Silencing CDCA8 Suppresses Hepatocellular Carcinoma Growth and Stemness via Restoration of ATF3 Tumor Suppressor and Inactivation of AKT/β-Catenin Signaling

Identification of PANoptosis-related subtypes, construction of a prognosis signature, and tumor microenvironment landscape of hepatocellular carcinoma using bioinformatic analysis and experimental verification

Background

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide. PANoptosis is a recently unveiled programmed cell death pathway, Nonetheless, the precise implications of PANoptosis within the context of HCC remain incompletely elucidated.

Methods

We conducted a comprehensive bioinformatics analysis to evaluate both the expression and mutation patterns of PANoptosis-related genes (PRGs). We categorized HCC into two clusters and identified differentially expressed PANoptosis-related genes (DEPRGs). Next, a PANoptosis risk model was constructed using LASSO and multivariate Cox regression analyses. The relationship between PRGs, risk genes, the risk model, and the immune microenvironment was studies. In addition, drug sensitivity between high- and low-risk groups was examined. The expression profiles of these four risk genes were elucidate by qRT-PCR or immunohistochemical (IHC). Furthermore, the effect of CTSC knock down on HCC cell behavior was verified using in vitro experiments.

Results

We constructed a prognostic signature of four DEPRGs (CTSC, CDCA8, G6PD, and CXCL9). Receiver operating characteristic curve analyses underscored the superior prognostic capacity of this signature in assessing the outcomes of HCC patients. Subsequently, patients were stratified based on their risk scores, which revealed that the low-risk group had better prognosis than those in the high-risk group. High-risk group displayed a lower Stromal Score, Immune Score, ESTIMATE score, and higher cancer stem cell content, tumor mutation burden (TMB) values. Furthermore, a correlation was noted between the risk model and the sensitivity to 56 chemotherapeutic agents, as well as immunotherapy efficacy, in patient with. These findings provide valuable guidance for personalized clinical treatment strategies. The qRT-PCR analysis revealed that upregulated expression of CTSC, CDCA8, and G6PD, whereas downregulated expression of CXCL9 in HCC compared with adjacent tumor tissue and normal liver cell lines. The knockdown of CTSC significantly reduced both HCC cell proliferation and migration.

Conclusion

Our study underscores the promise of PANoptosis-based molecular clustering and prognostic signatures in predicting patient survival and discerning the intricacies of the tumor microenvironment within the context of HCC. These insights hold the potential to advance our comprehension of the therapeutic contribution of PANoptosis plays in HCC and pave the way for generating more efficacious treatment strategies.

TuBG1 promotes hepatocellular carcinoma via ATR/P53-apoptosis and cycling pathways

BACKGROUND

As reported, γ-tubulin (TuBG1) is related to the occurrence and development of various types of malignant tumors. However, its role in hepatocellular cancer (HCC) is not clear. The present study was to investigate the relationship between TuBG1 and clinical parameters and survival in HCC patients.

METHODS

The correlation between TuBG1 and clinical parameters and survival in HCC patients was explored by bioinformatics analysis. Immunohistochemistry was used for the verification. The molecular function of TuBG1 was measured using colony formation, scratch assay, trans-well assay and flow cytometry. Gene set enrichment analysis (GSEA) was used to pick up the enriched pathways, followed by investigating the target pathways using Western blotting. The tumor-immune system interactions and drug bank database (TISIDB) was used to evaluate TuBG1 and immunity. Based on the TuBG1-related immune genes, a prognostic model was constructed and was further validated internally and externally.

RESULTS

The bioinformatic analysis found high expressed TuBG1 in HCC tissue, which was confirmed using immunohistochemistry and Western blotting. After silencing the TuBG1 in HCC cell lines, more G1 arrested cells were found, cell proliferation and invasion were inhibited, and apoptosis was promoted. Furthermore, the silence of TuBG1 increased the expressions of Ataxia-Telangiectasia and Rad-3 (ATR), phospho-P38 mitogen-activated protein kinase (P-P38MAPK), phospho-P53 (P-P53), B-cell lymphoma-2 associated X protein (Bax), cleaved caspase 3 and P21; decreased the expressions of B-cell lymphoma-2 (Bcl-2), cyclin D1, cyclin E2, cyclin-dependent kinase 2 (CDK2) and CDK4. The correlation analysis of immunohistochemistry and clinical parameters and survival data revealed that TuBG1 was negatively correlated with the overall survival. The constructed immune prognosis model could effectively evaluate the prognosis.

CONCLUSIONS

The increased expression of TuBG1 in HCC is associated with poor prognosis, which might be involved in the occurrence and development of HCC.

Comprehensive analysis of the potential pathogenesis of COVID-19 infection and liver cancer

BACKGROUND

A growing number of clinical examples suggest that coronavirus disease 2019 (COVID-19) appears to have an impact on the treatment of patients with liver cancer compared to the normal population, and the prevalence of COVID-19 is significantly higher in patients with liver cancer. However, this mechanism of action has not been clarified.

AIM

To investigate the disease relevance of COVID-19 in liver cancer.

METHODS

Gene sets for COVID-19 (GSE180226) and liver cancer (GSE87630) were obtained from the Gene Expression Omnibus database. After identifying the common differentially expressed genes (DEGs) of COVID-19 and liver cancer, functional enrichment analysis, protein-protein interaction network construction and screening and analysis of hub genes were performed. Subsequently, the validation of the differential expression of hub genes in the disease was performed and the regulatory network of transcription factors and hub genes was constructed.

RESULTS

Of 518 common DEGs were obtained by screening for functional analysis. Fifteen hub genes including aurora kinase B, cyclin B2, cell division cycle 20, cell division cycle associated 8, nucleolar and spindle associated protein 1, etc., were further identified from DEGs using the "cytoHubba" plugin. Functional enrichment analysis of hub genes showed that these hub genes are associated with P53 signalling pathway regulation, cell cycle and other functions, and they may serve as potential molecular markers for COVID-19 and liver cancer. Finally, we selected 10 of the hub genes for in vitro expression validation in liver cancer cells.

