New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine

Abstract

Over the past thirty years, the importance of chemokines and their seven-transmembrane G protein-coupled receptors (GPCRs) has been increasingly recognized. Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes, including host homeostasis and responses to disease. Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity. Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases, including cancer, immune and inflammatory diseases, and metabolic and neurological disorders, which render the system a focus of studies aiming to discover therapies and important biomarkers. The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states, including, among others, coronavirus disease 2019 (COVID-19). In this review, by reporting the latest advances in chemokine biology and results from analyses of a plethora of sequencing-based datasets, we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network, focusing on chemokine-mediated inflammation and cancer. Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.

Keywords: Chemokine; Chemokine receptor; Epigenetics; Genetics; Homeostasis; Migration.

Fig. 1

Chromosome location of chemokines and receptors. The locations of chemokines and receptors on human chromosomes. The diagrams of chromosomes were adapted from the NCBI website. The different subclasses of chemokines and receptors are highlighted with different colors

Fig. 2

The functional roles mediated by interactions of chemokines with receptors expressed on immune cells. The RNA-seq data were derived from HPA. The relative mRNA expression of chemokines (left hand columns) and receptors (upper right-hand columns) in selected immune cells is shown in the heatmap, with the color based on their transcript per million (TPM) values. The inflammatory and homeostatic chemokines and receptors are shown in red and green, respectively. Chemokines with dual functions are indicated in blue [11, 14, 18, 46]. Chemokine receptors with dual functions are classified into inflammatory families [14]; for example, CCR10/CCL27-CCL28 have been shown to have homeostatic functions [, , –354], and several mechanisms have been reported to be involved in inflammation [354]. The atypical chemokine receptors are shown in black. For instance, the platelet chemokine PF4/CXCL4 is quickly released as the first-line inflammatory mediator upon vascular injury and platelet activation. PF4 is also secreted by a variety of immune cells and has also been implicated in the pathology of a variety of inflammatory and autoimmune diseases and cancer [11, 355]. The association of chemokines with receptors was analyzed using STRING (https://string-db.org/), and their interaction networks identified based on the STRING analysis and published reviews [11, 14, 18, 46] are shown in the lower-right hand table, highlighted in purple

Fig. 3

Single-cell expression of chemokines and receptors. A summary of single-cell sequencing analyses of the expression of chemokines and receptors in human tissue cells, including immune cells and total peripheral blood mononuclear cells (PBMCs). Color coding is based on cell type, and each cell type group consists of cell types with common functions. The data were extracted from HPA (https://www.proteinatlas.org/)

Fig. 4

Genetic alterations of chemokine ligands and receptors associated with diseases. A, B. Clinically relevant single nucleotide variations (SNVs) affecting phenotype, as provided in recently published literature. A Chemokine- and receptor-associated SNVs affecting phenotype involved in health and disease. B Health- or disease-related SNVs of chemokine genes (left panel) or chemokine receptor genes (right panel) are highlighted with different colors. The predicted three-dimensional (3-D) structure models of the receptors were downloaded from AlphaFold DB (https://alphafold.ebi.ac.uk/). The inflammatory, homeostatic, and dual chemokine receptors are shown in red, blue, and green, respectively. C Genetic variations in the CCR5/CCR2 gene cluster at 3p21.31. D The structure of the CCL3L gene cluster in 17q12, showing common genetic variations. The 17q location contains the genes encoding most of the CCL subfamily members, including CCL1-5, 7, and 8, indicating their functional relevance. CCL3L, CCL3L3 and the pseudogene C-C motif chemokine ligand 3 pseudogene 1 (CCL3P1, gene ID: 390788, previous name: CCL3L2 (upper panels)) are also found in this location. The amino acid alignments and protein domains (lower panels) of CCL3 (gene ID: 6348), CCL3L1 (gene ID: 6349), and CCL3L3 (gene ID: 414062) are shown

