DYNC1I1 Promotes the Proliferation and Migration of Gastric Cancer by Up-Regulating IL-6 Expression

Gong, Libao; Wen, Ti; Li, Zhi; Xing, Xin; Che, Xiaofang; Wang, Jin; Liu, Yunpeng; Qu, Xiujuan

doi:10.3389/fonc.2019.00491

Cited by 31 publications

(27 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Among the six energy metabolism-related genes, DYNC1I1, GPER1, MFAP2, C3, and GLI1 were risk factors while ARRB1 was a protective factor for clinical outcomes in GC. The prognostic value of the ve risk genes have been sporadically reported in previous studies, while the protective value of ARRB1 in GC was rarely identi ed [44][45][46][47][48][49]. Functional enrichment analysis revealed that this metabolism-related signature was signi cantly involved in some classical cancerrelated pathways.…”

Section: Discussionmentioning

confidence: 89%

Comprehensive Molecular Characterization and Identification of Prognostic Signature in Stomach Adenocarcinoma on The Basis of Energy-Metabolism-Related Genes

Chang

Wang

et al. 2021

Preprint

View full text Add to dashboard Cite

Background: Stomach adenocarcinoma (STAD) is a leading cause of cancer deaths, but its molecular and prognostic characteristics has never been fully illustrated. Methods: We describe a comprehensive molecular evaluation of primary STAD based on comprehensive analysis of energy-metabolism-related gene (EMRG) expression profiles. Results: On the basis of 86 EMRGs that were significantly associated to patients’ progression-free survival (PFS), we propose a molecular classification dividing gastric cancer into two subtypes: Cluster 1, most of which are young patients and display more immune and stromal cell components in tumor microenvironment (TME) and lower tumor priority; and Cluster 2, which show early stages and better PFS. Moreover, we construct a 6-gene signature that can classify the prognostic risk of patients after a three-phase training, test and validation process. Compared with patients with low-risk score, patients with high risk score had shorter overall survival. Furthermore, calibration and DCA analysis plots indicate the excellent predictive performance of the 6-gene signature, and which present higher robustness and clinical usability compared with three previous reported prognostic gene signatures. According to gene set enrichment analysis (GSEA), gene sets related to the high-risk group were participated in the ECM receptor interaction and hedgehog signaling pathway.Conclusions: Identification of the EMRG-based molecular subtypes and prognostic gene model provides a roadmap for patient stratification and trials of targeted therapies.

show abstract

Section: Discussionmentioning

confidence: 89%

Comprehensive Molecular Characterization and Identification of Prognostic Signature in Stomach Adenocarcinoma on The Basis of Energy-Metabolism-Related Genes

Chang

Wang

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…However, the role it plays in cancer remains controversial. Depending on its transport cargo, DYNC1I1 can act as a promotion or suppression factor in tumors (16,17). Several studies showed subcellular distribution of GPSM2 was regulated by dynein (9,18).…”

Section: Discussionmentioning

confidence: 99%

“…One study reported a tumor-suppressive function of DYNC1I1 in GBM via transport of SK2 (16). Another study indicated, DYNC1I1 promoted gastric cancer progression by increasing NF-kB nuclear translocation (17). Moreover, several studies FIGURE 1 | The expression of GPSM2 correlates with clinical features and indicates prognosis in breast patients.…”

