KIF20A promotes cellular malignant behavior and enhances resistance to chemotherapy in colorectal cancer through regulation of the JAK/STAT3 signaling pathway

Bioinformatics and systems-biology approach to identify common pathogenic mechanisms for COVID-19 and systemic lupus erythematosus

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic has brought a heavy burden to the world, interestingly, it shares many clinical symptoms with systemic lupus erythematosus (SLE). It is unclear whether there is a similar pathological process between COVID-9 and SLE. In addition, we don't know how to treat SLE patients with COVID-19. In this study, we analyse the potential similar pathogenesis between SLE and COVID-19 and explore their possible drug regimens using bioinformatics and systems biology approaches.

METHODS

The common differentially expressed genes (DEGs) were extracted from the COVID-19 datasets and the SLE datasets for functional enrichment, pathway analysis and candidate drug analysis.

RESULT

Based on the two transcriptome datasets between COVID-19 and SLE, 325 common DEGs were selected. Hub genes were identified by protein-protein interaction (PPI) analysis. few found a variety of similar functional changes between COVID-19 and SLE, which may be related to the pathogenesis of COVID-19. Besides, we explored the related regulatory networks. Then, through drug target matching, we found many candidate drugs for patients with COVID-19 only or COVID-19 combined with SLE.

CONCLUSION

COVID-19 and SLE patients share many common hub genes, related pathways and regulatory networks. Based on these common targets, we found many potential drugs that could be used in treating patient with COVID-19 or COVID-19 combined with SLE.

Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles

Pathway analysis, including nontopology-based (non-TB) and topology-based (TB) methods, is widely used to interpret the biological phenomena underlying differences in expression data between two phenotypes. By considering dependencies and interactions between genes, TB methods usually perform better than non-TB methods in identifying pathways that include closely relevant or directly causative genes for a given phenotype. However, most TB methods may be limited by incomplete pathway data used as the reference network or by difficulties in selecting appropriate reference networks for different research topics. Here, we propose a gene set correlation enrichment analysis method, Gscore, based on an expression dataset-derived coexpression network to examine whether a differentially expressed gene (DEG) list (or each of its DEGs) is associated with a known gene set. Gscore is better able to identify target pathways in 89 human disease expression datasets than eight other state-of-the-art methods and offers insight into how disease-wide and pathway-wide associations reflect clinical outcomes. When applied to RNA-seq data from COVID-19-related cells and patient samples, Gscore provided a means for studying how DEGs are implicated in COVID-19-related pathways. In summary, Gscore offers a powerful analytical approach for annotating individual DEGs, DEG lists, and genome-wide expression profiles based on existing biological knowledge.

Cucurbitacin B Inhibits the Malignancy of Esophageal Carcinoma through the KIF20A/JAK/STAT3 Signaling Pathway

This study intends to explore the effects of Cucurbitacin B (CuB) and KIF20A on esophageal carcinoma (ESCA). Data were downloaded from the Cancer Genome Atlas (TCGA) database. The expression properties of KIF20A have been confirmed by GEPIA and ualcan from TCGA. The expression of KIF20A was determined using western blotting in ECA109 and KYSE150 cells after transfection with KIF20A, KIF20A siRNA, or numerical control siRNA (si-NC). Then, different concentrations of CuB were used to treat ECA109 and KYSE150 cells. CCK-8 and colony formation assays were used to measure cell viability, and a Transwell assay was utilized to assess cell migration and invasion ability. N-cadherin, E-cadherin, snail, p-Janus kinase 2 (JAK2), JAK2, p-signal transducer and activator of transcription 3 (STAT3), and STAT3 expression levels were evaluated using western blot. KIF20A was higher expressed in ESCA than in normal cells, and its overexpression was associated with squamous cell carcinoma, TNM stage, and lymph nodal metastasis of ESCA patients. In ECA109 and KYSE150 cells, increased KIF20A facilitated cell proliferation, migration, and invasion, whereas the knockdown of KIF20A can reverse these effects with N-cadherin. Snail expression diminished and E-cadherin increased. Similarly, CuB treatment could inhibit cell proliferation, migration, and invasion concentration dependently. Furthermore, KIF20A accelerated the expression of p-JAK2 and p-STAT3, while the application of CuB inhibited KIF20A expression and attenuated the activation of the JAK/STAT3 pathway. These findings revealed that CuB could inhibit the growth, migration, and invasion of ESCA through downregulating the KIF20A/JAK/STAT3 signaling pathway, and CuB could serve as an essential medicine for therapeutic intervention.

Ginsenoside 20(S)-Rg3 reduces KIF20A expression and promotes CDC25A proteasomal degradation in epithelial ovarian cancer

Background

Ginsenoside 20(S)-Rg3 shows promising tumor-suppressive effects in ovarian cancer via inhibiting NF-κB signaling. This study aimed to explore the downstream tumor suppressive mechanisms of ginsenoside Rg3 via this signaling pathway.

Materials and methods

A systematical screening was applied to examine the expression profile of 41 kinesin family member genes in ovarian cancer. The regulatory effect of ginsenoside Rg3 on KIF20A expression was studied. In addition, we explored interacting proteins of KIF20A and their molecular regulations in ovarian cancer. RNA-seq data from The Cancer Genome Atlas (TCGA) was used for bioinformatic analysis. Epithelial ovarian cancer cell lines SKOV3 and A2780 were used as in vitro and in vivo cell models. Commercial human ovarian cancer tissue arrays were used for immunohistochemistry staining.

Results

KIF20A is a biomarker of poor prognosis among the kinesin genes. It promotes ovarian cancer cell growth in vitro and in vivo. Ginsenoside Rg3 can suppress the transcription of KIF20A. GST pull-down and co-immunoprecipitation (IP) assays confirmed that KIF20A physically interacts with BTRC (β-TrCP1), a substrate recognition subunit for SCFβ-TrCP E3 ubiquitin ligase. In vitro ubiquitination and cycloheximide (CHX) chase assays showed that via interacting with BTRC, KIF20A reduces BTRC-mediated CDC25A poly-ubiquitination and enhances its stability. Ginsenoside Rg3 treatment partly abrogates KIF20A overexpression-induced CDC25A upregulation.

