scholarly journals Novel Autophagy-Related Gene Signature Investigation for Patients With Oral Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Lihong Huang ◽  
Xinghao Yu ◽  
Zhou Jiang ◽  
Ping Zeng
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Risk Group ◽  
Low Risk ◽  
Related Gene

The correlation between autophagy defects and oral squamous cell carcinoma (OSCC) has been previously studied, but only based on a limited number of autophagy-related genes in cell lines or animal models. The aim of the present study was to analyze differentially expressed autophagy-related genes through The Cancer Genome Atlas (TCGA) database to explore enriched pathways and potential biological function. Based on TCGA database, a signature composed of four autophagy-related genes (CDKN2A, NKX2-3, NRG3, and FADD) was established by using multivariate Cox regression models and two Gene Expression Omnibus datasets were applied for external validation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to study the function of autophagy-related genes and their pathways. The most significant GO and KEGG pathways were enriched in several key pathways that were related to the progression of autophagy and OSCC. Furthermore, a prognostic risk score was constructed based on the four genes; patients were then divided into two groups (i.e., high risk and low risk) in terms of the median of risk score. Prognosis of the two groups and results showed that patients at the low-risk group had a much better prognosis than those at the high-risk group, regardless of whether they were in the training datasets or validation datasets. Multivariate Cox regression results indicated that the risk score of the autophagy-related gene signatures could greatly predict the prognosis of patients after controlling for several clinical covariates. The findings of the present study revealed that autophagy-related gene signatures play an important role in OSCC and are potential prognostic biomarkers and therapeutic targets.

scholarly journals Identification and Validation of a Hypoxia-Immune-Based Prognostic mRNA Signature for Oral Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Shaohua Lv ◽  
Jianhao Li ◽  
Songlin Piao ◽  
jichen Li
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Status ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
Low Risk

Abstract Background: Oral squamous cell carcinoma (OSCC) is a frequently encountered head and neck malignancy. Increasing evidence points towards an aberrant immune response and chronic cell hypoxia in the development of OSCC. However, there is a lack of a reliable hypoxia-immune-based gene signature that may serve to accurately prognosticate OSCC. Methods: The mRNA expression data of OSCC patients was extracted from the TCGA database. Hypoxia status was identified using the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm. Both ESTIMATE and single-sample gene-set enrichment analysis (ssGSEA) was used for further evaluation of immune status. The DEGs in different hypoxia and immune status were determined. A Machine learning method-Least Absolute Shrinkage and Selection operator (LASSO) Cox regression analysis allowed us to select prognostically significant hypoxia- and immune-related mRNAs in order to construct prognostic gene signature to predict the overall survival (OS) of OSCC patients. Results: A total of 773 DEGs were classified into either Hypoxia_High and Hypoxia_Low groups. Immune-associated DEG expressions were used to divide individuals into Immune_High, Immune_ Medium and Immune_Low groups. A total of 193 mRNAs which were significant in both immune function and hypoxia status were identified. With the Lasso Cox regression model, 8 signature mRNAs (FAM122C, RNF157, RANBP17, SOWAHA, KIAA1211, RIPPLY2, INSL3, and DNAH1) associated with OS were selected for further calculation of their respective risk scores. The risk score showed a significant association with age, perineural and lymphovascular invasion. In the GEO validation cohort, a better OS was observed in patients from the low-risk group in comparison to those in the high-risk group. High-risk patients also demonstrated different immune infiltration characteristics from the low-risk group. All individuals from the TCGA OSCC cohort showed similar trends in all 6 immune checkpoints, with those of the low-risk group yielding higher immune indicator scores in contrast to their high-risk counterparts. Conclusion: The hypoxia-immune-based gene signature has prognostic potential in OSCC.

scholarly journals Saliva protein biomarkers to detect oral squamous cell carcinoma in a high-risk population in Taiwan

2016 ◽  
Vol 113 (41) ◽  
pp. 11549-11554 ◽  
Author(s):  
Jau-Song Yu ◽  
Yi-Ting Chen ◽  
Wei-Fan Chiang ◽  
Yung-Chin Hsiao ◽  
Lichieh Julie Chu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Oral Cancer ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Low Risk ◽  
Healthy Controls ◽  
Protein Biomarkers

