High expression of junctional adhesion molecule-A is associated with poor survival in patients with epithelial ovarian cancer

Purpose: Aberrant expression of different tight junction proteins, including the junctional adhesion molecule-A (JAM-A), has been frequently reported in association with tumor progression of several malignancies. To our knowledge, this is the first study examining the clinical significance of JAM-A gene expression in epithelial ovarian cancer. Methods: JAM-A expression levels in 44 epithelial ovarian cancer and 12 benign formalin-fixed paraffin-embedded samples were determined by reverse transcription quantitative polymerase chain reaction. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic and prognostic potential of JAM-A. Associations between JAM-A expression and clinicopathological characteristics of epithelial ovarian cancer were analyzed using Fisher’s exact test. The Kaplan–Meier method and univariate Cox regression analysis were used for the survival analysis. P ⩽ 0.05 was considered statistically significant. Results: ROC curve analyses showed that JAM-A gene expression exhibits both diagnostic and prognostic performance in epithelial ovarian cancer (area under the curve (AUC) 0.640, 95% confidence interval (CI) 0.488, 0.792, sensitivity 43.18%, specificity 100% and AUC 0.621, 95% CI 0.427, 0.816, sensitivity 52.63%, specificity 85%, respectively). JAM-A expression was significantly associated with International Federation of Gynecologists and Obstetricians (FIGO) stage ( P =0.049) and the Kaplan–Meier method demonstrated that patients with high expression of JAM-A had significantly worse overall survival compared to patients with low JAM-A expression ( P =0.004). Moreover, univariate Cox regression analysis showed that FIGO stage, peritoneal metastasis, residual tumor and JAM-A expression were significantly associated with reduced overall survival in epithelial ovarian cancer. Conclusions: Our results indicate that high levels of JAM-A expression are associated with an advanced clinicopathological feature and may have diagnostic potential; also, it could be a predictor of poor overall survival in patients with epithelial ovarian cancer.

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A randomized, phase III study (AGO-OVAR-9, GINECO-TCG, NSGO-OC-0102): Gemcitabine-paclitaxel-carboplatin (TCG) versus paclitaxel-carboplatin (TC) as first-line treatment of ovarian cancer (OC): Survival of FIGO stage I-IIA patients

Journal of Clinical Oncology ◽

10.1200/jco.2009.27.18_suppl.lba5510 ◽

2009 ◽

Vol 27 (18_suppl) ◽

pp. LBA5510-LBA5510 ◽

Cited By ~ 2

Author(s):

J. Herrstedt ◽

J. Huober ◽

F. Priou ◽

H. Müller ◽

M. Baekelandt ◽

...

Keyword(s):

Ovarian Cancer ◽

Overall Survival ◽

Cox Regression ◽

Residual Tumor ◽

Figo Stage ◽

Stage I ◽

Phase Iii ◽

Cox Regression Analysis ◽

Phase Iii Study ◽

First Diagnosis

LBA5510 Background: One option to increase the efficacy of TC in pts with first diagnosis of ovarian cancer is to add a not cross-resistant drug. Methods: We conducted a randomized, prospective, stratified, phase III study comparing therapy with TC to TC plus gemcitabine. From 7/02 to 4/04, pts with a histological verified first diagnosis of epithelial OC, FIGO IC-IV were randomized to either TC (paclitaxel [T] 175 mg/m2 3h iv d1 + carboplatin [C] AUC 5 iv d1) or TCG (TC + gemcitabine [G] 800 mg/m2 iv d1+8) for at least 6 cycles every 21 days starting within 6 weeks post-operatively. The randomization was balanced within three strata: 1) FIGO I-IIA, 2) FIGO IIB-IIIC with residual tumor ≤ 10mm, 3) FIGO IIB-IIIC with residual tumor > 10 mm or FIGO IV. Primary endpoint is overall survival. Results: We enrolled 1,742 pts and administered 5,268 cycles TC and 5,129 cycles TCG. All baseline characteristics of the patients in both arms were well balanced. Most pts received 6+ cycles (87.2% TC, 86.2% TCG). Previous interim analyses has shown that TCG was tolerable but induced more hematological toxicity and final analysis has shown that addition of gemcitabine did not improve overall survival in patients with FIGO stage IIB-IV disease. Approximately 11% of the patients (n = 175) had FIGO stage I-IIA disease (stratum I). Most patients received 6+ cycles (93.3% TC, 86.9% TCG). With a median follow-up of 53.8 (range 0 –75) months, and using the log rank test and Cox regression analysis, no relevant differences in progression free survival (first quartile about 57 months and median ≥ 75 months in both groups, HR = 0.90 [95% CI: 0.47–1.72], p = 0.7500) and a negative trend in overall survival (first quartile ≥ 75 months in both groups, HR = 2.19 [95% CI: 0.75–6.41], p = 0.1419) were seen. Conclusions: Addition of G to TC did not improve efficacy in patients with stage I-IIA ovarian cancer. This was also the case for stratum II-III patients (previously reported). The addition of G to TC in patients with first diagnosis of ovarian cancer cannot be recommended. [Table: see text]

