Helicobacter pylori Infection–Related Long Non-Coding RNA Signatures Predict the Prognostic Status for Gastric Cancer Patients

Xin, Zhuoyuan; Zhang, Luping; Liu, Mingqing; Wang, Yachen; Zhang, Yingli; Zhao, Wenjie; Sun, Yongxiao; Shi, Lei; Xu, Na; Zhang, Nan; Xu, Hong

doi:10.3389/fonc.2021.709796

Cited by 11 publications

(5 citation statements)

References 34 publications

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“…Compared to other prognostic signatures, our study mainly focused on lncRNAs correlated with angiogenesis status, identified prognosis-related ARLncs, and developed a risk model of prognosis in patients with STAD. Previous studies have investigated several prognostic models based on lncRNA expression involved in the process of ferroptosis [ 25 ], N6-methyladenosine modification [ 26 ], or Helicobacter pylori infection [ 27 ], which induce and activate the protumor signaling pathway of gastric cancer. Thus, our risk signatures had dual roles as it predicted the prognosis of STAD and contributed to the selection of proper cohorts who may benefit from antiangiogenesis treatment.…”

Section: Discussionmentioning

confidence: 99%

Angiogenesis-related lncRNAs predict the prognosis signature of stomach adenocarcinoma

et al. 2021

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Background Stomach adenocarcinoma (STAD), which accounts for approximately 95% of gastric cancer types, is a malignancy cancer with high morbidity and mortality. Tumor angiogenesis plays important roles in the progression and pathogenesis of STAD, in which long noncoding RNAs (lncRNAs) have been verified to be crucial for angiogenesis. Our study sought to construct a prognostic signature of angiogenesis-related lncRNAs (ARLncs) to accurately predict the survival time of STAD. Methods The RNA-sequencing dataset and corresponding clinical data of STAD were acquired from The Cancer Genome Atlas (TCGA). ARLnc sets were obtained from the Ensemble genome database and Molecular Signatures Database (MSigDB, Angiogenesis M14493, INTegrin pathway M160). A ARLnc-related prognostic signature was then constructed via univariate Cox and multivariate Cox regression analysis in the training cohort. Survival analysis and Cox regression were performed to assess the performance of the prognostic signature between low- and high-risk groups, which was validated in the validation cohort. Furthermore, a nomogram that combined the clinical pathological characteristics and risk score conducted to predict the overall survival (OS) of STAD. In addition, ARLnc-mRNA coexpression pairs were constructed with Pearson’s correlation analysis and visualized to infer the functional annotation of the ARLncs by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The expression of four ARLncs in STAD and their correlation with the angiogenesis markers, CD34 and CD105, were also validated by RT–qPCR in a clinical cohort. Results A prognostic prediction signature including four ARLncs (PVT1, LINC01315, AC245041.1, and AC037198.1) was identified and constructed. The OS of patients in the high-risk group was significantly lower than that of patients in the low-risk group (p < 0.001). The values of the time-dependent area under the curve (AUC) for the ARLnc signature for 1-, 3-, and 5- year OS were 0.683, 0.739, and 0.618 in the training cohort and 0.671, 0.646, and 0.680 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the ARLnc signature was an independent prognostic factor for STAD patients (p < 0.001). Furthermore, the nomogram and calibration curve showed accurate prediction of the survival time based on the risk score. In addition, 262 mRNAs were screened for coexpression with four ARLncs, and GO analysis showed that mRNAs were mainly involved in biological processes, including angiogenesis, cell adhesion, wound healing, and extracellular matrix organization. Furthermore, correlation analysis showed that there was a positive correlation between risk score and the expression of the angiogenesis markers, CD34 and CD105, in TCGA datasets and our clinical sample cohort. Conclusion Our study constructed a prognostic signature consisting of four ARLnc genes, which was closely related to the survival of STAD patients, showing high efficacy of the prognostic signature. Thus, the present study provided a novel biomarker and promising therapeutic strategy for patients with STAD.

