CCR4 is a prognostic biomarker and correlated with immune infiltrates in head and neck squamous cell carcinoma

Transcriptional Inflammatory Signature in Healthy Donors and Different Radiotherapy Cancer Patients

Cancer and ionizing radiation exposure are associated with inflammation. To identify a set of radiation-specific signatures of inflammation-associated genes in the blood of partially exposed radiotherapy patients, differential expression of 249 inflammatory genes was analyzed in blood samples from cancer patients and healthy individuals. The gene expression analysis on a cohort of 63 cancer patients (endometrial, head and neck, and prostate cancer) before and during radiotherapy (24 h, 48 h, ~1 week, ~4-8 weeks, and 1 month after the last fraction) identified 31 genes and 15 up- and 16 down-regulated genes. Transcription variability under normal conditions was determined using blood drawn on three separate occasions from four healthy donors. No difference in inflammatory expression between healthy donors and cancer patients could be detected prior to radiotherapy. Remarkably, repeated sampling of healthy donors revealed an individual endogenous inflammatory signature. Next, the potential confounding effect of concomitant inflammation was studied in the blood of seven healthy donors taken before and 24 h after a flu vaccine or ex vivo LPS (lipopolysaccharide) treatment; flu vaccination was not detected at the transcriptional level and LPS did not have any effect on the radiation-induced signature identified. Finally, we identified a radiation-specific signature of 31 genes in the blood of radiotherapy patients that were common for all cancers, regardless of the immune status of patients. Confirmation via MQRT-PCR was obtained for BCL6, MYD88, MYC, IL7, CCR4 and CCR7. This study offers the foundation for future research on biomarkers of radiation exposure, radiation sensitivity, and radiation toxicity for personalized radiotherapy treatment.

Exploring Prognostic Immune Microenvironment-Related Genes in Head and Neck Squamous Cell Carcinoma from the TCGA Database

Purpose: Head and neck squamous cell carcinoma (HNSCC) has a high rate of local and distant metastases. In tumor tissues, the interaction between tumor cells and the tumor microenvironment (TME) is closely related to cancer development and prognosis. Therefore, screening for TME-related genes in HNSCC is crucial for understanding metastatic patterns. Methods: Our research relied mainly on a novel algorithm called Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE). Fragments Per Kilobase of exon model per Million mapped fragments (FPKM) data and HNSCC clinical data were obtained from the TCGA database, and the purity of HNSCC tissue and the features of stromal and immune cell infiltration were determined. Furthermore, differentially expressed genes (DEGs) were screened based on immune, stromal, and ESTIMATE scores, and their protein-protein interaction (PPI) networks and ClueGO functions were evaluated. Finally, the expression profiles of DEGs related to immunity in HNSCC were determined. Differential gene expression was verified in the highly invasive oral cancer cell lines (SCC-25, CAL-27, and FaDu) and oral cancer tissues. Results: Our analysis found that both the immune and ESTIMATE scores were significantly associated with the prognosis of HNSCC. Moreover, cross-validation using the Venn algorithm revealed that 433 genes were significantly upregulated, and 394 genes were significantly downregulated. All DEGs were associated with both ESTIMATE and immune scores. The enrichment of cytokine-cytokine receptor interactions and chemokine signaling pathways was observed using pathway enrichment analyses. We initially screened 25 genes after analyzing the key sub-networks of the PPI network. Survival analysis revealed the significance of CCR4, CXCR3, P2RY14, CCR2, CCR8, and CCL19 in relation to survival and their association with immune infiltration-related metastasis in HNSCC. Conclusions: The expression profiles of relevant TME-related genes were screened following stromal and immune cell scoring using ESTIMATE, and DEGs associated with survival were identified. These TME-related gene markers offer valuable utility as both prognostic indicators and markers denoting metastatic traits in HNSCC.

Identification of aneuploidy-related gene signature to predict survival in head and neck squamous cell carcinomas

BACKGROUND

To parse the characteristics of aneuploidy related riskscore (ARS) model in head and neck squamous cell carcinomas (HNSC) and their predictive ability on patient prognosis.

METHODS

Molecular subtyping of HNSC specimens was clustered by Copy Number Variation (CNV) data from The Cancer Genome Atlas (TCGA) dataset applying consistent clustering, followed by immune condition evaluation, differentially expressed genes (DEGs) analysis and DEGs function annotation. Weighted gene co-expression network analysis (WGCNA), protein-protein interaction, Univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analysis were implemented to construct an ARS model. A nomogram for clinic practice was designed by rms package. Immunotherapy evaluation and drug sensitivity prediction were also carried out.

