Bhagwate, Aditya

Objective Pancreatic ductal adenocarcinoma (PDAC) displays a remarkable propensity towards therapy resistance. However, molecular epigenetic and transcriptional mechanisms enabling this are poorly understood. In this study, we aimed to identify novel mechanistic approaches to overcome or prevent resistance in PDAC. Design We used in vitro and in vivo models of resistant PDAC and integrated epigenomic, transcriptomic, nascent RNA and chromatin topology data. We identified a JunD-driven subgroup of enhancers, called interactive hubs (iHUBs), which mediate transcriptional reprogramming and chemoresistance in PDAC. Results iHUBs display characteristics typical for active enhancers (H3K27ac enrichment) in both therapy sensitive and resistant states but exhibit increased interactions and production of enhancer RNA (eRNA) in the resistant state. Notably, deletion of individual iHUBs was sufficient to decrease transcription of target genes and sensitise resistant cells to chemotherapy. Overlapping motif analysis and transcriptional profiling identified the activator protein 1 (AP1) transcription factor JunD as a master transcription factor of these enhancers. JunD depletion decreased iHUB interaction frequency and transcription of target genes. Moreover, targeting either eRNA production or signaling pathways upstream of iHUB activation using clinically tested small molecule inhibitors decreased eRNA production and interaction frequency, and restored chemotherapy responsiveness in vitro and in vivo. Representative iHUB target genes were found to be more expressed in patients with poor response to chemotherapy compared with responsive patients. Conclusion Our findings identify an important role for a subgroup of highly connected enhancers (iHUBs) in regulating chemotherapy response and demonstrate targetability in sensitisation to chemotherapy.

Abstract Differentiation of aseptic and septic causes of arthroplasty failure is essential due to their different treatment schemes. We hypothesized that predicted cellularity profiling of sonicate fluid using the RNASeq-based the cellular deconvolution tools CIBERSORTx and ABIS-seq can differentiate between PJI and non-infected arthroplasty failure (NIAF). Profiles were created for 93 sonicate fluid samples (40 from NIAF and 53 from PJI patients) that had been subjected to RNASeq analysis. CIBERSORTx provided 22 total predicted cell types; 12 predicted cellular abundances were differentially expressed in PJI versus NIAF, including increased neutrophils, activated mast cells, and eosinophils (p≤0.0004) and decreased M0 macrophages, M2 macrophages, and Treg cells (p≤0.0001). ABIS-seq provided 17 total predicted cell types; seven predicted cellular abundances were differentially expressed in PJI versus NIAF, including increased neutrophils, Vd2 γδ T cells, and basophils (p-values of <0.0001, 0.0003, and 0.0263, respectively) and decreased nonclassical/intermediate (NC+I) monocytes, mucosal-associated invariant T (MAIT) cells, and myeloid dendritic cells (mDC) (p-values ≤0.0001). Receiver operative characteristic area under the curve (AUC) analysis identified cells types most predictive of PJI (CIBERSORTx: neutrophils [AUC = 94], activated mast cells [AUC = 93]; ABIS-seq: neutrophils [AUC = 88]) and NIAF (ABIS-seq: NC+I monocytes [AUC = 85], MAIT cells [AUC = 80], mDCs [AUC = 81]). PJI and NIAF samples were differentially clustered by principal component analysis using both tools. Overall, cellularity profiling using RNASeq-based cellular deconvolution can differentiate between PJI and NIAF sonicate fluid samples. Work supported by NIAMS (NIH R01 AR056647). CF was supported by the Mayo Clinic Graduate School of Biomedical Sciences and the Ph.D. Training Grant in Basic Immunology (NIH R25 GM055252 24).

