A Four−Gene-Based Risk Score With High Prognostic Value in Gastric Cancer

Zhang, Bingdong; Li, Yuerui; Liu, Yang; Chen, Yongbing

doi:10.3389/fonc.2021.584213

Cited by 8 publications

(7 citation statements)

References 32 publications

(32 reference statements)

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“…More than half of the patients cannot survive for more than 5 years owing to the heterogeneity of AML despite the development of AML risk stratification ( 7 ). AML prognostic stratification needs to be more precise so that as many patients as possible receive the treatment that is most appropriate for them ( 8 ). This study demonstrated that the risk stratification based on the eight-gene risk scoring system was consistent with the NCCN guidelines.…”

Section: Discussionmentioning

confidence: 99%

A novel scoring system for the quantitative prediction of prognosis in acute myeloid leukemia

Wang

Yang

et al. 2023

Front. Oncol.

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BackgroundAcute myeloid leukemia (AML) is a heterogeneous hematopoietic malignancy. Patient prognosis cannot be accurately assessed in National Comprehensive Cancer Network (NCCN) risk stratification subgroups based on the current criteria. This study aimed to develop a novel prognostic score model for the quantitative prediction of prognosis in AML.ResultsWe developed a prognostic risk scoring model of AML using differentially expressed genes to predict prognosis in patients with AML. Furthermore, we evaluated the effectiveness and clinical significance of this prognostic model in 4 AML cohorts and 905 patients with AML. A prognostic risk scoring model of AML containing eight prognosis-related genes was constructed using a multivariate Cox regression model. The model had a higher predictive value for the prognosis of AML in the training and validation sets. In addition, patients with lower scores had significantly better overall survival (OS) and even-free survival (EFS) than those with higher scores among patients with intermediate-risk AML according to the NCCN guidelines, indicating that the model could be used to further predict the prognosis of the intermediate-risk AML populations. Similarly, patients with high scores had remarkably poor OS and EFS in the normal-karyotype populations, indicating that the scoring model had an excellent predictive performance for patients with AML having normal karyotype.ConclusionsOur study provided an individualized prognostic risk score model that could predict the prognosis of patients with AML.

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Section: Discussionmentioning

confidence: 99%

A novel scoring system for the quantitative prediction of prognosis in acute myeloid leukemia

Wang

Yang

et al. 2023

Front. Oncol.

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“…In the case of SORCS3, it has been detected its methylation (53) and this epigenetic modification has been associated with the progression of gastric precancerous lesions (54). In the case of CCDC178, an study that performed whole genome sequencing in samples from a GC patient, identified in the primary GC tumor a somatic nonsynonymous single nucleotide variation affecting CCDC178 (55), and another study identified in GC mutations (mainly missense mutations and frame shift deletions) in CCDC178 that were significantly associated with poor survival (56).…”

Section: Discussionmentioning

confidence: 99%

Identification of a novel gene signature related to prognosis and metastasis in gastric cancer

Matheu,

Elizazu,

Otaegi-Ugartemendia

et al. 2023

Preprint

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Background: Gastric Cancer (GC) presents poor outcome, which is consequence of the high incidence of recurrence and metastasis at early stages. GC patients presenting recurrent or metastatic disease display a median life expectancy of only 8 months. The mechanisms underlying GC progression remain poorly understood. Methods: We took advantage of public available GC datasets from TCGA using GEPIA, and identified the matched genes among the 100 genes most significantly associated with overall survival (OS) and disease free survival (DFS). Results were confirmed in ACRG cohort and in over 2,000 GC cases obtained from several cohorts integrated using our own analysis pipeline. The Kaplan-Meier method and multivariate Cox regression analyses were used for prognostic significance and linear modelling and correlation analyses for association with clinic-pathological parameters and biological hallmarks. In vitro and in vivo functional studies were performed in GC cells with candidate genes and the related molecular pathways were studied by RNA sequencing. Results: High expression of ANKRD6, ITIH3, SORCS3, NPY1R and CCDC178 individually and as a signature was associated with poor prognosis and recurrent disease in GC. Among the 5 genes, ANKRD6, ITIH3 and NPY1R represented independent prognostic factors determined through multivariate Cox regression analyses. Moreover, the expression of ANKRD6 and ITIH3 was significantly higher in metastasis and its levels associated to EMT and stemness markers. Moreover, ANKRD6 silencing in GC metastatic cells showed impairment in GC tumorigenic activity and EMT in functional studies in vivo and in molecular pathways in transcriptomic studies. Conclusions: Our study identified a novel signature involved in GC malignancy and prognosis, and revealed a novel pro-metastatic role of ANKRD6 in GC.

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“…In the process of gene signature establishment, besides univariate Cox regression analysis, a random survival forest algorithm was also applied for gene selection [ 33 ]; common angiogenesis-related genes selected by both approaches were further put into multivariate Cox regression analysis to develop ARS. In contrast with other clinicopathological factors, higher ARS consistently indicated poor prognosis of PCa patients, and it also has a promising ability in BCR prediction.…”

Section: Discussionmentioning

confidence: 99%

A Novel Angiogenesis-Related Gene Signature to Predict Biochemical Recurrence of Patients with Prostate Cancer following Radical Therapy

Fan

Wang

Zheng

et al. 2022

Journal of Oncology

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Background. Prostate cancer (PCa) is one of the most common malignancies in males; we aim to establish a novel angiogenesis-related gene signature for biochemical recurrence (BCR) prediction in PCa patients following radical therapy. Methods. Gene expression profiles and corresponding clinicopathological data were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We quantified the levels of various cancer hallmarks and identified angiogenesis as the primary risk factor for BCR. Then machine learning methods combined with Cox regression analysis were used to screen prognostic genes and construct an angiogenesis-related gene signature, which was further verified in external cohorts. Furthermore, estimation of immune cell abundance and prediction of drug responses were also conducted to detect potential mechanisms. Results. Angiogenesis was regarded as the leading risk factor for BCR in PCa patients (HR = 1.58, 95% CI: 1.38–1.81), and a novel prognostic signature based on three genes (NRP1, JAG2, and VCAN) was developed in the training cohort and successfully validated in another three independent cohorts. In all datasets, this signature was identified as a prognostic factor with promising and robust predictive values. Moreover, it also predicted higher infiltration of regulatory T cells and M2-polarized macrophages and increased drug sensitivity of angiogenesis inhibitors in high-risk patients. Conclusions. The angiogenesis-related three-gene signature may serve as an independent prognostic factor for BCR, which would contribute to risk stratification and personalized management of PCa patients after radical therapy in clinical practice.

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A Four−Gene-Based Risk Score With High Prognostic Value in Gastric Cancer

Cited by 8 publications

References 32 publications

A novel scoring system for the quantitative prediction of prognosis in acute myeloid leukemia

A novel scoring system for the quantitative prediction of prognosis in acute myeloid leukemia

Identification of a novel gene signature related to prognosis and metastasis in gastric cancer

A Novel Angiogenesis-Related Gene Signature to Predict Biochemical Recurrence of Patients with Prostate Cancer following Radical Therapy

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