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

A cellular senescence-related genes model allows for prognosis and treatment stratification of cervical cancer: a bioinformatics analysis and external verification

BACKGROUND

Cervical cancer (CC) is highly lethal and aggressive with an increasing trend of mortality for females. Molecular characterization-based methods hold great promise for improving the diagnostic accuracy and for predicting treatment response.

METHODS

The mRNAs expression data of CC patients and cellular senescence-related genes were obtained from the Cancer Genome Atlas (TCGA) and CellAge databases, respectively. Differentially expressed genes (DEGs) of senescence related genes between tumor and normal tissues were used for Least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model. Univariate and LASSO regression analyses were applied to establish a predictive nomogram. The performance of the nomogram were evaluated by Kaplan-Meier curve, receiver operating characteristic (ROC), Harrell's concordance index (C-index), and calibration curve. GSE44001 and GSE52903 were used for external validation.

RESULTS

We established a cellular senescence-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of CC patients in the TCGA database. The Kaplan-Meier curve indicated that patients in the low-risk group had considerably better overall survival (OS, P =2.021e-05). The area under the ROC curve (AUC) of this model was 0.743 for OS. Multivariate analysis found that the 6-gene risk signature (HR=3.166, 95%CI: 1.660-6.041, P<0.001) was an independent risk factor for CC patients. We then designed an OS-associated nomogram that included the risk signature and clinicopathological factors. The AUC reached 0.860 for predicting 5-year OS. The nomogram showed excellent consistency between the predictions and actual survival observations. Two external GEO validations were corresponding to the gene expression pattern in TCGA.

CONCLUSIONS

Our results suggested a six-senescence related signature and established a prognostic nomogram that reliably predicted the overall survival for CC. These findings may be beneficial to personalized treatment and medical decision-making.

Eight Aging-Related Genes Prognostic Signature for Cervical Cancer

This study searched for aging-related genes (ARGs) to predict the prognosis of patients with cervical cancer (CC). All data were obtained from Molecular Signatures Database, Cancer Genome Atlas, Gene Expression Integration, and Genotype Organization Expression. The R software was used to screen out the differentially expressed ARGs (DE-ARGs) between CC and normal tissues. A protein-protein interaction network was established by the DE-ARGs. The univariate and multivariate Cox regression analyses were conducted on the first extracted Molecular Complex Detection component, and a prognostic model was constructed. The prognostic model was further validated in the testing set and GSE44001 dataset. Prognosis was analyzed by Kaplan-Meier curves, and accuracy of the prognostic model was assessed by receiver operating characteristic area under the curve analysis. An independent prognostic analysis of risk score and some clinicopathological factors of CC was also performed. The copy-number variant (CNV) and single-nucleotide variant (SNV) of prognostic ARGs were analyzed by the BioPortal database. A clinical practical nomogram was established to predict individual survival probability. Finally, we carried out cell experiment to further verify the prognostic model. An eight-ARG prognostic signature for CC was constructed. High-risk CC patients had significantly shorter overall survival than low-risk patients. The receiver operating characteristic (ROC) curve validated the good performance of the signature in survival prediction. The Figo_stage and risk score served as independent prognostic factors. The eight ARGs mainly enriched in growth factor regulation and cell cycle pathway, and the deep deletion of FN1 was the most common CNV. An eight-ARG prognostic signature for CC was successfully constructed.

Icariin-Mediated miR-875-5p Inhibits Autophagy and Epithelial-Mesenchymal Transition by Regulation of MDM4 in Cervical Cancer

MicroRNAs, one type of non-coding RNA, and Icariin have attracted tremendous attention concerning various diseases, especially cancers. Also, the function of Icariin on malignant behaviors by targeting miR-875-5p/MDM4 axis in cervical cancer remains unknown. MiR-875-5p analogs combined with MDM4 or Icariin were used to explore autophagy and epithelial-mesenchymal transition in cancer cells. Xenograft mice were highlighted to elucidate the influences of Icariin and miR-875-5p in vivo. As a result, miR-875-5p was cut down in cervical cancer cells, which promoted malignant phenotype, autophagy, and limited apoptosis in cervical cancer cells. Contrarily,miR-875-5p overexpression had a contrary performance in cervical cancer cells. miR-875-5p was validated as a sponge of MDM4. Enhanced expression of MDM4 weakened the performance of miR-875-5p mimic on autophagy and epithelial-mesenchymal transition. Moreover, Icariin reversed the stimulative action of the inhibitor on autophagy and xenograft tumor growth. Generally, These findings imply that Icariin could be identified as a curative avenue for cervical cancer via miR-875-5p/MDM4 axis.

