KIF2C: a novel link between Wnt/β-catenin and mTORC1 signaling in the pathogenesis of hepatocellular carcinoma

KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker

KIF2C/MCAK (KIF2C) is the most well-characterized member of the kinesin-13 family, which is critical in the regulation of microtubule (MT) dynamics during mitosis, as well as interphase. This systematic review briefly describes the important structural elements of KIF2C, its regulation by multiple molecular mechanisms, and its broad cellular functions. Furthermore, it systematically summarizes its oncogenic potential in malignant progression and performs a meta-analysis of its prognostic value in cancer patients. KIF2C was shown to be involved in multiple crucial cellular processes including cell migration and invasion, DNA repair, senescence induction and immune modulation, which are all known to be critical during the development of malignant tumors. Indeed, an increasing number of publications indicate that KIF2C is aberrantly expressed in multiple cancer entities. Consequently, we have highlighted its involvement in at least five hallmarks of cancer, namely: genome instability, resisting cell death, activating invasion and metastasis, avoiding immune destruction and cellular senescence. This was followed by a systematic search of KIF2C/MCAK's expression in various malignant tumor entities and its correlation with clinicopathologic features. Available data were pooled into multiple weighted meta-analyses for the correlation between KIF2Chigh protein or gene expression and the overall survival in breast cancer, non-small cell lung cancer and hepatocellular carcinoma patients. Furthermore, high expression of KIF2C was correlated to disease-free survival of hepatocellular carcinoma. All meta-analyses showed poor prognosis for cancer patients with KIF2Chigh expression, associated with a decreased overall survival and reduced disease-free survival, indicating KIF2C's oncogenic potential in malignant progression and as a prognostic marker. This work delineated the promising research perspective of KIF2C with modern in vivo and in vitro technologies to further decipher the function of KIF2C in malignant tumor development and progression. This might help to establish KIF2C as a biomarker for the diagnosis or evaluation of at least three cancer entities.

KIF2C as a potential therapeutic target: insights from lung adenocarcinoma subtype classification and functional experiments

Objective: this study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression. Methods: high-expression genes linked to overall survival (OS) and progression-free interval (PFI) were selected from the TCGA-LUAD dataset. Consensus clustering analysis categorized lung adenocarcinoma (LUAD) patients into two subtypes, C1 and C2, which were compared using clinical, drug sensitivity, and immunotherapy analyses. A random forest algorithm pinpointed KIF2C as a prognostic hub gene, and its functional impact was assessed through various assays and in vivo experiments. Results: The study identified 163 key genes and distinguished two LUAD subtypes with differing OS, PFI, pathological stages, drug sensitivity, and immunotherapy response. KIF2C, highly expressed in the C2 subtype, was associated with poor prognosis, promoting cancer cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), with knockdown reducing tumor growth in mice. Conclusion: The research delineates distinct LUAD subtypes with significant clinical implications and highlights KIF2C as a potential therapeutic target for personalized treatment in LUAD.

Role of microRNAs in tumor progression by regulation of kinesin motor proteins

Aberrant cell proliferation is one of the main characteristics of tumor cells that can be affected by many cellular processes and signaling pathways. Kinesin superfamily proteins (KIFs) are motor proteins that are involved in cytoplasmic transportations and chromosomal segregation during cell proliferation. Therefore, regulation of the KIF functions as vital factors in chromosomal stability is necessary to maintain normal cellular homeostasis and proliferation. KIF deregulations have been reported in various cancers. MicroRNAs (miRNAs) and signaling pathways are important regulators of KIF proteins. MiRNAs have key roles in regulation of the cell proliferation, migration, and apoptosis. In the present review, we discussed the role of miRNAs in tumor biology through the regulation of KIF proteins. It has been shown that miRNAs have mainly a tumor suppressor function via the KIF targeting. This review can be an effective step to introduce the miRNAs/KIFs axis as a probable therapeutic target in tumor cells.

KIF2C is a critical regulator for malignant progression of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a significant cause of mortality, while the underlying mechanism remains unclear. Our studies have revealed that KIF2C plays a crucial role in tumor proliferation and metastasis in HNSCC. The results demonstrate that KIF2C is highly expressed at both the mRNA and protein levels and is closely associated with lymph node metastasis. The gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses indicate that the differentially expressed genes are enriched in processes or pathways related to cell adhesion and cell mitosis in HNSCC. Moreover, the established protein-protein interaction network identifies KIF2C as a potential hub gene in HNSCC. Knockdown of KIF2C has been demonstrated to significantly reduce cell migration and invasion ability, leading to cell cycle arrest, a high proportion of abnormal cell apoptosis, and cell chromosome division mismatches in the HNSCC cell line. Downstream genes such as PDGFA, EGFR, TP63, SNAI2, KRT5, and KRT14 were found to be down-regulated, and multiple critical pathways, including mTOR, ERK, and PI3K-AKT pathways, were inactivated as a result of KIF2C knockdown. These findings provide strong evidence for the crucial role of KIF2C in HNSCC and suggest that targeting KIF2C may be a promising therapeutic strategy for this disease. Knockdown of KIF2C has been shown to significantly inhibit tumor proliferation in nude mice, demonstrating the potential therapeutic role of KIF2C in HNSCC treatment.

ESCO2's oncogenic role in human tumors: a pan-cancer analysis and experimental validation

PURPOSE

Establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2) is involved in the mitotic S-phase adhesins acetylation and is responsible for bridging two sister chromatids. However, present ESCO2 cancer research is limited to a few cancers. No systematic pan-cancer analysis has been conducted to investigate its role in diagnosis, prognosis, and effector function.

METHODS

We thoroughly examined the ESCO2 carcinogenesis in pan-cancer by combining public databases such as The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), UALCAN and Tumor Immune Single-cell Hub (TISCH). The analysis includes differential expression analysis, survival analysis, cellular effector function, gene mutation, single cell analysis, and tumor immune cell infiltration. Furthermore, we confirmed ESCO2's impacts on clear cell renal cell carcinoma (ccRCC) cells' proliferative and invasive capacities in vitro.

RESULTS

In our study, 30 of 33 cancer types exhibited considerably greater levels of ESCO2 expression in tumor tissue using TCGA and GTEx databases, whereas acute myeloid leukemia (LAML) exhibited significantly lower levels. Kaplan-Meier survival analyses in adrenocortical carcinoma (ACC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), mesothelioma (MESO), and pancreatic adenocarcinoma (PAAD) demonstrated that tumor patients with high ESCO2 expression have short survival periods. However, in thymoma (THYM), colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ), ESCO2 was a favorable prognostic factor. Moreover, ESCO2 expression positively correlates with tumor stage and tumor size in several cancers, including LIHC, KIRC, KIRP and LUAD. Function analysis revealed that ESCO2 participates in mitosis, cell cycle, DNA damage repair, and other processes. CDK1 was identified as a downstream gene regulated by ESCO2. Furthermore, ESCO2 might also be implicated in immune cell infiltration. Finally, ESCO2'S knockdown significantly inhibited the A498 and T24 cells' proliferation, invasion, and migration.

CONCLUSIONS

In conclusion, ESCO2 is a possible pan-cancer biomarker and oncogene that can reliably predict the prognosis of cancer patients. ESCO2 was also implicated in the cell cycle and proliferation regulation. In a nutshell, ESCO2 is a therapeutically viable and dependable target.

The platelet-related genes associated with the prognosis of HCC by regulating cycling T cell and prolif-TAMs

Accumulating evidence highlighted the important roles of platelets in the prognosis and progression of various tumors. Nevertheless, the role of platelet-related genes (PRGs) in HCC remains limited. In this work, 92 differentially expressed PRGs were described in HCC using TCGA and ICGC databases. Then, based on the different expressions of PRGs, we explored two subtypes and developed the PRGs prognostic signature in HCC. The PRGs signature was an independent prognosis factor associated with immune cell infiltration in HCC. Furthermore, two external validation sets verified the expression and prognosis of the PRGs signature gene in HCC. Finally, scRNA-seq analysis demonstrated that the signature genes (CENPE and KIF2C) were mainly expressed in cycling T cells and prolif-TAMs. Enrichment analysis showed that CENPE and KIF2C regulated the cell cycle and p53 pathways in these cells. In conclusion, this study builds the PRGs-related risk signature of HCC and reveals the potential mechanism by which these signature genes regulate the immune microenvironment in HCC.

The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).

Silencing of KIF2C enhances the sensitivity of hepatocellular carcinoma cells to cisplatin through regulating the PI3K/AKT/MAPK signaling pathway

In the treatment of unresectable advanced hepatocellular carcinoma (HCC), cisplatin is administered transhepatic arterially for local treatment, but the clinical application of cisplatin drugs is frequently hindered by the emergence of drug resistance. Kinesin family member 2C( KIF2C ) has been shown as oncogene in a variety of tumors. Nevertheless, its effect on cisplatin sensitivity has yet to be ascertained. Herein, we aim to investigate the impact of the KIF2C gene on cisplatin sensitivity within HCC and the plausible underlying molecular mechanism. We examined the expression level of the KIF2C gene in HCC cells by real-time quantitative reverse transcription PCR and Western blot analysis, and analyzed bioinformatically by The Gene Expression Omnibus database and The Cancer Genome Atlas database. The KIF2C gene was silenced using the small interfering RNA technology, and its effect on cisplatin drug sensitivity in HCC cells was evaluated by flow cytometry, cell proliferation, cell migration, and invasion assays. Our results indicated that KIF2C was highly expressed in HCC cells. KIF2C silencing inhibits HCC cell proliferation, migration and invasion, promotes apoptosis, and keeps the cell cycle in G2 phase. In addition, KIF2C silencing enhanced the sensitivity of HCC cells to cisplatin. KIF2C silencing down-regulates the expression levels of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT) and mitogen-activated protein kinase 3 (MAPK3) proteins. In conclusion, KIF2C silencing amplifies the sensitivity of HCC cells to cisplatin by regulating the PI3K/AKT/MAPK signaling pathway. Consequently, targeting KIF2C shows great application potential as a strategy for enhancing the effectiveness of HCC treatment.

