CCL19 has potential to be a potential prognostic biomarker and a modulator of tumor immune microenvironment (TIME) of breast cancer: a comprehensive analysis based on TCGA database

Wang, Jinyan; Qin, Dongmei; Ye, Lingling; Li, Wan; Wang, Fen; Yang, Yan; Ma, Yajun; Yang, Hui; Yang, Zhaohui; Chen, Meili; Jiang, Wangjie; Zhang, Quan'an

doi:10.18632/aging.204081

Cited by 11 publications

(7 citation statements)

References 35 publications

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“…Interestingly, we discovered that most immunomodulators were highly expressed in the low-risk group, which contradicted our finding that the high-risk group would respond better to immunotherapy. Several findings demonstrated that the high expression of CCL11 and CCL19 predicts better OS of BRCA 67,68 , and Li et al 69 indicated that the high expression of CCL21 is highly associated with a lower distant recurrence rate of BRCA, through increasing the infiltration of CD8+T cells, thus, we confirmed that these studies may explain the up-regulation of immunomodulators in the low-risk group. Consequently, we hypothesized that the high-risk group would respond better to immunotherapy.…”

Section: Discussionsupporting

confidence: 84%

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Bai

Wang³

et al. 2022

Sci Rep

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Breast cancer (BRCA) is the most prevalent malignancy and the leading cause of death in women. Interleukin (IL) genes are critical in tumor initiation and control. Nevertheless, the prognosis value of the IL in BRCA remains unclear. We collected data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and 94 IL genes were identified from GeneCard. Based on the random forest (RF), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression analysis, we constructed an IL signature. GSE22219, GSE25065, and GSE21653 were derived as validation sets. The expression differences in the tumor microenvironment (TME), immunotherapy, and chemosensitivity of BRCA between the high- and low-risk groups were evaluated. Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA. IL score could distinguish BRCA patients with inferior outcomes, and AUC of it was 0.70, 0.76, and 0.72 for 1-,3- and 5- years, respectively, which was also verified in GSE22219, GSE25065, and GSE21653 cohorts. Meanwhile, compared to luminal A and luminal B, HER2-positive and TNBC had significantly higher IL score. Besides, the high-risk group had a significantly higher prevalence of TP53 and TTN but a lower prevalence of PIK3CA, as well as higher tumor mutation burden (TMB) and neoantigen level. High- and low-risk groups exhibited notable differences in immunomodulators and tumor infiltrates immune cells (TIICs), and the high-risk group had significantly lower Tumor Immune Dysfunction and Exclusion (TIDE) score. Additionally, the high-risk group has more responders to immune or anti-HER2 combination therapy, whereas the low-risk group has higher sensitivity to docetaxel and paclitaxel. Consequently, we constructed a reliable risk model based on the IL genes, which can provide more information on both the risk stratification and personalizing management strategies for BRCA.

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Section: Discussionsupporting

confidence: 84%

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Bai

Wang³

et al. 2022

Sci Rep

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“…CCL19 facilitates the secretion of IL-6 and IL-1β by DC cells, which promote tumor growth in triple-negative breast cancer (TNBC), leading to tumor invasion and worse prognosis in patients [31]. The latest research found CCL19 is a potential prognostic biomarker and is signi cantly correlated with TILs in breast cancer [32]. This study found that CCL19 was signi cantly elevated in tumor tissue in breast cancer and was signi cantly positively correlated with the prognosis of patients.…”

Section: Discussionmentioning

confidence: 99%

The Expression and Prognostic Value of CCL19 in Breast Cancer

Chen

Yang

et al. 2022

Preprint

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Background Breast cancer is the leading cause of cancer related death in women worldwide. Early diagnosis is the most effective way to reduce breast cancer mortality. Immune and tumor processes are closely related. This study aims to explore the mechanism of immune and potential biomarkers of breast cancer through bioinformatics. Objective First, differentially expressed genes (DEGs) were screened by consensus analysis of invasive breast cancer (BRCA) samples from The Cancer Genome Atlas (TCGA) database based on immune genes. Then, protein interaction (PPI) networks, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to narrow down the potential genes. Finally, expression analysis and prognostic analysis of hub genes were used to select reliable key genes to identify CCL19. Immunohistochemistry (IHC) was used to detect the differential expression of CCL19 in tumor tissues and adjacent tissues of breast cancer. Protein correlation analysis, signaling pathway analysis, immune infiltration analysis, gene co-expression analysis and drug sensitivity analysis of CCL19 were further used to explore the pathological clinical features and potential biological functions of CCL19. Results The expression of CCL19 was significantly increased in breast cancer. High expression of CCL19 correlates with tumor stage and predicts a better prognosis in breast cancer. The expression of CCL19 correlates with the levels of various tumor immune infiltrating cells (TILs). CCL19 has positive correlation with the expression of most immune-related genes, including immune activator, immunosuppressant, chemokine, chemokine receptor, and major histocompatibility complex (MHC) genes. Enrichment analysis showed that CCL19 was involved in immune-related pathways and PI3K-Akt signaling pathway. The above results indicate that CCL19 may modulate the prognosis of breast cancer through immune infiltration. CCL19 affects the sensitivity to chemotherapy and targeted therapy, which affects the sensitivity of TAK-715, KIN001-102 and 17-AAG. Conclusion CCL19 is overexpressed in breast cancer. CCL19 may serve as a promising biomarker for predicting breast prognosis and a candidate therapeutic target.