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Impact of cytoreductive surgery on outcomes of metastatic appendiceal carcinoma: a real-world, population-based study

Journal of Comparative Effectiveness Research ◽

10.2217/cer-2019-0179 ◽

2020 ◽

Vol 9 (6) ◽

pp. 431-439

Author(s):

Omar Abdel-Rahman

Keyword(s):

Overall Survival ◽

Regression Analysis ◽

Metastatic Disease ◽

Cytoreductive Surgery ◽

Mucinous Adenocarcinoma ◽

Cox Regression ◽

Cancer Specific Survival ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Appendiceal Carcinoma

Aim: To evaluate the impact of cytoreductive surgery on the outcomes of patients with metastatic appendiceal carcinoma. Methods: Surveillance, Epidemiology and End Results (SEER) database was accessed and patients with metastatic appendiceal carcinoma diagnosed (2010–2015) were reviewed. Kaplan–Meier survival estimates/log-rank testing were then used to assess overall survival outcomes according to cytoreductive surgery. Multivariable Cox regression analysis was then used to evaluate factors affecting cancer-specific survival. Factors included in this model were age, race, sex, stage and histology and cytoreductive surgery. Results: A total of 1339 patients with metastatic appendiceal carcinoma were included in the current study. Using Kaplan–Meier survival estimates to evaluate overall survival, patients with surgery for metastatic disease have better overall survival compared with patients without surgery for metastatic disease (p < 0.001). Stratifying survival analysis according to histology, the overall survival benefit from surgery for the metastases seems to be limited to patients with mucinous adenocarcinoma (p = 0.002) rather than patients with nonmucinous adenocarcinoma (p = 0.401). Multivariable Cox regression analysis was then conducted to evaluate factors predicting cancer-specific survival. The following factors were associated with worse cancer-specific survival: African-American race (hazard ratio [HR]: 1.356; 95% CI: 1.036–1.774; p = 0.026), more advanced stage (HR: 3.910; 95% CI: 2.735–5.588; p < 0.001), nonmucinous adenocarcinoma (HR for signet ring carcinoma vs mucinous adenocarcinoma: 2.119; 95% CI: 1.674–2.683; p < 0.001) and no surgical resection of metastatic disease (HR: 1.273; 95% CI: 1.067–1.519; p < 0.001). Conclusion: The current study suggests that among patients with metastatic appendiceal carcinoma, surgical cytoreduction of metastatic disease is associated with improved outcomes for patients with mucinous adenocarcinoma but not in patients with nonmucinous adenocarcinoma.

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Identification of 4-genes model in papillary renal cell tumor microenvironment based on comprehensive analysis

BMC Cancer ◽

10.1186/s12885-021-08319-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Liang Luo ◽

Haiyi Zhou ◽

Hao Su

Keyword(s):

Gene Expression ◽

Regression Analysis ◽

Tumor Microenvironment ◽

Renal Cell ◽

Cox Regression ◽

Ppi Network ◽

Hub Genes ◽

Cox Regression Analysis ◽

Venn Diagrams ◽

Kaplan Meier

Abstract Background The tumor microenvironment acts a pivotal part in the occurrence and development of tumor. However, there are few studies on the microenvironment of papillary renal cell carcinoma (PRCC). Our study aims to explore prognostic genes related to tumor microenvironment in PRCC. Methods PRCC expression profiles and clinical data were extracted from The Cancer Gene Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Immune/stromal scores were performed utilizing the ESTIMATE algorithm. Three hundred fifty-seven samples were split into two groups on the basis of median immune/stromal score, and comparison of gene expression was conducted. Intersect genes were obtained by Venn diagrams. Hub genes were selected through protein-protein interaction (PPI) network construction, and relevant functional analysis was conducted by DAVID. We used Kaplan–Meier analysis to identify the correlations between genes and overall survival (OS) and progression-free survival (PFS). Univariate and multivariate cox regression analysis were employed to construct survival model. Cibersort was used to predict the immune cell composition of high and low risk group. Combined nomograms were built to predict PRCC prognosis. Immune properties of PRCC were validated by The Cancer Immunome Atlas (TCIA). Results We found immune/stromal score was correlated with T pathological stages and PRCC subtypes. Nine hundred eighty-nine differentially expressed genes (DEGs) and 1169 DEGs were identified respectively on the basis of immune and stromal score. Venn diagrams indicated that 763 co-upregulated genes and 4 co-downregulated genes were identified. Kaplan-Meier analysis revealed that 120 genes were involved in tumor prognosis. Then PPI network analysis identified 22 hub genes, and four of which were significantly related to OS in patients with PRCC confirmed by cox regression analysis. Finally, we constructed a prognostic nomogram which combined with influence factors. Conclusions Four tumor microenvironment-related genes (CD79A, CXCL13, IL6 and CCL19) were identified as biomarkers for PRCC prognosis.

