scholarly journals Prognostic Role and Diagnostic Power of Seven Indicators in COVID-19 Patients

2021 ◽  
Vol 8 ◽  
Author(s):  
Lili Ding ◽  
Wanwan Zhang ◽  
Fengling Zhang ◽  
Chaoqun Huang ◽  
Ming Yang ◽  
...  
Keyword(s):  
High Risk ◽  
Oxygen Saturation ◽  
Risk Groups ◽  
Prognostic Signature ◽  
Prognostic Role ◽  
Diagnostic Ability ◽  
The Common ◽  
Disease Indicators ◽  
Critical Type ◽  
D Dimer

The prognostic role and diagnostic ability of coronavirus disease 2019 (COVID-19) disease indicators are not elucidated, thus, the current study aimed to investigate the prognostic role and diagnostic ability of several COVID-19 disease indicators including the levels of oxygen saturation, leukocytes, lymphocytes, albumin, C-reactive protein (CRP), interleukin-6 (IL-6), and D-dimer in patients with COVID-19. The levels of oxygen saturation, lymphocytes, and albumin were significantly higher in the common and severe clinical type patients compared with those in critical type patients. However, levels of leukocytes, CRP, IL-6, and D-dimer were significantly lower in the common and severe type patients compared with those in critical type patients (P < 0.001). Moreover, the current study demonstrated that the seven indicators have good diagnostic and prognostic powers in patients with COVID-19. Furthermore, a two-indicator (CRP and D-dimer) prognostic signature in training and testing datasets was constructed and validated to better understand the prognostic role of the indicators in COVID-19 patients. The patients were classified into high-risk and low-risk groups based on the median-risk scores. The findings of the Kaplan–Meier curve analysis indicated a significant divergence between the high-risk and low-risk groups. The findings of the receiver operating curve (ROC) analysis indicated the good performance of the signature in the prognosis prediction of COVID-19. In addition, a nomogram was constructed to assist clinicians in developing clinical decision-making for COVID-19 patients. In conclusion, the findings of the current study demonstrated that the seven indicators are potential diagnostic markers for COVID-19 and a two-indicator prognostic signature identification may improve clinical management for COVID-19 patients.

scholarly journals Development and Verification of the Hypoxia- and Immune-Associated Prognostic Signature for Pancreatic Ductal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Dongjie Chen ◽  
Hui Huang ◽  
Longjun Zang ◽  
Wenzhe Gao ◽  
Hongwei Zhu ◽  
...  
Keyword(s):  
High Risk ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Pearson Correlation ◽  
Risk Groups ◽  
Low Risk ◽  
Ductal Adenocarcinoma ◽  
Prognostic Signature ◽  
Score Model

We aim to construct a hypoxia- and immune-associated risk score model to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). By unsupervised consensus clustering algorithms, we generate two different hypoxia clusters. Then, we screened out 682 hypoxia-associated and 528 immune-associated PDAC differentially expressed genes (DEGs) of PDAC using Pearson correlation analysis based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression project (GTEx) dataset. Seven hypoxia and immune-associated signature genes (S100A16, PPP3CA, SEMA3C, PLAU, IL18, GDF11, and NR0B1) were identified to construct a risk score model using the Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, which stratified patients into high- and low-risk groups and were further validated in the GEO and ICGC cohort. Patients in the low-risk group showed superior overall survival (OS) to their high-risk counterparts (p < 0.05). Moreover, it was suggested by multivariate Cox regression that our constructed hypoxia-associated and immune-associated prognosis signature might be used as the independent factor for prognosis prediction (p < 0.001). By CIBERSORT and ESTIMATE algorithms, we discovered that patients in high-risk groups had lower immune score, stromal score, and immune checkpoint expression such as PD-L1, and different immunocyte infiltration states compared with those low-risk patients. The mutation spectrum also differs between high- and low-risk groups. To sum up, our hypoxia- and immune-associated prognostic signature can be used as an approach to stratify the risk of PDAC.