Background: Although cellularity is traditionally assessed morphologically, deep sequencing approaches being used for microorganism detection may be able to provide information about cellularity. We hypothesized that cellularity predicted using CIBERSORTx (Stanford University), a transcriptomic-based cellular deconvolution tool, would differentiate between infectious and non-infectious arthroplasty failure. Methods: CIBERSORTx-derived cellularity profiles of 93 sonicate fluid samples, including 53 from subjects who underwent failed arthroplasties due to periprosthetic joint infection (PJI) (abbreviated for the purpose of this study as PJIF) and 40 from subjects who had undergone non-infectious arthroplasty failure (abbreviated NIAF) that had been subjected to bulk RNA sequencing were evaluated. Results: Samples from PJIF and NIAF subjects were differentially clustered by principal component analysis based on the cellularity profile. Twelve of the 22 individual predicted cellular fractions were differentially expressed in the PJIF cases compared with the NIAF cases, including increased predicted neutrophils (mean and standard error, 9.73% ± 1.06% and 0.81% ± 0.60%), activated mast cells (17.12% ± 1.51% and 4.11% ± 0.44%), and eosinophils (1.96% ± 0.37% and 0.42% ± 0.21%), and decreased predicted M0 macrophages (21.33% ± 1.51% and 39.75% ± 2.45%), M2 macrophages (3.56% ± 0.52% and 8.70% ± 1.08%), and regulatory T cells (1.57% ± 0.23% and 3.20% ± 0.34%). The predicted total granulocyte fraction was elevated in the PJIF cases (32.97% ± 2.13% and 11.76% ± 1.61%), and the samples from the NIAF cases had elevated predicted total macrophage and monocyte (34.71% ± 1.71% and 55.34% ± 2.37%) and total B cell fractions (5.89% ± 0.30% and 8.62% ± 0.86%). Receiver operating characteristic curve analysis identified predicted total granulocytes, neutrophils, and activated mast cells as highly able to differentiate between the PJIF cases and the NIAF cases. Within the PJIF cases, the total granulocyte, total macrophage and monocyte, M0 macrophage, and M2 macrophage fractions were differentially expressed in Staphylococcus aureus compared with Staphylococcus epidermidis -associated samples. Within the NIAF cases, the predicted total B cell, naïve B cell, plasma cell, and M2 macrophage fractions were differentially expressed among different causes of failure. Conclusions: CIBERSORTx can predict the cellularity of sonicate fluid using transcriptomic data, allowing for the evaluation of the underlying immune response during the PJIF and NIAF cases, without a need to phenotypically assess cell composition.

Abstract BackgroundFormalin-fixed, paraffin-embedded (FFPE) tissues have many advantages for identification of risk biomarkers, including wide availability and potential for extended follow-up endpoints. However, RNA derived from archival FFPE samples has limited quality. Here we identified parameters that determine which FFPE samples have the potential for successful RNA extraction, library preparation, and generation of usable RNAseq data.MethodsWe optimized library preparation protocols designed for use with FFPE samples using seven FFPE and Fresh Frozen replicate pairs, and tested optimized protocols using a study set of 130 FFPE biopsies from women with benign breast disease. Metrics from RNA extraction and preparation procedures were collected and compared with bioinformatics sequencing summary statistics. Finally, a decision tree model was built to learn the relationship between pre-sequencing lab metrics and qc pass/fail status as determined by bioinformatics metrics.ResultsSamples that failed bioinformatics qc tended to have low median sample-wise correlation within the cohort (Spearman correlation < 0.75), low number of reads mapped to gene regions (< 25 million), or low number of detectable genes (11,400 # of detected genes with CPM > 2). The median RNA concentration and pre-capture library Qubit values for qc failed samples were 18.7 ng/ul and 1.68 ng/ul respectively, which were significantly lower than those of qc pass samples (40.8 ng/ul and 5.58 ng/ul). We built a decision tree model based on input RNA concentration, input library qubit values, and achieved an F score of 0.803 in predicting QC status (pass/fail) of FFPE samples. ConclusionsWe provide a bioinformatics quality control recommendation for FFPE samples from breast tissue by evaluating bioinformatic and sample metrics. Our results suggest a minimum concentration of 25 ng/ul FFPE-extracted RNA for library preparation and 1.8 ng/ul pre-capture library output to achieve adequate RNA-seq data for downstream bioinformatics analysis.

