Genome-wide CRISPR knockout screens identify NCAPG as an essential oncogene for hepatocellular carcinoma tumor growth

Important role and underlying mechanism of non‑SMC condensin I complex subunit G in tumours (Review)

At present, the incidence of tumours is increasing on a yearly basis, and tumourigenesis is usually associated with chromosomal instability and cell cycle dysregulation. Moreover, abnormalities in the chromosomal structure often lead to DNA damage, further exacerbating gene mutations and chromosomal rearrangements. However, the non‑SMC condensin I complex subunit G (NCAPG) of the structural maintenance of chromosomes family is known to exert a key role in tumour development. It has been shown that high expression of NCAPG is closely associated with tumour development and progression. Overexpression of NCAPG variously affects chromosome condensation and segregation during cell mitosis, influences cell cycle regulation, promotes tumour cell proliferation and invasion, and inhibits apoptosis. In addition, NCAPG has been associated with tumour cell stemness, tumour resistance and recurrence. The aim of the present review was to explore the underlying mechanisms of NCAPG during tumour development, with a view towards providing novel targets and strategies for tumour therapy, and through the elucidation of the mechanisms involved, to lay the foundation for future developments in health.

CRISPR-Cas9 in basic and translational aspects of cancer therapy

Introduction

The discovery of gene editing techniques has opened a new era within the field of biology and enabled scientists to manipulate nucleic acid molecules. CRISPR-Cas9 genome engineering has revolutionized this achievement by successful targeting the DNA molecule and editing its sequence. Since genomic changes are the basis of the birth and growth of many tumors, CRISPR-Cas9 method has been successfully applied to identify and manipulate the genes which are involved in initiating and driving some neoplastic processes.

Methods

By review of the existing literature on application of CRISPR-Cas9 in cancer, different databases, such as PubMed and Google Scholar, we started data collection for "CRISPR-Cas9", "Genome Editing", "Cancer", "Solid tumors", "Hematologic malignancy" "Immunotherapy", "Diagnosis", "Drug resistance" phrases. Clinicaltrials.gov, a resource that provides access to information on clinical trials, was also searched in this review.

Results

We have defined the basics of this technology and then mentioned some clinical and preclinical studies using this technology in the treatment of a variety of solid tumors as well as hematologic neoplasms. Finally, we described the progress made by this technology in boosting immune-mediated cell therapy in oncology, such as CAR-T cells, CAR-NK cells, and CAR-M cells.

Conclusion

CRISPR-Cas9 system revolutionized the therapeutic strategies in some solid malignant tumors and leukemia through targeting the key genes involved in the pathogenesis of these cancers.

A review of the literature on the use of CRISPR/Cas9 gene therapy to treat hepatocellular carcinoma

Noncoding RNAs instruct the Cas9 nuclease to site-specifically cleave DNA in the CRISPR/Cas9 system. Despite the high incidence of hepatocellular carcinoma (HCC), the patient's outcome is poor. As a result of the emergence of therapeutic resistance in HCC patients, clinicians have faced difficulties in treating such tumor. In addition, CRISPR/Cas9 screens were used to identify genes that improve the clinical response of HCC patients. It is the objective of this article to summarize the current understanding of the use of the CRISPR/Cas9 system for the treatment of cancer, with a particular emphasis on HCC as part of the current state of knowledge. Thus, in order to locate recent developments in oncology research, we examined both the Scopus database and the PubMed database. The ability to selectively interfere with gene expression in combinatorial CRISPR/Cas9 screening can lead to the discovery of new effective HCC treatment regimens by combining clinically approved drugs. Drug resistance can be overcome with the help of the CRISPR/Cas9 system. HCC signature genes and resistance to treatment have been uncovered by genome-scale CRISPR activation screening, although this method is not without limitations. It has been extensively examined whether CRISPR can be used as a tool for disease research and gene therapy. CRISPR and its applications to tumor research, particularly in HCC, are examined in this study through a review of the literature.

E2F1-mediated Up-regulation of NCAPG Promotes Hepatocellular Carcinoma Development by Inhibiting Pyroptosis

Background and Aims

As a subunit of the condensin complex, NCAPG has an important role in maintaining chromosome condensation, but its biological function and regulatory mechanism in hepatocellular carcinoma (HCC) remains undefined.