WNT/β-catenin signaling in hepatocellular carcinoma: The aberrant activation, pathogenic roles, and therapeutic opportunities

Hepatocellular carcinoma (HCC) is a liver cancer, highly heterogeneous both at the histopathological and molecular levels. It arises from hepatocytes as the result of the accumulation of numerous genomic alterations in various signaling pathways, including canonical WNT/β-catenin, AKT/mTOR, MAPK pathways as well as signaling associated with telomere maintenance, p53/cell cycle regulation, epigenetic modifiers, and oxidative stress. The role of WNT/β-catenin signaling in liver homeostasis and regeneration is well established, whereas in development and progression of HCC is extensively studied. Herein, we review recent advances in our understanding of how WNT/β-catenin signaling facilitates the HCC development, acquisition of stemness features, metastasis, and resistance to treatment. We outline genetic and epigenetic alterations that lead to activated WNT/β-catenin signaling in HCC. We discuss the pivotal roles of CTNNB1 mutations, aberrantly expressed non-coding RNAs and complexity of crosstalk between WNT/β-catenin signaling and other signaling pathways as challenging or advantageous aspects of therapy development and molecular stratification of HCC patients for treatment.

Hindbrain boundaries as niches of neural progenitor and stem cells regulated by the extracellular matrix proteoglycan chondroitin sulphate

The interplay between neural progenitors and stem cells (NPSCs), and their extracellular matrix (ECM) is a crucial regulatory mechanism that determines their behavior. Nonetheless, how the ECM dictates the state of NPSCs remains elusive. The hindbrain is valuable to examine this relationship, as cells in the ventricular surface of hindbrain boundaries (HBs), which arise between any two neighboring rhombomeres, express the NPSC marker Sox2, while being surrounded with the membrane-bound ECM molecule chondroitin sulphate proteoglycan (CSPG), in chick and mouse embryos. CSPG expression was used to isolate HB Sox2+ cells for RNA-sequencing, revealing their distinguished molecular properties as typical NPSCs, which express known and newly identified genes relating to stem cells, cancer, the matrisome and cell cycle. In contrast, the CSPG- non-HB cells, displayed clear neural-differentiation transcriptome. To address whether CSPG is significant for hindbrain development, its expression was manipulated in vivo and in vitro. CSPG manipulations shifted the stem versus differentiation state of HB cells, evident by their behavior and altered gene expression. These results provide further understanding of the uniqueness of hindbrain boundaries as repetitive pools of NPSCs in-between the rapidly growing rhombomeres, which rely on their microenvironment to maintain their undifferentiated state during development.

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

BACKGROUNDS

Poorly regulated mitosis and chromosomal instability are common characteristics in malignant tumor cells. Kinesin family member 2 C (KIF2C), also known as mitotic centromere-associated kinesin (MCAK) is an essential component during mitotic regulation. In recent years, KIF2C was shown to be dysregulated in several tumors and was involved in many aspects of tumor self-regulation. Research on KIF2C may be a new direction and target for anti-tumor therapy.

OBJECT

The article aims at reviewing current literatures and summarizing the research status of KIF2C in malignant tumors as well as the oncogenic signaling pathways associated with KIF2C and its role in immune infiltration.

RESULT

In this review, we summarize the KIF2C mechanisms and signaling pathways in different malignant tumors, and briefly describe its involvement in pathways related to classical chemotherapeutic drug resistance, such as MEK/ERK, mTOR, Wnt/β-catenin, P53 and TGF-β1/Smad pathways. KIF2C upregulation was shown to promote tumor cell migration, invasion, chemotherapy resistance and inhibit DNA damage repair. It was also highly correlated with microRNAs, and CD4 +T cell and CD8 +T cell tumor immune infiltration.

CONCLUSION

This review shows that KIF2C may function as a new anticancer drug target with great potential for malignant tumor treatment and the mitigation of chemotherapy resistance.

XYA-2: a marine-derived compound targeting apoptosis and multiple signaling pathways in pancreatic cancer

Background

Pancreatic cancer is a highly aggressive and fatal disease with limited treatment options and poor prognosis for patients. This study aimed to investigate the impact of XYA-2 {N-(3,7-dimethyl-2,6-octadienyl)-2-aza-2-deoxychaetoviridin A}, a nitrogenated azaphilon previously reported from a deep-sea-derived fungus on the progression of pancreatic cancer cells.

Methods

The inhibitory effects of XYA-2 on cell proliferation, clonogenic potential, cell cycle progression, apoptosis, migration, and invasion were assessed using various assays. The CCK-8 assay, clone formation assay, flow cytometry assay, wound healing assay, and transwell assay were employed to evaluate cell proliferation, clonogenic potential, cell cycle progression, apoptosis, migration, and invasion, respectively. Moreover, we employed RNA-seq and bioinformatics analyses to uncover the underlying mechanism by which XYA-2 influences pancreatic cancer cells. The revealed mechanism was subsequently validated through qRT-PCR.

Results

Our results demonstrated that XYA-2 dose-dependently inhibited the proliferation of pancreatic cancer cells and induced cell cycle arrest and apoptosis. Additionally, XYA-2 exerted a significant inhibitory effect on the invasion and migration of cancer cells. Moreover, XYA-2 was found to regulate the expression of genes involved in multiple cancer-related pathways based on our RNA-seq and bioinformatics analysis.

Conclusion

These findings highlight the potential of XYA-2 as a promising therapeutic option for the treatment of pancreatic cancer.

Machine learning and experiments identifies SPINK1 as a candidate diagnostic and prognostic biomarker for hepatocellular carcinoma

Machine learning techniques have been widely used in predicting disease prognosis, including cancer prognosis. One of the major challenges in cancer prognosis is to accurately classify cancer types and stages to optimize early screening and detection, and machine learning techniques have proven to be very useful in this regard. In this study, we aimed at identifying critical genes for diagnosis and outcomes of hepatocellular carcinoma (HCC) patients using machine learning. The HCC expression dataset was downloaded from GSE65372 datasets and TCGA datasets. Differentially expressed genes (DEGs) were identified between 39 HCC and 15 normal samples. For the purpose of locating potential biomarkers, the LASSO and the SVM-RFE assays were performed. The ssGSEA method was used to analyze the TCGA to determine whether there was an association between SPINK1 and tumor immune infiltrates. RT-PCR was applied to examine the expression of SPINK1 in HCC specimens and cells. A series of functional assays were applied to examine the function of SPINK1 knockdown on the proliferation of HCC cells. In this study, 103 DEGs were obtained. Based on LASSO and SVM-RFE analysis, we identified nine critical diagnostic genes, including C10orf113, SPINK1, CNTLN, NRG3, HIST1H2AI, GPRIN3, SCTR, C2orf40 and PITX1. Importantly, we confirmed SPINK1 as a prognostic gene in HCC. Multivariate analysis confirmed that SPINK1 was an independent prognostic factor for overall survivals of HCC patients. We also found that SPINK1 level was positively associated with Macrophages, B cells, TFH, T cells, Th2 cells, iDC, NK CD56bright cells, Th1 cells, aDC, while negatively associated with Tcm and Eosinophils. Finally, we demonstrated that SPINK1 expression was distinctly increased in HCC specimens and cells. Functionally, silence of SPINK1 distinctly suppressed the proliferation of HCC cells via regulating Wnt/β-catenin pathway. The evidence provided suggested that SPINK1 may possess oncogenic properties by inducing dysregulated immune infiltration in HCC. Additionally, SPINK1 was identified as a novel biomarker and therapeutic target for HCC.

Wnt/β-catenin signaling activation promotes lipogenesis in the steatotic liver via physical mTOR interaction

Background and aims

Wnt/β-catenin signaling plays an important role in regulating hepatic metabolism. This study is to explore the molecular mechanisms underlying the potential crosstalk between Wnt/β-catenin and mTOR signaling in hepatic steatosis.

Methods

Transgenic mice (overexpress Wnt1 in hepatocytes, Wnt+) mice and wild-type littermates were given high fat diet (HFD) for 12 weeks to induce hepatic steatosis. Mouse hepatocytes cells (AML12) and those transfected to cause constitutive β-catenin stabilization (S33Y) were treated with oleic acid for lipid accumulation.

Results

Wnt+ mice developed more hepatic steatosis in response to HFD. Immunoblot shows a significant increase in the expression of fatty acid synthesis-related genes (SREBP-1 and its downstream targets ACC, AceCS1, and FASN) and a decrease in fatty acid oxidation gene (MCAD) in Wnt+ mice livers under HFD. Wnt+ mice also revealed increased Akt signaling and its downstream target gene mTOR in response to HFD. In vitro, increased lipid accumulation was detected in S33Y cells in response to oleic acid compared to AML12 cells reinforcing the in vivo findings. mTOR inhibition by rapamycin led to a down-regulation of fatty acid synthesis in S33Y cells. In addition, β-catenin has a physical interaction with mTOR as verified by co-immunoprecipitation in hepatocytes.

Conclusions

Taken together, our results demonstrate that β-catenin stabilization through Wnt signaling serves a central role in lipid metabolism in the steatotic liver through up-regulation of fatty acid synthesis via Akt/mTOR signaling. These findings suggest hepatic Wnt signaling may represent a therapeutic strategy in hepatic steatosis.

KIF2C promotes clear cell renal cell carcinoma progression via activating JAK2/STAT3 signaling pathway

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors that can be highly aggressive. Despite advances in the exploration of its underlying molecular biology, the clinical outcome for advanced ccRCC is still unsatisfied. Recently, more attention was paid to the functions of Kinesin family member 2C (KIF2C) in cancer progression, while the specific function of KIF2C in ccRCC has not been sufficiently elucidated. The present study aims to investigate the role of KIF2C in the progression of ccRCC and reveal potential mechanisms.

