Expression, regulating mechanism and therapeutic target of KIF20A in multiple cancer

FoxM1 promotes the proliferation of cervical adenocarcinoma cells through transcriptional activation of FAM83D

Cervical adenocarcinoma exhibits a steadily increasing global incidence with notable demographic shifts toward younger populations. Despite the absence of distinct clinical guidelines differentiating its management from squamous cell carcinoma, treatment strategies remain non-specific, contributing to suboptimal patient outcomes. To address this therapeutic gap, we systematically investigated molecular disparities between adenocarcinoma and squamous cell carcinoma through integrated ChIP-seq and RNA-seq analyses. Our multi-omics approach identified FAM83D as a novel transcriptional target directly regulated by the FoxM1 oncoprotein, demonstrating adenocarcinoma-specific expression in HeLa cells. This regulatory relationship was experimentally validated using quantitative PCR and luciferase reporter assays. Mechanistically, we delineated that FoxM1 governs cell cycle progression and proliferation via FAM83D-dependent pathways. Intriguingly, co-immunoprecipitation studies revealed a physical interaction between FoxM1 and karyopherin α2 (KPNA2), another adenocarcinoma-enriched protein, with their expression levels showing significant positive correlation in clinical specimens. This study not only elucidates the oncogenic axis of FoxM1-FAM83D but also reveals the dual regulatory role of FoxM1 as both a transcriptional activator and protein interaction hub in cervical adenocarcinoma pathogenesis. These findings expand the molecular landscape of this malignancy and identify potential therapeutic entry points for targeted adenocarcinoma interventions.

Identification of key biomarker genes in liver hepatocellular carcinoma and kidney renal clear cell carcinoma progression: A shared high-throughput screening and molecular docking method with potentials for targeted therapeutic interventions

BACKGROUND AND OBJECTIVES

Liver Hepatocellular Carcinoma (LIHC) and Kidney Renal Clear Cell Carcinoma (KIRC) are leading causes of cancer death worldwide, but their early detections remain hindered by a lack of genetic markers. Our study aims to find prospective biomarkers that could serve as prognostic indicators for efficient drug candidates for KIRC and LIHC treatment.

METHODS

To detect differentially expressed genes (DEGs), four datasets were used: GSE66271 and GSE213324 for KIRC, and GSE135631 and GSE202853 for LIHC. Visualization of DEGs was done using heatmaps, volcano plots, and Venn diagrams. Hub genes were identified via PPI analysis and the cytoHubba plugin in Cytoscape. Their expression was evaluated using box plots, stage plots, and survival plots for prognostic assessment via GEPIA2. Molecular docking with PyRx's AutoDock Vina identified optimal binding interactions between compounds and proteins. Pharmacokinetic and toxicity analyses reinforced the drug-likeness and safety of these compounds.

RESULTS

In this study, 47 DEGs were identified, with the top 10 hub genes being TOP2A, BUB1, PTTG1, CCNB2, NUSAP1, KIF20A, BIRC5, RRM2, NDC80 and CDC45, chosen for their high MCC scores. Data mining revealed a correlation between TOP2A expression and clinical survival outcomes in KIRC and LIHC patients. Docking studies of the TOP2A structure identified a promising compound from Andrographis paniculata with high binding energy and interactions with TOP2A. Pharmacokinetic and toxicity assessments support its potential as a drug candidate.

CONCLUSION

Our study emphasizes TOP2A's prognostic significance in KIRC and LIHC and recognizes Andrographis paniculata compound as potential therapeutics, offering prospective for enhanced treatment and patient outcomes in these cancers.

Identification and validation a novel kinase-related gene signature for predicting prognosis and responsiveness to immunotherapy in hepatocellular carcinoma

Liver cancer research highlights the kinome's critical role in disease initiation and progression. However, comprehensive data analysis on the kinome's impact on hepatocellular carcinoma (HCC) prognosis is limited. We used the TCGA-LIHC mRNA expression profiles, analyzing them with various R packages. Key methods included univariate Cox regression for prognostic gene identification, consensus clustering for subtype classification, Gene Set Enrichment Analysis (GSEA), and immune landscape evaluation. A prognostic model was developed using LASSO Cox regression, and chemotherapy drug sensitivity was assessed using the pRRophetic package. We identified 45 kinases-related differentially expressed genes (DEGs), with 27 linked to HCC prognosis. Cluster analysis divided these genes into two subtypes, with distinct prognoses. We discovered 157 DEGs between kinase-related subtypes, 120 of which were prognostically relevant. A kinase-related gene signature (KRS) was developed for prognostic prediction. The high-KRS group showed poorer survival in TCGA-LIHC and validation cohorts, with notable differences in immune cell infiltration and checkpoint gene expression. This group also showed varying sensitivity to common drugs and anti-PD-L1 treatment. In contrast, the low-KRS group might respond better to anti-PD-1 immunotherapy. Our study introduces a kinase-related gene signature as a novel tool for predicting HCC prognosis. This signature aids in tailoring personalized treatment strategies, potentially improving clinical outcomes in HCC patients.

