The CXCL Family Contributes to Immunosuppressive Microenvironment in Gliomas and Assists in Gliomas Chemotherapy

SPI1-mediated CXCL12 expression in bladder cancer affects the recruitment of tumor-associated macrophages

Bladder cancer (BC) originates principally from the epithelial compartment of the bladder. The immune system and its diverse players, chemokines, in particular, have been related to the responses against BC. The goal of the study here was to examine if C-X-C motif chemokine 12 (CXCL12) in BC cells could manipulate protumorigenic properties of tumor-associated macrophages (TAMs) which affects anticancer immunity supporting tumor development in the tumor microenvironment. CXCL12 was found to be overexpressed in BC and predicted poor survival. CXCL12 in BC was associated with multiple immune cell infiltrations, with TAM infiltration playing a key role. CXCL12 elevated chemotaxis of TAMs. CXCL12 downregulation inhibited cellular activity and TAM and suppressed the ability of TAMs to secrete inflammatory factors and MMP9. Furthermore, chromatin immunoprecipitation analysis revealed that SPI1 was localized to the CXCL12 promoter in BC cells, suggesting that CXCL12 serves a direct target of SPI1, which was consistent with the fact that SPI1 reversed the repressive effects of si-CXCL12 on BC cell activity and TAM recruitment in vitro and in vivo. Collectively, these findings suggest that SPI1 is involved in modulating TAM recruitment, representing a new mechanism through which it may influence tumor growth. This may be partly mediated by regulating CXCL12 expression.

Identification of immune-related genes and integrated analysis of immune-cell infiltration in melanoma

OBJECTIVE

This study was conducted to screen out immune-related genes in connection with the prognosis of melanoma, construct a prognosis model and explore the relevant mechanisms.

METHODS AND MATERIALS

1973 genes associated with immune system were derived from the Immport database, and RNA-seq data of melanoma and information of patients were searched from the Xena database. Cox univariate analysis, Lasso analysis and Cox multivariate analysis were used to screen out six genes to construct the model. Then the risk scores were estimated for patients based on our constructed prognosis model. Estimate was used to affirm that the model was about immune infiltration, and CIBERSORT was used to screen out immune cells associated with prognosis. TIDE was applied to predict the efficacy of immunotherapy. Finally, GSE65904 and GSE19234 were used to confirm the effectiveness of the model.

RESULTS

ADCYAP1R1, GPI, NTS might cause poor prognosis while IFITM1, KIR2DL4, LIF were more likely conductive to prognosis of melanoma patients and a model of prognosis was constructed on the basis of these six genes. The effectiveness of the model has been proven by the ROC curve, and the miRNAs targeting the screened genes were found out, suggesting that the immune system might impact on the prognosis of melanoma by T cell CD8+, T cell CD4+ memory and NK cells.

CONCLUSIONS

In this study, the screened six genes were associated with the prognosis of melanoma, which was conductive to clinical prognostic prediction and individualized treatment strategy.

CHRM3 is a novel prognostic factor of poor prognosis and promotes glioblastoma progression via activation of oncogenic invasive growth factors

Glioblastoma (GBM) is the most aggressive cancer of the brain and has a high mortality rate due to the lack of effective treatment strategy. Clarification of molecular mechanisms of GBM's characteristic invasive growth is urgently needed to improve the poor prognosis. Single-nuclear sequencing of primary and recurrent GBM samples revealed that levels of M3 muscarinic acetylcholine receptor (CHRM3) were significantly higher in the recurrent samples than in the primary samples. Moreover, immunohistochemical staining of an array of GBM samples showed that high levels of CHRM3 correlated with poor prognosis, consistent with The Cancer Genome Atlas database. Knockdown of CHRM3 inhibited GBM cell growth and invasion. An assay of orthotopic GBM animal model in vivo indicated that inhibition of CHRM3 significantly suppressed GBM progression with prolonged survival time. Transcriptome analysis revealed that CHRM3 knockdown significantly reduced an array of classic factors involved in cancer invasive growth, including MMP1/MMP3/MMP10/MMP12 and CXCL1/CXCL5/CXCL8. Taken together, CHRM3 is a novel and vital factor of GBM progression via regulation of multiple oncogenic genes and may serve as a new biomarker for prognosis and therapy of GBM patients.