Conclusion

This study revealed a novel anti-tumor mechanism of ginsenoside Rg3. It can inhibit KIF20A transcription and promote CDC25A proteasomal degradation in epithelial ovarian cancer.

FOXM1/KIF20A axis promotes clear cell renal cell carcinoma progression via regulating EMT signaling and affects immunotherapy response

Background

The correlation between FOXM1 and KIF20A has not been revealed in clear cell renal cell carcinoma (ccRCC).

Methods

Public data was downloaded from The Cancer Genome Atlas (TCGA) database. R software was utilized for the execution of bioinformatic analysis. The expression levels of specific molecules (mRNA and protein) were detected using real-time quantitative PCR (qRT-PCR) and Western blot assays. The capacity of cell growth was assessed by employing CCK8 and colony formation assay. Cell invasion and migration ability were assessed using transwell assay.

Results

In our study, we illustrated the association between FOXM1 and KIF20A. Our results indicated that both FOXM1 and KIF20A were associated with poor prognosis and clinical performance. The malignant characteristics of ccRCC cells can be significantly suppressed by inhibiting FOXM1 and KIF20A, as demonstrated by in vitro experiments. Moreover, we found that FOXM1 can upregulate KIF20A. Then, EMT signaling was identified as the underlying pathway FOXM1 and KIF20A are involved. WB results indicated that FOXM1/KIF20A axis can activate EMT signaling. Moreover, we noticed that FOXM1 and KIF20A can affect the immunotherapy response and immune microenvironment of ccRCC patients.

Conclusions

Our results identified the role of the FOXM1/KIF20A axis in ccRCC progression and immunotherapy, making it the underlying target for ccRCC.

Circ_0084188 Regulates the progression of colorectal cancer through the miR-769-5p/KIF20A axis

BACKGROUND

Colorectal cancer (CRC) is one of the major gastrointestinal malignancies threatening human health. More and more studies indicate that circular RNAs (circRNAs) are important regulatory factors of CRC, but the mechanism is still indistinct.

METHODS

Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were used to detect the expression of circ_0084188, microRNA-769-5p (miR-769-5p), and kinesin family member 20A (KIF20A) in CRC tissues. Kaplan-Meier curve was used to analyze the relationship between circ_0084188 expression and the survival rate of CRC patients. Cell proliferation, viability, apoptosis, migration, and invasion were analyzed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), 5-ethynyl-2'-deoxyuridine (EdU), flow cytometry, wound-healing, and transwell assays, respectively. The relationship between miR-769-5p and circ_0084188 or KIF20A was detected by a dual-luciferase reporter and RNA pull-down. The effect of circ_0084188 on tumor growth was verified by xenograft studies in vivo.

RESULTS

Circ_0084188 and KIF20A were upregulated and miR-769-5p was downregulated in CRC. Circ_0084188 knockdown repressed the proliferation, migration, and invasion of CRC cells, as well as enhanced apoptosis in vitro. Mechanistically, circ_0084188 targeted miR-769-5p, and the reduction of miR-769-5p reversed the effects of circ_0084188 knockdown on cell functional behaviors. KLF20A was a direct miR-769-5p target, and circ_0084188 acted as a sponge for miR-769-5p to regulate the KIF20A level. Moreover, miR-769-5p regulated the functional behaviors of CRC cells by targeting KIF20A. In addition, circ_0084188 knockdown confined the growth of xenograft tumors in vivo.

CONCLUSION

Circ_0084188 upregulated the expression of KIF20A to promote the tumorigenesis of CRC through miR-769-5p, providing a new therapeutic target for CRC.

Multi-omics analysis and validation of the tumor microenvironment of hepatocellular carcinoma under RNA modification patterns

BACKGROUND

Multiple types of RNA modifications are associated with the prognosis of hepatocellular carcinoma (HCC) patients. However, the overall mediating effect of RNA modifications on the tumor microenvironment (TME) and the prognosis of patients with HCC is unclear.

METHODS

Thoroughly analyze the TME, biological processes, immune infiltration and patient prognosis based on RNA modification patterns and gene patterns. Construct a prognostic model (RNA modification score, RNAM-S) to predict the overall survival (OS) in HCC patients. Analyze the immune status, cancer stem cell (CSC), mutations and drug sensitivity of HCC patients in both the high and low RNAM-S groups. Verify the expression levels of the four characteristic genes of the prognostic RNAM-S using in vitro cell experiments.

RESULTS

Two modification patterns and two gene patterns were identified in this study. Both the high-expression modification pattern and the gene pattern exhibited worse OS. A prognostic RNAM-S model was constructed based on four featured genes (KIF20A, NR1I2, NR2F1 and PLOD2). Cellular experiments suggested significant dysregulation of the expression levels of these four genes. In addition, validation of the RNAM-S model using each data set showed good predictive performance of the model. The two groups of HCC patients (high and low RNAM-S groups) exhibited significant differences in immune status, CSC, mutation and drug sensitivity.

CONCLUSION

The findings of the study demonstrate the clinical value of RNA modifications, which provide new insights into the individualized treatment for patients with HCC.

STAT3 as a newly emerging target in colorectal cancer therapy: Tumorigenesis, therapy response, and pharmacological/nanoplatform strategies

Colorectal cancer (CRC) ranks as the third most aggressive tumor globally, and it can be categorized into two forms: colitis-mediated CRC and sporadic CRC. The therapeutic approaches for CRC encompass surgical intervention, chemotherapy, and radiotherapy. However, even with the implementation of these techniques, the 5-year survival rate for metastatic CRC remains at a mere 12-14%. In the realm of CRC treatment, gene therapy has emerged as a novel therapeutic approach. Among the crucial molecular pathways that govern tumorigenesis, STAT3 plays a significant role. This pathway is subject to regulation by cytokines and growth factors. Once translocated into the nucleus, STAT3 influences the expression levels of factors associated with cell proliferation and metastasis. Literature suggests that the upregulation of STAT3 expression is observed as CRC cells progress towards metastatic stages. Consequently, elevated STAT3 levels serve as a significant determinant of poor prognosis and can be utilized as a diagnostic factor for cancer patients. The biological and malignant characteristics of CRC cells contribute to low survival rates in patients, as the upregulation of STAT3 prevents apoptosis and promotes pro-survival autophagy, thereby accelerating tumorigenesis. Furthermore, STAT3 plays a role in facilitating the proliferation of CRC cells through the stimulation of glycolysis and promoting metastasis via the induction of epithelial-mesenchymal transition (EMT). Notably, an intriguing observation is that the upregulation of STAT3 can mediate resistance to 5-fluorouracil, oxaliplatin, and other anti-cancer drugs. Moreover, the radio-sensitivity of CRC diminishes with increased STAT3 expression. Compounds such as curcumin, epigallocatechin gallate, and other anti-tumor agents exhibit the ability to suppress STAT3 and its associated pathways, thereby impeding tumorigenesis in CRC. Furthermore, it is worth noting that nanostructures have demonstrated anti-proliferative and anti-metastatic properties in CRC.