Most cases of oral squamous cell carcinoma (OSCC) develop from visible oral potentially malignant disorders (OPMDs). The latter exhibit heterogeneous subtypes with different transformation potentials, complicating the early detection of OSCC during routine visual oral cancer screenings. To develop clinically applicable biomarkers, we collected saliva samples from 96 healthy controls, 103 low-risk OPMDs, 130 high-risk OPMDs, and 131 OSCC subjects. These individuals were enrolled in Taiwan’s Oral Cancer Screening Program. We identified 302 protein biomarkers reported in the literature and/or through in-house studies and prioritized 49 proteins for quantification in the saliva samples using multiple reaction monitoring-MS. Twenty-eight proteins were successfully quantified with high confidence. The quantification data from non-OSCC subjects (healthy controls + low-risk OPMDs) and OSCC subjects in the training set were subjected to classification and regression tree analyses, through which we generated a four-protein panel consisting of MMP1, KNG1, ANXA2, and HSPA5. A risk-score scheme was established, and the panel showed high sensitivity (87.5%) and specificity (80.5%) in the test set to distinguish OSCC samples from non-OSCC samples. The risk score >0.4 detected 84% (42/50) of the stage I OSCCs and a significant portion (42%) of the high-risk OPMDs. Moreover, among 88 high-risk OPMD patients with available follow-up results, 18 developed OSCC within 5 y; of them, 77.8% (14/18) had risk scores >0.4. Our four-protein panel may therefore offer a clinically effective tool for detecting OSCC and monitoring high-risk OPMDs through a readily available biofluid.

A Four-gene Autophagy-related Prognostic Signature and Its Association With Immune Landscape in Lung Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Lumeng Luo ◽  
Minghe Lv ◽  
Xuan Li ◽  
Tiankui Qiao ◽  
Kuaile Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Immune Suppression ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk

Abstract Background: Recent advances in immune checkpoint inhibitors (ICIs) have dramatically changed the therapeutic strategy against lung squamous cell carcinoma (LUSC). In the era of immunotherapy, effective biomarkers to better predict outcomes and inform treatment decisions for patients diagnosed with LUSC are urgently needed. We hypothesized that immune contexture of LUSC is potentially dictated by tumor intrinsic events, such as autophagy. Thus, we attempted to construct an autophagy-related risk signature and examine its prediction value for immune phenotype in LUSC.Method: The expression profile of LUSC was obtained from the cancer genome atlas (TCGA) database and the profile of autophagy-related genes (ARGs) was extracted. The survival‑related ARGs (sARGs) was screened out through survival analyses. Random forest was performed to select the sARGs and construct a prognostic risk signature based on these sARGs. The signature was further validated by receiver operating characteristic (ROC) analysis and Cox regression. GEO dataset was used as an independent testing dataset. Patients were divided into high-risk and low-risk group based on the risk score. Then, gene set enrichment analysis (GSEA) was conducted between the two groups. The Single-Sample GSEA (ssGSEA) was introduced to quantify the relative infiltration of immune cells. The correlations between risk score and several main immune checkpoints were examined. And the ESTIMATE algorithm was used to calculate the estimate/immune/stromal scores of the LUSC. Results: Four ARGs (CFLAR, RGS19, PINK1 and CTSD) with the most significant prognostic values were enrolled to construct the risk signature. Patients in high-risk group had better prognosis than the low-risk group (P < 0.0001 in TCGA; P < 0.01 in GEO) and considered as an independent prognosis factor. We also found that high-risk group indicated an immune-suppression status and had higher levels of infiltrating regulatory T cells and macrophages, which are correlated with worse outcome. Besides, risk score showed a significantly positive correlation with the expression of PD-1 and CTLA4, as well as estimate score and immune score.Conclusion: This study established a novel autophagy-related four-gene prognostic risk signature, and the autophagy-related scores are associated with immune landscape of LUSC, with higher score indicating a stronger immune-suppression status.

scholarly journals A glycolysis-based three-gene signature predicts survival in patients with lung squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guichuan Huang ◽  
Jing Zhang ◽  
Ling Gong ◽  
Yi Huang ◽  
Daishun Liu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Cox Regression Analysis

