Cherukuri, Yesesri

AbstractBackgroundSystemic inflammation plays a pivotal role in many chronic diseases including Alzheimer’s disease (AD). Assessing the composition of immune pathways in neurodegenerative diseases can contribute to precision medicine. Using publicly available transcriptomic data, we sought to elucidate transcriptional networks pertinent to inflammatory pathways across brain regions and peripheral blood in AD/mild cognitive impairment (MCI) and peripheral blood in Parkinson’s disease (PD).MethodFor the AD/MCI vs. control dataset, we analyzed bulk‐RNAseq collected from 6 brain regions of donors from ROSMAP, Mayo Clinic, and Mount Sinai School of Medicine (MSSM) brain banks available from the AMP‐AD consortium. Ante‐mortem, blood RNAseq expression data was retrieved from the AMP‐AD Emory Vascular cohort and Mayo Clinic Study of Aging (MCSA). We also collected blood‐derived microarray expression data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For the PD vs Control dataset, blood‐derived bulk‐RNAseq from the PDBP and PPMI cohorts were available through the AMP‐PD consortium. Following quality control, normalization, and residual generation to account for biological and technical variables, co‐expression network modules and their enriched pathways were identified using WGCNA within each dataset. Module/trait correlation tests for aging and diagnosis (cases [AD/MCI or PD] vs control) phenotypes were evaluated. Gene Ontology enrichment analyses were executed to identify enriched pathways and brain or blood cell types within the modules. Modules were tested for preservation across cohorts.ResultWe identified conserved immune signatures across brain regions and cohorts. Modules involved in immune response were preserved across all cohorts. Blood consensus modules involved in immune response were preserved in the brain and vice versa. Some immune modules were associated with AD/MCI, PD, and/or aging. Brain immune modules are significantly associated with aging and/or AD. Significant correlations (q<0.05) with PD diagnosis were present. In the MCSA and Emory vascular cohorts, there were no significant (q<0.05) associations between modules and diagnosis, while in ADNI there were nominal (p<0.05) associations.ConclusionPreserved transcriptional immune networks were identified across blood and brain and across two neurodegenerative diseases. Expanding gene co‐expression network analyses to other diseases and integrating additional omics measures and phenotypes can further strengthen these findings to unravel the immune signatures across complex diseases.

AbstractBackgroundAlzheimer’s disease (AD) is a complex, multicellular disease with immunological and genetic components. Previous studies demonstrated associations between AD and the missense variants ABI3‐rs616338‐T and PLCG2‐rs72824905‐G. The perturbed expression of these genes has been demonstrated to disrupt microglial function. To date, the transcriptomic profiles of variant carriers in the context of microglial subtype and state have not been explored in human brain. This represents a knowledge gap in our understanding of AD risk and resilience. We have developed and optimized a single nucleus RNAseq (snRNAseq) approach to study the impact of ABI3 and PLCG2 variants on microglial enriched nuclei from frozen human brain.MethodDOCK8 was identified as a nuclear microglial marker based on previous brain snRNAseq data. DOCK8 based microglial enrichment using fluorescent activated nuclei sorting (FANS) was validated using RT‐qPCR and snRNAseq in human cerebellum and temporal cortex (TCX), respectively. We are applying this enrichment and snRNAseq approach to TCX tissue from a cohort of 30 donors harboring ABI3 or PLCG2 missense mutations, or neither. Standard snRNAseq alignment and quality control pipelines will be applied, and nuclei annotated based on putative microglial markers. Differential gene expression will be assessed using pseudo bulk and MAST approaches, for association with ABI3 and PLCG2 genotype, diagnosis groups, risk factors, and pathology scores.ResultDOCK8 has several commercially available antibodies, making it an ideal microglia‐selection marker. Using RT‐qPCR in microglia enriched nuclei, we demonstrated an enrichment of microglia marker genes and depletion of other brain cell type markers. This is further supported by snRNA‐seq data from DOCK8‐sorted TCX tissue that yielded a 5x increase in microglia proportion (56% vs. 11% in unselected nuclei), enabling analyses of microglia sub‐populations. Leveraging this approach, we will investigate affected genes and pathways and uncover the resilience and risk mechanisms within microglia sub‐populations in ABI3 and PLCG2 variant‐carriers.ConclusionOur study presents a novel method for enriching microglial nuclei from frozen human brains and enables transcriptomic profiling of microglial subpopulations in ABI3 and PLCG2 missense variant‐carriers. We expect these insights will reveal novel genes and pathways that may play a key role in microglial function in AD.

