POC1A is highly expressed in pan-cancer
The TIMER2 webserver was used to explore POC1A expression in pan-cancer. As shown in Figure 1A, the expression levels of POC1A were significantly higher in the tumor tissues of BLCA, BRCA, CHOL, COAD, ESCA, HNSC, HNSC-HPV, LIHC, LUAD, LUSC, PRAD, STAD, THCA, UCEC (P<0.001), READ (P<0.01), and KIRP (P<0.05) compared to the adjacent normal tissues. The expression of P0C1A was assessed using TCGA and GTEx data for tumors without normal control. It was found that POC1A was overexpressed in 27 of 33 cancer types, including ACC, BLCA, BRCA, CESC, CHOL, COAD, DLBC, ESCA, GBM, HNSC, KICH, KIRP, LGG, LIHC, LUAD, LUSC, OV, PAAD, PRAD, READ, SARC, SKCM, STAD, THCA, THYM, UCEC, and UCS. However, POC1A was under-expressed in three tumor types, including LAML, PCPG, and TGCT (Figure 1B). The correlation between POC1A expression and tumor pathological staging in the TCGA cohort was further explored. The results demonstrated that POC1A expression was elevated with the increase of tumor stages in ACC, BRCA, HNSC, KICH, KIRC, KIRP, LUAD, LUSC, and PAAD (Figure 2A-I).
Gene alteration of POC1A in pan-cancer
Mutation and copy number alteration (CNA) influence gene expression. Thus, mutations and CNA of POC1A we assessed. The highest alteration frequency of POC1A (>7%) was observed in undifferentiated stomach adenocarcinoma patients, in which “Mutation” was the primary type (Figure 3A). The expression of POC1A was positively correlated with can in 23 of 33 tumor types and negatively correlated in KIRP (Figure 3B), indicating that high CNA was one of the main reasons for the high expression of POC1A in pan-cancer.
High expression of POC1A is associated with poor prognosis in pan-cancer
To explore the prognostic value of POC1A in pan-cancer, the Kaplan-Meier survival analysis and UniCox analysis were used. The best cut-off value was used to distinguish the high and low expression groups of POC1A. Kaplan-Meier survival analysis revealed that high expression of POC1A was associated with worse OS in ACC, BLCA, CHOL, KICH, KIRC, KIRP, LAML, LGG, LIHC, LUAD, MESO, PAAD, PCPG, PRAD, SARC, and SKCM (Figure 4). UniCox analysis showed that POC1A was a risk factor for OS in ACC, DLBC, KICH, KIRC, KIRP, LGG, LIHC, LUAD, MESO, PAAD, PCPG, PRAD, READ, SKCM, and THYM (Figure 5A). The prognostic value of POC1A for DSS, DFI, and PFI in pan-cancer was also analyzed and the results are shown in Figure 5B-D. All these results suggested that high expression of POC1A was associated with poor prognosis and might be a potential prognostic biomarker in pan-cancer.
POC1A is correlated with tumor immune infiltration and microenvironment in pan-cancer
The amount of tumor-infiltrating lymphocytes is an important predictor of prognosis in cancer patients and their response to immunotherapy. The StromalScore, ImmuneScore, and ESTIMATEScore of the tumor tissue were calculated using the R language “estimate” package, and their correlation with POC1A expression was evaluated. The results showed that POC1A was negatively correlated with StromalScore and ImmuneScore in most tumors and positively correlated with tumor purity (Figure 6A). By exploring the correlation between POC1A expression and immune cell infiltration using the immune cell infiltration data from the ImmuCellAI database, it was found that POC1A was positively correlated with nTreg cells in most tumors and negatively correlated with immune killer cells, such as activated natural killer (NK) cells, CD4 T cells, and CD8 T cells in pan-cancer (Figure 6B). Similarly, results of data from the TIMER2 database showed that POC1A was negatively correlated with CD8 T cells and NK cells in most tumors (Figure 7).
POC1A expression is associated with immune checkpoint genes
Immune checkpoint genes are important targets of immunotherapy. Five immune checkpoint genes were identified and the relationship between POC1A expression and immune checkpoint gene expression in pan-cancer was analyzed. The results revealed that the expression of POC1A was positively correlated with immune checkpoints in several tumors (Figure 8), suggesting that immune cells are inhibited. The correlation between POC1A expression and immune regulatory genes was further analyzed. The results showed that the POC1A gene has a potential immunomodulatory effect in most tumors (Figure 9).
POC1A expression is correlated with TMB and MSI in pan-cancer
The TMB of each tumor sample was calculated, and the relationship between POC1A expression and TMB was analyzed using Spearman’s rank correlation coefficient. The results are shown in Figure 10A. The expression levels of POC1A were significantly positively correlated with TMB in BLCA, BRCA, COAD, GBM, KICH, LGG, LIHC, LUAD, LUSC, PAAD, PRAD, SKCM, SARC, STAD, UCEC, UCS, and UVM, and inversely correlated with TMB in THYM. The correlation between POC1A expression and MSI was also analyzed using Spearman’s rank correlation coefficient, and the results are shown in Figure 10B. Notably, the expression levels of POC1A were significantly positively correlated with MSI in BLCA, COAD, ESCA, HNSC, KIRC, LIHC, MESO, SARC, STAD, and UCEC, and inversely correlated with MSI in READ.
GSEA analysis of POC1A
Based on the Reactome database, genes correlating with POC1A (P<0.05) were ranked and subjected to GSEA analysis in pan-cancer. The analysis was performed using the R package “clusterProfiler”. The top 20 results of each tumor identified by this analysis are shown in Figure 11. POC1A was positively correlated with cell cycle-related and immune-related pathways in various tumors, which is consistent with the previous conclusion that the POC1A has an immune regulatory function.
Drug sensitivity analysis
The correlation between POC1A1 and IC50 of 192 anti-cancer drugs was analyzed. It was discovered that patients with high POC1A expression might be resistant to most anti-cancer drugs, such as vincristine, oxaliplatin, carmustine, etc. (Figure 12, Supplementary Table 1).