scholarly journals Prognostic Matrisomal Gene Panel and Its Association with Immune Cell Infiltration in Head and Neck Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5761
Author(s):  
Yuri Belotti ◽  
Su Bin Lim ◽  
Narayanan Gopalakrishna Iyer ◽  
Wan-Teck Lim ◽  
Chwee Teck Lim
Keyword(s):  
Head And Neck ◽  
Immune Cell ◽  
Early Stage ◽  
Risk Groups ◽  
Gene Signature ◽  
Hpv Infection ◽  
Bioinformatics Pipeline ◽  
High Association ◽  
Genomic Tool ◽  
Tcga Dataset

Squamous cell carcinoma of the head and neck (SCCHN) is common worldwide and related to several risk factors including smoking, alcohol consumption, poor dentition and human papillomavirus (HPV) infection. Different etiological factors may influence the tumor microenvironment and play a role in dictating response to therapeutics. Here, we sought to investigate whether an early-stage SCCHN-specific prognostic matrisome-derived gene signature could be identified for HPV-negative SCCHN patients (n = 168), by applying a bioinformatics pipeline to the publicly available SCCHN-TCGA dataset. We identified six matrisome-derived genes with high association with prognostic outcomes in SCCHN. A six-gene risk score, the SCCHN TMI (SCCHN-tumor matrisome index: composed of MASP1, EGFL6, SFRP5, SPP1, MMP8 and P4HA1) was constructed and used to stratify patients into risk groups. Using machine learning-based deconvolution methods, we found that the risk groups were characterized by a differing abundance of infiltrating immune cells. This work highlights the key role of immune infiltration cells in the overall survival of patients affected by HPV-negative SCCHN. The identified SCCHN TMI represents a genomic tool that could potentially aid patient stratification and selection for therapy in these patients.

scholarly journals FOXD1 expression in head and neck squamous carcinoma: a study based on TCGA, GEO and meta-analysis

2021 ◽  
Author(s):  
Junjie Huang ◽  
Bin Liang ◽  
Tianjiao Wang
Keyword(s):  
Head And Neck ◽  
Cell Lines ◽  
Plasma Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Meta Analysis ◽  
Squamous Carcinoma ◽  
Hpv Infection ◽  
Signal Pathways ◽  
Tcga Dataset

Forkhead box D1 (FOXD1) is a new member of FOX transcription factor family. FOXD1 has demonstrated multi-level roles during normal development and several diseases’ pathogenesis. However, litter is known about the role of FOXD1 in the progression of head and neck squamous cancer (HNSC). In the present study, we analyzed FOXD1 expression pattern using TCGA dataset, GEO datasets, HNSC cell lines and HNSC tissues. Then, we analyzed the correlation between FOXD1 expression and clinical characteristics, and evaluated the prognostic value of FOXD1 in HNSC. Moreover, we assessed the relationship between FOXD1 expression and tumor environment (TME) and immune cell infiltration using ESTIMATE and CIBERSORT algorithms. Finally, we predicted the FOXD1-related biological processes and signal pathways. FOXD1 was up-regulated in HNSC tissues in TCGA datasets, validated by GEO datasets, HNSC cell lines and HNSC tissues. FOXD1 expression was significantly associated with tumor site and HPV infection. Univariate and multivariate Cox regression analyses showed that FOXD1 expression was an independent prognostic factor. Moreover, we found that the proportions of naïve B cells, plasma cells, and resting dendritic cells were negatively correlated with FOXD1 expression, otherwise, the proportion of activated mast cells was positively correlated with FOXD1 expression using CIBERSORT algorithm. GSEA analyses revealed that FOXD1 was mainly involved in cancer-related signaling pathway and metabolism-related pathways. FOXD1 was a potential oncogene, and might represent an indicator for predicting overall survival of HNSC patients. Moreover, many cancer-related pathways and metabolism-related processes may be regulated by FOXD1.

scholarly journals Identification of Autophagy- and Ferroptosis-Related lncRNAs Functioned through Immune-Related Pathways in Head and Neck Squamous Carcinoma

Life ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 835
Author(s):  
Qi Guo ◽  
Xuehan Zhang ◽  
Tao Shen ◽  
Xiangting Wang
Keyword(s):  
High Risk ◽  
Head And Neck ◽  
Cell Fate ◽  
Immune Cell ◽  
Squamous Carcinoma ◽  
Risk Groups ◽  
Bioinformatics Analyses ◽  
Functional Roles ◽  
Prognostic Features ◽  
Underlying Mechanisms

