scholarly journals Development and Clinical Validation of Novel 8-Gene Prognostic Signature Associated With the Proportion of Regulatory T Cells by Weighted Gene Co-Expression Network Analysis in Uterine Corpus Endometrial Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jinhui Liu ◽  
Rui Geng ◽  
Sheng Yang ◽  
Fang Shao ◽  
Zihang Zhong ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Network Analysis ◽  
Endometrial Carcinoma ◽  
Risk Score ◽  
Immune Status ◽  
Low Risk ◽  
Prognostic Signature ◽  
Uterine Corpus ◽  
Risk Patients

BackgroundUterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with low survival rate and poor prognosis. The traditional clinicopathological staging is insufficient to estimate the prognosis of UCEC. It is necessary to select a more effective prognostic signature of UCEC to predict the prognosis and immunotherapy effect of UCEC.MethodsCIBERSORT and weighted correlation network analysis (WGCNA) algorithms were combined to screen modules related to regulatory T (Treg) cells. Subsequently, univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the genes in key modules. The difference in overall survival (OS) between high- and low-risk patients was analyzed by Kaplan–Meier analysis. The Tregs-related risk signature (TRRS) was screened by uni- and multivariate Cox analyses. Afterward, we analyzed the expression difference of TRRS and verified its ability to predict the prognosis of UCEC and the effect of immunotherapy.ResultsRed module has the highest correlation with Tregs among all clustered modules. Pathways enrichment indicated that the related processes of UCEC were primarily associated to the immune system. Eight genes (ZSWIM1, NPRL3, GOLGA7, ST6GALNAC4, CDC16, ITPK1, PCSK4, and CORO1B) were selected to construct TRRS. We found that this TRRS is a significantly independent prognostic factor of UCEC. Low-risk patients have higher overall survival than high-risk patients. The immune status of different groups was different, and tumor-related pathways were enriched in patients with higher risk score. Low-risk patients are more likely take higher tumor mutation burden (TMB). Meanwhile, they are more sensitive to chemotherapy than patients with high-risk score, which indicated a superior prognosis. Immune checkpoints such as PD-1, CTLA4, PD-L1, and PD-L2 all had a higher expression level in low-risk group. TRRS expression really has a relevance with the sensitivity of UCEC patients to chemotherapeutic drugs.ConclusionWe developed and validated a TRRS to estimate the prognosis and reflect the immune status of UCEC, which could accurately assess the prognosis of patients with UCEC and supply personalized treatments for them.

scholarly journals A Novel Four-Gene Signature Associated With Immune Checkpoint for Predicting Prognosis in Lower-Grade Glioma

2020 ◽  
Vol 10 ◽  
Author(s):  
Youchao Xiao ◽  
Gang Cui ◽  
Xingguang Ren ◽  
Jiaqi Hao ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Risk Groups ◽  
Gene Signature ◽  
Low Risk ◽  
Lower Grade ◽  
Lower Grade Glioma ◽  
Risk Patients

The overall survival of patients with lower grade glioma (LGG) varies greatly, but the current histopathological classification has limitations in predicting patients’ prognosis. Therefore, this study aims to find potential therapeutic target genes and establish a gene signature for predicting the prognosis of LGG. CD44 is a marker of tumor stem cells and has prognostic value in various tumors, but its role in LGG is unclear. By analyzing three glioma datasets from Gene Expression Omnibus (GEO) database, CD44 was upregulated in LGG. We screened 10 CD44-related genes via protein–protein interaction (PPI) network; function enrichment analysis demonstrated that these genes were associated with biological processes and signaling pathways of the tumor; survival analysis showed that four genes (CD44, HYAL2, SPP1, MMP2) were associated with the overall survival (OS) and disease-free survival (DFS)of LGG; a novel four-gene signature was constructed. The prediction model showed good predictive value over 2-, 5-, 8-, and 10-year survival probability in both the development and validation sets. The risk score effectively divided patients into high- and low- risk groups with a distinct outcome. Multivariate analysis confirmed that the risk score and status of IDH were independent prognostic predictors of LGG. Among three LGG subgroups based on the presence of molecular parameters, IDH-mutant gliomas have a favorable OS, especially if combined with 1p/19q codeletion, which further confirmed the distinct biological pattern between three LGG subgroups, and the gene signature is able to divide LGG patients with the same IDH status into high- and low- risk groups. The high-risk group possessed a higher expression of immune checkpoints and was related to the activation of immunosuppressive pathways. Finally, this study provided a convenient tool for predicting patient survival. In summary, the four prognostic genes may be therapeutic targets and prognostic predictors for LGG; this four-gene signature has good prognostic prediction ability and can effectively distinguish high- and low-risk patients. High-risk patients are associated with higher immune checkpoint expression and activation of the immunosuppressive pathway, providing help for screening immunotherapy-sensitive patients.

