Screening and identification of CNIH4 gene associated with cell proliferation in gastric cancer based on a large-scale CRISPR-Cas9 screening database DepMap

Zhang, Hui; Yu, Lin; Zhuang, Minxue; Zhu, Lin; Dai, Yongmei; Lin, Mengbo

doi:10.1016/j.gene.2022.146961

Cited by 7 publications

(11 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A relevant study confirmed that CNIH4 increased the metastatic activity in patients with colon cancer by forming a positive feedback loop involving TMED9, GLI1, and TGFα 7 . Furthermore, knockdown of CNIH4 suppressed the proliferation of gastric cancer cells 9 . However, the clinical applications and functional studies of CNIH4 in glioma are still limited.…”

Section: Discussionmentioning

confidence: 90%

“…Researches indicated that CNIH4 potentially increases colon cancer cell metastatic activity by forming a positive feedback loop with TMED9, GLI1, and TGFα 7 . Besides, higher CNIH4 activity predicted poor prognosis in several human malignancies in recent investigations 7–9 . However, the therapeutic application and molecular processes of CNIH4 in glioma have not been fully discussed so far.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Integrated analysis based on vesicle trafficking‐related genes identifying CNIH4 as a novel therapeutic target for glioma

et al. 2023

View full text Add to dashboard Cite

Background Vesicle trafficking is a highly important process in numerous human diseases, especially in the central nervous system dysfunctions. However, as a key component of vesicle trafficking‐related genes (VRGs), Cornichon family AMPA receptor auxiliary protein 4 (CNIH4) has not been systematically elucidated in glioma so far. Methods Differentially expressed VRGs were selected using molecular signatures database (MSigDB), The Cancer Genome Atlas (TCGA), and Genotype‐Tissue Expression (GTEx) mRNA expression profiles. Further exploration of CNIH4 was determined using LASSO‐Cox regression algorithms. Then Kaplan–Meier (K‐M) plotter, receiver operating characteristic (ROC) curves, and multivariate Cox regression analyses were utilized to assess the independent significance of CNIH4 in the CGGA validation cohort. Functional exploration was performed with Gene Set Enrichment Analysis (GSEA) and then verified using a series of functional experiments in glioma cells. Finally, the consensus clustering algorithm was applied to identify clusters in glioma samples. After that, differences in prognosis, the tumor immune microenvironment (TIME), and therapy response were evaluated between clusters. Results CNIH4 was shown to be overexpressed in malignant glioma variants and was frequently observed in GCSs and TMZ‐resistant cell lines. Higher CNIH4 levels were significantly related to poor outcomes and positively correlated with adverse clinicopathological characteristics. Survival analyses revealed CNIH4 as an independent risk factor that outperformed traditional measures. Enrichment analysis indicated that overactive CNIH4 significantly gathered in stem cell processes. Furthermore, functional assays of silencing CNIH4 expression suppressed stem cell‐like properties in vitro and inhibited tumorigenicity in vivo. Finally, the CNIH4‐enriched subgroup negatively modulated immunotherapeutic response and reflected lower chemotherapy sensitivity for glioma patients. Conclusion Our study identified CNIH4 as a potential VRG that regulates tumor stemness, microenvironment immunity, and chemotherapy sensitivity. It may serve as a novel prognostic factor and a promising target against glioma therapy.

show abstract

Section: Discussionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Integrated analysis based on vesicle trafficking‐related genes identifying CNIH4 as a novel therapeutic target for glioma

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Usually, a multi-gene predictor is more accurate than a single-gene predictor as the prognostic ability of a single gene is limited. A predictor optimally constructed from the selected genes becomes a useful biomarker for predicting survival in breast cancer [ 10 , 11 , 12 , 13 , 14 , 15 ], lung cancer [ 6 , 7 , 8 , 9 , 16 , 17 ], gastric cancer [ 18 , 19 ], ovarian cancer [ 20 , 21 , 22 , 23 , 24 ], skin cancer [ 25 ], liver cancer [ 26 , 27 ], bladder cancer [ 28 ], head and neck cancer [ 29 , 30 ], glioma [ 31 ], myeloproliferative neoplasms [ 32 ], kidney cancer [ 33 ], and cancers of mixed types [ 34 , 35 ]. These analyses were performed mostly based on univariate Cox regression with the significance scaling of p -values, such as 0.05, 0.01, and 0.001, followed by cross-validation and/or external validation.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis for Survival Prognostic Prediction with Gene Selection: A Copula Method for Dependent Censoring

2023

View full text Add to dashboard Cite

Prognostic analysis for patient survival often employs gene expressions obtained from high-throughput screening for tumor tissues from patients. When dealing with survival data, a dependent censoring phenomenon arises, and thus the traditional Cox model may not correctly identify the effect of each gene. A copula-based gene selection model can effectively adjust for dependent censoring, yielding a multi-gene predictor for survival prognosis. However, methods to assess the impact of various types of dependent censoring on the multi-gene predictor have not been developed. In this article, we propose a sensitivity analysis method using the copula-graphic estimator under dependent censoring, and implement relevant methods in the R package “compound.Cox”. The purpose of the proposed method is to investigate the sensitivity of the multi-gene predictor to a variety of dependent censoring mechanisms. In order to make the proposed sensitivity analysis practical, we develop a web application. We apply the proposed method and the web application to a lung cancer dataset. We provide a template file so that developers can modify the template to establish their own web applications.

show abstract

“…Among leukemia patients, 59.04% were male and 40.96% were female. With the continuous development and progress in science and technology and medical technology, cancer treatment methods, such as surgery, chemotherapy and cell-based therapy, have made great progress [ 8 , 9 , 10 ]. However, due to the complex pathogenesis of cancer, it is very difficult to treat it.…”

Section: Introductionmentioning

confidence: 99%

Hot Spots and Trends in the Relationship between Cancer and Obesity: A Systematic Review and Knowledge Graph Analysis

Gao

Yang

Xue

et al. 2023

Life

View full text Add to dashboard Cite

Cancer is one of the most difficult medical problems in today’s world. There are many factors that induce cancer in humans, and obesity has become an important factor in inducing cancer. This study systematically and quantitatively describes the development trend, current situation and research hotspot of the relationship between cancer and obesity by using document statistics and knowledge graph visualization technology. Through the visualization technology analysis of knowledge graph in this study, the research hotspot and knowledge base source of the relationship between cancer and obesity in the last 20 years have been ascertained. Obesity-related factors, such as immunity, insulin, adiponectin, adipocytokines, nonalcoholic fatty liver and inflammatory reaction, may affect the occurrence of obesity and increase the risk of cancer. Obesity-related cancers include respiratory cancer, colorectal cancer, hepatocellular cancer, prostate cancer, gastric cancer, etc. Our research provides direction and basis for future research in this field, as well as technical and knowledge basis support for experts and researchers in related medical fields.

show abstract

Screening and identification of CNIH4 gene associated with cell proliferation in gastric cancer based on a large-scale CRISPR-Cas9 screening database DepMap

Cited by 7 publications

References 37 publications

Integrated analysis based on vesicle trafficking‐related genes identifying CNIH4 as a novel therapeutic target for glioma

Integrated analysis based on vesicle trafficking‐related genes identifying CNIH4 as a novel therapeutic target for glioma

Sensitivity Analysis for Survival Prognostic Prediction with Gene Selection: A Copula Method for Dependent Censoring

Hot Spots and Trends in the Relationship between Cancer and Obesity: A Systematic Review and Knowledge Graph Analysis

Contact Info

Product

Resources

About