METHODS

Expression of KIF2C in ccRCC tissues and adjacent normal tissue was compared and the association of KIF2C expression level with tumor grade, stage, and metastasis were analyzed using online web tool. Kaplan-Meier survival was performed to detect the association of KIF2C expression and patient' prognosis. Stably cell lines with KIF2C knockdown or overexpression were constructed by lentivirus infection. CCK-8, colony formation, scratch healing, and transwell invasion assays were carried out to explore the effect of KIF2C knockdown or overexpression on the proliferation, migration, and invasion of ccRCC cells. Gene set enrichment analysis (GSEA) was conducted to reveal signaling pathways associated with KIF2C expression. The effect of KIF2C on JAK2/STAT3 signaling pathway were explored by western blot assay.

RESULTS

KIF2C expression was significantly upregulated in ccRCC tissues and was higher with the increase of tumor grade, stage, and metastasis. Higher expression of KIF2C was correlated with worse overall survival and diseases free survival in ccRCC patients. Silence of KIF2C inhibited proliferation, migration, and invasion in ccRCC cells. Conversely, overexpression of KIF2C had the opposite effect. GSEA results showed that JAK/STAT signaling pathway was markedly enriched in KIF2Chigh group. Pearson' correlation revealed that KIF2C expression was significantly associated with genes in JAK2/STAT3 signaling. Western blot results showed that KIF2C knockdown decreased protein expression of p-JAK2 and p-STAT3, and KIF2C overexpression increased the phosphorylation of JAK2 and STAT3. AG490, a JAK2/STAT3 signaling inhibitor, could partly impair the tumor-promoting effects of KIF2C in ccRCC.

CONCLUSION

KIF2C expression was significantly upregulated in ccRCC and correlated with tumor grade, stage, metastasis, and patients' prognosis. KIF2C promoted ccRCC progression via activating JAK2/STAT3 signaling pathway, and KIF2C might be a novel target in ccRCC therapy.

Potential 'anti-cancer' effects of esketamine on proliferation, apoptosis, migration and invasion in esophageal squamous carcinoma cells

BACKGROUND

Esketamine, an N-methyl-D-aspartate receptor antagonist, is commonly used for anesthesia and analgesia clinically. It was reported to negatively regulate cell proliferation, metastasis and apoptosis in cancer cells, including lung cancer and pancreatic cancer. However, its impact on esophageal squamous cell carcinoma (ESCC) malignance and underlying mechanism remain elusive. This study was aimed to investigate the antitumor effects of esketamine on ESCC in vitro.

METHODS

ESCC cell lines (KYSE-30 and KYSE-150) were cultured and treated with different concentrations (0.1, 0.2, 0.4, 0.8, 1, 2 mM) of esketamine. Their proliferation, apoptosis, migration and invasion were assessed with various assays. Furthermore, mass spectrometry-based proteomic analysis and GO/KEGG enrichment analysis were applied to characterize the differentially expressed proteins (DEPs) with or without esketamine treatment. Some key proteins identified from proteomic analysis were further validated with Western blotting and bioinformatics analysis.

RESULTS

Esketamine significantly inhibited the proliferation, migration, invasion and promoted apoptosis of the both types of cell lines in a dose- and time-dependent manner. A total of 321 common DEPs, including 97 upregulated and 224 downregulated proteins, were found with HPLC-MS analyses. GO/KEGG enrichment analysis suggested that esketamine affected cell population proliferation, GTPase activity and Apelin signaling pathway. The ERCC6L, AHR and KIF2C protein expression was significantly downregulated in these ESCC cells treated with esketamine compared to the controls and their changes were associated with the suppressive effects of esketamine on ESCC through bioinformatics analysis.

CONCLUSIONS

Our work demonstrated that esketamine has potential anti-ESCC properties in vitro but subjected to further in vivo and clinical study.

Development and validation of a vesicle-mediated transport-associated gene signature for predicting prognosis and immune therapy response in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignant tumor with a poor prognosis. The progression of numerous malignancies has been linked to abnormal vesicle-mediated transport-related gene (VMTRG) expression. The prognostic importance of VMTRGs in HCC is uncertain nonetheless.

METHODS

Utilizing HCC data from TCGA and ICGC, we employed univariate cox analysis, unsupervised clustering, and lasso analysis to construct molecular subtypes and prognostic signature of HCC based on the prognostic-associated VMTRGs expression levels. Subsequently, we validated the expression levels of the signature genes. We investigated the probable pathways using gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). Six methods were utilized to compare immune cell infiltration between two risk groups. Moreover, the "pRRophetic" algorithm was utilized to test the drug sensitivity of both groups.

RESULTS

We identified two distinct subtypes with divergent biological behaviors and immune functionality through unsupervised clustering. Subtype C1 demonstrated a poorer prognosis. A prognostic signature incorporating two VMTRGs (KIF2C and RAC1) was formulated. Immunohistochemistry and qRT-PCR analyses unveiled a significant upregulation of these pivotal genes within HCC tissues. The prognosis was worse for the high-risk group, which also had a higher clinicopathological grade, higher levels of tumor mutation burden (TMB), a higher immunological infiltration of CD8 + T cells, a higher expression of immune checkpoints, and enhanced immunotherapy efficacy. These two risk groups also have varied chemotherapy drug sensitivities.

CONCLUSIONS

Based on VMTRGs, we have developed a signature that assists in accurate prognosis prediction and formulating personalized treatment strategies for HCC patients.

Increasing glutathione levels by a novel posttranslational mechanism inhibits neuronal hyperexcitability

Glutathione (GSH) depletion, and impaired redox homeostasis have been observed in experimental animal models and patients with epilepsy. Pleiotropic strategies that elevate GSH levels via transcriptional regulation have been shown to significantly decrease oxidative stress and seizure frequency, increase seizure threshold, and rescue certain cognitive deficits. Whether elevation of GSH per se alters neuronal hyperexcitability remains unanswered. We previously showed that thiols such as dimercaprol (DMP) elevate GSH via post-translational activation of glutamate cysteine ligase (GCL), the rate limiting GSH biosynthetic enzyme. Here, we asked if elevation of cellular GSH by DMP altered neuronal hyperexcitability in-vitro and in-vivo. Treatment of primary neuronal-glial cerebrocortical cultures with DMP elevated GSH and inhibited a voltage-gated potassium channel blocker (4-aminopyridine, 4AP) induced neuronal hyperexcitability. DMP increased GSH in wildtype (WT) zebrafish larvae and significantly attenuated convulsant pentylenetetrazol (PTZ)-induced acute 'seizure-like' swim behavior. DMP treatment increased GSH and inhibited convulsive, spontaneous 'seizure-like' swim behavior in the Dravet Syndrome (DS) zebrafish larvae (scn1Lab). Furthermore, DMP treatment significantly decreased spontaneous electrographic seizures and associated seizure parameters in scn1Lab zebrafish larvae. We investigated the role of the redox-sensitive mammalian target of rapamycin (mTOR) pathway due to the presence of several cysteine-rich proteins and their involvement in regulating neuronal excitability. Treatment of primary neuronal-glial cerebrocortical cultures with 4AP or l-buthionine-(S,R)-sulfoximine (BSO), an irreversible inhibitor of GSH biosynthesis, significantly increased mTOR complex I (mTORC1) activity which was rescued by pre-treatment with DMP. Furthermore, BSO-mediated GSH depletion oxidatively modified the tuberous sclerosis protein complex (TSC) consisting of hamartin (TSC1), tuberin (TSC2), and TBC1 domain family member 7 (TBC1D7) which are critical negative regulators of mTORC1. In summary, our results suggest that DMP-mediated GSH elevation by a novel post-translational mechanism can inhibit neuronal hyperexcitability both in-vitro and in-vivo and a plausible link is the redox sensitive mTORC1 pathway.

Bioinformatical analysis of the key differentially expressed genes for screening potential biomarkers in Wilms tumor

Wilms tumor (WT) is the most common pediatric renal malignant tumor in the world. Overall, the prognosis of Wilms tumor is very good. However, the prognosis of patients with anaplastic tumor histology or disease relapse is still poor, and their recurrence rate, metastasis rate and mortality are significantly increased compared with others. Currently, the combination of histopathological examination and molecular biology is essential to predict prognosis and guide the treatment. However, the molecular mechanism has not been well studied. Genetic profiling may be helpful in some way. Hence, we sought to identify novel promising biomarkers of WT by integrating bioinformatics analysis and to identify genes associated with the pathogenesis of WT. In the presented study, the NCBI Gene Expression Omnibus was used to download two datasets of gene expression profiles related to WT patients for the purpose of detecting overlapped differentially expressed genes (DEGs). The DEGs were then uploaded to DAVID database for enrichment analysis. In addition, the functional interactions between proteins were evaluated by simulating the protein-protein interaction (PPI) network of DEGs. The impact of selected hub genes on survival in WT patients was analyzed by using the online tool R2: Genomics Analysis and Visualization Platform. The correlation between gene expression and the degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA. Top 12 genes were identified for further study after constructing a PPI network and screening hub gene modules. Kinesin family member 2C (KIF2C) was identified as the most significant gene predicting the overall survival of WT patients. The expression of KIF2C in WT was further verified by quantitative real-time polymerase chain reaction and immunohistochemistry. Furthermore, we found that KIF2C was significantly correlated with immune cell infiltration in WT. Our present study demonstrated that altered expression of KIF2C may be involved in WT and serve as a potential prognostic biomarker for WT patients.

Lumican silencing ameliorates β-glycerophosphate-mediated vascular smooth muscle cell calcification by attenuating the inhibition of APOB on KIF2C activity

Adverse cardiovascular events are associated with vascular calcification (VC) process, where vascular smooth muscle cells (VSMCs) differentiate into osteoblastic phenotype and deposit hydroxyapatite crystals. Microtubule-associated protein kinesin family member 2C (KIF2C) expression is decreased obviously in VSMC during calcification induction. Accordingly, we investigate the role and potential mechanism of KIF2C on VSMC calcification. The effects of β-glycerophosphate (β-GP)/KIF2C/lumican (LUM) on calcification, calcium content, alkaline phosphatase (ALP) activity, calcification-related markers, Tubulin, the ratio of polymerized (Po) to free (Fr) tubulin, as well as levels of LUM, apolipoprotein B (APOB), and KIF2C were assessed by Alizarin red S staining, calcium assay kit, ALP assay kit, Western blot, immunofluorescence, and quantitative real-time PCR. The interplay between LUM and APOB was estimated using co-immunoprecipitation and immunofluorescence. As a result, β-GP promoted calcification of human VMSCs (HVMSCs) and repressed KIF2C expression. KIF2C overexpression reversed the effect of β-GP on HVSMCs. LUM silencing attenuated β-GP-induced promotion on HVSMC calcification and increased KIF2C expression by interacting with APOB. Collectively, LUM silencing can alleviate β-GP-induced VSMC calcification through mitigating the repression of APOB on KIF2C expression.