The interplay between autophagy and ferroptosis has been highlighted as an important event to decide cancer cell fate. However, the underlying mechanisms remain largely unclear. In this study, we systematically explored the expression, prognostic value and functional roles of lncRNA in autophagy and ferroptosis. By a set of bioinformatics analyses, we identified 363 autophagy- and ferroptosis-related lncRNAs (AF-lncRNAs) and found 17 of them are dramatically related to the prognosis of head and neck squamous cell carcinoma (HNSC) patients, named as prognosis-related AF-lncRNAs (PAF-lncRNAs). Based on six key PAF-lncRNAs, a risk score model was developed and used to categorize the TCGA-retrieved HNSC patients into two groups (high-risk vs. low-risk). Functional analysis showed the differentially expressed genes (DEGs) between the two groups were mainly enriched in immune-related pathways and regulated by a PAF-lncRNA-directed ceRNA (competitive endogenous RNA) network. Combined with a variety of immune infiltration analyses, we also found a decreased landscape of immune cell infiltration in high-risk groups. Together, by revealing PAF-lncRNAs with tumor prognostic features functioned through immune-related pathways, our work would contribute to show the pathogenesis of a lncRNA-directed interplay among autophagy, ferroptosis and tumor immunity in HNSC and to develop potential prognostic biomarkers and targets for tumor immunotherapy.

scholarly journals Identification of Immune-Related Gene Signatures in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Na Li ◽  
Jiahong Wang ◽  
Xianquan Zhan
Keyword(s):  
Prognostic Model ◽  
Immune Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Gene Signature ◽  
Low Risk ◽  
Prognostic Models ◽  
Related Gene ◽  
Immune Related Gene ◽  
Immune Related Genes

Accumulating evidence indicates that immunotherapy helped to improve the survival and quality-of-life of patients with lung adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC) besides chemotherapy and gene targeting treatment. This study aimed to develop immune-related gene signatures in LUAD and LUSC subtypes, respectively. LUAD and LUSC samples were divided into high- and low-abundance groups of immune cell infiltration (Immunity_H and Immunity_L) based on the abundance of immune cell infiltrations. The distribution of immune cells was significantly different between the high- and low-immunity subtypes in LUAD and LUSC samples. The differentially expressed genes (DEGs) between those two groups in LUAD and LUSC contain some key immune-related genes, such as PDL1, PD1, CTLA-4, and HLA families. The DEGs were enriched in multiple immune-related pathways. Furthermore, the seven-immune-related-gene-signature (CD1B, CHRNA6, CLEC12B, CLEC17A, CLNK, INHA, and SLC14A2) prognostic model-based high- and low-risk groups were significantly associated with LUAD overall survival and clinical characteristics. The eight-immune-related-gene-signature (C4BPB, FCAMR, GRAPL, MAP1LC3C, MGC2889, TRIM55, UGT1A1, and VIPR2) prognostic model-based high- and low-risk groups were significantly associated with LUSC overall survival and clinical characteristics. The prognostic models were tested as good ones by receiver operating characteristic, principal component analysis, univariate and multivariate analysis, and nomogram. The verifications of these two immune-related-gene-signature prognostic models showed consistency in the train and test cohorts of LUAD and LUSC. In addition, patients with LUAD in the low-risk group responded better to immunotherapy than those in the high-risk group. This study revealed two reliable immune-related-gene-signature models that were significantly associated with prognosis and tumor microenvironment cell infiltration in LUAD and LUSC, respectively. Evaluation of the integrated characterization of multiple immune-related genes and pathways could help to predict the response to immunotherapy and monitor immunotherapy strategies.

scholarly journals Establishment of a novel glycolysis-related prognostic gene signature for ovarian cancer and its relationships with immune infiltration of the tumor microenvironment

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jianlei Bi ◽  
Fangfang Bi ◽  
Xue Pan ◽  
Qing Yang
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Risk Groups ◽  
Cell Types ◽  
Gene Signature ◽  
Immune Cell Infiltration ◽  
Related Gene ◽  
Immune Related Genes

