Utility of a metabolic-associated nomogram to predict the recurrence-free survival of stage I cervical cancer

Aims: To identify metabolism-associated genes (MAGs) that serve as biomarkers to predict prognosis associated with recurrence-free survival (RFS) for stage I cervical cancer (CC). Patients & methods: By analyzing the Gene Expression Omnibus (GEO) database for 258 cases of stage I CC via univariate Cox analysis, LASSO and multivariate Cox regression analysis, we unveiled 11 MAGs as a signature that was also validated using Kaplan–Meier and receiver operating characteristic analyses. In addition, a metabolism-related nomogram was developed. Results: High accuracy of this signature for prediction was observed (area under the curve at 1, 3 and 5 years was 0.964, 0.929 and 0.852 for the internal dataset and 0.759, 0.719 and 0.757 for the external dataset). The high-risk score group displayed markedly worse RFS than did the low-risk score group. The indicators performed well in our nomogram. Conclusions: We identified a novel signature as a biomarker for predicting prognosis and a nomogram to facilitate the individual management of stage I CC patients.

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The impact of method of distal ureter management during radical nephroureterectomy on tumour recurrence

Canadian Urological Association Journal ◽

10.5489/cuaj.1985 ◽

2014 ◽

Vol 8 (11-12) ◽

pp. 845 ◽

Cited By ~ 17

Author(s):

Anil Kapoor ◽

Shawn Dason ◽

Christopher B. Allard ◽

Bobby Shayegan ◽

Louis Lacombe ◽

...

Keyword(s):

Cox Regression ◽

Tumour Recurrence ◽

Management Approach ◽

Management Technique ◽

Recurrence Free Survival ◽

Radical Nephroureterectomy ◽

Distal Ureter ◽

Free Survival ◽

Cox Regression Analysis

Introduction: Radical nephroureterectomy for upper tract urothelial carcinoma (UTUC) must include some form of distal ureter management to avoid high rates of tumour recurrence. It is uncertain which distal ureter management technique has the best oncologic outcomes. To determine which distal ureter management technique resulted in the lowest tumour recurrence rate, we analyzed a multiinstitutional Canadian radical nephroureterectomy database.Methods: We retrospectively analyzed patients who underwent radical nephroureterectomy with distal ureter management for UTUC between January 1990 and June 2010 at 10 Canadian tertiary hospitals. Distal ureter management approaches were divided into 3 categories: (1) extravesical tenting for ureteric excision without cystotomy (EXTRAVESICAL); (2) open cystotomy with intravesical bladder cuff excision (INTRAVESICAL); and (3) extravesical excision with endoscopic management of ureteric orifice (ENDOSCOPIC). Data available for each patient included demographic details, distal ureter management approach, pathology and operative details, as well as the presence and location of local or distant recurrence. Clinical outcomes included overall recurrence-free survival and intravesical recurrence-free survival. Survival analysis was performed with the Kaplan-Meier method. Multivariable Cox regression analysis was also performed.Results: A total of 820 patients underwent radical nephroureterectomy with a specified distal ureter management approach at 10 Canadian academic institutions. The mean patient age was 69.6 years and the median follow-up was 24.6 months. Of the 820 patients, 406 (49.5%) underwent INTRAVESICAL, 316 (38.5%) underwent EXTRAVESICAL, and 98 (11.9%) underwent ENDOSOPIC distal ureter management. Groups differed significantly in their proportion of females, proportion of laparoscopic cases, presence of carcinoma in situ and pathological tumour stage (p < 0.05). Recurrence-free survival at 5 years was 46.3%, 35.6%, and 30.1% for INTRAVESICAL, EXTRAVESICAL and ENDOSCOPIC, respectively (p < 0.05). Multivariable Cox regression analysis confirmed that INTRAVESICAL resulted in a lower hazard of recurrence compared to EXTRAVESICAL and ENDOSCOPIC. When looking only at intravesical recurrence-free survival (iRFS), a similar trend held up with INTRAVESICAL having the highest iRFS, followed by ENDOSCOPIC and then EXTRAVESICAL management (p < 0.05). At last follow-up, 406 (49.5%) patients were alive and free of disease.Conclusion: Open intravesical excision of the distal ureter (INTRAVESICAL) during radical nephroureterectomy was associated with improved overall and intravesical recurrence-free survival compared with extravesical and endoscopic approaches. These findings suggest that INTRAVESICAL should be considered the gold standard oncologic approach to distal ureter management during radical nephroureterectomy. Limitations of this study include its retrospective design, heterogeneous cohort, and limited follow-up.