Abstract Benign breast disease (BBD) is an established risk factor for development of breast cancer (BC). However, little is known about the prevalence of somatic genetic alterations at the time of BBD diagnosis and relationship to subsequent BC. To characterize DNA variants in BBD and investigate association with BC risk, we isolated DNA from formalin-fixed paraffin-embedded (FFPE) BBD biopsies and assessed mutations using a panel of 93 breast cancer predisposition genes (Qiagen GeneRead). The study set consisted of 120 BBD patients from three age-matched groups defined based on 16 years of BC follow-up: BBD-controls (cancer-free after 16 years), BBD-ER+, or BBD-ER- breast cancer (within 16 years). Bioinformatics quality checks included comparisons of paired fresh-frozen and FFPE replicates to reduce false variant calls induced by FFPE artifacts. Gene-level variant burden differences among study groups were assessed using 12 statistical approaches, adjusted for patient age, year of biopsy, and histology. To investigate possible immune implications of increased variant burden, extent of leukocytes in the BBD biopsies was assessed using CD45 immunohistochemistry. To assess variant profile changes during the progression from BBD to BC, we also performed targeted sequencing of 12 BBD-matched subsequent tumor samples (six ER+ and six ER-) developed within 5 years of BBD diagnosis. Gene-level association results showed consistently skewed distributions suggesting a higher variant burden in BBD controls: among the top 10 genes associated with case-status (p&lt;0.05), all had BC-risk odds ratio estimates less than 1.0. Immune infiltrates, assessed by CD45 H-scores, were positively associated with overall variant burden (r=0.42, p=0.0031), and noticeably higher in cancer-free controls (r=0.50, p=0.005). Comparison of mutation variants in 12 BBD cases that developed cancer within 5 years of diagnosis and their subsequent tumors revealed that more than half of the non-SNP variants were shared between the BBD and the subsequent tumor (54.6%), whereas less than one quarter were unique to the tumor (20.6%) or unique to the BBD (24.9%). Through BBD-BC paired variant analysis, three subjects were found with newly emergent clones uniquely appearing in the tumors and four subjects had loss of clones in the tumor that were present in the BBD. These results show that somatic variant burden is lower in patients with BBD that progress to BC, mutation profiles of BC progression are heterogeneous, and BBD tissues with reduced variant burden also show reduced immune infiltrate. This implicates a potential protective role for immune activation in BBD. Future directions will define the characteristics of the potentially protective immune response and its role in variant heterogeneity in a larger sample set, integrated with paired RNA sequencing to better understand the pathways involved and the relationship to immune infiltration. Citation Format: Stacey J. Winham, Julie M. Cunningham, Yuanhang Liu, Aditya V. Bhagwate, Ethan P. Heinzen, Samantha J. McDonough, Melody L. Stallings-Mann, Robert A. Vierkant, Jodi M. Carter, Mark E. Sherman, Derek C. Radisky, Amy C. Degnim, Chen Wang. Somatic variant burdenin benign breast disease and association with risk of subsequent breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2274.

Abstract Background: Benign breast disease (BBD) is a risk factor for breast cancer (BC); however, little is known about the genetic alterations present at the time of BBD diagnosis, and how these relate to risk of incident BC. Methods: A subset of a long-term BBD cohort was selected to examine DNA variation across three BBD groups (42 future estrogen receptor-positive (ER+) BC, 36 future estrogen receptor-negative (ER-) BC and 42 controls cancer-free for at least 16 years post-BBD). DNA extracted from archival formalin fixed, paraffin-embedded (FFPE) tissue blocks was tested and analyzed for presence of DNA alterations using a targeted panel of 93 BC-associated genes. To address artifacts frequently observed in FFPE tissues (e.g., C>T changes), we applied three filtering strategies based on alternative allele frequencies and nucleotide substitution context. Gene-level associations were performed using two burden tests, SKAT-O and logistic regression, and adjusted for clinical and technical covariates including epithelial percentage, histologic impression, patient age and year of BBD biopsy. Results: After filtering, the variant frequency of SNPs in our samples was highly consistent with population allele frequencies reported in 1KG/ExAC (0.986, p <1e-16). Ten genes were found to be associated with later cancer status by four of 12 association methods, with nominal p-values <0.05: MED12, MSH2, BRIP1, PMS1, GATA3, MUC16, FAM175A, EXT2, MLH1 and TGFB1. Additionally, analysis revealed 11 and 19 gene-level associations with p-values <0.05 and OR<1 for all cancer cases and ER- cases, respectively. Comparing between the three case groups, BBD ER+ cases were closer to controls in mutation profile, while BBD ER- cases were distinct. Notably, the variant burden was significantly higher in controls than in either ER+ or ER- cases. CD45 expression was associated with mutational burden (p=0.003).Conclusions: Somatic mutations were more frequent in benign breast tissue from women who did not develop cancer, opening questions of clonal diversity or immune-mediated restraint on future cancer development. CD45 expression was positively associated with mutational burden, most strongly in controls. Further studies in both normal and premalignant tissues are needed to better understand the role of somatic gene mutations and their contribution to future cancer development.