Section: Introductionmentioning

confidence: 99%

Localization of GPSM2 in the Nucleus of Invasive Breast Cancer Cells Indicates a Poor Prognosis

et al. 2020

View full text Add to dashboard Cite

Purpose: GPSM2 (G protein signaling modulator 2) was reported to be involved in the cell division of breast cancer cells. Additionally, cytoplasmic dynein may mediate the transport process of GPSM2. DYNC1I1 (Cytoplasmic dynein 1 intermediate chain 1) is the most common cargo-binding subunit of dynein. However, the relationship between GPSM2 and DYNC1I1 and its clinical value is unclear. Methods: Immunohistochemical staining was performed for assessment of GPSM2 and DYNC1I1 expression. Immunoprecipitation analysis was used to assess the interaction between GPSM2 and DYNC1I1. Results: GPSM2 was correlated with clinical characteristics of breast cancer patients and is an unfavorable independent prognostic factor. In addition, nuclear expression of GPSM2 is an unfavorable independent prognostic factor (HR = 2.658, 95% CI = 1.490-4.741, p = 0.001). GPSM2 and DYNC1I1 are known to form a complex in breast cancer cells. Patients who were positive for expression of both DYNC1I1 and GPSM2 presented with shorter recurrence-free survival than other patients. Importantly, patients with GPSM2 nuclear expression showed higher DYNC1I1 expression. Conclusion: GPSM2 was an independent prognostic factor in breast cancer and nuclear expression of GPSM2 was significantly associated with poor prognosis, which was related to the positive expression of DYNC1I1. Examination of both GPSM2 and DYNC1I1 is necessary to establish a prognosis in breast cancer patients.

show abstract

“…These genes may become new targets for immunotherapy. It has been reported that DYNC1I1 could promote the proliferation and migration of GC by upregulating the expression of interleukin 6 (IL6) [48]. Matrix metalloproteinase 13 (MMP13) was highly expressed in GC tissues and related to invasion, metastasis, tumor stage, and worse survival [49].…”

Section: Discussionmentioning

confidence: 99%

Influence of Tumor Mutational Burden on Immune-infiltrating Cells in Stomach Adenocarcinoma

Zhao

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Gastric cancer (GC) is one of the most common and fatal cancers worldwide. Tumor mutational burden (TMB) is described as a novel powerful signature to predict response to immunotherapy in gastric cancer. Nevertheless, tumor-infiltrating immune cells (TIICs) in different TMB GC remains unknown.Results: (1) The most common missense were single nucleotide polymorphisms and C>T. Furthermore, titin (TTN), tumor protein p53 (TP53), and mucin 16 (MUC16) had a higher rate of mutations in STAD. (2) TMB-high and -low groups were not associated with survival, T stage, M stage, and grade of patients with stomach adenocarcinoma (STAD) (Psurvival=0.086, PT=0.331, PM=0.804, Pgrade=0.695). However, TMB groupings were related with N stage and sex (PN=0.003, Psex=0.003). (3) There were intricate differences in immune infiltration cells (eg, T cells, monocytes, and mast cells) between the TMB-high and TMB-low groups. (4) A total of 458 genes were identified as DEGs; Dynein cytoplasmic 1 intermediate chain 1(DYNC1I1), matrix metalloproteinase 13 (MMP13) and zinc finger and BTB domain containing 16 (ZBTB16) were correlated with overall survival (OS). (5) DEGs were mainly involved in the regulation of the extracellular matrix-receptor interaction, and the Wnt and PI3K-AKT signaling pathways.Conclusion: The present study provides a comprehensive and systematic analysis of TMB and its clinical significance, and reveals the complicated differences of 22 TIICs between TMB-high and TMB-low groups in STAD.

show abstract

DYNC1I1 Promotes the Proliferation and Migration of Gastric Cancer by Up-Regulating IL-6 Expression

Cited by 31 publications

References 28 publications

Comprehensive Molecular Characterization and Identification of Prognostic Signature in Stomach Adenocarcinoma on The Basis of Energy-Metabolism-Related Genes

Comprehensive Molecular Characterization and Identification of Prognostic Signature in Stomach Adenocarcinoma on The Basis of Energy-Metabolism-Related Genes

Localization of GPSM2 in the Nucleus of Invasive Breast Cancer Cells Indicates a Poor Prognosis

Influence of Tumor Mutational Burden on Immune-infiltrating Cells in Stomach Adenocarcinoma

Contact Info

Product

Resources

About