Differences of the immune cell landscape between normal and tumor tissue in human prostate

Zhang, Erdong; Dai, Fang; Mao, Yiming; He, Wei; Liu, F.; Ma, Wenbin; Qiao, Yiting

doi:10.1007/s12094-019-02128-5

Cited by 25 publications

(23 citation statements)

References 38 publications

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“…With the development of microarray and high-throughput sequencing technologies, estimation of cell proportions from bulk tissues can be performed using genomics data via bioinformatics techniques (Shen-Orr and Gaujoux, 2013). Celltype Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) is a deconvolution algorithm that can analyze 22 distinct immune-cell subsets in complex tissues based on normalized bulk transcriptome profiles (Newman et al, 2015)and has been successfully used in different types of cancer (Peng et al, 2019;Yang et al, 2019;Zhang et al, 2019), as well as non-tumor diseases such as idiopathic pulmonary fibrosis and systemic lupus erythematosus (Liu et al, 2018;Panousis et al, 2019). In 2019, the developer of CIBERSORT introduced an updated version (CIBERSORTx) that provides more accurate portraits of tissue composition based on cell-expression signatures via single-cell experiments (Newman et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Identification of Immune Cell Landscape and Construction of a Novel Diagnostic Nomogram for Crohn’s Disease

Chen

Yuan

et al. 2020

Front. Genet.

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Crohn's disease (CD) has an increasing incidence and prevalence worldwide. The etiology of CD remains unclear and there is no gold standard for diagnosis. The dysregulated immune response and different infiltration status of immune cells are critical for CD pathogenesis; therefore, it is important to provide an overview of immunecell alterations in CD and explore a novel method for auxiliary diagnosis. Here we analyzed microarray datasets from Gene Expression Omnibus (GEO), and an extended version of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORTx) was utilized to estimate the fraction of 22 types of immune cells. Differentially expressed genes (DEGs) and a protein-protein interaction (PPI) network were identified, and we performed gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) to identify differentially regulated pathways in CD. Least absolute shrinkage and selection operator (LASSO) regression was conducted to filter features, and a diagnostic nomogram based on logistic regression was built and validated in an independent validation cohort. In the derivation cohort, we found a proportion of 17 immune-cell types to be significantly altered between CD and healthy controls and a total of 150 DEGs were identified, which were mostly related to the immune response. Among the 15 hub genes based on the PPI network, C-X-C chemokine ligand 8 (CXCL8) and interleukin-1B (IL-1B) showed the highest degree of interaction. Additionally, GSEA and GSVA identified five significantly enriched pathways, among which the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway was critical in the CD development. Furthermore, six variables comprising of CXCL8, IL-1B, M1 macrophages, regulatory T cells, CD8 + T cells, and plasma cells were identified by LASSO regression and incorporated into a logistic regression model. The nomogram displayed a good prediction, with a 0.915 area under the receiver operating curve (AUC) and a C-index of 0.915 [95% confidence interval (CI): 0.875-0.955]. Similar results were found in the validation cohort, with an AUC of 0.884 and a 0.884 C-index (95% CI: 0.843-0.924). These results provide novel in silico insight into cellular and molecular characteristics of CD and potential biomarkers for diagnosis and targeted therapy.

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Section: Introductionmentioning

confidence: 99%

Identification of Immune Cell Landscape and Construction of a Novel Diagnostic Nomogram for Crohn’s Disease

Chen

Yuan

et al. 2020

Front. Genet.

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“…In human bladder cancer, increased infiltration of tumor associated macrophages has been showed to be associated with the poor clinical prognosis [27]. Some researcher suggested that targeting macrophage may be a promising strategy for anticancer therapy [28,29]. Our analyses revealed t a high level of macrophages M0 and M1 existed in BLCA.…”

Section: Discussionmentioning

confidence: 61%

Immune Cell Infiltration in Bladder Cancer

Liu

et al. 2019

Preprint

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Background Bladder cancer is one of the most common malignant diseases with high recurrence rates worldwide. Although immunotherapy has been applied in bladder cancer for a long period of time, the tumor-infiltrating immune cells (TIICs) in bladder cancer has not been systematical investigated. Methods CIBERSORT, a versatile computational method for quantifying cell fractions from bulk tissue gene expression profiles (GEPs), was applied to calculate the TIICs fraction proportion in normal bladder tissues and in bladder cancer tissues with the TCGA data. Results compared to normal bladder tissue, B cells naïve, T cells CD4 memory resting and Mast cells resting fractions proportion decreased, and NK resting, macrophages M0 and macrophages M1 increased. In BLCAs tissue, pro-tumorigenic related immune cells were negatively correlated with anti-tumor immune cells. New tumor with locoregional had high fraction proportion of macrophages M0 and macrophages M1. Dendritic cells activated, Monocytes, macrophages M1, Tregs and T cells follicular helper significantly increased in low grade BLCAs. Tregs had a high proportion in BLCAs patients accepted low radiation dose. Conclusions This study indicates that macrophages M2 and Tregs could be the promising immunotherapy targets combined radiotherapy in BLCAs. The result provides valuable information to understand the immunity status in BLCAs.

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“…The infiltration of cell types such as monocyte-derived cell populations has previously been shown to be linked to the extent of proliferative inflammatory atrophy lesions, chronic prostatic inflammation and cancer gradehttps://paperpile.com/c/ BQQ95X/GLf0R [88]. In prostate cancer, specific and overall survival analyses have identified an elevated monocyte count as an independent prognostic factor for poor outcomehttps://paperpile.com/c/BQQ95X/vyBlX+ pxdwu+xaA8T+2mcuI [89][90][91][92]. Furthermore, the infiltration of tumour-associated macrophages in prostate needle biopsy specimens has been shown to have potential as a predictive factor for PSA failure or disease progression after hormonal therapyhttps://paperpile.com/c/ BQQ95X/eaIrr [93].…”

Section: Discussionmentioning

confidence: 99%

Transcriptome sequencing and multi-plex imaging of prostate cancer microenvironment reveals a dominant role for monocytic cells in progression

Mangiola

Modrák

Souza-Fonseca-Guimarães

et al. 2021

BMC Cancer

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Background Prostate cancer is caused by genomic aberrations in normal epithelial cells, however clinical translation of findings from analyses of cancer cells alone has been very limited. A deeper understanding of the tumour microenvironment is needed to identify the key drivers of disease progression and reveal novel therapeutic opportunities. Results In this study, the experimental enrichment of selected cell-types, the development of a Bayesian inference model for continuous differential transcript abundance, and multiplex immunohistochemistry permitted us to define the transcriptional landscape of the prostate cancer microenvironment along the disease progression axis. An important role of monocytes and macrophages in prostate cancer progression and disease recurrence was uncovered, supported by both transcriptional landscape findings and by differential tissue composition analyses. These findings were corroborated and validated by spatial analyses at the single-cell level using multiplex immunohistochemistry. Conclusions This study advances our knowledge concerning the role of monocyte-derived recruitment in primary prostate cancer, and supports their key role in disease progression, patient survival and prostate microenvironment immune modulation.

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Differences of the immune cell landscape between normal and tumor tissue in human prostate

Cited by 25 publications

References 38 publications

Identification of Immune Cell Landscape and Construction of a Novel Diagnostic Nomogram for Crohn’s Disease

Identification of Immune Cell Landscape and Construction of a Novel Diagnostic Nomogram for Crohn’s Disease

Immune Cell Infiltration in Bladder Cancer

Transcriptome sequencing and multi-plex imaging of prostate cancer microenvironment reveals a dominant role for monocytic cells in progression

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