Abstract Background Periprosthetic joint infection (PJI), a devastating complication of total joint replacement, is of incompletely understood pathogenesis and may sometimes be challenging to clinically distinguish from other causes of arthroplasty failure. Methods We characterized human gene expression in 93 specimens derived from surfaces of resected arthroplasties, comparing transcriptomes of subjects with infection- versus non-infection-associated arthroplasty failure. Results Differential gene expression analysis confirmed the association of 28 previously investigated biomarkers with PJI- bactericidal/permeability increasing protein (BPI), cathelicidin antimicrobial peptide (CAMP), chemokines CCL3, CCL4, and CXCL2, colony stimulating factor 2 receptor (CSF2RB), colony stimulating factor 3 (CSF3), alpha-defensin (DEFA4), receptor CD64B, intercellular adhesion molecule 1 (ICAM1), IFNG, IL13RA2, IL17D, IL1A, IL1B, IL1RN, IL2RA, IL2RG, IL5RA, IL6, IL8, lipopolysaccharide binding protein (LBP), lipocalin (LCN2), lactate dehydrogenase C (LDHC), lactotransferrin (LTF), matrix metallopeptidase 3 (MMP3), peptidase inhibitor 3 (PI3), and vascular endothelial growth factor A (VEGFA), as well as identified three novel molecules with diagnostic potential for detection of PJI- chemokine CCL20, coagulation factor VII (F7), B cell receptor FCRL4. Comparative analysis of infections caused by staphylococcal versus non-staphylococcal and Staphylococcus aureus versus Staphylococcus epidermidis showed significant elevated expression of IL13, IL17D, and metalloprotease protein MMP3 in staphylocococcal infections, and increased expression of IL1B, IL8, and platelet factor PF4V1 in S. aureus infections. Pathway analysis of over-presented genes suggested activation of host immune response and cellular maintenance and repair functions in response to invasion of infectious agents. Conclusion Our study provides new potential targets for diagnosis of PJI and targets for differentiation of PJI-associated infectious agents. Disclosures Matthew P. Abdel, MD, Dr. Abdel receives royalties from Stryker on certain hip and knee products, and is a paid consultant for Stryker. (Consultant) Robin Patel, MD, Accelerate Diagnostics (Grant/Research Support)CD Diagnostics (Grant/Research Support)Contrafect (Grant/Research Support)Curetis (Consultant)GenMark Diagnostics (Consultant)Heraeus Medical (Consultant)Hutchison Biofilm Medical Solutions (Grant/Research Support)Merck (Grant/Research Support)Next Gen Diagnostics (Consultant)PathoQuest (Consultant)Qvella (Consultant)Samsung (Other Financial or Material Support, Dr. Patel has a patent on Bordetella pertussis/parapertussis PCR issued, a patent on a device/method for sonication with royalties paid by Samsung to Mayo Clinic, and a patent on an anti-biofilm substance issued.)Selux Dx (Consultant)Shionogi (Grant/Research Support)Specific Technologies (Consultant)