Exploratory Analysis of Molecular Subtypes in Early-Stage Osteosarcoma: Identifying Resistance and Optimizing Therapy

Background: Osteosarcoma (OS) is a highly aggressive bone malignancy with limited treatment options and poor prognosis. This exploratory study aimed to identify molecular subtypes of early-stage, treatment-naive OS to guide precise therapeutic strategies. Methods: We analyzed RNA-seq data obtained from tumor tissues from 102 OS patients using a non-negative matrix factorization algorithm (NMF) to classify the tumors into three subtypes: S1, S2, and S3. Differential gene expression was evaluated using DESeq2, followed by functional enrichment analysis with clusterProfiler and CancerHallmarks. The tumor microenvironment was assessed through ESTIMATE and CIBERSORT, and drug sensitivity was predicted using OncoPredict. SAOS-2 and MG63 cells, representing the S1 subtype, were used in the viability essays to determine the effect of hesperidin, a natural phenolic compound noted for its anti-cancer potential, alone and in combination with doxorubicin and 5-fluorouracil. Results: This study revealed three OS subtypes: S1 was enriched in cell cycle regulation, vesicular transport, and RNA metabolism while S2 and S3 were enriched in pathways related to extracellular matrix organization and protein translation, respectively. S1 displayed high tumor purity, significant chemoresistance, and overexpression of KIF20 A, correlating with poor prognosis. AURKB, a hesperidin target, was implicated in S1 pathogenesis. In vitro, hesperidin significantly reduced the viability of SAOS-2 and MG63 cells and enhanced doxorubicin efficacy. Conclusions: Our findings support the molecular subclassification of OS, emphasizing subtype-specific mechanisms of tumor progression and chemoresistance, with hesperidin offering potential as a therapeutic adjunct for high-risk OS patients.

KIF20A promotes triple-negative breast cancer progression via activation of the IL-17 signaling pathway

BACKGROUND

Triple-negative breast cancer (TNBC), the only breast cancer subtype lacking effective targeted therapies, is associated with a poor prognosis. Emerging evidence highlights the oncogenic role of kinesin family member 20A (KIF20A) in human malignancies, though its mechanistic contributions to TNBC progression remain poorly understood.

METHODS

Candidate target genes were screened via bioinformatic analysis. Following KIF20A knockdown, we utilized cell counting kit-8, 5-Ethynyl-2'-deoxyuridine staining, transwell, and wound healing assays to assess TNBC cell viability, proliferative capacity, migratory ability, and invasive potential of TNBC cells. In vivo, we measured the volume, weight, and proliferation of solid tumors. Moreover, the downstream pathway of KIF20A was screened by bioinformatic analysis and validated by an agonist and an inhibitor for the interleukin 17 (IL-17) pathway. The expression levels of proteins associated with the IL-17 pathway were assessed via Western blot.

RESULTS

KIF20A, highly overexpressed in TNBC, was screened out as a promising target gene. In vitro, KIF20A knockdown significantly impaired TNBC cell viability, proliferation, migration, and invasion. In vivo, KIF20A knockdown suppressed the growth and proliferation of solid tumors in nude mice xenograft models. Mechanistically, the IL-17 signaling pathway was screened out and the expression of proteins in this pathway was suppressed by KIF20A knockdown. The agonist for the IL-17 signaling countered the impact of KIF20A knockdown on TNBC progression. Direct inhibition of IL-17 showed a similar effect as KIF20A silencing on TNBC cells.

CONCLUSION

KIF20A downregulation suppresses TNBC progression via the inactivation of the IL-17 signaling pathway, suggesting KIF20A as a potential therapeutic target for TNBC.

Transcriptomic signatures of prostate cancer progression: a comprehensive RNA-seq study

Transcriptomics has been entirely transformed by RNA-sequencing (RNA-seq) due to its high sensitivity, accuracy, and precision. This study analyzed RNA-seq data to identify potential biomarkers for prostate cancer (PCa), a serious health issue among aging men. Despite several existing studies, biomarkers that effectively detect PCa or its prognosis have yet to be entirely determined. The differentially expressed genes (DEGs) that are critical and clinically informative were identified in PCa patient samples that had been progression stage categorized into medium risk (MR) and high risk (HR). A total of 174 DEGs were found to be shared between MR and HR samples. Functional enrichment analysis revealed their involvement in crucial biological processes, such as p53 signaling, mitotic nuclear division, and inflammation. To further examine their interactions, a Protein-Protein Interaction (PPI) network was constructed, where key genes, such as KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67, were found in significant modules, hubs, and motifs. Several transcription factors, including STAT5B, MYC, and SOX5 controlled these genes. Heatmap analysis indicates that the expression of the six crucial genes (KIF20A, TPX2, BUB1, BIRC5, BUB1B, and MKI67) increases with progression from benign state to medium-risk and high-risk states. Additionally, a nomogram model was constructed to predict the prognostic value of these biomarkers. Among the studied genes, BIRC5, MKI67, and KIF20A are suggested as potential prognostic biomarkers, while NIFK and PPP1CC are suggested as new therapeutic targets. These findings indicate that these biomarkers show considerable promise in improving early detection and prognosis of PCa.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-025-04297-3.

Macrophage Polarization-Based Analysis of the Role of the FOXM1/KIF20A Axis in Breast Cancer Metastasis

To investigate the potential molecular processes underlying the function of forkhead box M1 (FOXM1)-mediated macrophage polarization in breast cancer (BC). The expression levels of Kinesin family member 20 A (KIF20A) and FOXM1 in BC tissues and tumor-associated macrophages (TAMs) were determined using RT-qPCR. Following co-culture of macrophages with BC cells, the impact of FOXM1 on the proliferation, invasive migration ability, and epithelial-mesenchymal transition (EMT) of BC cells was assessed using cell counting kit-8, Transwell, and Western blot assays respectively. Both the chromatin immunoprecipitation (ChIP) test and the dual luciferase reporter gene assay were used to confirm the connection between FOXM1 and KIF20A. Furthermore, the effect of FOXM1 on BC cell growth in vivo was evaluated via subcutaneous tumor formation assay conducted in nude mice. BC cell growth and metastasis were aided by M2 macrophage polarization. KIF20A and FOXM1 expression levels were markedly elevated in both TAMs and BC tissues. FOXM1 drived M2 polarization of macrophages by transcriptionally activating KIF20A. In vitro studies have demonstrated that FOXM1, through its regulation of KIF20A, enhanced BC cell proliferation, migration, invasion, and EMT. The upregulation of KIF20A expression by FOXM1 promotes M2 polarization of macrophages, thereby facilitating BC cell proliferation and metastasis.

