Identification and validation of a prognostic signature and combination drug therapy for immunotherapy of head and neck squamous cell carcinoma.
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ABSTRACT:
SUBMITTER: Qiang W
PROVIDER: S-EPMC7921014 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Head and neck squamous cell carcinoma (HNSCC) is among the most destructive of tumors, leading to considerable morbidity and mortality. Abnormal immune microenvironment is closely associated with tumor progression. This study aimed to construct a robust immune prognostic model for HNSCC. The RNA-seq transcriptome data and clinical information of HNSCC were downloaded from The Cancer Genome Atlas (TCGA) database. The key pathways and transcriptional factors (TFs) that are correlated with significantly altered immune related genes were identified. A robust immune prognostic model was constructed and further validated using a discovery-validation cohort design. An immune prognostic signature-based nomogram model was also developed. We have identified 400 significantly changed immune related genes in HNSCC. In addition, functional analysis of the altered immune related genes revealed many biological functions and pathways that might affect the tumor immune microenvironment. FOXP3, SNAI2, and STAT1 were identified as the hub TFs for regulating immunological changes in HNSCC. Moreover, an immune related gene-based prognostic signature significantly associated with the overall survival (OS) of HNSCC was constructed in the discovery cohort, and successfully validated in the validation cohort. Finally, a nomogram model based on immune prognostic signature was built and exhibited good performance for predicting the OS of HNSCC. In conclusion, the immune prognostic model is robust for predicting the prognosis of HNSCC and may evolve as a promising tool for risk evaluation and therapeutic selection.
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Project description:Increasing evidence has demonstrated that changes in alternative splicing (AS) events are closely associated with the initiation and progression of cancer. However, the concrete role of AS in tumorigenesis of head and neck squamous cell carcinoma (HNSCC) is poorly known. In this study, we aimed to investigate the AS profile in HNSCC, and build up a robust AS-based prognostic signature for HNSCC. Our results revealed a total of 4068 overall survival (OS) associated AS events in the TCGA HNSCC cohort. The whole TCGA HNSCC cohort was randomly divided into discovery cohort and validation cohort. A prognostic signature including five AS events was developed with the discovery cohort based on the most significant OS-associated AS events. Then it was further successfully validated in the validation cohort. The AS-based risk signature was an independent prognostic indicator in both discovery cohort and validation cohort. This prognostic signature-based nomogram model showed excellent performance for predicting the OS of HNSCC. Splicing network analysis have identified the most correlated splicing factor-AS network in HNSCC. Collectively, we have constructed a robust AS-based prognostic signature which might contribute to improve the clinical outcome of HNSCC.
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Project description:Head and neck squamous cell carcinoma (HNSCC) is one of the greatest public challenges because of delayed diagnosis and poor prognosis. In this study, we established an autophagy-associated long non-coding (Lnc)RNA prognostic signature to assess the prognosis of HNSCC patients. The LncRNA expression profiles and clinical information of 499 HNSCC samples were available in The Cancer Genome Atlas. Autophagic LncRNAs were analyzed using Pearson correlation. A co-expression network showed the interactions between autophagic genes and LncRNAs. An autophagic LncRNAs prognostic signature, consisting of MYOSLID, AL139287.1, AC068580.1, AL022328.2, AC104083.1, AL160006.1, AC116914.2, LINC00958, and AL450992.2, was developed through uni- and multivariate Cox regressions. High- and low-risk groups were classified based on the median risk scores. The high-risk group had significantly worse overall survival according to Kaplan-Meier curve analysis. Multivariate Cox regression demonstrated that risk scores were a significant independent prognostic factor (hazard ratio = 1.739, 95% confidence interval: 1.460-2.072), with an area under the curve of 0.735. Principal component analysis distinguished two categories based on the nine-LncRNA prognostic signature. In conclusion, this novel autophagic LncRNA signature is an independent prognostic factor and may suggest novel therapeutic targets for HNSCC.
