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Moore, Raymond M.

https://orcid.org/0000-0003-4196-1804

Mayo Clinic

Mayo Clinic

Citations 36

191 Expediting MxIF panel development in FFPE for the PhenoCycler platform: the ‘Joker’ panel development kit
McGrath, Kaitlyn, Moore, Raymond M. , Ferre, Roberto Leon, Soekojo, Cinnie Yentia , Villasboas, José C.

Regular and Young Investigator Award Abstracts | October 31, 2023 | Volume: No volume available | Issue: No issue available | Pages: A217-A218

10.1136/jitc-2023-sitc2023.0191 Get It

Multiplex Immunofluorescence Image Quality Checking Using DAPI Channel–referenced Evaluation
Moore, Raymond M. , Jordan, Clarissa E. , Guo, Ruifeng , Maus, Rachel L.G., Goode, Ellen L. , Wang, Chen , Jiang, Jun , Moore, Raymond , Maus, Rachel L, Wang, Chen , Guo, Ruifeng , Jiang, Jun , Liu, Hongfang , Markovic, Svetomir N.

Journal of Histochemistry & Cytochemistry | March 24, 2023 | Volume: 71 | Issue: 3 | Pages: 121-130

10.1369/00221554231161693 Get It

Multiplex immunofluorescence (MxIF) images provide detailed information of cell composition and spatial context for biomedical research. However, compromised data quality could lead to research biases. Comprehensive image quality checking (QC) is essential for reliable downstream analysis. As a reliable and specific staining of cell nuclei, 4′,6-diamidino-2-phenylindole (DAPI) signals were used as references for tissue localization and auto-focusing across MxIF staining–scanning–bleaching iterations and could potentially be reused for QC. To confirm the feasibility of using DAPI as QC reference, pixel-level DAPI values were extracted to calculate signal fluctuations and tissue content similarities in staining–scanning–bleaching iterations for identifying quality issues. Concordance between automatic quantification and human experts’ annotations were evaluated on a data set consisting of 348 fields of view (FOVs) with 45 immune and tumor cell markers. Cell distribution differences between subsets of QC-pass vs QC-failed FOVs were compared to investigate the downstream effects. Results showed that 87.3% FOVs with tissue damage and 73.4% of artifacts were identified. QC-failed FOVs showed elevated regional gathering in cellular feature space compared with the QC-pass FOVs. Our results supported that DAPI signals could be used as references for MxIF image QC, and low-quality FOVs identified by our method must be cautiously considered for downstream analyses.
Abstract 2203: Towards prediction of breast cancer risk in benign biopsies with high-plex GeoMx spatial protein profiling
Kachergus, Jennifer M., Shi, Ji , Moore, Raymond M. , McCauley, Bryan M. , Thompson, E. Aubrey , Vierkant, Robert A. , Carter, Jodi M. , Winham, Stacey J. , Wang, Chen , Pacheco-Spann, Laura M. , Radisky, Derek C. , Degnim, Amy C. , Sherman, Mark E.

Cancer Research | June 15, 2022 | Volume: 82 | Issue: 12_Supplement | Pages: 2203-2203