TRAIP serves as a potential prognostic biomarker and correlates with immune infiltrates in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the major types of lung cancer with high morbidity and mortality. The TRAF-interacting protein (TRAIP) is a ring-type E3 ubiquitin ligase which has been recently identified to play pivotal roles in various cancers. However, the expression and function of TRAIP in LUAD remain elusive.

METHODS

In this study, we used bioinformatic tools as well as molecular experiments to explore the exact role of TRAIP and the underlying mechanism.

RESULTS

Data mining across the UALCAN, GEPIA and GTEx, GEO and HPA databases revealed that TRAIP was significantly overexpressed in LUAD tissues than that in adjacent normal tissues. Kaplan-Meier curve showed that high TRAIP expression was associated with poor overall survival (OS) and relapse-free survival (RFS). Univariate and multivariate cox regression analysis revealed that TRAIP was an independent risk factor in LUAD. And the TRAIP-based nomogram further supported the prognostic role of TRAIP in LUAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that TRAIP-associated genes were mainly involved in DNA replication, cell cycle and other processes. The immune infiltration analysis indicated that TRAIP expression was tightly correlated with the infiltration of diverse immune cell types, including B cell, CD8 + T cell, neutrophil and dendritic cell. Moreover, TRAIP expression was observed to be significantly associated with tumor infiltrating lymphocytes (TILs) and immune checkpoint molecules. In vitro experiments further confirmed knockdown of TRAIP inhibited cell migration and invasion, as well as decreasing chemokine production and inhibiting M2-like macrophage recruitment. Lastly, CMap analysis identified 10 small molecule compounds that may target TRAIP, providing potential therapies for LUAD.

CONCLUSIONS

Collectively, our study found that TRAIP is an oncogenic gene in LUAD, which may be a potential prognostic biomarker and promising therapeutic target for LUAD.

Transcriptomic Context of RUNX3 Expression in Monocytes: A Cross-Sectional Analysis

The runt-related transcription factor 3 (RUNX3) regulates the differentiation of monocytes and their response to inflammation. However, the transcriptomic context of RUNX3 expression in blood monocytes remains poorly understood. We aim to learn about RUNX3 from its relationships within transcriptomes of bulk CD14+ cells in adults. This study used immunomagnetically sorted CD14+ cell gene expression microarray data from the Multi-Ethnic Study of Atherosclerosis (MESA, n = 1202, GSE56047) and the Correlated Expression and Disease Association Research (CEDAR, n = 281, E-MTAB-6667) cohorts. The data were preprocessed, subjected to RUNX3-focused correlation analyses and random forest modeling, followed by the gene ontology analysis. Immunity-focused differential ratio analysis with intermediary inference (DRAIMI) was used to integrate the data with protein-protein interaction network. Correlation analysis of RUNX3 expression revealed the strongest positive association for EVL (r_mean = 0.75, p_FDR-MESA = 5.37 × 10^-140, p_FDR-CEDAR = 5.52 × 10^-80), ARHGAP17 (r_mean = 0.74, p_FDR-MESA = 1.13 × 10^-169, p_FDR-CEDAR = 9.20 × 10^-59), DNMT1 (r_mean = 0.74, p_FDR-MESA = 1.10 × 10^-169, p_FDR-CEDAR = 1.67 × 10^-58), and CLEC16A (r_mean = 0.72, p_FDR-MESA = 3.51 × 10^-154, p_FDR-CEDAR = 2.27 × 10^-55), while the top negative correlates were C2ORF76 (r_mean = -0.57, p_FDR-MESA = 8.70 × 10^-94, p_FDR-CEDAR = 1.31 × 10^-25) and TBC1D7 (r_mean = -0.55, p_FDR-MESA = 1.36 × 10^-69, p_FDR-CEDAR = 7.81 × 10^-30). The RUNX3-associated transcriptome signature was involved in mRNA metabolism, signal transduction, and the organization of cytoskeleton, chromosomes, and chromatin, which may all accompany mitosis. Transcriptomic context of RUNX3 expression in monocytes hints at its relationship with cell growth, shape maintenance, and aspects of the immune response, including tyrosine kinases.

Metabolites and gene expression in the myocardium of fasting rats in an acute hypoxic environment

With the rising demand for entry to extremely high altitudes (HAs), rapid adaptability to extremely hypoxic environments is a challenge that we need to explore. Fasting was used to evaluate acute hypoxia tolerance at HA and was proven to be an effective method for improving the survival rate at extreme HA. Our experiments also showed that fasting pretreatment for 72 h significantly increased the 24 h survival rate of rats at 7620 m from 10 to 85% and protected the myocardium cells of rats. Here, we compared the metabolites and gene expression in the myocardium of SD rats pretreated with fasting and nonfasting at normal altitude and extreme HA. Our findings demonstrated that the dynamic contents of detected differential metabolites (DMs) between different rat groups were consistent with the expression of differentially expressed genes (DEGs), and DM clusters also showed strong correlations with DEG clusters. DM clusters related to amino acids and lipids were significantly lower in the fasting groups, and the correlated DEG clusters were enriched in mitotic pathways, including CDK1, CDC7, NUF2, and MCM6, suggesting that fasting can attenuate mitotic processes in cardiac tissues and reduce the synthesis of amino acids and lipids. L-Glutamine-related metabolites were particularly low at extreme HA without pretreatment but were normal in the fasting groups. The DEGs in the cluster related to L-glutamine-related metabolites were enriched for T-cell receptor V(D)J recombination, the Hippo signaling pathway, the Wnt signaling pathway, the cGMP-PKG signaling pathway, and the mTOR signaling pathway and were significantly downregulated, indicating that the content of L-glutamine decreased at extreme HA, while fasting increased it to adapt to the environment. Moreover, abundant fatty acids were detected when rats were exposed to extreme HA without pretreatment. Our study revealed the fasting and hypoxic environment-related factors in SD rats and provided new insights into the genetic and molecular characteristics in the myocardium, which is critical to developing more potential rapid adaptation methods to extreme HA.

KIF2C accelerates the development of non-small cell lung cancer and is suppressed by miR-186-3p via the AKT-GSK3β-β-catenin pathway

This study aimed to explore how kinesin family member 2C (KIF2C) influences the progression of non-small cell lung cancer (NSCLC). The levels of KIF2C and microRNA-186-3p (miR-186-3p) were examined by quantitative real-time polymerase chain reaction (qRT-PCR). Through the utilization of cell counting kit-8 (CCK-8) assay, colony formation assay, wound closure assay, and Transwell assay, NSCLC cell proliferation, migration, and invasion were identified, respectively. NSCLC cell apoptosis was assessed using the TUNEL assay and flow cytometry (FCM) assay. Luciferase reporter analysis was used to investigate the relationship between KIF2C and miR-186-3p. Western blot assays were conducted to investigate the influence of KIF2C on the AKT-GSK3β-β-catenin pathway. The results showed that KIF2C was up-regulated in NSCLC cells, which predicted poor prognosis. KIF2C overexpression promoted the proliferation, migration, and invasion of NSCLC cells as well as inhibited NSCLC cell apoptosis. KIF2C was as a key target of miR-186-3p. High expression of KIF2C, meanwhile, increased the levels of β-catenin, p-GSK-3β and phosphorylated protein kinase B (p-AKT). KIF2C downregulation and miR-186-3p upregulation reversed these outcomes. As an oncogenic factor, KIF2C is negatively regulated by miR-186-3p and participates in the progression of NSCLC through the AKT-GSK3β-β-catenin pathway.

Lactylation-Related Gene Signature Effectively Predicts Prognosis and Treatment Responsiveness in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignant tumor associated with high morbidity and mortality. Therefore, it is of great importance to develop effective prognostic models and guide clinical treatment in HCC. Protein lactylation is found in HCC tumors and is associated with HCC progression.

METHODS

The expression levels of lactylation-related genes were identified from the TCGA database. A lactylation-related gene signature was constructed using LASSO regression. The prognostic value of the model was assessed and further validated in the ICGC cohort, with the patients split into two groups based on risk score. Glycolysis and immune pathways, treatment responsiveness, and the mutation of signature genes were analyzed. The correlation between PKM2 expression and the clinical characteristics was investigated.

RESULTS

Sixteen prognostic differentially expressed lactylation-related genes were identified. An 8-gene signature was constructed and validated. Patients with higher risk scores had poorer clinical outcomes. The two groups were different in immune cell abundance. The high-risk group patients were more sensitive to most chemical drugs and sorafenib, while the low-risk group patients were more sensitive to some targeted drugs such as lapatinib and FH535. Moreover, the low-risk group had a higher TIDE score and was more sensitive to immunotherapy. PKM2 expression correlated with clinical characteristics and immune cell abundance in the HCC samples.

CONCLUSIONS

The lactylation-related model exhibited robust predictive efficiency in HCC. The glycolysis pathway was enriched in the HCC tumor samples. A low-risk score indicated better treatment response to most targeted drugs and immunotherapy. The lactylation-related gene signature could be used as a biomarker for the effective clinical treatment of HCC.

KIF2C is a prognostic biomarker associated with immune cell infiltration in breast cancer

BACKGROUND

The kinesin-13 family member 2C (KIF2C) is a versatile protein participating in many biological processes. KIF2C is frequently up-regulated in multiple types of cancer and is associated with cancer development. However, the role of KIF2C in immune cell infiltration of tumor microenvironment and immunotherapy in breast cancer remains unclear.

