1
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Blise KE, Sivagnanam S, Betts CB, Betre K, Kirchberger N, Tate BJ, Furth EE, Dias Costa A, Nowak JA, Wolpin BM, Vonderheide RH, Goecks J, Coussens LM, Byrne KT. Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer. Cancer Immunol Res 2024; 12:544-558. [PMID: 38381401 PMCID: PMC11065586 DOI: 10.1158/2326-6066.cir-23-0873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 01/12/2024] [Accepted: 02/19/2024] [Indexed: 02/22/2024]
Abstract
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multiplexed proteomic data set from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcomes. We designed a multiplex immunohistochemistry antibody panel to compare T-cell functionality and spatial localization in resected tumors from treatment-naïve patients with localized pancreatic ductal adenocarcinoma (PDAC) with resected tumors from a second cohort of patients treated with neoadjuvant agonistic CD40 (anti-CD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both cohorts were assayed, and over 1,000 tumor microenvironment (TME) features were quantified. We then trained ML models to accurately predict anti-CD40 treatment status and disease-free survival (DFS) following anti-CD40 therapy based on TME features. Through downstream interpretation of the ML models' predictions, we found anti-CD40 therapy reduced canonical aspects of T-cell exhaustion within the TME, as compared with treatment-naïve TMEs. Using automated clustering approaches, we found improved DFS following anti-CD40 therapy correlated with an increased presence of CD44+CD4+ Th1 cells located specifically within cellular neighborhoods characterized by increased T-cell proliferation, antigen experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of ML in molecular cancer immunology applications, highlight the impact of anti-CD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for anti-CD40-treated patients with PDAC.
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Affiliation(s)
- Katie E. Blise
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR USA
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
| | - Shamilene Sivagnanam
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Courtney B. Betts
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
- Current affiliation: Akoya Biosciences, 100 Campus Drive, 6 Floor, Marlborough, MA USA
| | - Konjit Betre
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Nell Kirchberger
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Benjamin J. Tate
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Immune Monitoring and Cancer Omics Services, Oregon Health & Science University, Portland, OR USA
| | - Emma E. Furth
- Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Andressa Dias Costa
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA
| | - Jonathan A. Nowak
- Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA USA
| | - Brian M. Wolpin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA
| | - Robert H. Vonderheide
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Jeremy Goecks
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR USA
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Current affiliation: Department of Machine Learning, H. Lee Moffitt Cancer Center, Tampa, FL USA
- Current affiliation: Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center, Tampa, FL USA
| | - Lisa M. Coussens
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Katelyn T. Byrne
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
- Lead contact: Katelyn T. Byrne, Department of Cell, Developmental and Cancer Biology, RLSB 6N032 Mail Code CL6C, 2730 S. Moody Ave, Portland, OR 97201
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2
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Blise KE, Sivagnanam S, Betts CB, Betre K, Kirchberger N, Tate B, Furth EE, Dias Costa A, Nowak JA, Wolpin BM, Vonderheide RH, Goecks J, Coussens LM, Byrne KT. Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer. bioRxiv 2023:2023.10.20.563335. [PMID: 37961410 PMCID: PMC10634700 DOI: 10.1101/2023.10.20.563335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Tumor molecular datasets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning to analyze a single-cell, spatial, and highly multiplexed proteomic dataset from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcome. A novel multiplex immunohistochemistry antibody panel was used to audit T cell functionality and spatial localization in resected tumors from treatment-naive patients with localized pancreatic ductal adenocarcinoma (PDAC) compared to a second cohort of patients treated with neoadjuvant agonistic CD40 (αCD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both treatment cohorts were assayed, and more than 1,000 tumor microenvironment (TME) features were quantified. We then trained machine learning models to accurately predict αCD40 treatment status and disease-free survival (DFS) following αCD40 therapy based upon TME features. Through downstream interpretation of the machine learning models' predictions, we found αCD40 therapy to reduce canonical aspects of T cell exhaustion within the TME, as compared to treatment-naive TMEs. Using automated clustering approaches, we found improved DFS following αCD40 therapy to correlate with the increased presence of CD44+ CD4+ Th1 cells located specifically within cellular spatial neighborhoods characterized by increased T cell proliferation, antigen-experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of machine learning in molecular cancer immunology applications, highlight the impact of αCD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for αCD40-treated patients with PDAC.