10.1158/1538-7445.am2022-2203 Get It

Abstract Background: Biopsy diagnoses of benign breast disease (BBD) confer a 1.5- to 4-fold increased risk of developing breast cancer (BC) compared with women without BBD. Previously, we reported that decreased numbers of specific immune cell types in lobules of BBD biopsies predicted increased BC risk, suggesting the promise of future tissue biomarker studies to define BC risk markers among BBD patients. Thus, we applied protein-based GeoMx® Digital Spatial Profiling (DSP) to BBD biopsies preceding BC (cases) and to BBD biopsies from cancer-free patients (controls) to identify possible BC risk markers, which we then evaluated in subsequent BC tissues and in surrounding normal lobules of cases. Methods: Archived pathology slides of BBD biopsies were reviewed and used to guide preparation of TMAs containing 1.0-mm diameter FFPE cores of lobules from an age- and cohort-period-matched set of 91 cases and 88 controls from the Mayo Clinic BBD Cohort. For patients who later developed BC, we prepared TMAs of BC tissue and surrounding mapped normal lobules. We applied GeoMx® DSP (immune and canonical signaling proteins) to both sets of TMAs. Following QC and data normalization, associations of case status with log-transformed biomarker expression in lobules of BBD biopsies were carried out using linear mixed modeling approaches, accounting for multiple ROIs per individual. Biomarkers significantly associated with case status (p<0.05) were further examined in BCs and adjacent normal lobules, using similar approaches. Results: The mean age at BBD biopsy was 52 years, and at BC diagnosis of cases, 61.4 years (mean time from BBD to BC was 10.2 years). A family history of BC was more frequent among cases (70% versus 43%; chi-square p=0.002). Of 72 biomarkers tested, 46 (64.4%) were evaluable after QC and normalization and 5 were associated with BC risk after adjustment for family history of BC: BCL2 (p=0.005), STING (p=0.006), CD44 (p=0.02), S100 protein (p=0.03) and pan-AKT (p=0.05); each showed higher levels in lobules of BBD biopsies of controls than cases. Three unique patterns appeared when examining these biomarkers across tissue type within cases: for BCL2 (p=5 x 10-9) and STING (p=2 x 10-19), levels were high in both BC and lobules surrounding BC but low in preceding BBD; for GAPDH (p=4 x 10-53) and pan-AKT (p=2 x 10-33), levels were high in BC, low in preceding BBD, and moderate in lobules surrounding BC; and for CD44 (p=2 x 10-6) and S100B (p=2 x 10-49), levels were low in BC, high in lobules surrounding BC and moderate in preceding BBD. Conclusions: Using a novel TMA of lobules in combination with DSP, we preliminarily identified immune-based and PI3 kinase-related protein biomarkers in BBD biopsies associated with BC risk. In case-only analyses, these markers demonstrated complex differences between lobules in BBD biopsies, subsequent BCs and adjacent normal lobules. Citation Format: Robert Alan Vierkant, Jodi M. Carter, Stacey J. Winham, Chen Wang, Jennifer M. Kachergus, Ji Shi, Raymond M. Moore, Bryan M. McCauley, Laura M. Pacheco-Spann, E A. Thompson, Derek C. Radisky, Amy C. Degnim, Mark E. Sherman. Towards prediction of breast cancer risk in benign biopsies with high-plex GeoMx spatial protein profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2203.
POKR: Building a Computable Heterogeneous Knowledge Resource for Precision Oncology
Moore, Raymond M. , Shen, Feichen , Guo, Yanbo, Moore, Raymond, Guo, Yanbo , Wang, Chen , Liu, Hongfang

Studies in Health Technology and Informatics | June 7, 2022 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.3233/shti220071 Get It

Precision oncology is expected to improve selection of targeted therapies, tailored to individual patients and ultimately improve cancer patients’ outcomes. Several cancer genetics knowledge databases have been successfully developed for such purposes, including CIViC and OncoKB, with active community-based curations and scoring of genetic-treatment evidences. Although many studies were conducted based on each knowledge base respectively, the integrative analysis across both knowledge bases remains largely unexplored. Thus, there exists an urgent need for a heterogeneous precision oncology knowledge resource with computational power to support drug repurposing discovery in a timely manner, especially for life-threatening cancer. In this pilot study, we built a heterogeneous precision oncology knowledge resource (POKR) by integrating CIViC and OncoKB, in order to incorporate unique information contained in each knowledge base and make associations amongst biomedical entities (e.g., gene, drug, disease) computable and measurable via training POKR graph embeddings. All the relevant codes, database dump files, and pre-trained POKR embeddings can be accessed through the following URL: https://github.com/shenfc/POKR.
Towards Defining Morphologic Parameters of Normal Parous and Nulliparous Breast Tissues by Artificial Intelligence
Ogony, Joshua, Bel, Thomas de , Kachergus, Jennifer M., Thompson, E. Aubrey , Degnim, Amy C., Ruddy, Kathryn J. , Hilton, Tracy, Vachon, Celine M. , White, Launia J. , Moore, Raymond M. , Carter, Jodi M. , Jensen, Matthew L. , Henry, Jill E. , Storniolo, Anna Maria , Laak, Jeroen van der , Carter, Jodi , Radisky, Derek C. , Degnim, Amy C. , Stallings‐Mann, Melody , Vachon, Celine M. , Hoskin, Tanya L. , Heckman, Michael G. , Vierkant, Robert A. , Jensen, Matthew, Pacheco-Spann, Laura M. , Winham, Stacey J. , Sherman, Mark E.

