Chemoradiation-induced changes in systemic inflammatory markers and their prognostic significance in oesophageal squamous cell carcinoma

Objective: Chemoradiation (CRT) may induce a change in systemic inflammatory state which could affect clinical outcomes in oesophageal cancer. We aimed to evaluate the changes and prognostic significance of systemic inflammatory markers following definitive CRT in oesophageal squamous cell carcinoma. Methods: A total of 53 patients treated with concurrent CRT were included in this retrospective analysis. We compared neutrophils, lymphocytes, platelets, neutrophil–lymphocyte ratio (NLR) and platelet–lymphocyte ratio (PLR) before and after CRT using Wilcoxon signed-rank test. Overall survival (OS) and progression-free survival (PFS) were calculated. Univariable and multivariable survival analysis were performed using Cox regression analysis. Clinical univariable survival prognostic factors with p < 0.1 were included in a multivariable cox regression analysis for backward stepwise model selection. Results: Both NLR (median ∆+2.8 [IQR −0.11, 8.62], p < 001) and PLR (median ∆+227 [81.3–523.5], p < 0.001) increased significantly after CRT. Higher levels of pre-CRT, post-CRT and change (∆) in NLR and PLR were associated with inferior OS and PFS. Post-CRT NLR (HR 1.04, 95% CI 1.02–1.07, p < 0.001), post-CRT platelets (HR 1.03, 95% CI 1.01–1.05, p = 0.005), cT-stage (HR 3.83, 95% CI 1.39–10.60, p = 0.01) and RT dose (HR 0.41, 95% CI 0.21–0.81, p = 0.01) were independent prognostic factors for OS in multivariable analysis. Change in NLR (HR 1.04, 95% CI 1.01–1.06, p = 0.001), post-CRT platelets (HR 1.03, 95% CI 1.01–1.05, p = 0.002), cT-stage (HR 3.98, 95% CI 1.55–10.25, p = 0.004) and RT dose (HR 0.41, 95% CI 0.21–0.80, p = 0.009) were independent prognostic factors for PFS. Conclusion: Both NLR and PLR increased following definitive CRT. Post-CRT NLR and ∆NLR were associated with adverse survival in oesophageal SCC. Advances in knowledge: We showed that CRT increased PLR and NLR, possibly reflecting a systemic inflammatory state which were associated with poor clinical outcomes in oesophageal SCC.

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Prognostic Significance of PD-L1 and mTOR Expression in Oral Squamous Cell Carcinoma

Journal of Health Science and Medical Research ◽

10.31584/jhsmr.2020745 ◽

2020 ◽

Author(s):

Nattinee Charoen ◽

Kitti Jantharapattana ◽

Paramee Thongsuksai

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

Prognostic Factors ◽

Oral Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Cox Regression ◽

Prognostic Significance ◽

P Value ◽

Cox Regression Analysis

Objective: Programmed cell death ligand 1 (PD-L1) and mammalian target of rapamycin (mTOR) are key players in host immune evasion and oncogenic activation, respectively. Evidence of the prognostic role in oral squamous cell carcinoma (OSCC) is conflicting. This study examined the associations of PD-L1 and mTOR expression with 5-year overall survival in OSCC patients. Material and Methods: The expressions of PD-L1 and mTOR proteins were immunohistochemically evaluated on tissue microarrays of 191 patients with OSCC who were treated by surgery at Songklanagarind Hospital, Thailand from 2008 to 2011. Cox regression analysis was used to determine independent prognostic factors. Results: PD-L1 expression was observed in 14.1% of cases while mTOR expression was present in 74.3% of cases. Females were more likely to have tumors with PD-L1 (p-value=0.007) and mTOR expressions (p-value=0.003) than males. In addition, lower clinical stage and well differentiated tumor are more likely to have mTOR expression (p-value= 0.038 and p-value<0.001, respectively). Cox regression analysis showed that age, tumor stage, nodal stage, combined surgical treatment with radiation or chemoradiation therapy, surgical margin status, PD-L1 expression and mTOR expression are independent prognostic factors. High PD-L1 expression (hazard ratio (HR) 3.14, 95% confidence interval (CI), 1.26–7.79) and high mTOR expression (HR 1.69, 95% CI, 1.00–2.84) are strong predictors of poor outcome. Conclusion: A proportion of OSCC expressed PD-L1 and mTOR proteins. Expression of PD-L1 and mTOR proteins are strong prognostic factors of OSCC.