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Tumor microenvironment related novel signature predict lung adenocarcinoma survival

PeerJ ◽

10.7717/peerj.10628 ◽

2021 ◽

Vol 9 ◽

pp. e10628

Author(s):

Juan Chen ◽

Rui Zhou

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Regression Analysis ◽

Tumor Microenvironment ◽

Prognostic Model ◽

Cox Regression ◽

Survival Prediction ◽

Clinical Parameters ◽

Ppi Network ◽

Cox Regression Analysis

Background Lung adenocarcinoma (LUAD) is the most common histological type of lung cancers, which is the primary cause of cancer‐related mortality worldwide. Growing evidence has suggested that tumor microenvironment (TME) plays a pivotal role in tumorigenesis and progression. Hence, we investigate the correlation of TME related genes with LUAD prognosis. Method The information of LUAD gene expression data was obtained from The Cancer Genome Atlas (TCGA). According to their immune/stromal scores calculated by the ESTIMATE algorithm, differentially expressed genes (DEGs) were identified. Then, we performed univariate Cox regression analysis on DEGs to obtain genes that are apparently bound up with LUAD survival (SurGenes). Functional annotation and protein-protein interaction (PPI) was also conducted on SurGenes. By validating the SurGenes with data sets of lung cancer from the Gene Expression Omnibus (GEO), 106 TME related SurGenes were generated. Further, intersection analysis was executed between the 106 TME related SurGenes and hub genes from PPI network, PTPRC and CD19 were obtained. Gene Set Enrichment Analysis and CIBERSORT analysis were performed on PTPRC and CD19. Based on the TCGA LUAD dataset, we conducted factor analysis and Step-wise multivariate Cox regression analysis for 106 TME related SurGenes to construct the prognostic model for LUAD survival prediction. The LUAD dataset in GEO (GSE68465) was used as the testing dataset to confirm the prognostic model. Multivariate Cox regression analysis was used between risk score from the prognostic model and clinical parameters. Result A total of 106 TME related genes were collected in our research totally, which were markedly correlated with the overall survival (OS) of LUAD patient. Bioinformatics analysis suggest them mainly concentrated on immune response, cell adhesion, and extracellular matrix. More importantly, among 106 TME related SurGenes, PTPRC and CD19 were highly interconnected nodes among PPI network and correlated with immune activity, exhibiting significant prognostic potential. The prognostic model was a weighted linear combination of the 106 genes, by which the low-OS LUAD samples could be separated from the high-OS samples with success. This model was also able to rebustly predict the situation of survival (training set: p-value < 0.0001, area under the curve (AUC) = 0.649; testing set: p-value = 0.0009, AUC = 0.617). By combining with clinical parameters, the prognostic model was optimized. The AUC achieved 0.716 for 3 year and 0.699 for 5 year. Conclusion A series of TME-related prognostic genes were acquired in this research, which could reflect immune disorders within TME, and PTPRC and CD19 show the potential to be an indicator for LUAD prognosis and tumor microenvironment modulation. The prognostic model constructed base on those prognostic genes presented a high predictive ability, and may have clinical implications in the overall survival prediction of LUAD.

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Cisplatin-Based versus Carboplatin-Based Chemotherapy for Extra-Pulmonary Neuroendocrine Carcinomas; A Real-World Study.