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Prognostic model of head and neck squamous cell carcinoma based on 12 ferroptosis-related genes

10.21203/rs.3.rs-349666/v1 ◽

2021 ◽

Author(s):

Sijia Li ◽

Hongyang Zhang ◽

Wei Li

Keyword(s):

Regression Analysis ◽

Risk Score ◽

Cox Regression ◽

Risk Group ◽

High Risk Group ◽

Risk Scores ◽

Cox Regression Analysis ◽

Normal Tissues ◽

Model Based ◽

Cox Analysis

Abstract Background: The purpose of our study is establishing a model based on ferroptosis-related genes predicting the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).Methods: In our study, transcriptome and clinical data of HNSCC patients were from The Cancer Genome Atlas, ferroptosis-related genes and pathways were from Ferroptosis Signatures Database. Differentially expressed genes (DEGs) were screened by comparing tumor and adjacent normal tissues. Functional enrichment analysis of DEGs, protein-protein interaction network and gene mutation examination were applied. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression were used to identified DEGs. The model was constructed by multivariate Cox regression analysis and verified by Kaplan-Meier analysis. The relationship between risk scores and other clinical features was also analyzed. Univariate and multivariate Cox analysis was used to verified the independence of our model. The model was evaluated by receiver operating characteristic analysis and calculation of the area under the curve (AUC). A nomogram model based on risk score, age, gender and TNM stages was constructed.Results: We analyzed data including 500 tumor tissues and 44 adjacent normal tissues and 259 ferroptosis-related genes, then obtained 73 DEGs. Univariate Cox regression analysis screened out 16 genes related to overall survival, and LASSO analysis fingered out 12 of them with prognostic value. A risk score model based on these 12 genes was constructed by multivariate Cox regression analysis. According to the median risk score, patients were divided into high-risk group and low-risk group. The survival rate of high-risk group was significantly lower than that of low-risk group in Kaplan-Meier curve. Risk scores were related to T and grade. Univariate and multivariate Cox analysis showed our model was an independent prognostic factor. The AUC was 0.669. The nomogram showed high accuracy predicting the prognosis of HNSCC patients.Conclusion: Our model based on 12 ferroptosis-related genes performed excellently in predicting the prognosis of HNSCC patients. Ferroptosis-related genes may be promising biomarkers for HNSCC treatment and prognosis.

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Application of an Autophagy-Related Gene Prognostic Risk Model Based on TCGA Database in Cervical Cancer

Frontiers in Genetics ◽

10.3389/fgene.2020.616998 ◽

2021 ◽

Vol 11 ◽

Author(s):

Huadi Shi ◽

Fulan Zhong ◽

Xiaoqiong Yi ◽

Zhenyi Shi ◽

Feiyan Ou ◽

...

Keyword(s):