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The Value of Complete Blood Count For The Prognosis Analysis of Esophageal Squamous Cell Carcinoma

10.21203/rs.3.rs-580465/v1 ◽

2021 ◽

Author(s):

Xiang Lv ◽

Songtao Han ◽

Bin Xu ◽

Yuqin Deng ◽

Feng Yangchun

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Blood Count ◽

Cox Regression ◽

Complete Blood Count ◽

Analysis Model ◽

Cox Regression Analysis

Abstract Objective To investigate the value of complete blood count in predicting the survival rate of patients with esophageal squamous cell carcinoma. Methods A total of 3587 patients with esophageal squamous cell carcinoma who were initially admitted to the Affiliated Cancer Hospital of Xinjiang Medical University from January 2010 to December 2017 were collected by retrospective study. The relevant clinical data were collected by the medical record system, and the patients were followed up by the hospital medical record follow-up system. The follow-up outcome was death. The survival time of all patients was obtained. The survival curve was established using the cut-off value of each index obtained by ROC curve. The Cox proportional hazards regression analysis model and nomogram were established to predict the survival prognosis of esophageal squamous cell carcinoma. The role of each index in the prognosis of patients with esophageal squamous cell carcinoma was studied Results The cut-off values of NLR, NMR, LMR, RDW and PDW in blood routine were 3.52, 10.22, 2.25, 13.85% and 12.05%, respectively. Survival curve analysis showed that patients aged < 60 years and NLR < 3.52 had survival. All indicators were divided into high and low groups according to ROC curve. Univariate Cox regression analysis model showed that RDW (≥ 13.85) and NLR (≥ 3.52) groups were risk factors for the prognosis of ESCC, with HR values of 1.099 (1.015–1.191; p = 0.020) and 1.340 (1.231–1.458; p < 0.001) compared with RDW (< 13.85) and NLR (< 3.52), respectively; multivariate Cox regression analysis model showed that NLR was significantly associated with the prognosis of ESCC, with HR of 1.342 (1.232–1.461; p < 0.001) for NLR (≥ 3.52) NLR (< 3.52). Conclusion NLR results in blood count can be used to predict the survival of patients with esophageal squamous cell carcinoma.

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

BMC Oral Health ◽

10.1186/s12903-021-01587-z ◽

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.

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lncRNA TMEM51-AS1 and RUSC1-AS1 function as ceRNAs for induction of laryngeal squamous cell carcinoma and prediction of prognosis

PeerJ ◽

10.7717/peerj.7456 ◽

2019 ◽

Vol 7 ◽

pp. e7456 ◽

Cited By ~ 3

Author(s):