METHODS

The expression of KIF2C was analyzed using Tumor Immune Estimation Resource (TIMER) database and further verified by immunohistochemical staining in human breast cancer tissues. The correlation between KIF2C expression and clinical parameters, the impact of KIF2C on clinical prognosis and independent prognostic factors were analyzed by using TCGA database, the Kaplan-Meier plotter, and Univariate and multivariate Cox analyses, respectively. The nomograms were constructed according to independent prognostic factors and validated with C-index, calibration curves, ROC curves, and decision curve analysis. A gene set enrichment analysis (GSEA) was performed to explore the underlying molecular mechanisms of KIF2C. The degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA (ssGSEA). The Tumor mutational burden and Tumor Immune Dysfunction and Rejection (TIDE) were used to analyze immunotherapeutic efficiency. Finally, the KIF2C-related competing endogenous RNA (ceRNA) network was constructed to predict the putative regulatory mechanisms of KIF2C.

RESULTS

KIF2C was remarkably up-regulated in 18 different types of cancers, including breast cancer. Kaplan-Meier survival analysis showed that high KIF2C expression was associated with poor overall survival (OS). KIF2C expression was associated with clinical parameters such as age, TMN stage, T status, and molecular subtypes. We identified age, stage, estrogen receptor (ER) and KIF2C expression as OS-related independent prognosis factors for breast cancer. An OS-related nomogram was developed based on these independent prognosis factors and displayed good predicting ability for OS of breast cancer patients. Finally, our results revealed that KIF2C was significantly related to immune cell infiltration, tumor mutational burden, and immunotherapy in patients with breast cancer.

CONCLUSION

KIF2C was overexpressed in breast cancer and was positively correlated with immune cell infiltration and immunotherapy response. Therefore, KIF2C can serve as a potential biomarker for prognosis and immunotherapy in breast cancer.

Oncogenic zinc finger protein ZNF687 accelerates lung adenocarcinoma cell proliferation and tumor progression by activating the PI3K/AKT signaling pathway

BACKGROUND

Zinc finger protein 687 (ZNF687) has previously been discovered as a potential oncogene in individuals with giant cell tumors of the bone, acute myeloid leukemia, and hepatocellular carcinoma. However, its role and mechanism in lung adenocarcinoma (LUAD) remain unclear.

METHODS

In LUAD cells, tumor, and matched adjacent tissue specimens, quantitative real-time RT- polymerase chain reaction (qRT-PCR), western blotting analyses, and immunohistochemistry staining (IHC) were conducted. Cell counting kit-8 (CCK8) assay, clonogenicity analysis, flow cytometry, and transwell assays were utilized to detect ZNF687 overexpression and knockdown impacts on cell growth, colony formation, cell cycle, migration, and invasion. Bioinformatic studies, qRT-PCR and western blotting studies were employed to validate the underlying mechanisms and signaling pathways implicated in the oncogenic effect of ZNF687.

RESULTS

This study demonstrated that ZNF687 expression was elevated in LUAD cells and tissues. Individuals with upregulated ZNF687 had a poorer prognosis than those with downregulatedZNF687 (p < 0.001). ZNF687 overexpression enhanced LUAD growth, migration, invasion and colony formation, and the cell cycle G1-S transition; additionally, it promoted the epithelial-mesenchymal transition (EMT). In contrast, knocking down ZNF687 showed to have the opposite impact. Moreover, these effects were associated with the activity of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling mechanism.

CONCLUSION

ZNF687 was upregulated in LUAD, and high ZNF687 expression levels are associated with poor prognoses. The activation of the PI3K/AKT signaling pathway by upregulated ZNF687 increased the proliferation of LUAD cells and tumor progression. ZNF687 may be a beneficial predictive marker and a therapeutic target in LUAD.

KIF2C Facilitates Tumor Growth and Metastasis in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer with a poor prognosis. For PDAC, an increase in the survival time of patients and a reduction mortality have not yet successfully been achieved. In many research works, Kinesin family member 2C (KIF2C) is highly expressed in several tumors. Nevertheless, the role of KIF2C in pancreatic cancer is unknown. In this study, we found that KIF2C expression is significantly upregulated in human PDAC tissues and cell lines such as ASPC-1 and MIA-PaCa2. Moreover, KIF2C upregulation is associated with a poor prognosis when combining the expression of KIF2C with clinical information. Through cell functional assays and the construction of animal models, we showed that KIF2C promotes PDAC cell proliferation, migration, invasion, and metastasis, both in vitro and in vivo. Finally, the results of sequencing showed that the overexpression of KIF2C causes a decrease in some proinflammatory factors and chemokines. The cell cycle detection indicated that the pancreatic cancer cells in the overexpressed group had abnormal proliferation in the G2 and S phases. These results revealed the potential of KIF2C as a therapeutic target for the treatment of PDAC.

Sulforaphane Targets the TBX15/KIF2C Pathway to Repress Glycolysis and Cell Proliferation in Gastric Carcinoma Cells

The effects of sulforaphane on glycolysis and proliferation of SGC7901 and BGC823 gastric carcinoma cell lines were analyzed, and the potential mediating role of the TBX15/KIF2C axis was explored. SGC7901 and BGC823 cells stably over- or underexpressing TBX15 were exposed to sulforaphane, and cell viability was assessed together with the expression of TBX15, KIF2C, and proteins involved in glycolysis, glucose uptake, and lactate production. Overexpressing TBX15 in SGC7901 and BGC823 cells significantly reduced glucose uptake, lactate production, cell viability, expression of KIF2C, and pyruvate kinase M2-mediated (PKM2) glycolysis. These effects were recapitulated by treatment with sulforaphane. The anti-tumor effects of sulforaphane were antagonized by down-regulation of TBX15, up-regulation of KIF2C or addition of a PKM2 agonist. Sulforaphane can reduce cell proliferation and PKM2-mediated glycolysis in gastric carcinoma cells, apparently by activating the TBX15/KIF2C pathway.

TEA Domain Transcription Factor 1 Inhibits Ferroptosis and Sorafenib Sensitivity of Hepatocellular Carcinoma Cells

BACKGROUND

Ferroptosis, as a unique form of cell death, plays crucial negative roles in tumorigenesis and progression. This study aimed to investigate the role and molecular mechanism of TEA domain transcription factor 1 (TEAD1) in HCC and its effect on sorafenib-induced ferroptosis.

METHODS

TEAD1 expression was analyzed in HCC tissues using quantitative PCR, and western blot. The effects on cell proliferation, migration and invasion were determined by CCK-8, wound healing and Transwell assays. Intracellular iron, reactive oxygen species (ROS), malondialdehyde (MDA) and GSH measurement was used to assess ferroptosis. Chromatin immunoprecipitation and luciferase reporter gene assays were performed to verify the relationship between TEAD1 and solute carrier family 3 member 2 (SLC3A2). Expression of mTOR, ribosomal protein S6, glutathione peroxidase 4 (GPX4) and SLC3A2 was analyzed by western blot. Tumor xenografts were used assess the effect of TEAD1 on tumor growth in vivo.

RESULTS

TEAD1 was more abundant in HCC compared with normal tissues. Overexpression of TEAD1 enhanced the proliferation, migration, and invasion of HCC cells, while knockdown of TEAD1 inhibited these cell behaviors. Further, TEAD1 inhibited ferroptosis, which was demonstrated by decreased intracellular Fe²⁺ content, ROS, and MDA levels, and increased GSH activity. Mechnistically, TEAD1 promotes the transcription of SLC3A2 and activates the mTOR signaling. Additionally, silenced TEAD1 restrained tumor growth and enhance sorafenib-induced antitumor activity in vivo.

CONCLUSIONS

TEAD1 confers resistance of HCC cells to ferroptosis, thereby promoting the progression of HCC, suggesting the potential value of TEAD1 in the diagnosis and treatment of HCC.

CDCA8 induced by NF-YA promotes hepatocellular carcinoma progression by regulating the MEK/ERK pathway

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors. Cell division cycle associated 8 (CDCA8) is an important multifactorial regulator in cancers. However, its up and downstream targets and effects in HCC are still unclear.

METHODS

A comprehensive bioinformatics analysis was performed using The Cancer Genome Atlas dataset (TCGA) to explore novel core oncogenes. We quantified CDCA8 levels in HCC tumors using qRT-PCR. HCC cell's proliferative, migratory, and invasive abilities were detected using a Cell Counting Kit-8 (CCK-8) assay, 5-ethynyl-2'-deoxyuridine (EdU) assay, clone formation, and a Transwell assay. An orthotopic tumor model and tail vein model were constructed to determine the effects of CDCA8 inhibition in vivo. The mechanism underlying CDCA8 was investigated using RNA sequencing. The prognostic value of CDCA8 was assessed with immunohistochemical staining of the tissue microarrays.

RESULTS

CDCA8 was identified as a novel oncogene during HCC development. The high expression of CDCA8 was an independent predictor for worse HCC outcomes both in publicly available datasets and in our cohort. We found that CDCA8 knockdown inhibited HCC cell proliferation, colony formation, and migration by suppressing the MEK/ERK pathway in vitro. Moreover, CDCA8 deficiency significantly inhibited tumorigenesis and metastasis. Next-generation sequencing and laboratory validation showed that CDCA8 silencing inhibited the expression of TPM3, NECAP2, and USP13. Furthermore, NA-YA overexpression upregulated the expression of CDCA8. CDCA8 knockdown could attenuate NF-YA-mediated cell invasion in vitro. The expression of NF-YA alone or in combined with CDCA8 were validated as significant independent risk factors for patient survival.

CONCLUSION

Our findings revealed that the expression of CDCA8 alone or in combined with NF-YA contributed to cancer progression, and could serve as novel potential therapeutic targets for HCC patients.