Canonical and Noncanonical ER Stress-Mediated Autophagy Is a Bite the Bullet in View of Cancer Therapy

Cancer cells adapt multiple mechanisms to counter intense stress on their way to growth. Tumor microenvironment stress leads to canonical and noncanonical endoplasmic stress (ER) responses, which mediate autophagy and are engaged during proteotoxic challenges to clear unfolded or misfolded proteins and damaged organelles to mitigate stress. In these conditions, autophagy functions as a cytoprotective mechanism in which malignant tumor cells reuse degraded materials to generate energy under adverse growing conditions. However, cellular protection by autophagy is thought to be complicated, contentious, and context-dependent; the stress response to autophagy is suggested to support tumorigenesis and drug resistance, which must be adequately addressed. This review describes significant findings that suggest accelerated autophagy in cancer, a novel obstacle for anticancer therapy, and discusses the UPR components that have been suggested to be untreatable. Thus, addressing the UPR or noncanonical ER stress components is the most effective approach to suppressing cytoprotective autophagy for better and more effective cancer treatment.

A new risk model for CSTA, FAM83A, and MYCT1 predicts poor prognosis and is related to immune infiltration in lung squamous cell carcinoma

OBJECTIVES

To create a prognostic model based on differentially expressed genes (DEGs) in early lung squamous cell carcinoma (LUSC) and characterize the relationship between risk scores and tumor immune infiltration.

METHODS

We identified DEGs in normal and tumor tissues that overlapped between LUSC-related data sets from the Gene Expression Omnibus and the Cancer Genome Atlas and evaluated their roles in the diagnosis and prognosis of LUSC by Kaplan-Meier survival analysis, receiver operating characteristic (ROC) analysis, meta-analysis and nomogram analysis. We then constructed a risk model based on Cox regression analysis and the Akaike information criterion and identified the relationship between LUSC risk scores and immune infiltration.

RESULTS

Sixty-two overlapping DEGs were involved with keratinocyte differentiation, epidermal cell differentiation, neutrophil migration, granulocyte chemotaxis, granulocyte migration, leukocyte aggregation, and positive regulation of nuclear factor-κB (NF-κB) activity. Overexpression of family with sequence similarity 83 member A (FAM83A) and MYC target 1 (MYCT1), kallikrein related peptidase 8 (KLK8), and downregulation of ADP ribosylation factor like GTPase 14 (ARL14), caspase recruitment domain family member 14 (CARD14), cystatin A (CSTA), dickkopf WNT signaling pathway inhibitor 4 (DKK4), desmoglein 3 (DSG3), and keratin 6B (KRT6B) were associated with a poor prognosis in LUSC and had significant value for LUSC diagnosis. The expression of CSTA, FAM83A, and MYCT1 and high-risk scores were independent risk factors for a poor prognosis in LUSC. A risk nomogram revealed that risk scores could predict the prognosis of LUSC. The risk score was associated with neutrophils, naive B cells, helper follicular T cells, and activated dendritic cells.

CONCLUSIONS

The expression levels of CSTA, FAM83A, and MYCT1 are related to the diagnosis and prognosis of LUSC and may have potential as therapeutic targets in LUSC. A risk model and nomogram based on CSTA, FAM83A, and MYCT1 can predict the prognosis of LUSC.

A Pyroptosis-Related Gene Panel for Predicting the Prognosis and Immune Microenvironment of Cervical Cancer