Lian Hui ◽

Jing Wang ◽

Jialiang Zhang ◽

Jin Long

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

Cell Carcinoma ◽

Squamous Cell ◽

Laryngeal Squamous Cell Carcinoma ◽

Cox Regression ◽

Negative Relationship ◽

Prognostic Biomarkers ◽

Cox Regression Analysis ◽

Cerna Network

Background Long non-coding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) to interact with miRNAs to regulate target genes and promote cancer initiation and progression. The expression of lncRNAs and miRNAs can be epigenetically regulated. The goal of this study was to construct an lncRNA-miRNA-mRNA ceRNA network in laryngeal squamous cell carcinoma (LSCC) and reveal their methylation patterns, which was not investigated previously. Methods Microarray datasets available from the Gene Expression Omnibus database were used to identify differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) between LSCC and controls, which were then overlapped with differentially methylated regions (DMRs). The ceRNA network was established by screening the interaction relationships between miRNAs and lncRNAs/mRNAs by corresponding databases. TCGA database was used to identify prognostic biomarkers. Results Five DELs (downregulated: TMEM51-AS1, SND1-IT1; upregulated: HCP5, RUSC1-AS1, LINC00324) and no DEMs were overlapped with the DMRs, but only a negative relationship occurred in the expression and methylation level of TMEM51-AS1. Five DELs could interact with 11 DEMs to regulate 242 DEGs, which was used to construct the ceRNA network, including TMEM51-AS1-miR-106b-SNX21/ TRAPPC10, LINC00324/RUSC1-AS1-miR-16-SPRY4/MICAL2/ SLC39A14, RUSC1-AS1-miR-10-SCG5 and RUSC1-AS1-miR-7-ZFP1 ceRNAs axes. Univariate Cox regression analysis showed RUSC1-AS1 and SNX21 were associated with overall survival (OS); LINC00324, miR-7 and ZFP1 correlated with recurrence-free survival (RFS); miR-16, miR-10, SCG5, SPRY4, MICAL2 and SLC39A14 were both OS and RFS-related. Furthermore, TRAPPC10 and SLC39A14 were identified as independent OS prognostic factors by multivariate Cox regression analysis. Conclusion DNA methylation-mediated TMEM51-AS1 and non-methylation-mediated RUSC1-AS1 may function as ceRNAs for induction of LSCC. They and their ceRNA axis genes (particularly TMEM51-AS1-miR-106b-TRAPPC10; RUSC1-AS1-miR-16-SLC39A14) may be potentially important prognostic biomarkers for LSCC.

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Induction chemotherapy followed by chemoradiotherapy with or without consolidation chemotherapy versus Chemoradiotherapy followed by consolidation chemotherapy for Esophageal Squamous Cell Carcinoma

10.21203/rs.3.rs-434480/v1 ◽

2021 ◽

Author(s):

Mingyue Xiang ◽

Dali Han ◽

Bo Liu ◽

Guifang Zhang ◽

Heyi Gong

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Induction Chemotherapy ◽

Concurrent Chemoradiotherapy ◽

Cox Regression ◽

Locally Advanced ◽

Consolidation Chemotherapy ◽

Cox Regression Analysis

Abstract Purpose To compare the efficacy and safety of induction chemotherapy followed by concurrent chemoradiotherapy(I-CCRT), induction chemotherapy followed by concurrent chemoradiotherapy and consolidation chemotherapy(I-CCRT-C), and concurrent chemoradiotherapy followed by consolidation chemotherapy(CCRT-C) for locally advanced esophageal squamous cell carcinoma(ESSC). Methods Patients with locally advanced ESCC who underwent definitive chemoradiotherapy with cisplatin plus fluorouracil or docetaxel from February 2012 to December 2018 were retrospectively reviewed. Kaplan-Meier curve was used to estimate survival. Efficacy was assessed using RECIST, version 1.0. Prognosis factors were identified with Cox regression analysis. Results Patients were treated with CCRT-C(n=59), I-CCRT(n=20), and I-CCRT-C(n=48), SCRT(n=119). The median follow-up duration was 73.9 months for the entire cohort. The ORR of the CCRT-C, I-CCRT, and I-CCRT-C, SCRT groups was 89.8%, 70.0%, and 77.1%, respectively ( P = 0.078). The median PFS in the CCRT-C, I-CCRT, and I-CCRT-C groups was 32.5, 16.1, and 27.1 months, respectively ( P = 0.464). The median OS of the CCRT-C, I-CCRT, and I-CCRT-C groups was 45.9, 35.5, and 54.0 months, respectively ( P = 0.788). Cox regression analysis indicated that I-CCRT and I-CCRT had comparable PFS and OS with CCRT-C( P > 0.05). Neutropenia grade ≥ 3 in CCRT-C, I-CCRT, I-CCRT-C, and SCRT groups was 47.5%, 15%, and 33.3% of patients, respectively( P =0.027). Conclusions I-CCRT and I-CCRT-C using cisplatin plus fluorouracil or docetaxel regimen had comparable outcomes with CCRT-C for locally advanced ESCC. I-CCRT and I-CCRT-C seem to have less severe neutropenia than CCRT-C, and potential to be a standard treatment option for locally advanced ESCC.