Comprehensive analysis of transcriptome-wide N6-methyladenosine methylomes in the Barrett's esophagus in rats

PURPOSE

As the most abundant RNA modification, N6-methyladenosine (m6A) methylation plays crucial roles in various diseases. The aim of this study is to comprehensively map the landscape of the mRNA m6A modification pattern in Barrett's esophagus (BE) in order to find key genes and potential therapy for BE and even esophageal adenocarcinoma (EAC).

METHODS

Methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA-sequencing (RNA-seq) were performed to compare the difference in mRNA m6A methylation and differentially expressed mRNAs between BE and normal control (NC) tissues. Bioinformatics analysis was used to describe the m6A modification pattern and specific genes in BE and NC tissues.

RESULTS

Through MeRIP-seq, we obtained m6A methylation profiling in BE and NC tissues. In total, 11,026 unique peaks were detected in the BE groups, whereas 8564 unique peaks were detected in the NC groups. Peaks were primarily enriched within CDS with GGACU motifs and most of the peaks were within 1000 bp in width. Moreover, functional enrichment analysis demonstrated that hypermethylated and hypomethylated genes were significantly enriched in coronavirus disease pathway, calcium signaling pathway and MAPK signaling pathways. Furthermore, PPI network was conducted and 18 hub genes were identified via STRING database and Cystoscope. Among them, ACTA1, CDC20, CKM, KIF20a, MYH11, TPM2, MYL9, DES, TNNT3 were overexpressed in EAC in the GEPIA gene bank and TPM1, KIF20a impaired patients' survival in the Kaplan-Meier plotter database. Finally, functional enrichment analysis demonstrated that co-expressed genes of TPM1 were significantly enriched in calcium signaling pathway, cGMP-PKG signaling pathway and PI3K-Akt signaling pathway.

CONCLUSION

Our study is the first to perform comprehensive and transcriptome-wide maps to identify the potential roles played by m6A methylation in BE, which widely involved in oxidative stress. This foresees a guiding role in revealing the molecular mechanism of m6A-mediated genes that govern the pathogenesis and progression of BE and EAC.

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.

Molecular complex detection in protein interaction networks through reinforcement learning

BACKGROUND

Proteins often assemble into higher-order complexes to perform their biological functions. Such protein-protein interactions (PPI) are often experimentally measured for pairs of proteins and summarized in a weighted PPI network, to which community detection algorithms can be applied to define the various higher-order protein complexes. Current methods include unsupervised and supervised approaches, often assuming that protein complexes manifest only as dense subgraphs. Utilizing supervised approaches, the focus is not on how to find them in a network, but only on learning which subgraphs correspond to complexes, currently solved using heuristics. However, learning to walk trajectories on a network to identify protein complexes leads naturally to a reinforcement learning (RL) approach, a strategy not extensively explored for community detection. Here, we develop and evaluate a reinforcement learning pipeline for community detection on weighted protein-protein interaction networks to detect new protein complexes. The algorithm is trained to calculate the value of different subgraphs encountered while walking on the network to reconstruct known complexes. A distributed prediction algorithm then scales the RL pipeline to search for novel protein complexes on large PPI networks.

RESULTS

The reinforcement learning pipeline is applied to a human PPI network consisting of 8k proteins and 60k PPI, which results in 1,157 protein complexes. The method demonstrated competitive accuracy with improved speed compared to previous algorithms. We highlight protein complexes such as C4orf19, C18orf21, and KIAA1522 which are currently minimally characterized. Additionally, the results suggest TMC04 be a putative additional subunit of the KICSTOR complex and confirm the involvement of C15orf41 in a higher-order complex with HIRA, CDAN1, ASF1A, and by 3D structural modeling.

CONCLUSIONS

Reinforcement learning offers several distinct advantages for community detection, including scalability and knowledge of the walk trajectories defining those communities. Applied to currently available human protein interaction networks, this method had comparable accuracy with other algorithms and notable savings in computational time, and in turn, led to clear predictions of protein function and interactions for several uncharacterized human proteins.

Identification of the prognostic biomarkers and their correlations with immune infiltration in colorectal cancer through bioinformatics analysis and in vitro experiments

Colorectal cancer (CRC) is the third most diagnosed malignancy and the second leading cause of cancer death. The objective was to identify novel hub genes that were helpful for prognosis and targeted therapy in CRC. GSE23878, GSE24514, GSE41657, GSE81582 were filtered from the gene expression omnibus (GEO). Differentially expressed genes (DEGs) were identified through GEO2R, which were enriched in the GO term and KEGG pathway in DAVID. PPI network was constructed and analyzed using STRING and hub genes were screened out. The relationships between hub genes and prognoses in CRC were evaluated in GEPIA based on the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx). The transcription factors and miRNA-mRNA interaction networks for hub genes were performed using miRnet and miRTarBase. The relationship between hub genes and tumor-infiltrating lymphocytes were analyzed in TIMER. The protein levels of hub genes were identified in HPA. The expression levels of hub gene in CRC and its effect on the biological effect of CRC cells were identified in vitro. As hub genes, the mRNA levels of BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 were highly expressed in CRC and had excellent prognostic value. The BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 were closely associated with transcription factors, miRNAs, tumor-infiltrating lymphocytes, suggesting their involvement in the regulation of CRC. BIRC5 highly expressed in CRC tissues and cells, and promoted the proliferation, migration, and invasion of CRC cells. BIRC5, CCNB1, KIF20A, NCAPG, and TPX2 are hub genes that serve as promising prognostic biomarkers in CRC. BIRC5 plays an important role in the development and progression of CRC.

