Expression of KIF18A Is Associated with Increased Tumor Stage and Cell Proliferation in Prostate Cancer

Cancer on motors: How kinesins drive prostate cancer progression?

Prostate cancer causes numerous male deaths annually. Although great progress has been made in the diagnosis and treatment of prostate cancer during the past several decades, much about this disease remains unknown, especially its pathobiology. The kinesin superfamily is a pivotal group of motor proteins, that contains a microtubule-based motor domain and features an adenosine triphosphatase activity and motility characteristics. Large-scale sequencing analyses based on clinical samples and animal models have shown that several members of the kinesin family are dysregulated in prostate cancer. Abnormal expression of kinesins could be linked to uncontrolled cell growth, inhibited apoptosis and increased metastasis ability. Additionally, kinesins may be implicated in chemotherapy resistance and escape immunologic cytotoxicity, which creates a barrier to cancer treatment. Here we cover the recent advances in understanding how kinesins may drive prostate cancer progression and how targeting their function may be a therapeutic strategy. A better understanding of kinesins in prostate cancer tumorigenesis may be pivotal for improving disease outcomes in prostate cancer patients.

Kinesin Family Member-18A (KIF18A) Promotes Cell Proliferation and Metastasis in Hepatocellular Carcinoma

BACKGROUND & AIMS

Kinesin family member 18A (KIF18A) is notable for its aberrant expression across various cancer types and its pivotal role is driving cancer progression. In this study, we aim to investigate the intricate molecular mechanisms underlying the impact of KIF18A on the progression of HCC.

METHODS

Western blotting assays, a quantitative real-time PCR and immunohistochemical analyses were performed to quantitatively assess KIF18A expression in HCC tissues. We then performed genetic manipulations within HCC cells by silencing endogenous KIF18A using short hairpin RNA (shRNA) and introducing exogenous plasmids to overexpress KIF18A. We monitored cell progression, analyzed cell cycle and cell apoptosis and assessed cell migration and invasion both in vitro and in vivo. Moreover, we conducted RNA-sequencing to explore KIF18A-related signaling pathways utilizing Reactome and KEGG enrichment methods and validated these critical mediators in these pathways.

RESULTS

Analysis of the TCGA-LIHC database revealed pronounced overexpression of KIF18A in HCC tissues, the finding was subsequently confirmed through the analysis of clinical samples obtained from HCC patients. Notably, silencing KIF18A in cells led to an obvious inhibition of cell proliferation, migration and invasion in vitro. Furthermore, in subcutaneous and orthotopic xenograft models, suppression of KIF18A sgnificantly redudce tumor weight and the number of lung metastatic nodules. Mechanistically, KIF18A appears to facilitate cell proliferation by upregulating MAD2 and CDK1/CyclinB1 expression levels, with the activation of SMAD2/3 signaling contributing to KIF18A-driven metastasis.

CONCLUSION

Our study elucidates the molecular mechanism by which KIF18A mediates proliferation and metastasis in HCC cells, offering new insights into potential therapeutic targets.

KIF18A interacts with PPP1CA to promote the malignant development of glioblastoma

Glioblastoma (GBM), which has poor prognosis and low 5-year survival rate, is the most common primary central nervous system malignant tumour in adults. Kinesin family member 18A (KIF18A) plays an important role in multiple tumours and is potential therapeutic target for GBM. Therefore, the present study investigated the role of KIF18A in GBM. The expression level and survival prognosis of KIF18A and protein phosphatase 1 catalytic subunit α (PPP1CA) in GBM patients were analysed using the Chinese Glioma Genome Atlas (CGGA) database. Reverse transcription-quantitative PCR and western blot analysis were applied to measure the expression of KIF18A and PPP1CA in normal and GBM cell lines. KIF18A expression was inhibited through cell transfection with a KIF18A-targeting short hairpin RNA. Cell proliferation was detected with the Cell Counting Kit-8 assay. Flow cytometry was used to detect cell cycle changes. Transwell and wound healing assays were used to measure cell invasion and migration. Western blotting was utilized for the detection of invasion- and migration-related proteins MMP9 and MMP2. Biological General Repository for Interaction Datasets and GeneMANIA databases were used to analyse the interaction between KIF18A and PPP1CA. The correlation between PPP1CA and KIF18A was examined using data from the CGGA database. Immunoprecipitation was used to demonstrate the binding relationship between KIF18A and PPP1CA. PPP1CA was overexpressed using cell transfection technology and its mechanism was further examined. The results demonstrated that KIF18A was upregulated in GBM cells compared with normal microglia HMC3. Compared with that in sh-NC group, silencing of KIF18A reduced cell proliferation, induced G₂/M cycle arrest and inhibited the migration and the invasion of A172 GBM cells by interacting with PPP1CA. In conclusion, KIF18A interacted with PPP1CA to promote the proliferation, cycle arrest, migration and invasion of GBM cells.