Abstract Background Glycolysis affects tumor growth, invasion, chemotherapy resistance, and the tumor microenvironment. In this study, we aimed to construct a glycolysis-related prognostic model for ovarian cancer and analyze its relationship with the tumor microenvironment’s immune cell infiltration. Methods We obtained six glycolysis-related gene sets for gene set enrichment analysis (GSEA). Ovarian cancer data from The Cancer Genome Atlas (TCGA) database and two Gene Expression Omnibus (GEO) datasets were divided into two groups after removing batch effects. We compared the tumor environments' immune components in high-risk and low-risk groups and analyzed the correlation between glycolysis- and immune-related genes. Then, we generated and validated a predictive model for the prognosis of ovarian cancer using the glycolysis-related genes. Results Overall, 27/329 glycolytic genes were associated with survival in ovarian cancer, 8 of which showed predictive value. The tumor cell components in the tumor microenvironment did not differ between the high-risk and low-risk groups; however, the immune score differed significantly between groups. In total, 13/24 immune cell types differed between groups, including 10 T cell types and three other immune cell types. Eight glycolysis-related prognostic genes were related to the expression of multiple immune-related genes at varying degrees, suggesting a relationship between glycolysis and immune response. Conclusions We identified eight glycolysis-related prognostic genes that effectively predicted survival in ovarian cancer. To a certain extent, the newly identified gene signature was related to the tumor microenvironment, especially immune cell infiltration and immune-related gene expression. These findings provide potential biomarkers and therapeutic targets for ovarian cancer.

scholarly journals The Pyroptosis-Related Gene Signature Predicts the Prognosis of Hepatocellular Carcinoma

2022 ◽  
Vol 8 ◽  
Author(s):  
Shuqiao Zhang ◽  
Xinyu Li ◽  
Xiang Zhang ◽  
Shijun Zhang ◽  
Chunzhi Tang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
High Risk ◽  
Immune Cell ◽  
Cox Regression ◽  
Expression Profiles ◽  
Risk Groups ◽  
Gene Signature ◽  
Immune Checkpoints ◽  
The Novel

Objective: Hepatocellular carcinoma (HCC) is a genetically and phenotypically heterogeneous tumor, and the prediction of its prognosis remains a challenge. In the past decade, studies elucidating the mechanisms that induce tumor cell pyroptosis has rapidly increased. The elucidation of their mechanisms is essential for the clinical development optimal application of anti-hepatocellular carcinoma therapeutics.Methods: Based on the different expression profiles of pyroptosis-related genes in HCC, we constructed a LASSO Cox regression pyroptosis-related genes signature that could more accurately predict the prognosis of HCC patients.Results: We identified seven pyroptosis-related genes signature (BAK1, CHMP4B, GSDMC, NLRP6, NOD2, PLCG1, SCAF11) in predicting the prognosis of HCC patients. Kaplan Meier survival analysis showed that the pyroptosis-related high-risk gene signature was associated with poor prognosis HCC patients. Moreover, the pyroptosis-related genes signature performed well in the survival analysis and ICGC validation group. The hybrid nomogram and calibration curve further demonstrated their feasibility and accuracy for predicting the prognosis of HCC patients. Meanwhile, the evaluation revealed that our novel signature predicted the prognosis of HCC patients more accurately than traditional clinicopathological features. GSEA analysis further revealed the novel signature associated mechanisms of immunity response in high-risk groups. Moreover, analysis of immune cell subsets with relevant functions revealed significant differences in aDCs, APC co-stimulation, CCR, check-point, iDCs, Macrophages, MHC class-I, Treg, and type II INF response between high- and low-risk groups. Finally, the expression of Immune checkpoints was enhanced in high-risk group, and m6A-related modifications were expressed differently between low- and high-risk groups.Conclusion: The novel pyroptosis-related genes signature can predict the prognosis of patients with HCC and insight into new cell death targeted therapies.

scholarly journals Identification and external validation of a prognostic signature associated with DNA repair genes in gastric cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shimin Chen ◽  
Wenbo Liu ◽  
Yu Huang
Keyword(s):  
Dna Repair ◽  
Immune Cell ◽  
Risk Group ◽  
External Validation ◽  
Risk Groups ◽  
Gene Signature ◽  
Low Risk ◽  
Prognostic Signature ◽  
Cox Analysis ◽  
Repair Genes

