Development and Validation of a Hypoxia-Related Gene Pairs Signature to Predict Overall Survival in Head and Neck Squamous Cell Carcinoma

2020 ◽  
Author(s):  
Zhao Ding ◽  
Hefeng Li ◽  
Deshun Yu
Keyword(s):  
Squamous Cell Carcinoma ◽  
T Cells ◽  
High Risk ◽  
Gene Silencing ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Poor Prognosis ◽  
Risk Group ◽  
Low Risk

Abstract Objective Head and neck squamous cell carcinoma (HNSCC) are a highly aggressive tumor with an extremely poor prognosis. Thus, we aimed to develop and validate a robust prognostic signature that can estimate the prognosis for HNSCC.Methods Data on gene expressions and clinical were downloaded from TCGA and GEO database. To develop the best prognosis signature, a LASSO Cox Regression model was employed. Time-dependent receiver-operating characteristic (ROC) was used to determine the best cut-off value. Patients were divided into high-risk and low-risk hypoxia groups according to cut-off value. Survival differences were evaluated by log-rank test, while multivariate analysis was performed by a Cox proportional hazards model.Results A 17-HRGPs composed of 24 unique genes was constructed, which was significantly related to OS. In the TCGA and GEO datasets, patients in the high hypoxia risk group have a poor prognosis (TCGA: P < 0.001, GEO: P < 0.05). After adjusting for other clinicopathological parameters, the 17-HRGP signature was independent prognostic factors in patients with HNSCC (P < 0.05). Functional analysis revealed that mRNA binding, gene silencing by RNA, RNA binding involved in posttranscriptional gene silencing signaling pathway were enriched in the low-risk groups. For this model, C-index was 0.684, which was higher than that of many established risk models. Macrophages M0, Mast cells activated, NK cells resting, and T cells CD4 memory resting, etc. were significantly higher in the high-risk group, and B cells memory, Plasma cells, T cells follicular helper, T cells gamma delta, and T cells CD8, etc. were significantly higher in the low-risk group.Conclusion In summary, our study constructed a robust HRGPs signature as molecular markers for predicting the outcome of HNSCC 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.

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 Novel Glycolysis-related Gene Signature for Survival Prediction in Patients with Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Haimei Qin ◽  
Junli Wang ◽  
Biyun Liao ◽  
Zhonglin Liu ◽  
Rong Wang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Poor Prognosis ◽  
Risk Group ◽  
Gene Signature ◽  
Neck Squamous Cell Carcinoma ◽  
Related Gene ◽  
Cancer Subtypes

Abstract Background: Head and neck squamous cell carcinoma (HNSCC) is most diagnosed at an advanced stage with poor prognosis. Single gene biomarkers cannot have enough predictive ability in HNSCC. Glycolysis participating in cancers was verified. Thus, this study aimed to identify glycolysis-related gene signature predict the outcome of HNSCC. Methods: The mRNA expression data of HNSCC downloaded The Cancer Genome Atlas (TCGA) project was analyzed by Gene Set Enrichment Analysis (GSEA). We use the Cox proportional regression model to construct a prognostic model. Kaplan–Meier and receiver operating characteristic (ROC) curves were employed to estimate the signature. We also analyzed the relationship of the signature and cancer subtypes. Results: We identified nine glycolysis-related genes including G6PD, EGFR, ALDH2, GPR87, STC2, PDK3, ELF3, STC1 and GNPDA1 as prognosis-related genes signature in HNSCC. HNSCC patients were divided into high and low risk group according to the signature. High risk group showed more poor prognosis and the risk score can precisely predict the prognosis of HNSCC. Additionally, the signature also can be used in cancer subtypes. Conclusion: This study established the 9-mRNA glycolysis signature which may serve as a prospective biomarker for prognosis and novel treatment target in HNSCC.

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 The Immune Heterogeneity Between Pulmonary Adenocarcinoma and Squamous Cell Carcinoma: A Comprehensive Analysis Based on lncRNA Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Yan ◽  
Guoyuan Ma ◽  
Kai Wang ◽  
Weidong Liu ◽  
Weiqing Zhong ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
T Cell ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Group ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores

