CXCL9 expression in breast cancer and its correlation with the characteristics of tumor immunoinfiltration

doi:10.3969/j.issn.1674-8115.2023.07.008

Abstract

Abstract:

Objective ·To explore the effect of C-X-C motif chemokine ligand 9 (CXCL9) expression on the prognosis of breast cancer patients and its correlation with tumor-infiltrating immune cells (TIICs). Methods ·Transcriptome data of 1 100 breast tumor tissues and 112 adjacent tissues were obtained from The Cancer Genome Atlas (TCGA) database. CIBERSORT deconvolution algorithm was used to analyze the proportion of TIIC subgroups in breast cancer immune microenvironment and its effect on the prognosis of patients. Differentially expressed genes, immune-related genes and breast cancer prognostic-related genes were downloaded from TCGA database, ImmPort database and GEPIA2 data platform, respectively. The intersection relationships of the three gene sets were analyzed by using R language, and the target genes were screened. Based on the downloaded transcriptome data, CXCL9 positive-related genes,the difference of CXCL9 mRNA expression in breast cancer tissues and adjacent tissues and its effect on the prognosis of patients were analyzed. STRING data platform was used to analyze the protein-protein interaction (PPI) network of CXCL9. Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis were performed on CXCL9 positive correlation genes and the genes corresponding to the interacting proteins obtained from the PPI network by using R language. Spearman correlation coefficient was used to analyze the correlation between CXCL9 mRNA expression and TIIC subgroups and immune checkpoint-related genes. Paraffin tissue samples of 60 clinical breast cancer patients were collected and made into tissue chips. The correlation between CXCL9 expression and CD8⁺ T cells infiltration in the tissue chips was detected by immunohistochemical staining (IHC). The types of CXCL9⁺ cells in breast cancer interstitium were analyzed by multiplex immunohistochemistry staining (mIHC). Kaplan-Meier (KM) survival curve was used to analyze the effect of CXCL9 mRNA expression and CD8⁺ T cell infiltration on the prognosis of breast cancer patients. Results ·CIBERSORT algorithm analysis showed that the distribution proportion of TIIC subgroups in breast cancer immune microenvironment varied greatly, and their effect on patients′ prognosis was also different. The Venn diagram of three types of gene sets was drawn, and CXCL9 was screened out. The top 150 positive correlation genes with CXCL9 were obtained. CXCL9 mRNA expression levels in four molecular types of breast cancer were higher than those in adjacent tissues (all P=0.000), and their high expressions were significantly associated with good prognosis of patients (P=0.013). A total of 41 interacting proteins were obtained through PPI network analysis. GO and KEGG analysis showed that CXCL9 and its related genes were mainly enriched in biological functions and pathways related to immune regulation. Spearman correlation coefficient analysis showed that the expression level of CXCL9 mRNA was positively correlated with CD8⁺ T cells infiltration ratio, negatively correlated with M2-type macrophages infiltration ratio, and positively correlated with most immune checkpoint genes expression (all P<0.05). IHC experiments showed that CXCL9 was highly expressed in breast cancer tissues compared with adjacent tissues, accompanied by an increased percentage of CD8⁺ T cells infiltration (P=0.000). mIHC results showed that CXCL9 was expressed in some CD68⁺ tumor-associated macrophages (TAMs) and CD11c⁺ dendritic cells (DCs) in the stroma of breast cancer. KM survival curve showed that when CXCL9 was highly expressed, CD8⁺ T cells high infiltration could prolong the survival of breast cancer patients. Conclusion ·CXCL9 can be used as a biomarker for good prognosis of breast cancer patients. The high expression of CXCL9 in the microenvironment of breast cancer is positively correlated with the infiltration ratio of CD8⁺ T cells and may activate its anti-tumor effect. The expression of CXCL9 may be closely related to the recruitment of lymphocytes into the tumor microenvironment for anti-tumor immune response.