scholarly journals Identification of a novel signature based on unfolded protein response-related gene for predicting prognosis in bladder cancer

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Ke Zhu ◽  
Liu Xiaoqiang ◽  
Wen Deng ◽  
Gongxian Wang ◽  
Bin Fu
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Unfolded Protein Response ◽  
Immune Cells ◽  
Risk Groups ◽  
Immune Checkpoints ◽  
Related Gene ◽  
Prognostic Signature ◽  
Unfolded Protein ◽  
Protein Response

Abstract Background The unfolded protein response (UPR) served as a vital role in the progression of tumors, but the molecule mechanisms of UPR in bladder cancer (BLCA) have been not fully investigated. Methods We identified differentially expressed unfolded protein response-related genes (UPRRGs) between BLCA samples and normal bladder samples in the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis and the least absolute shrinkage and selection operator penalized Cox regression analysis were used to construct a prognostic signature in the TCGA set. We implemented the validation of the prognostic signature in GSE13507 from the Gene Expression Omnibus database. The ESTIMATE, CIBERSORT, and ssGSEA algorithms were used to explore the correlation between the prognostic signature and immune cells infiltration as well as key immune checkpoints (PD-1, PD-L1, CTLA-4, and HAVCR2). GDSC database analyses were conducted to investigate the chemotherapy sensitivity among different groups. GSEA analysis was used to explore the potential mechanisms of UPR-based signature. Results A prognostic signature comprising of seven genes (CALR, CRYAB, DNAJB4, KDELR3, CREB3L3, HSPB6, and FBXO6) was constructed to predict the outcome of BLCA. Based on the UPRRGs signature, the patients with BLCA could be classified into low-risk groups and high-risk groups. Patients with BLCA in the low-risk groups showed the more favorable outcomes than those in the high-risk groups, which was verified in GSE13507 set. This signature could serve as an autocephalous prognostic factor in BLCA. A nomogram based on risk score and clinical characteristics was established to predict the over survival of BLCA patients. Furthermore, the signature was closely related to immune checkpoints (PD-L1, CTLA-4, and HAVCR2) and immune cells infiltration including CD8+ T cells, follicular helper T cells, activated dendritic cells, and M2 macrophages. GSEA analysis indicated that immune and carcinogenic pathways were enriched in high-risk group. Conclusions We identified a novel unfolded protein response-related gene signature which could predict the over survival, immune microenvironment, and chemotherapy response of patients with bladder cancer.

Elevated Levels of Prothrombin Fragment 1 + 2 Indicate High Risk of Thrombosis

2008 ◽  
Vol 14 (3) ◽  
pp. 279-285 ◽  
Author(s):  
Satoshi Ota ◽  
Hideo Wada ◽  
Yasunori Abe ◽  
Eri Yamada ◽  
Akane Sakaguchi ◽  
...  
Keyword(s):  
Plasma Concentration ◽  
High Risk ◽  
Plasma Concentrations ◽  
Diagnostic Ability ◽  
Soluble Fibrin ◽  
Prothrombin Fragment ◽  
Cutoff Values ◽  
D Dimer

Prothrombin fragment 1 + 2 (F1 + 2) is considered to be useful for diagnosis of thrombosis. However, the evidence for a diagnosis of thrombosis by F1 + 2 is still not well established. The plasma concentrations of F1 + 2, soluble fibrin, D-dimer, and thrombin-antithrombin complex were measured in 694 patients suspected of having thrombosis and then were correlated with thrombosis. Plasma concentrations of F1 + 2, soluble fibrin, D-dimer, and thrombin-antithrombin complex were significantly higher in patients with thrombosis, compared with patients without thrombosis. When cutoff values of more than 300 pmol/L for F1 + 2 were used for the diagnosis, more than 50% of the patients were thus found to have thrombosis. The findings showed that F1 + 2, soluble fibrin, D-dimer, and thrombin-antithrombin complex have similar diagnostic ability. The plasma concentration of F1 + 2 closely was well correlated with thrombin-antithrombin complex, soluble fibrin, and D-dimer. Finally, F1 + 2 is one of the most useful parameters for the diagnosis of thrombosis.

