Role of CD68 in tumor immunity and prognosis prediction in pan-cancer

Expression of CD68 in pan-cancer

First, to fully clarify the expression of CD68 in pan-cancer, we matched the GTEx normal samples with TCGA tumor samples (Fig. 1A). We found that the levels of CD68 were significantly elevated (P < 0.01) in colon adenocarcinoma (COAD), glioblastoma multiforme (GBM), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain low-grade glioma (LGG), ovarian serous cystadenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), rectum adenocarcinoma (READ), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD), testicular germ cell tumors (TGCT), and uterine carcinosarcoma (UCS) compared to in normal tissues. In contrast, CD68 was significantly decreased (P < 0.001) in thymoma (THYM) compared with GTEx normal controls. Moreover, we observed the expression of CD68 in these tumor and normal controls using tissue chip. Each tumor/normal tissue has three cores (diameter 1 mm). Even though statistical analysis was not possible due to the small sample size, we compared the expression of CD68 in these tumor tissues and normal tissues and found that the immunohistoactivity of CD68 was obviously enhanced in COAD, GBM, KIRC, LGG, OV, PAAD, READ, SKCM, and STAD compared with their normal controls (Fig. 1B), which might provide evidence for the difference in CD68 gene expression in Fig. 1A.

Figure 1
figure 1

Expresssion aspect of CD68 in tumor and normal tissues based on the TCGA and GETx databases. CD68 expression from the TCGA and GTEx databases (A). CD68 expression from tumor tissue chip using immunohistochemistry, n = 3 for tumor/control groups in COAD, GBM, KIRC, LGG, OV, PAAD, READ, SKCM, and STAD (B). *P < 0.05, **P < 0.01, ***P < 0.001.

Mutation profile and prognostic value of CD68 in pan-cancer

We then checked the mutant landscape of CD68 in different cancer types from the TCGA database using cBioportal (Fig. 2). The data showed that prostate adenocarcinoma (PRAD) and diffuse large B-cell lymphoma had a high mutation level with CD68 deep deletion of more than 4% (Fig. 2A,B). A total of 45 mutation sites (including 31 missense, 11 truncating, two splices, and one inflame) were found between amino acids 0 and 354 (Fig. 2C). Next, to understand the prognostic value of CD68 in pan-cancer further, we downloaded RNA-seq and clinical data of CD68 from the TCGA dataset. Elevated levels of CD68 were significantly related to poorer OS in GBM (hazard ratio [HR] 1.05, 95% confidence interval [CI] 1.00–1.09, P = 0.0370), KIRC (HR 1.04, 95% CI 1.0–21.06, P = 0.0007), LGG (HR 1.18, 95% CI 1.06–1.31, P = 0.0020), liver hepatocellular carcinoma (LIHC) (HR 1.06, 95% CI 1.02–1.11, P = 0.0058), lung squamous cell carcinoma (LUSC) (HR 1.04, 95% CI 1.00–1.08, P = 0.0470), thyroid carcinoma (THCA) (HR 1.17, 95% CI 1.06–1.29, P = 0.0023), and thymoma (THYM) (HR 1.47, 95% CI 1.08–2.00, P = 0.0130) (Fig. 3). In contrast, upregulated CD68 expression was associated with a favorable prognosis in kidney chromophobe (KICH) (HR 1.40, 95% CI 1.05–1.87, P = 0.0220). In addition, the high expression of CD68 was related to an unfavorable DSS in KIRC (HR 1.04, 95% CI 1.02–1.07, P = 0.0052), GBM (HR 1.05, 95% CI 1.00–1.10, P = 0.0490), LGG (HR 1.19, 95% CI 1.06–1.34, P = 0.0410), and THYM (HR 1.69, 95% CI 1.04–2.77, P = 0.0360) (Fig. 3B and Supplementary Fig. 1C–I). However, DSS was favorable in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) (HR 0.83, 95% CI 0.70–0.99, P = 0.0380) and KICH (HR 1.46, 95% CI 1.09–1.96, P = 0.0110). Furthermore, we observed the prognostic value of CD68 in DFI (Supplementary Fig. 1A) and PFI (Supplementary Fig. 1B). The results showed that high levels of CD68 were associated with a poorer DFI in GBM, LGG, and THYM and a better DFI in KICH (Supplementary Fig. 1E–I). High levels of CD68 were associated with a poorer PFI in cholangiocarcinoma (CHOL), LIHC, and STAD and a better DFI in CESC (Supplementary Fig. 1J–M).