Machine Learning Approach and Bioinformatics Analysis Discovered Key Genomic Signatures for Hepatitis B Virus-Associated Hepatocyte Remodeling and Hepatocellular Carcinoma

Hepatitis B virus (HBV) causes liver cancer, which is the third most common cause of cancer-related death worldwide. Chronic inflammation via HBV in the host hepatocytes causes hepatocyte remodeling (hepatocyte transformation and immortalization) and hepatocellular carcinoma (HCC). Recognizing cancer stages accurately to optimize early screening and diagnosis is a primary concern in the outlook of HBV-induced hepatocyte remodeling and liver cancer. Genomic signatures play important roles in addressing this issue. Recently, machine learning (ML) models and bioinformatics analysis have become very important in discovering novel genomic signatures for the early diagnosis, treatment, and prognosis of HBV-induced hepatic cell remodeling and HCC. We discuss the recent literature on the ML approach and bioinformatics analysis revealed novel genomic signatures for diagnosing and forecasting HBV-associated hepatocyte remodeling and HCC. Various genomic signatures, including various microRNAs and their associated genes, long noncoding RNAs (lncRNAs), and small nucleolar RNAs (snoRNAs), have been discovered to be involved in the upregulation and downregulation of HBV-HCC. Moreover, these genetic biomarkers also affect different biological processes, such as proliferation, migration, circulation, assault, dissemination, antiapoptosis, mitogenesis, transformation, and angiogenesis in HBV-infected hepatocytes.

Unravelling the antitumor mechanism of Ocoxin through cancer cell genomics

Cancer is one of the leading causes of death worldwide. Many therapies are being used to treat this disease, however, new treatments are now being implemented, since they are not always effective and their secondary effects represent one of the main reasons for cancer patients' loss of life quality during the progression of the disease. In this scenario, Ocoxin is a mixture of plant extracts, amino acids, vitamins and minerals, known for its antioxidant, anti-inflammatory and immunoregulatory properties, which has shown to exert antitumor effects in many cancers. The aim of this study is to elucidate the mechanism of action of the compound in colorectal cancer, triple negative breast cancer, pancreatic cancer and prostate cancer. Analyses performed through RNA sequencing revealed that the main effect of Ocoxin appears to be the alteration of cell metabolism, especially inducing the process of ferroptosis. Nevertheless, the modulation of the cell cycle was also remarkable. Ocoxin altered 13 genes in common in all the four cancers that were not only associated to metabolism and cell cycle but were also involved in the integrated stress response and unfolded protein response, suggesting that the compound causes the induction of cell death through several pathways. Although the mechanisms vary according to the type of cancer, this study highlights the potential of Ocoxin as an adjunctive treatment to improve outcomes in cancer therapy.

Gene Expression Changes Associated With Recurrence After Gross Total Resection of Newly Diagnosed World Health Organization Grade 1 Meningioma

BACKGROUND AND OBJECTIVE

Patients who undergo gross total resection (GTR) of Central Nervous System World Health Organization (WHO) grade 1 meningioma constitute a "low-risk" group, but some low-risk meningiomas can recur despite reassuring clinical and histological features. In this study, gene expression values in newly diagnosed WHO grade 1 meningiomas that had undergone GTR were evaluated for their association with recurrence.

METHODS

This was a retrospective, international, multicenter cohort study that included WHO grade 1 meningiomas that underwent GTR, as first treatment, based on postoperative magnetic resonance imaging. Normalized gene expression values from a previously validated 34-gene panel were evaluated for their association with recurrence. Kaplan-Meier, multivariable Cox proportional hazard analyses, and K-means clustering were performed to assess the association of genes of interest with recurrence and identify molecular subgroups among clinically and histologically low-risk meningiomas.

RESULTS

In total, 442 patients with WHO grade 1 meningiomas that underwent GTR and had available gene expression profiling data were included in the study. The median follow-up was 5.0 years (interquartile range 2.6-7.7 years), local recurrence occurred in 36 patients (8.1%), 5-year local freedom from recurrence was 90.5%, and median time to recurrence was 2.9 years (range 0.5-10.7 years). Eleven genes were associated with local recurrence, including lower expression of ARID1B , ESR1 , LINC02593 , PGR , and TMEM30B and higher expression of CDK6 , CDKN2C , CKS2 , KIF20A , PGK1 , and TAGLN . Of these genes, PGK1 had the largest effect size. K-means clustering based on these 11 genes distinguished 2 molecular groups of clinically and histologically low-risk meningiomas with significant differences in local freedom from recurrence (hazard ratio 2.5, 95% CI 1.2-5.1, P = .016).

CONCLUSION

Gene expression profiling may help to identify newly diagnosed WHO grade 1 meningiomas that have an elevated risk of recurrence despite GTR.

