Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing
As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed signific...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Journal of Pathology Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2153353923001669 |
| _version_ | 1797389468045410304 |
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| author | Rahul Rajendran Rachel C. Beck Morteza M. Waskasi Brian D. Kelly Daniel R. Bauer |
| author_facet | Rahul Rajendran Rachel C. Beck Morteza M. Waskasi Brian D. Kelly Daniel R. Bauer |
| author_sort | Rahul Rajendran |
| collection | DOAJ |
| description | As our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth. |
| first_indexed | 2024-03-08T22:57:23Z |
| format | Article |
| id | doaj.art-4dfc280073cd4d4eb54f1d744cd852b9 |
| institution | Directory Open Access Journal |
| issn | 2153-3539 |
| language | English |
| last_indexed | 2024-03-08T22:57:23Z |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Pathology Informatics |
| spelling | doaj.art-4dfc280073cd4d4eb54f1d744cd852b92023-12-16T06:06:55ZengElsevierJournal of Pathology Informatics2153-35392024-12-0115100352Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexingRahul Rajendran0Rachel C. Beck1Morteza M. Waskasi2Brian D. Kelly3Daniel R. Bauer4Roche Diagnostics Solutions, (Ventana Medical Systems, Inc.), Tucson, AZ, USARoche Diagnostics Solutions, (Ventana Medical Systems, Inc.), Tucson, AZ, USARoche Diagnostics Solutions, (Ventana Medical Systems, Inc.), Tucson, AZ, USARoche Diagnostics Solutions, (Ventana Medical Systems, Inc.), Tucson, AZ, USACorresponding author.; Roche Diagnostics Solutions, (Ventana Medical Systems, Inc.), Tucson, AZ, USAAs our understanding of the tumor microenvironment grows, the pathology field is increasingly utilizing multianalyte diagnostic assays to understand important characteristics of tumor growth. In clinical settings, brightfield chromogenic assays represent the gold-standard and have developed significant trust as the first-line diagnostic method. However, conventional brightfield tests have been limited to low-order assays that are visually interrogated. We have developed a hybrid method of brightfield chromogenic multiplexing that overcomes these limitations and enables high-order multiplex assays. However, how compatible high-order brightfield multiplexed images are with advanced analytical algorithms has not been extensively evaluated. In the present study, we address this gap by developing a novel 6-marker prostate cancer assay that targets diverse aspects of the tumor microenvironment such as prostate-specific biomarkers (PSMA and p504s), immune biomarkers (CD8 and PD-L1), a prognostic biomarker (Ki-67), as well as an adjunctive diagnostic biomarker (basal cell cocktail) and apply the assay to 143 differentially graded adenocarcinoma prostate tissues. The tissues were then imaged on our spectroscopic multiplexing imaging platform and mined for proteomic and spatial features that were correlated with cancer presence and disease grade. Extracted features were used to train a UMAP model that differentiated healthy from cancerous tissue with an accuracy of 89% and identified clusters of cells based on cancer grade. For spatial analysis, cell-to-cell distances were calculated for all biomarkers and differences between healthy and adenocarcinoma tissues were studied. We report that p504s positive cells were at least 2× closer to cells expressing PD-L1, CD8, Ki-67, and basal cell in adenocarcinoma tissues relative to the healthy control tissues. These findings offer a powerful insight to understand the fingerprint of the prostate tumor microenvironment and indicate that high-order chromogenic multiplexing is compatible with digital analysis. Thus, the presented chromogenic multiplexing system combines the clinical applicability of brightfield assays with the emerging diagnostic power of high-order multiplexing in a digital pathology friendly format that is well-suited for translational studies to better understand mechanisms of tumor development and growth.http://www.sciencedirect.com/science/article/pii/S2153353923001669Artificial intelligenceTumor immune microenvironmentImagingSpectroscopyPhenotypingImmunotherapy |
| spellingShingle | Rahul Rajendran Rachel C. Beck Morteza M. Waskasi Brian D. Kelly Daniel R. Bauer Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing Journal of Pathology Informatics Artificial intelligence Tumor immune microenvironment Imaging Spectroscopy Phenotyping Immunotherapy |
| title | Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing |
| title_full | Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing |
| title_fullStr | Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing |
| title_full_unstemmed | Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing |
| title_short | Digital analysis of the prostate tumor microenvironment with high-order chromogenic multiplexing |
| title_sort | digital analysis of the prostate tumor microenvironment with high order chromogenic multiplexing |
| topic | Artificial intelligence Tumor immune microenvironment Imaging Spectroscopy Phenotyping Immunotherapy |
| url | http://www.sciencedirect.com/science/article/pii/S2153353923001669 |
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