KIF2C: An important factor involved in signaling pathways, immune infiltration, and DNA damage repair in tumorigenesis

Li, Rui-Qing; Yang, Yan; Qiao, Lin; Yang, Li; Shen, Dan-Dan; Zhao, Xiao-Jing

doi:10.1016/j.biopha.2024.116173

Cited by 2 publications

(1 citation statement)

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“…Kinesin family member 2 C (KIF2C) is frequently involved in MEK/ERK, mTOR, Wnt/β-catenin, P53 and TGF-β1/Smad signaling, immune infiltration, and DNA damage repair in tumorigenesis. Upregulation of KIF2C was shown to promote tumor cell migration, invasion, and chemotherapy resistance and inhibit DNA damage repair 49 . RAB32 is expressed in many secretory epithelial cells and functions as a regulator of cellular metabolism by supporting mTORC1 signaling 50 .…”

Section: Discussionmentioning

confidence: 99%

Vesicle-mediated transport-related genes predict the prognosis and immune microenvironment in hepatocellular carcinoma

Ye,

Wang,

Yuan

et al. 2024

J. Cancer

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Background : Liver hepatocellular carcinoma (LIHC) is one of the leading causes of cancer-related death. The prognostic outcomes of advanced LIHC patients are poor. Hence, reliable prognostic biomarkers for LIHC are urgently needed. Methods : Data for vesicle-mediated transport-related genes (VMTRGs) were profiled from 338 LIHC and 50 normal tissue samples downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were performed to construct and optimize the prognostic risk model. Five GEO datasets were used to validate the risk model. The roles of the differentially expressed genes (DEGs) were investigated via Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses. Differences in immune cell infiltration between the high- and low-risk groups were evaluated using five algorithms. The “pRRophetic” was used to calculate the anticancer drug sensitivity of the two groups. Transwell and wound healing assays were performed to assess the role of GDP dissociation inhibitor 2 (GDI2) on LIHC cells. Results : A total of 166 prognosis-associated VMTRGs were identified, and VMTRGs-based risk model was constructed for the prognosis of LIHC patients. Four VMTRGs (GDI2, DYNC1LI1, KIF2C, and RAB32) constitute the principal components of the risk model associated with the clinical outcomes of LIHC. Tumor stage and risk score were extracted as the main prognostic indicators for LIHC patients. The VMTRGs-based risk model was significantly associated with immune responses and high expression of immune checkpoint molecules. High-risk patients were less sensitive to most chemotherapeutic drugs but benefited from immunotherapies. In vitro cellular assays revealed that GDI2 significantly promoted the growth and migration of LIHC cells. Conclusions : A VMTRGs-based risk model was constructed to predict the prognosis of LIHC patients effectively. This risk model was closely associated with the immune infiltration microenvironment. The four key VMTRGs are powerful prognostic biomarkers and therapeutic targets for LIHC.

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Section: Discussionmentioning

confidence: 99%