Methods

The prognostic ability of NCAPG in HCC patients was examined by univariate and multivariate Cox regression analysis. ROC curves were plotted to compare the predictive ability of NCAPG and AFP. Double luciferase reporter system, and ChIP were used to investigate transcriptional potential of E2F1 to NCAPG. Pyroptosis was observed by scanning electron microscopy. Protein expression of NCAPG, E2F1, and major proteins constituting NLRP3 inflammasome was determined by western blotting and ELISA. An in vivo tumor formation assay was conducted to verify the in vitro results.

Results

Up-regulated NCAPG was identified in HCC tissues compared with adjacent tissue and high NCAPG was positively correlated with poor prognosis. Serum NCAPG mRNA level was a prognostic factor in HCC patients and also a diagnostic factor with higher predictive ability compared with AFP [AUROC 0.766 (95% CI: 0.650-0.881) vs. 0.649 (95% CI 0.506-0.793)]. HBx transfection resulted in concomitant up-regulation of E2F1 and NCAPG. E2F1 significantly increased the activity of luciferase reporter fused with NCAPG reporter, and the interaction of E2F1 and NCAPG gene was confirmed by ChIP. Silencing of E2F1 resulted in significant down-regulation of NCAPG. Knockdown of NCAPG promote pyroptosis mediated by NLRP3 inflammasome activation in multiple HCC cell lines and also suppressed tumorigenesis in vitro.

Conclusions

We identified a novel role of NCAPG in the regulation of NLRP3 inflammasome-mediated pyroptosis, which was regulated by its upstream transactivator, E2F1. The role of E2F1-NCAPG-NLRP3 regulation of pyroptosis network may be a potential target in HCC treatment.

Identification of NCAPG as an Essential Gene for Neuroblastoma Employing CRISPR-Cas9 Screening Database and Experimental Verification

Neuroblastoma is the most common extracranial solid tumor in children. Patients with neuroblastoma have a poor prognosis. The development of therapy targets and the ability to predict prognosis will be enhanced through further exploration of the genetically related genes of neuroblastoma. The present investigation utilized CRISPR-Cas9 genome-wide screening based on the DepMap database to determine essential genes for neuroblastoma cells' continued survival. WGCNA analysis was used to determine the progression-related genes, and a prognostic signature was constructed. The signature gene, NCAPG, was downregulated in neuroblastoma cells to explore its impact on various cellular processes. This research used DepMap and WGCNA to pinpoint 45 progression-related essential genes for neuroblastoma. A risk signature comprising NCAPG and MAD2L1 was established. The suppression of NCAPG prevented neuroblastoma cells from proliferating, migrating, and invading. The results of flow cytometric analysis demonstrated that NCAPG inhibition caused cell cycle arrest during the G2 and S phases and the activation of apoptosis. Additionally, NCAPG downregulation activated the p53-mediated apoptotic pathway, inducing cell apoptosis. The present work showed that NCAPG knockdown reduced neuroblastoma cell progression and may serve as a basis for further investigation into diagnostic indicators and therapy targets for neuroblastoma.

Research progress and application of the CRISPR/Cas9 gene-editing technology based on hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is now a common cause of cancer death, with no obvious change in patient survival over the past few years. Although the traditional therapeutic modalities for HCC patients mainly involved in surgery, chemotherapy, and radiotherapy, which have achieved admirable achievements, challenges are still existed, such as drug resistance and toxicity. The emerging gene therapy of clustered regularly interspaced short palindromic repeat/CRISPR-associated nuclease 9-based (CRISPR/Cas9), as an alternative to traditional treatment methods, has attracted considerable attention for eradicating resistant malignant tumors and regulating multiple crucial events of target gene-editing. Recently, advances in CRISPR/Cas9-based anti-drugs are presented at the intersection of science, such as chemistry, materials science, tumor biology, and genetics. In this review, the principle as well as statues of CRISPR/Cas9 technique were introduced first to show its feasibility. Additionally, the emphasis was placed on the applications of CRISPR/Cas9 technology in therapeutic HCC. Further, a broad overview of non-viral delivery systems for the CRISPR/Cas9-based anti-drugs in HCC treatment was summarized to delineate their design, action mechanisms, and anticancer applications. Finally, the limitations and prospects of current studies were also discussed, and we hope to provide comprehensively theoretical basis for the designing of anti-drugs.