scholarly journals Identification of the prognostic value of ferroptosis-related gene signature in breast cancer patients

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ding Wang ◽  
Guodong Wei ◽  
Ju Ma ◽  
Shuai Cheng ◽  
Longyuan Jia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
High Risk ◽  
Cancer Patients ◽  
Roc Curves ◽  
Risk Groups ◽  
Gene Signature ◽  
Breast Cancer Patients ◽  
Prognostic Signature ◽  
Kaplan Meier

Abstract Background Breast cancer (BRCA) is a malignant tumor with high morbidity and mortality, which is a threat to women’s health worldwide. Ferroptosis is closely related to the occurrence and development of breast cancer. Here, we aimed to establish a ferroptosis-related prognostic gene signature for predicting patients’ survival. Methods Gene expression profile and corresponding clinical information of patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. The Least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analysis model was utilized to construct a multigene signature. The Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and single-sample gene set enrichment analysis (ssGSEA) were performed for patients between the high-risk and low-risk groups divided by the median value of risk score. Results We constructed a prognostic signature consisted of nine ferroptosis-related genes (ALOX15, CISD1, CS, GCLC, GPX4, SLC7A11, EMC2, G6PD and ACSF2). The Kaplan-Meier curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the ROC curves manifested that the ferroptosis-related signature had moderate predictive power. GO and KEGG functional analysis revealed that immune-related responses were largely enriched, and immune cells, including activated dendritic cells (aDCs), dendritic cells (DCs), T-helper 1 (Th1), were higher in high-risk groups (p < 0.001). Oppositely, type I IFN response and type II IFN response were lower in high-risk groups (p < 0.001). Conclusion Our study indicated that the ferroptosis-related prognostic signature gene could serve as a novel biomarker for predicting breast cancer patients’ prognosis. Furthermore, we found that immunotherapy might play a vital role in therapeutic schedule based on the level and difference of immune-related cells and pathways in different risk groups for breast cancer patients.

scholarly journals Comprehensive Analysis of the Prognostic Significance of Hsa-miR-100-5p and Its Related Gene Signature in Stomach Adenocarcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Gaoming Wang ◽  
Ludi Yang ◽  
Miao Hu ◽  
Renhao Hu ◽  
Yongkun Wang ◽  
...  
Keyword(s):  
High Risk ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Tumor Development ◽  
Risk Groups ◽  
Gene Signature ◽  
Risk Scores ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Stomach Adenocarcinoma

Stomach adenocarcinoma (STAD) is one of the most common cancers in the world. However, the prognosis of STAD remains poor, and the therapeutic effect of chemotherapy and immunotherapy varies from person to person. MicroRNAs (miRNAs) play vital roles in tumor development and metastasis and can be used for cancer diagnosis and prognosis. In this study, hsa-miR-100-5p was identified as the only dysregulated miRNA in STAD samples through an analysis of three miRNA expression matrices. A weighted gene co-expression network analysis (WGCNA) was performed to select hsa-miR-100-5p-related genes. A least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to establish a miR-100-5p-related prognostic signature. Kaplan–Meier analyses, nomograms, and univariate and multivariate Cox regression analyses were used to evaluate the prognostic signature, which was subsequently identified as an independent risk factor for STAD patients. We investigated the tumor immune environment between low- and high-risk groups and found that, among component types, M2 macrophages contributed the most to the difference between these groups. A drug sensitivity analysis suggested that patients with high-risk scores may be more sensitive to docetaxel and cisplatin chemotherapy and that patients in the low-risk group may be more likely to benefit from immunotherapy. Finally, external cohorts were evaluated to validate the robustness of the prognostic signature. In summary, this study may provide new ideas for developing more individualized therapeutic strategies for STAD patients.