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Project description:Head and neck cancer (HNC) is the fifth most common cancer worldwide. In this study, we performed an integrative analysis of the discovery set and established an eight-gene signature for the prediction of prognosis in patients with head and neck squamous cell carcinoma (HNSCC). Univariate Cox analysis was used to identify prognosis-related genes (with P < 0.05) in the GSE41613, GSE65858, and TCGA-HNSC RNA-Seq datasets after data collection. We performed LASSO Cox regression analysis and identified eight genes (CBX3, GNA12, P4HA1, PLAU, PPL, RAB25, EPHX3, and HLF) with non-zero regression coefficients in TCGA-HNSC datasets. Survival analysis revealed that the overall survival (OS) of GSE41613 and GSE65858 datasets and the progression-free survival(DFS)of GSE27020 and GSE42743 datasets in the low-risk group exhibited better survival outcomes compared with the high-risk group. To verify that the eight-mRNA prognostic model was independent of other clinical features, KM survival analysis of the specific subtypes with different clinical characteristics was performed. Univariate and multivariate Cox regression analyses were used to identify three independent prognostic factors to construct a prognostic nomogram. Finally, the GSVA algorithm identified six pathways that were activated in the intersection of the TCGA-HNSC, GSE65858, and GSE41613 datasets, including early estrogen response, cholesterol homeostasis, oxidative phosphorylation, fatty acid metabolism, bile acid metabolism, and Kras signaling. However, the epithelial-mesenchymal transition pathway was inhibited at the intersection of the three datasets. In conclusion, the eight-gene prognostic signature proved to be a useful tool in the prognostic evaluation and facilitate personalized treatment of HNSCC patients.
| S-EPMC8252784 | biostudies-literature
Project description:Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5-10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile data for the patients with HNSCC were obtained from the TCGA database (GEO). A total of 500 samples with full clinical following-up were randomly divided into a training set and a validation set. The training set was used to screen for differentially expressed lncRNAs. Single-factor survival analysis was performed to obtain lncRNAs that associated with prognosis. A robust likelihood-based survival model was constructed to identify the lncRNAs that are essential for the prognosis of HNSCC. A co-expression network between genes and lncRNAs was also constructed to identify lncRNAs co-expressed with genes to serve as the final signature lncRNAs for prognosis. Finally, the prognostic effect of the signature lncRNAs was tested by multi-factor survival analysis and a scoring model for the prognosis of HNSCC was constructed. Moreover, the results of the validation set and the relative expression levels of the signature lncRNAs in the tumour and the adjacent tissue were consistent with the results of the training set. The 5 lncRNAs were distributed among 3 expression modules. Further KEGG pathway enrichment analysis showed that these 3 co-expressed modules participate in different pathways, and many of these pathways are associated with the development and progression of disease. Therefore, we proposed that the 5 validated lncRNAs can be used to predict the prognosis of HNSCC patients and can be applied in postoperative treatment and follow-up.
| S-EPMC6189101 | biostudies-literature
Project description:The immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, very limited robust and reliable immunological biomarkers have been developed that are capable of estimating prognosis in HNSCC patients. In this study, we aimed to identify the effects of novel immune-related gene signatures (IRGs) that can predict HNSCC prognosis. Based on gene expression profiles and clinical data of HNSCC patient cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, a total of 439 highly variable expressed immune-related genes (including 239 upregulated and 200 downregulated genes) were identified by using differential gene expression analysis. Pathway enrichment analysis indicated that these immune-related differentially expressed genes were enriched in inflammatory functions. After process screening in the training TCGA cohort, six immune-related genes (PLAU, STC2, TNFRSF4, PDGFA, DKK1, and CHGB) were significantly associated with overall survival (OS) based on the LASSO Cox regression model. Integrating these genes with clinicopathological features, a multivariable model was built and suggested better performance in determining patients' OS in the testing cohort, and the independent validation cohort. In conclusion, a well-established model encompassing both immune-related gene signatures and clinicopathological factors would serve as a promising tool for the prognostic prediction of HNSCC.
| S-EPMC8249947 | biostudies-literature
Project description:PURPOSE OF REVIEW:Discussion of current strategies targeting the immune system related to solid tumors with emphasis on head and neck squamous cell carcinoma (HNSCC).This review will outline the current challenges with immunotherapy and future goals for treatment using these agents. RECENT FINDINGS:Agents targeting immune checkpoint receptors (IR) such as program death 1 (PD1) have been used in the clinical realm for melanoma and non-small cell lung cancer (NSCLC), and the use of these agents for these malignancies has provided crucial information about how and why patients respond or not to inhibitory checkpoint receptor blockade therapy (ICR). The anti PD1 agent, nivolumab, was recently approved by the FDA as a standard of care regimen for patients with platinum refractory recurrent/metastatic (R/M) HNSCC. Molecular pathways leading to resistance are starting to be identified, and work is underway to understand the most optimal treatment regimen with incorporation of immunotherapy. ICR has renewed interest in the immunology of cancer, but resistance is not uncommon, and thus understanding of these mechanisms will allow the clinician to appropriately select patients that will benefit from this therapy.