Abstract Glioblastoma (GBM) is the most devastating and common form of primary brain cancer in adults. Tumor location plays a significant role in patient prognosis; in particular, GBM tumors contacting the lateral ventricles (LVs) are more aggressive than LV-distal counterparts. This may be due to interaction of tumors with unique features of the LV microenvironment, including the cerebrospinal fluid (CSF) and neural progenitor cells (NPCs) of the subventricular zone. Despite LV contact having a role on tumor malignancy, studies using bulk tumor samples to identify molecular contributors to LV-contacting prognosis have been only moderately successful, in large part due to intratumoral heterogeneity. Here, we leverage intraoperative surgical navigation to collect matched biopsies of adult LV-contacting primary GBM at locations proximal (&lt; 2 cm) and distal ( &gt; 2 cm) from the LV. Matched samples were collected from ten patients with equal sex distribution and an age range of 46 to 81 years. RNA sequencing of biopsies revealed a localized transcriptional signature of gene expression in LV-proximal locations. These genes include those identified to be associated with GBM malignancy and upregulated in primary GBM cells by CSF exposure or co-culture with NPCs, such as SERPINA3, CD44, and CTSB, as well as many newly identified genes. Implicated biological pathways involved in this transcriptional signature involve inflammation, chemotaxis, Notch signaling, angiogenesis, integrin signaling, and more. The top 50 upregulated genes by LV-proximity of GBM were used to cluster patient transcriptomes from the TCGA GBM database and evaluate the contribution to patient outcome. This analysis revealed a cluster with significantly extended overall survival that displayed a general downregulation of LV-proximity genes. Ultimately, these studies provide evidence that regional tumoral analysis is essential in identifying molecular signatures associated with microenvironmental influence, and that LV-contacting GBM has regional gene expression changes in many genes associated with malignancy.

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of virus evolution and spread and to inform policy decisions. We sequenced viral genomes from over 22,000 patient samples tested at Mayo Clinic Laboratories between 2020 and 2022 and used Bayesian phylodynamics to describe county and regional spread in Minnesota. The earliest calculated introduction into Minnesota was to Hennepin County from a domestic source around 22 January 2020; 6 weeks before the first confirmed case in the state. This led to the virus spreading to Northern Minnesota and, eventually, the rest of the state. International introductions were most abundant in Hennepin (home to the Minneapolis/St. Paul International Airport) totaling 45 (out of 107) over the 2-year period. Southern Minnesota counties were most common for domestic introductions, with 19 (out of 64), potentially driven by bordering states such as Iowa and Wisconsin as well as Illinois, which is nearby. Hennepin also was, by far, the most dominant source of in-state transmissions to other Minnesota locations ( n = 772) over the 2-year period. We also analyzed the diversity of the location source of SARS-CoV-2 viruses in each county and noted the timing of state-wide policies as well as trends in clinical cases. Neither the number of clinical cases nor the major policy decisions, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, appeared to have an impact on virus diversity across each individual county. IMPORTANCE We analyzed over 22,000 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes of patient samples tested at Mayo Clinic Laboratories during a 2-year period in the COVID-19 pandemic, which included Alpha, Delta, and Omicron variants of concern to examine the roles and relationships of Minnesota virus transmission. We found that Hennepin County, the most populous county, drove the transmission of SARS-CoV-2 viruses in the state after including the formation of earlier clades including 20A, 20C, and 20G, as well as variants of concern Alpha and Delta. We also found that Hennepin County was the source for most of the county-to-county introductions after an initial predicted introduction with the virus in early 2020 from an international source, while other counties acted as transmission “sinks.” In addition, major policies, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, did not appear to have an impact on virus diversity across individual counties.

