scholarly journals Relating the gut metagenome and metatranscriptome to immunotherapy responses in melanoma patients

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Brandilyn A. Peters ◽  
Melissa Wilson ◽  
Una Moran ◽  
Anna Pavlick ◽  
Allison Izsak ◽  
...  
Keyword(s):  
Microbial Community ◽  
Gut Microbiota ◽  
Cox Regression ◽  
Risk Group ◽  
Progression Free Survival ◽  
High Risk Group ◽  
Rrna Gene ◽  
Nucleotide Biosynthesis ◽  
Microbiome Composition ◽  
Melanoma Patients

Abstract Background Recent evidence suggests that immunotherapy efficacy in melanoma is modulated by gut microbiota. Few studies have examined this phenomenon in humans, and none have incorporated metatranscriptomics, important for determining expression of metagenomic functions in the microbial community. Methods In melanoma patients undergoing immunotherapy, gut microbiome was characterized in pre-treatment stool using 16S rRNA gene and shotgun metagenome sequencing (n = 27). Transcriptional expression of metagenomic pathways was confirmed with metatranscriptome sequencing in a subset of 17. We examined associations of taxa and metagenomic pathways with progression-free survival (PFS) using 500 × 10-fold cross-validated elastic-net penalized Cox regression. Results Higher microbial community richness was associated with longer PFS in 16S and shotgun data (p < 0.05). Clustering based on overall microbiome composition divided patients into three groups with differing PFS; the low-risk group had 99% lower risk of progression than the high-risk group at any time during follow-up (p = 0.002). Among the species selected in regression, abundance of Bacteroides ovatus, Bacteroides dorei, Bacteroides massiliensis, Ruminococcus gnavus, and Blautia producta were related to shorter PFS, and Faecalibacterium prausnitzii, Coprococcus eutactus, Prevotella stercorea, Streptococcus sanguinis, Streptococcus anginosus, and Lachnospiraceae bacterium 3 1 46FAA to longer PFS. Metagenomic functions related to PFS that had correlated metatranscriptomic expression included risk-associated pathways of l-rhamnose degradation, guanosine nucleotide biosynthesis, and B vitamin biosynthesis. Conclusions This work adds to the growing evidence that gut microbiota are related to immunotherapy outcomes, and identifies, for the first time, transcriptionally expressed metagenomic pathways related to PFS. Further research is warranted on microbial therapeutic targets to improve immunotherapy outcomes.

scholarly journals SOX1 and PAX1 Are Hypermethylated in Cervical Adenocarcinoma and Associated with Better Prognosis

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Zitong Zhao ◽  
Xiaoye Zhang ◽  
Xueheng Zhao ◽  
Jingting Cai ◽  
Na-Yi Yuan Wu ◽  
...  
Keyword(s):  
Cox Regression ◽  
Risk Group ◽  
Methylation Status ◽  
Progression Free Survival ◽  
High Risk Group ◽  
Cervical Adenocarcinoma ◽  
Survival Prediction ◽  
Kaplan Meier ◽  
Increased Risk ◽  
Poor Survival Outcome

Background. The increased risk and poor survival outcome of cervical adenocarcinoma (CAC) demand for effective early diagnostic biomarkers that can predict the disease progression and outcome. The purpose of this study was to investigate the value of methylation status of SOX1 and PAX1 in the detection and prognosis of CAC. Methods. We performed a quantitative methylation-specific polymerase chain reaction in 205 cervical paraffin-embedded specimens (175 CACs, 30 noncancer cervical tissues). Overall and progression-free survival (OS and PFS, respectively) rates were calculated and compared using the Kaplan-Meier method. The prognostic value of SOX1m and PAX1m on CAC patients was assessed by the Cox regression model. A mathematical formula combining SOX1m, PAX1m, and age was constructed for survival prediction. Results. The methylation status of SOX1 and PAX1 was higher in CAC tissues than in noncancer cervical tissues. In addition, SOX1m-positive CAC patients showed a higher 5-year OS rate than SOX1m-negative patients. In CAC patients with smaller tumor size (<4 cm), the PAX1m-positive group showed a higher 5-year PFS rate than the PAX1m-negative group. In the algorithm combining SOX1m, PAX1m, and age, the low-risk group showed a better 5-year OS and PFS rate than the high-risk group. Conclusion. SOX1 and PAX1 methylation levels are higher in CAC than in normal cervical tissues and are potential biomarkers for monitoring CAC prognosis.