Pan-cancer TCGA analysis reveals the potential involvement of B-type lamins in dysregulating chromosome segregation in human cancer

Lamins play a crucial role in maintaining nuclear structure and function. Our study investigates the expression patterns and clinical implications of B-type lamins with a special focus on lamin B2 across various cancer types using comprehensive RNA sequencing datasets. We found that high expression levels of lamin B1 and lamin B2 are associated with decreased overall and disease-free survival in cancer. This association is further pronounced when both lamins are co-expressed, indicating a compounded negative impact on patient prognosis. Additionally, we highlighted the relationship between B-type lamins and the tumor microenvironment. Lamin B1 mRNA expression shows a strong positive correlation with activated CD4+ T-cells and type 2 T-helper cells (Th2), suggesting its role in immune cell infiltration and response within tumors. Lamin B2 expression also correlates moderately with these immune cells, indicating a potential but lesser role in modulating the immune landscape. Notably, the epigenetic state of lamin B1 significantly affects the tumor microenvironment, suggesting a dual role in structural integrity and immune modulation. We have identified 9 lamin B2 interacting proteins that are co-expressed with B-type lamins in cancerous conditions and modulate cytokinesis and cell division pathways during tumorigenesis. Furthermore, we have identified specific molecular targets of B-type lamins that co-express with them in a range of human cancers and are potentially involved in dysregulating chromosome segregation and mRNA binding. Overexpression of these targets alongside B-type lamins correlates with poor prognosis in multiple cancers. These findings underscore the potential of B-type lamins as biomarkers for poor prognosis and as targets for cancer therapies.

Targeting Kinesins for Therapeutic Exploitation of Chromosomal Instability in Lung Cancer

New therapeutic approaches that antagonize tumour-promoting phenotypes in lung cancer are needed to improve patient outcomes. Chromosomal instability (CIN) is a hallmark of lung cancer characterized by the ongoing acquisition of genetic alterations that include the gain and loss of whole chromosomes or segments of chromosomes as well as chromosomal rearrangements during cell division. Although it provides genetic diversity that fuels tumour evolution and enables the acquisition of aggressive phenotypes like immune evasion, metastasis, and drug resistance, too much CIN can be lethal because it creates genetic imbalances that disrupt essential genes and induce severe proteotoxic and metabolic stress. As such, sustaining advantageous levels of CIN that are compatible with survival is a fine balance in cancer cells, and potentiating CIN to levels that exceed a tolerable threshold is a promising treatment strategy for inherently unstable tumours like lung cancer. Kinesins are a superfamily of motor proteins with many members having functions in mitosis that are critical for the correct segregation of chromosomes and, consequently, maintaining genomic integrity. Accordingly, inhibition of such kinesins has been shown to exacerbate CIN. Therefore, inhibiting mitotic kinesins represents a promising strategy for amplifying CIN to lethal levels in vulnerable cancer cells. In this review, we describe the concept of CIN as a therapeutic vulnerability and comprehensively summarize studies reporting the clinical and functional relevance of kinesins in lung cancer, with the goal of outlining how kinesin inhibition, or "targeting kinesins", holds great potential as an effective strategy for treating lung cancer.

Single-cell RNA sequencing reveals tumor heterogeneity in small cell neuroendocrine cervical carcinoma

Small cell neuroendocrine cervical carcinoma (SCNECC) is an aggressive gynecological malignancy with poor prognosis. The precision therapeutic strategies for SCNECC are severely limited by the complex tumor microenvironment. Here, we mapped the single-cell landscape of a total of six samples from matched SCNECC cancerous foci and normal adjacent cervical tissues. Through analysis of 68,455 high-quality cells, malignant epithelial cells were identified with increased neuroendocrine differentiation and reduced keratinization. Within four epithelial cell clusters, the key transcription factors ASCL1, NEUROD1, POU2F3, and YAP1 defined molecular subtypes. Transitional trajectory among subtypes characterized two distinct carcinogenesis pathways in SCNECC. The P-type SCNECC showed potentially enhanced immune infiltration over other subtypes. Intercellular communication analysis identified several immune checkpoints and differentially expressed signaling pathways among subtypes. Through western blotting, the TC-YIK cell line was identified as an N-type SCNECC cell with high expression of SLFN11 and mTOR. Based on immunohistochemical staining of malignant subtyping markers, a cohort of 66 SCNECC patients from our hospital were divided into five subtypes. We further combined YAP1 expression with other clinicopathological factors (Cox p < 0.05) to establish a prognostic nomogram. Overall, these findings provide clues for tumorigenesis, precision treatments and prognostic prediction in SCNECC.

CBX3 contributes to pancreatic adenocarcinoma progression via promoting KIF20A expression

Pancreatic adenocarcinoma (PAAD) is one of the malignant tumors with poor prognosis. This study aims to inquiry the effects of Chromobox homologue 3 (CBX3) on PAAD progression. Pan-cancer analysis of CBX3 and its correlation with PAAD progression were investigated by informatics analysis. The role of CBX3 in PAAD was explored in vitro and in vivo. Cell viability, proliferation, migration and invasion were inspected by CCK-8 assay, EdU staining, scratch test and transwell assay, respectively. The morphology of tumors was observed by hematoxylin-eosin staining. Immunohistochemistry (Ki67) was performed to inspect the proliferation of tumor tissue. The protein levels were measured by western blot. Moreover, the downstream genes of CBX3 were screened, and the effects of target gene on PAAD was investigated in vitro. CBX3 was overexpressed in multi cancers, and high CBX3 expression indicated poor prognosis in PAAD. Through the in vitro assays, knockdown of CBX3 suppressed the viability, migration and invasion of PAAD cells, and restrained tumor growth in vivo. Subsequently, kinesin family member 20A (KIF20A) was screened as the downstream gene of CBX3, which was up-regulated in PAAD and related to low overall survival. Mechanistically, we discovered that CBX3 could regulate KIF20A expression. Knockdown of CBX3 promoted the oncogenic effects of KIF20A silencing on PAAD cells, and attenuated the pro-oncogenic effects of KIF20A overexpression on PPAD. Collectively, silencing CBX3 suppressed PAAD progression through regulating KIF20A expression, providing an underlying target for PAAD treatment.

Therapeutic target genes and regulatory networks of gallic acid in cervical cancer

Introduction

This study aims to identify the therapeutic targets and regulatory mechanisms of the antitumor drug gallic acid (GA) in cervical cancer (CC).