scholarly journals Development and Validation of a Robust Pyroptosis-Related Signature for Predicting Prognosis and Immune Status in Patients with Colon Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Zhicheng Zhuang ◽  
Huajun Cai ◽  
Hexin Lin ◽  
Bingjie Guan ◽  
Yong Wu ◽  
...  
Keyword(s):  
High Risk ◽  
Immune Cells ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Immune Checkpoints ◽  
Prognostic Signature ◽  
Tumor Purity ◽  
Kaplan Meier

Background. Pyroptosis has been confirmed as a type of inflammatory programmed cell death in recent years. However, the prognostic role of pyroptosis in colon cancer (CC) remains unclear. Methods. Dataset TCGA-COAD which came from the TCGA portal was taken as the training cohort. GSE17538 from the GEO database was treated as validation cohorts. Differential expression genes (DEGs) between normal and tumor tissues were confirmed. Patients were classified into two subgroups according to the expression characteristics of pyroptosis-related DEGs. The LASSO regression analysis was used to build the best prognostic signature, and its reliability was validated using Kaplan–Meier, ROC, PCA, and t-SNE analyses. And a nomogram based on the multivariate Cox analysis was developed. The enrichment analysis was performed in the GO and KEGG to investigate the potential mechanism. In addition, we explored the difference in the abundance of infiltrating immune cells and immune microenvironment between high- and low-risk groups. And we also predicted the association of common immune checkpoints with risk scores. Finally, we verified the expression of the pyroptosis-related hub gene at the protein level by immunohistochemistry. Results. A total of 23 pyroptosis-related DEGs were identified in the TCGA cohort. Patients were classified into two molecular clusters (MC) based on DEGs. Kaplan–Meier survival analysis indicated that patients with MC1 represented significantly poorer OS than patients with MC2. 13 overall survival- (OS-) related DEGs in MCs were used to construct the prognostic signature. Patients in the high-risk group exhibited poorer OS compared to those in the low-risk group. Combined with the clinical features, the risk score was found to be an independent prognostic factor of CC patients. The above results are verified in the external dataset GSE17538. A nomogram was established and showed excellent performance. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the varied prognostic performance between high- and low-risk groups may be related to the immune response mediated by local inflammation. Further analysis showed that the high-risk group has stronger immune cell infiltration and lower tumor purity than the low-risk group. Through the correlation between risk score and immune checkpoint expression, T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3) was predicted as a potential therapeutic target for the high-risk group. Conclusion. The 13-gene signature was associated with OS, immune cells, tumor purity, and immune checkpoints in CC patients, and it could provide the basis for immunotherapy and predicting prognosis and help clinicians make decisions for individualized treatment.

scholarly journals Pyroptosis-associated molecular classification and prognostic signature in glioma

2021 ◽  
Author(s):  
Yanyan Li ◽  
Lin Shen ◽  
Na Li ◽  
Yajie Zhao ◽  
Qin Zhou ◽  
...  
Keyword(s):  
High Risk ◽  
Clinical Features ◽  
Immune Cell ◽  
Risk Groups ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Prognostic Signature ◽  
Molecular Alterations ◽  
Genome Atlas

Purpose: Integrative analysis was performed in the Chinese Glioma Genome Atlas and The Cancer Genome Atlas to describe the pyroptosis-associated molecular classification and prognostic signature in glioma. Experimental Design: Pyroptosis-related genes were used for consensus clustering and to develop a prognostic signature. The immune statuses, molecular alterations and clinical features of differentially expressed genes were analyzed among different subclasses and risk groups. A lncRNA-miRNA-mRNA network was built, and drug sensitivity analysis was used to identify small molecular drugs for the identified genes. Results: Glioma can be divided into two subclasses using 30 pyroptosis-related genes. Cluster 1 displayed high immune signatures and poor prognosis as well as high immune-related function scores. A prognostic signature based on 15 pyroptosis-related genes of the CGGA cohort can predict the overall survival of glioma and was well validated in the TCGA cohort. Cluster 1 had higher risk scores. The high-risk group had high immune cell and function scores and low DNA methylation of pyroptosis-related genes. The differences in pyroptosis-related gene mutations and somatic copy numbers were significant between the high-risk and low-risk groups. The ceRNA regulatory network uncovered the regulatory patterns of different risk groups in glioma. Nine pairs of target genes and drugs were identified. Conclusions: Pyroptosis-related genes can reflect the molecular biological and clinical features of glioma subclasses. The established prognostic signature can predict prognosis and distinguish molecular alterations in glioma patients. Our comprehensive analyses provide valuable guidelines for improving glioma patient management and individualized therapy.