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“…The clinicopathological characteristics included age, gender, grade and tumor node metastasis (TNM) stage. Survival and survminer packages in R were used for survival analysis, the same as our previous research ( 29 ). We used Kaplan–Meier plot and log-rank to test the correlations between molecular subtypes and overall survival (OS) of GC patients.…”

Section: Methodsmentioning

confidence: 99%

Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in gastric cancer

et al. 2022

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IntroductionCuproptosis is a novel identified regulated cell death (RCD), which is correlated with the development, treatment response and prognosis of cancer. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of gastric cancer (GC) remains unknown.MethodsTranscriptome profiling, somatic mutation, somatic copy number alteration and clinical data of GC samples were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database to describe the alterations of CRGs from genetic and transcriptional fields. Differential, survival and univariate cox regression analyses of CRGs were carried out to investigate the role of CRGs in GC. Cuproptosis molecular subtypes were identified by using consensus unsupervised clustering analysis based on the expression profiles of CRGs, and further analyzed by GO and KEGG gene set variation analyses (GSVA). Genes in distinct molecular subtypes were also analyzed by GO and KEGG gene enrichment analyses (GSEA). Differentially expressed genes (DEGs) were screened out from distinct molecular subtypes and further analyzed by GO enrichment analysis and univariate cox regression analysis. Consensus clustering analysis of prognostic DEGs was performed to identify genomic subtypes. Next, patients were randomly categorized into the training and testing group at a ratio of 1:1. CRG Risk scoring system was constructed through logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis, univariate and multivariate cox analyses in the training group and validated in the testing and combined groups. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to evaluate the expression of key Risk scoring genes. Sensitivity and specificity of Risk scoring system were examined by using receiver operating characteristic (ROC) curves. pRRophetic package in R was used to investigate the therapeutic effects of drugs in high- and low- risk score group. Finally, the nomogram scoring system was developed to predict patients’ survival through incorporating the clinicopathological features and CRG Risk score.ResultsMost CRGs were up-regulated in tumor tissues and showed a relatively high mutation frequency. Survival and univariate cox regression analysis revealed that LIAS and FDX1 were significantly associated with GC patients’ survival. After consensus unsupervised clustering analysis, GC patients were classified into two cuproptosis molecular subtypes, which were significantly associated with clinical features (gender, age, grade and TNM stage), prognosis, metabolic related pathways and immune cell infiltration in TME of GC. GO enrichment analyses of 84 DEGs, obtained from distinct molecular subtypes, revealed that DEGs primarily enriched in the regulation of metabolism and intracellular/extracellular structure in GC. Univariate cox regression analysis of 84 DEGs further screened out 32 prognostic DEGs. According to the expression profiles of 32 prognostic DEGs, patients were re-classified into two gene subtypes, which were significantly associated with patients’ age, grade, T and N stage, and survival of patients. Nest, the Risk score system was constructed with moderate sensitivity and specificity. A high CRG Risk score, characterized by decreased microsatellite instability-high (MSI-H), tumor mutation burden (TMB) and cancer stem cell (CSC) index, and high stromal and immune score in TME, indicated poor survival. Four of five key Risk scoring genes expression were dysregulated in tumor compared with normal samples. Moreover, CRG Risk score was greatly related with sensitivity of multiple drugs. Finally, we established a highly accurate nomogram for promoting the clinical applicability of the CRG Risk scoring system.DiscussionOur comprehensive analysis of CRGs in GC demonstrated their potential roles in TME, clinicopathological features, and prognosis. These findings may improve our understanding of CRGs in GC and provide new perceptions for doctors to predict prognosis and develop more effective and personalized therapy strategies.

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CCL19 has potential to be a potential prognostic biomarker and a modulator of tumor immune microenvironment (TIME) of breast cancer: a comprehensive analysis based on TCGA database

Cited by 11 publications

References 35 publications

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

The Expression and Prognostic Value of CCL19 in Breast Cancer

Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in gastric cancer

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