RESULTS

We stratified HNSC patients into three different molecular subgroups, with the best prognosis in C1 cluster among 3 clusters. C1 cluster displayed greatest immune infiltration status. The most DEGs between C1 and C2 groups, mainly enriched in cell cycle and immune function. We constructed a nine-gene ARS model (ICOS, IL21R, CCR7, SELL, CYTIP, ZAP70, CCR4, S1PR4 and CD79A) that effectively differentiates between high- and low-risk patients. Patients in low ARS group showed a higher sensitivity to immunotherapy. A nomogram built by integrating ARS and clinic-pathological characteristics helped predict clinic survival benefit. Drug sensitivity evaluation found that 4/9 inhibitor drugs (MK-8776, AZD5438, PD-0332991, PHA-665752) acted on the cell cycle.

CONCLUSIONS

We classified 3 molecular subtypes for HNSC patients and established an ARS prognostic model, which offered a prospective direction for prognosis in HNSC.

Chemokine receptors on human regulatory T cells during cutaneous leishmaniasis

The aim of this work was to define the population of regulatory T cells (Tregs) which are circulating in the blood of Leishmania infected individuals clinically displaying a lesion (active disease-AD) and sub-clinical (SC) ones. We have individually collected blood samples, processed the PBMC and stained with fluorochrome-conjugated antibodies against CD3, CD4, Foxp3, CD25, CTLA-4, Ki-67, CCR4, CCR5, and CCR7. Cells were analyzed by flow cytometry. Our results suggest that CD25 and CTLA-4 are upregulated in Tregs of AD patients when compared to SC and uninfected (UN) controls. Moreover, Tregs proliferate upon infection based on Ki-67 nuclear antigen staining. Finally, we have observed that these Tregs of SC and AD patients upregulate CCR4, but not CCR5 and CCR7. There is an increase in the number of circulating Tregs in the blood of Leishmania infected individuals. These cells are potentially more suppressive based on the increased upregulation of CD25 and CTLA-4 during clinical infection (AD) when compared to SC infection. Tregs of both SC and AD cohorts are proliferating and express CCR4, which potentially guide them to the skin, but do not upregulate CCR5 and CCR7.

Identification and Biological Validation of a Chemokine/Chemokine Receptor-Based Risk Model for Predicting Immunotherapeutic Response and Prognosis in Head and Neck Squamous Cell Carcinoma

Over 80% of head and neck squamous cell carcinoma (HNSCC) patients failed to respond to immunotherapy, which can likely be attributed to the tumor microenvironment (TME) remolding mediated by chemokines/chemokine receptors (C/CR). This study aimed to establish a C/CR-based risk model for better immunotherapeutic responses and prognosis. After assessing the characteristic patterns of the C/CR cluster from the TCGA-HNSCC cohort, a six-gene C/CR-based risk model was developed to stratify patients by LASSO Cox analysis. The screened genes were multidimensionally validated by RT-qPCR, scRNA-seq, and protein data. A total of 30.4% of patients in the low-risk group had better responses to anti-PD-L1 immunotherapy. A Kaplan-Meier analysis showed that patients in the low-risk group had longer overall survival. A time-dependent receiver operating characteristic curve and Cox analyses indicated that risk score served as an independent predictive indicator. The robustness of the immunotherapy response and prognosis prediction was also validated in independent external datasets. Additionally, the TME landscape revealed that the low-risk group was immune activated. Furthermore, the cell communication analysis on the scRNA-seq dataset revealed that cancer-associated fibroblasts were the main communicators within the C/CR ligand-receptor network of TME. Collectively, The C/CR-based risk model simultaneously predicted immunotherapeutic response and prognosis, potentially optimizing personalized therapeutic strategies of HNSCC.

Screening of Tumor Antigens and Construction of Immune Subtypes for mRNA Vaccine Development in Head and Neck Squamous Cell Carcinoma

BACKGROUND

A growing number of clinical studies have confirmed that mRNA vaccines are effective in the treatment of malignant tumors; however, their efficacy in head and neck squamous cell carcinoma (HNSCC) has not been determined. This study aimed to identify the potential antigens of HNSCC for mRNA vaccine development and further distinguish the immune subtypes of HNSCC to select suitable patients for vaccination.

METHODS

We obtained gene expression profiles and corresponding clinical information of HNSCC from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). We visualized the genetic alterations of potential antitumor antigens using cBioPortal and obtained the immune gene set from Immport. The correlation between the expression of the identified antigens and the infiltration of antigen-presenting cells was visualized by Tumor Immune Estimation Resource (TIMER). We evaluated the potential biological functions of different samples and described the immune landscape.

