2
|
Hessellund KB, Xu G, Guan Y, Waagepetersen R. Second‐order semi‐parametric inference for multivariate log Gaussian Cox processes. J R Stat Soc Ser C Appl Stat 2021. [DOI: 10.1111/rssc.12530] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
| | - Ganggang Xu
- Department of Management Science University of Miami Coral Gables Florida USA
| | - Yongtao Guan
- Department of Management Science University of Miami Coral Gables Florida USA
| | | |
Collapse
|
3
|
Hessellund KB, Xu G, Guan Y, Waagepetersen R. Semiparametric Multinomial Logistic Regression for Multivariate Point Pattern Data. J Am Stat Assoc 2021. [DOI: 10.1080/01621459.2020.1863812] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
| | - Ganggang Xu
- Department of Management Science, University of Miami, Coral Gables, FL
| | - Yongtao Guan
- Department of Management Science, University of Miami, Coral Gables, FL
| | | |
Collapse
|
4
|
Gong C, Anders RA, Zhu Q, Taube JM, Green B, Cheng W, Bartelink IH, Vicini P, Wang B, Popel AS. Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid Tumors. Front Oncol 2019; 8:649. [PMID: 30666298 PMCID: PMC6330341 DOI: 10.3389/fonc.2018.00649] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 12/10/2018] [Indexed: 11/13/2022] Open
Abstract
Quantitative characterization of the tumor microenvironment, including its immuno-architecture, is important for developing quantitative diagnostic and predictive biomarkers, matching patients to the most appropriate treatments for precision medicine, and for providing quantitative data for building systems biology computational models able to predict tumor dynamics in the context of immune checkpoint blockade therapies. The intra- and inter-tumoral spatial heterogeneities are potentially key to the understanding of the dose-response relationships, but they also bring challenges to properly parameterizing and validating such models. In this study, we developed a workflow to detect CD8+ T cells from whole slide imaging data, and quantify the spatial heterogeneity using multiple metrics by applying spatial point pattern analysis and morphometric analysis. The results indicate a higher intra-tumoral heterogeneity compared with the heterogeneity across patients. By comparing the baseline metrics with PD-1 blockade treatment outcome, our results indicate that the number of high-density T cell clusters of both circular and elongated shapes are higher in patients who responded to the treatment. This methodology can be applied to quantitatively characterize the tumor microenvironment, including immuno-architecture, and its heterogeneity for different cancer types.
Collapse
Affiliation(s)
- Chang Gong
- Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Robert A Anders
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Bloomberg-Kimmel Institute of Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Qingfeng Zhu
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Janis M Taube
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Dermatopathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Benjamin Green
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Dermatopathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Wenting Cheng
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
| | - Imke H Bartelink
- Clinical Pharmacology, Pharmacometrics and DMPK, MedImmune, Mountain View, CA, United States
| | - Paolo Vicini
- Clinical Pharmacology, Pharmacometrics and DMPK, MedImmune, Cambridge, United Kingdom
| | - Bing Wang
- Clinical Pharmacology, Pharmacometrics and DMPK, MedImmune, Mountain View, CA, United States
| | - Aleksander S Popel
- Department of Biomedical Engineering, School of Medicine, Johns Hopkins University, Baltimore, MD, United States.,Department of Oncology and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, United States
| |
Collapse
|