No container title available | February 21, 2022 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-1359557/v1 Get It

Abstract Background:Breast terminal duct lobular units (TDLUs), the source of most breast cancer (BC) precursors, are shaped by age-related involution, a gradual process, and postpartum involution (PPI), a dramatic inflammatory process that restores baseline microanatomy after weaning. Dysregulated PPI is implicated in the pathogenesis of postpartum BCs. We propose that assessment of TDLUs in the postpartum period may have value in risk estimation, but characteristics of these tissues in relation to epidemiological factors are incompletely described.Methods: Using validated Artificial Intelligence and morphometric methods, we analyzed digitized images of tissue sections of normal breast tissues stained with hematoxylin and eosin from donors <45 years from the Komen Tissue Bank (180 parous and 545 nulliparous). Metrics assessed by AI, included: TDLU count; adipose tissue fraction; mean acini count/TDLU; mean dilated acini; mean average acini area; mean “capillary” area; mean epithelial area; mean ratio of epithelial area versus intralobular stroma; mean mononuclear cell count (surrogate of immune cells); mean fat area proximate to TDLUs and TDLU area. We compared epidemiologic characteristics collected via questionnaire by parity status and race, using a Wilcoxon rank sum test or Fisher’s exact test. Histologic features were compared between nulliparous and parous women (overall and by time between last birth and donation [ recent birth: ≤5 years versus remote birth: >5 years]) using multivariable regression models.Results:Normal breast tissues of parous women contained significantly higher TDLU counts and acini counts, more frequent dilated acini, higher mononuclear cell counts in TDLUs and smaller acini area per TDLU than nulliparas (all multivariable analyses p<0.001). Differences in TDLU counts and average acini size persisted for >5 years postpartum whereas increases in immune cells were most marked <5 years of a birth. Relationships were suggestively modified by several other factors, including demographic and reproductive characteristics, ethanol consumption and breastfeeding duration. Conclusions:Our study identified sustained expansion of TDLU numbers and reduced average acini area among parous versus nulliparous women and notable increases in immune responses within five years following childbirth. Further, we show that quantitative characteristics of normal breast samples vary with demographic features and BC risk factors.
Resolving the Heterogeneous Tumor-Centric Cellular Neighborhood through Multiplexed, Spatial Paracrine Interactions in the Setting of Immune Checkpoint Blockade
Maus, Rachel L.G., Leontovich, Alexey A. , Moore, Raymond M. , Becher, Laura , Nevala, Wendy K. , Flotte, Thomas J. , Guo, Ruifeng , Dicke, Betty A., Yan, Yiyi , Leontovich, Alexey L, Schimke, Jill, Guo, Ruifeng , Schimke, Jill M. , Markovic, Svetomir N.

Cancer Research Communications | February 10, 2022 | Volume: 2 | Issue: 2 | Pages: 78-89

10.1158/2767-9764.crc-21-0146 Get It

Direct interactions between tumor and immune cells mediate the antitumor effect of all modern cancer immunotherapeutic agents. Simultaneously, tumor cells have evolved mechanisms of evasion, including the downregulation of HLA-I, potentially disrupting the mechanism of action employed by many immune checkpoint inhibitors. And yet, the in situ interplay between these cells within the tumor immune microenvironment (TIME) remains elusive. Recent advances in histologic multiplex bioimaging platforms have enabled in-depth molecular characterization of single cells within spatially preserved and clinically archived tumor tissues. Herein, we applied multiplex immunofluorescence to excisional lymph node biopsies from 14 patients with metastatic melanoma who experienced clear objective responses to immunotherapy (7 complete response; 7 progressive disease) to determine distinguishing features of the TIME in the pretreatment setting. Distinct regions of the TIME were evaluated using 35 proteins probing tumor, immune, and vasculature components across 323 fields of view. Single-cell compositional analysis confirmed established prognostic immune cell types including increased prevalence of cytotoxic T cells within the tumor core fields of view of responders. Integrating single-cell quantification with the spatial arrangement of cellular neighborhoods surrounding tumor cells revealed novel, spatial immune signatures capable of stratifying TIME based on clinical response. Our analysis revealed dynamic cellular composition of the tumor-centric cellular neighborhood (TCCN) based on anatomic subregion, functional expression of HLA-I by the index tumor cell and ultimately clinical response to immunotherapy. Overall, this study provides an analytic framework to resolve the cellular complexity of the TIME, increasingly relevant to the outcomes of modern cancer immunotherapy. Significance: Findings from this work propose a novel approach to resolving clinical heterogeneity of the TIME by objectively quantifying the cellular interactions occurring in metastatic melanoma lymph node tissue utilizing multiplex immunofluorescence. This study provides an analytic and biologically derived unit of measure, the TCCN which is customizable for studying critical paracrine interactions within spatially preserved tissue of various cancers and across the spectrum of multiplex imaging modalities.
Liquid Biopsy in Cholestatic Liver Disease Using Hepatocyte-Specific Methylation Markers
Punia, Sohan, Juran, Brian D., Ali, Ahmad H. , Schlicht, Erik M., Moore, Raymond M. , Sun, Zhifu , Lazaridis, Konstantinos N.