Cervical Cancer ◽

Risk Score ◽

Risk Model ◽

Cox Regression ◽

Expression Profiles ◽

Survival Prediction ◽

Aberrant Expression ◽

Cox Regression Analysis ◽

Normal Tissues ◽

Model Based

Background: Autophagy plays an important role in the development of cancer. However, the prognostic value of autophagy-related genes (ARGs) in cervical cancer (CC) is unclear. The purpose of this study is to construct a survival model for predicting the prognosis of CC patients based on ARG signature.Methods: ARGs were obtained from the Human Autophagy Database and Molecular Signatures Database. The expression profiles of ARGs and clinical data were downloaded from the TCGA database. Differential expression analysis of CC tissues and normal tissues was performed using R software to screen out ARGs with an aberrant expression. Univariate Cox, Lasso, and multivariate Cox regression analyses were used to construct a prognostic model which was validated by using the test set and the entire set. We also performed an independent prognostic analysis of risk score and some clinicopathological factors of CC. Finally, a clinical practical nomogram was established to predict individual survival probability.Results: Compared with normal tissues, there were 63 ARGs with an aberrant expression in CC tissues. A risk model based on 3 ARGs was finally obtained by Lasso and Cox regression analysis. Patients with high risk had significantly shorter overall survival (OS) than low-risk patients in both train set and validation set. The ROC curve validated its good performance in survival prediction, suggesting that this model has a certain extent sensitivity and specificity. Multivariate Cox analysis showed that the risk score was an independent prognostic factor. Finally, we mapped a nomogram to predict 1-, 3-, and 5-year survival for CC patients. The calibration curves indicated that the model was reliable.Conclusion: A risk prediction model based on CHMP4C, FOXO1, and RRAGB was successfully constructed, which could effectively predict the prognosis of CC patients. This model can provide a reference for CC patients to make precise treatment strategy.

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Prognostic impact of LDH and HCG levels in marker-positive seminomas.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.6_suppl.392 ◽

2020 ◽

Vol 38 (6_suppl) ◽

pp. 392-392 ◽

Cited By ~ 2

Author(s):

Christoph Alexander Seidel ◽

Gedske Daugaard ◽

Tim Nestler ◽

Alexey Tryakin ◽

Christian Daniel Fankhauser ◽

...

Keyword(s):

Regression Analysis ◽

Cox Regression ◽

Serum Levels ◽

Rank Test ◽

Prognostic Impact ◽

Recurrence Free Survival ◽

Free Survival ◽

Cox Regression Analysis ◽

Oncological Outcomes ◽

Log Rank Test

392 Background: The prognostic impact of LDH and HCG serum levels in marker positive metastatic seminoma patients is uncertain. This analysis evaluated the association between LDH and HCG levels with oncological outcomes in this patient population. Methods: Seminoma patients with elevated HCG levels were retrospectively analyzed. After stratification according to tumor marker levels pre- and post-orchiectomy, outcomes of subgroups were compared using log-rank test and cox-regression analysis. Study endpoints were cancer specific- (CSS) and recurrence-free survival (RFS). Results: In total, 429 HCG-positive metastatic seminoma patients (stage II n=291; stage III n=138) diagnosed between 1981 and 2018 were included. LDH + HCG levels ranged from 124 U/l to 8833 U/l (median: 619; IQR: 955) + 2 IU/l to 283,782 IU/l (median: 20; IQR: 63) pre- and from 107 U/l to 8650 U/l (median: 324; IQR: 481) + 0 IU/l to 36700 IU/l post-orchiectomy (median: 30; IQR: 121), respectively. Five-year CSS and RFS rates were 90% and 79%, respectively. Patients with LDH levels pre-orchiectomy <1.5 UNL (n=142) had a 5-year CSS (RFS) rate of 97% (88%), compared to 86% (81%) for ≥1.5 to 3 UNL (n=40), 83% (77%) for >3 to 5 UNL (n=44) and 83% (72%) for >5 UNL (n=44) (CSS p <0.001; RFS p=0.142). Concerning LDH levels post-orchiectomy this stratification was not significant but patients with LDH levels ≥3 UNL (n=77) displayed an impaired prognosis associated with a 5-year CSS (RFS) rate of 85% (79%) compared to 94% (82%) for levels <3 UNL (n=186) (CSS p=0.025; RFS p=0.447). Patients with HCG levels ≥2000 IU/l (n=17) pre- but not post-orchiectomy had a 5-year CSS (RFS) rate of 73% (60%) compared to 94% (79%) for patients with HCG levels <2000 IU/l (n=855) (CSS p=0.09; RFS p=0.04). In cox-regression analysis LDH ≥1.5 UNL (p=0.037; HR 3.32, CI95%1.08-10.26) and HCG levels ≥2000 IU/l (p=0.044; HR 3.69, 95%CI1.04-13.13) pre-orchiectomy were confirmed as prognostic factors for CSS. Conclusions: LDH levels inversely correlate with survival outcomes, suggesting ≥1.5 UNL pre- and ≥3 UNL post-orchiectomy as potential cut-off values for further risk assessment. Patients with extensive HCG elevations may represent an unfavorable subgroup concerning RFS and CSS, but only few patients were affected.