KIF20A as a potential biomarker of renal and bladder cancers based on bioinformatics and experimental verification

BACKGROUND

Bladder cancer (BC) is a malignant tumor that occurs in the bladder wall and often appears in elderly individuals. Renal cancer (RC) arises from the renal tubular epithelium, but its molecular mechanism remains unclear.

METHODS

We downloaded RC datasets (GSE14762 and GSE53757) and a BC dataset (GSE121711) to screen differentially expressed genes (DEGs). We also performed weighted gene coexpression network analysis (WGCNA). We created a protein-protein interaction (PPI) network and performed functional enrichment analysis, such as gene set enrichment analysis (GSEA). Heatmaps were made for gene expression. Survival analysis and immunoinfiltration analysis were performed. Comparative toxicogenomics database (CTD) analysis was performed to find the relationship between disease and hub genes. Western blotting was performed to verify the role of KIF20A in apoptosis.

RESULTS

A total of 764 DEGs were identified. The GSEA showed that the DEGs were mainly enriched in organic acid metabolism, drug metabolism, mitochondria, and metabolism of cysteine and methionine. The PPI network in GSE121711 showed that KIF20A was a hub gene of renal clear cell carcinoma. Where the expression level of KIF20A was higher, the prognosis of patients was worse. CTD analysis showed that KIF20A was associated with inflammation, proliferation, and apoptosis. KIF20A expression in the RC group was upregulated, as shown by western blotting. The core proteins (including pRB Ser 780, CyclinA, E2F1, CCNE1, and CCNE2) in the pRB Ser 780/CyclinA signaling pathway were also upregulated in the RC group.

CONCLUSIONS

KIF20A might be a novel biomarker for researching renal and bladder cancers.

Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools

Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan-Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4+ T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment.

Mir-153-3p Modulates the Breast Cancer Cells’ Chemosensitivity to Doxorubicin by Targeting KIF20A

Breast cancer is considered the solid tumor most sensitive to chemotherapy. However, it can become resistant to various chemotherapeutic drugs, including doxorubicin, which triggers cell death by intercalation between DNA bases, free radical formation, and topoisomerase II inhibition. When drug resistance develops, several miRNAs are dysregulated, suggesting that miRNAs may play a significant role in resistance formation. In the current study, we investigated how doxorubicin sensitivity of breast cancer cells is affected by miR-153-3p and its target gene. The MTT method was used to determine the chemo-sensitizing effect of miR-153-3p on doxorubicin in MCF-7 and MDA-MB-231 cell lines. Results of Western blot and dual luciferase confirmed that miR-153-3p targets KIF20A and decreases its expression. Transwell and flow cytometry experiments showed that miR-153-3p and doxorubicin together had higher effects on MCF-7 and MDA-MB-231 cell proliferation, migration, and invasion, as well as increasing apoptosis and arresting cells in the G1 phase. Proteins related to apoptosis and the cell cycle exhibited the same tendency. Intracellular vesicle formation was inhibited and RAB26 was also downregulated by treatment with miR-153-3p alone or in combination with doxorubicin. Doxorubicin’s ability to suppress tumors may be enhanced by miR-153-3p, according to in vivo studies. According to our findings, miR-153-3p has a direct effect on KIF20A and may regulate the formation of intracellular vesicles, which in turn makes breast cancer cells more susceptible to doxorubicin.

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

Kinesin family member 20A (KIF20A) is a member of the kinesin family. It transports chromosomes during mitosis, plays a key role in cell division. Recently, studies proved that KIF20A was highly expressed in cancer. High expression of KIF20A was correlated with poor overall survival (OS). In this review, we summarized all the cancer that highly expressed KIF20A, described the role of KIF20A in cancer. We also organized phase I and phase II clinical trials of KIF20A peptides vaccine. All results indicated that KIF20A was a promising therapeutic target for multiple cancer.

High expression of KIF20A in bladder cancer as a potential prognostic target for poor survival of renal cell carcinoma

Urinary system tumors are malignant tumors, including renal cancer and bladder cancer. however, molecular target of them remains unclear. GSE14762 and GSE53757 were downloaded from GEO database to screen differentially expressed genes (DEGs). Weighted gene co-expression network analysis was performed. Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes were used for enrichment analysis. Gene ontology and Kyoto encyclopedia of genes and genomes analyses were performed on whole genome, as formulated by gene set enrichment analysis. Survival analysis was also performed. Comparative toxicogenomics database was used to identify diseases most associated with hub genes. A total of 1517 DEGs were identified. DEGs were mainly enriched in cancer pathway, HIF-1 signaling pathway, organic acid metabolism, glyoxylate and dicarboxylate metabolism, and protein homodimerization activity. Ten hub genes (TPX2, ASPM, NUSAP1, RAD51AP1, CCNA2, TTK, PBK, MELK, DTL, kinesin family member 20A [KIF20A]) were obtained, which were up-regulated in tumor tissue. The expression of KIF20A was related with the overall survival of renal and bladder cancer. KIF20A was up-regulated in the tumor tissue, and might worsen the overall survival of bladder and kidney cancer. KIF20A could be a novel biomarker of bladder and kidney cancer.

An evaluation of KIF20A as a prognostic factor and therapeutic target for lung adenocarcinoma using integrated bioinformatics analysis

The identification of prognostic and therapeutic biomarkers is essential to reduce morbidity and mortality from lung adenocarcinoma (LUAD). This study aimed to identify a reliable prognostic and therapeutic biomarker for LUAD using integrated bioinformatics. Based on the cancer genome atlas (TCGA) and genome-tissue expression (GTEx) analyses, KIF20A has been identified as the hub gene. Following validation using a series of cohorts, survival analysis, meta-analysis, and univariate Cox analysis was conducted. ESTIMATE and CIBERSORT algorithms were then used to study the association of KIF20A with the tumor microenvironment (TME) and the percentage of tumor-infiltrating immune cells (TICs). In vitro experiments were conducted to determine the function of KIF20A. Finally, there was a negative association between the expression of the KIF20A and overall survival, progression-free survival, and disease-free survival, which was confirmed by meta-analysis and COX analysis. Furthermore, KIF20A also had a potential role of altering the TME and TICs proportions in LUAD. Validations in vitro were performed on A549 and PC-9 cell lines, and we found that the knockdown of KIF20A exhibited inhibitory effects on cell proliferation, resulted in cell cycle arrest during the G2/M phase, and induced cellular apoptosis. Our study demonstrated that KIF20A could be utilized as a reliable prognostic marker and treatment target for LUAD. However, further studies are required to validate these findings.

