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. 2021 Nov 29;21(1):635.
doi: 10.1186/s12935-021-02350-8.

Correlation of CCL8 expression with immune cell infiltration of skin cutaneous melanoma: potential as a prognostic indicator and therapeutic pathway

Peipei Yang #  1 , Wanrong Chen #  2 , Hua Xu  3 , Junhan Yang  1 , Jinghang Jiang  2   4 , Yunhui Jiang  5 , Ganglin Xu  6
Affiliations

Correlation of CCL8 expression with immune cell infiltration of skin cutaneous melanoma: potential as a prognostic indicator and therapeutic pathway

Peipei Yang et al. Cancer Cell Int. .

Abstract

Background: The tumor microenvironment (TME) is critical in the progression and metastasis of skin cutaneous melanoma (SKCM). Differences in tumor-infiltrating immune cells (TICs) and their gene expression have been linked to cancer prognosis. Given that immunotherapy can be effective against SKCM, we aimed to identify key genes that regulate the immunological state of the TME in SKCM.

Methods: Data from 471 SKCM patients in the The Cancer Genome Atlas were analyzed using ESTIMATE algorithms to generate an ImmuneScore, StromalScore, and EstimateScore for each patient. Patients were classified into low- or high-score groups based on median values, then compared in order to identify differentially expressed genes (DEGs). Then a protein-protein interaction (PPI) network was developed, and a prognostic model was created using uni- and multivariate Cox regression as well as the least absolute shrinkage and selection operator (LASSO). Key DEGs were identified using the web-based tool GEPIA. Profiles of TIC subpopulations in each patient were analyzed using CIBORSORT, and possible correlations between key DEG expression and TICs were explored. Levels of CCL8 were determined in SKCM and normal skin tissue using immunohistochemistry.

Results: Two scores correlated positively with the prognosis of SKCM patients. Comparison of the low- and high-score groups revealed 1684 up-regulated and 18 down-regulated DEGs, all of which were enriched in immune-related functions. The prognostic model identified CCL8 as a key gene, which CIBERSORT found to correlate with M1 macrophages. Immunohistochemistry revealed strong expression in SKCM tissue, but failed to detect the protein in normal skin tissue.

Conclusions: CCL8 is a potential prognostic marker for SKCM, and it may become an effective target for melanoma in which M1 macrophages play an important role.

Keywords: M1 macrophages; Skin cutaneous melanoma; Tumor microenvironment; Tumor-infiltrating immune cells.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Correlation of A EstimateScore, B ImmuneScore and C StromalScore with overall survival of SKCM patients, based on Kaplan–Meier analysis
Fig. 2
Fig. 2
Correlation of A–D EstimateScore, E–H ImmuneScore and I–L StromalScore with clinical features of SKCM patients
Fig. 3
Fig. 3
Differentially expressed genes (DEGs) between patients with low or high ImmuneScores or StromalScores. A, B Heat map of the top 50 up- and down-regulated DEGs between patients with low or high scores. C, D Venn plot showing the DEGs common to the comparisons based on ImmuneScore or StromalScore
Fig. 4
Fig. 4
Functional Enrichment of DEGs. A Enrichment in Gene Ontology (GO) terms. B Enrichment in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. C Protein–protein interaction (PPI) network for the 30 genes with the largest numbers of interconnected nodes
Fig. 5
Fig. 5
Establishment of a prognostic model. A Cross-validation to select the tuning parameter for the least absolute shrinkage and selection operator (LASSO) model for overall survival. B LASSO coefficients for DEGs associated with overall survival of SKCM patients. C Forest plots of the four genes in the final prediction model (PLA2G5, ABCB1, CCL8, and KLRK1), based on multivariate Cox regression
Fig. 6
Fig. 6
Validation of the prognostic model. A Nomogram for predicting overall survival of SKCM patients at 5, 10 and 20 years, based on the four key genes. B Calibration curves for predicting patient survival at 5, 10 and 20 years. C Heat map showing expression of the four genes among patients in the training group, stratified by overall survival. Distribution of the four-gene risk score and survival times of patients in the training group. D Heat map showing expression of the four genes among patients in the validation group, stratified by overall survival. Distribution of the four-gene risk score and survival times of patients in the validation group. E Heat map showing expression of the four genes among all patients in study, stratified by overall survival. Distribution of the four-gene risk score and survival times of all patients
Fig. 7
Fig. 7
The four-gene signature risk score was determined based on Kaplan–Meier analysis of overall survival and on receiver operating characteristic curves. A–C Analysis of the training group, validation group and all patients in the study. D–F Time-dependent receiver operating characteristic curves for 5, 10 and 20 years in the training group, validation group, and all patients in the study
Fig. 8
Fig. 8
Verification of survival differences based on GEPIA. A–D Differences in the expression of CCL8, ABCB1, KLRK1, and PLA2G5 between tumor and normal tissues. The difference in CCL8 expression was statistically significant
Fig. 9
Fig. 9
The prognostic role of CCL8 in SKCM. A Relationship between CCL8 expression and SKCM prognosis. B, C Correlation between CCL8 expression and clinical features
Fig. 10
Fig. 10
Analysis of TICs and CCL8. A Relative proportions of 22 immune cell types in each patient, based on the CIBERSORT algorithm. B Correlations among the 22 immune cell types. Blue and red represent positive and negative relationships, respectively. C Correlation between M1 macrophages and patient survival. D Positive correlation between CCL8 expression and M1 macrophages
Fig. 11
Fig. 11
Immunohistochemical analysis of CCL8. A Positive immunostaining for CCL8 in the cytoplasm of SKCM tissue. B Positive immunostaining is visible in SKCM cells (left) but not in adjacent normal cells (right) within the same surgical sample. C CCL8 was undetectable in normal skin tissue. Arrow, anti-CCL8 staining; pentagon, lack of anti-CCL8 staining
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