Figure 2
figure 2

Mutant landscapes of CD68 in pan-cancer. Mutant frequency (A) and count (B) of CD68 in pan-cancer from the TGCA database based on cBioPortal analysis. Mutation aspect of CD68 in pan-cancer across protein domains (C).

Figure 3
figure 3

Survival analysis of CD68 in pan-cancer from the TCGA database. Forest plot compared the prognostic value of CD68 on OS (A) and DSS (B) across pan-cancer. Kaplan–Meier Method displayed the prognostic value of CD68 on OS in GBM (C), KICH (D), KIRC (E), LGG (F), LIHC (G), LUSC (H), THCA (I), THYM (J). The cut-off points are 61.89% (GBM), 73.44% (KICH), 15.66% (KIRC), 20.04% (LGG), 15.14% (LIHC), 16.57% (LUSC), 10.96% (THCA), 16.95% (THYM). *P < 0.05, **P < 0.01, ***P < 0.001.

Relationship between CD68 expression and immune infiltrates

Next, we explored the relationship between CD68 expression and immune infiltrates in the tumor microenvironment in 33 tumor types based on the TIMER2.0 database. As shown in Fig. 4, CD68 expression was positively correlated with immune cell infiltration, including dendritic cells, monocytes, macrophages, and neutrophils. However, CD68 expression is negatively associated with the infiltration of myeloid-derived suppressor cells. Next, we analyzed the correlation between CD68 levels and immune cell infiltration in the tumor microenvironment in 33 cancer types. The results indicated that the expression of CD68 was positively related to the abundance of B cells, CD4+ and CD8+ T cells, dendritic cells, macrophages, and neutrophils in many tumor types. As shown in Fig. 5A, the three most significantly related tumors were adrenocortical carcinoma (ACC), BRCA, and CESC. The details of other tumor types are shown in Supplementary Fig. 2. We calculated the stromal, immune, and estimated score of 33 cancer types using the ESTIMATE algorithm. As shown in Fig. 5B, the top three tumor types with CD68 expression positively correlated with stromal score were BLCA, BRCA, and GBM (P < 0.001). The top three tumor types with CD68 expression positively correlated with immune score were ACC, BLCA, and BRCA (p < 0.001). The top three tumor types with CD68 expression positively correlated with the estimate score were BLCA, BRCA, and CESC (P < 0.001). The data in Supplementary Fig. 3 shows that the expression of CD68 was significantly and positively correlated with the stromal score in all tumor types except CHOL and mesothelioma (MESO). In addition, CD68 levels were found to significantly and positively correlate with the immune score (Supplementary Fig. 4) and estimate the score (Supplementary Fig. 5) in all tumor types. These results indicate that CD68 has a close relationship with immune infiltrates in the tumor microenvironment and might act as a promising immunotherapy target.

Figure 4
figure 4

The relationship between CD68 and immune infiltrates based on the TIMER2.0 analysis in pan-cancer. The correlation between CD68 with B cell, CD4+ T cell, CD8+ T cell, dendritic cell, monocyte, macrophage in pan-cancer (A). The correlation between CD68 with NK cell, neutrophil, Tregs, mast cell, NKT, Tfh, γδT, HSC, Endo, progenitor, Eos, CAF, and MDSC in pan-cancer (B).

Figure 5
figure 5

Correlation of CD68 expression with immune infiltrates based on the CIBERSORT analysis in pan-cancer. Top three cancer types that most related to immune cell infiltration (A) and stromal score, immune score, and estimate score (B) in pan-cancer.

Tumor neoantigens are foreign proteins absent from normal human organs/tissues and are encoded by a mutated gene of tumor cells, which plays a crucial role in tumor immunotherapy. We then explored the relationship between CD68 expression and the number of neoantigens in human cancers (Fig. 6 and Supplementary Table 1). Our results indicated that high levels of CD68 were significantly and positively related to the number of neoantigens in LUAD, KIRP, CESC, and PRAD (P < 0.05).

Figure 6
figure 6

Relationship between neoantigen counts and CD68 expression in pan-cancer.