No container title available | February 19, 2021 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-209005/v1 Get It

Abstract Background: Quantification of circulating organ-specific cell-free DNA (cfDNA) provides a sensitive measure of ongoing cell death that could benefit evaluation of the cholestatic liver diseases primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC), which lack reliable non-invasive biomarkers. Our goal in this pilot study was to determine whether liver-specific cfDNA levels are increased in PBC and PSC patients relative to controls and in advanced versus early disease, to evaluate their potential as novel disease biomarkers.Methods: Peripheral blood derived bisulfite-treated DNA was PCR amplified from patients with PBC (n=48), PSC (n=48) and controls (n=96) to evaluate methylation status at 16 CpG sites reported to be specifically unmethylated in liver tissue near the genes IGF2R, ITIH4 and VTN. Amplicons were used to prepare paired end libraries which were sequenced on a MiSeq sequencer. Trimmed reads were aligned and used to determine unmethylation ratios and to calculate concentration of liver-specific cfDNA. Comparisons between groups were performed using the two-tailed Mann-Whitney Test and relationships between variables were evaluated using Pearson’s Correlation. Results: Levels of liver-specific cfDNA, as measured at the 3 genetic loci, were increased in PBC and PSC patients relative to controls and in late-stage relative to early-stage patients. As well, cfDNA levels were correlated with levels of alkaline phosphatase, a commonly used biochemical test to evaluate disease severity in liver disease, in patients, but not in controls. Conclusions: cfDNA offers promise as a non-invasive liquid-biopsy to evaluate liver-specific cell-death in patients with cholestatic liver diseases.
Genome-wide Resolution Peripheral Blood Methylome Profiling Reveals Signatures for Cholestatic Liver Disease
Moore, Raymond M. , Juran, Brian D., Lazaridis, Konstantinos N. , Lazaridis, Konstantinos N , Sun, Zhifu

Epigenomics | September 11, 2020 | Volume: 12 | Issue: 16 | Pages: 1363-1375

10.2217/epi-2020-0048 Get It

Utilizing quantitative multiplex immunofluorescence to characterize paracrine interactions within the tumor-immune landscape of metastatic melanoma.
Maus, Rachel L.G., Leontovich, Alexey A. , Moore, Raymond M. , Nevala, Wendy K. , Flotte, Thomas J. , Geyer, Susan M. , Dicke, Betty A., Guo, Ruifeng , Schimke, Jill M. , Markovic, Svetomir N.

Journal of Clinical Oncology | May 25, 2020 | Volume: 38 | Issue: 15_suppl | Pages: e15184-e15184

10.1200/jco.2020.38.15_suppl.e15184 Get It

e15184 Background: Clinical responses to anti-PD1 immunotherapy in patients with metastatic melanoma (MM) remain challenging to predict. This clinical heterogeneity is also reflected in the tumor-immune microenvironment among patients and within a single tumor lesion. With the emergence of multiplex imaging platforms, defining complex phenotypes at single cell resolution has become possible. Here, we sought to objectively quantify paracrine tumor-immune interactions contributing to the variable clinical responses observed in patients receiving anti-PD1 therapy. Methods: Excisional lymph node (LN) biopsies were obtained from treatment-naïve patients with MM who underwent subsequent anti-PD1 therapy. A single 5µm section of LN tissue was used to assess a 42 analyte panel by multiplex immunofluorescence. From 30 LN samples, 418 fields of view (FOVs) were selected resulting in 14,360 high-resolution images of 4 anatomical subregions: tumor core, tumor-immune interface, tumor infiltrate and adjacent immune stroma. Following image processing, we developed an adaptive classification for tumor-centric cellular neighborhoods (TCCN) to identify and quantify critical paracrine interactions within the tumor-immune microenvironment. Results: Stratification based on responsiveness to anti-PD1 therapy resulted in 4 complete responders (CR) and 12 non-responders (NR) at 12-week follow-up. From 126 FOVs, we defined the cellular composition of 197,865 TCCN across patients based on clinical response and LN subregions. Overall, the percentage of TCCN devoid of any T cells, B cells or macrophages was significantly higher in NR compared to CR irrespective of subregion. However, other markers differentiated TCCN based on subregion. Specifically in CR, tumor core regions were enriched for CD8 T cells, while enrichment for B cells and endothelial cells was demonstrated at the tumor-immune interface. Strikingly, tumor infiltrate regions demonstrate robust immune reactivity with enrichment for M1 polarized macrophages, NK cells and B cells in CR compared to NR. Complete data from the 30 patient cohort across 418 FOVs will be presented. Conclusions: Taken together, this data suggests cellular composition of TCCN across subregions of the LN is dynamic within a single metastatic site. In this small cohort, we introduce a formalized stratification to quantify and classify critical paracrine interactions within the immune-tumor microenvironment with the potential to inform clinical responsiveness to therapy.