Adenocarcinoma (AD) and squamous cell carcinoma (SCC) are both classified as major forms of non-small cell lung cancer, but differences in clinical prognoses and molecular mechanisms are remarkable. Recent studies have supported the importance of understanding immune status in that it influences clinical outcomes of cancer, and immunotherapies based on the theory of “immune editing” have had notable clinical success. Our study aimed to identify specific long non-coding (lnc) RNAs that control key immune-related genes and to use them to construct risk models for AD and SCC. Risk scores were used to separate patients into high- and low-risk groups, and we validated the prognostic significance of both risk scores with our own cohorts. A Gene Set Enrichment Analysis suggested that the immune responses of patients in the AD high-risk group and the SCC low-risk group tended to be weakened. Evaluation of immune infiltration revealed that the degree of infiltration of dendritic cells is of particular importance in AD. In addition, prediction of responses to immune checkpoint inhibitor (ICI) treatments, based on the T Cell Immune Dysfunction and Exclusion and immunophenoscore models, indicated that deterioration of the immune microenvironment is due mainly to T cell exclusion in AD patients and T cell dysfunction in SCC patients and that high-risk patients with SCC might benefit from ICI treatment. The prediction of downstream targets via The Cancer Proteome Atlas and RNA-seq analyses of a transfected lung cancer cell line indicated that the lncRNA LINC00996 is a potential therapeutic target in AD.

scholarly journals A Ferroptosis-Related Gene Signature for Predicting the Prognosis and Drug Sensitivity of Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Wei Lu ◽  
Yihua Wu ◽  
Shengyun Huang ◽  
Dongsheng Zhang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Drug Sensitivity ◽  
Risk Group ◽  
Low Risk ◽  
Neck Squamous Cell Carcinoma ◽  
Survival Prediction ◽  
Prognostic Signature

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide and has a high mortality. Ferroptosis, an iron-dependent form of programmed cell death, plays a crucial role in tumor suppression and chemotherapy resistance in cancer. However, the prognostic and clinical values of ferroptosis-related genes (FRGs) in HNSCC remain to be further explored. In the current study, we constructed a ferroptosis-related prognostic model based on the Cancer Genome Atlas database and then explored its prognostic and clinical values in HNSCC via a series of bioinformatics analyses. As a result, we built a four-gene prognostic signature, including FTH1, BNIP3, TRIB3, and SLC2A3. Survival analysis showed that the high-risk group presented significantly poorer overall survival than the low-risk group. Moreover, the ferroptosis-related signature was found to be an independent prognostic predictor with high accuracy in survival prediction for HNSCC. According to immunity analyses, we found that the low-risk group had higher anti-tumor immune infiltration cells and higher expression of immune checkpoint molecules and meanwhile corelated more closely with some anti-tumor immune functions. Meanwhile, all the above results were validated in the independent HSNCC cohort GSE65858. Besides, the signature was found to be remarkably correlated with sensitivity of common chemotherapy drugs for HNSCC patients and the expression levels of signature genes were also significantly associated with drug sensitivity to cancer cells. Overall, we built an effective ferroptosis-related prognostic signature, which could predict the prognosis and help clinicians to perform individualized treatment strategy for HNSCC patients.

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.

Identification of a novel CpG methylation signature to predict prognosis in lung squamous cell carcinoma

2020 ◽  
pp. 1-11
Author(s):  
Nan Lee ◽  
Xuelian Xia ◽  
Hui Meng ◽  
Weiliang Zhu ◽  
Xiankai Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Risk Group ◽  
Lung Squamous Cell Carcinoma ◽  
High Risk Group ◽  
Low Risk ◽  
Risk Patients

BACKGROUND: DNA methylation plays a vital role in modulating genomic function and warrants evaluation as a biomarker for the diagnosis and treatment of lung squamous cell carcinoma (LUSC). OBJECTIVE: In this study, we aimed to identify effective potential biomarkers for predicting prognosis and drug sensitivity in LUSC. METHODS: A univariate Cox proportional hazards regression analysis, a random survival forests-variable hunting (RSFVH) algorithm, and a multivariate Cox regression analysis were adopted to analyze the methylation profile of patients with LUSC included in public databases: The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO). RESULTS: A methylated region consisting of 3 sites (cg06675147, cg07064331, cg20429172) was selected. Patients were divided into a high-risk group and a low-risk group in the training dataset. High-risk patients had shorter overall survival (OS) (hazard ratio [HR]: 2.72, 95% confidence interval [CI]: 1.82–4.07, P< 0.001) compared with low-risk patients. The accuracy of the prognostic signature was validated in the test and validation cohorts (TCGA, n= 94; GSE56044, n= 23). Gene set variation analysis (GSVA) showed that activity in the cell cycle/mitotic, ERBB, and ERK/MAPK pathways was higher in the high-risk compared with the low-risk group, which may lead to differences in OS.Interestingly, we observed that patients in the high-risk group were more sensitive to gemcitabine and docetaxel than the low-risk group, which is consistent with results of the GSVA. CONCLUSION: We report novel methylation sites that could be used as powerful tools for predicting risk factors for poorer survival in patients with LUSC.

scholarly journals An Immune-associated lncRNA Signature Predicts the Survival of Patients With Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Jian Wang ◽  
Qinjiang Bian ◽  
Jialin Liu ◽  
Lijuan Du ◽  
Adili Moming
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Operating Characteristic ◽  
Low Risk ◽  
Neck Squamous Cell Carcinoma ◽  
Differentially Expressed ◽  
Risk Scores