Relationship between CD68 expression and checkpoint gene markers, tumor mutation burden, and microsatellite instability

To further elucidate the potential immune mechanisms of CD68, we next compared the association of CD68 expression with various checkpoint markers in different cancer types (Fig. 7A). The results showed that CD68 expression positively correlated with the expression of LAIR1, HAVCR2, LGALS9, and PD-1 (PDCD1) in most of the 33 tumor types. We also studied the relationship between CD68 expression and five DNA mismatch repair (MMR) markers (Fig. 7B). CD68 levels were significantly and negatively correlated with mutL homolog 1, mutS homolog 2, mutS homolog 6 (MSH6), postmeiotic segregation increased 2 (PMS2), and epithelial cell adhesion molecule in BRCA, CESC, KIRC, OV, and THCA (P < 0.05). However, CD68 levels were significantly and positively correlated with MSH6 in KICH and READ (P < 0.05). In addition, we studied the correlation between tumor mutation burden (TMB) and microsatellite instability (MSI) with CD68 levels. Moreover, CD68 expression was positively correlated (P < 0.05) with TMB in UCEC, SKCM, sarcoma (SARC), READ, PRAD, LGG, KIRP, KIRC, COAD, CESC, and BRCA, and negatively correlated (P < 0.05) with TMB in THCA, READ, LIHC, LAML, and GBM (Fig. 7C). CD68 expression was positively correlated (P < 0.05) with MSI in UCEC, READ, LIHC, and COAD, but negatively correlated (P < 0.05) with MSI in KIRC, LUAD, LUSC, and TGCT (Fig. 7D). In addition, we analyzed the prognostic value of the combination of CD68 expression and these markers (MMR markers and PD-1). The results indicated that the combination of CD68 expression and MMR markers had prognostic value in KIRC, LGG, PAAD, and SARC (Supplementary Fig. 6A). The combination of CD68 expression and PD-1 had prognostic value in KIRC, LGG, SKCM, and THYM (Supplementary Fig. 6B).

Figure 7
figure 7

Relationship between immune checkpoints, DNA mismatch repair markers, TMB, MSI, and CD68 expression in pan-cancer. Correlation of CD68 expression with various immune checkpoints (A), DNA mismatch repair markers (B), TMB (C) and MSI (D) in pan-cancer. *P< 0.05, **P < 0.01, ***P < 0.001.

Functional analysis by GSEA and drug response of CD68

In addition, we analyzed the related functional signaling pathways of CD68 through GSEA based on KEGG and HALLMARK databases in pan-cancer. The top three negatively enriched KEGG terms (P < 0.001) in the upregulated CD68 subgroup were the chemokine signaling pathway, cytokine-cytokine receptor interaction, and cell adhesion molecule cams (Fig. 8A). The top three positively enriched KEGG terms in the upregulated CD68 subgroup were aminoacyl tRNA biosynthesis, valine leucine, and isoleucine biosynthesis and taste transduction (Fig. 8B). In addition, the top three negatively enriched HALLMARK terms (P < 0.001) in the upregulated CD68 subgroup were a complement, allograft rejection, and inflammatory response (Fig. 8C). The top three positively enriched HALLMARK terms in the upregulated CD68 subgroup were pancreatic beta cells and MYC targets V1 and V2 (Fig. 8D). The top five enriched pathways are shown in Supplementary Table 2.

Figure 8
figure 8

Functional enrichment of KEGG and HALLMARK terms on CD68 based on GSEA in pan-cancer. The top three negative (A) and top four positive (B) enriched KEGG terms on CD68 in pan-cancer. The top three negative (C) and top four positive (D) enriched HALLMARK terms on CD68 in pan-cancer.

Finally, we analyzed three public databases (CellMiner, CTRP, and Genomics of Drug Sensitivity in Cancer [GDSC]) to identify small molecules and sensitive drugs based on CD68 expression. The results from drug response analysis by CellMiner suggested that many small molecules were associated with CD68 expression, of which the top 16 are shown in Supplementary Fig. 7. These small molecules were found to be active in inhibiting human tumor cell line growth, including adenocarcinoma, non-small lung, melanoma, prostate, CNS, and colon. In addition, the top 20 sensitive drugs predicted from the CTRP (Supplementary Table 3) and GDSC (Supplementary Table 4) databases exhibited a close relationship with the metabolism and activation of macrophages.

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