scholarly journals Molecular characterization of triple negative breast cancer formaldehyde-fixed paraffin-embedded samples by data-independent acquisition proteomics

2020 ◽  
Author(s):  
Silvia García-Adrián ◽  
Lucía Trilla-Fuertes ◽  
Angelo Gámez-Pozo ◽  
Cristina Chiva ◽  
Rocío López-Vacas ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Graphical Models ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Risk Groups ◽  
Prognostic Signature ◽  
Data Independent Acquisition ◽  
Formalin Fixed Paraffin Embedded ◽  
Using Data

AbstractTriple negative breast cancer (TNBC) accounts for 15-20% of all breast carcinomas and it is clinically characterized by an aggressive phenotype and bad prognosis. TNBC does not benefit from any targeted therapy, so further characterization is needed to define subgroups with potential therapeutic value. In this work, the proteomes of one hundred twenty-five formalin-fixed paraffin-embedded samples from patients diagnosed with triple negative breast cancer were analyzed by mass spectrometry using data-independent acquisition. Hierarchical clustering, probabilistic graphical models and Significance Analysis of Microarrays were used to characterize molecular groups. Additionally, a predictive signature related with relapse was defined. Two molecular groups with differences in several biological processes as glycolysis, translation and immune response, were defined in this cohort, and a prognostic signature based on the abundance of proteins RBM3 and NIPSNAP1 was defined. This predictor split the population into low-risk and high-risk groups. The differential processes identified between the two molecular groups may serve to design new therapeutic strategies in the future and the prognostic signature could be useful to identify a population at high-risk of relapse that could be directed to clinical trials.

scholarly journals ВИВЧЕННЯ ВПЛИВУ ВІКУ ТА ІНДЕКСУ КОМОРБІДНОСТІ НА РИЗИК ТРОМБОТИЧНИХ УСКЛАДНЕНЬ У ХВОРИХ НА РАК ЕНДОМЕТРІЯ НА ДООПЕРАЦІЙНОМУ ЕТАПІ

2018 ◽  
Author(s):  
B. D. Kryvokulsky ◽  
I. V. Zhulkevich ◽  
D. B. Kryvokulsky ◽  
L. V. Shkrobot
Keyword(s):  
Risk Factors ◽  
Endometrial Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Groups ◽  
Pelvic Plexus ◽  
Increased Risk ◽  
Thrombotic Complications ◽  
Comorbidity Index ◽  
D Dimer