Abstract BackgroundThe malignant progression and treatment resistance of head and neck squamous cell carcinoma are closely related to the tumor immune microenvironment. Long non-coding RNA (lncRNA) plays a regulatory role in this process and may be exploited as new signatures for head and neck squamous cell carcinoma(HNSCC) diagnosis, prognosis, and treatment.MethodsHNSCC transcriptome data was abstracted from the Cancer Genome Atlas (TCGA) data resource, and uncovered immune-linked lncRNA through co-expression analysis. Besides, univariate along with Lasso penalty regression were employed to determine immune-linked lncRNA pairs with different expressions. We then compared area under the curve, calculated the Akaike information criterion (AIC) value of the receiver operating characteristic curve for 5 years, determined cutoff points, and established an optimal predictive model for identifying high- and low-risk HNSCC patients. Then, we evaluated these patients with high- and low-risk HNSCC in terms of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutic efficacy, and immunosuppressed biomarkers.ResultsThis study included 545 samples. By co-expression analysis of known immune-linked genes and lncRNAs, a total of 809 immune-related lncRNAs were collected. 77 differentially expressed immune-related lncRNAs were identified (logFC>2,FDR<0.01). The identified differentially-expressed immune-linked lncRNAs were used to develop differential immune-linked lncRNA pairs. Univariate and modified Lasso regression analysis identified 40 differentially expressed immune linked lncRNAs pairs, 17 of which were incorporated in the Cox proportional hazard model by a stepwise approach. The signature could well predict the survival of patients, and the area under the receiver operating characteristic (ROC) of 17 lncRNA pairs predicted 1, 3, and 5-year survival rates (AUC) were all greater than 0.74. Kaplan-Meier analysis found that patients at low risk had longer survival than those in the high-risk group (p<.001). In addition, T stage, survival status, N stage, and clinical stage, were remarkably linked to the risk. The high- and low risk groups were correlated with tumor invading immune cells like macrophages, CD8+ T-cells, monocytes, along with CD4+ T-cells. ICI-related biomarker correlation analysis showed high risk scores were positively linked to high CDK8 expression (p<0.001) and negatively correlated with BTLA , LAG3 and PDCD1 (p<0.001). High-risk scores were correlated with lower IC50 for chemotherapeutics like Docetaxel (p<0.01), indicating that this model can predict chemotherapeutic efficacy.ConclusionsOur results offer promising prospects for identifying innovative molecular targets of immunotherapy and to improve therapeutic approaches for head and neck squamous cell carcinoma patients.

scholarly journals The Prognostic Value and Immune Landscapes of a m6A/m5C/m1A-Related LncRNAs Signature in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Enhao Wang ◽  
Yang Li ◽  
Ruijie Ming ◽  
Jiahui Wei ◽  
Peiyu Du ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Risk Group ◽  
Prognostic Signature ◽  
Mutational Burden ◽  
Tumor Mutational Burden

Background: N6-methyladenosine (m6A), 5-methylcytosine (m5C) and N1-methyladenosine (m1A) are the main RNA methylation modifications involved in the progression of cancer. However, it is still unclear whether m6A/m5C/m1A-related long non-coding RNAs (lncRNAs) affect the prognosis of head and neck squamous cell carcinoma (HNSCC).Methods: We summarized 52 m6A/m5C/m1A-related genes, downloaded 44 normal samples and 501 HNSCC tumor samples with RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) database, and then searched for m6A/m5C/m1A-related genes co-expressed lncRNAs. We adopt the least absolute shrinkage and selection operator (LASSO) Cox regression to obtain m6A/m5C/m1A-related lncRNAs to construct a prognostic signature of HNSCC.Results: This prognostic signature is based on six m6A/m5C/m1A-related lncRNAs (AL035587.1, AC009121.3, AF131215.5, FMR1-IT1, AC106820.5, PTOV1-AS2). It was found that the high-risk subgroup has worse overall survival (OS) than the low-risk subgroup. Moreover, the results showed that most immune checkpoint genes were significantly different between the two risk groups (p &lt; 0.05). Immunity microenvironment analysis showed that the contents of NK cell resting, macrophages M2, and neutrophils in samples of low-risk group were significantly lower than those of high-risk group (p &lt; 0.05), while the contents of B cells navie, plasma cells, and T cells regulatory (Tregs) were on the contrary (p &lt; 0.05). In addition, patients with high tumor mutational burden (TMB) had the worse overall survival than those with low tumor mutational burden.Conclusion: Our study elucidated how m6A/m5C/m1A-related lncRNAs are related to the prognosis, immune microenvironment, and TMB of HNSCC. In the future, these m6A/m5C/m1A-related lncRNAs may become a new choice for immunotherapy of HNSCC.

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