Prognostic Significance and Therapeutic Target of CXC Chemokines in the Microenvironment of Lung Adenocarcinoma

Abstract

Background: Lung adenocarcinoma (LUAD) is one of the most important subtypes of lung cancer and has a high morbidity and mortality. Inflammatory CXC chemokines in tumor microenvironment can stimulate tumor growth, invasion, and metastasis, affecting the prognosis of patients. However, the differential expression profiles, prognostic values, and specific mechanisms of the CXC chemokine family in LUAD have not been clarified. Methods: Transcriptome expression profile data were extracted from TIMER and TCGA. GEPIA was used to compare the relationship between CXC chemokines and clinicopathologic parameters. The prognostic analysis was performed using a Kaplan-Meier curve in GEPIA. LinkedOmics and TRRUST were applied to conduct the enrichment analysis of the regulatory networks containing the kinase targets, miRNA targets, and transcriptional factor targets. The characteristics of immune infiltration and immune-related clinical outcomes were evaluated with TIMER algorithms. Single-cell RNA sequencing localization analysis of genes as prognostic biomarkers were performed by PanglaoDB. Results: Nine differentially expressed genes were identified in LUAD compared to normal tissues. Aberrant expression of CXCL2 (P =0.0017), CXCL13 (P= 0.0271), CXCL16 (P= 0.016), and CXCL17 (P= 2.14e-5) was significantly correlated with clinical cancer stage. Furthermore, patients with low gene transcription of CXCL 7 (P = 0.017) and high expression of CXCL 17 (P = 0.00045) had a better prognosis in LUAD. We also found that immune cell infiltration was significantly correlated with LUAD microenvironment mediated by CXC chemokines. Cox proportional hazard model test was conducted and indicated that B cell infiltration could prolong the survival of the LUAD patients. CXCL17 exerted anti-tumors effect through pulmonary alveolar type II cells according to singlecell analysis. Conclusion: Our research identified the aberrant expression profiles and prognostic biomarkers of CXC chemokines in LUAD. This detailed analysis of the regulatory factor networks for CXC chemokine gene expression may provide novel insights for selecting potential immunotherapeutic targets.

Role of pyroptosis-related cytokines in the prediction of lung cancer

“…MIP-1α, MIP-1β and MIP-2, as important chemokines, play pivotal role in attracting immune cells to tumor tissues sites [ 22 , 23 ]. However, other studies also found that higher expression of MIP-1α, MIP-1β or MIP-2 were also associated with poorer prognosis and decreased survival rate in lung adenocarcinoma patients [ [24] , [25] , [26] ]. High levels of MIP-1α have also been linked to promoting cancer cells growth and survival by stimulating tumor neovascularization [ 27 , 28 ].…”

Establishment of lung adenocarcinoma classification and risk model based on necroptosis-related genes

“…In this study, seven genes were identified as prognostic genes related to the phenotype of necroptosis, and FAM83A was one of them. In addition, these six genes (HMMR ( Li et al, 2020b ; Li et al, 2021 ), ANLN ( Zhang et al, 2020 ; Deng et al, 2021 ), RHOV ( Wang et al, 2021b ; Zhang et al, 2021 ), CXCL17 ( Liu et al, 2020 ; Wang et al, 2022 ), MS4A1 ( Ma et al, 2020 ; Song et al, 2020 ), and CCR2 ( Liu and Wu, 2021 ; Wan et al, 2021 )) have also been studied to support their use as potential prognostic biomarkers and possible immunotherapeutic targets related to LUAD, but our research supports their involvement in the incidence and development of LUAD from the perspective of cell necroptosis.…”

Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing

“…The prognostic markers and the indications for prognosis in these studies are summarized in Table 2 . 36 , 44 , 45 , 47 – 49 , 55 – 89 DEGs and their combined prognostic model were the most common types of prognostic markers in these studies. For example, one study identified nine cancer-specific DEGs (CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6) and established a prognostic risk model in combination with clinical factors.…”

“…Immune cell infiltration, specifically B-cell infiltration was significantly correlated with LUAD microenvironment mediated by cysteine(C)-non cysteine(X)-cysteine(C) (CXC) chemokines. 68 In addition, Arf-GAP with coiled-coil ankyrin (ANK) repeat and PH domain-containing protein 1 (ACAP1) expression appeared to be positively associated with the infiltrating level of immune cells in TIME and the expression of immune checkpoint molecules. 76 ACAP1 was highly correlated with T-cell activation and immune response.…”