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Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer

The primary objective of this study is to detect biomarkers and develop models that enable the identification of clinically significant prostate cancer and to understand the biologic implications of the genes involved. Peripheral blood samples (1018 patients) were split chronologically into independ...

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Autores principales: Van Neste, Leander, Wojno, Kirk J., Henao, Ricardo, Mane, Shrikant, Korman, Howard, Hafron, Jason, Kernen, Kenneth, Tinawi-Aljundi, Rima, Putzi, Mathew, Kassis, Amin I., Kantoff, Philip W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8533765/
https://www.ncbi.nlm.nih.gov/pubmed/34685549
http://dx.doi.org/10.3390/cells10102567
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author Van Neste, Leander
Wojno, Kirk J.
Henao, Ricardo
Mane, Shrikant
Korman, Howard
Hafron, Jason
Kernen, Kenneth
Tinawi-Aljundi, Rima
Putzi, Mathew
Kassis, Amin I.
Kantoff, Philip W.
author_facet Van Neste, Leander
Wojno, Kirk J.
Henao, Ricardo
Mane, Shrikant
Korman, Howard
Hafron, Jason
Kernen, Kenneth
Tinawi-Aljundi, Rima
Putzi, Mathew
Kassis, Amin I.
Kantoff, Philip W.
author_sort Van Neste, Leander
collection PubMed
description The primary objective of this study is to detect biomarkers and develop models that enable the identification of clinically significant prostate cancer and to understand the biologic implications of the genes involved. Peripheral blood samples (1018 patients) were split chronologically into independent training (n = 713) and validation (n = 305) sets. Whole transcriptome RNA sequencing was performed on isolated phagocytic CD14+ and non-phagocytic CD2+ cells and their gene expression levels were used to develop predictive models that correlate to adverse pathologic features. The immune-transcriptomic model with the highest performance for predicting adverse pathology, based on a subtraction of the log-transformed expression signals of the two cell types, displayed an area under the curve (AUC) of the receiver operating characteristic of 0.70. The addition of biomarkers in combination with traditional clinical risk factors (age, serum prostate-specific antigen (PSA), PSA density, race, digital rectal examination (DRE), and family history) enhanced the AUC to 0.91 and 0.83 for the training and validation sets, respectively. The markers identified by this approach uncovered specific pathway associations relevant to (prostate) cancer biology. Increased phagocytic activity in conjunction with cancer-associated (mis-)regulation is also represented by these markers. Differential gene expression of circulating immune cells gives insight into the cellular immune response to early tumor development and immune surveillance.
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spelling pubmed-85337652021-10-23 Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer Van Neste, Leander Wojno, Kirk J. Henao, Ricardo Mane, Shrikant Korman, Howard Hafron, Jason Kernen, Kenneth Tinawi-Aljundi, Rima Putzi, Mathew Kassis, Amin I. Kantoff, Philip W. Cells Article The primary objective of this study is to detect biomarkers and develop models that enable the identification of clinically significant prostate cancer and to understand the biologic implications of the genes involved. Peripheral blood samples (1018 patients) were split chronologically into independent training (n = 713) and validation (n = 305) sets. Whole transcriptome RNA sequencing was performed on isolated phagocytic CD14+ and non-phagocytic CD2+ cells and their gene expression levels were used to develop predictive models that correlate to adverse pathologic features. The immune-transcriptomic model with the highest performance for predicting adverse pathology, based on a subtraction of the log-transformed expression signals of the two cell types, displayed an area under the curve (AUC) of the receiver operating characteristic of 0.70. The addition of biomarkers in combination with traditional clinical risk factors (age, serum prostate-specific antigen (PSA), PSA density, race, digital rectal examination (DRE), and family history) enhanced the AUC to 0.91 and 0.83 for the training and validation sets, respectively. The markers identified by this approach uncovered specific pathway associations relevant to (prostate) cancer biology. Increased phagocytic activity in conjunction with cancer-associated (mis-)regulation is also represented by these markers. Differential gene expression of circulating immune cells gives insight into the cellular immune response to early tumor development and immune surveillance. MDPI 2021-09-28 /pmc/articles/PMC8533765/ /pubmed/34685549 http://dx.doi.org/10.3390/cells10102567 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Van Neste, Leander
Wojno, Kirk J.
Henao, Ricardo
Mane, Shrikant
Korman, Howard
Hafron, Jason
Kernen, Kenneth
Tinawi-Aljundi, Rima
Putzi, Mathew
Kassis, Amin I.
Kantoff, Philip W.
Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer
title Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer
title_full Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer
title_fullStr Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer
title_full_unstemmed Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer
title_short Evaluation of an RNAseq-Based Immunogenomic Liquid Biopsy Approach in Early-Stage Prostate Cancer
title_sort evaluation of an rnaseq-based immunogenomic liquid biopsy approach in early-stage prostate cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8533765/
https://www.ncbi.nlm.nih.gov/pubmed/34685549
http://dx.doi.org/10.3390/cells10102567
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