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Affiliation(s)
- Katie E. Blise
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR USA
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
| | - Shamilene Sivagnanam
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Courtney B. Betts
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
- Current affiliation: Akoya Biosciences, 100 Campus Drive, 6th Floor, Marlborough, MA USA
| | - Konjit Betre
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Nell Kirchberger
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Benjamin Tate
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Immune Monitoring and Cancer Omics Services, Oregon Health & Science University, Portland, OR USA
| | - Emma E. Furth
- Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Andressa Dias Costa
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA
| | - Jonathan A. Nowak
- Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA USA
| | - Brian M. Wolpin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA
| | - Robert H. Vonderheide
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
- Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Jeremy Goecks
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR USA
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Current affiliation: Department of Machine Learning, H. Lee Moffitt Cancer Center, Tampa, FL USA
- Current affiliation: Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center, Tampa, FL USA
| | - Lisa M. Coussens
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
| | - Katelyn T. Byrne
- The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
- Lead contact
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3
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Doha ZO, Wang X, Calistri NL, Eng J, Daniel CJ, Ternes L, Kim EN, Pelz C, Munks M, Betts C, Kwon S, Bucher E, Li X, Waugh T, Tatarova Z, Blumberg D, Ko A, Kirchberger N, Pietenpol JA, Sanders ME, Langer EM, Dai MS, Mills G, Chin K, Chang YH, Coussens LM, Gray JW, Heiser LM, Sears RC. MYC Deregulation and PTEN Loss Model Tumor and Stromal Heterogeneity of Aggressive Triple-Negative Breast Cancer. Nat Commun 2023; 14:5665. [PMID: 37704631 PMCID: PMC10499828 DOI: 10.1038/s41467-023-40841-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 08/14/2023] [Indexed: 09/15/2023] Open
Abstract
Triple-negative breast cancer (TNBC) patients have a poor prognosis and few treatment options. Mouse models of TNBC are important for development of new therapies, however, few mouse models represent the complexity of TNBC. Here, we develop a female TNBC murine model by mimicking two common TNBC mutations with high co-occurrence: amplification of the oncogene MYC and deletion of the tumor suppressor PTEN. This Myc;Ptenfl model develops heterogeneous triple-negative mammary tumors that display histological and molecular features commonly found in human TNBC. Our research involves deep molecular and spatial analyses on Myc;Ptenfl tumors including bulk and single-cell RNA-sequencing, and multiplex tissue-imaging. Through comparison with human TNBC, we demonstrate that this genetic mouse model develops mammary tumors with differential survival and therapeutic responses that closely resemble the inter- and intra-tumoral and microenvironmental heterogeneity of human TNBC, providing a pre-clinical tool for assessing the spectrum of patient TNBC biology and drug response.
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Affiliation(s)
- Zinab O Doha
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
- Department of medical laboratory technology, Taibah University, Al-Madinah al-Munawwarah, Saudi Arabia
| | - Xiaoyan Wang
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Nicholas L Calistri
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Jennifer Eng
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
| | - Colin J Daniel
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Luke Ternes
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Eun Na Kim
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
| | - Carl Pelz
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR, USA
| | - Michael Munks
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR, USA
- Department of Molecular Microbiology and Immunology, Oregon Health and Science University, Portland, OR, USA
| | - Courtney Betts
- Department of Cell, Developmental & Cancer Biology, Oregon Health and Science University, Portland, OR, USA
| | - Sunjong Kwon
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
| | - Elmar Bucher
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
| | - Xi Li
- Division of Oncologic Sciences, Oregon Health and Science University, Portland, OR, USA
| | - Trent Waugh
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Zuzana Tatarova
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
| | - Dylan Blumberg
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
| | - Aaron Ko
- Department of Molecular Microbiology and Immunology, Oregon Health and Science University, Portland, OR, USA
| | - Nell Kirchberger
- Department of Cell, Developmental & Cancer Biology, Oregon Health and Science University, Portland, OR, USA
| | - Jennifer A Pietenpol
- Department of Biochemistry, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Melinda E Sanders
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ellen M Langer
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Mu-Shui Dai
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Gordon Mills
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR, USA
- Division of Oncologic Sciences, Oregon Health and Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Koei Chin
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Young Hwan Chang
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Lisa M Coussens
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR, USA
- Department of Cell, Developmental & Cancer Biology, Oregon Health and Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Joe W Gray
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Laura M Heiser
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
- OHSU Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Rosalie C Sears
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA.