KDELR2-KIF20A axis facilitates bladder cancer growth and metastasis by enhancing Golgi-mediated secretion

Background

Bladder cancer (BCa) is a fatal form of cancer worldwide associated with a poor prognosis. Identifying novel drivers of growth and metastasis hold therapeutic potential for the disease. Transport homeostasis between the endoplasmic reticulum and Golgi and the secretion of matrix metalloproteinases (MMPs) mediated by Golgi have been reported to be closely associated with tumor progression. However, to date, mechanistic studies remain limited.

Results

Here, we identified KDELR2 as a potential risk factor with prognostic value in patients with BCa, especially those harbouring the KDELR2 amplification. In addition, we found that KDELR2 is a regulator of BCa cell proliferation and tumorigenicity based on bioinformatic analysis with functional studies. Mechanistically, we revealed that KDELR2 could regulate the expression of KIF20A, thus stimulating the expression of MMP2, MMP9 and MKI67. Functionally, the overexpression of KDELR2 and KIF20A markedly promoted proliferation, migration, and invasion in vitro and enhanced tumor growth in vivo, while knockdown of KDELR2 and KIF20A exerted the opposite effects. And the overexpression of KDELR2 also enhanced lymph node metastasis in vivo.

Conclusions

Collectively, our findings clarified a hitherto unexplored mechanism of KDELR2-KIF20A axis in increasing Golgi-mediated secretion of MMPs to drive tumor progression in BCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12575-022-00174-y.

KIF20A promotes the development of fibrosarcoma via PI3K-Akt signaling pathway

Adult fibrosarcoma is an aggressive subtype of soft tissue sarcoma (STS), in which high expression of KIF20A indicates a poor prognosis. However, the precise role of KIF20A in fibrosarcoma progression remains unknown. In this study, we initially examined KIF20A expression and function in the human fibrosarcoma cell line HT-1080. The results showed that KIF20A was highly expressed in HT-1080, knockdown of KIF20A impaired cell proliferation, migration, invasion and induced G2/M arrest and cell apoptosis. Transcriptome study suggested that PI3K-Akt signal pathway was involved in these biological changes. We confirmed that PI3K-Akt and NF-κB signaling pathways were impaired after the down-regulation of KIF20A, which can be reversed by the Akt activator SC79 in HT-1080 in vitro. In a xenograft mouse model, knockdown of KIF20A inhibited tumor growth, Ki67 expression and liver metastasis. Taken together, our results suggested that KIF20A promoted fibrosarcoma progression via PI3K-Akt signaling pathway and might be a potential therapeutic target for fibrosarcoma.

Ribonucleotide reductase subunit M2 promotes proliferation and epithelial-mesenchymal transition via the JAK2/STAT3 signaling pathway in retinoblastoma

Retinoblastoma (RB) is an intraocular malignant tumor that often occurs in children. Along with the improvement of treatment strategies, the cure rate of RB has increased significantly. However, the treatment of advanced and recurrent RB remains as a critical challenge. Therefore, studying the molecular mechanisms underlying the progression of RB is essential for the development of novel and effective therapeutic strategies. Through the analysis of a previously published microarray study, we found that ribonucleotide reductase subunit M2 (RRM2) was highly expressed in RB tissues as compared to normal tissues. The purpose of this study is to clarify the role and mechanism of RRM2 in regulating the progression of RB. We first demonstrated that RRM2 expression level in RB tissues and cell lines was significantly higher when compared to that in normal retinal tissue and cell lines, and high RRM2 expression level was associated with a poorer overall survival of patients. In RB cells, RRM2 overexpression promoted cell proliferation, migration, invasion and epithelial-mesenchymal transformation (EMT), while RRM2 silencing suppressed these biological features. Silencing RRM2 reduced the activation of Janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) signaling pathway, and the presence of JAK2/STAT3 signaling pathway inhibitor INCB attenuated the effect of RRM2 overexpression. Collectively, our data indicate that RRM2 promotes the progression of RB by activating JAK2/STAT3 signaling pathway. Targeting RRM2/JAK2/STAT3 axis lays a theoretical foundation for the formulation of novel RB therapy.

Identification of Key Pathways and Genes in SARS-CoV-2 Infecting Human Intestines by Bioinformatics Analysis

COVID-19 is a serious infectious disease that has recently swept the world, and research on its causative virus, SARS-CoV-2, remains insufficient. Therefore, this study uses bioinformatics analysis techniques to explore the human digestive tract diseases that may be caused by SARS-CoV-2 infection. The gene expression profile data set, numbered GSE149312, is from the Gene Expression Omnibus (GEO) database and is divided into a 24-h group and a 60-h group. R software is used to analyze and screen out differentially expressed genes (DEGs) and then gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses are performed. In KEGG, the pathway of non-alcoholic fatty liver disease exists in both the 24-h group and 60-h group. STRING is used to establish a protein–protein interaction (PPI) network, and Cytoscape is then used to visualize the PPI and define the top 12 genes of the node as the hub genes. Through verification, nine statistically significant hub genes are identified: AKT1, TIMP1, NOTCH, CCNA2, RRM2, TTK, BUB1B, KIF20A, and PLK1. In conclusion, the results of this study can provide a certain direction and basis for follow-up studies of SARS-CoV-2 infection of the human digestive tract and provide new insights for the prevention and treatment of diseases caused by SARS-CoV-2.

A Novel Risk Factor Model Based on Glycolysis-Associated Genes for Predicting the Prognosis of Patients With Prostate Cancer

Background

Prostate cancer (PCa) is one of the most prevalent cancers among males, and its mortality rate is increasing due to biochemical recurrence (BCR). Glycolysis has been proven to play an important regulatory role in tumorigenesis. Although several key regulators or predictors involved in PCa progression have been found, the relationship between glycolysis and PCa is unclear; we aimed to develop a novel glycolysis-associated multifactor prediction model for better predicting the prognosis of PCa.