Cervical cancer (CC) is one of the most common malignant tumors of the female reproductive system. And the immune system disorder in patients results in an increasing incidence rate and mortality rate. Pyroptosis is an immune system-related programmed cell death pathway that produces systemic inflammation by releasing pro-inflammatory intracellular components. However, the diagnostic significance of pyroptosis-related genes (PRGs) in CC is still unclear. Therefore, we identified 52 PRGs from the TCGA database and screened three Differentially Expressed Pyroptosis-Related Genes (DEPRGs) in the prognosis of cervical cancer: CHMP4C, GZMB, TNF. The least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate COX regression analysis were then used to construct a gene panel based on the three prognostic DEPRGs. The patients were divided into high-and low-risk groups based on the median risk score of the panel. According to the Kaplan-Meier curve, there was a substantial difference in survival rates between the two groups, with the high-risk group’s survival rate being significantly lower than the low-risk group’s. The PCA and t-SNE analyses revealed that the panel was able to differentiate patients into high-and low-risk groups. The area under the ROC curve (AUC) shows that the prognostic panel has high sensitivity and specificity. The risk score could then be employed as an independent prognostic factor using univariate and multivariate COX regression analyses paired with clinical data. The analyses of GO and KEGG functional enrichment of differentially expressed genes (DEGs) in the high-and low-risk groups revealed that these genes were primarily engaged in immune response and inflammatory cell chemotaxis. To illustrate immune cell infiltration in CC patients further, we used ssGSEA to compare immune-related cells and immune pathway activation between the high-and low-risk groups. The link between three prognostic DEPRGs and immune-related cells was still being discussed after evaluating immune cell infiltration in the TCGA cohort with “CIBERSORT.” In addition, the GEPIA database and qRT-PCR analysis were used to verify the expression levels of prognostic DEPRGs. In conclusion, PRGs are critical in tumor immunity and can be utilized to predict the prognosis of CC.

Comprehensive Molecular Analyses of a TNF Family-Based Gene Signature as a Potentially Novel Prognostic Biomarker for Cervical Cancer

Background

Increasing evidence suggests that tumour necrosis factor (TNF) family genes play important roles in cervical cancer (CC). However, whether TNF family genes can be used as prognostic biomarkers of CC and the molecular mechanisms of TNF family genes remain unclear.

Methods

A total of 306 CC and 13 normal samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We identified differentially expressed TNF family genes between CC and normal samples and subjected them to univariate Cox regression analysis for selecting prognostic TNF family genes. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to screen genes to establish a TNF family gene signature. Gene set enrichment analysis (GSEA) was performed to investigate the biological functions of the TNF family gene signature. Finally, methylation and copy number variation data of CC were used to analyse the potential molecular mechanisms of TNF family genes.

Results

A total of 26 differentially expressed TNF family genes were identified between the CC and normal samples. Next, a TNF family gene signature, including CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 was constructed based on univariate Cox, LASSO, and multivariate Cox regression analyses. The TNF family gene signature was related to age, pathological stages M and N, and could predict patient survival independently of clinical factors. Moreover, KEGG enrichment analysis suggested that the TNF family gene signature was mainly involved in the TGF-β signaling pathway, and the TNF family gene signature could affect the immunotherapy response. Finally, we confirmed that the mRNA expressions of CD27, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 were upregulated in CC, while that of EDA was downregulated. The mRNA expressions of CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be influenced by gene methylation and copy number variation.

Conclusion

Our study is the first to demonstrate that CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be used as prognostic biomarkers of CC and are associated with the immunotherapy response of CC.

DNA Damage Repair-Related Genes Signature for Immune Infiltration and Outcome in Cervical Cancer

Background: The mechanism of DNA damage repair plays an important role in many solid tumors represented by cervical cancer.

Purpose: The purpose of this study was to explore the effect of DNA damage repair-related genes on immune function of patients with cervical cancer, and to establish and evaluate a prognosis model based on DNA damage repair-related genes.

Methods: In the study, we analyzed the genes related to DNA damage and repair, and obtained two subtypes (F1 and F2). We selected two groups of samples for different selection, and studied which pathways were enriched expression. For different subtypes, the immune score was explored to explain immune infiltration. We got the key genes through screening, and established the prognosis model through the key genes. These 11 key genes were correlated with the expression of common Clusters of Differentiation (CD) genes in order to explore the effects of these genes on immunity.

Results: Through the Least absolute shrinkage and selection operator (LASSO) method, we screened 11 genes from 232 candidate genes as the key genes for the prognosis score. Through the Kaplan-Meier method, four genes (HAP1, MCM5, RNASEH2A, CETN2) with significant prognostic significance were screened into the final model, forming a Nomogram with C-index of 0.716 (0.649–1.0).

Conclusion: In cervical cancer, DNA damage repair related genes and immune cell infection characteristics have certain association, and DNA damage repair related genes and immune cell infection characteristics can effectively predict the prognosis.

Values of a novel pyroptosis-related genetic signature in predicting outcome and immune status of pancreatic ductal adenocarcinoma

Background

Pyroptosis is an emerging form of programmed cell death associated with progression in malignancies. Yet, there are few studies reporting on the association between pancreatic ductal adenocarcinoma (PDAC) and pyroptosis. Therefore, we aimed to construct a pyroptosis-related genetic signature to predict the clinical outcome and immune status in PDAC patients.

