Identification of biomarkers predicting the chemotherapeutic outcomes of capecitabine and oxaliplatin in patients with gastric cancer

Zhang, Yan; Yuan, Zhen; Shen, Renbin; Jiang, Yannan; Xu, Wei; Gu, Menghui; Gu, Xueping

doi:10.3892/ol.2020.12153

Cited by 13 publications

(8 citation statements)

References 32 publications

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“…Previously, MATN3 was aberrantly methylated and expressed in gastric cancer and related to survival outcomes [28]. UPK1B expression was in relation to response to capecitabine and oxaliplatin and prognoses for gastric cancer patients [29]. GPX3 hypermethylation was in gastric cancer and correlated to lymph node metastases, tumor invasion depth, tumor differentiation as well as relapse [30].…”

Section: Discussionmentioning

confidence: 99%

[Retracted] Characterization of Tumor Mutation Burden‐Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer

Cheng

Shen

et al. 2022

BioMed Research International

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Objective. Tumor mutation burden (TMB) represents a useful biomarker for predicting survival outcomes and immunotherapy response. Here, we aimed to conduct TMB-based gene signature and molecular subtypes in gastric cancer. Methods. Based on differentially expressed genes (DEGs) between high- and low-TMB groups in TCGA, a LASSO model was developed for predicting overall survival (OS) and disease-free survival (DFS). The predictive performance was externally verified in the GSE84437 dataset. Molecular subtypes were conducted via consensus clustering approach based on TMB-related DEGs. The immune microenvironment was estimated by ESTIMATE and ssGSEA algorithms. Results. High-TMB patients had prolonged survival duration. TMB-related DEGs were distinctly enriched in cancer- (MAPK, P53, PI3K-Akt, and Wnt pathways) and immune-related pathways (T cell selection and differentiation). The TMB-based gene model was developed (including MATN3, UPK1B, GPX3, and RGS2), and high-risk score was predictive of poor prognosis and recurrence. ROC and multivariate analyses revealed the well predictive performance, which was confirmed in the external cohort. Furthermore, we established the nomogram containing the risk score, age, and stage for personalized prediction of OS and DFS. High-risk score was characterized by high stromal score, increased immune checkpoints, immune cell infiltrations, and enhanced sensitivity to gefitinib, vinorelbine, and gemcitabine. Three TMB-based molecular subtypes were conducted, characterized by distinct prognosis, immune microenvironment, and drug sensitivity. Conclusion. Collectively, we established a prognostic signature and three distinct molecular subtypes based on TMB features for gastric cancer, which might be beneficial for prognostic prediction and clinical decision-making.

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Section: Discussionmentioning

confidence: 99%

[Retracted] Characterization of Tumor Mutation Burden‐Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer

Cheng

Shen

et al. 2022

BioMed Research International

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“…It is identified that UPK1B can be used as a biomarker to predict the chemotherapeutic outcomes of capecitabine and oxaliplatin in gastric cancer patients (89). The high expression of UPK1B in adjuvant capecitabine and oxaliplatin treated patients with GC was associated with poor outcomes.…”

Section: Tspan20/upk1bmentioning

confidence: 99%

Tetraspanins: Novel Molecular Regulators of Gastric Cancer

et al. 2021

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Gastric cancer is the fourth and fifth most common cancer worldwide in men and women, respectively. However, patients with an advanced stage of gastric cancer still have a poor prognosis and low overall survival rate. The tetraspanins belong to a protein superfamily with four hydrophobic transmembrane domains and 33 mammalian tetraspanins are ubiquitously distributed in various cells and tissues. They interact with other membrane proteins to form tetraspanin-enriched microdomains and serve a variety of functions including cell adhesion, invasion, motility, cell fusion, virus infection, and signal transduction. In this review, we summarize multiple utilities of tetraspanins in the progression of gastric cancer and the underlying molecular mechanisms. In general, the expression of TSPAN8, CD151, TSPAN1, and TSPAN4 is increased in gastric cancer tissues and enhance the proliferation and invasion of gastric cancer cells, while CD81, CD82, TSPAN5, TSPAN9, and TSPAN21 are downregulated and suppress gastric cancer cell growth. In terms of cell motility regulation, CD9, CD63 and CD82 are metastasis suppressors and the expression level is inversely associated with lymph node metastasis. We also review the clinicopathological significance of tetraspanins in gastric cancer including therapeutic targets, the development of drug resistance and prognosis prediction. Finally, we discuss the potential clinical value and current limitations of tetraspanins in gastric cancer treatments, and provide some guidance for future research.