Methods

Differential mRNA expression profiles derived from the Cancer Genome Atlas (TCGA) PCa cohort were generated through the “edgeR” package. Glycolysis-related genes were obtained from the GSEA database. Univariate Cox and LASSO regression analyses were used to identify genes significantly associated with disease-free survival. ROC curves were applied to evaluate the predictive value of the model. An external dataset derived from Gene Expression Omnibus (GEO) was used to verify the predictive ability. Glucose consumption and lactic production assays were used to assess changes in metabolic capacity, and Transwell assays were used to assess the invasion and migration of PC3 cells.

Results

Five glycolysis-related genes were applied to construct a risk score prediction model. Patients with PCa derived from TCGA and GEO (GSE70770) were divided into high-risk and low-risk groups according to the median. In the TCGA cohort, the high-risk group had a poorer prognosis than the low-risk group, and the results were further verified in the GSE70770 cohort. In vitro experiments demonstrated that knocking down HMMR, KIF20A, PGM2L1, and ANKZF1 separately led to less glucose consumption, less lactic production, and inhibition of cell migration and invasion, and the results were the opposite with GPR87 knockdown.

Conclusion

The risk score based on five glycolysis-related genes may serve as an accurate prognostic marker for PCa patients with BCR.

Low expression of KIF20A suppresses cell proliferation, promotes chemosensitivity and is associated with better prognosis in HCC

This study analysed the microarray datasets from Gene Expression Omnibus (GEO) database, and aimed to identify novel potential hub genes associated with the progression of HCC via bioinformatics analysis and experimental validation. The common differentially expressed genes (DEGs) from five GEO datasets were screened using GEO2R tool. The expression and survival analysis of hub genes in HCC were performed using Gene Expression Profiling Interactive Analysis, UALCAN and Kaplan-Meier plotter tools. In vitro functional assays were used to determine the caspase-3, -9, cell proliferation and chemo-sensitivity of HCC cells. A total of 177 common DEGs were identified between normal liver and HCC tissues among these datasets. Functional enrichment and PPI network analysis identified 22 hub genes from the common DEGs. The mRNA expression of 22 hub genes was all significantly up-regulated in HCC tissues compared to that in normal liver tissues. Further survival analysis showed that 10 hub genes predicted poor prognosis of patients with HCC. More importantly, the in vitro functional studies demonstrated that KIF20A knockdown suppressed the HCC cell proliferation and promoted the chemosensitivity of HCC cells to cisplatin and sorafenib. In conclusion, the present study identified a total of 177 common DEGs among 5 GEO microarray datasets and found that 10 hub genes could predict the poor prognosis of patients with HCC using the comprehensive bioinformatics analysis. Furthermore, KIF20A silence suppressed cell proliferation and enhanced chemosensitivity in HCC cells. Further studies may be required to determine the mechanistic role of these hub genes in HCC progression.

KIF18B as a regulator in tumor microenvironment accelerates tumor progression and triggers poor outcome in hepatocellular carcinoma

BACKGROUND

The tumor microenvironment plays an important role in the progression and recurrence of tumors and immunotherapy outcomes. The use of immune checkpoint blockers to improve the overall survival rate of patients with advanced hepatocellular carcinoma has yielded inconsistent outcomes. We examined the tumor microenvironment-related genes for their clinical significance and biological functions in hepatocellular carcinoma.

METHODS

Bioinformatic analysis was performed to screen the differentially expressed genes and to identify the core gene of the tumor microenvironment in hepatocellular carcinoma. The expression of KIF18B in hepatocellular carcinoma cell lines and tumor samples was determined using western blotting, quantitative real-time polymerase chain reaction, and immunohistochemistry. The malignancy-promoting ability of KIF18B was evaluated using Cell Counting Kit-8, colony formation, cell proliferation, migration and invasion, and xenograft tumor assays.

RESULTS

KIF18B was identified as one of the core genes in the hepatocellular carcinoma microenvironment and was significantly associated with infiltrating immune cell subtypes and tumor cell stemness. Upregulation of KIF18B was associated with poor clinicopathological characteristics and poor patient outcomes; its downregulation inhibited the proliferation ability of hepatocellular carcinoma cells, which was consistent with the findings of in vivo experiments. Knockdown of KIF18B inhibited epithelial-mesenchymal transition which reduced the migration and invasion abilities of tumor cells. A pulmonary metastasis model confirmed that the downregulation of KIF18B inhibited hepatocellular carcinoma cell metastasis in vivo.

CONCLUSION

KIF18B could be a useful marker for determining the treatment outcomes of immune checkpoint blockers in the context of hepatocellular carcinoma.

ASPM is a Novel Candidate Gene Associated with Colorectal Cancer Cell Growth

Colorectal cancer (CRC) is one of the most prevalent diseases worldwide; however, the molecular mechanisms involved in CRC remain unclear. Thus, we aimed to explore a novel biomarker for CRC. In this study, we screened 361 differentially expressed genes; 152 downregulated genes; and 209 upregulated genes) through analysis of the GSE44861, GSE110223, GSE110224, and GSE113513 CRC datasets. Next, ASPM, CCNA2, CCNB1, CEP55, KIF20A, MAD2L1, MELK, RRM2, TOP2A, TPX2, TRIP13, and TTK were identified as hub genes associated with the cell cycle in CRC through comprehensive bioinformatics analysis using the Cytoscape and Metascape software, the Database for Annotation, Visualization, and Integrated Discovery (DAVID), and the Oncomine and Gene Expression Profiling Interactive Analysis 2 (GEPIA2) databases. Furthermore, ASPM mRNA expression in CRC tissues was verified in Oncomine, The Cancer Genome Atlas and our data, and ASPM was found to be significantly upregulated in CRC tissues compared with that in the noncancer colon tissues. Functionally, we showed that overexpression of ASPM significantly promoted the proliferation and inhibited apoptosis; silencing of ASPM suppressed the proliferation of CRC cells by affecting the cell cycle G1/S transition by reducing cyclin E1 expression, and inducing apoptosis. Overall, our findings indicated that ASPM plays a crucial role in the regulation of CRC cell proliferation, and ASPM is a potential candidate diagnostic tool and therapeutic target for CRC.