CONCLUSION

Our study reveals a common pathogenesis of liver cancer and COVID-19. These common pathways and key genes may provide new ideas for further mechanistic studies.

Knockdown of LMNA inhibits Akt/β-catenin-mediated cell invasion and migration in clear cell renal cell carcinoma cells

The LMNA gene encoding lamin A/C is amplified in some clear cell renal cell carcinoma (ccRCC) samples. Our data showed that depletion of the tumor suppressor PBRM1 can upregulate lamin A/C levels, and lamin A/C could interact with PBRM1. However, the role of lamin A/C in ccRCC is not yet fully understood. Our functional assays showed that although the proliferation ability was slightly impaired after LMNA depletion, the migration and invasion of ccRCC cells were significantly inhibited. This suppression was accompanied by a reduction in MMP2, MMP9, AKT/p-AKT, and Wnt/β-catenin protein levels. Our data therefore suggest that lamin A/C, as an interaction partner of the tumor suppressor PBRM1, plays a crucial role in tumor invasion and metastasis in ccRCC.

Prognostic related gene index for predicting survival and immunotherapeutic effect of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common malignant liver tumor. It is an aggressive disease with high mortality rate. In this study, we investigated a new prognosis-related gene index (PRGI) that can predict the survival and efficacy of immunotherapy in patients with HCC. RNA-seq data and clinical data of HCC samples were obtained from the cancer genome atlas and ICGC databases. Prognosis-related genes were obtained using log-rank tests and univariate Cox proportional hazards regression. Univariate and multivariate analyses were performed on the overall survival rate of patients with prognosis-related genes and multiple clinicopathological factors, and a nomogram was constructed. A PRGI was then constructed based on least absolute shrinkage and selection operator or multivariate Cox Iterative Regression. The possible correlation between PRGI and immune cell infiltration or immunotherapy efficacy was discussed. Eight genes were identified to construct the PRGI. PRGI can predict the infiltration of immune cells into the tumor microenvironment of HCC and the response to immunotherapy. PRGI can accurately predict the survival rate of patients with HCC, reflect the immune microenvironment, and predict the efficacy of immunotherapy.

Comprehensive Analysis of METTLs (METTL1/13/18/21A/23/25/2A/2B/5/6/9) and Associated mRNA Risk Signature in Hepatocellular Carcinoma

Currently, 80%-90% of liver cancers are hepatocellular carcinomas (HCC). HCC patients develop insidiously and have an inferior prognosis. The methyltransferase-like (METTL) family principal members are strongly associated with epigenetic and tumor progression. The present study mainly analyzed the value of METTLs (METTL1/13/18/21A/23/25/2A/2B/5/6/9) and associated mRNA risk signature for HCC. METTLs expression is upregulated in HCC and is a poor prognostic factor in HCC. METTLs were upregulated in patients older than 60 and associated with grade. Except for METTL25, the remaining 10 genes were associated with the HCC stage, invasion depth (T). In addition, METTLs showed an overall alteration rate of 50%. Except for METTL13/2A/25/9, the expression of the other seven genes was significantly associated with overall survival, disease-specific survival, and progression-free survival. Multivariate studies have shown that METTL21A/6 can be an independent prognostic marker in HCC. A total of 664 mRNAs were selected based on Pearson correlation coefficient (R > 0.5), unsupervised consensus clustering, weighted coexpression network analysis, and univariate Cox analysis. These mRNAs were significantly associated with METTLs and were poor prognostic factors in HCC patients. The least absolute shrinkage and selection operator (lasso) was used to construct the best METTLs associated with mRNA risk signature. The mRNA risk signature was significantly associated with age, stage, and t grade. The mRNA high-risk group had higher TP53 and RB1 mutations. This study constructed a nomogram with the mRNA risk profile and clinicopathological features, which could better predict the OS of individuals with HCC. We also analyzed associations between METTLs and mRNA risk signatures in epithelial-mesenchymal transition, immune checkpoints, immune cell infiltration, tumor mutational burden, microsatellite instability, cancer stem cells, tumor pathways, and drug sensitivity. In addition, this study constructed a protein interaction network network including METTLs and mRNA risk signature genes related to tumor microenvironment remodeling based on single-cell sequencing. In conclusion, this study provides a theoretical basis for the mechanism, biomarker screening, and treatment of HCC.

CDCA8 promotes bladder cancer survival by stabilizing HIF1α expression under hypoxia

Hypoxia is an essential hallmark of solid tumors and HIF1α is a central regulator of tumor cell adaptation and survival in the hypoxic environment. In this study, we explored the biological functions of cell cycle division-related gene 8 (CDCA8) in bladder cancer (BCa) cells in the hypoxic settings. Specifically, we found that CDCA8 was significantly upregulated in BCa cell lines and clinical samples and its expression was positively correlated with advanced BCa stage, grade, and poor overall survival (OS). The expression of CDCA8 proteins was required for BCa cells to survive in the hypoxic condition. Mechanistically, CDCA8 stabilizes HIF1α by competing with PTEN for AKT binding, consequently leading to PTEN displacement and activation of the AKT/GSK3β signaling cascade that stimulates HIF1α protein stability. Significantly, HIF1α proteins bind to CDCA8 promoter for transcriptional activation, forming a positive-feedback loop to sustain BCa tumor cells under oxygen-deficient environment. Together, we defined CDCA8 as a key regulator for BCa cells to sense and prevail oxygen deprivation and as a novel BCa therapeutic target.