Prognostic significance and mechanisms of CXCL genes in clear cell renal cell carcinoma

This study aimed to investigate the clinical significance, biological functions, and underlying mechanisms of CXCL genes in clear cell renal cell carcinoma (ccRcc) based on patient datasets and pan-cancer analysis. The interaction between CXCL genes in ccRcc and immune components, particularly in relation to neutrophil recruitment and polarization mechanisms, was also evaluated. Furthermore, a risk score was developed using a signature for neutrophil polarization. The role of CXCL2 was assessed through in vitro experiments. Results showed that five CXCL genes (CXCL 2, 5, 9, 10, and 11) were upregulated in renal cancer tissue, while seven genes (CXCL 1, 2, 3, 5, 8, 13, and 14) significantly impacted patient survival. Moreover, CXCL 1, 5, and 13 affected progression-free survival. Besides, differences in mRNA expression and immune components affected renal cancer outcomes. Furthermore, three pairs of CXCL gene-immune cell interactions (CXCL13-CD8+ T cells, CXCL9/10-M1 cells, CXCL1/2/3/8-neutrophils) were identified through single-cell and pan-cancer analysis. A TAN risk score with prognostic value for KIRC patients was constructed using 11 genes and a TAN signature. Neutrophil polarization significantly impacted survival. Notably, CXCL2 was involved in neutrophil recruitment and polarization, thus promoting ccRcc progression. In conclusion, seven prognostic CXCL genes (CXCL 1/2/3/5/8/13/14) for ccRcc patients and three pairs of CXCL gene-immune cell interactions were identified. Furthermore, results showed that CXCL 2 promotes ccRcc progression through neutrophil recruitment and polarization.

Pan-cancer and single-cell analysis reveal the prognostic value and immune response of NQO1

Background: Overexpression of the NAD(P)H: Quinone Oxidoreductase 1 (NQOI) gene has been linked with tumor progression, aggressiveness, drug resistance, and poor patient prognosis. Most research has described the biological function of the NQO1 in certain types and limited samples, but a comprehensive understanding of the NQO1's function and clinical importance at the pan-cancer level is scarce. More research is needed to understand the role of NQO1 in tumor infiltration, and immune checkpoint inhibitors in various cancers are needed. Methods: The NQO1 expression data for 33 types of pan-cancer and their association with the prognosis, pathologic stage, gender, immune cell infiltration, the tumor mutation burden, microsatellite instability, immune checkpoints, enrichment pathways, and the half-maximal inhibitory concentration (IC50) were downloaded from public databases. Results: Our findings indicate that the NQO1 gene was significantly upregulated in most cancer types. The Cox regression analysis showed that overexpression of the NQO1 gene was related to poor OS in Glioma, uveal melanoma, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma, and adrenocortical carcinoma. NQO1 mRNA expression positively correlated with infiltrating immune cells and checkpoint molecule levels. The single-cell analysis revealed a potential relationship between the NQO1 mRNA expression levels and the infiltration of immune cells and stromal cells in bladder urothelial carcinoma, invasive breast carcinoma, and colorectal cancer. Conversely, a negative association was noted between various drugs (17-AAG, Lapatinib, Trametinib, PD-0325901) and the NQO1 mRNA expression levels. Conclusion: NQO1 expression was significantly associated with prognosis, immune infiltrates, and drug resistance in multiple cancer types. The inhibition of the NQO1-dependent signaling pathways may provide a promising strategy for developing new cancer-targeted therapies.

