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. 2022 May 18:2022:5009512.
doi: 10.1155/2022/5009512. eCollection 2022.

Comprehensive Analysis of RELL2 as a Potential Biomarker Associated with Tumor Immune Infiltrating Cells in a Pan-Cancer Analysis

Kadeerjiang Musha  1 , Xinqi Ge  2 , Nuraliya Ablikim  3 , Bing Lu  2 , Chen Chen  4   5 , Jianfei Huang  2   3
Affiliations

Comprehensive Analysis of RELL2 as a Potential Biomarker Associated with Tumor Immune Infiltrating Cells in a Pan-Cancer Analysis

Kadeerjiang Musha et al. Dis Markers. .

Abstract

Background: Receptor expressed in lymphoid tissues-like 2 (RELL2), which is a member of RELT family, is closely associated with the plasma membrane and acts as a modulator for RELT signaling. Overexpression of RELL2 induces the activation of MAPK14/p38 cascade and apoptosis. However, whether RELL2 contributes to cancers remains unclear. Here, we examined its role in cancer patient prognosis and various tumors.

Methods: We used several bioinformatics methods, specifically gene set enrichment analysis (GSEA), ScanNeo, and ESTIMATE, to analyze the CCLE dataset, GTEx dataset, and TCGA dataset. We investigated the possible association of RELL2 with the microsatellite instability (MSI) of various tumors, tumor mutational burden (TMB), immune checkpoint, immune neoantigens, immune microenvironment, and patient prognosis.

Result: RELL2 is highly expressed in cancer compared with normal tissues. RELL2 expression is linked with worse progression-free interval and overall survival in numerous cancers. In most cancers, high RELL2 expression was related to a poor prognosis. RELL2 expression was significantly associated with the tumor microenvironment, MSI, and TMB. RELL2 expression is strongly associated with phenotypes that are of major clinical significance, particularly those associated with immune neoantigens and the expression profiles of immune checkpoint genes in pan-cancer. RELL2 expression strongly linked with the expressions of methyltransferases and DNA repair genes. It also significantly correlated with multiple signaling pathways through gene set enrichment analysis.

Conclusion: RELL2 may be a prognostic biomarker in pan-cancer and may have an important function in tumorigenesis and progression.

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Conflict of interest statement

The authors declare that they have no conflicts of interests.

Figures

Figure 1
Figure 1
RELL2 expression level across various cancer types. (a) RELL2 expression in 31 tissues in the GTEx database. (b) RELL2 expression in 21 tumor cell lines/tissues in the CCLE database. (c) RELL2 expression level in normal and tumor tissues in the TCGA database. (d) RELL2 expression in normal and tumor tissues in GTEx and TCGA databases. (e) RELL2 expression in normal and tumor tissues in the TIMER database.
Figure 2
Figure 2
Forest plot and Kaplan-Meier OS curves of RELL2 expression in TCGA database. (a) The relationships between RELL2 expression and OS (overall survival) in 33 kinds of cancers. (b–j) Kaplan-Meier analysis of OS on the basis of RELL2 expression and 33 types of cancers.
Figure 3
Figure 3
Forest plot and Kaplan-Meier DSS curves of RELL2 expression in TCGA database. (a) The relationships between RELL2 expression and 33 kinds of cancers associated with DSS (disease-specific survival). (b–j) Kaplan–Meier analysis of disease-specific survival outcomes on the basis of RELL2 expression in 33 types of cancers.
Figure 4
Figure 4
Forest plot and Kaplan-Meier DFI curves of RELL2 expression in TCGA database. (a) The relationships between RELL2 expression and 33 kinds of cancers associated with DFI (disease-free interval). (b, c) Kaplan–Meier analysis results on disease-free interval outcomes on the basis of RELL2 expression in 33 types of cancers.
Figure 5
Figure 5
Forest plot and Kaplan-Meier PFI curves of RELL2 expression in TCGA database. (a) The relationships between RELL2 expression and 33 kinds of cancers associated with PFI (progression-free interval). (b–g) The most significant Kaplan-Meier analysis results regarding to the progression-free interval outcomes between RELL2 expression and 33 types of cancers.
Figure 6
Figure 6
The relationships between RELL2 expression and different stages among 32 cancers and TMB, MSI in theTCGA database. (a–f) Distinct pathological stages of the most significant RELL2 expression levels across various cancer types. (g) Correlations of RELL2 expression levels with TMB. (h) Correlations of RELL2 expression levels and MSI.
Figure 7
Figure 7
The relationships between RELL2 expression level and tumor immune infiltration in the TCGA database. (a) RELL2 expression and its correlations with the immune cell infiltration in KIRC. (b) Association of RELL2 expression with immune cell infiltration in LIHC. (c) Association of RELL2 expression levels and immune score, ESTIMATE immune score, and stromal score in pan-cancer analysis.
Figure 8
Figure 8
RELL2 expression level in ICG expression and neoantigens in different cancers. (a) Relation between RELL2 expression levels and key ICG expression. Statistical significance: ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001. (b) RELL2 expression and its correlations with immune neoantigens across 19 types of tumors.
Figure 9
Figure 9
RELL2 expression level in 5 MMRs and 4 methyltransferases. (a) Relation between RELL2 expression and five MMR gene expressions based on pan-cancer analysis. (b) Relationships between RELL2 expression and four methyltransferases. DNMT1 is indicated in red, DNMT2 is indicated in blue, DNMT3a is indicated in green, and DNMT3b is indicated in purple.
Figure 10
Figure 10
GSEA of RELL2 expression. (a) Gene set enrichment analysis results showing the top three signaling pathways correlated with RELL2 expression in the KEGG database. (b) Gene set enrichment analysis results showing the top three signaling pathways correlated with RELL2 expression in the hallmark database.
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