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“…It is overexpressed in GC and causes poor prognosis by affecting cell viability, invasion, and migration [19]. In recurrent GC, elevated UPK1B expression has a worse prognosis [20]. The mechanism for poor prognosis may be that UPK1B signi cantly affects the expression of critical genes in the Wnt/β-catenin signaling pathway in cancer cells [21].…”

Section: Discussionmentioning

confidence: 99%

Construction of a prognostic model for gastric cancer patients based on NAD+ metabolism-related genes and tumor microenvironment analysis

Xing

Zhang

Gao

et al. 2023

Preprint

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Background Nicotinamide adenine dinucleotide (NAD+) metabolism is important in the regulation of tumor immune escape. This study endeavored to develop a NAD + metabolism-related signature in gastric cancer (GC), which could provide a theoretical foundation for prognosis and therapy of GC patients. Methods First, differentially expressed genes (DEGs) between GC and paraneoplastic tissues were intersected with NAD + metabolism-related genes (NMRGs) to obtain differentially expressed NMRGs (DE NMRGs). Then, based on the transcript levels of NMRGs, GC patients were classified into high and low scoring groups using the Gene set variation analysis (GSVA) algorithm. Next, the DEGs between the high and low scoring groups were intersected with DEGs between GC and paraneoplastic tissues to obtain the GC-NM DEGs. Additionally, univariate Cox analysis and Least absolute shrinkage and selection operator (LASSO) regression analysis of GC-NM DEGs were performed to obtain prognostic biomarkers, which were used to construct a risk model. In addition, independent prognostic factors were obtained by Cox analysis based on risk scores and clinicopathological factors. Gene set enrichment analysis (GSEA) enrichment analysis and immune infiltration analysis were performed for the high- and low-risk groups. Finally, the mRNA expression of prognostic related genes was verified by experiment. Results 10 DE NMRGs were obtained and they were involved in the biological process of NAD biosynthetic process, nicotinamide nucleotide, and biosynthetic process. Further 7 biomarkers, including DNAJB13, CST2, THPO, CIDEA, ONECUT1, UPK1B, and SNCG, were obtained through univariate Cox and LASSO analyses of 1001 GC-NM DEGs. In addition, risk score and gender were demonstrated as credible independent prognostic factors for GC. Moreover, GSEA showed that the high-risk group was associated with bile secretion, intrinsic component of synaptic membrane and other pathways, while the low-risk group was associated with CMG complex. In addition, T cells, B cells, and natural killer cells were positively correlated with risk scores, and plasmacytoid dendritic cells were negatively correlated with risk scores. By QRT-PCR, the expression of prognostic genes in GC tissues was significantly up-regulated compared with paraneoplastic tissues. Conclusion This study established a NAD + metabolism-related signature based on DNAJB13, CST2, THPO, CIDEA, ONECUT1, UPK1B, and SNCG, which is of great significance in developing prognostic molecular biomarkers, clinical prognosis prediction, and treatment strategy decision for GC patients.

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Identification of biomarkers predicting the chemotherapeutic outcomes of capecitabine and oxaliplatin in patients with gastric cancer

Cited by 13 publications

References 32 publications

[Retracted] Characterization of Tumor Mutation Burden‐Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer

[Retracted] Characterization of Tumor Mutation Burden‐Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer

Tetraspanins: Novel Molecular Regulators of Gastric Cancer

Construction of a prognostic model for gastric cancer patients based on NAD+ metabolism-related genes and tumor microenvironment analysis

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