scholarly journals A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dongdong Zhou ◽  
Xiaoli Liu ◽  
Xinhui Wang ◽  
Fengna Yan ◽  
Peng Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Surgical Therapy ◽  
Calibration Curve ◽  
Cox Regression ◽  
Validation Cohort ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Alpha Fetoprotein ◽  
Clinicopathologic Characteristics

Abstract Background Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC. Methods A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort. Results The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively. Conclusions Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

A Hypoxia-related LncRNA Signature Predicts Survival of Primary Lower-grade glioma

2021 ◽  
Author(s):  
Yanjia Hu ◽  
Jing Zhang ◽  
Jing Chen
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Prognostic Signature ◽  
Gene Set Enrichment

Abstract Background Hypoxia-related long non-coding RNAs (lncRNAs) have been proven to play a role in multiple cancers and can serve as prognostic markers. Lower-grade gliomas (LGGs) are characterized by large heterogeneity. Methods This study aimed to construct a hypoxia-related lncRNA signature for predicting the prognosis of LGG patients. Transcriptome and clinical data of LGG patients were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). LGG cohort in TCGA was chosen as training set and LGG cohorts in CGGA served as validation sets. A prognostic signature consisting of fourteen hypoxia-related lncRNAs was constructed using univariate and LASSO Cox regression. A risk score formula involving the fourteen lncRNAs was developed to calculate the risk score and patients were classified into high- and low-risk groups based on cutoff. Kaplan-Meier survival analysis was used to compare the survival between two groups. Cox regression analysis was used to determine whether risk score was an independent prognostic factor. A nomogram was then constructed based on independent prognostic factors and assessed by C-index and calibration plot. Gene set enrichment analysis and immune cell infiltration analysis were performed to uncover further mechanisms of this lncRNA signature. Results LGG patients with high risk had poorer prognosis than those with low risk in both training and validation sets. Recipient operating characteristic curves showed good performance of the prognostic signature. Univariate and multivariate Cox regression confirmed that the established lncRNA signature was an independent prognostic factor. C-index and calibration plots showed good predictive performance of nomogram. Gene set enrichment analysis showed that genes in the high-risk group were enriched in apoptosis, cell adhesion, pathways in cancer, hypoxia etc. Immune cells were higher in high-risk group. Conclusion The present study showed the value of the 14-lncRNA signature in predicting survival of LGGs and these 14 lncRNAs could be further investigated to reveal more mechanisms involved in gliomas.

scholarly journals Ferroptosis-Related Long Non-Coding RNAs and the Roles of LASTR in Stomach Adenocarcinoma

2021 ◽  
Author(s):  
Gongjun Wang ◽  
Libin Sun ◽  
Shasha Wang ◽  
Jing Guo ◽  
Hui Li ◽  
...  
Keyword(s):  
Cox Regression ◽  
Comprehensive Evaluation ◽  
Progression Free Survival ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Regulatory Relationship ◽  
Data Resource ◽  
Stomach Adenocarcinoma