Methods

HeLa cells were treated with GA and subjected to RNA-sequencing using the DNBSEQ platform. By combining the results of the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) analysis and RNA-seq, the differentially expressed genes (DEGs), including those upregulated and downregulated genes in CC compared with the normal cervix in the GEO and TCGA database, while expressed reversed after treatment with GA, were identified. Subsequently, the function enrichment analysis and protein-protein interaction of the DEGs were conducted. The candidate genes were identified using the Cytoscape software Gentiscape2.2 and MCODE plug-ins. Furthermore, the upstream microRNA (miRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA) of the candidate genes were predicted using the online tools of MirDIP, TarBase, and ENCORI. Finally, the regulatory network was constructed using Cytoscape software.

Results

CC cells are significantly inhibited by GA. Combining the GEO and TCGA databases and RNA-seq analyses, 127 DEGs were obtained and subjected to functional enrichment analysis. This analysis revealed that 221 biological processes, 82 cellular components, 63 molecular functions, and 36 KEGG pathways were employed to identify three therapeutic candidate genes, including CDC20, DLGAP5, and KIF20A. The upstream 13 miRNAs, 4 lncRNA, and 42 circRNAs were detected and used to construct a lncRNA/circRNA-miRNA-mRNA-pathway regulatory network.

Conclusion

This study identified candidate genes and the regulatory networks underlying the therapeutic effects of GA on CC using GA data mining methods, thus establishing a theoretical basis for targeted therapy of CC.

The miRNA-mRNA Regulatory Network in Human Hepatocellular Carcinoma by Transcriptomic Analysis From GEO

BACKGROUND

Bioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.

AIM

In this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs).

METHODS AND RESULTS

Common DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes. The reduced levels of tumor suppressor miRNAs or down regulated DEmiRs may be increased levels of oncogenes, the oncomirs or up regulated DEmiRs may be decreased levels of tumor suppressor genes in cancerous cells. According to this strategy, increased and decreased DEGs, also increased and decreased DEmiRs were selected. The multimir package was employed to predict target genes for DEmiRs then DEmiRs-hub gene network created. We identified approximately 1000 overlapping DEGs and 60 DEmiRs. Hub genes included RRM2, MELK, KIF11, KIF23, NCAPG, DLGAP5, BUB1B, AURKB, CCNB1, KIF20A, CCNA2, TTK, PBK, TOP2A, CDK1, MAD2L1, BIRC5, ASPM, CDCA8, and CENPF, all associated with significantly worse survival in HCC. miR-224, miR-24, miR-182, miRNA-1-3p, miR-30a, miR-27a, and miR-214 were identified as important DEmiRs with targeting more than six hub genes.

CONCLUSION

Generally, our findings offer insight into the interaction of hub genes and miRNAs in the development of HCC by bioinformatics analysis, information that may prove useful in identifying biomarkers and therapeutic targets in HCC.

Identification and validation of KIF20A for predicting prognosis and treatment outcomes in patients with breast cancer

Breast cancer is a leading cause of cancer-related deaths among women globally. It is imperative to explore novel biomarkers to predict breast cancer treatment response as well as progression. Here, we collected six breast cancer samples and paired normal tissues for high-throughput sequencing. By differential expression analysis, we found 1687 DEGs and identified the top 10 hub genes, including TOP2A, CDK1, BUB1B, KIF11, CCNA2, BUB1, CCNB1, KIF20A, DLGAP5 and CDC20. Univariate and multivariate Cox analyses on the METABRIC database and GSE96058 dataset demonstrated that KIF20A was an independent prognostic predictor for overall survival. KIF20A was positively correlated with cell cycle phases, including the cell cycle process, cycle G2 M phase transition and cell cycle DNA replication initiation. Single-cell analyses revealed that KIF20A was enriched in fibroblasts and endothelial within breast cancer stroma. Meanwhile, multidrug resistance (MDR) genes ABCB1, ABCC1 and ABCG2 were co-expressed with KIF20A in fibroblasts and endothelial cells within the stroma. MTABRIC database confirmed that high expression of KIF20A was positively correlated with treatment efficacy in patients with breast cancer. In conclusion, KIF20A could be served as a predictive biomarker for breast cancer prognosis and treatment outcomes. KIF20A may play a significant role by regulating cell cycle progression and modulating stromal progression in breast cancer. Our findings provided novel molecular insights that can guide personalized treatment strategies in breast cancer.

Targeting CDK1 and copper homeostasis in breast cancer via a nanopolymer drug delivery system

The prevalence of breast cancer (BRCA) is notable in the female population, being a commonly diagnosed malignancy, where the management of copper levels is crucial for treatment success. This research aims to explore the influence of copper homeostasis on BRCA therapy, with a specific focus on the role of Cyclin-Dependent Kinase 1 (CDK1) and its relationship to copper regulation. A novel thermosensitive hydrogel incorporating nanoparticles (NPs) was engineered to synergize with the chemotherapy drug vincristine (VCR) in inhibiting tumor growth and metastasis. Through a comprehensive approach involving bioinformatics analyses, in vitro experiments, and in vivo models, the study identified CDK1 as a significant factor in BRCA progression under copper homeostasis. MBVP-Gel, a novel thermosensitive hydrogel incorporating NPs, was developed to enhance the delivery of chemotherapy drugs and regulate copper homeostasis in breast cancer treatment. The MBVP-Gel, formulated with copper chelation and VCR NPs, effectively suppressed CDK1 expression, thereby restraining BRCA cell growth and metastasis while enhancing the therapeutic impact of VCR. This investigation offers fresh insights and experimental validation on the interaction between copper homeostasis and BRCA, providing a valuable foundation for refining future treatment strategies. These findings underscore the potential advantages of targeting copper homeostasis and CDK1 in enhancing BRCA therapy, setting the stage for individualized interventions and improved patient consequences.

