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Forjaz A, Vaz E, Romero VM, Joshi S, Braxton AM, Jiang AC, Fujikura K, Cornish T, Hong SM, Hruban RH, Wu PH, Wood LD, Kiemen AL, Wirtz D. Three-dimensional assessments are necessary to determine the true, spatially-resolved composition of tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.04.569986. [PMID: 38106231 PMCID: PMC10723352 DOI: 10.1101/2023.12.04.569986] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Methods for spatially resolved cellular profiling using thinly cut sections have enabled in-depth quantitative tissue mapping to study inter-sample and intra-sample differences in normal human anatomy and disease onset and progression. These methods often profile extremely limited regions, which may impact the evaluation of heterogeneity due to tissue sub-sampling. Here, we applied CODA, a deep learning-based tissue mapping platform, to reconstruct the three-dimensional (3D) microanatomy of grossly normal and cancer-containing human pancreas biospecimens obtained from individuals who underwent pancreatic resection. To compare inter- and intra-sample heterogeneity, we assessed bulk and spatially resolved tissue composition in a cohort of two-dimensional (2D) whole slide images (WSIs) and a cohort of thick slabs of pancreas tissue that were digitally reconstructed in 3D from serial sections. To demonstrate the marked under sampling of 2D assessments, we simulated the number of WSIs and tissue microarrays (TMAs) necessary to represent the compositional heterogeneity of 3D data within 10% error to reveal that tens of WSIs and hundreds of TMA cores are sometimes needed. We show that spatial correlation of different pancreatic structures decay significantly within a span of microns, demonstrating that 2D histological sections may not be representative of their neighboring tissues. In sum, we demonstrate that 3D assessments are necessary to accurately assess tissue composition in normal and abnormal specimens and in order to accurately determine neoplastic content. These results emphasize the importance of intra-sample heterogeneity in tissue mapping efforts.
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Affiliation(s)
- André Forjaz
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD
| | - Eduarda Vaz
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD
| | - Valentina Matos Romero
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD
| | - Saurabh Joshi
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD
| | - Alicia M. Braxton
- Department of Comparative Medicine, Medical University of South Carolina, Charleston, SC
| | - Ann C. Jiang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
| | - Kohei Fujikura
- Department of Medical Genetics, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada
| | - Toby Cornish
- Department of Pathology, University of Colorado School of Medicine, Aurora, CO
| | - Seung-Mo Hong
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Ralph H. Hruban
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD
| | - Pei-Hsun Wu
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD
- The Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD
| | - Laura D. Wood
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD
| | - Ashley L. Kiemen
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD
- The Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD
| | - Denis Wirtz
- Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD
- Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD
- The Johns Hopkins Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD
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Gallagher RI, Wulfkuhle J, Wolf DM, Brown-Swigart L, Yau C, O'Grady N, Basu A, Lu R, Campbell MJ, Magbanua MJ, Coppé JP, Asare SM, Sit L, Matthews JB, Perlmutter J, Hylton N, Liu MC, Symmans WF, Rugo HS, Isaacs C, DeMichele AM, Yee D, Pohlmann PR, Hirst GL, Esserman LJ, van 't Veer LJ, Petricoin EF. Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial. Cell Rep Med 2023; 4:101312. [PMID: 38086377 PMCID: PMC10772394 DOI: 10.1016/j.xcrm.2023.101312] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 07/03/2023] [Accepted: 11/14/2023] [Indexed: 12/22/2023]
Abstract
Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.
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Affiliation(s)
- Rosa I Gallagher
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA 20110, USA.
| | - Julia Wulfkuhle
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA 20110, USA.
| | - Denise M Wolf
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Lamorna Brown-Swigart
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Christina Yau
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Nicholas O'Grady
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Amrita Basu
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Ruixiao Lu
- Quantum Leap Healthcare Collaborative, San Francisco, CA 94118, USA
| | - Michael J Campbell
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Mark J Magbanua
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jean-Philippe Coppé
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Smita M Asare
- Quantum Leap Healthcare Collaborative, San Francisco, CA 94118, USA
| | - Laura Sit
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Jeffrey B Matthews
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | | | - Nola Hylton
- Department of Radiology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Minetta C Liu
- Department of Surgery, Mayo Clinic, Rochester, MN 55905, USA
| | - W Fraser Symmans
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Hope S Rugo
- Division of Hematology/Oncology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Claudine Isaacs
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20007, USA
| | - Angela M DeMichele
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Douglas Yee
- Department of Medicine, University of Minnesota, Minneapolis, MN 55455, USA
| | - Paula R Pohlmann
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Gillian L Hirst
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Laura J Esserman
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Laura J van 't Veer
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Emanuel F Petricoin
- Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA 20110, USA.
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