Predictive investigation of idiopathic pulmonary fibrosis subtypes based on cellular senescence-related genes for disease treatment and management

Background: Idiopathic pulmonary fibrosis (IPF), a chronic, progressive lung disease characterized by interstitial remodeling and tissue destruction, affects people worldwide and places a great burden on society. Cellular senescence is thought to be involved in the mechanisms and development of IPF. The aim of this study was to predictively investigate subtypes of IPF according to cellular senescence-related genes and their correlation with the outcome of patients with IPF, providing possible treatment and management options for disease control. Methods: Gene expression profiles and follow-up data were obtained from the GEO database. Senescence-related genes were obtained from the CSGene database and analyzed their correlation with the outcome of IPF. A consensus cluster was constructed to classify the samples based on correlated genes. The GSVA and WGCNA packages in R were used to calculate the immune-related enriched fractions and construct gene expression modules, respectively. Metascape and the clusterProfiler package in R were used to enrich gene functions. The ConnectivityMap was used to probe suitable drugs for potential treatment. Results: A total of 99 cellular senescence-related genes were associated with IPF prognosis. Patients with IPF were divided into two subtypes with significant prognostic differences. Subtype S2 was characterized by enhanced fibrotic progression and infection, leading to acute exacerbation of IPF and poor prognosis. Finally, five cellular senescence-related genes, TYMS, HJURP, UBE2C, BIRC5, and KIF2C, were identified as potential biomarkers in poor prognostic patients with IPF. Conclusion: The study findings indicate that cellular senescence-related genes can be used to distinguish the prognosis of patients with IPF. Among them, five genes can be used as candidate biomarkers to predict patients with a poor prognostic subtype for which anti-fibrosis and anti-infection treatments could be suitable.

N6-Methyladenosine Modification of ANLN Enhances Hepatocellular Carcinoma Bone Metastasis

Bones are categorized as the second most prevalent location of extra-hepatic metastasis in Hepatocellular Carcinoma (HCC), which is linked to an extremely poor prognosis due to limited therapeutic options. N⁶-methyladenosine (m⁶A) is a prominent modification involved in HCC, but the exact mechanisms on how m⁶A modifications induce HCC bone metastases (BM) remain unclear. The key modulators responsible for the abundant m⁶A RNA modification-induced HCC BM was found to be the METTL3 and YTHDF1. The expression of Anillin actin-binding protein (ANLN) was dramatically higher in HCC with BM tissues, and its messenger RNA (mRNA) stability was enhanced via m⁶A epitranscriptomic regulation by METTL3 and YTHDF1. High METTL3 and YTHDF1 expression along with nuclear ANLN protein was clinically correlated with BM in HCC patients. Furthermore, HCC BM was attributed to over-expression of nuclear ANLN forming a transcriptional complex with SP1 which enhanced KIF2C transcriptional activity to activate the mTORC1 pathway, therefore increased the expression of RANKL and disproportionated RANKL-OPG expression in bone microenvironment leading to malignant neoplasms invade bone tissue. In addition, inhibition of ANLN m⁶A modification by DZNeP attenuated HCC BM. This data provides meaningful understanding of the modulation and association of m⁶A epitranscriptomic-regulated BM in HCC, and moreover, defines potentially valuable therapeutic targets.

Screening of Key Prognosis Genes of Lung Adenocarcinoma Based on Expression Analysis on TCGA Database

Objective

The data of lung adenocarcinoma- (LUAD-) related gene expression profiles were mined from the Cancer Genome Atlas (TCGA) database using bioinformatics methods and potential biomarkers related to the occurrence, development, and prognosis of LUAD were screened out to explore the key prognostic genes and clinical significance.

Methods

Following the LUAD gene expression profile data that were initially exported from the TCGA database, R software DESeq2 was employed to analyze the difference between the expression profiles of LUAD and normal tissues. The R package "clusterProfiler" was subsequently utilized to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the differential genes. A protein-protein interaction (PPI) network was constructed via the String database, and cytohubba, a plugin of Cytoscape, was applied to screen hub genes using the MCC algorithm. The Gene Expression Profile Data Interactive Analysis (GEPIA) was used to analyze expressions of 10 candidate genes in LUAD samples and healthy lung samples, and the selected genes were employed for survival analysis.

Results

A total of 1,598 differential genes were identified through differential analyses and data mining, with 1,394 genes upregulated and 204 downregulated. A total of 10 hub genes CCNA2, CDC20, CCNB2, KIF11, TOP2A, BUB1, BUB1B, CENPF, TPX2, and KIF2C were obtained using the cytohubba plugin. The results of the GEPIA analysis indicated that compared with normal lung tissue, the mRNA expression level of the described hub genes in LUAD tissue was significantly increased (P < 0.05). Survival analysis revealed that these genes had a significant impact on the overall survival time of LUAD patients (P < 0.05).

Conclusion

The previously described key genes related to LUAD identified in the TCGA database may be used as potential prognostic biomarkers, which will contribute to further comprehension of the occurrence and development of LUAD and provide references for its diagnosis and treatment.

Multi-omics analysis of kinesin family member 2C in human tumors: novel prognostic biomarker and tumor microenvironment regulator

Kinesin family member 2C (KIF2C) is the best-characterized member of the kinesin-13 family and is involved in accurately fine-tuned dynamics of mitotic spindles. As KIF2C is involved in both spindle formation and regulation of DNA double-strand breaks, precise regulation of KIF2C is essential to prevent malignant transformation associated with gains and losses of DNA content. In the present study, we initially reviewed The Cancer Genome Atlas database and observed that KIF2C is abundantly expressed in most tumor types. We then analyzed the gene alteration profile, protein expression, prognosis, and immune reactivities of KIF2C in more than 10,000 samples from several well-established databases. In addition, we conducted a gene enrichment set analysis to investigate the potential mechanisms underlying the role of KIF2C in tumorigenesis. Multi-omics analysis of KIF2C demonstrated significant statistical correlations between KIF2C expression and clinical prognosis, oncogenic signature gene sets, myeloid-derived suppressor cell infiltration, ImmunoScore, immune checkpoints, microsatellite instability, and tumor mutational burden across multiple tumors. Single-cell data showed that KIF2C is abundantly expressed in malignant cells. The experimental validation demonstrated that KIF2C is highly expressed in gastric cancer cell lines, gastric adenocarcinoma, and hepatocelluar carcinoma. The findings of this study provide important insight for understanding the role and mechanisms of KIF2C in tumorigenesis and immunotherapy in a variety of cancers.

Screening of the Key Genes for the Progression of Liver Cirrhosis to Hepatocellular Carcinoma Based on Bioinformatics

Hepatocellular carcinoma (HCC), which is among the most globally prevalent cancers, is strongly associated with liver cirrhosis. Using a bioinformatics approach, we have identified and investigated the hub genes responsible for the progression of cirrhosis into HCC. We analyzed the Gene Expression Omnibus (GEO) microarray datasets, GSE25097 and GSE17549, to identify differentially expressed genes (DEGs) in these two conditions and also performed protein-protein interaction (PPI) network analysis. STRING database and Cytoscape software were used to analyze the modules and locate hub genes following which the connections between hub genes and the transition from cirrhosis to HCC, progression of HCC, and prognosis of HCC were investigated. We used the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to detect the molecular mechanisms underlying the action of the primary hub genes. In all, 239 DEGs were obtained, with 94 of them showing evidence of upregulation and 145 showing evidence of downregulation in HCC tissues as compared to cirrhotic liver tissues. We identified six hub genes, namely, BUB1B, NUSAP1, TTK, HMMR, CCNA2, and KIF2C, which were upregulated and had a high diagnostic value for HCC. Besides, these six hub genes were positively related to immune cell infiltration. Since these genes may play a direct role in the progression of cirrhosis to HCC, they can be considered as potential novel molecular indicators for the onset and development of HCC.

Risk model of hepatocellular carcinoma based on cuproptosis-related genes

Background: Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors. Materials and methods: "ConsensusClusterPlus" tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis. Results: Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence (p < 0.01). The clust3 subtype with poor prognosis had a low "ImmuneScore" and low immune cell infiltration, and the three subtypes had significant differences in the antigen processing and presentation pathway of the macrophages. Clust1 had a low TIDE score and was sensitive to immunotherapy. Then, according to the prognosis-related genes of cuproptosis, a prognosis risk model related to cuproptosis was constructed, containing seven genes (KIF2C, PTTG1, CENPM, CDC20, CYP2C9, SFN, and CFHR3). "High" group had a higher TIDE score compared to the TIDE score value shown by the "Low" group, which benefited less from immunotherapy, whereas the "High" group patients were more sensitive to the conventional drugs. Finally, the prognosis risk model related to cuproptosis was combined with clinical pathological characteristics to further improve the prognostic model and survival prediction. Conclusion: Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy.

A cohesin-associated gene score may predict immune checkpoint blockade in hepatocellular carcinoma

Stromal antigen 1 (STAG1), a component of cohesion, is overexpressed in various cancers, but it is unclear whether it has a role in the transcriptional regulation of hepatocellular carcinoma (HCC). To test this hypothesis, here, we screened global HCC datasets and performed multiscale embedded gene co-expression network analysis to identify the potential functional modules of differentially expressed STAG1 co-expressed genes. The putative transcriptional targets of STAG1 were identified using chromatin immunoprecipitation followed by high-throughput DNA sequencing. The cohesin-associated gene score (CAGS) was quantified using the The Cancer Genome Atlas HCC cohort and single-sample gene set enrichment analysis. Distinct cohesin-associated gene patterns were identified by calculating the euclidean distance of each patient. We assessed the potential ability of the CAGS in predicting immune checkpoint blockade (ICB) treatment response using IMvigor210 and GSE78220 cohorts. STAG1 was upregulated in 3313 HCC tissue samples compared with 2692 normal liver tissue samples (standard mean difference = 0.54). A total of three cohesin-associated gene patterns were identified, where cluster 2 had a high TP53 mutated rate and a poor survival outcome. Low CAGS predicted a significant survival advantage but presaged poor immunotherapy response. Differentially expressed STAG1 co-expression genes were enriched in the mitotic cell cycle, lymphocyte activation, and blood vessel development. PDS5A and PDGFRA were predicted as the downstream transcriptional targets of STAG1. In summary, STAG1 is significantly upregulated in global HCC tissue samples and may participate in blood vessel development and the mitotic cell cycle. A cohesin-associated gene scoring system may have potential to predict the ICB response.