Neuroendocrinology ◽

10.1159/000520193 ◽

2021 ◽

Author(s):

Omar Abdel-Rahman ◽

Sheryl L. Koski

Keyword(s):

Overall Survival ◽

Regression Analysis ◽

Cox Regression ◽

Survival Outcomes ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Platinum Agent ◽

Extra Pulmonary ◽

The Impact ◽

Neuroendocrine Carcinomas

Objective: To assess the survival differences between cisplatin/etoposide versus carboplatin/etoposide chemotherapy regimens in the management of extra-pulmonary neuroendocrine carcinomas (NECs). Methods: Administrative cancer care databases in the province of Alberta, Canada were reviewed, and patients with extra-pulmonary NECs (including those with small cell and large cell neuroendocrine carcinomas) who were treated with either cisplatin/ etoposide or carboplatin/ etoposide, 2004-2019, were reviewed. Kaplan-Meier survival estimates were used to compare the survival outcomes according to the type of platinum agent, and multivariable Cox regression analysis was used to assess the impact of the type of platinum agent on overall survival outcomes. Results: A total of 263 eligible patients were included in this analysis. These include 176 patients who received cisplatin/ etoposide and 87 patients who received carboplatin/etoposide. Using Kaplan-Meier survival estimates, patients treated with cisplatin have better overall survival compared to patients treated with carboplatin (P=0.005). Multivariable Cox regression analysis suggested that the following factors were associated with worse overall survival: higher Charlson comorbidity index (HR: 1.17; 95% CI: 1.05-1.30), gastrointestinal primary site (HR: 1.55; 95% CI: 1.12-2.14), stage IV disease (HR: 1.75; 95% CI: 1.28-2.38) and use of carboplatin (HR: 1.40; 95% CI: 1.02-1.92). Conclusions: The current study suggested that cisplatin/etoposide might be associated with better overall survival compared to carboplatin/etoposide among patients with extra-pulmonary NECs. It is unclear if this is related to differences in inherent responsiveness to the two platinum agents, or due to differences in comorbidity burden between the two treatment groups.

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Down-regulation of siglec-2 (CD22) predicts worse overall survival from HBV-related early-stage hepatocellular carcinoma: a preliminary analysis from Gene Expression Omnibus

Bioscience Reports ◽

10.1042/bsr20181423 ◽

2018 ◽

Vol 38 (6) ◽

Author(s):

Xiaojing Ren ◽

Yuanyuan Ji ◽

Xuhua Jiang ◽

Xun Qi

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Overall Survival ◽

Regression Analysis ◽

Cox Regression ◽

Early Stage ◽

Down Regulation ◽

Cox Regression Analysis ◽

Tumor Tissues ◽

Chi Square Analysis

Sialic-acid-binding immunoglobulin-like lectin (siglec) regulates cell death, anti-proliferative effects and mediates a variety of cellular activities. Little was known about the relationship between siglecs and hepatocellular carcinoma (HCC) prognosis. Siglec gene expression between tumor and non-tumor tissues were compared and correlated with overall survival (OS) from HCC patients in GSE14520 microarray expression profile. Siglec-1 to siglec-9 were all down-regulated in tumor tissues compared with those in non-tumor tissues in HCC patients (all P < 0.05). Univariate and multivariate Cox regression analysis revealed that siglec-2 overexpression could predict better OS (HR = 0.883, 95%CI = 0.806–0.966, P = 0.007). Patients with higher siglec-2 levels achieved longer OS months than those with lower siglec-2 levels in the Kaplan–Meier event analysis both in training and validation sets (P < 0.05). Alpha-fetoprotein (AFP) levels in siglec-2 low expression group were significantly higher than those in siglec-2 high expression group using Chi-square analysis (P = 0.043). In addition, both logistic regression analysis and ROC curve method showed that siglec-2 down-regulation in tumor tissues was significantly associated with AFP elevation over 300 ng/ml (P < 0.05). In conclusion, up-regulation of siglec-2 in tumor tissues could predict better OS in HCC patients. Mechanisms of siglec-2 in HCC development need further research.

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CAMK2N1/RUNX3 methylation is an independent prognostic biomarker for progression-free and overall survival of platinum-sensitive epithelial ovarian cancer patients

Clinical Epigenetics ◽

10.1186/s13148-021-01006-8 ◽

2021 ◽

Vol 13 (1) ◽

Cited By ~ 1

Author(s):

Karolin Heinze ◽

Matthias Rengsberger ◽

Mieczyslaw Gajda ◽

Lars Jansen ◽

Linea Osmers ◽

...

Keyword(s):