Abstract Background Lung cancer is one of the most lethal and most prevalent malignant tumors worldwide, and lung squamous cell carcinoma (LUSC) is one of the major histological subtypes. Although numerous biomarkers have been found to be associated with prognosis in LUSC, the prediction effect of a single gene biomarker is insufficient, especially for glycolysis-related genes. Therefore, we aimed to develop a novel glycolysis-related gene signature to predict survival in patients with LUSC. Methods The mRNA expression files and LUSC clinical information were obtained from The Cancer Genome Atlas (TCGA) dataset. Results Based on Gene Set Enrichment Analysis (GSEA), we found 5 glycolysis-related gene sets that were significantly enriched in LUSC tissues. Univariate and multivariate Cox proportional regression models were performed to choose prognostic-related gene signatures. Based on a Cox proportional regression model, a risk score for a three-gene signature (HKDC1, ALDH7A1, and MDH1) was established to divide patients into high-risk and low-risk subgroups. Multivariate Cox regression analysis indicated that the risk score for this three-gene signature can be used as an independent prognostic indicator in LUSC. Additionally, based on the cBioPortal database, the rate of genomic alterations in the HKDC1, ALDH7A1, and MDH1 genes were 1.9, 1.1, and 5% in LUSC patients, respectively. Conclusion A glycolysis-based three-gene signature could serve as a novel biomarker in predicting the prognosis of patients with LUSC and it also provides additional gene targets that can be used to cure LUSC patients.

scholarly journals A TP53 mutation model for the prediction of prognosis and therapeutic responses in head and neck squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Congyu Shi ◽  
Shan Liu ◽  
Xudong Tian ◽  
Xiaoyi Wang ◽  
Pan Gao
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Risk Score ◽  
Squamous Cell ◽  
Risk Group ◽  
High Risk Group ◽  
Mutation Model ◽  
Therapeutic Responses

Abstract Background Tumor protein p53 (TP53) is the most frequently mutated gene in head and neck squamous cell carcinoma (HNSC), and TP53 mutations are associated with inhibited immune signatures and poor prognosis. We established a TP53 mutation associated risk score model to evaluate the prognosis and therapeutic responses of patients with HNSC. Methods Differentially expressed genes between patients with and without TP53 mutations were determined by using data from the HNSC cohort in The Cancer Genome Atlas database. Patients with HNSC were divided into high- and low-risk groups based on a prognostic risk score that was generated from ten TP53 mutation associated genes via the multivariate Cox regression model. Results TP53 was the most common mutant gene in HNSC, and TP53 mutations were associated with immunogenic signatures, including the infiltration of immune cells and expression of immune-associated genes. Patients in the high-risk group had significantly poorer overall survival than those in the low-risk group. The high-risk group showed less response to anti-programmed cell death protein 1 (PD-1) therapy but high sensitivity to some chemotherapies. Conclusion The risk score based on our TP53 mutation model was associated with poorer survival and could act as a specific predictor for assessing prognosis and therapeutic response in patients with HNSC.

scholarly journals Development and Validation of a Ferroptosis-Related Gene Signature and Nomogram for Predicting the Prognosis of Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiecheng Ye ◽  
Yining Wu ◽  
Heyuan Cai ◽  
Li Sun ◽  
Wanying Deng ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
Clinical Variable ◽  
Cox Regression Analysis

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with high mortality and poor prognosis. Ferroptosis is a newly discovered form of cell death induced by iron-catalyzed excessive peroxidation of polyunsaturated fatty acids (PUFAs). However, the prognostic value of ferroptosis-related genes (FRGs) for ESCC remains unclear. Based on the ESCC dataset from the Gene Expression Omnibus (GEO) database, we identified 39 prognostic FRGs through univariate Cox regression analysis. After LASSO regression and multivariate Cox regression analyses, a multigene signature based on 10 prognostic FRGs was constructed and successfully divided ESCC patients into two risk groups. Patients in the low-risk group showed a significantly better prognosis than patients in the high-risk group. In addition, we combined the risk score with clinical predictors to construct a nomogram for ESCC. The predictive ability of the nomogram was further verified by ROC curves and calibration plots in both the training and validation sets. The predictive power of the nomogram was demonstrated to be better than that of either the risk score or clinical variable alone. Furthermore, functional analysis revealed that the 10-FRG signature was mainly associated with ferroptosis, differentiation and immune response. Connectivity map analysis identified potential compounds capable of targeting FRGs in ESCC. Finally, we demonstrated the prognostic value of SRC gene in ESCC using the clinical samples and found that SRC inhibition sensitized ESCC cells to ferroptosis inducers by in vitro experiments. In conclusion, we identified and verified a 10-FRG prognostic signature and a nomogram, which provide individualized prognosis prediction and provide insight into potential therapeutic targets for ESCC.