Three E2F target-related genes signature for predicting prognosis, immune features, and drug sensitivity in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is extremely malignant and difficult to treat. The adenoviral early region 2 binding factors (E2Fs) target pathway is thought to have a major role in tumor growth. This study aimed to identify a predictive E2F target signature and facilitate individualized treatment for HCC patients. Methods: We constructed an E2F target-related gene profile using univariate COX and LASSO regression models and proved its predictive efficacy in external cohorts. Furthermore, we characterized the role of the E2F target pathway in pathway enrichment, immune cell infiltration, and drug sensitivity of HCC. Results: Lasso Cox regression created an E2F target-related gene signature of GHR, TRIP13, and CDCA8. HCC patients with high risk were correlated with shorter survival time, immune evasion, tumor stem cell characteristics and high sensitivity to Tipifarnib and Camptothecin drugs. Conclusion: Hepatocellular carcinoma prognosis was predicted by an E2F target signature. This finding establishes the theoretical usefulness of the E2F target route in customized identification and treatment for future research.

M7G methylated core genes (METTL1 and WDR4) and associated RNA risk signatures are associated with prognosis and immune escape in HCC

N7 methylguanosine (m7G) has a crucial role the development of hepatocellular carcinoma (HCC). This study aimed to investigate the impact of the m7G methylation core genes (METTL1 and WDR4) and associated RNA risk signatures on HCC. we found m7G methylation core genes (METTL1 and WDR4) were upregulated in four HCC cell lines, and downregulation of METTL1 and WDR4 attenuated HCC cell proliferation, migration, and invasion. Moreover, METTL1 and WDR4 are upregulated in HCC tissues, and that there is a significant positive correlation between them. METTL1 and WDR4 were identified as independent prognostic markers for HCC by employing overall survival (OS), disease-specific survival (DSS), Progression Free Interval survival (PFI), and univariate/multivariate Cox analyses. We identified 1479 coding RNAs (mRNAs) and 232 long non-coding RNAs (lncRNAs) associated with METTL1 / WDR4 by using weighted coexpression network analysis (WGCNA) and co-clustering analysis. The least absolute shrinkage and selection operator (lasso) were used to constructing mRNA and lncRNA risk signatures associated with the METTL1 / WDR4. These risk were independent poor prognostic factors in HCC. Furthermore, we found that METTL1 / WDR4 expression and mRNA / lncRNA risk scores were closely associated with TP53 mutations. Clinicopathological features correlation results showed that METTL1 / WDR4 expression and mRNA / lncRNA risk score were associated with the stage and invasion depth (T) of HCC. To predict the overall survival of HCC individuals, we constructed a nomogram with METTL1/WDR4 expression, mRNA/lncRNA risk score, and clinicopathological features. In addition, we combined single-cell sequencing datasets and immune escape-related checkpoints to construct an immune escape-related protein-protein interaction(PPI) network. In conclusion, M7G methylated core genes (METTL1 and WDR4) and associated RNA risk signatures are associated with prognosis and immune escape in HCC.

A novel prognostic signature for hepatocellular carcinoma based on SUMOylation-related genes

SUMOylation (SUMO modification) has been confirmed to play an essential role in the progression of various malignancies. As the value of SUMOylation-related genes (SRGs) in prognosis prediction of hepatocellular carcinoma (HCC) has not been explored, we aim to construct an HCC SRGs signature. RNA sequencing was utilized to identify differentially expressed SRGs. The 87 identified genes were used in Univariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) analysis to build a signature. The accuracy of the model was validated by the ICGC and GEO datasets. The GSEA revealed that the risk score was associated with common cancer-related pathways. The ssGSEA showed that NK cells in the high-risk group were significantly reduced. The sensitivities of anti-cancer drugs confirmed the sensitivity of the high-risk group to sorafenib was lower. Further, our cohort showed that risk scores were correlated with advanced grade and vascular invasion (VI). Finally, the results of H&E staining and immunohistochemistry of Ki67 showed that higher-risk patients are more malignant.

Cell division cycle-associated 8 is a prognostic biomarker related to immune invasion in hepatocellular carcinoma

BACKGROUND

Cell division cycle-associated 8 (CDCA8) is involved in numerous signaling networks, and it serves a crucial modulatory function in multiple malignant tumors. However, its significance in prognosis and immune infiltration in hepatocellular carcinoma (HCC) remains unclear.

MATERIALS AND METHODS

Herein, we examined the CDCA8 levels in tumor tissues, as well as its associated signaling pathways and correlation with immune infiltration. Additionally, we further clarified the prognostic significance of CDCA8 among HCC patients. HCC patient information was recruited from The Cancer Genome Atlas (TCGA). Using bioinformatics, the following parameters were analyzed among HCC patients: CDCA8 expression, enrichment analysis, immune infiltration, and prognosis analysis. Moreover, we employed in vitro investigations, such as, qRT-PCR, immunohistochemistry (IHC), and cell functional experiments to validate our results.

RESULTS

Elevated CDCA8 expression in HCC patients was markedly associated with T stage, pathological status (PS), tumor status (TS), histologic grade (HG), and AFP. Elevated CDCA8 expression HCC patients exhibited reduced overall survival (OS) (p < 0.001), disease-specific survival (DSS) (p < 0.001), and progress free interval (PFI) H(p < 0.001). According to the ROC analysis, the area under the curve (AUC) was 0.997. Multivariate analysis revealed that CDCA8 was a stand-alone prognostic indicator of patient OS (p = 0.009) and DSS (p = 0.006). A nomogram was then generated based on the multivariate analysis, and the C-indexes and calibration chart revealed excellent predictive performance in determining HCC patient outcome. Based on the GSEA analysis, CDCA8 modulated the P53, Notch, PPAR, E2F networks. We observed a direct link between CDCA8 levels and Th2 and T helper cells, and a negative link between CDCA8 levels and dendritic cells (DC), neutrophils, cytotoxic cells, and CD8 T cells. Furthermore, CDCA8 deficiency inhibited liver cancer cell proliferation and invasion.

