both DP and OS. TP53 MT was not associated with worse outcome. Findings may be due to limited cases in the particular genes and different gene panels from multiple institutions. A longer follow-up is planned to further describe the predictors for outcome in this ongoing study. Figure 1 Figure 1. Disclosures Komrokji: Jazz: Consultancy, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMSCelgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Acceleron: Consultancy; PharmaEssentia: Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy; Taiho Oncology: Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy. Zeidan: BioCryst: Other: Clinical Trial Committees; Kura: Consultancy, Other: Clinical Trial Committees; Ionis: Consultancy; Geron: Other: Clinical Trial Committees; Incyte: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Boehringer Ingelheim: Consultancy, Research Funding; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Janssen: Consultancy; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Aprea: Consultancy, Research Funding; AstraZeneca: Consultancy; Agios: Consultancy; BeyondSpring: Consultancy; Gilead: Consultancy, Other: Clinical Trial Committees; Daiichi Sankyo: Consultancy; Jazz: Consultancy; Astex: Research Funding; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Acceleron: Consultancy, Research Funding; Pfizer: Other: Travel support, Research Funding; Genentech: Consultancy; Epizyme: Consultancy; Jasper: Consultancy; Astellas: Consultancy; ADC Therapeutics: Research Funding; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding. Madanat: Blue Print Pharmaceutical: Honoraria; Stem line pharmaceutical: Honoraria; Onc Live: Honoraria; Geron Pharmaceutical: Consultancy. Coombs: LOXO: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Genentech: Honoraria; MEI Pharma: Honoraria. Griffiths: Celgene/Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Takeda Oncology: Consultancy, Honoraria; Taiho Oncology: Consultancy, Honoraria; Apellis Pharmaceuticals: Research Funding; Novartis: Honoraria; Alexion Pharmaceuticals: Consultancy, Research Funding; Boston Biomedical: Consultancy; Astex Pharmaceuticals: Honoraria, Research Funding; Genentech: Research Funding; Abbvie: Consultancy, Honoraria. Lai: Astellas: Speakers Bureau; Jazz Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Speakers Bureau; Macrogenics: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Foran: trillium: Research Funding; actinium: Research Funding; kura: Research Funding; boehringer ingelheim: Research Funding; takeda: Research Funding; abbvie: Research Funding; aptose: Research Funding; pfizer: Honoraria; novartis: Honoraria; servier: Honoraria; bms: Honoraria; revolution medicine: Honoraria; OncLive: Honoraria; gamida: Honoraria; certara: Honoraria; sanofi aventis: Honoraria; syros: Honoraria; taiho: Honoraria; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding. Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Desai: Astex: Research Funding; Janssen R&D: Research Funding; Kura Oncology: Consultancy; Takeda: Consultancy; Bristol Myers Squibb: Consultancy; Agios: Consultancy. Ades: ABBVIE: Honoraria; CELGENE/BMS: Honoraria; NOVARTIS: Honoraria; TAKEDA: Honoraria; JAZZ: Honoraria, Research Funding; CELGENE: Research Funding. Brunner: Novartis, Celgene, Takeda, AstraZeneca: Research Funding; Celgene, Forty Seven Inc, Jazz: Other: Advisory Board. Carraway: Celgene, a Bristol Myers Squibb company: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Other: Independent review committee; Stemline: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Other: Independent review committee; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astex: Other: Independent review committee; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Prebet: BMS: Research Funding; BMS, Curios, Daichi: Consultancy. Patnaik: Kura Oncology: Research Funding; Stemline Therapeutics: Membership on an entity's Board of Directors or advisory committees; Stemline Therapeutics: Membership on an entity's Board of Directors or advisory committees. Savona: Karyopharm: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; CTI: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS-Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Taiho: Consultancy, Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ALX Oncology: Research Funding; Astex: Research Funding; Incyte: Research Funding. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution.