Maternal genetic variants in kinesin motor domains prematurely increase egg aneuploidy

The female reproductive lifespan is highly dependent on egg quality, especially the presence of a normal number of chromosomes in an egg, known as euploidy. Mistakes in meiosis leading to egg aneuploidy are frequent in humans. Yet, knowledge of the precise genetic landscape that causes egg aneuploidy in women is limited, as phenotypic data on the frequency of human egg aneuploidy are difficult to obtain and therefore absent in public genetic datasets. Here, we identify genetic determinants of reproductive aging via egg aneuploidy in women using a biobank of individual maternal exomes linked with maternal age and embryonic aneuploidy data. Using the exome data, we identified 404 genes bearing variants enriched in individuals with pathologically elevated egg aneuploidy rates. Analysis of the gene ontology and protein-protein interaction network implicated genes encoding the kinesin protein family in egg aneuploidy. We interrogate the causal relationship of the human variants within candidate kinesin genes via experimental perturbations and demonstrate that motor domain variants increase aneuploidy in mouse oocytes. Finally, using a knock-in mouse model, we validate that a specific variant in kinesin KIF18A accelerates reproductive aging and diminishes fertility. These findings reveal additional functional mechanisms of reproductive aging and shed light on how genetic variation underlies individual heterogeneity in the female reproductive lifespan, which might be leveraged to predict reproductive longevity. Together, these results lay the groundwork for the noninvasive biomarkers for egg quality, a first step toward personalized fertility medicine.

Bulk- and single cell-RNA sequencing reveal KIF20A as a key driver of hepatocellular carcinoma progression and immune evasion

Introduction

Kinesin family member 20A (KIF20A) is essential for cell proliferation and is implicated in promoting tumor progression, but its role in hepatocellular carcinoma (HCC) remains poorly studied.

Methods

Through the analysis of bulk RNA-sequencing (bulk RNA-seq) and single-cell RNA sequencing (scRNA-seq) data, the expression of KIF20A and its relationship with diagnosis, prognosis, and the immune microenvironment were examined. The association between KIF20A and the malignant progression and metastasis of HCC was confirmed through in vitro and in vivo experiments. Furthermore, patient re-staging was performed using Recursive Partitioning Analysis (RPA) to enhance clinical benefit.

Results

In this study, we firstly found KIF20A was overexprerssed in HCC both by bulk RNA-seq and scRNA-seq, and then the overexpression of KIF20A significantly promoted the proliferation, invasion, and metastasis in vitro. In vivo, the overexpression of KIF20A promoted the growth and lung metastasis of HCC. Furthermore, gene set variation analysis of bulk RNA-seq and scRNA-seq revealed that KIF20A might be associated with cell cycle related signaling pathways of E2F and G2M, and overexpression of KIF20A inhibited the activity of p21 and bax, as well as shortened G2 phase. Importantly, we found that KIF20A could induce T cell exhaustion via the SPP1-CD44 axe using scRNA-seq. Additionally, KIF20A was also correlated with the expression of immune checkpoint inhibitors (ICIs), and KIF20Ahigh subgroup might be benefited from the ICIs therapy.

Conclusion

KIF20A emerges as a pivotal driver of HCC progression, intricately regulating cell cycle pathways and modulating immune responses, which position KIF20A as a promising target for HCC management.

Emerging roles of cytoskeletal transport and scaffold systems in human viral propagation

Viruses have long been recognized as significant pathogens, contributing to multiple global pandemics throughout human history. Recent examples include the 2009 influenza pandemic and the COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019. Despite ongoing experimental and clinical efforts, the development of effective antiviral treatments and vaccines remains challenging due to the high mutation rates of many human pathogenic viruses including influenza virus and SARS-CoV-2. As an alternative approach, antiviral strategies targeting host factors shared by multiple viruses could provide a more universally applicable solution. Emerging evidence suggests that viruses exploit the host cytoskeletal network to facilitate efficient viral replication and propagation. Therefore, a comprehensive understanding of the interactions between viral components and the cytoskeletal machinery may offer valuable insights for the development of broad-spectrum antiviral therapeutics. This review compiles and discusses current knowledge on the interactions between viruses and cytoskeletal elements, including kinesin, dynein, myosin, and vimentin, and explores their potential as therapeutic targets. The potential for these cytoskeletal components to serve as targets for new antiviral interventions is discussed in the context of diverse human viruses, including influenza virus, SARS-CoV-2, herpes simplex virus, human papillomavirus, and human immunodeficiency virus.

Exploring MPC1 as a potential ferroptosis-linked biomarker in the cervical cancer tumor microenvironment: a comprehensive analysis

BACKGROUND

The increasing problems of drug and radiotherapy resistance in cervical cancer underscores the need for novel methods for its management. Reports indicate that the expression of MPC1 may be associated with the tumor microenvironment and the occurrence of ferroptosis in cervical cancer. The objective of this study was to visually illustrate the prognostic significance and immunological characterization of MPC1 in cervical cancer.

METHODS

The expression profile and prognostic significance of MPC1 were analyzed using various databases, including UALCAN, TIMER2, GEPIA2, and Kaplan-Meier Plotter. TISIDB, TIMER2, and immunohistochemical analysis were used to investigate the correlation between MPC1 expression and immune infiltration. GO enrichment analysis, KEGG analysis, Reactome analysis, ConsensusPathDB, and GeneMANIA were used to visualize the functional enrichment of MPC1 and signaling pathways related to MPC1. The correlation analysis was carried out to examine the relationship between MPC1 and Ferroptosis gene in TIMER 2.0, ncFO, GEPIA Database and Kaplan-Meier Plotter.