Bcl-2 and Mcl-1 proteins play a role in multiple myeloma (MM) cell survival, for which targeted inhibitors are being developed. AT-101 is an oral drug, which disrupts Bcl-2 and Mcl-1 function, impedes mitochondrial bioenergetic processes and induces apoptosis in MM cells. When combined with lenalidomide and dexamethasone (Rd), AT-101 significantly reduced tumor burden in an in vivo xenograft model of MM. These data provided rationale for a phase I/II study to establish the effective dose of AT-101 in combination with Rd (ARd regimen) in relapsed/refractory MM. A total of 10 patients were enrolled, most with high-risk cytogenetics (80%) and prior stem cell transplant (70%). Three patients were lenalidomide-refractory, 2 were bortezomib-refractory and 3 were daratumumab-refractory. The ARd combination was well tolerated with most common grade 3/4 adverse events being cytopenia’s. The overall response rate was 40% and clinical benefit rate was 90%. The median progression free survival was 14.9 months (95% CI 7.1-NE). Patients responsive to ARd showed a decrease in Bcl-2:Bim or Mcl-1:Noxa protein complexes, increased CD8+ T and NK cells and depletion of T and B-regulatory cells. The ARd regimen demonstrated an acceptable safety profile and promising efficacy in patients with relapsed/refractory MM prompting further investigation in additional patients.

Abstract TMB is used to guide PD-1-directed immunotherapy in solid tumor Oncology. However, it has not been systematically studied in AML, where the focus has been on cytogenetic risk and individual driver gene mutations (GM's). TMB contribution to AML epidemiology is also uncertain. We therefore studied its association with epidemiologic risk factors; driver GM's and somatic mutations (SM's) in AML risk genes which we recently demonstrated (ABCB1; CYP1A1; CYP2B6; EPHX1; ERCC1,2,& 5; MEFV; MTRR; and TERT); clinical and cytogenetic features; and outcome after therapy in the MCAEC, a highly annotated clinical epidemiology cohort of consecutive AML pts [Finn, Cancer Epidemiol 39:1084, 2015]. Methods: We obtained somatic leukemia DNA from remnant diagnostic cytogenetic pellets in 98 MCAEC patients (pts), as previously described [Foran, Blood (2017) 130:570a]. Whole exome sequencing (WES) was performed at depth of ~100 million paired end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Reads were mapped to human genome build hg19 using BWA-MEM. Single nucleotide variants (SNVs) and small INDELs were identified using Mayo Clinic (MC) analytic pipeline GenomeGPS 4.0.1 following Broad GATK variant discovery best practices of alignment, realignment and recalibration, and multi-sample joint genotyping; and filtered using both germline whole exome and genome sequencing of ~1200 MC Biobank samples and public germline variant databases of 1000 genome project, 6500 individuals in exome sequencing project, and HapMap phase 3. Remaining variants were annotated using ANNOVAR, and functional variants of non-synonymous, truncating, frame-shift, and splice-sites were used in the statistical association analyses. TMB was defined as the number of functional mutations per Mb of coding region, heterozygous or homozygous. TMB associations with epidemiologic risk, clinical characteristics, and SM's in AML risk genes (listed above) or driver GM's (occurring in 5 or more pts: ASXL1, BCOR, CEBPA, DNMT3A, FLT3, IDH2, KRAS, MLL2-5, NF1, NPM1, NRAS, PHF6, RUNX1, SF3B1, STAG2, TET2, TP53, U2AF1) were evaluated using linear regression models; a rank transformation of TMB was utilized due to its skewed distribution. Multivariable analysis (MVA) models were adjusted for variables with p-value &lt;0.05 in unadjusted analysis. Regression coefficients ("β") were estimated, interpreted as change in mean TMB rank for specified variables or characteristic. Associations with outcomes were examined using logistic regression or Cox proportional hazards regression models. All statistical tests were two-sided (version 3.6.2; R Foundation for Statistical Computing, Vienna, Austria). Results Median age at AML diagnosis was 70 yrs (Range: 19-94 yrs), and 67 pts were male. Cytogenetic risk group was favorable (7%), intermediate-normal (46%) or abnormal (20%), and poor risk (27%). 