Establishment and validation of a novel integrin-based prognostic gene signature that sub-classifies gliomas and effectively predicts immunosuppressive microenvironment

The integrin family members play a key role in cancer immunomodulation and prognosis. We comprehensively analyzed the expression patterns and clinical significance of integrin family-related genes in gliomas. A total of 2293 gliomas from the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and Gliovis platform were enrolled for analyses. Twenty-six integrin coding genes showed different expression patterns between glioma and normal brain tissues. We screened an integrin family-related gene signature (ITGA5, ITGA9, ITGAE, ITGB7 and ITGB8) that showed independent prognostic value and sub-classified gliomas into different prognostic and molecular clusters, further composed an integrin-based risk score model associated with glioma malignant clinical features, overall survival (OS), and immune microenvironment alterations. Besides, glioma patients with high-risk scores showed chemotherapeutic resistance and more immune cells infiltration as well as high immune checkpoints expression. Concurrently, we also revealed that high-risk score group presented resistance to T cell-mediated cancer killing process and lower rates of response to immune checkpoint blockade (ICB) treatment. In conclusion, our study identified a valuable integrin gene signature that predicted gliomas OS effectively, and sub-classified them into different phenotypes and accompanied with immunological changes, possibly acted as a biomarker for ICB treatment.

Tumor-secreted lactate contributes to an immunosuppressive microenvironment and affects CD8 T-cell infiltration in glioblastoma

Introduction

Glioblastoma is a malignant brain tumor with poor prognosis. Lactate is the main product of tumor cells, and its secretion may relate to immunocytes' activation. However, its role in glioblastoma is poorly understood.

Methods

This work performed bulk RNA-seq analysis and single cell RNA-seq analysis to explore the role of lactate in glioblastoma progression. Over 1400 glioblastoma samples were grouped into different clusters according to their expression and the results were validated with our own data, the xiangya cohort. Immunocytes infiltration analysis, immunogram and the map of immune checkpoint genes' expression were applied to analyze the potential connection between the lactate level with tumor immune microenvironment. Furthermore, machine learning algorithms and cell-cell interaction algorithm were introduced to reveal the connection of tumor cells with immunocytes. By co-culturing CD8 T cells with tumor cells, and performing immunohistochemistry on Xiangya cohort samples further validated results from previous analysis.

Discussion

In this work, lactate is proved that contributes to glioblastoma immune suppressive microenvironment. High level of lactate in tumor microenvironment can affect CD8 T cells' migration and infiltration ratio in glioblastoma. To step further, potential compounds that targets to samples from different groups were also predicted for future exploration.

Combined serum CXCL8, CXCL9 and CXCL13 tests for the prediction of microvascular invasion in hepatocellular carcinoma

Aim: This work is to explore the predictive and diagnostic value of chemokine C-X-C motif ligand 8 (CXCL8), CXCL9 and CXCL13 combined detections for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. Materials & methods: A total of 82 HCC patients with MVI were recruited as the MVI group and 154 patients with non MVI were recruited as the non MVI group. Results: In HCC patients with MVI, CXCL8, CXCL9, CXCL13 levels were significantly elevated. Child-Pugh scores and serum α-fetoprotein level had positive correlation with CXCL8, CXCL9 and CXCL13 levels. The serum levels of CXCL8, 9 and 13 were effective in predicting MVI in HCC patients. Conclusion: CXCL8, CXCL9 and CXCL13 levels in HCC patients are valuable parameters in the prediction of MVI.

Prognostic Significance of the CXCLs and Its Impact on the Immune Microenvironment in Ovarian Cancer

The chemokine (C-X-C motif) ligand (CXCL) family in tumor tissue is closely related to tumor growth, metastasis, and survival. However, the differential expression profile and prognostic value of the CXCLs in ovarian cancer (OC) have not been elucidated. Therefore, we studied the expression levels and mutations of CXCLs in OC patient in TCGA and various public databases. The expression differences of CXCLs in OC cancer tissues and normal tissues were compared through the Gene Expression Profiling Interactive Analysis (GEPIA) database. The effect of CXCLs on OC prognosis was analyzed using the Kaplan-Meier curves in GEPIA database. The impact of CXCLs on immune infiltration and clinicopathological outcomes in OC was assessed using the TIMER algorithm. Compared with normal tissues, we found that eight CXCLs were significantly differentially expressed in OC. The expression levels of CXCL9 (P = 0.0201), CXCL11 (P = 0.0385), and CXCL13 (P = 0.0288) were significantly associated with tumor stage. CXCL13 was the only gene that significantly affected both disease-free survival (DFS) and overall survival (OS) in OC, and higher CXCL13 transcript levels implied longer DFS and OS. Although there was no significant impact on DFS, CXCL10 (P = 0.0079) and CXCL11 (P = 0.0011) expression levels had a significant effect on OS in OC. At the same time, CXCLs were significantly associated with several immune-infiltrating cells in OC tissues. The CXCLs were significantly associated with one or more immune-infiltrating cells in OC tissue. CXCL13 was differentially expressed in OC and significantly affected the prognosis of patients and was a potential marker of OC prognosis.

Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas

Background

Low-grade gliomas (LGG) are one of the most prevalent types of brain cancers. The efficacy of immunotherapy in LGG is limited compared to other cancers. Immunosuppression in the tumor microenvironment (TME) of LGG is one of the main reasons for the low efficacy of immunotherapy. Recent studies have identified 33 positive regulators of T cell functions (TPRs) that play a critical role in promoting the proliferation, activity, and functions of multiple immunocytes. However, their role in the TME of LGG has not been investigated. This study aimed to construct a risk model based on these TPRs and to detect the significance of immunotypes in predicting LGG prognosis and immunotherapy efficacy.

Methods

A total of 688 LGGs and 202 normal brain tissues were extracted from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases. The NMF R package was used to identify TRP-related subtypes. The TPR prognostic model was established using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival of LGG samples.

Results

The Subtype 2 patients had worse survival outcomes, suppressed immune function, and higher immune cell infiltration. A risk regression model consisting of 14 TPRs was established, and its performance was validated in CGGA325 cohorts. The low-risk group exhibited better overall survival, immune microenvironment, and immunotherapy response, as determined via the TIDE algorithm, indicating that increasing the level of immune infiltration can effectively improve the response to immunotherapy in the low-risk group. The risk score was determined to be an independent hazard factor (p<0.001) although other clinical features (age, sex, grade, IDH status, 1p19q codel status, MGMT status, and accepted radiotherapy) were considered. Lastly, high-risk groups in both cohorts revealed optimal drug responses to rapamycin, paclitaxel, JW-7-52-1, and bortezomib.

Conclusions

Our study identified two distinct TPR subtypes and built a TPR signature to elucidate the characteristics of T cell proliferation in LGG and its association with immune status and prognosis. These findings shed light on possible immunotherapeutic strategies for LGGs.

Bioinformatics Analysis of Prognostic Significance and Immune Characteristics of CXC Chemokine Family in Patients with Lung Adenocarcinoma

Objective

To screen CXC chemokines related to the risk of lung adenocarcinoma (LUAD) using bioinformatics and construct a CXC-based prognostic risk model to improve the diagnosis and treatment of LUAD patients.

Methods

The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database were searched to obtain mRNA expression data and clinicopathological information of LUAD patients. CXC genes differentially expressed in LUAD were screened using the R packages. Further, risk factors significantly associated with the survival of LUAD patients were obtained by the univariate Cox proportional hazard regression, LASSO regression, and multivariate Cox proportional hazard regression analysis, following which a risk prediction model was constructed. The performance of the CXCL13-based model in predicting the prognosis of low-risk and high-risk effect LUAD patients was verified, and the association between the model and the degree of tumor immune cell infiltration was investigated.

Results

CXCL13 was significantly highly expressed in the cancer tissues of LUAD patients. The risk of death in patients with highly expressed CXCL13 was about 1.5 times higher than in those with lowly expressed CXCL13 (HR = 1.5153357). CXCL13-based risk scoring showed that the high-risk score of LUAD patients was significantly correlated with poor prognosis, but no relation between the two was found in the GEO validation sets, suggesting that this risk model may not be accurate enough. In addition, activated B cells, CD4+ T cells, CD8+ T cells, and dendritic cells were significantly positively correlated with the high risk of LUAD.

Conclusions

Although we found that a high expression of CXCL13 was associated with a high risk of death and immune cell infiltration and activation in LUAD patients, the CXCL13-based risk model was not accurate enough for predicting the prognosis of LUAD patients.

