ANXA2P2: A Potential Immunological and Prognostic Signature in Ovarian Serous Cystadenocarcinoma via Pan-Carcinoma Synthesis

Abstract

Background: Although the effect of pseudogene ANXA2P2 on some tumors has been reported in a few literatures, the therapeutic potential and prognostic value of ANXA2P2 in ovarian serous cystadenocarcinoma (OV) have not been elucidated.

Methods: The correlation for ANXA2P2 expression patterns to prognostic characteristics, tumor immune microenvironment, immune cell infiltration level, tumor mutation burden (TMB), tumor microsatellite instability (MSI), drug sensitivity, and pathway function enrichment were investigated in pan-carcinoma via TCGA and GTEx databases. Subsequently, the role of ANXA2P2 expression levels in the pathway enrichments and prognosis prediction in OV were further explored using weighted correlation network analysis (WGCNA) analysis, gene mutation analysis, and risk-independent prognostic analysis.

Results: ANXA2P2 was frequently overexpressed in a variety of tumors compared with normal tissues. The correlation analysis for prognostic characteristics, tumor immune microenvironment, immune cell infiltration level, TMB, MSI, drug sensitivity, and pathway function enrichment revealed that ANXA2P2 expression patterns might deal a significant impact on the pathogenesis, development, and prognosis of various tumors. Then, GSVA, GSEA, WGCNA, gene mutation, and independent prognostic analysis for OV have indicated that high expression in ANXA2P2 could be mostly enriched in TNF-α signaling-via-NF-κB, epithelial-mesenchymal transition, apical junction, IL-6-JAK STAT3 signaling, etc., which were also proved to act as crucial factors on tumorigenesis, development, invasion, and metastasis. The mutation of TP53 (94%), TTN (24%), and CSMD3 (9%) in the biological process of tumor had been confirmed by relevant studies. Finally, the independent prognostic analysis demonstrated that ANXA2P2 expression in OV contributes greatly to the dependability of 3- and 5-year survival prediction.

Conclusion: In summary, our findings might provide a helpful foundation for prospective explorative researches, afford new strategies for the clinical treatment, deal prognosis prediction, and give new hope for OV patients.

Keywords: ANXA2P2; immune characteristics; ovarian serous cystadenocarcinoma; prognostic signature; pseudogene.

Figure 1

Differential transcriptional expression of ANXA2P2 and its correlation to tumor stages in pan-carcinoma. (A) The landscape of ANXA2P2 expression levels based on TCGA dataset. *P < 0.05, **P < 0,01, ***P < 0.001, ****P < 0.0001 and ns indicated no significant. (B) The landscape of ANXA2P2 expression levels based on TCGA and GTEx datasets; red represents tumor tissue, and blue represents normal tissue. Correlations between ANXA2P2 expression and tumor stages in (C) BLCA, (D) LUAD, (E) LUSC, (F) PAAD, (G) STAD, and (H) THCA.

Figure 2

Relevance for ANXA2P2 expression levels to overall survival in months. (A) Forest map related to OS of pan-carcinoma. Kaplan-Meier analysis of the correlation between ANXA2P2 expression and OS in (B) CESC, (C) HNSC, (D) LGG, (E) LUAD, (F) MESO, (G) OV, (H) PAAD, and (I) UVM.

Figure 3

Relevance for ANXA2P2 expression levels to progression-free interval in months. (A) Forest map related to PFI of pan-carcinoma. Kaplan-Meier analysis of the correlation between ANXA2P2 expression and PFI in (B) HNSC, (C) LGG, (D) LIHC, (E) MESO, (F) PAAD, (G) OV, (H) USC, and (I) UVM.

Figure 4

Analysis of tumor microenvironment associated with ANXA2P2. (A) Associations between tumor microenvironment and ANXA2P2 in pan-carcinoma. The relationships of tumor microenvironment and different ANXA2P2 expression subtypes in (B) HNSC, (C) LGG, (D) MESO, (E) OV, (F) PAAD, and (G) UVM; the red means the high-expression subtype, and the yellow-green indicates the low-expression subtype. *P < 0.05, **P < 0,01, ***P < 0.001, ****P < 0.0001 and ns indicated no significant.

Figure 5

Correlation analysis of ANXA2P2 to ESTIMATE-related score and to immunocyte on the TIMER database. (A) The heatmap of correlation of ANXA2P2 to immune score, estimate score, stromal score, and tumor purity. (B) Relevance of ANXA2P2 expression to immune infiltration in pan-carcinoma. *P < 0.05, **P < 0,01 and ***P < 0.001.

Figure 6

The correlation between ANXA2P2 expression and immunotherapeutic markers. (A) TMB and (B) MSI in pan-carcinoma. *P < 0.05, **P < 0,01 and ***P < 0.001.

Figure 7

Correlation between ANXA2P2 and IC50 of drugs. (A) Kahalide f; (B) irofulven; (C) staurosporine; (D) simvastatin; (E) ifosfamide; (F) chelerythrine; (G) dimethylaminoparthenolide; (H) cyclophosphamide; (I) imexon; (J) cisplatin; (K) carboplatin; and (L) oxaliplatin.

Figure 8

Relevance with ANXA2P2 and immune-related genes. (A) Immunostimulatory; (B) immunoinhibitory; (C) immune checkpoint; (D) chemokine; (E) chemokine receptor; and (F) MHC molecule. *P < 0.05, **P < 0,01 and ***P < 0.001.

Figure 9

WGCNA regulatory network analysis for ANXA2P2 in OV. (A) Correlation between various modules and ANXA2P2 expression. The top number means the coefficient among them, and the bottom number indicates the p-value. (B) KEGG enrichment pathway analysis was applied for genes with brown module meaning highest correlation. (C) GO term analysis for genes with brown module meaning highest correlation.

Figure 10

Nomogram prediction model for ANXA2P2 in OV. (A) The model of relevant nomogram chart, with different lines meaning different clinical features of the sample. (B) The corrective curve of the correlative nomogram chart, with blue for 3 years and red for 5 years.