Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data

Tian, Xi; Xu, Wenhao; Wang, Yuchen; Anwaier, Aihetaimujiang; Wang, Hongkai; Wan, Fangning; Zhu, Yu; Cao, Dalong; Shi, Guohai; Zhu, Yiping; Qu, Yuanyuan; Zhang, Ye; Ye, Dingwei

doi:10.1080/2162402x.2020.1784529

Cited by 32 publications

(26 citation statements)

References 40 publications

(39 reference statements)

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“…In this study, we utilized multiplatform immunogenomic deconvolution to detangle the role of MC tumor infiltration and signaling activity within ACC TME. Our findings are multifaceted in that they support previous research characterizing TIMC abundance as a favorable prognostic factor in ACC 9 . Our analysis dives deeper to identify the optimal degree of TIMCs in the ACC microenvironment, delineate prognostic pro- and anti-tumorigenic MC signaling genes, and lay a foundation for future mechanistic studies and the development of new therapeutic interventions.…”

Section: Discussionsupporting

confidence: 89%

“…This study does not include single-cell analysis and the expression of genes analyzed in this study are likely not entirely of MC origin. Instead, this study aims to identify the potential activity of (but not limited to) MCs that may underly the prognostic significance in ACC TME that has now been deemed consistent across multiple methods of immunogenomic and immunohistochemistry quantification 9 .…”

Section: Discussionmentioning

confidence: 99%

“…Current studies revealed that the function, prognostic value, and degree of tumor-infiltrating mast cell (TIMC) varies greatly with the type of tumor 8 . A recent study by Tian et al identified tumor mast cell infiltration (TMCI) to be associated with improved outcomes in ACC patients using CIBERSORT immunogenomic TIIC estimation of the TCGA database and validated the positive prognostic value of TIMCs in a single-center cohort 9 . Our study aims to further dissect MC activity within the ACC microenvironment by analyzing the expression of the MC signaling gene to characterize MC pro- and anti-tumor effects and offer new insights for potential therapeutic targets.…”

Section: Introductionmentioning

confidence: 98%

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Multiplatform Computational Analysis of Mast Cells in Adrenocortical Carcinoma Tumor Microenvironment

Baechle

Hanna

Sekhar

et al. 2021

Preprint

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Introduction: Immunotherapeutic response failure of adrenocortical carcinomas (ACC) highlights a need for novel strategies. Recent studies have alluded to tumor mast cell (MC) infiltration and improved patient outcomes. In this study, we examine MC activity within the ACC microenvironment to offer new insights for novel therapeutic targets. Methods: CIBERSORTx immunogenomic deconvolution of ACC tumors (TCGA, N=79). estimated tumor immune infiltrating MCs. We evaluated MC signaling genes for their prognostic potential characterizing pro- and anti-tumor signatures and impact on overall (OS) and disease-free(DFS) survival in ACC. Results: MC infiltration was strongly associated with favorable DFS in ACC patients. Anti-tumor (ALOX5, CCL2, CCL5, CXCL10, HDC, IL16, TNF, TPSAB1, VEGFD) and pro-tumor (CXCL1, CXCL3, CXCL8, IL4, IL13, PTGS3, TNSF4, VEGFD) expression signatures were compiled from genes with significantly prolonged and shortened prognosis (OS, DFS p<0.05). Anti-tumor MC signature emerged as the predominant phenotype associated with improved OS and DFS and notably downregulated in immunotherapy resistant cortisol-secreting ACC (CS-ACC). Conclusion: Increased mast cell infiltration in ACC microenvironment correlates with a favorable prognosis. Mast cells play complex mixed anti- and pro-tumor roles in ACC, with predominantly anti-tumor activity. Modulating tumor mast cell infiltration and activity may offer a potential target for novel synergistic immunotherapies for the treatment of CS-ACC.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Multiplatform Computational Analysis of Mast Cells in Adrenocortical Carcinoma Tumor Microenvironment

Baechle

Hanna

Sekhar

et al. 2021

Preprint

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“…Bioinformatics can help identify potential biomarkers of prognosis and progression, and in this way to predict survival outcomes in patients with cancer [ 9 , 10 ]. Long noncoding RNAs (lncRNAs) constitute a class of noncoding RNA molecules that regulate the growth of cancer cells and progression [ 11 ], and they are potential biomarkers to predict cancer risk and survival outcomes [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