scholarly journals A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Yan ◽  
Wenjiang Zheng ◽  
Boqing Wang ◽  
Baoqian Ye ◽  
Huiyan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Performance ◽  
Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

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 A Novel Autophagy-Related lncRNA Gene Signature to Improve the Prognosis of Patients with Melanoma

2020 ◽  
Author(s):  
Yi Ding ◽  
Tian Li ◽  
Min Li ◽  
Tuersong Tayier ◽  
MeiLin Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Risk Model ◽  
Risk Group ◽  
Clinical Information ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Positive Regulation ◽  
Risk Patients ◽  
Cox Analysis

Abstract Background: Autophagy and long non-coding RNAs (lncRNAs) have been the focus of research on the pathogenesis of melanoma. However, the autophagy network of lncRNAs in melanoma has not been reported. The purpose of this study was to investigate the lncRNA prognostic markers related to melanoma autophagy and predict the prognosis of patients with melanoma.Methods: We downloaded RNA-sequencing data and clinical information of melanoma from The Cancer Genome Atlas. The co-expression of autophagy-related genes (ARGs) and lncRNAs was analyzed. The risk model of autophagy-related lncRNAs was established by univariate and multivariate COX regression analyses, and the best prognostic index was evaluated combined with clinical data. Finally, gene set enrichment analysis was performed on patients in the high- and low-risk groups.Results: According to the results of the univariate COX analysis, only the overexpression of LINC00520 was associated with poor overall survival, unlike HLA-DQB1-AS1, USP30-AS1, AL645929, AL365361, LINC00324, and AC055822. The results of the multivariate COX analysis showed that the overall survival of patients in the high-risk group was shorter than that recorded in the low-risk group (p<0.001). Moreover, in the receiver operating characteristic curve of the risk model we constructed, the area under the curve (AUC) was 0.734, while the AUC of T and N was 0.707 and 0.658, respectively. The Gene Ontology was mainly enriched with the positive regulation of autophagy and the activation of the immune system. The results of the Kyoto Encyclopedia of Genes and Genomes enrichment were mostly related to autophagy, immunity, and melanin metabolism.Conclusion: The positive regulation of autophagy may slow the transition from low-risk patients to high-risk patients in melanoma. Furthermore, compared with clinical information, the autophagy-related lncRNAs risk model may better predict the prognosis of patients with melanoma and provide new treatment ideas.

scholarly journals Expression ofFOXP3,CD14, andARG1in Neuroblastoma Tumor Tissue from High-Risk Patients Predicts Event-Free and Overall Survival

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Sara Stigliani ◽  
Michela Croce ◽  
Fabio Morandi ◽  
Paola Scaruffi ◽  
Valentina Rigo ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Immune Status ◽  
Primary Tumors ◽  
Neuroblastoma Tumor ◽  
Elevated Expression ◽  
Risk Patients ◽  
History Of ◽  
Low Levels ◽  
Positive Correlations