Key words: breast cancer, C-X-C motif chemokine ligand 9 (CXCL9), tumor immunoinfiltration, bioinformatics analysis, CD8⁺T cell

CLC Number:

R737.9

DU Shaoqian, TAO Mengyu, CAO Yuan, WANG Hongxia, HU Xiaoqu, FAN Guangjian, ZANG Lijuan. CXCL9 expression in breast cancer and its correlation with the characteristics of tumor immunoinfiltration[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2023, 43(7): 860-872.

Figures/Tables 7

Fig 1 Differential analysis of TIIC subgroups in breast cancer TME

Fig 2 Effect of TIICs infiltration ratio in TME on the prognosis of breast cancer patients

Fig 3 Screening of target gene

Fig 4 Effect of the expression of target genes on the prognosis of breast cancer patients

Fig 5 PPI network construction of CXCL9 and GO functional analysis and KEGG pathway analysis of CXCL9 and its related genes

Fig 6 Correlation between CXCL9 mRNA expression and TIICs infiltration ratio in breast cancer

Fig 7 Effect of CXCL9 mRNA expression level and CD8+ T cells infiltration ratio on the prognosis of breast cancer patients

TrendMD

References 30

1	SIEGEL R L, MILLER K D, FUCHS H E, et al. Cancer statistics, 2022[J]. CA Cancer J Clin, 2022, 72(1): 7-33.
2	SCHMID P, ADAMS S, RUGO H S, et al. Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer[J]. N Engl J Med, 2018, 379(22): 2108-2121.
3	FRANZOI M A, DE AZAMBUJA E. Atezolizumab in metastatic triple-negative breast cancer: IMpassion130 and 131 trials-how to explain different results?[J]. ESMO Open, 2020, 5(6): e001112.
4	CORTES J, CESCON D W, RUGO H S, et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for previously untreated locally recurrent inoperable or metastatic triple-negative breast cancer (KEYNOTE-355): a randomised, placebo-controlled, double-blind, phase 3 clinical trial[J]. Lancet, 2020, 396(10265): 1817-1828.
5	GOODING A J, ZHANG B, GUNAWARDANE L, et al. The lncRNA BORG facilitates the survival and chemoresistance of triple-negative breast cancers[J]. Oncogene, 2019, 38(12): 2020-2041.
6	GONÇALVES H, GUERRA M R, DUARTE CINTRA J R, et al. Survival study of triple-negative and non-triple-negative breast cancer in a Brazilian cohort[J]. Clin Med Insights Oncol, 2018, 12: 1179554918790563.
7	杨芳, 于雁. 肿瘤微环境: 肿瘤转移的关键因素[J]. 中国肺癌杂志, 2015, 18(1): 48-54.
	YANG F, YU Y. Tumor microenvironment: the critical element of tumor metastasis[J]. Chinese Journal of Lung Cancer, 2015, 18(1): 48-54.
8	JIA Q, WANG A, YUAN Y, et al. Heterogeneity of the tumor immune microenvironment and its clinical relevance[J]. Exp Hematol Oncol, 2022, 11(1): 24.
9	JIA Q, WU W, WANG Y, et al. Local mutational diversity drives intratumoral immune heterogeneity in non-small cell lung cancer[J]. Nat Commun, 2018, 9(1): 5361.
10	OHTANI H. Focus on TILs: prognostic significance of tumor infiltrating lymphocytes in human colorectal cancer[J]. Cancer Immun, 2007, 7: 4.
11	BULE P, AGUIAR S I, AIRES-DA-SILVA F, et al. Chemokine-directed tumor microenvironment modulation in cancer immunotherapy[J]. Int J Mol Sci, 2021, 22(18): 9804.
12	HARLIN H, MENG Y, PETERSON A C, et al. Chemokine expression in melanoma metastases associated with CD8⁺ T-cell recruitment[J]. Cancer Res, 2009, 69(7): 3077-3085.