Bioinformatics analysis of lncRNAs in the occurrence and development of osteosarcoma

BACKGROUND

Osteosarcoma (OS) is a disease with high mortality in children and adolescents, and metastasis is one of its important clinical features. However, the molecular mechanism of OS occurrence is not completely clear. Thus, we screened potential biomarkers of OS and analyze their prognostic value.

METHODS

The Cancer Genome Atlas (TCGA) datasets were used to analyze the differential lncRNAs in patients with OS of different immune score and the lncRNAs expressed by immune cells. Cox regression was used to develop the prognosis prediction model and specify the prognosis outcomes. Risk-proportional regression model was constructed, and the samples were divided into high and low groups based on the risk scores for the survival analysis. The areas under the receiver operating characteristic (ROC) curve were calculated and the risk-score model was verified. Finally, using 4 gene sets (comprising chemokines, immune checkpoint blockades, immune activity-related genes, and immune cells), and 4 analysis tools (CIBERSORT, TIMER, XCELL and MCP) to evaluated tumor immune infiltration.

RESULTS

Twenty-nine long non-coding ribonucleic acids (lncRNAs) were obtained from the intersection of the screened lncRNAs. Caspase recruitment domain-containing protein 8-antisense RNA 1 (CARD8-AS1), lncRNA five prime to Xist (FTX), KAT8 regulatory NSL complex unit 1-antisense RNA 1 (KANSL1-AS1), Neuroplastin Intronic Transcript 1 (NPTN-IT1), oligodendrocyte maturation-associated long intervening non-coding RNA (OLMALINC) and RPARP Antisense RNA 1 (RPARP-AS1) were found to be correlated with survival. Univariate and multivariate regression analysis showed risk score [HR (hazard ratio) 3.5, P value 0.0043; HR 3.7, P value 0.0033] and metastasis (HR 4.7, P value 6.60E-05; HR 4.8, P value 8.36E-05) were the key factors of patients with OS. The areas under curves (AUCs) of the 1-, 3-, and 5-year ROC curves of the prognostic model were 0.715, 0.729, and 0.771. The low-risk patients tended to have a high abundance of immune cells.

CONCLUSIONS

This study showed that a risk score based on 6 lncRNAs has potential value in the prognosis of OS, and patients with low-risk scores have high immune cell infiltration and good prognosis. This study may enrich understandings of underlying mechanisms related to the occurrence and development of OS.

Large-Scale Single-Cell and Bulk Sequencing Analyses Reveal the Prognostic Value and Immune Aspects of CD147 in Pan-Cancer

CD147 plays an important role in promoting tumor proliferation and inhibiting cancer cell apoptosis in the tumor microenvironment. However, the mechanisms by which CD147 is involved in tumorigenesis remains unclear. This study systematically analyzed the prognostic value and immune characteristics of CD147 in 31 cancer types. The expression levels and mutant landscapes of CD147 in pan-cancer were explored. The Kaplan-Meier (KM) analysis was applied to analyze the prognostic value of CD147. The immune characteristics of CD147 in the tumor microenvironment were evaluated via TIMER 2.0 and R package (immunedeconv). We also explored the expression of CD147 on tumor cells and stromal cells through Gene Set Variation Analysis and single-cell sequencing analysis. The co-expression of CD147 and macrophage markers CD68 and CD163 in pan-cancer was detected using multiplex immunofluorescence staining on tissue microarrays. CD147 was found to be overexpressed in almost all cancer types, which was related to poor outcome. CD147 expression exhibited a strong association with immune infiltrates, immune checkpoint molecules, and neoantigen levels in the tumor microenvironment. In addition, CD147 was expressed on various cell types in the tumor microenvironment, including tumor cells, macrophages, T cells, monocytes, fibroblasts, etc. Furthermore, multiplex immunofluorescence revealed the co-expression pattern of CD147 and macrophage markers CD68 and CD163 in many tumor types. Finally, the immunotherapy response and sensitive small molecule drugs based on CD147 expression were predicted. In sum, CD147 has a significant relationship with the clinical outcome and immune infiltrates in multiple cancer types. Inhibiting the CD147-dependent signaling pathways might be a promising therapeutic strategy for tumor immunotherapy.