Prognostic Biomarkers and Immunotherapeutic Targets Among CXC Chemokines in Pancreatic Adenocarcinoma

Huang, Jiacheng; Chen, Zhitao; Ding, Chenchen; Lin, Shigang; Wan, Dalong; Ren, Kuiwu

doi:10.3389/fonc.2021.711402

Cited by 17 publications

(15 citation statements)

References 90 publications

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“…Chemokines regulate cancer‐related inflammation, tumor microenvironment, tumor growth, and metastasis 39 . Recently, chemokine‐based risk signatures have showed a good prediction for clinical outcome and immunotherapy response in lung adenocarcinoma and pancreatic adenocarcinoma 40,41 . Additionally, a dysregulated chemokine network is one of the characteristics of glioma 39 .…”

Section: Discussionmentioning

confidence: 99%

“… 39 Recently, chemokine‐based risk signatures have showed a good prediction for clinical outcome and immunotherapy response in lung adenocarcinoma and pancreatic adenocarcinoma. 40 , 41 Additionally, a dysregulated chemokine network is one of the characteristics of glioma. 39 Thus, we performed the comprehensive analysis of the chemokine genes in glioma.…”

Section: Discussionmentioning

confidence: 99%

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A novel chemokine‐based signature for prediction of prognosis and therapeutic response in glioma

Fan

Wang

et al. 2022

CNS Neurosci Ther

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Aims Gliomas are the primary malignant brain tumor and characterized as the striking cellular heterogeneity and intricate tumor microenvironment (TME), where chemokines regulate immune cell trafficking by shaping local networks. This study aimed to construct a chemokine‐based gene signature to evaluate the prognosis and therapeutic response in glioma. Methods In this study, 1024 patients (699 from TCGA and 325 from CGGA database) with clinicopathological information and mRNA sequencing data were enrolled. A chemokine gene signature was constructed by combining LASSO and SVM‐RFE algorithm. GO, KEGG, and GSVA analyses were performed for function annotations of the chemokine signature. Candidate mRNAs were subsequently verified through qRT‐PCR in an independent cohort including 28 glioma samples. Then, through immunohistochemical staining (IHC), we detected the expression of immunosuppressive markers and explore the role of this gene signature in immunotherapy for glioma. Lastly, the Genomics of Drug Sensitivity in Cancer (GDSC) were leveraged to predict the potential drug related to the gene signature in glioma. Results A constructed chemokine gene signature was significantly associated with poorer survival, especially in glioblastoma, IDH wildtype. It also played an independent prognostic factor in both datasets. Moreover, biological function annotations of the predictive signature indicated the gene signature was positively associated with immune‐relevant pathways, and the immunosuppressive protein expressions (PD‐L1, IBA1, TMEM119, CD68, CSF1R, and TGFB1) were enriched in the high‐risk group. In an immunotherapy of glioblastoma cohort, we confirmed the chemokine signature showed a good predictor for patients' response. Lastly, we predicted twelve potential agents for glioma patients with higher riskscore. Conclusion In all, our results highlighted a potential 4‐chemokine signature for predicting prognosis in glioma and reflected the intricate immune landscape in glioma. It also threw light on integrating tailored risk stratification with precision therapy for glioblastoma.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A novel chemokine‐based signature for prediction of prognosis and therapeutic response in glioma

Fan

Wang

et al. 2022

CNS Neurosci Ther

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“…Many of chemokines are important for the regulation of chemotaxis of immune cells, especially T lymphocyte, monocytes/macrophages, and eosinophils. 34 As listed in Table 2 , SLC7A11 expression was significantly positively correlated with T lymphocyte-related chemokines and monocyte/macrophage-related chemokines (CCL22), mast cell-related chemokines (CCR3 and CXCR4), eosinophil-related chemokines (CCL24) in UCEC. These findings indicate that SLC7A11 expression may regulate immune cell infiltration in UCEC.…”

Section: Resultsmentioning

confidence: 89%

Solute Carrier Family 7 Member 11 (SLC7A11) is a Potential Prognostic Biomarker in Uterine Corpus Endometrial Carcinoma

Fang¹,

Zhang²,

Chen³

2023

IJGM

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Background Uterine corpus endometrial carcinoma (UCEC) is a common type of gynecological cancers, second only to cervical cancer in incidence. Thus, it is necessary to develop effective therapies and identify biomarkers for its prognosis. Solute carrier family 7 member 11 (SLC7A11) is well known for its role in maintaining the intracellular glutathione level and preventing oxidative-stress-induced cell death. However, the association between SLC7A11 expression and prognosis as well as the correlation between tumor-infiltrating immune cells (TIICs) and immunotherapy of UCEC has rarely been reported. This study aims to evaluate the prognostic significance and immune cell infiltration level of SLC7A11 in UCEC. Methods Bioinformatics analysis tools and databases, including R software, National Center for Biotechnology Information (NCBI), The Cancer Genome Atlas (TCGA), GEPIA2, Sangerbox, Kaplan–Meier (K-M) Plotter, TISIDB, and TIMER2, were utilized to measure the expression level and clarify the clinical significance of SLC7A11 in UCEC. Results SLC7A11 expression was dramatically up-regulated in UCEC patients and associated with prognosis. DNA methylation levels in the SLC7A11-promoter region were significantly higher in normal participants than in patients with UCEC. We also showed that SLC7A11 overexpression was associated with TIICs, immune checkpoint blockers (ICBs), and immunotherapy response in UCEC. The half-maximal inhibitory concentration (IC50) results obtained with the cohort from TCGA showed that Z-VAD-FMK (Caspase inhibitor), S-Triphenylmethyl-L-cysteine (S-Trityl-L-cysteine), and TAE684 (ALK inhibitor) had higher IC50 values in low-expression patient (p < 0.05). Conclusion SLC7A11 overexpression is associated with favorable prognosis of patients with UCEC and is associated with TIICs and the responses to immunotherapy.

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“…Recently, it has been shown that chemokine-based risk signatures show good predictive power in clinical prognosis and response to immunotherapy in glioma, lung adenocarcinoma and pancreatic adenocarcinoma. ( Chen et al, 2021 ; Huang et al, 2021 ; Fan et al, 2022 ). As a result, we investigated thoroughly the chemokine genes in ccRCC.…”

Section: Discussionmentioning

confidence: 99%

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma

et al. 2023

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Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort.Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package “Seurat” was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the “ssGSEA” algorithm. In order to develop possible medications for patients with high-risk ccRCC, the “pRRophetic” package is employed.Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature’s biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications.Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient’s prognosis for ccRCC and reflect the disease’s complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

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Prognostic Biomarkers and Immunotherapeutic Targets Among CXC Chemokines in Pancreatic Adenocarcinoma

Cited by 17 publications

References 90 publications

A novel chemokine‐based signature for prediction of prognosis and therapeutic response in glioma

A novel chemokine‐based signature for prediction of prognosis and therapeutic response in glioma

Solute Carrier Family 7 Member 11 (SLC7A11) is a Potential Prognostic Biomarker in Uterine Corpus Endometrial Carcinoma

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma

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