Development of Chromatin Regulator-related Molecular Subtypes and a Signature to Predict Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma.

Chromatin regulators (CRs) serve as indispensable factors in tumor biological processes by influencing tumorigenesis and the immune microenvironment and have been identified in head and neck squamous cell carcinoma (HNSCC). Hence, CR-related genes (CRRGs) are considered potential biomarkers for predicting prognosis and immune infiltration in HNSCC. In this study, we established a novel signature for predicting the prognosis and immunotherapeutic response of HSNCC. A total of 870 CRRGs were obtained according to previous studies. Subsequently, patients in the TCGA-HNSC cohort were divided into different clusters based on the expression of prognostic CRRGs. Kaplan‒Meier (K‒M) survival analysis was conducted to compare the prognosis in clusters, and the CIBERSORT and ssGSEA methods assessed the immune infiltration status. In addition, the differences in immunotherapeutic responses were determined based on the TICA database. Furthermore, the differentially expressed CRRGs between clusters were identified, and the predictive signature was established according to the results of univariate Cox, least absolute shrinkage and selection operator regression analysis, and multivariate Cox. The predictive effects of the risk model were evaluated according to the area under the receiver operating characteristic (ROC) curve (AUC) in both the training and external test cohorts. A nomogram was established, and survival comparisons, functional enrichment analyses, and immune infiltration status and clinical treatment assessments were performed. In addition, the hub gene network and related analysis were conducted with the Cytohubba application. Based on the expression of prognostic CRRGs, patients were divided into two clusters, in which Cluster 1 exhibited a better prognosis, more enriched immune infiltration, and a better immunotherapeutic response but exhibited chemotherapy sensitivity. The AUC values of the 1-, 3- and 5- year ROC curves for the risk model were 0.673, 0.732, and 0.692, respectively, as well as 0.645, 0.608, and 0.623 for the test set. In addition, patients in the low-risk group exhibited more immune cell enrichment and immune function activation, as well as a better immunotherapy response. The hub gene network indicated ACTN2 as the core gene differentially expressed between the two risk groups. We identified molecular subtypes and established a novel predictive signature based on CRRGs. This effective CRRS system can possibly provide a novel research direction for exploring the correlation between CRs and HNSCC and requires further experimental validation.

Huang J ，Xu Z ，Wang Z ，Zhou C ，Shen Y ... -  《-》

Seven Immune-Related Genes' Prognostic Value and Correlation with Treatment Outcome in Head and Neck Squamous Cell Carcinoma.

Mu R ，Shen Y ，Guo C ，Zhang X ，Yang H ，Yang H ... -  《-》

DNA-methylome-derived epigenetic fingerprint as an immunophenotype indicator of durable clinical immunotherapeutic benefits in head and neck squamous cell carcinoma.

Cancer immunotherapy provides durable response and improves survival in a subset of head and neck squamous cell carcinoma (HNSC) patients, which may due to discriminative tumor microenvironment (TME). Epigenetic regulations play critical roles in HNSC tumorigenesis, progression, and activation of functional immune cells. This study aims to identify an epigenetic signature as an immunophenotype indicator of durable clinical immunotherapeutic benefits in HNSC patients. Unsupervised consensus clustering approach was applied to distinguish immunophenotypes based on five immune signatures in The Cancer Genome Atlas (TCGA) HNSC cohort. Two immunophenotypes (immune 'Hot' and immune 'Cold') that had different TME features, diverse prognosis, and distinct DNA methylation patterns were recognized. Immunophenotype-related methylated signatures (IPMS) were identified by the least absolute shrinkage and selector operation algorithm. Additionally, the IPMS score by deconvolution algorithm was constructed as an immunophenotype classifier to predict clinical outcomes and immunotherapeutic response. The 'Hot' HNSC immunophenotype had higher immunoactivity and better overall survival (p = 0.00055) compared to the 'Cold' tumors. The immunophenotypes had distinct DNA methylation patterns, which was closely associated with HNSC tumorigenesis and functional immune cell infiltration. 311 immunophenotype-related methylated CpG sites (IRMCs) was identified from TCGA-HNSC dataset. IPMS score model achieved a strong clinical predictive performance for classifying immunophenotypes. The area under the curve value (AUC) of the IPMS score model reached 85.9% and 89.8% in TCGA train and test datasets, respectively, and robustness was verified in five HNSC validation datasets. It was also validated as an immunophenotype classifier for predicting durable clinical benefits (DCB) in lung cancer patients who received anti-PD-1/PD-L1 immunotherapy (p = 0.017) and TCGA-SKCM patients who received distinct immunotherapy (p = 0.033). This study systematically analyzed DNA methylation patterns in distinct immunophenotypes to identify IPMS with clinical prognostic potential for personalized epigenetic anticancer approaches in HNSC patients. The IPMS score model may serve as a reliable epigenome prognostic tool for clinical immunophenotyping to guide immunotherapeutic strategies in HNSC.