Abstract Background: Ferroptosis is a form of cell death involved in diverse physiological context. Increasing evidence suggests that there is a closely regulatory relationship between ferroptosis and long noncoding RNAs (lncRNAs).Method: RNA-sequencing data from The Cancer Genome Atlas (TCGA) data resource and ferroptosis-related genes from FerrDb (http://www.zhounan.org/ferrdb/) data resource were employed to select differentially expressed lncRNAs. We performed Univariate Cox regression and multivariate Cox analyses analysis on these differentially expressed lncRNAs to screen independent predictive factors. Subsequently, we established two signatures for predicting overall survival (OS) and progression-free survival (PFS). Finally, experiments were conducted to verify the roles of LASTR in gastric cancer (GC).Results: We identified 12 differentially expressed lncRNAs linked with OS and 13 associated with PFS. Kaplan-Meier(K-M) analyses exhibited that the high-risk group was related to a poor prognosis of stomach adenocarcinoma (STAD). The AUCs of the OS, as well as PFS signatures of lncRNAs were 0.734 and 0.771, respectively, indicating their excellent efficacy in predicting STAD prognosis. Our experimental results illustrated that the inhibition of LASTR inhibited tumor proliferation and migration in GC.Conclusion: This comprehensive evaluation of the ferroptosis-related lncRNA landscape in STAD unearthed novel lncRNAs related to carcinogenesis. In addition, we also experimentally confirmed the effects of LASTR on proliferation, migration and ferroptosis. These results provide potential novel targets for tumor treatment and promote personalized medicine.

scholarly journals A Risk Signature of Nine Autophagy-Related Genes Associated With Immune Microenvironment and Clinical Prognosis in Wilms Tumor

2021 ◽  
Author(s):  
Shaopei Ye ◽  
Wenbin Tang ◽  
Ke Huang
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Wilms Tumor ◽  
Risk Group ◽  
High Risk Group ◽  
Differentially Expressed ◽  
Clinical Prognosis ◽  
Cox Regression Analysis

Abstract Background: Autophagy is a biological process to eliminate dysfunctional organelles, aggregates or even long-lived proteins. . Nevertheless, the potential function and prognostic values of autophagy in Wilms Tumor (WT) are complex and remain to be clarifed. Therefore, we proposed to systematically examine the roles of autophagy-associated genes (ARGs) in WT.Methods: Here, we obtained differentially expressed autophagy-related genes (ARGs) between healthy and Wilms tumor from Therapeutically Applicable Research To Generate Effective Treatments(TARGET) and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology. Then univariate COX regression analysis and multivariate COX regression analysis were performed to acquire nine autophagy genes related to WT patients’ survival. According to the risk score, the patients were divided into high-risk and low-risk groups. The Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis.Results: Eighteen DEARGs were identifed, and nine ARGs were fnally utilized to establish the FAGs based signature in the TCGA cohort. we found that patients in the high-risk group were associated with mutations in TP53. We further conducted CIBERSORT analysis, and found that the infiltration of Macrophage M1 was increased in the high-risk group. Finally, the expression levels of crucial ARGs were verifed by the experiment, which were consistent with our bioinformatics analysis.Conclusions: we emphasized the clinical significance of autophagy in WT, established a prediction system based on autophagy, and identified a promising therapeutic target of autophagy for WT.

scholarly journals Exploration of a Novel Prognostic Risk Signature and Its Effect on the Immune Response in Nasopharyngeal Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Shuang Zhao ◽  
Xin Dong ◽  
Xiaoguang Ni ◽  
Lin Li ◽  
Xin Lu ◽  
...  
Keyword(s):  
Immune Response ◽  
Nasopharyngeal Carcinoma ◽  
Risk Group ◽  
Progression Free Survival ◽  
Gene Signature ◽  
Metastatic Carcinoma ◽  
High Risk Group ◽  
Molecular Characteristics ◽  
Novel Gene ◽  
Kaplan Meier