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Clinical impact of abdominal versus mediastinal metastases as a prognostic factor for poor outcomes following esophageal cancer surgery: a retrospective study

BMC Cancer ◽

10.1186/s12885-021-08484-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yutaka Miyawaki ◽

Hiroshi Sato ◽

Shuichiro Oya ◽

Hirofumi Sugita ◽

Yasumitsu Hirano ◽

...

Keyword(s):

Esophageal Cancer ◽

Regression Analysis ◽

Lymph Node ◽

Prognostic Factor ◽

Cox Regression ◽

Recurrence Free Survival ◽

Free Survival ◽

Cox Regression Analysis ◽

Systemic Recurrence ◽

Significant Difference

Abstract Background Surgery is still the mainstay of radical treatment for resectable esophageal cancer (EC). It is apparent that the presence or spread of lymph node metastasis (LNM) is a powerful prognostic factor in patients with EC who are eligible for curative treatment. Although the importance and efficacy of lymph node dissection in radical esophagectomy have been reported, the clinical or prognostic relevance of specific metastatic patterns within the mediastinal cavity and abdomen remains unclear. Methods We retrospectively analyzed the association of postoperative survival with clinical mediastinal LNM (cMLNM) and abdominal LNM (cALNM) in 157 patients who underwent radical EC surgery at our hospital between May 2012 and March 2018. Results A significant difference in cause-specific survival (CSS) was observed between patients with and without cALNM (log-rank p = 0.000). A multivariate Cox regression analysis revealed that cALNM and thoracic surgery (mediastinal lymphadenectomy via conventional open right thoracotomy or video-assisted thoracoscopic surgery) independently predicted CSS (p = 0.0007 and 0.021, respectively). Moreover, a significant difference in systemic recurrence-free survival was observed between those with and without cALNM (log-rank p = 0.000). Multivariate Cox regression analysis revealed that cALNM and sex independently predicted systemic recurrence-free survival (p = 0.000 and 0.015, respectively). Conclusion cALNM was an independent poor prognostic factor for CSS after EC surgery. It may also be an independent prognostic factor for postoperative systemic recurrence, which can shorten the CSS. For patients with cALNM-positive EC who have a high potential risk of systemic metastases, more extensive treatment besides the conventional perioperative systemic chemotherapy may be necessary.

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A Novel Four-Gene Prognostic Signature as a Risk Biomarker in Cervical Cancer

International Journal of Genomics ◽

10.1155/2020/4535820 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Jun Wang ◽

Hua Zheng ◽

Yatian Han ◽

Geng Wang ◽

Yanbin Li

Keyword(s):