- Brenden-Colson Center for Pancreatic Care, Oregon Health & Science University, Portland, OR, USA.
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
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4
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Sivagnanam S, Betts CM, Kirchberger N, Betre K, Coussens LM. Abstract 4293: Strategies and resources for applying a quantitative multiplex IHC imaging workflow to characterize immune contexture in solid tumors. Cancer Res 2023. [DOI: 10.1158/1538-7445.am2023-4293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
Abstract
Conventional immunohistochemistry (IHC) is a standardized diagnostic technique used in tissue pathology. However, the capacity to label only one marker per tissue section is a critical limitation. Multiplex immunohistochemistry (mIHC) is a powerful imaging technique used in basic, translational research and clinical settings to simultaneously detect the expression of multiple epitopes in a single formalin-fixed paraffin-embedded (FFPE) tissue section, allowing for characterization and quantification of cells while maintaining their spatial location. This technique allows for a comprehensive view of the immune milieu, expression patterns, and interactions between cell types that can help elucidate the complexity of the tumor-immune microenvironment (TiME). Multiplex imaging has emerged as a powerful tool to better understand tumor progression, response or resistance to therapy, and potentially identify predictive biomarkers. However, this technique requires careful tissue considerations and generates enormous amounts of hierarchical data, including single cell marker expressions, locations, and shape features, resulting in complex and challenging analyses. We previously published a validated platform using nine matched primary and recurrent head and neck squamous cell carcinoma (HNSCC) sections stained sequentially with a panel of 29 antibodies identifying malignant tumor cells, and 17 distinct leukocyte lineages and their functional states1. Here, we have optimized and consolidated important considerations, including tissue quality and QC steps necessary for generating high quality data from multiplex imaging studies. We demonstrate strategies for a streamline analytic pipeline using our quantitative workflow developed to characterize immune cells and infiltration patterns within spatial compartments of solid tumors in FFPE tissues, and herein, provide strategies and resources to practically adapt and utilize our analytic mIHC pipeline.
1. Banik, G., et al., Methods Enzymol., 2020
Citation Format: Shamilene Sivagnanam, Courtney M. Betts, Nell Kirchberger, Konjit Betre, Lisa M. Coussens. Strategies and resources for applying a quantitative multiplex IHC imaging workflow to characterize immune contexture in solid tumors. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4293.
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5
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Afshinnekoo E, Meydan C, Chowdhury S, Jaroudi D, Boyer C, Bernstein N, Maritz JM, Reeves D, Gandara J, Chhangawala S, Ahsanuddin S, Simmons A, Nessel T, Sundaresh B, Pereira E, Jorgensen E, Kolokotronis SO, Kirchberger N, Garcia I, Gandara D, Dhanraj S, Nawrin T, Saletore Y, Alexander N, Vijay P, Hénaff EM, Zumbo P, Walsh M, O'Mullan GD, Tighe S, Dudley JT, Dunaif A, Ennis S, O'Halloran E, Magalhaes TR, Boone B, Jones AL, Muth TR, Paolantonio KS, Alter E, Schadt EE, Garbarino J, Prill RJ, Carlton JM, Levy S, Mason CE. Modern Methods for Delineating Metagenomic Complexity. Cell Syst 2015; 1:6-7. [PMID: 27135684 DOI: 10.1016/j.cels.2015.07.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2015] [Revised: 07/16/2015] [Accepted: 07/16/2015] [Indexed: 01/31/2023]
Affiliation(s)
- Ebrahim Afshinnekoo
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; School of Earth and Environmental Sciences, City University of New York (CUNY) Queens College, Flushing, NY 11367, USA
| | - Cem Meydan
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Shanin Chowdhury
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; CUNY Hunter College, New York 10065, NY, USA
| | - Dyala Jaroudi
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Collin Boyer
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Nick Bernstein
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Julia M Maritz
- Center for Genomics, New York University, New York, NY 10065, USA
| | - Darryl Reeves
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; Tri-Institutional Program on Computational Biology and Medicine (CBM), New York, NY Center for Genomics, USA
| | - Jorge Gandara
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Sagar Chhangawala
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Sofia Ahsanuddin