A Novel Metabolism-Related Gene Signature for Predicting the Prognosis of HBV-Infected Hepatocellular Carcinoma

Metabolic reprogramming is one of the crucial hallmarks of cancer. Hepatocellular carcinoma (HCC) resulting from hepatitis B has various altered metabolic features. However, the impact of such alterations on the tumor microenvironment (TME) and immunotherapy efficacy is still unclear. Here, a prognostic signature of metabolism-related gene (MRG) composition was constructed, and the immune profile of different subgroups and potential response to immunotherapy were described. Based on the HCC gene dataset, we used weighted gene coexpression network analysis for identifying MRGs linked to hepatitis B. An MRG prognostic index (MRGPI) with two genes, ATIC and KIF2C, was constructed using Cox regression analysis, an independent prognostic factor. In addition, the model was validated using the GEO dataset. The immune profile and prediction of HCC response to immunotherapy in different subgroups were analyzed using CIBERSORT and TIDE. Based on the outcomes, the distributions of memory B cells, monocytes, resting mast cells, and M0 macrophages in TME were different with a greater benefit of immunotherapy in the low MRGPI risk group. In addition, the MRGPI risk groups showed substantial differences in sensitivity to conventional drug therapy. This study concludes that MRGPI is an effective biomarker for predicting the prognoses of patients with HCC resulting from hepatitis B virus infections and determining the efficacy of immunotherapy and conventional medical therapy.

Hallmark-guided subtypes of hepatocellular carcinoma for the identification of immune-related gene classifiers in the prediction of prognosis, treatment efficacy, and drug candidates

Hepatocellular carcinoma (HCC), accounting for ~90% of all primary liver cancer, is a prevalent malignancy worldwide. The intratumor heterogeneity of its causative etiology, histology, molecular landscape, and immune phenotype makes it difficult to precisely recognize individuals with high mortality risk or tumor-intrinsic treatment resistance, especially immunotherapy. Herein, we comprehensively evaluated the activities of cancer hallmark gene sets and their correlations with the prognosis of HCC patients using gene set variation analysis (GSVA) and identified two HCC subtypes with distinct prognostic outcomes. Based on these subtypes, seven immune-related genes (TMPRSS6, SPP1, S100A9, EPO, BIRC5, PLXNA1, and CDK4) were used to construct a novel prognostic gene signature [hallmark-guided subtypes-based immunologic signature (HGSIS)] via multiple statistical approaches. The HGSIS-integrated nomogram suggested an enhanced predictive performance. Interestingly, oncogenic hallmark pathways were significantly enriched in the high-risk group and positively associated with the risk score. Distinct mutational landscapes and immune profiles were observed between different risk groups. Moreover, immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analysis showed different sensitivities of HGSIS risk groups for immune therapy efficacy, and the pRRophetic algorithm indicated distinguishable responses for targeted/chemotherapies in different groups. KIF2C was picked out as the key target concerning HGSIS, and the top 10 small molecules were predicted to bind to the active site of KIF2C via molecular docking, which might be further used for candidate drug discovery of HCC. Taken together, our study offers novel insights for clinically significant subtype recognition, and the proposed signature may be a helpful guide for clinicians to improve the treatment regimens.

Identification and Validation in a Novel Classification of Helicase Patterns for the Prediction of Tumor Proliferation and Prognosis

Background

Helicases have been classified as a class of enzymes that determine the stability of the cellular genome. There is growing evidence that helicases can help tumor cells resist drug killing by repairing Deoxyribose Nucleic Acid (DNA) or stabilizing transcription, which may contribute to the understanding of drug resistance. Currently, identifying cancer biomarkers among helicases and stratifying patients according to helicase activity will be able to guide treatment well.

Methods

We clustered 371 hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) by consensus clustering based on helicase expression profiles to identify potential molecular subtypes. The Multiscale Embedded Gene Co-Expression Network Analysis (MEGENA) algorithm was used to find core differential gene modules between different molecular subtypes, and single-cell analysis was utlized to explore the potential function of hub gene. Immunohistochemical (IHC) staining was used to verify the diagnostic value of DDX56 and its ability to reflect the proliferation efficiency of cancer cells.

Results

We identified two subtypes associated with helicase. High helicase subtype was associated with poor clinical outcome, massive M0 macrophage infiltration, and highly active cell proliferation features. In addition, we identified a new biomarker, DDX56, which has not been reported in HCC, was highly expressed in HCC tissues, associated with poor prognosis, and was also shown to be associated with high cell proliferative activity.

Conclusion

In conclusion, based on helicase expression profiles, we have developed a new classification system for HCC, which is a proliferation-related system, and has clinical significance in evaluating prognosis and treating HCC patients, including immunotherapy and chemotherapy. In addition, we identified a new biomarker, DDX 56, which is overexpressed in HCC tissues, predicts a poor prognosis and is a validated index of tumor cell proliferation.

Identifying a Novel Endoplasmic Reticulum-Related Prognostic Model for Hepatocellular Carcinomas

From the standpoint of the ER (endoplasmic reticulum), we were interested in identifying hub genes that impact clinical prognosis for HCC (hepatocellular carcinoma) patients and developing an ER-related prognostic model. Using TCGA-LIHC (The Cancer Genome Atlas-Liver Hepatocellular Carcinoma) and GSE14520 datasets, we conducted a series of analyses, which included differential gene screening, clinical prognostic analysis, Lasso regression, nomogram prediction, tumour clustering, gene functional enrichment, and tumour infiltration of immune cells. Following our screening for ER-related genes ( $n=1975$ ), we conducted a Lasso regression model to obtain five hub genes, KPNA2, FMO3, SPP1, KIF2C, and LPCAT1, using TCGA-LIHC as a training set. According to risk scores, HCC samples within either the TCGG-LIHC or GSE14520 cohort were categorized into high- and low-risk groups. Compared to the high-risk group of HCC patients, patients in the low-risk group had a better prognosis of OS (overall survival) or RFS (relapse-free survival). For TCGA-LIHC training set, with the factors of risk score, stage, age, and sex, we plotted a nomogram for 1-, 3-, and 5-year survival predictions. Our model demonstrated better clinical validity in both TCGA-LIHC and GSE14520 cohorts. Additionally, events related to biological enzyme activity, biological metabolic processes, or the cell cycle were associated with the prognostic risk of ER. Furthermore, two HCC prognosis-associated tumour clusters were identified by ER hub gene-based consensus clustering. Our findings indicated a link between ER prognostic signature-related high/low risk and tumour infiltration levels of several immune cells, such as “macrophages M2/M0” and “regulatory T cells (Tregs).” Overall, we developed a novel ER-related clinical prognostic model for HCC patients.

Identification and Validation of Prognosis-Related Necroptosis Genes for Prognostic Prediction in Hepatocellular Carcinoma

Background

The prediction of hepatocellular carcinoma (HCC) survival is challenging because of its rapid progression. In recent years, necroptosis was found to be involved in the progression of multiple cancer types. However, the role of necroptosis in HCC remains unclear.

Methods

Clinicopathological parameters and transcriptomic data of 370 HCC patients were obtained from TCGA-LIHC dataset. Prognosis-related necroptosis genes (PRNGs) were identified and utilized to construct a LASSO risk model. The GEO cohorts (GSE54236 and GSE14520) were used for external validation. We evaluated the distribution of HCC patients, the difference in prognosis, and the accuracy of the prognostic prediction of the LASSO risk model. The immune microenvironment and functional enrichment of different risk groups were further clarified. Finally, we performed a drug sensitivity analysis on the PRNGs that constructed the LASSO model and verified their mRNA expression levels in vitro. Results: A total of 48 differentially expressed genes were identified, 23 of which were PRNGs. We constructed the LASSO risk model using nine genes: SQSTM1, FLT3, HAT1, PLK1, MYCN, KLF9, HSP90AA1, TARDBP, and TNFRSF21. The outcomes of low-risk patients were considerably better than those of high-risk patients in both the training and validation cohorts. In addition, stronger bile acid metabolism, xenobiotic metabolism, and more active immune cells and immune functions were observed in low-risk patients, and high expressions of TARDBP, PLK1, and FLT3 were associated with greater drug sensitivity. With the exception of FLT3, the mRNA expression of the other eight genes was verified in Huh7 and 97H cells. Conclusions. The PRNG signature provides a novel and effective method for predicting the outcome of HCC as well as potential targets for further research.

Large-Scale Transcriptome Data Analysis Identifies KIF2C as a Potential Therapeutic Target Associated With Immune Infiltration in Prostate Cancer

Prostate cancer (PCa) is one of the most prevalent cancers of the urinary system. In previous research, Kinesin family member 2C (KIF2C), as an oncogene, has been demonstrated to have a key role in the incidence and progression of different cancers. However, KIF2C has not been reported in PCa. We combined data from different databases, including The Cancer Genome Atlas, the Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, and the Genomics of Drug Sensitivity in Cancer database, to explore the potential oncogenic role of KIF2C in PCa through a series of bioinformatics approaches, including analysis of the association between KIF2C and prognosis, clinicopathological features, gene mutations, DNA methylation, immune cell infiltration, and drug resistance. The results showed that KIF2C was significantly up-regulated in PCa. High KIF2C expression was associated with age, pathological stage, lymph node metastases, prostate-specific antigen (PSA), and Gleason score and significantly predicted an unfavorable prognosis in PCa patients. Results from Gene Set Enrichment Analysis (GSEA) suggested that KIF2C was involved in the cell cycle and immune response. KIF2C DNA methylation was reduced in PCa and was inversely linked with KIF2C expression. KIF2C was shown to have a strong relationship with the tumor microenvironment (TME), infiltrating cells, and immune checkpoint genes. Furthermore, high KIF2C expression was significantly resistant to a variety of MAPK signaling pathway-related inhibitors. Our study reveals that KIF2C may be a possible predictive biomarker for assessing prognosis in PCa patients with immune infiltration.