Cervical Cancer ◽

Cox Regression ◽

Treatment Options ◽

Treatment Strategies ◽

Gene Signature ◽

Gene Expression Omnibus ◽

Prognostic Signature ◽

Tissue Samples ◽

Kaplan Meier ◽

Cox Analysis

Background. Cervical cancer (CC) is a major malignancy affecting women worldwide, with limited treatment options for patients with advanced disease. The aim of this study was to identify novel prognostic biomarkers for CC. Methods. RNA-Seq data from four Gene Expression Omnibus datasets (GSE5787, GSE6791, GSE26511, and GSE63514) were used to identify differentially expressed genes (DEGs) between CC and normal cervical tissues. Functional and enrichment analyses of the DEGs were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Oncomine database, Cytoscape software, and Kaplan-Meier survival analyses were used for in-depth screening of hub DEGs. The Cox regression was then used to develop a prognostic signature, which was in turn used to create a nomogram. Results. A total of 207 DEGs were identified in the tissue samples, eight of which were prognostically significant in terms of overall survival (OS). Thereafter, a novel four-gene signature consisting of DSG2, MMP1, SPP1, and MCM2 was developed and validated using stepwise Cox analysis. The area under the receiver operating characteristic (ROC) curve (AUC) values were 0.785, 0.609, and 0.686 in the training, verification, and combination groups, respectively. The protein expression levels of the four genes were well validated by the western blotting. Moreover, the nomogram analysis showed that a combination of this four-gene signature plus lymph node metastasis (LNM) status effectively predicted the 1- and 3-year OS probabilities of CC patients with accuracies of 69.01% and 83.93%, respectively. Conclusions. We developed a four-gene signature that can accurately predict the prognosis in terms of OS, of CC patients, and could be a valuable tool for designing treatment strategies.

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Long Intergenic Non Coding RNA and MicroRNA Profiles of Pheochromocytoma and Paraganglioma as Prognostic Biomarkers

Journal of the Endocrine Society ◽

10.1210/jendso/bvab048.2096 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. A1024-A1024

Author(s):

Suman Ghosal

Keyword(s):

Multivariate Analysis ◽

Risk Score ◽

Cox Regression ◽

Expression Profiles ◽

Differential Expression Analysis ◽

Hormone Secretion ◽

Tumor Location ◽

The Cancer Genome Atlas ◽

Free Survival ◽

Cox Regression Analysis

Abstract microRNAs (miRNAs) and long intergenic noncoding RNAs (lincRNAs) have been reported as important markers for many cancers. In search of new markers for the metastatic or aggressive phenotypes in the neuroendocrine tumor pheochromocytomas and paragangliomas (PCPG), we analyzed the non-coding transcriptome from patient gene expression data in The Cancer Genome Atlas. We used differential expression analysis and an elastic-net machine-learning model to identify miRNA and lincRNA transcriptomic signature specific to PCPG molecular subtypes. Similarly, miRNAs and lincRNAs specific to aggressive PCPGs were identified, and univariate and multivariate analysis were performed for identifying factors associated with metastasis-free survival. Upregulation of 13 lincRNAs and 4 miRNAs was found to be associated with aggressive/metastatic PCPGs. RT-PCR validation in tumor samples from PCPG patients confirmed the overexpression of 4 miRNAs and 4 lincRNAs in metastatic compared to non-metastatic PCPGs. Kaplan-Meier analysis identified 3 miRNAs and 5 lincRNAs as prognostic markers for metastasis-free survival of patients in PCPGs. In a multivariate Cox regression analysis combining these miRNA and lincRNA expression signatures with the previously identified clinically relevant parameters like SDHB germline mutation, ATRX somatic mutation, tumor location and hormone secretion phenotypes, we identified the miRNA miR-182 and lincRNA HIF1A-AS2 as independent predictors of poor metastasis-free survival. We formulated a risk-score model using multivariate analysis of lincRNA and miRNA expression profiles, presence of SDHB and ATRX mutations, tumor location, and hormone secretion phenotypes. Stratification of PCPG patients with this risk-score showed significant differences in metastasis-free survival.

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Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma

PeerJ ◽

10.7717/peerj.9943 ◽

2020 ◽

Vol 8 ◽

pp. e9943 ◽

Cited By ~ 1

Author(s):

Baowei Ji ◽

Lihua Chen ◽

Qiang Cai ◽

Qiao Guo ◽

Zhibiao Chen ◽

...

Keyword(s):

Regression Analysis ◽

Molecular Mechanisms ◽

Cox Regression ◽

Characteristic Curve ◽

Area Under The Curve ◽

Gene Expression Omnibus ◽

Related Factor ◽

Lasso Regression ◽

Mirna Signature ◽

Cox Regression Analysis

Background Glioma is the most common form of primary malignant intracranial tumor. Methods In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO). Results Eight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227−35.268], p = 0.028]. Conclusion On the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study.