| S-EPMC5835060 | biostudies-literature
Project description:BackgroundDeciphering the immune characteristics within tumors and identifying the immune signals related to the prognostic factor are helpful for the treatment and management of tumor patients. However, systematic analysis of immune signatures in head and neck squamous cell carcinoma (HNSCC) remains largely unstudied.MethodsA total of 718 immune-related genes were extracted from RNA sequencing data from 519 HNSCC patients in the TCGA database, and survival analysis with integrated bioinformatics analyses was performed to build the final predictive prognosis model.ResultsThe 178 survival-associated genes (P < 0.05) participated in important immune functions, including immune cell activation and migration. Multivariate regression analysis using 93 genes (P < 0.01), together with survival-associated clinicopathological parameters, identified 35 independent prognostic factors. The most significant 8 independent factors were CD3E, CD40LG, TNFRSF4, CD3G, CD5, ITGA2B, ABCB1, and TNFRSF13b. The final prognostic model achieved outstanding predictive efficiency with the highest AUC of 0.963.ConclusionOur prognostic model based on the immune signature could effectively predict the prognosis of HNSCC patients, providing novel predictive biomarkers and potential therapeutic targets for HNSCC patients.
| S-EPMC7593737 | biostudies-literature
Project description:BackgroundRecurrent and metastatic head and neck squamous cell carcinoma (HNSCC) has a dismal prognosis with limited progression-free survival and overall survival, even when treated with different combinations of chemotherapy, targeted therapies and immunotherapy. We explored in vitro and in vivo the effect of the epidermal growth factor receptor (EGFR) inhibitor, osimertinib, alone and in combination with dihydroartemisinin (DHA) in HNSCC.MethodsThe combination of osimertinib with DHA was tested in the FaDu and CAL27 HNSCC cell lines. Tumor cell proliferation assays were conducted in cultured cells and mouse xenografts. Western blotting analysis of related signal pathways was performed to investigate the molecular mechanisms of the inhibitory effect of DHA and the combination. Other compounds, which inhibit signal transducer and activator of transcription 3 (STAT3), Src-family kinases (SFKs), sphingosine kinase 1 (SPHK1), or the receptor tyrosine kinase (RTK) AXL were also combined with osimertinib in vitro.ResultsOsimertinib exerted synergistic cytotoxicity toward FaDu and CAL27 HNSCC cells when combined with DHA. DHA reversed the osimertinib-induced STAT3 and Src phosphorylation. The double combination inhibited AXL expression. The anticancer potential of osimertinib plus DHA combination was validated in vivo on FaDu and CAL27 xenografts in mice without notable side effects.ConclusionsThe results illustrate that the combinatory therapy of osimertinib and DHA, as a repurposing anticancer drug, could be a novel therapeutic strategy for recurrent and/or metastatic HNSCC patients. The findings strongly indicate that a clinical trial is warranted to confirm the benefit of the combination.
| S-EPMC6944621 | biostudies-literature
Project description:PurposeTo construct a prognostic signature composed of DNA repair genes to effectively predict the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).MethodsAfter downloading the transcriptome and clinical data of HNSCC from the Cancer Genome Atlas (TCGA), 499 patients with HNSCC were equally divided into training and testing sets. In the training set, 13 DNA repair genes were screened using univariate proportional hazard (Cox) regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a risk model, which was validated in the testing set.ResultsIn the training and testing sets, there were significant differences in the clinical outcomes of patients in the high- and low-risk groups showed by Kaplan-Meier survival curves (P < 0.001). Univariate and multivariate Cox regression analyses showed that the risk score had independent prognostic predictive ability (P < 0.001). At the same time, the immune cell infiltration, immune score, immune-related gene expression, and tumor mutation burden (TMB) of patients with HNSCC were also different between the high- and low-risk groups (P < 0.05). Finally, we screened several chemotherapeutics for HNSCC, which showed significant differences in drug sensitivity between the high- and low-risk groups (P < 0.05).ConclusionThis study constructed a 13-DNA-repair-gene signature for the prognosis of HNSCC, which could accurately and independently predict the clinical outcome of the patient. We then revealed the immune landscape, TMB, and sensitivity to chemotherapy drugs in different risk groups, which might be used to guide clinical treatment decisions.
| S-EPMC8362833 | biostudies-literature