Li R ，Wen X ，Lv RX ，Ren XY ，Cheng BL ，Wang YK ，Chen RZ ，Hu W ，Tang XR ... -  《-》

A novel Pyroptosis-related long non-coding RNA signature for predicting the prognosis and immune landscape of head and neck squamous cell carcinoma.

Pyroptosis plays an essential function in carcinogenesis and the antitumor immune response. Herein, we constructed a pyroptosis-related long noncoding RNA (prLncRNA) signature to predict therapeutic effects and outcomes for head and neck squamous cell carcinoma (HNSCC) patients. Patients obtained from the TCGA-HNSC project were divided randomly into the training as well as the validation sets at a ratio of 7:3. A novel prognostic prLncRNA signature was constructed from the results of the training set using the least absolute shrinkage and selection operation. The medium value was used as the basis for categorizing all HNSCC patients into a low- or high-risk cohort. Cox regression and Kaplan-Meier (KM) survival analyses were executed to estimate the prognostic value. We also evaluated the functional enrichment, tumor microenvironment, immune cell infiltration, and the sensitivity to chemotherapy and immunotherapy between the high- and low-risk cohorts. Nineteen prognostic prlncRNAs were identified to establish the prognostic signature. Multivariate Cox regression and KM survival analyses confirmed that this prlncRNA signature might serve as an independent prognostic indicator of patient survival, which was subsequently confirmed using a validating dataset. Multiple ROC curves indicated the prlncRNA signature presented a more predictive power than clinicopathological factors (age, sex, tumor grade, and tumor stage). GO, KEGG, and GSEA enrichment analysis disclosed several immune-related pathways which appeared to be enhanced in the low-risk cohort. ESTIMATE, CIBERSORT, and ssGSEA algorithms indicated considerable differences in the tumor microenvironment and immune cell infiltration in the low- and high-risk cohorts. Furthermore, the low-risk cohort was predicted to achieve a better response to immunotherapeutic drugs, while in contrast, the high-risk cohort would be more sensitive to chemotherapy drugs. Our findings robustly demonstrate that our constructed prlncRNA signature could serve as an efficient indicator of prognosis, immunotherapy response, and chemosensitivity for HNSCC patients.

Zhou C ，Shen Y ，Jin Y ，Shen Z ，Ye D ，Shen Y ，Deng H ... -  《Cancer Medicine》

Characterization of macrophages in head and neck squamous cell carcinoma and development of MRG-based risk signature.

Macrophages are immune cells in the TME that can not only inhibit angiogenesis, extracellular matrix remodeling, cancer cell proliferation, and metastasis but also mediate the phagocytosis and killing of cancer cells after activation, making them key targets in anti-tumor immunotherapy. However, there is little research on macrophages and their relation to disease prognosis in HNSCC. Initially, we collected scRNA-seq, bulk RNA-seq, and clinical data. Subsequently, we identified macrophages and distinguished MRGs. Using the K-means algorithm, we performed consensus unsupervised clustering. Next, we used ssGSEA analysis to assess immune cell infiltration in MRG clusters. A risk model was established using multivariate Cox analysis. Then, Kaplan-Meier, ROC curves, univariate and multivariate COX analyses, and C-index was used to validate the predictive power of the signature. The TIDE method was applied to assess the response to immunotherapy in patients diagnosed with HNSCC. In addition, drug susceptibility predictions were made for the GDSC database using the calcPhenotype function. We found that 8 MRGs had prognostic potential. Patients in the MRG group A had a higher probability of survival, and MRG clusters A and B had different characteristics. Cluster A had a higher degree of expression and infiltration in MRG, indicating a closer relationship with MRG. The accuracy of the signature was validated using univariate and multivariate Cox analysis, C-index, and nomogram. Immune landscape analysis found that various immune functions were highly expressed in the low-risk group, indicating an improved response to immunotherapy. Finally, drugs with high sensitivity to HNSCC (such as 5-Fluorouracil, Temozolomide, Carmustine, and EPZ5676) were explored and analyze the malignant characteristics of HNSCC. We constructed a prognostic model using multivariate Cox analysis, consisting of 8 MRGs (TGM2, STC1, SH2D3C, PIK3R3, MAP3K8, ITGA5, ARHGAP4, and AQP1). Patients in the low-risk group may have a higher response to immunotherapy. The more prominent drugs for drug selection are 5-fluorouracil, temozolomide and so on. Malignant features associated with HNSCC include angiogenesis, EMT, and the cell cycle. This study has opened up new prospects for the prognosis, prediction, and clinical treatment strategy of HNSCC.

Liu L ，Liu Q 《Scientific Reports》