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; Department of Biology, CUNY Brooklyn College, Brooklyn, NY 11210, USA
| | - Amber Simmons
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | | | | | | | | | | | - Nell Kirchberger
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Isaac Garcia
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - David Gandara
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Sean Dhanraj
- Department of Biology, CUNY Brooklyn College, Brooklyn, NY 11210, USA
| | - Tanzina Nawrin
- Department of Biology, CUNY Brooklyn College, Brooklyn, NY 11210, USA
| | - Yogesh Saletore
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; Tri-Institutional Program on Computational Biology and Medicine (CBM), New York, NY Center for Genomics, USA
| | - Noah Alexander
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Priyanka Vijay
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; Tri-Institutional Program on Computational Biology and Medicine (CBM), New York, NY Center for Genomics, USA
| | - Elizabeth M Hénaff
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Paul Zumbo
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Michael Walsh
- State University of New York, Downstate, Brooklyn, NY 11203, USA
| | - Gregory D O'Mullan
- School of Earth and Environmental Sciences, City University of New York (CUNY) Queens College, Flushing, NY 11367, USA
| | - Scott Tighe
- University of Vermont, Burlington, VT 05405, USA
| | - Joel T Dudley
- Icahn School of Medicine at Mount Sinai, New York, NY, 10029 USA
| | - Anya Dunaif
- Rockefeller University, New York, NY 10065, USA
| | - Sean Ennis
- National Children's Research Centre, Our Lady's Children's Hospital, Dublin 12, Ireland; Academic Centre on Rare Diseases, School of Medicine and Medical Science, University College, Dublin 12, Ireland
| | - Eoghan O'Halloran
- National Children's Research Centre, Our Lady's Children's Hospital, Dublin 12, Ireland
| | - Tiago R Magalhaes
- Academic Centre on Rare Diseases, School of Medicine and Medical Science, University College, Dublin 12, Ireland
| | - Braden Boone
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Angela L Jones
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Theodore R Muth
- Department of Biology, CUNY Brooklyn College, Brooklyn, NY 11210, USA
| | | | | | - Eric E Schadt
- Icahn School of Medicine at Mount Sinai, New York, NY, 10029 USA
| | | | - Robert J Prill
- Accelerated Discovery Lab, IBM Almaden Research Center, San Jose, CA 95120, USA
| | - Jane M Carlton
- Center for Genomics, New York University, New York, NY 10065, USA
| | - Shawn Levy
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA; The Feil Family Brain and Mind Research Institute, New York, NY 10065, USA.
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Afshinnekoo E, Meydan C, Chowdhury S, Jaroudi D, Boyer C, Bernstein N, Maritz JM, Reeves D, Gandara J, Chhangawala S, Ahsanuddin S, Simmons A, Nessel T, Sundaresh B, Pereira E, Jorgensen E, Kolokotronis SO, Kirchberger N, Garcia I, Gandara D, Dhanraj S, Nawrin T, Saletore Y, Alexander N, Vijay P, Hénaff EM, Zumbo P, Walsh M, O'Mullan GD, Tighe S, Dudley JT, Dunaif A, Ennis S, O'Halloran E, Magalhaes TR, Boone B, Jones AL, Muth TR, Paolantonio KS, Alter E, Schadt EE, Garbarino J, Prill RJ, Carlton JM, Levy S, Mason CE. Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics. Cell Syst 2015; 1:97-97.e3. [PMID: 27135689 DOI: 10.1016/j.cels.2015.07.006] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Afshinnekoo E, Meydan C, Chowdhury S, Jaroudi D, Boyer C, Bernstein N, Maritz JM, Reeves D, Gandara J, Chhangawala S, Ahsanuddin S, Simmons A, Nessel T, Sundaresh B, Pereira E, Jorgensen E, Kolokotronis SO, Kirchberger N, Garcia I, Gandara D, Dhanraj S, Nawrin T, Saletore Y, Alexander N, Vijay P, Hénaff EM, Zumbo P, Walsh M, O'Mullan GD, Tighe S, Dudley JT, Dunaif A, Ennis S, O'Halloran E, Magalhaes TR, Boone B, Jones AL, Muth TR, Paolantonio KS, Alter E, Schadt EE, Garbarino J, Prill RJ, Carlton JM, Levy S, Mason CE. Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics. Cell Syst 2015; 1:72-87. [PMID: 26594662 PMCID: PMC4651444 DOI: 10.1016/j.cels.2015.01.001] [Citation(s) in RCA: 176] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for harmless genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can reveal a station’s history, such as marine-associated bacteria in a hurricane-flooded station. Some evidence of pathogens was found (Bacillus anthracis), but a lack of reported cases in NYC suggests that the pathogens represent a normal, urban microbiome. This baseline metagenomic map of NYC could help long-term disease surveillance, bioterrorism threat mitigation, and health management in the built environment of cities.