Abstract Introduction: Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the presence and subsequent expansion of leukemia-associated driver mutations (MT). These MT predominantly involve epigenetic regulators such as DNMT3A, ASXL1, and TET2 (DAT, 75%). CHIP is a disease of aging and is associated with increased all-cause mortality. Clonal Hematopoiesis (CH), when present in the context of unexplained cytopenias and MT variant allele fractions (VAF) &gt;20%, is termed as clonal cytopenias of undetermined significance (CCUS). Chronic myelomonocytic leukemia (CMML) is a hematological malignancy characterized by TET2, ASXL1, and SRSF2MT as well as sustained monocytosis. It usually arises in the setting of existing CH and clonal monocytosis. Here, we assessed the clonal compositions involving DAT genes in patients (pts) with CHIP, CCUS, and CMML. Methods: We included 1008 pts: 54 (5%) with CHIP, 334 (33%) with CCUS, and 620 (62%) with CMML. Demographics, laboratory parameters, and mutational spectrum at diagnosis were collected. We characterized and compared DAT MT in all three cohorts and assessed correlations with clinical parameters. MT locus and type along with protein sequences were analyzed using ProteinPaint. All statistical analyses were performed using R. Results: Of the 1008 pts, 427 (42%) had DAT MT; 36 had CHIP (67%); 96 had CCUS (29%), and 296 had CMML (48%). The median age was 71 years (IQR 65-76), and 68% were male. CMML pts had higher white blood cell counts, absolute neutrophil counts, absolute monocyte counts, and lower hemoglobin and platelet counts in comparison to CCUS and CHIP pts. The distribution of age and sex were similar among the three groups. After a median follow-up of 11 months (IQR 9.5-12.8), there were no myeloid progressions in the CHIP group and 17 (18%) in the CCUS group (8 of which developed CMML, Table 1). There were 738 protein-altering or splice-site DATMT in 495 unique MT hotspots. Pts with TET2MT were older (71 years, compared to DNMT3AMT: 69 years and ASXL1MT: 69 years , p&lt;0.022). ASXL1MT were more common in males (75%, compared to DNMT3AMT: 52% and TET2MT: 66%, p=0.005). The mean VAF (mVAF) were 15.5% for DNMT3AMT, 35% for ASXL1MT and 39.2% TET2MT, respectively (p&lt;0.001). We then compared DATMT characteristics in CHIP, CCUS, and CMML groups: DNMT3AMT were most common in CHIP, followed by CCUS, and were very rare in CMML (35% vs. 15% vs. 3%, p&lt;0.001), with mVAF of DNMT3AMT increasing across this spectrum (CHIP: 6.5% vs. CCUS: 17.1% vs. CMML: 43.4%, p&lt;0.0001). While DNMT3A missense MTs were most common (n=62, 67.4%), the AML-associated R882 hotspot MT was seen in 26 (28%) pts (CHIP: n=3, 5%, CCUS: n=10, 16%, and CMML n=13, 21%, Figure 1a). None of the DNMT3AMT CHIP and CCUS pts progressed to CMML.ASXL1MT were most frequently seen in CMML (n=178, 28.6%), followed by CHIP (n=4, 7.4%), and CCUS (n=17, 5%, p&lt;0.001). The mVAF of ASXL1MT was significantly lower in CHIP, followed by CCUS, and CMML (11% vs. 34% vs. 36%, p&lt;0.0001). Truncating ASXL1 MTs were most common (n=205, 53%). Mutational hotspots included G646W (n=81, CCUS: n=6, 3%, CMML: n=75, 37%) and E635 (n=27, CHIP: n=1, 0.5%, CCUS: n=1, 0.5%, CMML: n=27, 13%, Figure 1b). Four ASXL1MT CCUS pts transformed to CMML (R965, E635, G646W, Q910*, and Q925*); of which 2 co-mutated with TET2MT, one with SRSF2MT, and one with an additional ASXL1MT.TET2MT were frequently encountered in CMML, followed by CCUS and CHIP pts (CMML: n=205, 33% vs. CCUS: n=88, 26.3% vs. CHIP: n=15, 27.8%, p=0.02). The mVAF of TET2MT progressively increased across the 3 groups (CHIP: 14.1%, CCUS: 31.9%, CMML: 45.5%, p&lt;0.001). TET2MT occurred across the span of the gene, with no clear hotspots identified, with nonsense MT being most frequent (n=150, 37.3%, Figure 1c). Among the nonsense and frameshift TET2MT (n=209), 131 (63%) involved the N terminal region, and 78 (37%) involved the catalytic domain. Among 8 CCUS pts that transformed to CMML, 6 had TET2MT, including 4 with spliceosome co-MT. Conclusion: While CMML, a disease of aging, arises in the background of CH, the most common CH MT, DNMT3AMT, plays a minor role in this process, and in fact, DNMT3AMT tend to occur at younger ages. While DNMT3A MT and ASXL1MT are preferentially observed in hotspots, TET2MT span the entire gene. Clonal compositions largely involving truncating TET2MT and frameshift ASXL1MT, in conjunction with splicing MT, shape the CMML genotype. Figure 1 Figure 1. Disclosures Komrokji: Geron: Honoraria; Novartis: Honoraria; Agios: Honoraria, Speakers Bureau; Abbvie: Honoraria, Speakers Bureau; JAZZ: Honoraria, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Acceleron: Honoraria. Zeidan: Genentech: Consultancy; BeyondSpring: Consultancy; Kura: Consultancy, Other: Clinical Trial Committees; Amgen: Consultancy, Research Funding; Cardiff Oncology: Consultancy, Other: Travel support, Research Funding; Astex: Research Funding; Epizyme: Consultancy; Geron: Other: Clinical Trial Committees; Boehringer Ingelheim: Consultancy, Research Funding; AstraZeneca: Consultancy; Acceleron: Consultancy, Research Funding; Astellas: Consultancy; Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding; Agios: Consultancy; Aprea: Consultancy, Research Funding; AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding; Loxo Oncology: Consultancy, Other: Clinical Trial Committees; Pfizer: Other: Travel support, Research Funding; ADC Therapeutics: Research Funding; Gilead: Consultancy, Other: Clinical Trial Committees; BMS: Consultancy, Other: Clinical Trial Committees, Research Funding; Jazz: Consultancy; Incyte: Consultancy, Research Funding; Ionis: Consultancy; Jasper: Consultancy; Daiichi Sankyo: Consultancy; Janssen: Consultancy; BioCryst: Other: Clinical Trial Committees. Coombs: LOXO: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Genentech: Honoraria; MEI Pharma: Honoraria. Madanat: Blue Print Pharmaceutical: Honoraria; Stem line pharmaceutical: Honoraria; Onc Live: Honoraria; Geron Pharmaceutical: Consultancy. Griffiths: Takeda Oncology: Consultancy, Honoraria; Novartis: Honoraria; Taiho Oncology: Consultancy, Honoraria; Apellis Pharmaceuticals: Research Funding; Alexion Pharmaceuticals: Consultancy, Research Funding; Boston Biomedical: Consultancy; Astex Pharmaceuticals: Honoraria, Research Funding; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Genentech: Research Funding; Abbvie: Consultancy, Honoraria. Lai: Jazz Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Astellas: Speakers Bureau; Jazz Pharma: Speakers Bureau; Macrogenics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Savona: CTI: Consultancy, Membership on an entity's Board of Directors or advisory committees; Geron: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; BMS-Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; NOVARTIS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Taiho: Consultancy, Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; ALX Oncology: Research Funding; Astex: Research Funding; Incyte: Research Funding. Litzow: AbbVie: Research Funding; Actinium: Research Funding; Pluristem: Research Funding; Amgen: Research Funding; Astellas: Research Funding; Jazz: Other: Advisory Board; Omeros: Other: Advisory Board; Biosight: Other: Data monitoring committee. Al-Kali: Novartis: Research Funding; Astex: Other: Research support to institution. Patnaik: StemLine: Research Funding; Kura Oncology: Research Funding.

Background: Previous studies report elevated serum titanium (Ti) levels in children with spinal implants. To provide additional data on this topic, we sought to assess serum ion levels at multiple timepoints in pediatric patients with growing spine devices, spinal fusion instrumentation, and extremity implants placed for fracture treatment. We hypothesized that serum Ti, cobalt (Co), and chromium (Cr) levels would be elevated in pediatric patients with growing spine devices compared with patients with extremity implants. Methods: Pediatric patients undergoing any primary spine implant placement, those with spine implant revision or removal surgery and patients with other appendicular implant removal had serum Ti, Co, and Cr ion levels drawn at the time of surgery. Fifty-one patients (12 growing spine devices, 13 fusions, and 26 extremity implants) had one set of labs, 31 of whom had labs drawn both preoperatively and postoperatively. Biopsies obtained from tissue specimens at the time of implant revision were analyzed histologically for the presence of metal debris and macrophage activity. Results: Patients with growing spine implants had elevated serum Ti (3.3 vs. 1.9 ng/mL, P=0.01) and Cr levels (1.2 vs. 0.27 ng/mL, P=0.01) in comparison to patients with fusion rods or extremity implants. With respect to patients with extremity implants, patients with growing spine devices had elevated serum Ti (3.3 vs. 0.98 ng/mL, P=0.013), Co (0.63 vs. 0.26 ng/mL, P=0.017), and Cr levels (1.18 vs. 0.26 ng/mL, P=0.005). On matched pairs analysis, patients who had labs drawn before and after spine implantation had significant increase in serum Ti levels (0.57 vs. 3.3 ng/mL, P=0.02). Histology of tissue biopsies adjacent to growing spine implants showed presence of metal debris and increased macrophage activity compared with patients with extremity implants. Conclusion: Serum Ti, Co, and Cr levels are elevated in children with spinal implants compared with those with extremity implants, particularly in those with growing spine devices. However, the clinical significance of these findings remains to be determined. Level of Evidence: Level II—prospective comparative study.