Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of colorectal cancer

Ge, Penglei; Wang, Weiwei; Lin, Liang-In; Zhang, Gong; Gao, Zhiqiang; Tang, Zhe; Dang, Xiaowei; Wu, Yang

doi:10.1016/j.biopha.2019.109228

Cited by 198 publications

(180 citation statements)

References 49 publications

Supporting

Mentioning

174

Contrasting

Order By: Relevance

“…It is generally considered that M0 macrophages are unactivated and without specific function (19). While M0 can differentiate into M1 and M2 under different stimulations, and they, respectively, exhibit inflammatory response against tumor cells and immunosuppressive response promoting tumor cells proliferation and differentiation (23). However, this concept of dual-polarization status is likely to be oversimplified (24) and is strongly debated (25).…”

Section: Discussionmentioning

confidence: 99%

Development of an Immune Infiltration-Related Prognostic Scoring System Based on the Genomic Landscape Analysis of Glioblastoma Multiforme

Tang

2020

Front. Oncol.

View full text Add to dashboard Cite

Introduction: Glioblastoma multiforme (GBM) is the most common deadly brain malignancy and lacks effective therapies. Immunotherapy acts as a promising novel strategy, but not for all GBM patients. Therefore, classifying these patients into different prognostic groups is urgent for better personalized management. Materials and Methods: The Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to estimate the fraction of 22 types of immune-infiltrating cells, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune infiltration-related prognostic scoring system (IIRPSS). Additionally, a quantitative predicting survival nomogram was also established based on the immune risk score (IRS) derived from the IIRPSS. Moreover, we also preliminarily explored the differences in the immune microenvironment between different prognostic groups. Results: There was a total of 310 appropriate GBM samples (239 from TCGA and 71 from CGGA) included in further analyses after CIBERSORT filtering and data processing. The IIRPSS consisting of 17 types of immune cell fractions was constructed in TCGA cohort, the patients were successfully classified into different prognostic groups based on their immune risk score (p = 1e-10). What's more, the prognostic performance of the IIRPSS was validated in CGGA cohort (p = 0.005). The nomogram also showed a superior predicting value. (The predicting AUC for 1-, 2-, and 3-year were 0.754, 0.813, and 0.871, respectively). The immune microenvironment analyses reflected a significant immune response and a higher immune checkpoint expression in high-risk immune group. Conclusion: Our study constructed an IIRPSS, which maybe valuable to help clinicians select candidates most likely to benefit from immunological checkpoint inhibitors (ICIs) and laid the foundation for further improving personalized immunotherapy in patients with GBM.

show abstract

Section: Discussionmentioning

confidence: 99%

Development of an Immune Infiltration-Related Prognostic Scoring System Based on the Genomic Landscape Analysis of Glioblastoma Multiforme

Tang

2020

Front. Oncol.

View full text Add to dashboard Cite

show abstract

“…The macrophages can be divided into three subtypes (M0, M1, and M2), where M0 is the unactivated subtype and can be differentiated into two M1 and M2 activated subtypes. M1 macrophages are proinflammatory and participate in the host innate immunity to kill tumor cells (41,42). M2 macrophages are regarded as tumor-promotive and are correlated with poor prognosis in various cancers, including ESCC (43,44).…”

Section: Discussionmentioning

confidence: 99%

“…M2 macrophages could promote tumor metastasis by inducing epithelial-mesenchymal transition (EMT) or secreting cytokines such as IL-1β (45). The infiltrated immune cell can induce the host immune response to inhibit or promote the progression of tumor cells in the tumor microenvironment (42). Hence, the high infiltration rate of M2 macrophages in the MetS group might be associated with tumor microenvironment.…”

Section: Discussionmentioning

confidence: 99%

“…Above all, the change of tumor microenvironment in the MetS group might be the possible mechanism on tumor progression and a reason for the poor prognosis. The recent studies have shown that immune cell infiltration could be used to establish a prognosis model in prostate cancer and colorectal cancer (42,50). Hence, we also tried to establish a prognosis predictive signature based on immune infiltration profiles.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