CONCLUSION

In conclusion, these findings indicate that CDCA8 is a new molecular bioindicator of HCC patient prognosis, and it is an excellent candidate for therapeutic target against HCC.

Let-7c-5p down-regulates immune-related CDCA8 to inhibit hepatocellular carcinoma

OBJECTIVE

The aim of this study is to investigate the effect of let-7c-5p on the malignant behaviors of hepatocellular carcinoma (HCC) and its specific molecular pathway.

METHODS

Differential expression and survival analysis of let-7c-5p were obtained from The Cancer Genome Atlas database, and then its expression level was preliminarily verified through qPCR. The effect of let-7c-5p on the malignant phenotype of HCC cells was subsequently evaluated using CCK-8, transwell, wound healing, and flow cytometry assays. Downstream mRNA regulated by let-7c-5p was identified and confirmed by ENCORI database, dual-luciferase reporter, and western blot assays. The immunocorrelation of genes was evaluated by Xiantao tool, and TIMER and TISIDB databases.

RESULTS

The expression level of let-7c-5p in HCC was obviously reduced, which was found to be closely associated with the short survival time of HCC patients. Cell phenotypic experiments showed that let-7c-5p inhibited proliferation, invasion, and migration and promoted apoptosis of HCC cells. Dual-luciferase reporter and western blot analysis demonstrated that CDCA8 is a downstream mRNA of let-7c-5p and is negatively regulated by it. Rescue experiment revealed that CDCA8 reversed the effect of let-7c-5p on the malignant phenotype of HCC cells. Furthermore, analysis of the public database revealed that CDCA8 is related to some immune cells and immunomodulators, and that it may participate in the regulation of some immune pathways and immune functions.

CONCLUSION

Let-7c-5p has been proved to suppress HCC by down-regulating immune-related CDCA8, which will help understand the pathogenesis of HCC and develop drugs for its treatment.

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.

CDCA8/SNAI2 Complex Activates CD44 to Promote Proliferation and Invasion of Pancreatic Ductal Adenocarcinoma

Simple Summary

There is an urgent need to find an effective therapeutic target for pancreatic cancer owing to late diagnosis, tumor metastasis, and current ineffective targeted drugs. We aimed to identified potential targets for the treatment of pancreatic cancer. In this study, the specific mechanism by which the CDCA8 contributes to pancreatic cancer progression via the activation of CD44 was clarified, and CDCA8 knockdown inhibited the proliferation and metastasis of pancreatic cancer. This finding may provide a promising target for future targeted therapies of pancreatic cancer.

Abstract

(1) Background: Recently, cell division cycle associated 8 (CDCA8) was found to be overexpressed in pancreatic ductal adenocarcinoma (PDAC). Here, we aimed to explore the specific mechanism of action of CDCA8 in PDAC progression. (2) Methods: All human PDAC samples and clinical data were collected from Huashan Hospital, Fudan University. All experimental studies were carried out using many in vitro and in vivo assays, including lentiviral transfection, real-time quantitative polymerase chain reaction (qPCR), western blotting, co-immunoprecipitation (Co-IP), chromatin IP (ChIP)-qPCR, dual-luciferase reporter, and in vivo imaging assays. (3) Results: Clinical data analysis of human PDAC samples revealed that CDCA8 overexpression were positively and negatively associated with tumor grade (p = 0.007) and overall survival (p = 0.045), respectively. CDCA8 knockdown inhibited PDAC proliferation and invasion in in vitro and in vivo assays. CD44 was also up-regulated by CDCA8 during PDAC progression. CDCA8 could be combined with SNAI2 to form a CDCA8/SNAI2 complex to integrate with the CD44 promoter as indicated through ChIP-qPCR and dual-luciferase reporter assays. (4) Conclusion: We showed that CDCA8-CD44 axis plays a key role in the proliferation and invasion of PDAC, which provides a potential target for treatment.

ATG101-related signature predicts prognosis and therapeutic option in hepatocellular carcinoma

Autophagy plays a critical role in tumor pathogenesis. However, autophagy-related signature in Hepatocellular carcinoma (HCC) has not been revealed yet. We quantified the levels of various cancer hallmarks and identified ATG101 as the major risk factor for overall survival in HCC. A robust ATG101-related gene signature (ATS) for prognosis was constructed using a combination of bioinformatic and statistical approaches. Additionally, genetic and immunological properties were measured between ATS-high and ATS-low groups. The ATS signature was associated with shortened overall survival in HCC patients independently of clinicopathological characteristics. ATS status defines an inflamed yet exhausted tumor microenvironment, in which the activities of the exhausted CD8+ or CD4+ T cells were strongly associated with ATS. The ATS signature predicts the drug resistance to the immunotherapy, thus a combination of targeted therapy and immunotherapy might be suitable for ATS-high patients. This work shed light on the function of ATG101-related genes in HCC and revealed that the ATS signature may be a useful prognostic biomarker for differentiating molecular and immunological features and predicting probable response to the therapy.

KNTC1 as a putative tumor oncogene in pancreatic cancer

Purpose

Recent studies have demonstrated that kinetochore-associated protein 1 (KNTC1) plays a significant role in the carcinogenesis of numerous types of cancer. This study aimed to explore the role and possible mechanisms of KNTC1 in the development of pancreatic cancer.

