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Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes

Discordant abundances of different immune cell subtypes is regarded to be an essential feature of tumour tissue. Direct studies in Prostate cancer (PC) of intratumoral immune heterogeneity characterized by immune cell subtype, are still lacking. Using the single sample gene set enrichment analysis (...

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Autores principales: Han, Jianpeng, Zhou, Yan, Zhang, Chundong, Feng, Jianyong, Wang, Junhao, Guo, Kuo, Chen, Wenbin, Li, Yongzhang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9806298/
https://www.ncbi.nlm.nih.gov/pubmed/36524848
http://dx.doi.org/10.1111/jcmm.17641
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author Han, Jianpeng
Zhou, Yan
Zhang, Chundong
Feng, Jianyong
Wang, Junhao
Guo, Kuo
Chen, Wenbin
Li, Yongzhang
author_facet Han, Jianpeng
Zhou, Yan
Zhang, Chundong
Feng, Jianyong
Wang, Junhao
Guo, Kuo
Chen, Wenbin
Li, Yongzhang
author_sort Han, Jianpeng
collection PubMed
description Discordant abundances of different immune cell subtypes is regarded to be an essential feature of tumour tissue. Direct studies in Prostate cancer (PC) of intratumoral immune heterogeneity characterized by immune cell subtype, are still lacking. Using the single sample gene set enrichment analysis (ssGSEA) algorithm, the abundance of 28 immune cells infiltration (ICI) were determined for PC. A NMF was performed to determine tumour‐sample clustering based on the abundance of ICI and PFS information. Hub genes of clusters were identified via weighted gene co‐expression network analysis (WGCNA). The multivariate dimensionality reduction analysis of hub genes expression matrix was carried out via principal component analysis (PCA) to obtain immune score (IS). We analysed the correlation between clustering, IS and clinical phenotype. We divided the 495 patients into clusterA (n = 193) and clusterB (n = 302) on the basis of ICI and PFS via NMF. The progression‐free survival (PFS) were better for clusterA than for clusterB (p < 0.001). Each immune cell subtypes was more abundant in clusterA than in clusterB (p < 0.001). The expression levels of CTAL‐4 and PD‐L1 were lower in clusterB than in clusterA (p < 0.001 and p = 0.006). We obtained 103 hub genes via WGCNA. In the training and validation cohorts, the prognosis of high IS group was worse than that of the low IS group (p < 0.05). IS had good predictive effect on 5‐year PFS. The expression of immune checkpoint genes was higher in the low IS group than in the high IS group (p < 0.01). Patients with low IS and receiving hormone therapy had better prognosis than other groups. The combination of IS and clinical characteristics including lymph node metastasis and gleason score can better differentiate patient outcomes than using it alone. IS was a practical algorithm to predict the prognosis of patients. Advanced PC patients with low IS may be more sensitive to hormone therapy. CXCL10, CXCL5, MMP1, CXCL12, CXCL11, CXCL2, STAT1, IL‐6 and TLR2 were hub genes, which may drive the homing of immune cells in tumours and promote immune cell differentiation.
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spelling pubmed-98062982023-01-04 Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes Han, Jianpeng Zhou, Yan Zhang, Chundong Feng, Jianyong Wang, Junhao Guo, Kuo Chen, Wenbin Li, Yongzhang J Cell Mol Med Original Articles Discordant abundances of different immune cell subtypes is regarded to be an essential feature of tumour tissue. Direct studies in Prostate cancer (PC) of intratumoral immune heterogeneity characterized by immune cell subtype, are still lacking. Using the single sample gene set enrichment analysis (ssGSEA) algorithm, the abundance of 28 immune cells infiltration (ICI) were determined for PC. A NMF was performed to determine tumour‐sample clustering based on the abundance of ICI and PFS information. Hub genes of clusters were identified via weighted gene co‐expression network analysis (WGCNA). The multivariate dimensionality reduction analysis of hub genes expression matrix was carried out via principal component analysis (PCA) to obtain immune score (IS). We analysed the correlation between clustering, IS and clinical phenotype. We divided the 495 patients into clusterA (n = 193) and clusterB (n = 302) on the basis of ICI and PFS via NMF. The progression‐free survival (PFS) were better for clusterA than for clusterB (p < 0.001). Each immune cell subtypes was more abundant in clusterA than in clusterB (p < 0.001). The expression levels of CTAL‐4 and PD‐L1 were lower in clusterB than in clusterA (p < 0.001 and p = 0.006). We obtained 103 hub genes via WGCNA. In the training and validation cohorts, the prognosis of high IS group was worse than that of the low IS group (p < 0.05). IS had good predictive effect on 5‐year PFS. The expression of immune checkpoint genes was higher in the low IS group than in the high IS group (p < 0.01). Patients with low IS and receiving hormone therapy had better prognosis than other groups. The combination of IS and clinical characteristics including lymph node metastasis and gleason score can better differentiate patient outcomes than using it alone. IS was a practical algorithm to predict the prognosis of patients. Advanced PC patients with low IS may be more sensitive to hormone therapy. CXCL10, CXCL5, MMP1, CXCL12, CXCL11, CXCL2, STAT1, IL‐6 and TLR2 were hub genes, which may drive the homing of immune cells in tumours and promote immune cell differentiation. John Wiley and Sons Inc. 2022-12-16 /pmc/articles/PMC9806298/ /pubmed/36524848 http://dx.doi.org/10.1111/jcmm.17641 Text en © 2022 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Han, Jianpeng
Zhou, Yan
Zhang, Chundong
Feng, Jianyong
Wang, Junhao
Guo, Kuo
Chen, Wenbin
Li, Yongzhang
Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes
title Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes
title_full Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes
title_fullStr Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes
title_full_unstemmed Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes
title_short Intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes
title_sort intratumoral immune heterogeneity of prostate cancer characterized by typing and hub genes
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9806298/
https://www.ncbi.nlm.nih.gov/pubmed/36524848
http://dx.doi.org/10.1111/jcmm.17641
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