Methods

RNA-seq data of 176 PDAC patients from The Cancer Genome Atlas (TCGA) and 167 PDAC patients from the Genotype-Tissue Expression Project were analysed for pyroptosis-related differentially expressed genes (DEGs) between PDAC and normal pancreas. The risk signature of DEGs was analysed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and its accuracy was validated in the Gene Expression Omnibus (GEO) cohort (n = 190). Functional enrichment analyses were performed to explore the mechanisms of the DEGs. The immune characteristics were evaluated using single-sample gene set enrichment analysis and ESTIMATE algorithms for each group.

Results

A nine-gene risk signature was generated from LASSO Cox regression analysis and classified PDAC patients into either a high- or low-risk group according to the median risk score. The high-risk group had significantly shorter overall survival than the low-risk group and it was verified in the external GEO database. A nomogram based on the risk signature was constructed and showed an ideal prediction performance. Functional enrichment analyses revealed that pyroptosis might regulate the tumor immune microenvironment in PDAC. Immune infiltration evaluation suggested that immune status was more activated in the low-risk group than in the high-risk group.

Conclusion

The risk signature encompassing nine pyroptosis-related genes may be a prognostic marker for PDAC. Pyroptosis might affect the prognosis of PDAC patients via regulating the tumor immune microenvironment.

A Novel Pyroptosis-Related Signature for Predicting Prognosis and Indicating Immune Microenvironment Features in Osteosarcoma

Osteosarcoma is a common malignant bone tumor with a propensity for drug resistance, recurrence, and metastasis. A growing number of studies have elucidated the dual role of pyroptosis in the development of cancer, which is a gasdermin-regulated novel inflammatory programmed cell death. However, the interaction between pyroptosis and the overall survival (OS) of osteosarcoma patients is poorly understood. This study aimed to construct a prognostic model based on pyroptosis-related genes to provide new insights into the prognosis of osteosarcoma patients. We identified 46 differentially expressed pyroptosis-associated genes between osteosarcoma tissues and normal control tissues. A total of six risk genes affecting the prognosis of osteosarcoma patients were screened to form a pyroptosis-related signature by univariate and LASSO regression analysis and verified using GSE21257 as a validation cohort. Combined with other clinical characteristics, including age, gender, and metastatic status, we found that the pyroptosis-related signature score, which we named “PRS-score,” was an independent prognostic factor for patients with osteosarcoma and that a low PRS-score indicated better OS and a lower risk of metastasis. The result of ssGSEA and ESTIMATE algorithms showed that a lower PRS-score indicated higher immune scores, higher levels of tumor infiltration by immune cells, more active immune function, and lower tumor purity. In summary, we developed and validated a pyroptosis-related signature for predicting the prognosis of osteosarcoma, which may contribute to early diagnosis and immunotherapy of osteosarcoma.

Increased ATG5 Expression Predicts Poor Prognosis and Promotes EMT in Cervical Carcinoma

Cervical cancer has the second-highest incidence and mortality of female malignancy. The major causes of mortality in patients with cervical cancer are invasion and metastasis. The epithelial–mesenchymal transition (EMT) process plays a major role in the acquisition of metastatic potential and motility. Autophagy-related genes (ARGs) are implicated in the EMT process, and autophagy exerts a dual function in EMT management at different phases of tumor progression. However, the role of specific ARGs during the EMT process has not yet been reported in cervical cancer. Based on the data from the Cancer Genome Atlas (TCGA) cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) sequencing database, we performed the prognosis analysis for those ARGs obtained from the Human Autophagy database. ATG5 was identified as the only important harmful marker influencing survival of cervical cancer patients by univariate Cox regression (HR 1.7; 95% CI: 1.0–2.8, p = 0.047), and the 5-years survival rate for the high- and low-ATG5 expression groups was 0.486 (0.375–0.631) and 0.782 (0.708–0.863), respectively. TCGA CESC methylation data showed that eight methylation sites of ATG5 could also be significantly associated with the overall survival (OS) of cervical cancer patients. Single-sample gene-set enrichment and gene functional enrichment results showed that ATG5 was correlated with some cancer-related pathways, such as phagocytosis-related genes, endocytosis-related genes, immune-related genes, EMT score, and some EMT signature-related genes. Next, cell migration and invasion assay and Western blot were applied to detect the function of ATG5 in EMT of cervical cancer. In cervical cancer cells, ATG5 knockdown resulted in attenuation of migration and invasion. The functional study showed that knockdown of ATG5 could reverse EMT process by P-ERK, P-NFκBp65, P-mTOR pathways, and so on. In conclusion, the present study implies that ATG5 was a major contributor to EMT regulation and poor prognosis in cervical cancer.