40/61 pts (66%) achieved complete remission (CR). With a median follow-up of 8.0 months (Range: 0.1 - 186), 80 pts (82%) died and 20 (20%) underwent allogeneic transplantation (AlloBMT). Median TMB was 18.2 (Range: 15.0-70.1). In MVA, significant associations with increased TMB were observed in pts with history of prior immunosuppressive therapy or solid organ transplantation (β=19.48, P=0.015), and with FLT3 (β=21.12, P=0.015), MLL2 (β=20.91, P=0.001), and MLL3 (β=11.31, P=0.031) GM's. A borderline association was observed for U2AF1 (β=16.14, P=0.057). TMB was also associated with SM's in TERT (β=25.13, P=0.028); a borderline association with SM's in ABCB1 was not confirmed in MVA (β=-17.98, P=0.069). Additionally, cytogenetic risk group was associated with TMB in MVA (P=0.005), being highest in intermediate-normal and lowest in poor risk groups. Body Mass Index was inversely associated with TMB (unadjusted β=-16.99, P=0.005), but unconfirmed in MVA (β=-8.29, P=0.12). There was no association with CR (OR=0.93, P=0.46), use of (HR=0.96, P=0.64) or relapse risk (HR=1.00, P=0.98) following AlloBMT, or survival (HR=0.97, P=0.56) (Figure). Conclusions Measurement of TMB is feasible in this AML epidemiologic cohort, and we observed important associations with AML risk factors, risk gene SM's, cytogenetic risk group, and driver GM's. We acknowledge the relatively small sample size and possibility of type II error, and therefore these observations require validation in a large prospective cohort which is planned. Figure 1 Figure 1. Disclosures Foran: OncLive: Honoraria; certara: Honoraria; actinium: Research Funding; boehringer ingelheim: Research Funding; novartis: Honoraria; abbvie: Research Funding; servier: Honoraria; taiho: Honoraria; pfizer: Honoraria; revolution medicine: Honoraria; gamida: Honoraria; takeda: Research Funding; sanofi aventis: Honoraria; trillium: Research Funding; syros: Honoraria; aptose: Research Funding; bms: Honoraria; kura: Research Funding; h3bioscience: Research Funding; aprea: Research Funding; sellas: Research Funding; stemline: Research Funding. Murthy: CRISPR Therapeutics: Research Funding. Finn: Jazz: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; BeiGene: Consultancy, Speakers Bureau; ADC Therapeutics: Consultancy, Speakers Bureau. Badar: Pfizer Hematology-Oncology: Membership on an entity's Board of Directors or advisory committees. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Genentech: Research Funding; NanoString: Research Funding; Regeneron Genetics Center: Other: Research Collaboration.

Introduction: Population studies have identified genes with germline polymorphisms associated with acute myeloid leukemia (AML) risk and outcome. However, somatic mutations in these genes have not been reported in an AML clinical population and whether they are associated with epidemiologic exposures, clinical AML phenotypes and outcome after therapy. Methods: We systemically interrogated PubMed database (1998-2018), to identify genes with germline polymorphisms associated with AML risk, response to chemotherapy or outcome. To determine the prevalence and relevance of somatic mutations in these genes in an unselected AML population, we performed an analysis using Whole-Exome Sequencing (WES) on remnant diagnostic cytogenetic pellets from 98 patients from the Mayo Clinic AML Epidemiology Cohort, a detailed and highly-annotated cohort of 295 consecutive AML patients treated at Mayo Clinic Florida & Arizona between October, 2000 and December, 2011. Patient characteristics are shown in Table 1. Samples were sequenced at a depth of ~100 million paired-end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Sequencing reads were aligned to human reference genome, and somatic mutations including non-synonymous and truncating single nucleotide variants and small INDELs were identified and filtered using Exome Sequencing Project, 1000 genome, HapMap, & Mayo Clinic internal biobank genetic variants database. Copy number aberrations were identified & filtered using public copy number polymorphism databases. The association analyses were performed at the gene level, with a primary endpoint of whether a given patient harbored a somatic mutation in any genes linked to AML risk or outcome in literature, and to determine the associations of these mutations with epidemiologic exposures, AML phenotype and clinical outcomes. Results: From the literature search, we identified 77 unique genes with known germline polymorphisms associated with AML risk, response to chemotherapy or outcome. Fifty-eight of these were found to be somatically mutated in our WES dataset, with subsequent analysis focusing on the 11 genes (ABCB1, CYP1A1, CYP2B6, EPHX1, ERCC1, ERCC2, ERCC5, JAK2, MEFV, MTRR, and TERT) that had greater than 5 patients with nonsynonymous somatic mutations in the given gene. Significant associations with epidemiologic exposures and