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Data Mining Identifies Six Proteins that Can Act as Prognostic Markers for Head and Neck Squamous Cell Carcinoma

Cell Transplantation ◽

10.1177/0963689720929308 ◽

2020 ◽

Vol 29 ◽

pp. 096368972092930

Author(s):

Zeng-hong Wu ◽

Yun-Tang ◽

Qing Cheng

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

High Throughput Sequencing ◽

Cox Regression ◽

Neck Squamous Cell Carcinoma ◽

The Cancer Genome Atlas ◽

Cox Regression Analysis

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor of the upper aerodigestive tract affecting the oral cavity, lips, paranasal sinuses, larynx, and nasopharynx. Proteogenomics combines proteomics and genomics and employs mass spectrometry and high-throughput sequencing technologies to identify novel peptides. The aim of this study was to identify potential protein biomarkers for clinical treatment of HNSCC. To achieve this, we utilized two sets of data, one on proteins from The Cancer Proteome Atlas (TCPA) and the other on gene expression from The Cancer Genome Atlas (TCGA) database, to evaluate dysfunctional proteogenomics microenvironment. Univariate Cox regression analysis was performed to examine the relationship between protein signatures and prognosis. A total of 19 proteins were significantly associated with overall survival (OS) of patients, of which E2F transcription factor 1 (E2F1; HR = 4.557, 95% CI = 1.810 to 11.469) and enhancer of zeste homolog 2 (EZH2; HR = 0.430, 95% CI = 0.187 to 0.984) were the most differentially expressed between patients with longer and shorter OS, respectively. Furthermore, multivariate Cox regression analysis on six proteins (ERALPHA, HER3, BRAF, P27, RAPTOR, and E2F1) was performed to build the prognostic model. The receiver operating characteristic curves were used to determine whether the expression pattern of survival-related proteins could provide an early prediction of the occurrence of HNSCC. Herein, we found an AUC of 0.720. Based on an online database, we identified novel protein markers for the prognosis of HNSCC. The findings of the present study may provide new insights into the development of new and reliable tools for precise cancer intervention.

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Identification of a Seven-Gene Signature and Establishment of a Nomogram Predicting Overall Survival in Head and Neck Squamous Cell Carcinoma

10.21203/rs.3.rs-70821/v1 ◽

2020 ◽

Author(s):

Haige Zheng ◽

Xiangkun Wu ◽

Huixian Liu ◽

Yumin Lu ◽

Hengguo Li

Keyword(s):

Overall Survival ◽

Squamous Cell Carcinoma ◽

Regression Analysis ◽

High Risk ◽

Cell Carcinoma ◽

Cox Regression ◽

Risk Groups ◽

Gene Signature ◽

Cox Regression Analysis ◽

Kaplan Meier

Abstract Background: Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous tumor with high incidence and poor prognosis. Therefore, effective predictive models are needed to evaluate patient outcomes and optimize treatment. Methods: Ten gene microarray datasets were obtained from the gene expression omnibus (GEO) database. Level 3 mRNA expression and clinical data were obtained in The Cancer Genome Atlas (TCGA) database. We identified highly robust differentially-expressed genes (DEGs) between HNSCC and normal tissue in nine GEO and TCGA datasets using Robust Rank Aggregation (RRA) method. Univariate Cox regression analysis and lasso Cox regression analysis were performed to identify DEGs related to the Overall-survival (OS) and to construct a prognostic gene signature. External validation was performed using GSE65858. Moreover, gene set enrichment analyses (GSEA) analysis was used to analyze significantly rich pathways in high-risk and low-risk groups, and tumor immunoassays were used to clarify immune correlation of the prognostic gene. Finally, integrate multiple forecast indicators were used to build a nomogram using the TCGA-HNSCC dataset. Kaplan–Meier analysis, receiver operating characteristic (ROC), a calibration plot, Harrell’s concordance index (C-index), and decision curve analysis (DCA) were used to test the predictive capability of the seven genetic signals and the nomogram. Results: A novel seven-gene signature (including SLURP1, SCARA5, CLDN10, MYH11, CXCL13, HLF, and ITGA3) was established to predict overall survival in HNSCC patients. ROC curve performed well in the training and validation data sets. Kaplan–Meier analysis demonstrated that low-risk groups had a longer survival time. The nomogram containing seven genetic markers and clinical prognostic factors was a good predictor of HNSCC survival and showed a certain net clinical benefit through the DCA curve. Further research demonstrated that the infiltration degree of CD8 + T cells, B cells, neutrophils, and NK cells were significantly lower in the high-risk group.Conclusion: Our analysis established a seven-gene model and nomogram to accurately predict the prognosis status of HNSCC patients, immune relevance was also described, which may provide a new possibility for individual treatment and medical decision-making.