An epithelial–mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer

Tong

Gao

et al. 2021

Bioscience Reports

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Bladder cancer is a common malignant tumour worldwide. Epithelial–mesenchymal transition (EMT)-related biomarkers can be used for early diagnosis and prognosis of cancer patients. To explore, accurate prediction models are essential to the diagnosis and treatment for bladder cancer. In the present study, an EMT-related long noncoding RNA (lncRNA) model was developed to predict the prognosis of patients with bladder cancer. Firstly, the EMT-related lncRNAs were identified by Pearson correlation analysis, and a prognostic EMT-related lncRNA signature was constructed through univariate and multivariate Cox regression analyses. Then, the diagnostic efficacy and the clinically predictive capacity of the signature were assessed. Finally, Gene set enrichment analysis (GSEA) and functional enrichment analysis were carried out with bioinformatics. An EMT-related lncRNA signature consisting of TTC28-AS1, LINC02446, AL662844.4, AC105942.1, AL049840.3, SNHG26, USP30-AS1, PSMB8-AS1, AL031775.1, AC073534.1, U62317.2, C5orf56, AJ271736.1, and AL139385.1 was constructed. The diagnostic efficacy of the signature was evaluated by the time-dependent receiver-operating characteristic (ROC) curves, in which all the values of the area under the ROC (AUC) were more than 0.73. A nomogram established by integrating clinical variables and the risk score confirmed that the signature had a good clinically predict capacity. GSEA analysis revealed that some cancer-related and EMT-related pathways were enriched in high-risk groups, while immune-related pathways were enriched in low-risk groups. Functional enrichment analysis showed that EMT was associated with abundant GO terms or signaling pathways. In short, our research showed that the 14 EMT-related lncRNA signature may predict the prognosis and progression of patients with bladder cancer.

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“…Previous studies have demonstrated that infiltrating immune cells can be isolated from tumors suggesting that tumor immune infiltration is a crucial biological process that occurs as a result of immune cell migration from the blood into the TME ( Ge et al, 2019 ; R. Liu et al, 2020 ). Multiple reports have suggested that the proportion and functional alterations of different tumor infiltrated immune cells contribute to the initiation and progression of PAAD ( Meng et al, 2020 ; Tian et al, 2020 ). However, the regulatory mechanisms of immune cells, stromal components of TME, and tumor immune infiltration in PAAD remain largely unknown.…”

Section: Introductionmentioning

confidence: 99%

CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma

Huang

Zhou

Chen

et al. 2021

Front. Mol. Biosci.

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Pancreatic adenocarcinoma (PAAD) is the 10th most common cancer worldwide and the outcomes for patients with the disease remain extremely poor. Precision biomarkers are urgently needed to increase the efficiency of early diagnosis and to improve the prognosis of patients. The tumor microenvironment (TME) and tumor immune infiltration are thought to impact the occurrence, progression, and prognosis of PAAD. Novel biomarkers excavated originating from the TME and immune infiltration may be effective in predicting the prognosis of PAAD patients. In the current study, the ESTIMATE and CIBERSORT algorithms were applied to estimate the division of immune and stromal components and the proportion of tumor-infiltrating immune cells in 182 PAAD cases downloaded from The Cancer Genome Atlas database. Intersection analyses of the Protein-Protein Interaction networks and Cox regression analysis identified the chemokine (CXC-motif) ligand 10 (CXCL10) as a predictive biomarker. We verified that CXCL10 in the TME negatively correlates with prognosis in PAAD and positively correlates with tumor cell differentiation. GSE62452 from the GEO database and cumulative survival analysis were performed to validate CXCL10 expression as an independent prognostic indicator. We also found that memory B cells, regulatory T cells, and macrophages M0 and M1 were correlated with the expression of CXCL10 indicating that expression of CXCL10 influenced the immune activity of the TME. Our data suggest that CXCL10 is beneficial as a prognostic indicator in PAAD patients and highlights the potential for immune targeted therapy in the treatment of PAAD.

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Identification of tumor-infiltrating immune cells and prognostic validation of tumor-infiltrating mast cells in adrenocortical carcinoma: results from bioinformatics and real-world data

Cited by 32 publications

References 40 publications

Multiplatform Computational Analysis of Mast Cells in Adrenocortical Carcinoma Tumor Microenvironment

Multiplatform Computational Analysis of Mast Cells in Adrenocortical Carcinoma Tumor Microenvironment

An epithelial–mesenchymal transition-related long noncoding RNA signature correlates with the prognosis and progression in patients with bladder cancer

CXCL10 is a Tumor Microenvironment and Immune Infiltration Related Prognostic Biomarker in Pancreatic Adenocarcinoma

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