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Section: Discussionmentioning

confidence: 99%

Angiogenesis-related lncRNAs predict the prognosis signature of stomach adenocarcinoma

et al. 2021

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“…Mounting evidence indicated that lncRNAs have an undeniable prognosis prediction function in GC cancer. Prognostic signatures based on ferroptosis-related lncRNA, immune-related lncRNA and helicobacter pylori infectionrelated lncRNA were proved to have preferable prognosis prediction functions in GC (Ma et al, 2021;Pan J. et al, 2021;Wei et al, 2021;Xin et al, 2021). Apart from this, lncRNAs could be used for subtype identification and therapy response prediction of GC Jiang et al, 2021b).…”

Section: Introductionmentioning

confidence: 99%

Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Liang

Zha

et al. 2022

Front. Cell Dev. Biol.

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Gastric cancer (GC) is a malignant tumor with poor survival outcomes. Immunotherapy can improve the prognosis of many cancers, including GC. However, in clinical practice, not all cancer patients are sensitive to immunotherapy. Therefore, it is essential to identify effective biomarkers for predicting the prognosis and immunotherapy sensitivity of GC. In recent years, chemokines have been widely reported to regulate the tumor microenvironment, especially the immune landscape. However, whether chemokine-related lncRNAs are associated with the prognosis and immune landscape of GC remains unclear. In this study, we first constructed a novel chemokine-related lncRNA risk model to predict the prognosis and immune landscape of GC patients. By using various algorithms, we identified 10 chemokine-related lncRNAs to construct the risk model. Then, we determined the prognostic efficiency and accuracy of the risk model. The effectiveness and accuracy of the risk model were further validated in the testing set and the entire set. In addition, our risk model exerted a crucial role in predicting the infiltration of immune cells, immune checkpoint genes expression, immunotherapy scores and tumor mutation burden of GC patients. In conclusion, our risk model has preferable prognostic performance and may provide crucial clues to formulate immunotherapy strategies for GC.

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“…Long noncoding RNAs (lncRNAs) are a type of non-coding RNA defined as transcripts >200 nucleotides that lack the potential to encode proteins and are involved in the regulation of a variety of tumors 18,19 . In addition, some lncRNAs are closely associated with drug resistance in osteosarcoma cells 20 .…”

Section: Discussionmentioning

confidence: 99%

Lnc BACE1-AS Promotes The Progression of Osteosarcoma Through miR-762/SOX7 Axis

Wang

Zhang

et al. 2021

Preprint

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Background: Osteosarcoma (OS) is a rare malignant primary tumor of mesenchymal origin affecting bone that occurs in adolescents and children. LncRNAs are important regulators of tumorigenesis and development. This study aimed to explore the role and molecular basis of LncRNA BACE1-AS in OS. Methods and results : Through the analysis of differential expressed lncRNAs in OS tissues by GEO database, LncRNA BACE1-AS displayed a remarkably lower expression. This found could also be observed in both OS tissues and cell lines by qRT-PCR. Furthermore, using Cell counting kit-8 (CCK-8), transwell, wound healing and westernblot assays, overexpression LncRNA BACE1-AS remarkably reduced cell proliferation, migration and invasion abilities in OS. In addition, LncRNA BACE1-AS was validated as a sponge of miR-762 through the prediction of lncRNASNP. Further, luciferase reporter and RIP assays were conducted to confirm the binding sites between LncRNA BACE1-AS and miR-762. SOX7 was a target of miR-762 and could be regulate by LncRNA BACE1-AS. Moreover, inhibition of miR-762 could attenuate the role of sh-LncRNA BACE1-AS in OS cells, at meanwhile reduced the expression of SOX7. Conclusion : In this study, LncRNA BACE1-AS regulated proliferation, migration, invasion and apoptosis of OS cells by miR-762/SOX7 axis, implying that LncRNA BACE1-AS was a potential target for OS therapy.

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Helicobacter pylori Infection–Related Long Non-Coding RNA Signatures Predict the Prognostic Status for Gastric Cancer Patients

Cited by 11 publications

References 34 publications

Angiogenesis-related lncRNAs predict the prognosis signature of stomach adenocarcinoma

Angiogenesis-related lncRNAs predict the prognosis signature of stomach adenocarcinoma

Identification and Comprehensive Prognostic Analysis of a Novel Chemokine-Related lncRNA Signature and Immune Landscape in Gastric Cancer

Lnc BACE1-AS Promotes The Progression of Osteosarcoma Through miR-762/SOX7 Axis

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