Ovarian Cancer ◽

Overall Survival ◽

Epithelial Ovarian Cancer ◽

Prognostic Value ◽

Cox Regression ◽

Univariate Analysis ◽

Cox Regression Analysis ◽

Gynecological Malignancy ◽

Platinum Sensitive ◽

Marker Combination

Abstract Background To date, no predictive or prognostic molecular biomarkers except BRCA mutations are clinically established for epithelial ovarian cancer (EOC) despite being the deadliest gynecological malignancy. Aim of this biomarker study was the analysis of DNA methylation biomarkers for their prognostic value independent from clinical variables in a heterogeneous cohort of 203 EOC patients from two university medical centers. Results The marker combination CAMK2N1/RUNX3 exhibited a significant prognostic value for progression-free (PFS) and overall survival (OS) of sporadic platinum-sensitive EOC (n = 188) both in univariate Kaplan–Meier (LogRank p < 0.05) and multivariate Cox regression analysis (p < 0.05; hazard ratio HR = 1.587). KRT86 methylation showed a prognostic value only in univariate analysis because of an association with FIGO staging (Fisher’s exact test p < 0.01). Thus, it may represent a marker for EOC staging. Dichotomous prognostic values were observed for KATNAL2 methylation depending on BRCA aberrations. KATNAL2 methylation exhibited a negative prognostic value for PFS in sporadic EOC patients without BRCA1 methylation (HR 1.591, p = 0.012) but positive prognostic value in sporadic EOC with BRCA1 methylation (HR 0.332, p = 0.04) or BRCA-mutated EOC (HR 0.620, n.s.). Conclusion The retrospective analysis of 188 sporadic platinum-sensitive EOC proved an independent prognostic value of the methylation marker combination CAMK2N1/RUNX3 for PFS and OS. If validated prospectively this combination may identify EOC patients with worse prognosis after standard therapy potentially benefiting from intensive follow-up, maintenance therapies or inclusion in therapeutic studies. The dichotomous prognostic value of KATNAL2 should be validated in larger sample sets of EOC.

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A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer

Journal of Oncology ◽

10.1155/2019/3614207 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Yue Zhao ◽

Shao-Min Yang ◽

Yu-Lan Jin ◽

Guang-Wu Xiong ◽

Pin Wang ◽

...

Keyword(s):

Gene Expression ◽

Ovarian Cancer ◽

Overall Survival ◽

Scoring System ◽

Cox Regression ◽

High Grade ◽

Serous Ovarian Cancer ◽

Prognostic Signature ◽

Clinical Value ◽

Cox Regression Analysis

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan–Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment.

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Multiplex Immunoassay of Cytokines for The Short-Term Prognosis Predictive Value of Patients With Acute-on-Chronic Liver Failure

10.21203/rs.3.rs-154337/v1 ◽

2021 ◽

Author(s):

Yongyuan Zheng ◽

Genglin Zhang ◽

Lina Wu ◽

Jing Xiong ◽

Lu Wang ◽

...

Keyword(s):

Overall Survival ◽

Regression Analysis ◽

Hepatitis B ◽

Cox Regression ◽

Curve Analysis ◽

Chronic Liver Failure ◽

Roc Curve Analysis ◽

Cox Regression Analysis ◽

Multiplex Immunoassay ◽

Kaplan Meier

Abstract Background: Since the systemic inflammation has been found to be associated with disease progression and mortality in patients with hepatitis B virus (HBV)-related acute-on-chronic liver failure (HBV-ACLF), the objective of this study was to detect inflammatory factors in ACLF patients by a Luminex-based multiplex immunoassay system for high throughput screening of the cytokine with the most prognostic value.Methods: Luminex-based multiplex immunoassay technology was used to determine the concentrations of 48 cytokines in total at once in serum samples from 40 patients with HBV-ACLF, 30 patients with chronic hepatitis B (CHB) and 25 healthy volunteers as normal controls (NC). Then, the receiver operating characteristic (ROC) curve analysis was applied to evaluate the prognostic prediction accuracy. Besides, Kaplan–Meier curves was used to analyze survival, while the Cox regression analysis to determine the mortality predictors.Results: The level of IL-6, IL-10, IL-15, IL-18, M-CSF, IP-10 and CXCL9 were significantly higher in patients with HBV-ACLF than in either patients with CHB or NC subjects, while the level of EGF, PDGF-AA, PDGF-AB/BB, MDC and sCD40L were significantly lower. The concentrations of IL-6, CXCL9, and IL-15 was higher in non-surviving patients with HBV-ACLF than in surviving patients while MDC was lower. Increased serum IL-6 was positively correlated with disease severity. The ROC curve analysis showed that IL-6 and CXCL-9 accurately predicted 90-day survival in patients with HBV-ACLF, with an accuracy equivalent to those of the Model for End-Stage Liver Disease (MELD), MELD-Na. Kaplan–Meier analysis showed an association between the increase in serum concentration of IL-6 as well as CXCL9 and poor overall survival in patients with HBV-ACLF. Moreover, the multivariate Cox regression analysis showed that only serum IL-6 was an independent predictor of overall survival in patients with HBV-ACLF.Conclusion: Although HBV-related ACLF patients have significantly increased serum levels of multiple cytokines, only serum IL-6 levels could be an independent prognostic biomarker in patients with HBV-ACLF.

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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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