RESULTS

We demonstrated that the expression levels of MPC1 in cervical cancer tissues were lower than those in normal cervical tissues. Kaplan-Meier survival curves showed shorter overall survival in cervical cancer patients with low levels of MPC1 expression. The expression of MPC1 was related to the infiltrating levels of tumor-infiltrating immune cells in cervical cancer. Moreover, MPC1 expression was associated with the iron-mediated cell death pathway, and several important ferroptosis genes were upregulated in cervical cancer cells. Furthermore, after knocking down MPC1 in HeLa cells, the expression of these genes decreased.

CONCLUSION

These findings indicate that MPC1 functions as a prognostic indicator and plays a role in the regulation of the ferroptosis pathway in cervical cancer.

Consensus, debate, and prospective on pancreatic cancer treatments

Pancreatic cancer remains one of the most aggressive solid tumors. As a systemic disease, despite the improvement of multi-modality treatment strategies, the prognosis of pancreatic cancer was not improved dramatically. For resectable or borderline resectable patients, the surgical strategy centered on improving R0 resection rate is consensus; however, the role of neoadjuvant therapy in resectable patients and the optimal neoadjuvant therapy of chemotherapy with or without radiotherapy in borderline resectable patients were debated. Postoperative adjuvant chemotherapy of gemcitabine/capecitabine or mFOLFIRINOX is recommended regardless of the margin status. Chemotherapy as the first-line treatment strategy for advanced or metastatic patients included FOLFIRINOX, gemcitabine/nab-paclitaxel, or NALIRIFOX regimens whereas 5-FU plus liposomal irinotecan was the only standard of care second-line therapy. Immunotherapy is an innovative therapy although anti-PD-1 antibody is currently the only agent approved by for MSI-H, dMMR, or TMB-high solid tumors, which represent a very small subset of pancreatic cancers. Combination strategies to increase the immunogenicity and to overcome the immunosuppressive tumor microenvironment may sensitize pancreatic cancer to immunotherapy. Targeted therapies represented by PARP and KRAS inhibitors are also under investigation, showing benefits in improving progression-free survival and objective response rate. This review discusses the current treatment modalities and highlights innovative therapies for pancreatic cancer.

Advancing Cancer Therapy: The Role of KIF20A as a Target for Inhibitor Development and Immunotherapy

The analysis begins with a detailed examination of the gene expression and protein structure of KIF20A, highlighting its interaction with critical cellular components that influence key processes such as Golgi membrane transport and mitotic spindle assembly. The primary focus is on the development of specific KIF20A inhibitors, detailing their roles and the challenges encountered in enhancing their efficacy, such as achieving specificity, overcoming tumor resistance, and optimizing delivery systems. Additionally, it delves into the prognostic value of KIF20A across multiple cancer types, emphasizing its role as a novel tumor-associated antigen, which lays the groundwork for the development of targeted peptide vaccines. The therapeutic efficacy of these vaccines as demonstrated in recent clinical trials is discussed. Future directions are proposed, including the integration of precision medicine strategies to personalize treatments and the use of combination therapies to improve outcomes. By concentrating on the significant potential of KIF20A as both a direct target for inhibitors and an antigen in cancer vaccines, this review sets a foundation for future research aimed at harnessing KIF20A for effective cancer treatment.

Identification of Hub Genes for Psoriasis and Cancer by Bioinformatic Analysis

Psoriasis increases the risk of developing various cancers, including colon cancer. The pathogenesis of the co-occurrence of psoriasis and cancer is not yet clear. This study is aimed at analyzing the pathogenesis of psoriasis combined with cancer by bioinformatic analysis. Skin tissue data from psoriasis (GSE117239) and intestinal tissue data from colon cancer (GSE44076) were downloaded from the GEO database. One thousand two hundred ninety-six common differentially expressed genes and 688 common shared genes for psoriasis and colon cancer were determined, respectively, using the limma R package and weighted gene coexpression network analysis (WGCNA) methods. The results of the GO and KEGG enrichment analyses were mainly related to the biological processes of the cell cycle. Thirteen hub genes were selected, including AURKA, DLGAP5, NCAPG, CCNB1, NDC80, BUB1B, TTK, CCNB2, AURKB, TOP2A, ASPM, BUB1, and KIF20A. These hub genes have high diagnostic value, and most of them are positively correlated with activated CD4 T cells. Three hub transcription factors (TFs) were also predicted: E2F1, E2F3, and BRCA1. These hub genes and hub TFs are highly expressed in various cancers. Furthermore, 251 drugs were predicted, and some of them overlap with existing therapeutic drugs for psoriasis or colon cancer. This study revealed some genetic mechanisms of psoriasis and cancer by bioinformatic analysis. These hub genes, hub TFs, and predicted drugs may provide new perspectives for further research on the mechanism and treatment.

Maternal genetic variants in kinesin motor domains prematurely increase egg aneuploidy

The female reproductive lifespan depends on egg quality, particularly euploidy. Mistakes in meiosis leading to egg aneuploidy are common, but the genetic landscape causing this is not well understood due to limited phenotypic data. We identify genetic determinants of reproductive aging via egg aneuploidy using a biobank of maternal exomes linked with maternal age and embryonic aneuploidy data. We found 404 genes with variants enriched in individuals with high egg aneuploidy rates and implicate kinesin protein family genes in aneuploidy risk. Experimental perturbations showed that motor domain variants in these genes increase aneuploidy in mouse oocytes. A knock-in mouse model validated that a specific variant in kinesin KIF18A accelerates reproductive aging and diminishes fertility. These findings suggest potential non-invasive biomarkers for egg quality, aiding personalized fertility medicine.