Endometrial cancer (EC) is the most common gynecological malignancy in women over 50 years of age. Age is a specific, significant predictor of the survival outcome in EC. Thrombotic complications (TC) are the other frequencies due to death in cancer patients. The problem of thrombosis is relevant and occupies a large proportion of the immediate causes of death in patients with oncological practice. Identification of risk groups, the implementation of a personalized approach to the prevention of TB is very practical in patients with EC.The aim of the study – to conduct an assessment of the Charleson Comorbidity Index and identify the link between an increased risk of thrombotic formation in patients with EС and associated pathology at the preoperative stage.Materials and Methods. The study used general clinical methods of examination: laboratory, specific for determining the state of hemostasis (D-dimer, antithrombin III, protein C, fibrinogen B, ACTH , IF, PM ), ultrasound examination (abdominal organs, small pelvis, lower vessels limbs and pelvic plexus; elastography of the vessels of the lower extremities and pelvic plexus). Histologic methods of tumor investigation – to determine the relationship between histological type, depth of invasion, degree of malignancy of the tumor. Mathematical, statistical – for analysis and generalization of data in the package "Statgraph" (v.3.0).Results and Discussion. On the basis of the obtained data and analysis of the risk factors of the occurrence of TC on the scale of Caprini, we came to the conclusion that the whole surveyed group of patients in the EC referred to the high risk of TC since they had 6 or more points. This is due to age, overweight, increased body surface area and body mass index, cancer pathology, concomitant pathology, which coincides with the data of world literature. Based on the integrated assessment of the Charleson Comorbidity Index and the assessment of the risk of developing TC on the Caprini scale, we noted that the most common risk factors for thrombosis are: abnormal fat metabolism, hypertonic disease, atherosclerosis, vascular disease. The combination of two or more risk factors for thrombosis was noted at 46.25 %. Relevant statistical discrepancies (p <0.05) in the hemostasis system in patients, depending on anthropometric indices, were confirmed by correlation bonds. We established a statistically significant (0.001 <p <0.05) positive relationship (r2> 0.17) between pelvic vein thrombosis and weight, age, BM I, Caprini scale, PPT , proper weight and PPT , PM , ACTCH Fibrinogen, D-dimer and a reliable negative (r2 <-0.17) relationship between thrombosis of the veins of the small pelvis and: the relation between the level of the MS and the level of D-dimer; PM / D-dimer; AT III / D-dimer.Conclusions. Based on the correlation data, it can be argued that the calculation of the Charleson Comorbidity Index is an important element in predicting survival rates in patients, but it does not provide an opportunity to predict the risk of thrombotic complications in patients with PE . The parallel compilation of the Charleson Comorbidity Index and the determination of the risk of developing thrombotic complications in endometrial cancer patients at the preoperative stage allows the isolation of high and high-risk groups of TU , especially in women over the age of 50 with existing comorbidity.

scholarly journals Identification of a novel autophagy signature for predicting survival in patients with lung adenocarcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11074
Author(s):  
Jin Duan ◽  
Youming Lei ◽  
Guoli Lv ◽  
Yinqiang Liu ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Immune Cell ◽  
Cox Regression ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Cell Analysis ◽  
Prognostic Signature

Background Lung adenocarcinoma (LUAD) is the most commonhistological lung cancer subtype, with an overall five-year survivalrate of only 17%. In this study, we aimed to identify autophagy-related genes (ARGs) and develop an LUAD prognostic signature. Methods In this study, we obtained ARGs from three databases and downloaded gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used TCGA-LUAD (n = 490) for a training and testing dataset, and GSE50081 (n = 127) as the external validation dataset.The least absolute shrinkage and selection operator (LASSO) Cox and multivariate Cox regression models were used to generate an autophagy-related signature. We performed gene set enrichment analysis (GSEA) and immune cell analysis between the high- and low-risk groups. A nomogram was built to guide the individual treatment for LUAD patients. Results We identified a total of 83 differentially expressed ARGs (DEARGs) from the TCGA-LUAD dataset, including 33 upregulated DEARGs and 50 downregulated DEARGs, both with thresholds of adjusted P < 0.05 and |Fold change| > 1.5. Using LASSO and multivariate Cox regression analyses, we identified 10 ARGs that we used to build a prognostic signature with areas under the curve (AUCs) of 0.705, 0.715, and 0.778 at 1, 3, and 5 years, respectively. Using the risk score formula, the LUAD patients were divided into low- or high-risk groups. Our GSEA results suggested that the low-risk group were enriched in metabolism and immune-related pathways, while the high-risk group was involved in tumorigenesis and tumor progression pathways. Immune cell analysis revealed that, when compared to the high-risk group, the low-risk group had a lower cell fraction of M0- and M1- macrophages, and higher CD4 and PD-L1 expression levels. Conclusion Our identified robust signature may provide novel insight into underlying autophagy mechanisms as well as therapeutic strategies for LUAD treatment.

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