The prognosis of children with metastatic neuroblastoma (NB) > 18 months at diagnosis is dismal. Since the immune status of the tumor microenvironment could play a role in the history of disease, we evaluated the expression ofCD45,CD14,ARG1,CD163,CD4,FOXP3,Perforin-1(PRF1),Granzyme B (GRMB), andIL-10mRNAs in primary tumors at diagnosis from children with metastatic NB and tested whether the transcript levels are significantly associated to event-free and overall survival (EFS and OS, resp.). Children with high expression ofCD14,ARG1andFOXP3mRNA in their primary tumors had significantly better EFS. Elevated expression ofCD14, andFOXP3mRNA was significantly associated to better OS.CD14mRNA expression levels significantly correlated to all markers, with the exception ofCD4. Strong positive correlations were found betweenPRF1andCD163, as well as betweenPFR1andFOXP3. It is worth noting that the combination of high levels ofCD14,FOXP3, andARG1mRNAs identified a small group of patients with excellent EFS and OS, whereas low levels ofCD14were sufficient to identify patients with dismal survival. Thus, the immune status of the primary tumors of high-risk NB patients may influence the natural history of this pediatric cancer.

Multicentre validation of the Geneva Risk Score for hospitalised medical patients at risk of venous thromboembolism

2014 ◽  
Vol 111 (03) ◽  
pp. 531-538 ◽  
Author(s):  
Drahomir Aujesky ◽  
Daniel Hayoz ◽  
Jürg Beer ◽  
Marc Husmann ◽  
Beat Frauchiger ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
High Risk ◽  
Risk Score ◽  
Primary Endpoint ◽  
Low Risk ◽  
Prediction Score ◽  
Medical Patients ◽  
Cumulative Rate ◽  
Patients At Risk ◽  
Risk Patients

SummaryThere is a need to validate risk assessment tools for hospitalised medical patients at risk of venous thromboembolism (VTE). We investigated whether a predefined cut-off of the Geneva Risk Score, as compared to the Padua Prediction Score, accurately distinguishes low-risk from high-risk patients regardless of the use of thromboprophylaxis. In the multicentre, prospective Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE) cohort study, 1,478 hospitalised medical patients were enrolled of whom 637 (43%) did not receive thromboprophylaxis. The primary endpoint was symptomatic VTE or VTE-related death at 90 days. The study is registered at ClinicalTrials.gov, number NCT01277536. According to the Geneva Risk Score, the cumulative rate of the primary endpoint was 3.2% (95% confidence interval [CI] 2.2–4.6%) in 962 high-risk vs 0.6% (95% CI 0.2–1.9%) in 516 low-risk patients (p=0.002); among patients without prophylaxis, this rate was 3.5% vs 0.8% (p=0.029), respectively. In comparison, the Padua Prediction Score yielded a cumulative rate of the primary endpoint of 3.5% (95% CI 2.3–5.3%) in 714 high-risk vs 1.1% (95% CI 0.6–2.3%) in 764 lowrisk patients (p=0.002); among patients without prophylaxis, this rate was 3.2% vs 1.5% (p=0.130), respectively. Negative likelihood ratio was 0.28 (95% CI 0.10–0.83) for the Geneva Risk Score and 0.51 (95% CI 0.28–0.93) for the Padua Prediction Score. In conclusion, among hospitalised medical patients, the Geneva Risk Score predicted VTE and VTE-related mortality and compared favourably with the Padua Prediction Score, particularly for its accuracy to identify low-risk patients who do not require thromboprophylaxis.

Predictors of thromboprophylaxis in hospitalised medical patients

2015 ◽  
Vol 113 (05) ◽  
pp. 1127-1134 ◽  
Author(s):  
David Spirk ◽  
Mathieu Nendaz ◽  
Drahomir Aujesky ◽  
Daniel Hayoz ◽  
Jürg H. Beer ◽  
...  
Keyword(s):  
Cohort Study ◽  
Venous Thromboembolism ◽  
High Risk ◽  
Risk Score ◽  
Low Risk ◽  
Medical Patients ◽  
Clinical Factors ◽  
Thromboembolic Risk ◽  
Factors Associated ◽  
Risk Patients