KIF2C is a Biomarker Correlated With Prognosis and Immunosuppressive Microenvironment in Human Tumors

Kinesin superfamily member 2C (KIF2C) is an essential regulator of the cell cycle and its aberrant expression can promote tumor progression. However, the mechanism of KIF2C in pan-cancer is unclear.Data were obtained from public databases, including The Cancer Genome Atlas (TCGA), UALCAN, TIMER and CellMiner. The data came from public databases such as The Cancer Genome Atlas (TCGA), UALCAN, TIMER, and CellMiner. We analyzed the correlation of KIF2C with expression, prognosis, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repairs (MMR), immune infiltration and anticancer drug sensitivity by R language.KIF2C was highly expressed in several tumors and correlated with poor prognosis. KIF2C expression was significantly correlated with TMB, MSI, MMRs, and immune checkpoint genes, and with the level of immune cell infiltration such as tumor-associated macrophage (TAM), cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs) and Tregs. The GO and KEGG results suggest that KIF2C is involved in immune regulation in addition to cell cycle regulation.In addition, KIF2C is associated with DNA methylation, m6A modifications and m7G modifications. Our data suggest that KIF2C is a prognostic biomarker linked to immunosuppression, targeting KIF2C may improve the outcome of immunotherapy. Our findings indicate that KIF2C is a prognostic biomarker associated with immunosuppression, and that targeting KIF2C may improve the outcome of immunotherapy.

Identification of Pathologic and Prognostic Genes in Prostate Cancer Based on Database Mining

Background: Prostate cancer (PCa) is an epithelial malignant tumor that occurs in the urinary system with high incidence and is the second most common cancer among men in the world. Thus, it is important to screen out potential key biomarkers for the pathogenesis and prognosis of PCa. The present study aimed to identify potential biomarkers to reveal the underlying molecular mechanisms.

Methods: Differentially expressed genes (DEGs) between PCa tissues and matched normal tissues from The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset were screened out by R software. Weighted gene co-expression network analysis was performed primarily to identify statistically significant genes for clinical manifestations. Protein–protein interaction (PPI) network analysis and network screening were performed based on the STRING database in conjunction with Cytoscape software. Hub genes were then screened out by Cytoscape in conjunction with stepwise algorithm and multivariate Cox regression analysis to construct a risk model. Gene expression in different clinical manifestations and survival analysis correlated with the expression of hub genes were performed. Moreover, the protein expression of hub genes was validated by the Human Protein Atlas database.

Results: A total of 1,621 DEGs (870 downregulated genes and 751 upregulated genes) were identified from the TCGA-PRAD dataset. Eight prognostic genes [BUB1, KIF2C, CCNA2, CDC20, CCNB2, PBK, RRM2, and CDC45] and four hub genes (BUB1, KIF2C, CDC20, and PBK) potentially correlated with the pathogenesis of PCa were identified. A prognostic model with good predictive power for survival was constructed and was validated by the dataset in GSE21032. The survival analysis demonstrated that the expression of RRM2 was statistically significant to the prognosis of PCa, indicating that RRM2 may potentially play an important role in the PCa progression.

Conclusion: The present study implied that RRM2 was associated with prognosis and could be used as a potential therapeutic target for PCa clinical treatment.

Identification of potential circular RNA biomarkers in lung adenocarcinoma: A bioinformatics analysis and retrospective clinical study

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-associated mortality. Lung adenocarcinoma (LAC) is the most prevalent pathological subtype of NSCLC and accounts for ~40% of all lung cancer mortalities. There remains an urgent demand for the identification of novel biomarkers for the diagnosis and development of therapeutic strategies for LAC. In the present study, the profiles of the differentially-expressed circular RNAs (circRNAs) in LAC tissues compared with those in their corresponding non-cancerous tissues were obtained after analyzing the circRNA microarray dataset GSE101586. The expression pattern of the indicated circRNAs in the LAC tissues were subsequently verified using reverse transcription-quantitative PCR (RT-qPCR). The potential prognostic significance of these circRNAs in patients with LAC were then analyzed in a retrospective clinical study. A circRNA-microRNA (miR or miRNA)-mRNA regulatory network in LAC was established by using Cytoscape. In addition, a protein-protein interaction (PPI) network was plotted using the Search Tool for the Retrieval of Interacting Genes/Proteins and visualized through Cytoscape. The prognostic value of the hub genes found was then analyzed based on the Gene Expression Profiling Interactive Analysis database. In total, four differentially-expressed circRNAs were obtained from the GSE101586 microarray dataset, three of which (hsa_circ_0006220, hsa_circ_0072088 and hsa_circ_0001666) were confirmed by RT-qPCR to be highly expressed in LAC tissues. This retrospective clinical study revealed that higher expression levels of these three circRNAs were associated with poorer prognoses in patients with LAC. In addition, siRNA-mediated knockdown of these circRNAs was found to inhibit cell proliferation, migration and invasion in LAC cells. Following analysis of the molecular mechanism underlying these circRNAs, eight miRNAs, namely miR-520f, miR-1261, miR-1270, miR-620, miR-188-3p, miR-516b, miR-940 and miR-661, were identified with potential binding sites for these three circRNAs. Subsequently, 232 overlapped genes from the 795 upregulated genes in the LAC samples from The Cancer Genome Atlas database and 7,829 predicted target genes of the list of eight aforementioned miRNAs were obtained. A circRNA-miRNA-mRNA network was then constructed. A PPI network was established, with six hub genes, namely kinesin family member (KIF) 2C, KIF18B, maternal embryonic leucine zipper kinase, baculoviral IAP repeat-containing 5, polo-like kinase 1 and cytoskeleton-associated protein 2-like, determined from this network. Higher expression levels of each of these hub genes were found to be associated with poorer prognoses of patients with LAC. To conclude, data from the present study suggested that circRNAs hsa_circ_0006220, hsa_circ_0072088 and hsa_circ_0001666 have the potential to be viable biomarkers and therapeutic targets for LAC.

An Integrative Pan-Cancer Analysis of Kinesin Family Member C1 (KIFC1) in Human Tumors

Kinesin family member C1 (KIFC1) is a minus-end-directed motor protein that is critically involved in microtubule crosslinking and spindle formation. KIFC1 is essential for supernumerary centrosomes, and it is associated with the initiation and progression of cancers. In the present study, we initially reviewed the The Cancer Genome Atlas database and observed that KIFC1 is abundantly expressed in most types of tumors. We then analyzed the gene alteration profiles, protein expressions, prognoses, and immune reactivities of KIFC1 in more than 10,000 samples from several well-established databases. In addition, we conducted a gene set enrichment analysis to investigate the potential mechanisms for the roles of KIFC1 in carcinogenesis. The pan-cancer analysis of KIFC1 demonstrates significant statistical correlations of the KIFC1 expression with the clinical prognoses, the oncogenic signature gene sets, the myeloid-derived suppressor cell infiltration, the ImmunoScore, the immune checkpoints, the microsatellite instabilities, and the tumor mutational burdens across multiple tumors. These data may provide important information on the understanding of the role and mechanisms of KIFC1 in carcinogenesis and immunotherapy, as well as on the clinical progression of a variety of cancers.

A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion

BACKGROUND

Hepatocellular carcinoma (HCC) is prevalent worldwide with a high mortality rate. Prognosis prediction is crucial for improving HCC patient outcomes, but effective tools are still lacking. Characteristics related to vascular invasion (VI), an important process involved in HCC recurrence and metastasis, may provide ideas on prognosis prediction.

METHODS

Tools, including R 4.0.3, Funrich version 3, Cytoscape 3.8.2, STRING 11.5, Venny 2.1.0, and GEPIA 2, were used to perform bioinformatic analyses. The VI-related microRNAs (miRNAs) were identified using Gene Expression Omnibus HCC miRNA dataset GSE67140, containing 81 samples of HCC with VI and 91 samples of HCC without VI. After further evaluated the identified miRNAs based on The Cancer Genome Atlas database, a prognostic model was constructed via Cox regression analysis. The miRNAs in this model were also verified in HCC patients. Moreover, a nomogram was developed by integrating risk score from the prognostic model with clinicopathological parameters. Finally, a potential miRNA-mRNA network related to VI was established through weighted gene co-expression network analysis of HCC mRNA dataset GSE20017, containing 40 samples of HCC with VI and 95 samples of HCC without VI.

RESULTS

A prognostic model of 5 VI-related miRNAs (hsa-miR-126-3p, hsa-miR-148a-3p, hsa-miR-15a-5p, hsa-miR-30a-5p, hsa-miR-199a-5p) was constructed. The area under receiver operating characteristic curve was 0.709 in predicting 5-year survival rate, with a sensitivity of 0.74 and a specificity of 0.63. The nomogram containing risk score could also predict prognosis. Moreover, a VI-related miRNA-mRNA network covering 4 miRNAs and 15 mRNAs was established.

CONCLUSION

The prognostic model and nomogram might be potential tools in HCC management, and the VI-related miRNA-mRNA network gave insights into how VI was developed.

β-Catenin signaling in hepatocellular carcinoma

Deregulated Wnt/β-catenin signaling is one of the main genetic alterations in human hepatocellular carcinoma (HCC). Comprehensive genomic analyses have revealed that gain-of-function mutation of CTNNB1, which encodes β-catenin, and loss-of-function mutation of AXIN1 occur in approximately 35% of human HCC samples. Human HCCs with activation of the Wnt/β-catenin pathway demonstrate unique gene expression patterns and pathological features. Activated Wnt/β-catenin synergizes with multiple signaling cascades to drive HCC formation, and it functions through its downstream effectors. Therefore, strategies targeting Wnt/β-catenin have been pursued as possible therapeutics against HCC. Here, we review the genetic alterations and oncogenic roles of aberrant Wnt/β-catenin signaling during hepatocarcinogenesis. In addition, we discuss the implication of this pathway in HCC diagnosis, classification, and personalized treatment.