RESULTS

Increased expression of three potential tumor antigens, CCR4, TMCO1, and SPACA4, associated with superior prognoses and infiltration of antigen-presenting cells, was identified in HNSCC. Three immune subtypes (C1-C3) with different molecular, cellular, and clinical characteristics were defined. Patients with C3 tumor had a better prognosis, representing an immune "cold" phenotype, which may be more suitable for mRNA vaccination. In addition, different immune characteristics were observed among the three immune subtypes, including markers of immune cells, mutation burden, expression of immune checkpoints, and immune modulators. Finally, the immune landscape of HNSCC showed a high degree of heterogeneity between individual patients.

CONCLUSION

CCR4, TMCO1, and SPACA4 may be potential antigens for developing mRNA vaccines against HNSCC, especially for patients with C3 tumor. This study could provide a theoretical basis for the development of an mRNA vaccine against HNSCC.

Identification and validation of a prognostic model based on ferroptosis-associated genes in head and neck squamous cancer

Ferroptosis is that under the action of ferrous iron or ester oxygenase, unsaturated fatty acids highly expressed on the cell membrane are catalyzed to undergo lipid peroxidation, thereby inducing cell death. In this study, we used ferroptosis marker genes to identify 3 stable molecular subtypes (C1, C2, C3) with distinct prognostic, mutational, and immune signatures by consensus clustering; TP53, CDKN2A, etc. Have higher mutation frequencies in the three subtypes. C3 has a better prognosis, while the C1 subtype has a worse prognosis. WGCNA is used to identify molecular subtype-related gene modules.After filting, we obtained a total of 540 genes related to the module feature vector (correlation>0.7).We performed univariate COX regression analysis on these genes, and identified a total of 97 genes (p < 0.05) that had a greater impact on prognosis, including 8 ''Risk" and 89 ''Protective" genes. After using lasso regression, we identified 8 genes (ZNF566, ZNF541, TMEM150C, PPAN, PGLYRP4, ENDOU, RPL23 and MALSU1) as ferroptosis-related genes affecting prognosis. The ferroptosis prognosis-related risk score (FPRS) was calculated for each sample in TCGA-HNSC dataset. The results showed that FPRS was negatively correlated with prognosis.The activated pathways in the PFRS-high group mainly include immune-related pathways and invasion-related pathways. We assessed the extent of immune cell infiltration in patients in our TCGA-HNSC cohort by using the expression levels of gene markers in immune cells. The FPRS-high group had a higher level of immune cell infiltration. We found that the expression of immune checkpoints was significantly up-regulated in the FPRS-low group and the FPRS-high group had a higher probability of immune escape and a lower probability of benefiting from immunotherapy. In this work, we constructed a scoring Ferroptosis-related prognostic model that can well reflect risk and positive factors for prognosis in patients with head and neck squamous cell carcinoma. It can be used to guide individualized adjuvant therapy and chemotherapy for patients with head and neck cancer. Therefore, it has a good survival prediction ability and provides an important reference for clinical treatment.

Comprehensive Analysis of Ferroptosis- and Immune-Related Signatures to Improve the Prognosis and Diagnosis of Kidney Renal Clear Cell Carcinoma

Background

Almost 40% of patients with kidney renal clear cell carcinoma (KIRC) with advanced cancers eventually develop to metastases, and their 5-year survival rates are approximately 10%. Aberrant DNA methylations are significantly associated with the development of KIRC. The aim of our present study was to identify suitable ferroptosis- and immune-related (FI) biomarkers correlated with aberrant methylations to improve the prognosis and diagnosis of KIRC.

Methods

ChAMP and DESeq2 in R (3.6.2) were used to screen the differentially expressed methylation probes and differentially expressed genes, respectively. Univariate and multivariate Cox regression were used to identify the overall survival (OS)-related biomarkers.

Results

We finally identified five FI biomarkers (CCR4, CMTM3, IFITM1, MX2, and NR3C2) that were independently correlated with the OS of KIRC. The area under the curve value of the receiver operating characteristic value of prognosis model was 0.74, 0.68, and 0.72 in the training, validation, and entire cohorts, respectively. The sensitivity and specificity of the diagnosis model were 0.8698 and 0.9722, respectively. In addition, the prognosis model was also significantly correlated with several immune cells and factors.

Conclusion

Our present study suggested that these five FI-DEGs (CCR4, CMTM3, IFITM1, MX2, and NR3C2) could be used as prognosis and diagnosis biomarkers for patients with KIRC, but further cross-validation clinical studies are still needed to confirm them.