13	MESSINA J L, FENSTERMACHER D A, ESCHRICH S, et al. 12-Chemokine gene signature identifies lymph node-like structures in melanoma: potential for patient selection for immunotherapy?[J]. Sci Rep, 2012, 2: 765.
14	FRIDMAN W H, PAGÈS F, SAUTÈS-FRIDMAN C, et al. The immune contexture in human tumours: impact on clinical outcome[J]. Nat Rev Cancer, 2012, 12(4): 298-306.
15	TENG M W, NGIOW S F, RIBAS A, et al. Classifying cancers based on T-cell infiltration and PD-L1[J]. Cancer Res, 2015, 75(11): 2139-2145.
16	GALON J, BRUNI D. Approaches to treat immune hot, altered and cold tumours with combination immunotherapies[J]. Nat Rev Drug Discov, 2019, 18(3): 197-218.
17	GARRIDO F, APTSIAURI N, DOORDUIJN E M, et al. The urgent need to recover MHC class Ⅰ in cancers for effective immunotherapy[J]. Curr Opin Immunol, 2016, 39: 44-51.
18	BONAVENTURA P, SHEKARIAN T, ALCAZER V, et al. Cold tumors: a therapeutic challenge for immunotherapy[J]. Front Immunol, 2019, 10: 168.
19	WHERRY E J, KURACHI M. Molecular and cellular insights into T cell exhaustion[J]. Nat Rev Immunol, 2015, 15(8): 486-499.
20	RIBAS A, WOLCHOK J D. Cancer immunotherapy using checkpoint blockade[J]. Science, 2018, 359(6382): 1350-1355.
21	NEWMAN A M, LIU C L, GREEN M R, et al. Robust enumeration of cell subsets from tissue expression profiles[J]. Nat Methods, 2015, 12(5): 453-457.
22	FRANCESCHINI A, SZKLARCZYK D, FRANKILD S, et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration[J]. Nucleic Acids Res, 2013, 41(database issue): D808-D815.
23	ADAMS S, GATTI-MAYS M E, KALINSKY K, et al. Current landscape of immunotherapy in breast cancer: a review[J]. JAMA Oncol, 2019, 5(8): 1205-1214.
24	NANDA R, CHOW L Q, DEES E C, et al. Pembrolizumab in patients with advanced triple-negative breast cancer: phase Ⅰb KEYNOTE-012 study[J]. J Clin Oncol, 2016, 34(21): 2460-2467.
25	ADAMS S, LOI S, TOPPMEYER D, et al. Pembrolizumab monotherapy for previously untreated, PD-L1-positive, metastatic triple-negative breast cancer: cohort B of the phase Ⅱ KEYNOTE-086 study[J]. Ann Oncol, 2019, 30(3): 405-411.
26	WALSER T C, MA X, KUNDU N, et al. Immune-mediated modulation of breast cancer growth and metastasis by the chemokine Mig (CXCL9) in a murine model[J]. J Immunother, 2007, 30(5): 490-498.
27	YU L, YANG X, XU C, et al. Comprehensive analysis of the expression and prognostic value of CXC chemokines in colorectal cancer[J]. Int Immunopharmacol, 2020, 89(Pt B): 107077.
28	BRONGER H, KRAEFT S, SCHWARZ-BOEGER U, et al. Modulation of CXCR3 ligand secretion by prostaglandin E2 and cyclooxygenase inhibitors in human breast cancer[J]. Breast Cancer Res, 2012, 14(1): R30.
29	Pein M, Insua-Rodríguez J, Hongu T, et al. Metastasis-initiating cells induce and exploit a fibroblast niche to fuel malignant colonization of the lungs[J]. Nat Commun, 2020, 11(1): 1494.
30	DANGAJ D, BRUAND M, GRIMM A J, et al. Cooperation between constitutive and inducible chemokines enables T cell engraftment and immune attack in solid tumors[J]. Cancer Cell, 2019, 35(6): 885-900.e10.

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