Nasopharyngeal carcinoma (NPC) is a highly invasive and metastatic carcinoma with different molecular characteristics and clinical outcomes. In this work, we aimed to establish a novel gene signature that could predict the prognosis of NPC patients. A total of 13 significant genes between the recurrence/metastasis (RM) group and the no recurrence/metastasis (no-RM) group were identified by machine learning from RNA-Seq data including 60 NPC tumor biopsies. Based on these genes, a 4-mRNA signature (considering U2AF1L5, TMEM265, GLB1L and MLF1) was identified. Receiver operating characteristic (ROC) and Kaplan-Meier (K-M) analyses indicated that this signature had good prognostic value for NPC. The overall survival (OS) and progression-free survival (PFS) of the patients in the high-risk group were significantly shorter than those of the patients in the low-risk group (p = 0.00126 and p = 0.000059, respectively). The area under the ROC curve (AUC) values of the 4-mRNA signature were higher than those of T stage and N stage for OS (0.893 vs 0.619 and 0.582, respectively) and PFS (0.86 vs 0.538 and 0.622, respectively). Furthermore, the 4-mRNA signature was closely associated with cell proliferation and the immune response. The expression of GLB1L and TMEM265 was associated with the level of tumor-infiltrating immune cells (r &gt; 0.4, p &lt; 0.05). We have validated the model through measuring the expression levels of the 4-mRNA signature by qRT-PCR, in an independent cohort of NPC patients. Here, we report a novel gene signature that can serve as a new tool for predicting the prognosis of NPC patients.

scholarly journals Clinical and Biological Prognostic Factors in Follicular Lymphoma Patients During Treatment

2021 ◽  
Author(s):  
Ádám Jóna ◽  
Anna Kenyeres ◽  
Sándor Barna ◽  
Árpád Illés ◽  
Zsófia Simon
Keyword(s):  
Prognostic Factors ◽  
High Risk ◽  
Follicular Lymphoma ◽  
Risk Group ◽  
Standardized Uptake Value ◽  
Progression Free Survival ◽  
High Risk Group ◽  
Pet Ct ◽  
Significant Difference ◽  
Biological Prognostic Factors

Abstract Introduction: Follicular lymphoma (FL) is an indolent yet heterogeneous B-cell lymphoproliferative disorder. Most people respond to treatment well. However, a particular group of patients has a poor prognosis, and these patients are difficult to define.Patients and methods: We retrospectively analyzed FL patients treated at the University of Debrecen in the past 20 years. We investigated prognostic factors that may influence the survival of FL patients.Results: We found a standardized uptake value (SUV)max cut-off value of 9.85 at the staging PET/CT to significantly separate FL patients’ progression-free survival (PFS) (p=0.0003, HR: 0.2560, 95%CI: 0.1232-0.5318). Lymphocyte/ monocyte (Ly/Mo) ratio of 3.45 drawn at diagnosis also significantly predicted PFS (p=0.0324, HR: 1.806, 95% CI: 1.051-3.104). Combining patients’ with staging SUVmax >9.85 and Ly/Mo < 3.45 a high-risk group of FL patients can be identified (p<0.0001, HR: 0.1033, 95%CI: 0.03719-0.2868). Similarly, a significant difference was shown with a SUVmax cut-off of 3.15 at the interim PET/CT (p<0.0001, HR: 0.1535, 95%CI: 0.06329-0.3720). Combining patients with staging SUVmax >9.85 and interim SUVmax >3.15, a high-risk group of FL patients can be identified (p<0.0001, HR: 0.1037, 95%CI: 0.03811-0.2824). The PFS difference is translated into overall survival advantage (p=0.0506, HR: 0.1187, 95%CI: 0.01401-1.005).Discussion: Biological prognostic factors, such as the Ly/ Mo ratio, may improve the prognostic assessment of staging PET/CT. Nevertheless, PFS difference is translated into OS when using a combination of staging and interim SUVmax. We consider investigating additional biological prognostic factors while currently highlighting PET/CT's role in FL.

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

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.

