Identification of a novel gene pairs signature in the prognosis of gastric cancer

Peng, Pailan; Zhou, Xiangyu; Yi, Guo-Dong; Chen, Pengfei; Wang, Fan; Dong, Weiguo

doi:10.1002/cam4.1303

Cited by 50 publications

(43 citation statements)

References 19 publications

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“…For advanced gastric tumor, the fiveyear mortality rate of GC is as high as 30%~50% [4]. Currently, TNM (tumor/lymph node/metastatic) staging system has been widely used in prognosis of gastric tumor [5]. In fact, the occurrence of gastric tumor is attributed to interaction of multiple molecules and genes involved in the process [6], thus it is crucial to figure out its molecular mechanism and explore sensitive or effective biomarkers for early diagnosis and new treatment of patients with GC.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: LncRNA CASC11 promoted gastric cancer cell proliferation, migration and invasion in vitro by regulating cell cycle pathway

et al. 2018

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In this study, we aimed to investigate the effects of lncRNA CASC11 on gastric cancer (GC) cell progression through regulating miR-340-5p and cell cycle pathway. Expressions of lncRNA CASC11 in gastric cancer tissues and cell lines were determined by qRT-PCR. Differentially expressed lncRNAs, mRNAs and miRNAs were screened through microarray analysis. The relationship among CASC11, CDK1 and miR-340-5p was predicted by TargetScan and validated through dual luciferase reporter assay. Western blot assay examined the protein level of CDK1 and several cell cycle regulatory proteins. GO functional analysis and KEGG pathway analysis were used to predict the association between functions and related pathways. Cell proliferation was determined by CCK-8 assays. Cell apoptosis and cell cycle were detected by flow cytometry assay. CASC11 was highly expressed in GC tissues and cell lines. Knockdown of CASC11 inhibited GC cell proliferation, promoted cell apoptosis and blocked cell cycle. KEGG further indicated an enriched cell cycle pathway involving CDK1. QRT-PCR showed that miR-340-5p was down-regulated in GC cells tissues, while CDK1 was up-regulated. Furthermore, CASC11 acted as a sponge of miR-340-5p which directly targeted CDK1. Meanwhile, miR-340-5p overexpression promoted GC cell apoptosis and induced cell cycle arrest, while CDK1 overexpression inhibited cell apoptosis and accelerated cell cycle. Our study revealed the mechanism of CASC11/miR-340-5p/CDK1 network in GC cell line, and suggested that CASC11 was a novel facilitator that exerted a biological effect by activating the cell cycle signaling pathway. This finding provides a potential therapeutic target for GC.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: LncRNA CASC11 promoted gastric cancer cell proliferation, migration and invasion in vitro by regulating cell cycle pathway

et al. 2018

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“…In this study, because our IRGPs were generated by pairwise comparison and the score was calculated entirely based on gene expression in the same patient, our prognostic signature can not only overcome the batch effects of the different platforms but also does not require the scaling and normalization of data. This approach has been reported to be robust in several studies, including cancer‐related studies, and it is a major advantage in our study …”

Section: Discussionmentioning

confidence: 95%

A signature of 33 immune‐related gene pairs predicts clinical outcome in hepatocellular carcinoma

Sun

Zhang

et al. 2020

Cancer Medicine

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Objective: Hepatocellular carcinoma (HCC) has become the second most common tumor type that contributes to cancer-related death worldwide. The study aimed to establish a robust immune-related gene pair (IRGP) signature for predicting the prognosis of HCC patients. Methods: Two RNA-seq datasets (The Cancer Genome Atlas Program and International Cancer Genome Consortium) and one microarray dataset (GSE14520) were included in this study. We used a series of immune-related genes from the ImmPort database to construct gene pairs. Lasso penalized Cox proportional hazards regression was employed to develop the best prognostic signature. We assigned patients into two groups with low immune risk and high immune risk. Then, the prognostic ability of the signature was evaluated by a log-rank test and a Cox proportional hazards regression model. Results: After 1000 iterations, the 33-immune gene pair model obtained the highest frequency. As a result, we chose the 33 immune gene pairs to establish the immunerelated prognostic signature. As we expected, the immune-related signature accurately predicted the prognosis of HCC patients, and high-risk groups showed poor prognosis in the training datasets and testing datasets as well as in the validation datasets. Furthermore, the immune-related gene pair (IRGP) signature also showed higher predictive accuracy than three existing prognostic signatures. Conclusion: Our prognostic signature, which reflects the link between the immune microenvironment and HCC patient outcome, is promising for prognosis prediction in HCC.

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“…Over the past decades, in-depth gene sequencing and bioinformatics provided us the chance to identify novel diagnostic parameters and guide the individual treatment optimization for various illnesses [12][13][14]. Gene expression microarray was an effective method to show large-scale data at genomic levels, and rapid progression of bioinformatics make it possible to mine more reliable biomarkers [15].…”

Section: Introductionmentioning

confidence: 99%

Identification and Validation of a Five-gene Signature Associated with Overall Survival in Breast Cancer Patients

Wang

Chen

et al. 2020

Preprint

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Background Recent years, attributed to early detection and new therapies, the mortality rates of breast cancer (BC) decreased. Nevertheless, the global prevalence was still high and the underlying molecular mechanisms were remained largely unknown. The investigation of prognosis-related genes as the novel biomarkers for diagnosis and individual treatment had become an urgent demand for clinical practice. Methods Gene expression profiles and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database and randomly divided into training (n = 514) and internal validation (n = 562) cohort by using a random number table. The differentially expressed genes (DEGs) were estimated by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In the training set, the gene signature was constructed by the least absolute shrinkage and selection operator (LASSO) method based on DEGs screened by R packages. The results were further tested in the internal validation cohort and the entire cohort. Moreover, functions of five genes were explored by MTT, Colony-Formation, scratch and transwell assays. Western blot analysis was used to explore the mechanisms. Results In the training cohort, a total of 2805 protein coding DEGs were acquired through comparing breast cancer tissues (n = 514) with normal tissues (n = 113). A risk score formula involving five novel prognostic associated biomarkers (EDN2, CLEC3B, SV2C, WT1 and MUC2) were then constructed by LASSO. The prognostic value of the risk model was further confirmed in the internal validation set and the entire set. To explore the biological functions of the selected genes, in vitro assays were performed, indicating that these novel biomarkers could markedly influence breast cancer progression. Conclusion We established a predictive five-gene signature, which could be helpful for prognosis assessment and personalized management in breast cancer patients.

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Identification of a novel gene pairs signature in the prognosis of gastric cancer

Cited by 50 publications

References 19 publications

RETRACTED ARTICLE: LncRNA CASC11 promoted gastric cancer cell proliferation, migration and invasion in vitro by regulating cell cycle pathway

RETRACTED ARTICLE: LncRNA CASC11 promoted gastric cancer cell proliferation, migration and invasion in vitro by regulating cell cycle pathway

A signature of 33 immune‐related gene pairs predicts clinical outcome in hepatocellular carcinoma

Identification and Validation of a Five-gene Signature Associated with Overall Survival in Breast Cancer Patients

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