Methods and results

We analyzed differentially expressed genes by RNA sequencing in three paired pancreatic cancer and para-cancerous tissue samples and found that the expression of KNTC1 was significantly upregulated in pancreatic cancer. A Cancer and Tumor Gene Map pan-analysis showed that high expression of KNTC1 was related to poor prognosis in 9499 tumor samples. With immunohistochemical staining, we found that the high expression of KNTC1 in pancreatic cancer was related to pathological grade and clinical prognosis. Similarly, RT-PCR results indicated that the expression of KNTC1 was higher in three groups of pancreatic cancer cell lines (BxPC-3, PANC-1, and SW1990) than in normal pancreatic ductal cells. We introduced lentivirus-mediated shRNA targeting KNTC1 into PANC-1 and SW1990 cells and found that KNTC1 knockdown significantly decreased cell growth and increased cell apoptosis compared to the control group cells. Bioinformatic analysis of the cell expression profile revealed that differential genes were mainly enriched in the cell cycle, mitosis, and STAT3 signaling pathways, and co-immunoprecipitation confirmed an interaction between KNTC1 and cell division cycle associated 8.

Conclusions

KNTC1 could be linked to the pathophysiology of pancreatic cancer and may be an early diagnostic marker of cervical precancerous lesions.

Identification and Validation of Genomic Subtypes and a Prognostic Model Based on Antigen-Presenting Cells and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

Currently, the prognosis of hepatocellular carcinoma (HCC) is poor, and there is a lack of effective targeted therapy. As key mediators of the immune response, the prognostic value of antigen-presenting cells (APCs) in HCC still remains unclear. In this study, we aimed to identify APC-related genomic subtypes and develop a novel prognostic model in HCC. Our results indicated that overall survival (OS) and the level of immune infiltration significantly differed between different APC clusters. By analyzing the gene expression profile between APC clusters, APC-related genomic subtypes were identified. There was a significant difference in OS and tumor microenvironment infiltration in HCC patients with different genomic subtypes. With the aid of genomic subtypes, significantly differentially expressed genes were screened to generate a novel prognostic model. The risk score of the model had a significant positive correlation with APCs and was associated with immune checkpoint expressions. Through the clinical cohort collected from the First Affiliated Hospital of Wenzhou Medical University, the prognostic value of the risk score was further validated. Moreover, after the risk score and clinical characteristics were combined, a nomogram was constructed to evaluate the prognosis for HCC patients. In conclusion, we mainly identified the APC-related genomic subtypes and generated a novel prognostic model to improve the prognostic prediction and targeted therapy for HCC patients.

Comprehensive Molecular Analyses of a Macrophage-Related Gene Signature With Regard to Prognosis, Immune Features, and Biomarkers for Immunotherapy in Hepatocellular Carcinoma Based on WGCNA and the LASSO Algorithm

Macrophages have been reported to exert a crucial role in hepatocellular carcinoma (HCC). This study aimed to explore the macrophage-related genes and establish a macrophage-related signature (MRS) model to predict the overall survival (OS) of patients with HCC based on these genes’ expression. We screened the macrophage-related gene module by weighted gene coexpression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO) Cox regression analysis was utilized for further selection, and the selected genes were entered into stepwise regression to develop the MRS model, which was further validated in the Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC) datasets. We analyzed the biological phenotypes associated with macrophages in terms of functional enrichment, tumor immune signature, and tumor mutational signature. The patient’s response to immunotherapy was inferred by the tumor immune dysfunction and exclusion (TIDE) score, the immunophenotype score (IPS), and the IMvigor210 dataset. A novel MRS model was established based on the LASSO regression coefficients of the genes PON1, IL15RA, NEIL3, HILPDA, PFN2, HAVCR1, ANXA10, CDCA8, EPO, S100A9, TTK, KLRB1, SPP1, STC2, CYP26B1, GPC1, G6PD, and CBX2. In either dataset, MRS was identified as an independent risk factor for OS in HCC patients. Additionally, our research indicated that a high-risk score in the MRS model was significantly correlated with tumor staging, pathological grade, tumor–node–metastasis (TNM) stage, and survival. Several genes of the human leukocyte antigen (HLA) family and immune checkpoints were highly expressed in the high-risk group. In addition, the frequency of tumor mutations was also higher in the high-risk group. According to our analyses, a higher risk score in the MRS model may predict a better response to immunotherapy.

Identification of unique transcriptomic signatures and key genes through RNA sequencing and integrated WGCNA and PPI network analysis in HIV infected lung cancer

With the widespread use of highly active antiretroviral therapy (HARRT), the survival time of AIDS patients has been greatly extended. However, the incidence of lung cancer in HIV-infected patients is increasing and has become a major problem threatening the survival of AIDS patients. The aim of this study is to use Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene analysis to find possible key genes involved in HIV-infected lung cancer. In this study, using lung tissue samples from five pairs of HIV-infected lung cancer patients, second-generation sequencing was performed and transcriptomic data were obtained. A total of 132 HIV-infected lung cancer-related genes were screened out by WGCNA and differential gene expression analysis methods. Based on gene annotation analysis, these genes were mainly enriched in mitosis-related functions and pathways. In addition, in protein-protein interaction (PPI) analysis, a total of 39 hub genes were identified. Among them, five genes (ASPM, CDCA8, CENPF, CEP55, and PLK1) were present in both three hub gene lists (intersection gene, DEGs, and WCGNA module) suggesting that these five genes may become key genes involved in HIV-infected lung cancer.