Fig. 5

Regulatory chromatin markers and health- and disease-associated CpG methylation. A Chromatin in nondividing cells can be divided into euchromatin and heterochromatin, and the two chromatin states refer to areas that are transcriptionally active and inactive, respectively. Epigenetic factors include DNA/RNA methylation and histone modifications, RNA transcript variations (e.g., different splice forms of RNA as epigenetic regulators), and noncoding RNAs (ncRNAs, such as miRNAs, sRNAs, and ncRNAs as well as RNAi and AS), as well as chromatin architecture remodeling [, –166]. Covalent epigenetic modifications of histones and DNA are the most common epigenetic marks, and they alter neighboring nucleosomes to impact the accessibility of loci for transcription factors and coregulators. The gene or regulatory element associated with these epigenetic modification marks indicates the status (active, repressive or poised). These epigenetic marks can be determined using epigenetic analyses. Examples include chromatin immunoprecipitation (ChIP), micrococcal nuclease (MNase) and DNase I hypernasality site (DHS) assays with PCR or sequencing techniques [, , , –174]. B Heatmap showing the differentially methylated chemokine genes associated with health and disease. C Chemokine genes with differential CpG methylation associated with normal processes such as aging, body weight control, immune responses, metabolism and diseases such as neurological and mental disorders. D Health- and disease-associated CpG methylation is found in the CCR5/CCR2 gene cluster

Fig. 6

Chemokines and receptor expression and its association with clinical outcomes in human cancer. The associations of chemokine expression and receptor expression (A) with clinical patient outcomes (B) in multiple cancer types was identified using the limma method and the GEPIA tool (http://gepia.cancer-pku.cn/). Red: upregulated in tumor samples (log2FC > 1 and adjusted p < 0.05), blue: downregulated in tumor samples (log2FC < -1 and adjusted p < 0.05), gray: stable. BLCA bladder urothelial carcinoma, BRCA breast invasive carcinoma, CESC cervical squamous cell carcinoma, CHOL cholangiocarcinoma, ESCA esophageal carcinoma, GBM glioblastoma multiforme, HNSC head and neck squamous cell carcinoma, KICH kidney chromophobe, KIRC kidney renal clear cell carcinoma, KIRP kidney renal papillary cell carcinoma, LIHC liver hepatocellular carcinoma, LUAD lung adenocarcinoma, LUSC lung squamous cell carcinoma, PRAD prostate adenocarcinoma, READ rectum adenocarcinoma, STAD stomach adenocarcinoma, THCA thyroid carcinoma, UCEC uterine corpus endometrial carcinoma

Fig. 7

RNA splicing of chemokines and receptors. A Schematic representation of alternative splicing (AS) and different splicing events. Human protein-coding genes undergo AS through the use of alternate acceptor (AA) sites, alternate donor (AD) sites, alternate promoters (APs), alternate terminators (ATs), exon skipping (ES), mutually exclusive exons (ME), and retained introns (RIs), and the most common form of RIs is mutually exclusive exons (MEs), which allows constitutive splicing (Fig. 6A). B Schematic of the CXCL12 and CXCR4 transcripts. C Comparison of the alternative splicing events of CXCL12 and CXCR4 between multiple types of tumor and normal tissues. The data were extracted from TCGA RNA-seq data (https://bioinformatics.mdanderson.org/TCGASpliceSeq/). For each splicing event, the percent spliced in (PSI) was compared between normal and tumor samples by the Wilcoxon rank sum test, and splicing events with significant differences (p < 0.05) are marked with red labels. For CXCL12, AT1 is an AT event affecting exon 5.2; AT2 is an AT event affecting exon 3.3; AT3 is an AT event affecting exon 4; AT4 is an AT event affecting exon 6; RI is an RI event affecting exon 3.2; and ES is an ES event affecting exons 2.2, 3.1 and 5.1. For CXCR4, AP1 is an AP event affecting exon 1, and AP2 is an AP event affecting exon 2.1

Fig. 8

Chemokine molecules as potential noninvasive biomarkers. Heatmaps showing that differential expression of chemokines and receptors in tumor tissues from cancer patients compared to normal controls (A) or in COVID-19 specimens compared to healthy controls (B). The significant differences in between tumor tissues and normal tissues are shown in red (upregulation) or blue (downregulation) ( | log2FC | >1 & adjusted p value < 0.05). The data were downloaded from the Bbcancer database (http://bbcancer.renlab.org). The total sample number (tumor and normal samples) is shown at the bottom right. The color bars on the top indicate the sample type (yellow: CTCs; green: blood; blue: extracellular vesicles, EVs)