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. 2021 Nov 9:12:765615.
doi: 10.3389/fimmu.2021.765615. eCollection 2021.

Pattern Recognition Receptors (PRRs) in Macrophages Possess Prognosis and Immunotherapy Potential for Melanoma

Qihang Zhao  1 , Qiang Wang  2 , Tengjiao Wang  3 , Junfang Xu  1   4 , Tingting Li  5 , Qiuyan Liu  1 , Qinghua Yao  6   7 , Pin Wang  1
Affiliations

Pattern Recognition Receptors (PRRs) in Macrophages Possess Prognosis and Immunotherapy Potential for Melanoma

Qihang Zhao et al. Front Immunol. .

Abstract

Background: Pattern recognition receptors (PRRs) family plays a vital role in the initial stage of innate immune response and the subsequent activation of adaptive immunity. Increasing evidences have indicated that several PRRs play critical roles in the progress of inflammation and tumorigenesis. However, the comprehensive significance of PRRs family in clinical prognosis of different cancers is still elusive.

Methods: We analyzed expression of 20 canonical PRRs in tumor samples from 9502 patients of 33 tumor types. Next, we used expression profiles of PRRs in skin cutaneous melanoma (SKCM) to build a Cox prognosis model. Then, we analyzed immune infiltration features and immune activity of high risk score and low risk score patients. Finally, we analyzed the single-cell sequencing data of different cancers and detected the expression of PRRs in mouse melanoma model to identify PRRs-expressing cell types.

Results: We found PRRs had a significantly positive correlation with prognosis in SKCM rather than other tumors, and PRR-based Cox model had a much better prognosis potential than any single PRR. Further analysis shows risk score could indicate immunocyte infiltration and immune activity in SKCM. We also found the expressions of some PRR genes were highly correlated with the expression of immune checkpoints molecules in SKCM, indicating they could be indicators for clinical immune therapy. Finally, we found only in SKCM samples, the expression of PRRs is especially high in a subpopulation of macrophages with a trait of CD206 low expression, probably explaining why PRRs have prognosis potential in melanoma.

Conclusions: Our study reveals PRR family in macrophages has a positive prognosis potential in melanoma and could be valuable for clinical prognosis and immune therapy.

Keywords: immune-infiltration; macrophage; pattern recognition receptors; prognosis; skin cutaneous melanoma.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Pan-cancer prognosis analysis of PRRs. Pan-cancer prognosis analysis of PRRs by GEPIA2 shows PRRs family have the specific positive prognosis ability in SKCM (33 tumor types, 9502 samples, the square frame of some samples means P value <0.05 in this prognosis analysis of the indicated PRR).
Figure 2
Figure 2
Establish of PRR-based prognosis model in SKCM. (A) Heatmap of 8 PRR molecules’ expression used in the prognosis model in 468 SKCM patients ranked by their risk score. (B) Survival curve of low risk score group and high risk score group of SKCM patients, samples which no data of survival times are filtered out. (C) Risk score is high-positive correlated to primary tumor (T). (D) ESTIMATE analysis shows risk score is positive-correlated to tumor purity (R=0.45). (E) ESTIMATE analysis shows risk score is negative-correlated to immune score in SKCM (R=-0.5). (F) ESTIMATE analysis shows risk score is negative-correlated to stromal score in SKCM (R=-0.27) .
Figure 3
Figure 3
High risk score indicates low immunocyte infiltration and weak immune activity in SKCM. (A) Correlation analysis between risk score and different immunocyte infiltration, including Neutrophil, DC, CD8+T cell, CD4+T cell, B cell, and macrophage, and immunocyte infiltration data of different SKCM samples is downloaded from TIMER database. (B) The groups of SKCM samples used for immune activity and immune-infiltration analysis. (C) Immune activity of TOP20 low risk SKCM samples and TOP20 high risk SKCM samples in TIP analysis (t test, P<0.0001). (D) Immunocyte composition of TOP20 low risk SKCM samples and TOP20 high risk SKCM samples in TIP analysis.
Figure 4
Figure 4
Expression of PRRs positively correlated with that of immune checkpoint molecules in SKCM. (A) Pearson correlation analysis reveals the correlations between 8 PRRs and immune checkpoints. (B) Expression of immune checkpoint genes in low risk and high risk SKCM patients (n=234 in low risk group, n=234 in high risk group, “*” means p<0.05, “**” means p<0.01, “***” means p<0.001). (C) The expression correlation analysis between each two of these immune checkpoint genes (PDCD1, LAG3, TIM3, and TIGIT).
Figure 5
Figure 5
Expression of immune effector genes play a positive role in SKCM prognosis. (A) Pan-cancer prognosis analysis shows the expression of PRR-driven effector molecules highly correlated to SKCM prognosis (33 tumor types, 9502 samples). (B) 6 inflammatory cytokines express higher in low risk SKCM patients (n(low risk)=234, n(high risk)=234, “***”means p<0.001).
Figure 6
Figure 6
Single cell sequencing analysis reveals PRRs’ specific expression on macrophages in melanoma. (A) Single-cell expression profiles distinguish different cell types in SKCM (tSNE). (B) Single-cell PRR expression profiles of different cellular types in SKCM. (C) tSNE graphs show PRRs’ specifically express on macrophages in SKCM samples. (D) CD206 has a specific low expression in PRR high macrophages only in SKCM samples (P<0.01).
Figure 7
Figure 7
Mouse model experiment shows PRRs’ specific expression on macrophages in melanoma samples. Melanoma cell line B16 cells were injected into subcutaneous of C57/B6-L mice (n=3), after injection of 18 days, different types of immunocytes were isolated, and then total RNA were extracted. After RT-PCR, qPCR analysis was performed to detect the expression of PRRs. The relative expression of PRRs were normalized to that of GAPDH. Results were analyzed in GraphPad Prism version 8.0.1.
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