A Cell Cycle-Related 13-mRNA Signature to Predict Prognosis in Hepatocellular Carcinoma

We aimed to propose a cell cycle-related multi/mRNA signature (CCS) for prognosis prediction and uncover new tumor-driver genes for hepatocellular carcinoma (HCC). Cell cycle-related gene sets and HCC samples with mRNA-Seq data were retrieved from public sources. The genes differentially expressed in HCCs relative to normal peritumoral tissues were extracted through statistical analysis. The CCS was constructed by Cox regression analyses. Predictive capacity and clinical practicality of the signature were evaluated and validated. The expression of the function-unknown genes in the CCS was determined by RT-qPCR. Candidate gene TICRR was selected for subsequent validation through functional experiments. A cell cycle-related 13-mRNA signature was generated from the exploratory cohort [The Cancer Genome Atlas (TCGA), n = 371)]. HCC cases were classified as high- vs. low-risk groups per overall survival (OS) [hazard ratio (HR) = 2.699]. Significantly, the CCS exhibited great predictive value for prognosis in three independent cohorts, particularly in GSE76427 cohort [area under the curve (AUC) = 0.835/0.822/0.808/0.821/0.826 at 1/2/3/4/5 years]. The nomogram constructed by integrating clinicopathological features with the CCS indicated high accuracy and practicability. Significant enrichment of tumorigenesis-associated pathways was observed in the high-risk patients by Gene Set Enrichment Analysis (GSEA). RT-qPCR revealed that TICRR was overexpressed in HCC samples. Increased TICRR expression implied poor prognosis in HCC patients. Furthermore, depletion of TICRR in HCC cells decreased cell proliferation and the G1/S transition. In conclusion, the established 13-CCS had efficacy in prognostic prediction of HCC patients. Additionally, TICRR was demonstrated as a tumor-driver gene for this deadly disease.

Development an Immune-Related MicroRNA Risk Index in Hepatocellular Carcinoma

Purpose

Hepatocellular carcinoma (HC) has emerged as one of the most prevalent malignancies on a global scale. Recently, immunotherapy has achieved favorable effectiveness in the management of multiple cancers. However, there are limited therapeutic options for advanced HC. As the liver is a special immune organ, we intend to uncover potential and effective immunotherapeutic modalities for HC. Our study was designed to develop specific immune-related miRNAs (IRMs) for outcome assessment and individualized strategies for the management of HC.

Methods

The miRNA-seq and survival data of TCGA-LIHC dataset was enrolled into this program. We first collected IRMs from Immune-miR website. Differentially expression analysis was applied to screen aberrantly expressed IRMs. In order to set up an IRM-related index (IRMRI) in HC, we conducted the Cox relevant methods. Next, the statistical approaches (survival curve and ROC curve analyses) were utilized to detect the evaluation capacity of our IRMRI. Subsequently, we obtained the target genes of hub miRNAs from IRMRI through three miRNA-related predictive online tools (miRDB, miRTarBase, and TargetScan websites).

Results

Five IRMs were determined to develop the IRMRI. It can effectively segregate all HC cases from two different risk subgroups. We identified a marked discrepancy in survival outcome between the two groups by survival analysis and confirmed the reliability of IRMRI in two testing sets. Moreover, we collected 10 hub target genes (ESR1, IGF1, PDGFRB, JUN, MYC, ZWINT, MAD2L1, TOP2A, KIF11, and CDCA8) which were strongly linked to HC progression and malignant behavior.

Conclusion

We screened out five hub IRMs with clinical value and constructed a risk index model in HC, which can precisely assess the risk status and outcome of patients to a certain extent.

Multiple datasets to explore the tumor microenvironment of cutaneous squamous cell carcinoma

BACKGROUND

Cutaneous squamous cell carcinoma (cSCC) is one of the most frequent types of cutaneous cancer. The composition and heterogeneity of the tumor microenvironment significantly impact patient prognosis and the ability to practice precision therapy. However, no research has been conducted to examine the design of the tumor microenvironment and its interactions with cSCC.

MATERIAL AND METHODS

We retrieved the datasets GSE42677 and GSE45164 from the GEO public database, integrated them, and analyzed them using the SVA method. We then screened the core genes using the WGCNA network and LASSO regression and checked the model's stability using the ROC curve. Finally, we performed enrichment and correlation analyses on the core genes.

RESULTS

We identified four genes as core cSCC genes: DTYMK, CDCA8, PTTG1 and MAD2L1, and discovered that RORA, RORB and RORC were the primary regulators in the gene set. The GO semantic similarity analysis results indicated that CDCA8 and PTTG1 were the two most essential genes among the four core genes. The results of correlation analysis demonstrated that PTTG1 and HLA-DMA, CDCA8 and HLA-DQB2 were significantly correlated.

CONCLUSIONS

Examining the expression levels of four primary genes in cSCC aids in our understanding of the disease's pathophysiology. Additionally, the core genes were found to be highly related with immune regulatory genes, suggesting novel avenues for cSCC prevention and treatment.

Immune-related lincRNA pairs predict prognosis and therapeutic response in hepatocellular carcinoma

Growing evidence has demonstrated the functional relevance of long intergenic noncoding RNAs (lincRNAs) to tumorigenesis and immune response. However, immune-related lincRNAs and their value in predicting the clinical outcomes of patients with liver cancer remain largely unexplored. Herein, we utilized the strategy of iterative gene pairing to construct a tumor-specific immune-related lincRNA pairs signature (IRLPS), which did not require specific expression levels, as an indicator of patient outcomes. The 18-IRLPS we developed was associated with overall survival, tumor progression, and recurrence in liver cancer patients. Multivariate analysis revealed that the risk model was an independent predictive factor. A high IRLPS risk was correlated suppressive immune microenvironment, and IRLPS-high patients might benefit more from CD276 blockade or TMIGD2 agonist. Patients in the high-risk group were associated with elevated tumor mutation, increased sensitivity to dopamine receptor antagonists, cisplatin, doxorubicin, and mitomycin but more resistance to vinblastine. Mechanistically, IRLPS high scores might lead to poor prognosis by promoting cell proliferation and metabolic reprogramming. The prognostic significance of the 18-IRLPS was confirmed in independent cancer datasets. These findings highlighted the robust predictive performances of the 18-IRLPS for prognosis and personalized treatment.

Borealin Promotes Tumor Growth and Metastasis by Activating the Wnt/β-Catenin Signaling Pathway in Hepatocellular Carcinoma

Background and Aims

Hepatocellular carcinoma (HCC) is a common malignant disease with high morbidity and mortality throughout the world. While Borealin is a putative oncogene that is dysregulated in multiple tumors, its exact role in HCC remains less investigated.