AbstractThe aim of this study was to construct and validate a DNA repair-related gene signature for evaluating the overall survival (OS) of patients with gastric cancer (GC). Differentially expressed DNA repair genes between GC and normal gastric tissue samples obtained from the TCGA database were identified. Univariate Cox analysis was used to screen survival-related genes and multivariate Cox analysis was applied to construct a DNA repair-related gene signature. An integrated bioinformatics approach was performed to evaluate its diagnostic and prognostic value. The prognostic model and the expression levels of signature genes were validated using an independent external validation cohort. Two genes (CHAF1A, RMI1) were identified to establish the prognostic signature and patients ware stratified into high- and low-risk groups. Patients in high-risk group presented significant shorter survival time than patients in the low-risk group in both cohorts, which were verified by the ROC curves. Multivariate analysis showed that the prognostic signature was an independent predictor for patients with GC after adjustment for other known clinical parameters. A nomogram incorporating the signature and known clinical factors yielded better performance and net benefits in calibration plot and decision curve analyses. Further, the logistic regression classifier based on the two genes presented an excellent diagnostic power in differentiating early HCC and normal tissues with AUCs higher than 0.9. Moreover, Gene Set Enrichment Analysis revealed that diverse cancer-related pathways significantly clustered in the high-risk and low-risk groups. Immune cell infiltration analysis revealed that CHAF1A and RMI1 were correlated with several types of immune cell subtypes. A prognostic signature using CHAF1A and RMI1 was developed that effectively predicted different OS rates among patients with GC. This risk model provides new clinical evidence for the diagnostic accuracy and survival prediction of GC.

scholarly journals A Metabolic Gene Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yue Zhou
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Gene Signature ◽  
Neck Squamous Cell Carcinoma ◽  
Expression Data ◽  
Geo Dataset ◽  
Tcga Dataset

Background. Head and neck squamous cell carcinoma (HNSCC) is a common malignancy that emanates from the lips, mouth, paranasal sinuses, oropharynx, larynx, nasopharynx, and from other pharyngeal cancers. The availability of high-throughput expression data has made it possible to use global gene expression data to analyze the relationship between metabolic-related gene expression and clinical outcomes in HNSCC patients. Method. In this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy. Results. We extracted data for 529 patients and 327 metabolic genes (198 upregulated and 129 downregulated genes) in the TCGA database. Carbonic anhydrase 9 (CA9) and CA6 had the largest logFCs in the upregulated and downregulated genes, respectively. Our Cox regression model data showed 51 prognostic-related genes with lysocardiolipin acyltransferase 1 (LCLAT1) and choline dehydrogenase (CHDH) being associated with the highest risk ( HR = 1.144 , 95% CI = 1.044 ~ 1.251 ) and the lowest risk ( HR = 0.580 , 95% CI = 0.400 ~ 0.839 ) in HNSCC, respectively. We next used the ROC curve to evaluate whether the differentially expressed metabolic-related genes could serve as early predictors of HNSCC. The findings showed an AUC of 0.745 and 0.618 in the TCGA and GEO analysis, respectively. Besides, the ability for the genes to predict clinicopathological HNSCC status was analyzed and the data showed that the AUC for age, gender, grade, stage, T, M, and N was 0.520, 0.495, 0.568, 0.606, 0.577, 0.476, and 0.673, respectively, in the TCGA dataset. On the other hand, the AUC for age, gender, stage, T, M, N, smoking, and HPV16-pos was 0.599, 0.531, 0.622, 0.606, 0.616, 0.550, 0.614, 0.519, and 0.397, respectively, in the GEO dataset. Conclusion. Taken together, our study unearths a novel metabolic gene signature for the prediction of HNSCC prognosis based on the TCGA dataset. Our signature might point out the metabolic microenvironment disorders and provides potential treatment targets and prognostic biomarkers.

scholarly journals Molecular Characteristics, Clinical Implication, and Cancer Immunity Interactions of Pyroptosis-Related Genes in Breast Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Dandan Xu ◽  
Zhipeng Ji ◽  
Ling Qiang
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Signature ◽  
Immune Checkpoints ◽  
Molecular Characteristics ◽  
Predictive Index ◽  
Cox Regression Analysis ◽  
Cancer Immunity ◽  
Tcga Dataset

Objective: Pyroptosis represents an emerging inflammatory form of programmed cell death. Herein, specific functions and clinical implications of pyroptosis-related genes were systematically characterized in breast cancer.Methods: Expression, somatic mutation and copy number variation of 33 pyroptosis-related genes were assessed in breast cancer from TCGA dataset. Their interactions, biological functions and prognostic values were then observed. By stepwise Cox regression analysis, a pyroptosis-related gene signature was generated. The predictive efficacy in survival was examined by survival analyses, ROCs, univariate and multivariate analyses and subgroup analyses. Associations between risk score (RS) and cancer immunity cycle, HLA, immune cell infiltrations, and immune checkpoints were analyzed.Results: Most of pyroptosis-related genes were abnormally expressed in breast cancer. CASP8, NLRC4, NLRP3, NLRP2, PLCG1, NLRP1, NLRP7, SCAF11, GSDMC, and NOD1 occurred somatic mutations as well as most of them had high frequency of CNV. There were closely interactions between them. These genes were distinctly enriched in immune-related processes. A three-gene signature was generated, containing IL-18, GSDMC, and TIRAP. High RS predicted poorer overall survival, progression, and recurrence. After verification, this RS was an independent and sensitive predictive index. This RS was negatively correlated to cancer immunity cycle. Also, low RS was characterized by high HLA, immune cell infiltrations and immune checkpoints. A nomogram including age and RS was generated for accurately predicting 5-, 8-, and 10-year survival probabilities.Conclusion: Pyroptosis-related genes exert key roles in cancer immunity and might be applied as a prognostic factor of breast cancer.