Hydroxychloroquine Induces Apoptosis in Cholangiocarcinoma via Reactive Oxygen Species Accumulation Induced by Autophagy Inhibition

Purpose: Despite considerable efforts to improve treatment modalities for cholangiocarcinoma, a common form of malignant tumor, its long-term survival rate remains poor. Hydroxychloroquine (HCQ) is a 4-aminoquinoline derivative antimalarial drug that has antimalarial and autophagy inhibition effects and exhibits comprehensive therapeutic effects on various cancers. In this study, we aimed to explore the anticancer potential and the underlying molecular mechanism of HCQ in cholangiocarcinoma treatment in vitro and in vivo. Methods: Autophagy-related genes (ARGs) were obtained from the Human Autophagy Database and Molecular Signatures Database, and the expression profiles of ARGs were downloaded from the database of The Cancer Genome Atlas. Different expression gene sets were performed using R software. The Gene Ontology and KEGG enrichment analyses were performed to reveal significantly enriched signaling pathways and to identify differentially expressed genes in cholangiocarcinoma tissues. HuCCT-1 and CCLP-1 cells were exposed to different concentrations of HCQ. Cell proliferation was detected by Cell Counting Kit-8 (CCK-8), colony formation, and 5-ethynyl-2'-deoxyuridine (EdU) assays. Cell apoptosis and cycle arrest were detected by the Live/Dead cell assay and flow cytometry (FCM). The inhibition of autophagy was observed using fluorescence microscopy. The reactive oxygen species levels were assessed by fluorescence microscopy and flow cytometry. The protein levels were determined by western blot. A cholangiocarcinoma cell line xenograft model was used to evaluate the antitumor activity of HCQ in vivo. Results: Compared with normal tissues, there were 141 ARGs with an aberrant expression in cholangiocarcinoma tissues which were mainly enriched in autophagy-related processes. Inhibition of autophagy by HCQ effectively suppressed cholangiocarcinoma in vitro and in vivo. HCQ inhibited cell proliferation and induced apoptosis and cycle arrest in vitro by increasing ROS accumulation, which was involved in autophagy inhibition. The ROS scavenger reduced l-glutathione distinctly weakened HCQ-induced cell apoptosis and viability inhibition in cholangiocarcinoma cells. In addition, HCQ inhibited growth of cholangiocarcinoma cell line xenograft tumors. Conclusion: HCQ could inhibit cell proliferation and induce apoptosis in cholangiocarcinoma by triggering ROS accumulation via autophagy inhibition, which makes HCQ a potential antitumor drug candidate for cholangiocarcinoma treatment.

Screening and evaluation of the role of immune genes of brain metastasis in lung adenocarcinoma progression based on the TCGA and GEO databases

Background

Brain metastasis was one of the factors leading to the poor long-term prognosis of patients with lung adenocarcinoma (LUAD).

Methods

The expression levels of immune genes in LUAD and LUAD brain metastases tissues were analyzed in GSE161116 dataset using the GEO2R, and the levels of differential immune genes in normal lung and LUAD tissues were verified. The biological functions and signaling mechanisms of the differential immune genes were explored via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Cox regression analysis was used to screen the prognostic factors of LUAD patients, and a risk model was constructed. The role of the model was checked in the development of LUAD via receiver operating characteristic analysis, gene set enrichment analysis, and Cox regression analysis.

Results

Differentially expressed genes (DEGs) in brain metastasis were involved in the adaptive immune response, B cell differentiation, leukocyte migration, NF-kB signaling pathway, among others. The expression levels of TNFRSF11A, MS4A2, IL11, CAMP, MS4A1, and F2RL1 were independent factors affecting the poor prognosis of LUAD patients via Cox regression analysis and Akaike information criterion. In the constructed risk model, the overall survival of LUAD patients in the high-risk group was poor. The risk model was significantly related to the gender, clinical stage, T stage, lymph node metastasis, and survival status of LUAD patients. In addition, the risk model score was an independent risk factor that affected the poor prognosis of LUAD patients. TNFRSF11A, CAMP, F2RL1, IL11, MS4A1, and MS4A2 of the risk factors had diagnostic significance in LUAD brain metastasis and LUAD. The risk model participated in cytokinetic process, cell cycle, citrate cycle TCA cycle, etc. The risk model score was correlated with the levels of B cells memory, mast cells resting, macrophages M0, mast cells activated, neutrophils, eosinophils, T cells gamma delta, and immune cell markers.