Methods

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) assays were employed to examine the relative amount of Borealin. Gene set enrichment analysis (GSEA) and other bioinformatic analyses were implemented to probe into the potential functions of Borealin. The biological roles and mechanisms of Borealin in the tumorigenesis and development of HCC were further evaluated using a battery of functional assays in vivo and in vitro.

Results

Borealin was enhanced in the HCC tissue samples and hepatoma cells when compared with the nontumor tissues and normal liver cells. Higher Borealin expression was positively linked with advanced pathological phenotypes and inferior overall survival. The overexpression of Borealin promoted the cells’ abilities on proliferation, invasion and epithelial–mesenchymal transition (EMT) in vitro, facilitated tumor growth and lung metastasis in vivo, whereas the silencing of Borealin inhibited these capabilities in vitro. Furthermore, Borealin interacted with β-catenin and further activated the Wnt/β-catenin signaling pathway, which endowed HCC cells with highly aggressive and metastatic capabilities.

Conclusion

Borealin was identified as an oncogene that could promote HCC growth and metastasis by activating the WNT/β-catenin signaling pathway. These findings extended the understanding of Borealin in HCC tumorigenesis and development and highlighted the significance of Borealin in HCC diagnosis and treatment.

Methylation-dependent and -independent roles of EZH2 synergize in CDCA8 activation in prostate cancer

Cell division cycle-associated 8 (CDCA8) is a component of chromosomal passenger complex (CPC) that participates in mitotic regulation. Although cancer-related CDCA8 hyperactivation has been widely observed, its molecular mechanism remains elusive. Here, we report that CDCA8 overexpression maintains tumorigenicity and is associated with poor clinical outcome in patients with prostate cancer (PCa). Notably, enhancer of zeste homolog 2 (EZH2) is identified to be responsible for CDCA8 activation in PCa. Genome-wide assays revealed that EZH2-induced H3K27 trimethylation represses let-7b expression and thus protects the let-7b-targeting CDCA8 transcripts. More importantly, EZH2 facilitates the self-activation of E2F1 by recruiting E2F1 to its own promoter region in a methylation-independent manner. The high level of E2F1 further promotes transcription of CDCA8 along with the other CPC subunits. Taken together, our study suggests that EZH2-mediated cell cycle regulation in PCa relies on both its methyltransferase and non-methyltransferase activities.

Screening of Potential Key Biomarkers for Ewing Sarcoma: Evidence from Gene Array Analysis

Background

Ewing’s sarcoma (ES) is a common bone cancer in children and adolescents. There are ethnic differences in the incidence and treatment effects. People have made great efforts to clarify the cause; however, the molecular mechanism of ES is still poorly understood.

Methods

We download the microarray datasets GSE68776, GSE45544 and GSE17674 from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) of the three datasets were screened and enrichment analysis was performed. STRING and Cytoscape were used to carry out module analysis, building a protein–protein interaction (PPI) network. Finally, a series of analyses such as survival analysis and immune infiltration analysis were performed on the selected genes.

Results

A total of 629 differentially expressed genes were screened, including 206 up-regulated genes and 423 down-regulated genes. The pathways and rich-functions of DEGs include protein activation cascade, carbohydrate binding, cell-cell adhesion junctions, mitotic cell cycle, p53 pathway, and cancer pathways. Then, a total of 10 hub genes were screened out. Biological process analysis showed that these genes were mainly enriched in mitotic nuclear division, protein kinase activity, cell division, cell cycle, and protein phosphorylation.

Conclusion

Survival analysis and multiple gene comparison analysis showed that CDCA8, MAD2L1 and FANCI may be involved in the occurrence and prognosis of ES. The purpose of our study is to clarify the DEG and key genes, which will help us know more about the molecular mechanisms of ES, provide potential pathway or targets for the diagnosis and treatment.

Development and Validation of a Pyroptosis-Related Signature for Predicting Prognosis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has emerged as a primary health problem and threat to global mortality, especially in China. Since pyroptosis as a new field for HCC prognosis is not well studied, it is important to open a specific prognostic model. In this study, consensus clustering method for 42 pyroptosis-related genes to classify 374 HCC patients in the TCGA database. After cox regression analysis of the differentially expressed genes between the two clusters, LASSO-Cox analysis was then performed to construct a pyroptosis-related prognostic model with 11 genes including MMP1, KPNA2, LPCAT1, NEIL3, CDCA8, SLC2A1, PSRC1, CBX2, HAVCR1, G6PD, MEX3A. The ICGC dataset was served as the validation cohort. Patients in the high-risk group had significantly lower overall survival (OS) rates than those in the low-risk group (p &lt; 0.05). COX regression analysis showed that our model could be used as an independent prognostic factor to predict prognosis of patients and was significantly correlated with clinicopathological characteristics. Nomogram showing the stability of the model predicting the 1, 3, 5 year survival probability of patients. In addition, based on the risk model, ssGSEA analysis revealed significant differences in the level of immune cell infiltration and activation of immune-related functional pathways between high and low-risk groups, and patients with the high-risk score may benefit more from treatment with immune checkpoint inhibitors. Furthermore, patients in the high-risk group were more tend to develop chemoresistance. Overall, we identified a novel pyroptosis-related risk signature for prognosis prediction in HCC patients and revealed the overall immune response intensity of the tumor microenvironment. All these findings make the pyroptosis signature shed light upon a latent therapeutic strategy aimed at the treatment and prevention of cancers.

Liquid-Liquid Phase Separation-Related Genes Associated with Tumor Grade and Prognosis in Hepatocellular Carcinoma: A Bioinformatic Study

Aim

The aim of the present study was to identify the association between tumor grade and liquid-liquid phase separation (LLPS)-related genes, and to generate a LLPS-related gene-based risk index (LLPSRI) as a prognostic tool for hepatocellular carcinoma (HCC).