summaryBoth, underuse and overuse of thromboprophylaxis in hospitalised medical patients is common. We aimed to explore clinical factors associated with the use of pharmacological or mechanical thromboprophylaxis in acutely ill medical patients at high (Geneva Risk Score ≥ 3 points) vs low (Geneva Risk Score < 3 points) risk of venous thromboembolism. Overall, 1,478 hospitalised medical patients from eight large Swiss hospitals were enrolled in the prospective Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE) cohort study. The study is registered on ClinicalTrials. gov, number NCT01277536. Thromboprophylaxis increased stepwise with increasing Geneva Risk Score (p< 0.001). Among the 962 high-risk patients, 366 (38 %) received no thromboprophylaxis; cancer-associated thrombocytopenia (OR 4.78, 95 % CI 2.75–8.31, p< 0.001), active bleeding on admission (OR 2.88, 95 % CI 1.69–4.92, p< 0.001), and thrombocytopenia without cancer (OR 2.54, 95 % CI 1.31–4.95, p=0.006) were independently associated with the absence of prophylaxis. The use of thromboprophylaxis declined with increasing severity of thrombocytopenia (p=0.001). Among the 516 low-risk patients, 245 (48 %) received thromboprophylaxis; none of the investigated clinical factors predicted its use. In conclusion, in acutely ill medical patients, bleeding and thrombocytopenia were the most important factors for the absence of thromboprophylaxis among highrisk patients. The use of thromboprophylaxis among low-risk patients was inconsistent, without clearly identifiable predictors, and should be addressed in further research.

scholarly journals The Landscape of Glycosyltransferase Gene Signature for Overall Survival Prediction in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Qiang Cai ◽  
Shizhe Yu ◽  
Jian Zhao ◽  
Duo Ma ◽  
Long Jiang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Risk Score ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Groups ◽  
Gene Signature ◽  
Low Risk ◽  
Regression Analyses ◽  
Risk Patients

Abstract Background: Hepatocellular carcinoma (HCC) is heterogeneous disease occurring in the background of chronic liver diseases. The role of glycosyltransferase (GT) genes have recently been the focus of research associating with the development of tumors. However, the prognostic value of GT genes in HCC remains not elucidated. This study aimed to demonstrate the GT genes related to the prognosis of HCC through bioinformatics analysis.Methods: The GT genes signatures were identified from the training set of The Cancer Genome Atlas (TCGA) dataset using univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Then, we analyzed the prognostic value of GT genes signatures related to the overall survival (OS) of HCC patients. A prognostic model was constructed, and the risk score of each patient was calculated as formula, which divided HCC patients into high- and low-risk groups. Kaplan-Meier (K-M) and Receiver operating characteristic (ROC) curves were used to assess the OS of HCC patients. The prognostic value of GT genes signatures was further investigated in the validation set of TCGA database. Univariate and multivariate Cox regression analyses were performed to demonstrate the independent factors on OS. Finally, we utilized the gene set enrichment analysis (GSEA) to annotate the function of these genes between the two risk categories. Results: In this study, we identified and validated 4 GT genes as the prognostic signatures. The K-M analysis showed that the survival rate of the high-risk patients was significantly lower than that of the low-risk patients. The risk score calculated with 4 gene signatures could predict OS for 3-, 5-, and 7-year in patients with HCC, revealing the prognostic ability of these gene signature. In addition, Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for HCC. Functional analysis further revealed that immune-related pathways were enriched, and immune status in HCC were different between the two risk groups.Conclusion: In conclusion, a novel GT genes signature can be used for prognostic prediction in HCC. Thus, targeting GT genes may be a therapeutic alternative for HCC.

scholarly journals Prognostic value of an autophagy-related gene expression signature for endometrial cancer patients

2020 ◽  
Author(s):  
Hui Wang ◽  
Xiaoling Ma ◽  
Jinhui Liu ◽  
Yicong Wan ◽  
Yi Jiang ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
High Risk ◽  
Risk Score ◽  
Risk Group ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Gene Set Enrichment ◽  
Test Set ◽  
Gene Set