scholarly journals A 12-chemokine Gene Signature Is Associated With an Enhanced Cancer-immunity Cycle and Is Relevant for Precision Immunotherapy

2021 ◽  
Author(s):  
Xingchen Li ◽  
Zhiyi Wan ◽  
Xiu Liu ◽  
Kai Ou ◽  
Lin Yang
Keyword(s):  
Bladder Cancer ◽  
Immune Cell ◽  
Predictive Biomarkers ◽  
Gene Signature ◽  
Cytolytic Activity ◽  
The Cancer Genome Atlas ◽  
Cancer Immunity ◽  
Lymphoid Structures ◽  
Tcga Dataset ◽  
Predictive And Prognostic Biomarker

Abstract Background: Advances in the understanding of checkpoint blockade immunotherapy have suggested that boosting the cancer-immunity cycle (CIC) can help induce regression of tumors. However, good efficacy only occurs in a subset of patients. Predictive biomarkers that can reflect the tumor microenvironment (TME) and CIC may have great potential. More recently, the presence of intratumoral tertiary lymphoid structures (TLSs) has also been correlated with clinical benefit in patients.Methods: In this study, we comprehensively measured the immunogram scores (IGSs) for the CIC and explored the associations between immunological and mutational features and a 12-chemokine metagene TLS signature in data from The Cancer Genome Atlas (TCGA). Three immunotherapy datasets were further applied for validation.Results: In the TCGA dataset, we observed that the 12-chemokine TLS signature score was positively associated with a boosted CIC, as represented by increased tumor mutational burden (TMB) and neoantigen burden (TNB), enriched immune cell infiltration, and elevated cytolytic activity and checkpoint expression. Specifically, in bladder cancer and melanoma, a high 12-chemokine TLS signature score was found to potentially reflect an expanded CIC phenotype characterized by high TNB and an immune-inflamed feature. The predictive and prognostic value of the 12-chemokine TLS signature was further validated in several immunotherapy datasets.Conclusion: The score of a 12-chemokine metagene signature may serve as a pancancer marker of the immune-active phenotype. The 12-chemokine TLS signature showed promise as a predictive and prognostic biomarker for ICB efficacy, especially in melanoma and bladder cancer.

scholarly journals Current Status of Human Papillomavirus-Related Head and Neck Cancer: From Viral Genome to Patient Care

2021 ◽  
Author(s):  
Haoru Dong ◽  
Xinhua Shu ◽  
Qiang Xu ◽  
Chen Zhu ◽  
Andreas M. Kaufmann ◽  
...  
Keyword(s):  
Human Papillomavirus ◽  
Head And Neck ◽  
Treatment Strategies ◽  
Hpv Infection ◽  
Immune Checkpoint Blockade ◽  
Current Status ◽  
Future Directions ◽  
Sequencing Technologies ◽  
E6 And E7 ◽  
The Continuum

AbstractHuman papillomavirus (HPV) infection identified as a definitive human carcinogen is increasingly being recognized for its role in carcinogenesis of human cancers. Up to 38%–80% of head and neck squamous cell carcinoma (HNSCC) in oropharyngeal location (OPSCC) and nearly all cervical cancers contain the HPV genome which is implicated in causing cancer through its oncoproteins E6 and E7. Given by the biologically distinct HPV-related OPSCC and a more favorable prognosis compared to HPV-negative tumors, clinical trials on de-escalation treatment strategies for these patients have been studied. It is therefore raised the questions for the patient stratification if treatment de-escalation is feasible. Moreover, understanding the crosstalk of HPV-mediated malignancy and immunity with clinical insights from the proportional response rate to immune checkpoint blockade treatments in patients with HNSCC is of importance to substantially improve the treatment efficacy. This review discusses the biology of HPV-related HNSCC as well as successful clinically findings with promising candidates in the pipeline for future directions. With the advent of various sequencing technologies, further biomolecules associated with HPV-related HNSCC progression are currently being identified to be used as potential biomarkers or targets for clinical decisions throughout the continuum of cancer care.

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