outcomes were noted in patients with somatic mutations in ERCC2, CYP1A1 and ERCC5 genes. Table 2 shows a comparison of patient characteristics and associations according to the presence of somatic mutations in these genes. Patients with mutations in CYP1A1 had a significantly younger age at AML diagnosis (Median: 51.7 vs. 71.0 years, P=.02) and significantly shorter OS in age-adjusted analysis (HR=4.45, P=.003). The former is a novel finding, whereas the latter is consistent with previous reports. Patients with mutations in ERCC2 more commonly used statins (66.7% vs. 21.7%, P=.03). Patients with ERCC5 mutations had a lower rate of tobacco use (20.0% vs. 54.5%, P=.049). In unadjusted analysis, there was a significant association between presence of somatic mutations in JAK2 and poorer survival after AML diagnosis (HR=2.83, P=.017), but this attenuated and did not retain significance when adjusting for age at AML diagnosis (HR=2.22, P=.067). Conclusion: Our exploratory study describes a novel association of CYP1A1 somatic nonsynonymous mutations with age of AML onset, as well as novel associations of ERCC2 and ERCC5 mutations with epidemiologic exposures in an unselect cohort of patients with AML. We confirm the association of CYP1A1 with inferior overall survival after AML diagnosis. These findings suggest that some genes associated with AML risk may also harbor somatic mutations that are clinically relevant. These results will guide a planned confirmatory prospective study to determine frequency and impact of both germline and somatic mutations of risk genes in AML patients, and may contribute to a better understanding leukemia risk assessment and potentially to prevention strategies. Disclosures Finn: Jazz Pharmaceuticals: Speakers Bureau; Celgene: Speakers Bureau; Seattle Genetics: Speakers Bureau. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding. Foran:Revolution Medicine: Consultancy; Servier: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding; H3Biosciences: Research Funding; Xencor: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Kura Oncology: Research Funding; Aptose: Research Funding; Aprea: Research Funding; Actinium: Research Funding; Agios: Honoraria, Research Funding.

7021 Background: Case-control studies (CCS) have identified germline variants (GVs) & genes associated with AML risk and/or outcome. However, whether these genes also harbor somatic mutations (SMs) in AML and whether these SMs are associated with clinical phenotypes and outcome is unknown. We systemically interrogated PubMed (terms "AML genetic polymorphisms"), yielding 612 reports (1981-2018), from which we identified unique variants/single nucleotide polymorphisms (SNPs) in 100 genes associated with AML risk and/or outcome in CCS. To determine the prevalence and relevance of SMs in these genes in an unselected AML population, we performed an analysis using WES of cases in the highly-annotated MCAEC (Finn, Ca Epidemiol 2015). Methods: We performed WES using remnant cytogenetic pellets from AML diagnosis in 98 MCAEC patients with available samples, sequenced at a depth of ~100 million paired-end 100bp reads using Agilent SureSelectXT Human All Exon V5 + UTRs target enrichment kit. Sequencing reads were aligned to human reference genome, and SMs including non-synonymous (NS) and truncating single nucleotide variants (SNVs) and small INDELs were identified and filtered using Exome Sequencing Project, 1000 genome, HapMap, & Mayo Clinic (MC) internal Biobank GV database. Copy number aberrations (CNAs) were identified & filtered using public CN polymorphism databases. For this analysis we evaluated the prevalence of somatic SNVs, INDELs, & CNAs in the 100 nominated genetic risk genes in collaboration with MC Cancer Center to determine their association with clinical phenotype and outcome. Results: Of the 100 unique genes, there were 40 with SM in our dataset, with 126 total mutations. Most were mutated in a very small number of patients, allowing insufficient statistical power to perform association analyses. However, an NS mutation in CYP2B6 (c.785A > G, p.Lys262Arg) had a minor allele frequency of 12.0%; this variant has been reported in association with breast cancer risk, but not with AML. Conclusions: We studied SM’s in AML genetic risk genes using WES of tumor samples. While representing a smaller sample size, this suggests their contribution to AML development may be limited in a broader clinical population. These results & prevalence of the novel CYP2B6 rs2279343 variant in AML must be confirmed in larger cohorts.