scholarly journals Comprehensive analysis of the significance of ferroptosis-related genes in the prognosis and immunotherapy of oral squamous cell carcinoma

2020 ◽  
Author(s):  
Junhao Yin ◽  
Xiaoli Zeng ◽  
Zexin Ai ◽  
Miao Yu ◽  
Yang'ou Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Oral Squamous Cell Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Low Risk ◽  
Regression Analyses

Abstract Background: Oral squamous cell carcinoma (OSCC) is a life-threatening disease that emerged as a major international health concern, associated with poor prognosis and the absence of specific biomarkers. Studies have shown that the ferroptosis-related genes (FRGs) can be used as tumor prognostic markers. However, FRGs’ prognostic value in OSCC needs further exploration. Our aim was to construct a novel FRG signature for overall survival (OS) prediction in OSCC patients and explore its role in immunotherapy.Methods: In our study, gene expression profile and clinical data of OSCC patients were collected from a public domain. FRGs were available from the FerrDb database. We performed univariate and multivariate Cox regression analyses to construct a multigene signature. The Kaplan-Meier (K-M) and receiver operating characteristic (ROC) methods were utilized to test the effectiveness of the FRG signature. A differential gene expression analysis was performed by the limma R package, followed by functional enrichment analyses. CIBERSORT was applied to analyze the tumor microenvironment (TME). Finally, the expression of human leukocyte antigen (HLA) and immune checkpoint molecules were analyzed to confirm the sensitivity of immunotherapy.Results: A total of 103 FRGs, expressed in OSCC (FRGs-OSCC), were identified from the two datasets by the Venn analysis. The Cox regression analysis identified 5 FRGs-OSCC that were associated with overall survival (all P < 0.01). The FRGs-OSCC risk model was established to classify patients into high risk and low risk groups. Compared with the low risk group, the survival time of the high-risk group was significantly reduced (P < 0.001). According to the multivariate Cox regression analyses, the risk score acted as an independent predictor for OS (HR > 1, P < 0.001). The accuracy of the FRGs-OSCC risk predictive model was confirmed by ROC curve analysis. The results of the Kyoto Encyclopedia of Genes and Genomes (KEGG) showed significant enrichment of immune-related pathways, and a difference in tumor microenvironment between the two groups. The low risk group had the characteristics of higher expression of HLA and immune checkpoints (IDO1, LAG3, PDCD1 and TIGHT), a lower tumor purity and a higher infiltration of immune cells, indicating a more sensitive response to immunotherapy.Conclusions: The novel FRGs-OSCC risk score system can be used to predict OSCC prognosis. Ferroptosis targeting may be a therapeutic option for OSCC.

scholarly journals A Novel Prognostic Model for Oral Squamous Cell Carcinoma: The Functions and Prognostic Values of RNA-Binding Proteins

2021 ◽  
Vol 11 ◽  
Author(s):  
Yingjuan Lu ◽  
Yongcong Yan ◽  
Bowen Li ◽  
Mo Liu ◽  
Yancan Liang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Binding Proteins ◽  
Rna Binding ◽  
Cox Regression ◽  
Rna Binding Proteins