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Benefit of chemotherapy based on platinum with definitive radiotherapy in older patients with locally advanced esophageal squamous cell carcinoma

Radiation Oncology ◽

10.1186/s13014-021-01931-1 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Haishan Wu ◽

Yilin Yu ◽

Qunhao Zheng ◽

Tianxiu Liu ◽

Yahua Wu ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Older Patients ◽

Cox Regression ◽

Locally Advanced ◽

Cox Regression Analysis ◽

Significant Difference

Abstract Objective There is still no definitely therapeutic evidence of a beneficial effect of chemotherapy with radiotherapy for older patients with esophageal squamous cell carcinoma (ESCC). We aim to determine the influence of chemoradiotherapy (CRT) and radiotherapy (RT) alone in patients aged 65 years or older with locally advanced ESCC. Methods We retrospectively analyzed 581 ESCC patients who underwent CRT and RT alone. Univariate and multivariate Cox regression analysis was used to analyze the impact of clinical factors on long‐term overall survival (OS) and progression-free survival (PFS). Finally, we compared the toxicity rates of these patients. Results The median OS and PFS of the overall population were 23.2 months (2.0–162.6 months) and 18.6 months (1.1–159.6 months). Multivariate Cox regression analysis showed that chemotherapy (p < 0.05), tumor thickness (p < 0.01), and N stage (p < 0.05) were independent prognostic factors associated with both OS and PFS. In the chemotherapy subgroup, patients who received 2–8 cycles of chemotherapy had better OS than those who received 1 cycle (p = 0.015). The results also revealed that the CRT group has better OS and PFS than RT alone group for patients aged 65–74 years (both p < 0.01). However, for patients aged 75 years or older, there was no statistically significant difference between CRT and RT alone (both p > 0.05). Besides, higher staged ESCC has the inferior OS and PFS than lower staged ESCC for patients received RT alone and aged 65–74 years (both p < 0.05). Finally, there were significantly more severe hematologic toxicities in the CRT group than in those treated with RT alone in this study (p < 0.001). Conclusions The present study suggested that CRT for locally advanced ESCC in patients aged 65 years or older had a significant benefit over RT alone in terms of OS and PFS. However, for patients aged 75 years or older, there was no statistically significant difference between CRT and RT alone. CRT should be performed with special attention in patients aged 75 years or older.

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Immune-Related lncRNA Signature for Predicting the Immune Landscape of Head and Neck Squamous Cell Carcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.689224 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ji Yin ◽