INTRODUCTION: Epigenetic modifications have been implicated to mediate several complications of diabetes mellitus (DM), especially nephropathy and retinopathy. Our aim was to ascertain whether epigenetic alterations in whole blood discriminate among patients with DM with normal, delayed, and rapid gastric emptying (GE). METHODS: Using the ChIP-seq (chromatin immunoprecipitation combined with next-generation sequencing) assays, we compared the genome-wide enrichment of 3 histone modifications (i.e., H3K4me3, H3K9ac, and H3K27ac) in buffy coats from 20 diabetic patients with gastrointestinal symptoms and normal (n = 6), delayed (n = 8), or rapid (n = 6) GE. RESULTS: Between patients with DM with delayed vs normal GE, there were 108 and 54 genes that were differentially bound (false discovery rate < 0.05) with H3K27ac and H3K9ac, respectively; 100 genes were differentially bound with H3K9ac in patients with rapid vs normal GE. The differentially bound genes with H3K27ac were functionally linked to the type 2 immune response, particularly Th2 cell activation and function (e.g., CCR3 , CRLF2 , CXCR4 , IL5RA , and IL1RL1 ) and glucose homeostasis ( FBP-1 , PDE4A , and CMKLR1 ). For H3K9ac, the differentially occupied genes were related to T-cell development and function (e.g., ICOS and CCR3 ) and innate immunity ( RELB , CD300LB , and CLEC2D ). Compared with normal GE, rapid GE had differential H3K9ac peaks at the promoter site of diverse immunity-related genes (e.g., TNFRSF25 and CXCR4 ) and genes related to insulin resistance and glucose metabolism. Motif analysis disclosed enrichment of binding sites for transcription factors relevant to the pathogenesis and complications of DM. DISCUSSION: GE disturbances in DM are associated with epigenetic alterations that pertain to dysimmunity, glucose metabolism, and other complications of DM.

Abstract Background: Archived formalin fixed paraffin embedded (FFPE) samples are valuable clinical resources to examine clinically relevant morphology features and also to study genetic changes. However, DNA quality and quantity of FFPE samples are sub-optimal, and resulting NGS-based genetics variant detections are prone to false positives. Evaluations of wet-lab and bioinformatics approaches are needed to optimize variant detection from FFPE samples. Results: As a pilot study, we designed within-subject triplicate samples of DNA derived from paired FFPE and fresh frozen breast tissues to highlight FFPE-specific artifacts. For FFPE samples, we tested two FFPE DNA extraction methods to determine impact of wet-lab procedures on variant calling: QIAGEN QIAamp DNA Mini Kit ("QA"), and QIAGEN GeneRead DNA FFPE Kit ("QGR"). We also used negative-control (NA12891) and positive control samples (Horizon Discovery Reference Standard FFPE). All DNA sample libraries were prepared for NGS according to the QIAseq Human Breast Cancer Targeted DNA Panel protocol and sequenced on the HiSeq 4000. Variant calling and filtering were performed using QIAGEN Gene Globe Data Portal. Detailed variant concordance comparisons and mutational signature analysis were performed to investigate effects of FFPE samples compared to paired fresh frozen samples, along with different DNA extraction methods. In this study, we found that five times or more variants were called with FFPE samples, compared to their paired fresh-frozen tissue samples even after applying molecular barcoding error-correction and default bioinformatics filtering recommended by the vendor. We also found that QGR as an optimized FFPE-DNA extraction approach leads to much fewer discordant variants between paired fresh frozen and FFPE samples. Approximately 92 % of the uniquely called FFPE variants were of low allelic frequency range (<5%), and collectively shared a “C>T|G>A” mutational signature known to be representative of FFPE artifacts resulting from cytosine deamination. Based on control samples and FFPE-frozen replicates, we derived an effective filtering strategy with associated empirical false-discovery estimates. Conclusions: Through this study, we demonstrated feasibility of calling and filtering genetic variants from FFPE tissue samples using a combined strategy with molecular barcodes, optimized DNA extraction, and bioinformatics methods incorporating genomics context such as mutational signature and variant allelic frequency.