Methods

Weighted gene correlation network analysis was performed to test whether the LLPS-related gene modules were associated with tumor grade of HCC. The candidate modules were subjected to functional enrichment analysis. We generated a LLPSRI using the expression profiles of the hub genes among the candidate modules in order to identify patients at high risk. Then, the biological characteristics of the high-risk patients were revealed using gene set enrichment analysis. Additionally, an independent external data set was used to validate the LLPSRI.

Results

Four gene modules showed a significant positive correlation with tumor grade and involved various cancer-related pathways. Among the hub genes, six were selected to generate the LLPSRI, which was significantly associated with prognosis of HCC patients. The LLPSRI could successfully divide patients with HCC into high- and low-risk groups, and patients in the high-risk group showed shorter overall survival than those in the low-risk group. E2F, MYC, and mTORC1 signaling may be important determinants of survival in the high-risk group. The prognostic value of the LLPSRI was validated with the independent external data set.

Conclusion

We identified LLPS-related gene modules that are associated with HCC tumor grade. The LLPSRI may be useful as a prognostic marker of HCC, and it may reliably stratify patients into groups at low or high risk of worse survival. Our analysis also suggests that certain biological characteristics of HCC may be associated with high risk of worse survival.

A Cell Cycle Progression-Derived Gene Signature to Predict Prognosis and Therapeutic Response in Hepatocellular Carcinoma

Objective

Dysregulation of cell cycle progression (CCP) is one of the hallmarks of cancer. Here, our study is aimed at developing a CCP-derived gene signature for predicting high-risk population of hepatocellular carcinoma (HCC).

Methods

Our study retrospectively analyzed the transcriptome profiling and clinical information of HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) projects. Uni- and multivariate cox regression models were conducted for identifying which hallmarks of cancer were risk factors of HCC. CCP-derived gene signature was developed with LASSO method. The predictive efficacy was verified by ROC curves and subgroup analyses. A nomogram was then generated and validated by ROC, calibration, and decisive curves. Immune cell infiltration was estimated with ssGSEA method. Potential small molecular compounds were predicted via CTRP and CMap analyses. The response to chemotherapeutic agents was evaluated based on the GDSC project.

Results

Among hallmarks of cancer, CCP was identified as a dominant risk factor for HCC prognosis. CCP-derived gene signature displayed the favorable predictive efficacy in HCC prognosis independent of other clinicopathological parameters. A nomogram was generated for optimizing risk stratification and quantifying risk evaluation. CCP-derived signature was in relation to immune cell infiltration, HLA, and immune checkpoint expression. Combining CTRP and CMap analyses, fluvastatin was identified as a promising therapeutic agent against HCC. Furthermore, CCP-derived signature might be applied for predicting the response to doxorubicin and gemcitabine.

Conclusion

Collectively, CCP-derived gene signature was a promising marker in prediction of survival outcomes and therapeutic responses for HCC patients.

Identification of a Novel Epigenetic Signature CHFR as a Potential Prognostic Gene Involved in Metastatic Clear Cell Renal Cell Carcinoma

Metastasis is the main cause of clear cell renal cell carcinoma (ccRCC) treatment failure, and the key genes involved in ccRCC metastasis remain largely unknown. We analyzed the ccRCC datasets in The Cancer Genome Atlas database, comparing primary and metastatic ccRCC tumor records in search of tumor metastasis-associated genes, and then carried out overall survival, Cox regression, and receiver operating characteristic (ROC) analyses to obtain potential prognostic markers. Comprehensive bioinformatics analysis was performed to verify that the checkpoint with forkhead associated and ring finger domains (CHFR) gene is a reliable candidate oncogene, which is overexpressed in ccRCC metastatic tumor tissue, and that high expression levels of CHFR indicate a poor prognosis. A detailed analysis of the methylation of CHFR in ccRCC tumors showed that three sites within 200 bp of the transcription initiation site were significantly associated with prognosis and that hypomethylation was associated with increased CHFR gene expression levels. Knockdown of CHFR in ccRCC cells inhibited cell proliferation, colony formation, and migration ability. In summary, our findings suggest that the epigenetic signature on CHFR gene is a novel prognostic feature; furthermore, our findings offer theoretical support for the study of metastasis-related genes in ccRCC and provided new insights for the clinical treatment of the disease.

Wnt/β-Catenin Signaling as a Driver of Hepatocellular Carcinoma Progression: An Emphasis on Molecular Pathways

Liver cancers cause a high rate of death worldwide and hepatocellular carcinoma (HCC) is considered as the most common primary liver cancer. HCC remains a challenging disease to treat. Wnt/β-catenin signaling pathway is considered a tumor-promoting factor in various cancers; hence, the present review focused on the role of Wnt signaling in HCC, and its association with progression and therapy response based on pre-clinical and clinical evidence. The nuclear translocation of β-catenin enhances expression level of genes such as c-Myc and MMPs in increasing cancer progression. The mutation of CTNNB1 gene encoding β-catenin and its overexpression can lead to HCC progression. β-catenin signaling enhances cancer stem cell features of HCC and promotes their growth rate. Furthermore, β-catenin prevents apoptosis in HCC cells and increases their migration via triggering EMT and upregulating MMP levels. It is suggested that β-catenin signaling participates in mediating drug resistance and immuno-resistance in HCC. Upstream mediators including ncRNAs can regulate β-catenin signaling in HCC. Anti-cancer agents inhibit β-catenin signaling and mediate its proteasomal degradation in HCC therapy. Furthermore, clinical studies have revealed the role of β-catenin and its gene mutation (CTNBB1) in HCC progression. Based on these subjects, future experiments can focus on developing novel therapeutics targeting Wnt/β-catenin signaling in HCC therapy.