Dynamic Regulation Genes at Microtubule Plus Ends: A Novel Class of Glioma Biomarkers

Simple Summary

Microtubule plus-end-related genes (MPERGs) encode a group of proteins that specifically aggregate at the microtubule plus ends to play critical biological roles in the cell cycle, cell movement, ciliogenesis, and neuronal development by coordinating microtubule assembly and dynamics; however, the MPERG correlations and their clinical significance in glioma are not fully understood. This study is the first to systematically analyze and define a seven-gene signature (CTTNBP2, KIF18A, NAV1, SLAIN2, SRCIN1, TRIO, and TTBK2) and nomogram model closely associated with clinical factors and the tumor microenvironment as a reliable and independent prognostic biomarker to guide personalized choices of immunotherapy and chemotherapy for glioma patients.

Abstract

Glioma is the most prevalent and aggressive primary nervous system tumor with an unfavorable prognosis. Microtubule plus-end-related genes (MPERGs) play critical biological roles in the cell cycle, cell movement, ciliogenesis, and neuronal development by coordinating microtubule assembly and dynamics. This research seeks to systematically explore the oncological characteristics of these genes in microtubule-enriched glioma, focusing on developing a novel MPERG-based prognostic signature to improve the prognosis and provide more treatment options for glioma patients. First, we thoroughly analyzed and identified 45 differentially expressed MPERGs in glioma. Based on these genes, glioma patients were well distinguished into two subgroups with survival and tumor microenvironment infiltration differences. Next, we further screened the independent prognostic genes (CTTNBP2, KIF18A, NAV1, SLAIN2, SRCIN1, TRIO, and TTBK2) using 36 prognostic-related differentially expressed MPERGs to construct a signature with risk stratification and prognostic prediction ability. An increased risk score was related to the malignant progression of glioma. Therefore, we also designed a nomogram model containing clinical factors to facilitate the clinical use of the risk signature. The prediction accuracy of the signature and nomogram model was verified using The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets. Finally, we examined the connection between the signature and tumor microenvironment. The signature positively correlated with tumor microenvironment infiltration, especially immunoinhibitors and the tumor mutation load, and negatively correlated with microsatellite instability and cancer stemness. More importantly, immune checkpoint blockade treatment and drug sensitivity analyses confirmed that this prognostic signature was helpful in anticipating the effect of immunotherapy and chemotherapy. In conclusion, this research is the first study to define and validate an MPERG-based signature closely associated with the tumor microenvironment as a reliable and independent prognostic biomarker to guide personalized choices of immunotherapy and chemotherapy for glioma patients.

Prognostic and diagnostic value of circRNA expression in prostate cancer: A systematic review and meta-analysis

BACKGROUND

Circular RNAs (circRNAs) are receiving increasing attention as novel biomarkers. Our goal was to investigate the diagnostic, clinicopathological, and prognostic utility of circRNAs in prostate cancer (PCa).

METHODS

Relevant literature was searched in PubMed, Web of Science, and EMBASE. Sensitivity, specificity, diagnostic odds ratio (DOR), negative likelihood ratio (NLR), positive likelihood ratio (PLR), and the area under the curve (AUC) were calculated to evaluate the diagnostic accuracy of circRNA expression. circRNAs' clinical, pathological, and prognostic value was examined using pooled odds ratios (ORs) and hazard ratios (HRs).

RESULTS

This meta-analysis included 23 studies, with 5 for diagnosis, 16 for clinicopathological parameters, and 10 for prognosis. For diagnostic value, the pooled sensitivity, pooled specificity, PLR, NLR, DOR, and AUC were 0.82, 0.62, 2.17, 0.29, 7.37, and 0.81, respectively. Upregulation of carcinogenic circRNAs was associated with poor clinical parameters (Gleason score: OR = 0.222, 95% CI: 0.145-0.340; T classification: OR = 0.274, 95% CI: 0.175-0.430; lymph node metastasis: OR = 0.353, 95% CI: 0.175-0.716; tumor size: OR = 0.226, 95% CI: 0.099-0.518) and could predict poor survival outcomes (HR = 2.408, 95% CI: 1.559-3.720, p < 0.001). Conversely, downregulation of tumor-suppressor circRNAs was also associated with poor clinical parameters (Gleason score: OR = 1.689, 95% CI: 1.144-2.493; T classification: OR = 2.586, 95% CI: 1.779-3.762) and worse prognosis (HR = 1.739, 95% CI: 1.147-2.576, p = 0.006).

CONCLUSION

Our results showed that circRNAs might be useful biomarkers for the diagnosis and prognosis of PCa.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier CRD42021284785.