Conclusions

The risk model based on the LUAD brain metastasis immune factors TNFRSF11A, MS4A2, IL11, CAMP, MS4A1, and F2RL1 was related to the diagnosis, poor prognosis, and immune infiltrating cells of LUAD patients, and is expected to provide a reference for the development of treatment strategies for LUAD patients.

Elevated Ras related GTP binding B (RRAGB) expression predicts poor overall survival and constructs a prognostic nomogram for colon adenocarcinoma

Currently, no articles have explored the roles of RRAGB gene in the occurrence and development of cancer. By means of The Cancer Genome Atlas (TCGA) data mining, we found that this gene might be a novel prognostic predictor for colon adenocarcinoma (COAD). Hence, this article was carried out to explore its roles in COAD and associations with immunity. RRAGB single-gene expression matrix and corresponding clinical information were extracted from TCGA database. Univariate/multivariate cox regression analyses and gene set enrichment analysis (GSEA) were utilized to identify independent prognostic factors and RRAGB related pathways, respectively. Relationships between RRAGB and immunity were also analyzed. Boxplot and K-M survival analysis indicated that RRAGB was not only differently expressed in COAD (P < 0.05), but also significantly associated with overall survival (OS; P < 0.05). Univariate and multivariate Cox hazard regression analyses indicated that RRAGB could serve as an independent prognostic factor for COAD (both P < 0.05). GSEA identified five signaling pathways significantly enriched in the high-RRAGB expression phenotype. Moreover, a RRAGB-based nomogram was successfully constructed and displayed a satisfactory performance. In addition, RRAGB expression was found to be significantly associated with microsatellite instability (MSI), tumor mutational burden (TMB) and immunity. Our results revealed that RRAGB could be a prognostic biomarker for COAD in terms of OS and markedly related to MSI, TMB, and immunity. We also constructed an RRAGB-based nomogram with a satisfactory performance. Further researches should be carried out to validate our findings.

Identification and Validation of Autophagy-Related Gene Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer

Autophagy is a process of engulfing one's own cytoplasmic proteins or organelles and coating them into vesicles, fusing with lysosomes to form autophagic lysosomes, and degrading the contents it encapsulates. Increasing studies have shown that autophagy disorders are closely related to the occurrence of tumors. However, the prognostic role of autophagy genes in cervical cancer is still unclear. In this study, we constructed risk signatures of autophagy-related genes (ARGs) to predict the prognosis of cervical cancer. The expression profiles and clinical information of autophagy gene sets were downloaded from TCGA and GSE52903 queues as training and validation sets. The normal cervical tissue expression profile data from the UCSC XENA website (obtained from GTEx) were used as a supplement to the TCGA normal cervical tissue. Univariate COX regression analysis of 17 different autophagy genes was performed with the consensus approach. Tumor samples from TCGA were divided into six subtypes, and the clinical traits of the six subtypes had different distributions. Further absolute shrinkage and selection operator (LASSO) and multivariable COX regression yielded an autophagy genetic risk model consisting of eight genes. In the training set, the survival rate of the high-risk group was lower than that of the low-risk group (p < 0.0001). In the validation set, the AUC area of the receiver operating characteristic (ROC) curve was 0.772 for the training set and 0.889 for the verification set. We found that high and low risk scores were closely related to TNM stage (p < 0.05). The nomogram shows that the risk score combined with other indicators, such as G, T, M, and N, better predicts 1-, 3-, and 5-year survival rates. Decline curve analysis (DCA) shows that the risk model combined with other indicators produces better clinical efficacy. Immune cells with an enrichment score of 28 showed statistically significant differences related to high and low risk. GSEA enrichment analysis showed the main enrichment being in KRAS activation, genes defining epithelial and mesenchymal transition (EMT), raised in response to the low oxygen level (hypoxia) gene and NF-kB in response to TNF. These pathways are closely related to the occurrence of tumors. Our constructed autophagy risk signature may be a prognostic tool for cervical cancer.