KIF11 is upregulated in colorectal cancer and silencing of it impairs tumor growth and sensitizes colorectal cancer cells to oxaliplatin via p53/GSK3β signaling

Colorectal cancer (CRC) is the most frequently diagnosed cancer of the digestive tract. Chemotherapy drugs such as oxaliplatin are frequently administered to CRC patients diagnosed with advanced or metastatic disease. A deep understanding of the molecular mechanism underlying CRC tumorigenesis and identification of optimal biomarkers for estimating chemotherapy sensitivity are essential for the treatment of CRC. Numerous members of the kinesin family are dysregulated in cancers, contributing to tumorigenesis, metastasis and drug resistance. KIF11 is a key component of the bipolar spindle and is highly expressed in several cancer types. We analyzed KIF11 expression in clinical samples by Western blotting and qRT-PCR and explored its role and mechanism in CRC growth and sensitivity to oxaliplatin via detection of the phosphorylation profile of kinases and gain-and-loss-of-function assays. We found that KIF11 was upregulated in CRC tissues and was associated with advanced clinical stage and vessel invasion and that knockdown of KIF11 led to tumor growth arrest and increased sensitivity to oxaliplatin via enhanced DNA damage and apoptosis. Mechanistically, aberrantly activated p53 signaling or possibly deactivated GSK3β signaling was responsible for KIF11 knockdown-mediated effects in CRC cells. Thus, our data firmly demonstrated that KIF11 could serve as a potential oncogene and proper biomarker for assessing oxaliplatin sensitivity in CRC.

A novel 10 glycolysis-related genes signature could predict overall survival for clear cell renal cell carcinoma

Background

The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration.

Methods

Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature.

Results

Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature.

Conclusions

A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients’ survival.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08111-0.

Six genes involved in prognosis of hepatocellular carcinoma identified by Cox hazard regression

BACKGROUND

Hepatocellular carcinoma (HCC), derived from hepatocytes, is the main histological subtype of primary liver cancer and poses a serious threat to human health due to the high incidence and poor prognosis. This study aimed to establish a multigene prognostic model to predict the prognosis of patients with HCC.

RESULTS

Gene expression datasets (GSE121248, GSE40873, GSE62232) were used to identify differentially expressed genes (DEGs) between tumor and adjacent or normal tissues, and then hub genes were screened by protein-protein interaction (PPI) network and Cytoscape software. Seventeen genes among hub genes were significantly associated with prognosis and used to construct a prognostic model through COX hazard regression analysis. The predictive performance of this model was evaluated with TCGA data and was further validated with independent dataset GSE14520. Six genes (CDKN3, ZWINT, KIF20A, NUSAP1, HMMR, DLGAP5) were involved in the prognostic model, which separated HCC patients from TCGA dataset into high- and low-risk groups. Kaplan-Meier (KM) survival analysis and risk score analysis demonstrated that low-risk group represented a survival advantage. Univariate and multivariate regression analysis showed risk score could be an independent prognostic factor. The receiver operating characteristic (ROC) curve showed there was a better predictive power of the risk score than that of other clinical indicators. At last, the results from GSE14520 demonstrated the reliability of this prognostic model in some extent.

CONCLUSION

This prognostic model represented significance for prognosis of HCC, and the risk score according to this model may be a better prognostic factor than other traditional clinical indicators.

Nrf2 signaling pathway in cisplatin chemotherapy: Potential involvement in organ protection and chemoresistance

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a vital transcription factor and its induction is of significant importance for protecting against oxidative damage. Increased levels of Reactive Oxygen Species (ROS) stimulate Nrf2 signaling, enhancing the activity of antioxidant enzymes such as catalase, superoxide dismutase and glutathione peroxidase. These enzymes are associated with retarding oxidative stress. On the other hand, Nrf2 activation in cancer cells is responsible for the development of chemoresistance due to disrupting oxidative mediated-cell death by reducing ROS levels. Cisplatin (CP), cis-diamminedichloroplatinum(II), is a potent anti-tumor agent extensively used in cancer therapy, but its frequent application leads to the development of chemoresistance as well. In the present study, association of Nrf2 signaling with chemoresistance to CP and protection against its deleterious effects is discussed. Anti-tumor compounds, mainly phytochemicals, retard chemoresistance by suppressing Nrf2 signaling. Upstream mediators such as microRNAs can regulate Nrf2 expression during CP chemotherapy regimens. Protection against side effects of CP is mediated via activating Nrf2 signaling and its downstream targets activating antioxidant defense system. Protective agents that activate Nrf2 signaling, can ameliorate CP-mediated ototoxicity, nephrotoxicity and neurotoxicity. Reducing ROS levels and preventing cell death are the most important factors involved in alleviating CP toxicity upon Nrf2 activation. As pre-clinical experiments advocate the role of Nrf2 in chemoprotection and CP resistance, translating these findings to the clinic can provide a significant progress in treatment of cancer patients.

Identification of potential markers for differentiating epithelial ovarian cancer from ovarian low malignant potential tumors through integrated bioinformatics analysis

Background

Epithelial ovarian cancer (EOC), as a lethal malignancy in women, is often diagnosed as advanced stages. In contrast, intermediating between benign and malignant tumors, ovarian low malignant potential (LMP) tumors show a good prognosis. However, the differential diagnosis of the two diseases is not ideal, resulting in delays or unnecessary therapies. Therefore, unveiling the molecular differences between LMP and EOC may contribute to differential diagnosis and novel therapeutic and preventive policies development for EOC.

Methods

In this study, three microarray data (GSE9899, GSE57477 and GSE27651) were used to explore the differentially expressed genes (DEGs) between LMP and EOC samples. Then, 5 genes were screened by protein–protein interaction (PPI) network, receiver operating characteristic (ROC), survival and Pearson correlation analysis. Meanwhile, chemical-core gene network construction was performed to identify the potential drugs or risk factors for EOC based on 5 core genes. Finally, we also identified the potential function of the 5 genes for EOC through pathway analysis.