PurposeThe biological roles and clinical significance of RNA-binding proteins (RBPs) in oral squamous cell carcinoma (OSCC) are not fully understood. We investigated the prognostic value of RBPs in OSCC using several bioinformatic strategies.Materials and MethodsOSCC data were obtained from a public online database, the Limma R package was used to identify differentially expressed RBPs, and functional enrichment analysis was performed to elucidate the biological functions of the above RBPs in OSCC. We performed protein-protein interaction (PPI) network and Cox regression analyses to extract prognosis-related hub RBPs. Next, we established and validated a prognostic model based on the hub RBPs using Cox regression and risk score analyses.ResultsWe found that the differentially expressed RBPs were closely related to the defense response to viruses and multiple RNA processes. We identified 10 prognosis-related hub RBPs (ZC3H12D, OAS2, INTS10, ACO1, PCBP4, RNASE3, PTGES3L-AARSD1, RNASE13, DDX4, and PCF11) and effectively predicted the overall survival of OSCC patients. The area under the receiver operating characteristic (ROC) curve (AUC) of the risk score model was 0.781, suggesting that our model exhibited excellent prognostic performance. Finally, we built a nomogram integrating the 10 RBPs. The internal validation cohort results showed a reliable predictive capability of the nomogram for OSCC.ConclusionWe established a novel 10-RBP-based model for OSCC that could enable precise individual treatment and follow-up management strategies in the future.

scholarly journals A four-hypoxia-genes-based prognostic signature for oral squamous cell carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chenguang Zhao ◽  
Yingrui Zhou ◽  
Hongwei Ma ◽  
Jinhui Wang ◽  
Haoliang Guo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Relative Proportion ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis

Abstract Background Oral squamous cell carcinoma (OSCC) is one of the most common maligancies of the head and neck. The prognosis was is significantly different among OSCC patients. This study aims to identify new biomarkers to establish a prognostic model to predict the survival of OSCC patients. Methods The mRNA expression and corresponding clinical information of OSCC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus. Additionally, a total of 26 hypoxia-related genes were also obtained from a previous study. Univariate Cox regression analysis and LASSO Cox regression analysis were performed to screen the optimal hypoxia-related genes which were associated with the prognosis of OSCC. to establish the predictive model (Risk Score) was established for estimating the patient's overall survival (OS). Multivariate Cox regression analysis was used to determine whether the Risk Score was an independent prognostic factor. Based on all the independent prognostic factors, nomogram was established to predict the OS probability of OSCC patients. The relative proportion of 22 immune cell types in each patient was evaluated by CIBERSORT software. Results We determined that a total of four hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA were significantly associated with the prognosis of OSCC patients. The nomogram established based on all the independent factors could reliably predict the long-term OS of OSCC patients. In addition, our resluts indicated that the inferior prognosis of OSCC patients with high Risk Score might be related to the immunosuppressive microenvironments. Conclusion This study shows that high expression of hypoxia-related genes including ALDOA, P4HA1, PGK1 and VEGFA is associated with poor prognosis in OSCC patients, and they can be used as potential markers for predicting prognosis in OSCC patients.

scholarly journals Evaluation of Histopathological Risk Model in a Cohort of Oral Squamous Cell Carcinoma Patients Treated with Accompanying Neck Dissection

2021 ◽  
Author(s):  
N. Rahman ◽  
B. Conn
Keyword(s):  
Squamous Cell Carcinoma ◽  
Oral Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Neck Dissection ◽  
Risk Score ◽  
Squamous Cell ◽  
Risk Model ◽  
Nodal Metastasis ◽  
Low Risk ◽  
Term Survival

AbstractTo investigate the applicability of the validated histological risk model in a cohort of oral cavity squamous cell carcinoma patients treated concurrently with neck dissections. Primary tumours from 85 patients with primary excision of T1 and T2 Oral Squamous Cell Carcinomas (TNM 7th edition) including neck dissection were scored by three pathologists in consensus according to the validated risk model. The risk score data, along with traditional dataset values, were analysed to determine possible association with nodal metastasis and extracapsular spread. Seventy-two patients (54%) were classified with low or intermediate risk and 62 (46%) patients were ‘high risk’. A chi squared test showed that cases with nodal metastasis were highly statistically significant with the overall risk model score (X2 = 22.62 p = 0.0001). None of the neck dissections from tumours with low risk score showed evidence of metastasis (NPV = 100%) suggesting the risk score may also be a useful tool for predicting an absence of metastasis. Risk assessment of low-stage oral squamous cell carcinoma primary tumours may be predictive of the presence or absence of metastasis at presentation. Knowledge of the risk score and its constituent parts may inform treatment decisions at multidisciplinary meetings. Low risk squamous cell carcinoma may be a rare variant with low metastatic potential and excellent long-term survival.

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