One sentence summary

The study identifies novel genetic determinants of reproductive aging linked to egg aneuploidy by analyzing maternal exomes and demonstrates that variants in kinesin genes, specifically KIF18A , contribute to increased aneuploidy and accelerated reproductive aging, offering potential for personalized fertility medicine.

Upregulation of the key biomarker kinesin family member 20A (KIF20A) is associated with pulmonary artery hypertension

OBJECTIVE

Pulmonary artery hypertension (PAH) is a complex, fatal disease with limited treatments. This study aimed to investigate possible key targets in PAH through bioinformatics.

METHODS

GSE144274 were obtained from Gene Expression Omnibus (GEO) database. Then, differentially expressed genes (DEGs) between idiopathic pulmonary hypertension (IPAH) and healthy subjects were identified and analyzed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed, and a protein-protein interaction (PPI) network was constructed using STRING. The hub genes were identified by MCODE method. The expression levels of hub genes were validated in vitro and in vivo models. Finally, the ROC analysis was performed based on the level of hub genes in clinical plasma samples.

RESULTS

A total of 363 DEGs were identified. GO analysis on these DEGs were mainly enriched in cell division, inflammatory response, among others. In the KEGG pathways analysis, DEGs mainly involved in cytokine-cytokine receptor interaction, rheumatoid arthritis, and IL-17 signaling pathways were enriched. The DEGs were analyzed with the STRING for PPI network analysis, and 62 hub genes were identified by MCODE. Finally, 6 central genes, KIF18B, SPC25, DLGAP5, KIF20A, CEP55 and ANLN, were screened out due to their novelty role in PAH. The expression of KIF20A was validated to be significantly upregulated both in the lung tissue of hypoxia-induced pulmonary hypertension (HPH) mice and proliferative PASMCs. Additionally, KIF20A levels is evelated in PAH plasma and the area under the curve (AUC) to identify PAH was 0.8591 for KIF20A.

CONCLUSION

The level of KIF20A elevates during the progression of PAH, which suggestes it could be a potential diagnostic and therapeutic target for the PAH.

KIF20A is a Prognostic Marker for Female Patients with Estrogen Receptor-Positive Breast Cancer and Receiving Tamoxifen as Adjuvant Endocrine Therapy

Purpose

Our aim was to verify whether KIF20A has the potential to serve as a prognostic marker for female patients with estrogen receptor (ER)-positive breast cancer (BC) and treated with tamoxifen (TAM).

Patients and Methods

Online tools were used to investigate the potential correlation between KIF20A gene expression and survival of patients with ER-positive BC and TAM treatment. Furthermore, immunohistochemistry (IHC) was conducted to assess the expression levels of KIF20A in patients included from our center. The prognostic value of KIF20A for disease-free survival (DFS) and overall survival (OS) was further evaluated using Cox regression analysis.

Results

According to the results obtained from online tools, it was found that patients with low KIF20A expression exhibited significantly better survival outcomes in terms of relapse-free survival (RFS), distant metastasis-free survival (DMFS), and OS compared to those with high KIF20A expression (P < 0.001, P < 0.001, and P = 0.008, respectively). Additionally, significantly lower gene expression of KIF20A was found in patients who responded to TAM than in those who did not respond to TAM (P < 0.001). We further included 203 patients with adjuvant TAM therapy, and IHC for KIF20A was performed on sections from paraffin-embedded blocks. Patients with low KIF20A expression had significantly better DFS and OS (P = 0.001 and 0.002, respectively, log rank test), and the expression of KIF20A was identified as an independent factor for predicting both DFS and OS (P = 0.001 and 0.008, respectively).

Conclusion

KIF20A expression is an independent prognostic factor for survival in patients with ER-positive BC who received adjuvant TAM therapy. In clinical practice, IHC evaluation of KIF20A expression in surgical samples before administering tamoxifen may assist in predicting the treatment outcomes of these patients.

Identification, characterization, and prognosis investigation of pivotal genes shared in different stages of breast cancer

One of the leading causes of death (20.1 per 100,000 women per year), breast cancer is the most prevalent cancer in females. Statistically, 95% of breast cancer are categorized as adenocarcinomas, and 55% of all patients may go into invasive phases; however, it can be successfully treated in approximately 70-80% of cases if diagnosed in the nascent stages. The emergence of breast tumor cells which are intensely resistant to conventional therapies, along with the high rate of metastasis occurrence, has highlighted the importance of finding novel strategies and treatments. One of the most advantageous schemes to alleviate this complication is to identify the common differentially expressed genes (DEGs) among primary and metastatic cancerous cells to use resultants for designing new therapeutic agents which are able to target both primary and metastatic breast tumor cells. In this study, the gene expression dataset with accession number GSE55715 was analyzed containing two primary tumor samples, three bone-metastatic samples, and three normal samples to distinguish the up- and down regulated genes in each stage compared to normal cells as control. In the next step, the common upregulated genes between the two experimental groups were detected by Venny online tool. Moreover, gene ontology, functions and pathways, gene-targeting microRNA, and influential metabolites were determined using EnrichR 2021 GO, KEGG pathways miRTarbase 2017, and HMDB 2021, respectively. Furthermore, elicited from STRING protein-protein interaction networks were imported to Cytoscape software to identify the hub genes. Then, identified hub genes were checked to validate the study using oncological databases. The results of the present article disclosed 1263 critical common DEGs (573 upregulated + 690 downregulated), including 35 hub genes that can be broadly used as new targets for cancer treatment and as biomarkers for cancer detection by evaluation of expression level. Besides, this study opens a new horizon to reveal unknown aspects of cancer signaling pathways by providing raw data evoked from in silico experiments. This study's outcomes can also be widely utilized in further lab research since it contains diverse information on common DEGs of varied stages and metastases of breast cancer, their functions, structures, interactions, and associations.