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Affiliation(s)
- Ebrahim Afshinnekoo
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA ; School of Earth and Environmental Sciences, City University of New York (CUNY) Queens College, Flushing, NY 11367, USA
| | - Cem Meydan
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Shanin Chowdhury
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA ; CUNY Hunter College, New York, NY 10065, USA
| | - Dyala Jaroudi
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Collin Boyer
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Nick Bernstein
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Julia M Maritz
- Center for Genomics, New York University, New York, NY 10003, USA
| | - Darryl Reeves
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA ; Tri-Institutional Program on Computational Biology and Medicine (CBM), New York, NY 10065, USA
| | - Jorge Gandara
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Sagar Chhangawala
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Sofia Ahsanuddin
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA ; CUNY Brooklyn College, Department of Biology, Brooklyn, NY 11210, USA
| | - Amber Simmons
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | | | | | | | | | | | - Nell Kirchberger
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Isaac Garcia
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - David Gandara
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Sean Dhanraj
- CUNY Brooklyn College, Department of Biology, Brooklyn, NY 11210, USA
| | - Tanzina Nawrin
- CUNY Brooklyn College, Department of Biology, Brooklyn, NY 11210, USA
| | - Yogesh Saletore
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA ; Tri-Institutional Program on Computational Biology and Medicine (CBM), New York, NY 10065, USA
| | - Noah Alexander
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Priyanka Vijay
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA ; Tri-Institutional Program on Computational Biology and Medicine (CBM), New York, NY 10065, USA
| | - Elizabeth M Hénaff
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Paul Zumbo
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Michael Walsh
- State University of New York, Downstate, Brooklyn, NY 11203, USA
| | - Gregory D O'Mullan
- School of Earth and Environmental Sciences, City University of New York (CUNY) Queens College, Flushing, NY 11367, USA
| | - Scott Tighe
- University of Vermont, Burlington, VT 05405, USA
| | - Joel T Dudley
- Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Anya Dunaif
- Rockefeller University, New York, NY 10065, USA
| | - Sean Ennis
- Academic Centre on Rare Diseases, School of Medicine and Medical Science, University College Dublin 4, Ireland ; National Centre for Medical Genetics, Our Lady's Children's Hospital, Dublin 12, Ireland
| | - Eoghan O'Halloran
- Academic Centre on Rare Diseases, School of Medicine and Medical Science, University College Dublin 4, Ireland
| | - Tiago R Magalhaes
- Academic Centre on Rare Diseases, School of Medicine and Medical Science, University College Dublin 4, Ireland ; National Centre for Medical Genetics, Our Lady's Children's Hospital, Dublin 12, Ireland
| | - Braden Boone
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Angela L Jones
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Theodore R Muth
- CUNY Brooklyn College, Department of Biology, Brooklyn, NY 11210, USA
| | | | | | - Eric E Schadt
- Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Robert J Prill
- Accelerated Discovery Lab, IBM Almaden Research Center, San Jose, CA 95120, USA
| | - Jane M Carlton
- Center for Genomics, New York University, New York, NY 10003, USA
| | - Shawn Levy
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA ; The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10065, USA ; The Feil Family Brain and Mind Research Institute, New York, NY 10065, USA
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