Results

Two hundred thirty-four DEGs were successfully screened, including 81 up-regulated genes and 153 down-regulated genes. Then, 5 core genes (CCNB1, KIF20A, ASPM, AURKA, and KIF23) were identified through PPI network analysis, ROC analysis, survival and Pearson correlation analysis, which show better diagnostic efficiency and higher prognostic value for EOC. Furthermore, NetworkAnalyst was used to identify top 15 chemicals that link with the 5 core genes. Among them, 11 chemicals were potential drugs and 4 chemicals were risk factors for EOC. Finally, we found that all 5 core genes mainly regulate EOC development via the cell cycle pathway by the bioinformatic analysis.

Conclusion

Based on an integrated bioinformatic analysis, we identified potential biomarkers, risk factors and drugs for EOC, which may help to provide new ideas for EOC diagnosis, condition appraisal, prevention and treatment in future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00794-0.

Anthraquinone derivative C10 inhibits proliferation and cell cycle progression in colon cancer cells via the Jak2/Stat3 signaling pathway

Since its discovery, anthraquinone has become very valuable as a lead compound in the development of anti-cancer drugs. Previously, we designed and synthesized a new type of amide anthraquinone derivative (1-nitro-2-acylanthraquinone glycine, C10) with good activity against colon cancer. However, its effect and the underlying mechanism are unclear. In this study, C10 significantly inhibited the proliferation of HCT116 and HT29 colon cancer cells by blocking the cell cycle at the G2/M phase. C10 also plays a role in cell cycle arrest by reducing the protein and gene expression levels of cyclin B1 and its downstream signaling molecule cyclin-dependent kinase (CDK1). In addition, molecular docking studies showed that C10 has high affinity for Jak2, the first target in the cell cycle-related Jak2/Stat3 signaling pathway. Furthermore, C10 downregulated the expression of Jak2/Stat3 signaling pathway-related signaling molecules proteins and genes, and up-regulated the expression of PIAS-3, the upstream signaling molecule of Stat3, thereby down-regulating Stat3 phosphorylation. C10 reversed the expression of Jak2/Stat3 signaling pathway-related molecules activated by IL-6. Overall, our results indicate for the first time that C10 induces cell cycle arrest and inhibits cell proliferation by inhibiting the Jak2/Stat3 signaling pathway. This study provides new insights into the potential role of Jak2/Stat3 in the regulating cell cycle-related signaling pathways that mediate the inhibitory effects of C10 on colon cancer cell proliferation.

Aberrant KIF23 expression is associated with adverse clinical outcome and promotes cellular malignant behavior through the Wnt/β-catenin signaling pathway in Colorectal Cancer

Purpose: The aim of the present study was to reveal the clinicopathological significance and prognostic role of kinesin family member 23 (KIF23) in colorectal cancer (CRC) and characterize its biological function and the underlying mechanisms.

Methods: Bioinformatics analysis, immunohistochemistry, Western blot and qRT-PCR were utilized to investigate the expression of KIF23 in CRC tissues. The CCK-8 assay, wound healing assay and Matrigel assay were used to detect cell proliferation, migration and invasion in vitro. Western blot, immunofluorescence staining and cell function experiment were performed to explore the underlying mechanism.

Results: The overexpression of KIF23 was associated with T stage, N stage, M stage and TNM stage, and CRC patients with high KIF23 expression had a worse prognosis. KIF23 knockdown inhibits CRC cells proliferation, migration and invasion in vitro. The mechanism study determined that KIF23 activates the Wnt/β-catenin signaling pathway by promoting the nuclear translocation of β-catenin to regulate the malignant behavior of CRC cells.

Conclusion: These results suggest that KIF23 may act as a putative oncogene and a potential therapeutic target in CRC.

Upregulation of KIF20A promotes tumor proliferation and invasion in renal clear cell carcinoma and is associated with adverse clinical outcome

Extensive research has revealed the pivotal role of kinesin family member 20A (KIF20A) in cancer. However, its latent involvement in renal clear cell carcinoma (ccRCC) still remains unclear. Thus, here we explored the role of KIF20A in ccRCC. For this, a series of software including R (v. 3.6.1), SPSS (v. 23), ImageJ and FlowJo were used for the analyses. Open-access data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases. Weighted Gene Co-expression Network Analysis (WGCNA) was used for module gene identification. In vitro results indicated that KIF20A expression is up-regulated in ccRCC tissue. KIF20A knockdown was able to inhibite cell proliferation and invasion of kidney A498 and Caki-1 cells. Meanwhile, KIF20A showed a strong association with immune infiltration. Particularly, KIF20A had a strong positive correlation with Th2 cells, Treg cells and Macrophages, but a negative correlation with Th17 cells, Mast cells and NK cells. These correlations may suggest the use of KIF20A as an underlying immunotherapy target in ccRCC. Our data indicated that KIF20A may promote cell invasion and proliferation in ccRCC, thus serving as an independent tumor marker and a putative therapeutic target.

CTCF promotes colorectal cancer cell proliferation and chemotherapy resistance to 5-FU via the P53-Hedgehog axis

CTCF is overexpressed in several cancers and plays crucial roles in regulating aggressiveness, but little is known about whether CTCF drives colorectal cancer progression. Here, we identified a tumor-promoting role for CTCF in colorectal cancer. Our study demonstrated that CTCF was upregulated in colorectal cancer specimens compared with adjacent noncancerous colorectal tissues. The overexpression of CTCF promoted colorectal cancer cell proliferation and tumor growth, while the opposite effects were observed in CTCF knockdown cells. Increased GLI1, Shh, PTCH1, and PTCH2 levels were observed in CTCF-overexpressing cells using western blot analyses. CCK-8 and apoptosis assays revealed that 5-fluorouracil chemosensitivity was negatively associated with CTCF expression. Furthermore, we identified that P53 is a direct transcriptional target gene of CTCF in colorectal cancer. Western blot and nuclear extract assays showed that inhibition of P53 can counteract Hedgehog signaling pathway repression induced by CTCF knockdown. In conclusion, we uncovered a crucial role for CTCF regulation that possibly involves the P53-Hedgehog axis and highlighted the clinical utility of colorectal cancer-specific potential therapeutic target as disease progression or clinical response biomarkers.