Prognostic Biomarker KIF18A and Its Correlations With Immune Infiltrates and Mitosis in Glioma

Background: Glioma is globally recognised as one of the most frequently occurring primary malignant brain tumours, making the identification of glioma biomarkers critically significant. The protein KIF18A (Kinesin Family Member 18A) is a member of the kinesin superfamily of microtubule-associated molecular motors and has been shown to participate in cell cycle and mitotic metaphase and anaphase. This is the first investigation into the expression of KIF18A and its prognostic value, potential biological functions, and effects on the immune system and mitosis in glioma patients. Methods: Gene expression and clinicopathological analysis, enrichment analysis, and immune infiltration analysis were based on data obtained from The Cancer Genome Atlas (TCGA), with additional bioinformatics analyses performed. Statistical analysis was conducted in R software. Clinical samples were used to evaluate the expression of KIF18A via immunohistochemical staining. In addition, the expression level of KIF18A was validated on U87 cell line. Results: Our results highlighted that KIF18A plays a key role as an independent prognostic factor in patients with glioma. KIF18A was highly expressed in glioma tissues, and KIF18A expression was associated with age, World Health Organization grade, isocitrate dehydrogenase (IDH) status, 1p/19q codeletion, primary therapy outcome, and overall survival (OS). Enrichment analysis revealed that KIF18A is closely correlated with the cell cycle and mitosis. Single sample gene set enrichment analysis (ssGSEA) analysis revealed that KIF18A expression was related to the immune microenvironment. The increased expression of KIF18A in glioma was verified in clinical samples and U87 cell line. Conclusion: The identification of KIF18A as a new biomarker for glioma could help elucidate how changes in the glioma cell and immune microenvironment promote glioma malignancy. With further analysis, KIF18A may serve as an independent prognostic indicator for human glioma.

Dauricine inhibits human pancreatic carcinoma cell proliferation through regulating miRNAs

Pancreatic cancer is one of the most malignant digestive tract tumors with the worst prognosis. Dauricine (Dau) can inhibit the proliferation of the pancreatic cancer cell line, and has the potential to be used as an adjuvant drug against pancreatic cancer; however, the working mechanism of Dau has not been elucidated. To unravel the effects and mechanisms of Dau on proteins and metabolic pathways, we evaluated the mRNA and microRNA expression in BxPC3 cells treated with Dau. The differences in the gene expression were compared using principal component analysis using mRNA and miRNA data to detect and analyze the sample discrimination. 187 miRNA and 907 mRNA that were significantly differentially expressed were identified using Python programming. On comparing genes and miRNAs in the DISEASES database, 79 known miRNA and 47 mRNA were found to be affected by Dau. The up-regulated and down-regulated genes were annotated with GO biological processes to determine the functional effect. Interactions between mRNA and mRNA were analyzed using the STRING database and the miRBase database was queried to obtain experimentally verified interactions between miRNA and mRNA as edges of miRNA and mRNA in the network. Finally, 413 sites and 2125 sides of the network were obtained, including 1 up-regulated and 18 down-regulated miRNAs. The expression of 19 miRNAs was identified by qPCR. The analysis of the protein-protein interaction network, using the Molecular Complex Detection (MCODE) plug-in of cytoscape, helped in identifying 12 important sub-networks. Most subnets are indirectly or directly related to specific miRNAs. This study provides evidence for the anticancer effect of Dau as a potential anticancer compound.

Knockdown of Circ_CCNB2 Sensitizes Prostate Cancer to Radiation Through Repressing Autophagy by the miR-30b-5p/KIF18A Axis

Background: Circular RNAs (circRNAs) have recently emerged as crucial regulatory molecules in prostate cancer (PCa), but few researches focus on the effects of circRNAs on PCa radiosensitivity. The issue will be addressed in this study using circRNA Cyclin B2 (circ_CCNB2) as an object. Materials and Methods: All RNA and protein levels were severally examined using quantitative real-time polymerase chain reaction and Western blot. Colony formation assay and flow cytometry were implemented for detecting cell colony capacity and apoptotic cells, respectively. Cellular migration and invasion abilities were evaluated by transwell assay. The combination between potential target molecules was analyzed by dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. The effect of circ_CCNB2 on PCa radiosensitivity in vivo was explored using xenograft models in mice. Results: Circ_CCNB2 was upregulated in irradiation-resistant PCa tissues and cells. Circ_CCNB2 knockdown had promoted effect on the radiosensitivity of irradiation-resistant PCa cells by inhibiting autophagy. Besides, circ_CCNB2 could directly sponge miR-30b-5p, and the promotion of circ_CCNB2 knockdown on PCa radiosensitivity was achieved by elevating miR-30b-5p. MiR-30b-5p enhanced the radiosensitivity of irradiation-resistant PCa cells through repressing the expression of its target kinesin family member 18A (KIF18A). Furthermore, circ_CCNB2 regulated the KIF18A level through targeting miR-30b-5p. Circ_CCNB2 downregulation facilitated PCa radiosensitivity in vivo through inhibiting autophagy by miR-30b-5p/KIF18A. Conclusions: In this study, knockdown of circ_CCNB2 was shown to promote PCa radiosensitivity through autophagy repression by miR-30b-5p/KIF18A axis, developing a molecular resistance mechanism of PCa radiotherapy and a feasible strategy to increase radiosensitivity.