Abstract Background: Autophagy is associated with cancer development. Autophagy-related genes play significant roles in endometrial cancer (EC), a major gynecological malignancy worldwide, but little was known about their value as prognostic markers. Here we evaluated the value of a prognostic signature based on autophagy-related genes for EC.Methods: First, various autophagy-related genes were obtained via the Human Autophagy Database and their expression profiles were downloaded from The Cancer Genome Atlas. Second, key prognostic autophagy-related genes were identified via univariat, LASSO, and multivariate Cox regression analyses. Finally, a risk score to predict the prognosis of EC was calculated and validated by using the test and the entire data sets. Besides, gene set enrichment and somatic mutation analyses were also used for these prognostic autophagy-related genes. Results: A total of 40 differentially expressed autophagy-related genes in EC were screened and five of them were prognosis-related (CDKN1B, DLC1, EIF4EBP1, ERBB2 and GRID1). A prognostic signature was constructed based on these five genes using the train set, which stratified EC patients into high-risk and low-risk groups (P<0.05). In terms of overall survival, the analyses of the test set and the entire set yielded consistent results (test set: p < 0.05; entire set: p < 0.05). Time-dependent ROC analysis suggested that the risk score predicted EC prognosis accurately and independently (0.674 at 1 year, 0.712 at 3 years and 0.659 at 5 years). A nomogram with clinical utility was built. Patients in the high-risk group displayed distinct mutation signatures compared with those in the low-risk group. Gene set enrichment analysis revealed high risk score was associated with tumor initiation and progression associated pathways.Conclusions: Based on five autophagy-related genes (CDKN1B, DLC1, EIF4EBP1, ERBB2 and GRID1), our model can independently predict the OS of EC patients by combining molecular signature and clinical characteristics.

scholarly journals Construction and Validation of a Universal Applicable Prognostic Signature for Gastric Cancer Based on Seven Immune-Related Gene Correlated With Tumor Associated Macrophages

2021 ◽  
Vol 11 ◽  
Author(s):  
Junyu Huo ◽  
Liqun Wu ◽  
Yunjin Zang
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Risk Score ◽  
Critical Role ◽  
External Validation ◽  
Low Risk ◽  
Prognostic Signature ◽  
Tumor Associated Macrophages ◽  
Cox Regression Analysis ◽  
Significant Difference

BackgroundTumor-associated macrophages (TAMs) play a critical role in the progression of malignant tumors, but the detailed mechanism of TAMs in gastric cancer (GC) is still not fully explored.MethodsWe identified differentially expressed immune-related genes (DEIRGs) between GC samples with high and low macrophage infiltration in The Cancer Genome Atlas datasets. A risk score was constructed based on univariate Cox analysis and Lasso penalized Cox regression analysis in the TCGA cohort (n=341). The optimal cutoff determined by the 5-year time-dependent receiver operating characteristic (ROC) curve was considered to classify patients into groups with high and low risk. We conducted external validation of the prognostic signature in four independent cohorts (GSE84437, n=431; GSE62254, n=300; GSE15459, n=191; and GSE26901, n=109) from the Gene Expression Omnibus (GEO) database.ResultsThe signature consisting of 7 genes (FGF1, GRP, AVPR1A, APOD, PDGFRL, CXCR4, and CSF1R) showed good performance in predicting overall survival (OS) in the 5 independent cohorts. The risk score presented an obviously positive correlation with macrophage abundance (cor=0.7, p&lt;0.001). A significant difference was found between the high- and low-risk groups regarding the overall survival of GC patients. The high-risk group exhibited a higher infiltration level of M2 macrophages estimated by the CIBERSORT algorithm. In the five independent cohorts, the risk score was highly positively correlated with the stromal cell score, suggesting that we can also evaluate the infiltration of stromal cells in the tumor microenvironment according to the risk score.ConclusionOur study developed and validated a general applicable prognostic model for GC from the perspective of TAMs, which may help to improve the precise treatment strategy of GC.

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