The predictive value of MAP2K1/2 mutations for efficiency of immunotherapy in melanoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e21587-e21587
Author(s):  
Ting Ye ◽  
Jieying Zhang ◽  
Xinyi Liu ◽  
Mengmei Yang ◽  
Yuhan Zhou ◽  
...  
Keyword(s):  
Overall Survival ◽  
Predictive Value ◽  
Cox Regression ◽  
Treatment Options ◽  
Objective Response ◽  
Progression Free Survival ◽  
Driver Mutations ◽  
Cox Regression Analysis ◽  
Melanoma Patients ◽  
The Impact

e21587 Background: Immunotherapies targeting immune checkpoint receptors have become the cornerstone of systemic treatment options for malignant melanoma. The response to these immunotherapies may correlate with driver mutations. MAP2K1/2 genes are mutated in approximately 10% of melanomas, however, the impact of MAP2K1/2 gene alterations on the efficiency of immunotherapy has not been clarified. Methods: Six metastatic melanoma clinical cohorts treated with ICIs were included to investigate the association between clinical efficacy of immunotherapy and MAP2K1/2 mutations. Survival analyses were conducted in cohorts receiving two kinds of ICB agents, namely anti-CTLA-4 or anti-PD-1. RNA expression profiling from these cohorts and from the TCGA melanoma cohort were used to explore the potential mechanism related to immune activation. Results: In an independent anti-CTLA-4-treated cohort (n = 110), we found that MAP2K1/2 mutations are predictive of high objective response rate (17.6% vs 1.3%, p = 0.0185) and long progression-free survival [median OS, 49.2 months vs 8.3 months; hazard ratio (HR) = 0.37; 95% CI, 0.15–0.91; p = 0.0307] and overall survival (median PFS, 19.4 months vs 2.8 months; HR = 0.2; 95% CI, 0.05–0.83; p = 0.0262). This predictive value was further validated in a pooled anti-CTLA-4-treated cohort (n = 235) in terms of overall survival (median OS, 49.3 months vs 22.0 months; HR = 0.44; 95% CI, 0.22–0.91; p = 0.0255). However, no correlation between MAP2K1/2 mutations and overall survival was observed in the anti-PD-1-treated cohort (n = 285). Subgroup Cox regression analysis indicated that MAP2K-mutated patients receive less benefit from the anti-PD-1 monotherapy than from the anti-CTLA-4 treatment (median OS, 27.0 months vs 49.3 months; HR = 3.26; 95% CI, 1.18–9.02; p = 0.0225), which was contrary to the result obtained for the total population. Furthermore, transcriptome profiling analysis revealed that MAP2K-mutated tumors are enriched in CD8+ T cells, B cells, and neutrophil cells and also express high levels of CD33 and IL10, which might be the underlying mechanism for melanoma patients with MAP2K1/2-mutated benefit more from anti-CTLA-4 treatment. Conclusions: We identified mutations in MAP2K1/2 genes as the independent predictive factors for anti-CTLA-4 therapy in melanoma patients and found that anti-CTLA-4 treatment in patient harbouring MAP2K1/2 mutations might be more effective than the anti-PD-1 therapy.

A prognostic nomogram in AFP-negative hepatocellular carcinoma based on LASSO Cox regression

2020 ◽  
Author(s):  
Dong dong Zhou ◽  
Xiao li Liu ◽  
Xin hui Wang ◽  
Feng na Yan ◽  
Peng Wang ◽  
...  
Keyword(s):  
Calibration Curve ◽  
Cox Regression ◽  
Validation Cohort ◽  
Risk Group ◽  
Hazard Analysis ◽  
Risk Groups ◽  
High Risk Group ◽  
Clinicopathologic Characteristics ◽  
Actual Observation ◽  
Prognostic Prediction

Abstract PurposeHepatocellular carcinoma (HCC) patients with alpha-fetoprotein (AFP)-negative (<8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of HCC patients with AFP-negative.Materials and MethodsA total of 410 AFP-negative patients with clinical diagnosed with HCC as a primary cohort; 148 AFP-negative HCC patients as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by univariate and multivariate Cox hazard analysis were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort.ResultsThe C-index of nomogram1was 0.708 (95%CI: 0.673-0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606-0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690-0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691-0.813; AUC: 0.784, 95%CI: 0.709-0.847) and good calibration. The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively.ConclusionsNovel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-negative HCC. This model could help AFP-negative HCC facilitate a personalized prognostic evaluation.

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