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Establishment And Validation Of Coagulation Factor-based Nomogram For Predicting The Recurrence-free Survival Of Prostate Cancer

10.21203/rs.3.rs-143707/v1 ◽

2021 ◽

Author(s):

Jialin Meng ◽

Zichen Bian ◽

Chenyu Zhu ◽

Zhi Tao ◽

Xiaoyan Jin ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Patients ◽

Cox Regression ◽

Coagulation Factor ◽

Calibration Plot ◽

Recurrence Free Survival ◽

Free Survival ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Coagulation Pathway

Abstract Background: We aimed to establish and validate a coagulation-feature-based nomogram to predict recurrence-free survival for prostate cancer patients.Methods: The study contained 168 prostate cancer patients who had received radical prostatectomy between 2012 and 2018. The Kaplan-Meier plot and log-rank analysis were used to screen recurrence-free survival-related features. The nomogram was established by combining the significant coagulation features with clinicopathological characteristics by using Cox regression analysis. The accuracy and clinical significance of the nomogram model were assessed by receiver operating characteristic (ROC) curve, Kaplan-Meier plot, and calibration plot. Besides, we explored the correlation between coagulation pathway activity and patients’ prognosis based on public datasets by using gene set variation analysis (GSVA) analysis.Results: The results suggested that patients in the high-risk subgroup showed unfavorable prognoses than those in the low-risk subgroup classified by the nomogram model in both the training (log-rank P < 0.0001) and validation (log-rank P = 0.0004) cohorts. The nomogram model exhibited high discriminative accuracy in the training cohort [1-year area under the curve (AUC) of 0.74, and 3-year AUC of 0.69], which was confirmed in the internal validation cohort (C-index = 0.651). Besides, the calibration plots confirmed good concordance for the prediction of recurrence-free survival at 1 and 3 years. Besides, the subgroup analyses confirmed the usage of this model in different clinicopathological subgroups. Finally, GSVA analyses suggested that patients with higher coagulation pathway scores mostly had unfavorable prognoses than those with lower scores, a result consistent with the findings obtained above.Conclusions: In conclusion, we develop a practical nomogram model for the recurrence-free survival predicting of prostate cancer patients. This model may offer clinicians prognostic assessments and facilitate personalized treatment.

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Identification of an autophagy-related gene signature for survival prediction in patients with cervical cancer

Journal of Ovarian Research ◽

10.1186/s13048-020-00730-8 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Hengyu Chen ◽

Qingchun Deng ◽

Wenwen Wang ◽

Huishan Tao ◽

Ying Gao

Keyword(s):

Cervical Cancer ◽

High Risk ◽

Risk Score ◽

Squamous Cell ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Survival Prediction ◽

Prognostic Signature ◽

Cox Regression Analysis

Abstract Cervical cancer is one of the most common female malignancy that occurs worldwide and is reported to cause over 300,000 deaths in 2018. Autophagy controls the survival and death of cancerous cells by regulating the degradation process of cytoplasm and cellular organelle. In the present study, the differentially expressed autophagy-related genes (ARGs) between healthy and cancerous cervical tissues (squamous cell neoplasms) were obtained using data from GTEx and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology (GO) as well as the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Next, we conducted univariate Cox regression assay and obtained 12 ARGs that were associated with the prognosis of cervical cancer patients. We carried out a multivariate Cox regression analysis and developed six ARG-related prognostic signature for the survival prediction of patients with squamous cell cervical cancer (Risk score = − 0.63*ATG3–0.42*BCL2 + 0.85*CD46–0.38*IFNG+ 0.23*NAMPT+ 0.82*TM9SF1). Following the calculation of risk score using the signature, the patients were divided into high and low-risk groups according to the median value. Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis (P < 0.001). The value for area under the curves corresponding to the receiver operating characteristic (ROC) was 0.740. As observed, the expression of IFNG was negatively associated with lymph node metastasis (P = 0.026), while a high-risk score was significantly associated with increased age (P = 0.008). To further validate the prognostic signature, we carried out a permutation test and confirmed the performance of the risk score. In conclusion, our study developed six ARG-related prognostic signature for patients with squamous cell cervical cancer, which might help in improving the prognostic predictions of such patients.

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