Xiaohui Li ◽

Caifeng Lv ◽

Xian He ◽

Xiaoqin Luo ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

High Risk ◽

Cell Carcinoma ◽

Cox Regression ◽

Risk Group ◽

Risk Groups ◽

High Risk Group ◽

Survival Prediction ◽

Cox Regression Analysis

Background: Long non-coding RNA (lncRNA) plays a significant role in the development, establishment, and progression of head and neck squamous cell carcinoma (HNSCC). This article aims to develop an immune-related lncRNA (irlncRNA) model, regardless of expression levels, for risk assessment and prognosis prediction in HNSCC patients.Methods: We obtained clinical data and corresponding full transcriptome expression of HNSCC patients from TCGA, downloaded GTF files to distinguish lncRNAs from Ensembl, discerned irlncRNAs based on co-expression analysis, distinguished differentially expressed irlncRNAs (DEirlncRNAs), and paired these DEirlncRNAs. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multivariate Cox regression analysis were then performed to screen lncRNA pairs, calculate the risk coefficient, and establish a prognosis model. Finally, the predictive power of this model was validated through the AUC and the ROC curves, and the AIC values of each point on the five-year ROC curve were calculated to select the maximum inflection point, which was applied as a cut-off point to divide patients into low- or high-risk groups. Based on this methodology, we were able to more effectively differentiate between these groups in terms of survival, clinico-pathological characteristics, tumor immune infiltrating status, chemotherapeutics sensitivity, and immunosuppressive molecules.Results: A 13-irlncRNA-pair signature was built, and the ROC analysis demonstrated high sensitivity and specificity of this signature for survival prediction. The Kaplan–Meier analysis indicated that the high-risk group had a significantly shorter survival rate than the low-risk group, and the chi-squared test certified that the signature was highly related to survival status, clinical stage, T stage, and N stage. Additionally, the signature was further proven to be an independent prognostic risk factor via the Cox regression analyses, and immune infiltrating analyses showed that the high-risk group had significant negative relationships with various immune infiltrations. Finally, the chemotherapeutics sensitivity and the expression level of molecular markers were also significantly different between high- and low-risk groups.Conclusion: The signature established by paring irlncRNAs, with regard to specific expression levels, can be utilized for survival prediction and to guide clinical therapy in HNSCC.

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Six Glycolysis-Related Genes as Prognostic Risk Markers Can Predict the Prognosis of Patients with Head and Neck Squamous Cell Carcinoma

BioMed Research International ◽

10.1155/2021/8824195 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

LangXiong Chen ◽

XiaoSong He ◽

ShiJiang Yi ◽

GuanCheng Liu ◽

Yi Liu ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Regression Analysis ◽

Cell Carcinoma ◽

Head And Neck ◽

Squamous Cell ◽

Cox Regression ◽

Neck Squamous Cell Carcinoma ◽

Risk Markers ◽

Cox Regression Analysis ◽

Normal Head

Objective. Head and neck squamous cell carcinoma (HNSCC) is one of the worst-prognosis malignant tumors. This study used bioinformatic analysis of the transcriptome sequencing data of HNSCC and the patients’ survival and clinical data to construct a prediction signature of glycolysis-related genes as the prognostic risk markers. Methods. Gene expression profile data about HNSCC tissues ( n = 498 ) and normal tissues in the head and neck ( n = 44 ) were got from The Cancer Genome Atlas (TCGA), as well as patients’ survival and clinical data. Then, we obtained core genes; their expression in head and neck squamous cell carcinoma tissues is significantly different from that in normal head and neck tissues. The predicted glycolysis-related genes are screened through univariate Cox regression analysis, and then, the prognostic risk markers were constructed through further correction of multivariate Cox regression analysis. The Kaplan-Meier curve and receiver operating characteristic curve are used to analyze the potential value of these risk markers in diagnosis and prognosis. We also evaluated that the glycolysis-related prognostic risk markers composed of 6 oncogenes are correlated with clinical features, such as age, gender, grade, and clinical stage of the tumor, by univariate and multivariate Cox regression analyses. Results. Differentially expressed glycolytic genes in HNSCC tissues and normal head and neck tissues were screened from TCGA databases using the bioinformatic method. We confirmed a set of six glycolytic genes that were significantly associated with OS in the test series. According to our analysis, the prognostic risk markers composed of HPRT1, STC2, PLCB3, GPR87, PYGL, and SLC5A12 may be an independent risk factor for the prognosis of HNSCC. Conclusions. Through this analysis, we constructed new prognostic risk markers related to glycolysis as a prognostic risk marker for patients with HNSCC and provided new ideas and molecular targets for the research and individualized treatment of HNSCC.

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