The Prognostic Significance of Metabolic Syndrome and a Related Six-lncRNA Signature in Esophageal Squamous Cell Carcinoma

et al. 2020

View full text Add to dashboard Cite

Background: Metabolic syndrome (MetS) is associated with the development of esophageal squamous cell carcinoma (ESCC), and long non-coding RNAs (lncRNAs) are involved in a variety of mechanisms of MetS and tumor. This study will explore the prognostic effect of MetS and the associated lncRNA signature on ESCC.Methods: Our previous RNA-chip data (GSE53624, GSE53622) for 179 ESCC patients were reanalyzed according to MetS. The recurrence-free survival (RFS) was collected for these patients. The status of the MetS-related tumor microenvironment was analyzed with the CIBERSORT and ESTIMATE algorithms. A lncRNA signature was established with univariate and multivariate Cox proportional hazards regression (PHR) analysis and verified using the Kaplan-Meier survival curve analysis and time-dependent receiver operating characteristic (ROC) curves. A clinical predictive model was constructed based on multiple risk factors, evaluated using C-indexes and calibration curves, and verified using data from the GEO and TCGA databases. Results:The results showed that MetS was an independent risk factor for ESCC patients conferring low OS and RFS. Tumor microenvironment analysis indicated that patients with MetS have high stromal scores and M2 macrophage infiltration. A six-lncRNA signature was established by 60 ESCC patients randomly selected from GSE53624 and identified with an effective predictive ability in validation cohorts (59 patients from GSE53624 and 60 patients from GSE53622), subgroup analysis, and ESCC patients from TCGA. MetS and the six-lncRNA signature could be regarded as independent risk factors and enhanced predictive ability in the clinical predictive model. Conclusions:Our results indicated that MetS was associated with poor prognosis in ESCC patients, and the possible mechanism was related to changes in the tumor microenvironment. MetS and the six-lncRNA signature could also serve as independent risk factors with available clinical application value.

show abstract

“…CIBERSORT is an analysis tool that uses RNA-seq data to evaluate the expression of immune cells and obtain various immune cell proportions from samples [7]. It has been widely used in the analysis of immune cell infiltration in a variety of diseases such as lupus nephritis [8], atopic dermatitis [9], and colorectal cancer [10]. However, so far, no studies have used CIBERSORT to analyze immune cell infiltration in OA.…”

Section: Introductionmentioning

confidence: 99%

GRB10 and E2F3 as Diagnostic Markers of Osteoarthritis and Their Correlation with Immune Infiltration

et al. 2020

View full text Add to dashboard Cite

This study aimed to find potential diagnostic markers for osteoarthritis (OA) and analyze the role of immune cells infiltration in this pathology. We used OA datasets from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and perform functional correlation analysis. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination algorithms were used to screen and verify the diagnostic markers of OA. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in OA tissues, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. A total of 458 DEGs were screened in this study. GRB10 and E2F3 (AUC = 0.962) were identified as diagnostic markers of OA. Immune cell infiltration analysis found that resting mast cells, T regulatory cells, CD4 memory resting T cells, activated NK cells, and eosinophils may be involved in the OA process. In addition, GRB10 was correlated with NK resting cells, naive CD4 + T cells, and M1 macrophages, while E2F3 was correlated with resting mast cells. In conclusion, GRB10 and E2F3 can be used as diagnostic markers of osteoarthritis, and immune cell infiltration plays an important role in the occurrence and progression of OA.

show abstract

Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of colorectal cancer

Cited by 198 publications

References 49 publications

Development of an Immune Infiltration-Related Prognostic Scoring System Based on the Genomic Landscape Analysis of Glioblastoma Multiforme

Development of an Immune Infiltration-Related Prognostic Scoring System Based on the Genomic Landscape Analysis of Glioblastoma Multiforme

The Prognostic Significance of Metabolic Syndrome and a Related Six-lncRNA Signature in Esophageal Squamous Cell Carcinoma

GRB10 and E2F3 as Diagnostic Markers of Osteoarthritis and Their Correlation with Immune Infiltration

Contact Info

Product

Resources

About