NCAPG as a novel prognostic biomarker in numerous cancers: a meta-analysis and bioinformatics analysis

BACKGROUND

Identification of effective biomarkers for cancer prognosis is a primary research challenge. Recently, several studies have reported the relationship between NCAPG and the occurrence of various tumors. However, none have combined meta-analytical and bioinformatics approaches to systematically assess the role of NCAPG in cancer.

METHODS

We searched four databases, namely, PubMed, Web of Science, Embase, and the Cochrane Library, for relevant articles published before April 30, 2022. The overall hazard ratio or odds ratio and 95% confidence intervals were calculated to assess the relationship between NCAPG expression and cancer survival prognosis or clinical characteristics. Furthermore, the aforementioned results were validated using the GEPIA2, Kaplan-Meier plotter, and PrognoScan databases.

RESULTS

The meta-analysis included eight studies with 1096 samples. The results showed that upregulation of NCAPG was correlated with poorer overall survival (hazard ratio = 2.90, 95% confidence interval = 2.06-4.10, P < 0.001) in the cancers included in the study. Subgroup analysis showed that in some cancers, upregulation of NCAPG was correlated with age, distant metastasis, lymph node metastasis, TNM stage, relapse, differentiation, clinical stage, and vascular invasion. These results were validated using the GEPIA2, UALCAN, and PrognoScan databases. We also explored the processes of NCAPG methylation and phosphorylation.

CONCLUSION

Dysregulated NCAPG expression is associated with the clinical prognostic and pathological features of various cancers. Therefore, NCAPG can serve as a human cancer therapeutic target and a new potential prognostic biomarker.

Over-expression of RRM2 predicts adverse prognosis correlated with immune infiltrates: A potential biomarker for hepatocellular carcinoma

Background

Ribonucleotide reductase regulatory subunit M2 (RRM2) has been reported to be an oncogene in some malignant tumors, such as lung adenocarcinoma, oral squamous cell carcinoma, glioblastoma, and breast cancer. However, the clinical significance of RRM2 in hepatocellular carcinoma has been less studied. The aim of this study was to assess the importance of RRM2 in hepatocellular carcinoma (HCC) based on the Cancer Genome Atlas (TCGA) database.

Methods

The RRM2 expression levels and clinical features were downloaded from the TCGA database. Immunohistochemistry results between tumor tissues and normal tissues were downloaded from the Proteinatlas database. Meanwhile, the expression levels of RRM2 in tumor and paraneoplastic tissues were further verified by qRT-PCR and Western Blotting. Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein-interactions (PPI) network were constructed to analyze RRM2-related downstream molecules. In addition, RRM2 expression-related pathways performed by gene set enrichment analysis (GSEA). Association analysis of RRM2 gene expression and immune infiltration was performed by single-sample GSEA (ssGSEA).

Results

The RRM2 expression level in tumor tissues was higher than normal tissues (P &lt;0.001). The elevated expression of RRM2 in HCC was significantly correlated with T stage (P &lt;0.05), pathologic stage (P &lt;0.05), tumor status (P &lt;0.05), histologic grade (P&lt;0.001), and AFP (P &lt;0.001). HCC with higher RRM2 expression was positively associated with worse OS (overall survival), PFS (progression-free survival), and DSS (disease-specific survival). In the univariate analysis, the expression of RRM2, T stage, M stage, pathologic stage, and tumor status were negatively correlated with OS (P &lt;0.05). Further analysis using multivariate Cox regression showed that tumor status (P&lt;0.01) and RRM2 expression (P&lt;0.05) were independent prognostic factors of OS in HCC. GO/KEGG analysis showed that the critical biological process (chromosome condensation and p53 signaling pathway) might be the possible function mechanism in promoting HCC. Moreover, GSEA showed that several pathways were enriched in RRM2 high-expression samples, including PD-1 signaling, cell cycle, P27 pathway, and T cell receptor signaling pathway. RRM2 was significantly correlated with the infiltration level of CD8 T cells, Cytotoxic cells, DCs, Neutrophils, NK cells, and T helper cells (P &lt;0.05).

Conclusion

Over-expression of RRM2 predict adverse prognosis and is correlated with immune infiltrates in HCC. RRM2 may be a significant molecular biomarker for HCC diagnosis and prognosis.

Identification of Prognostic Biomarkers for Suppressing Tumorigenesis and Metastasis of Hepatocellular Carcinoma through Transcriptome Analysis

Cancer is one of the deadliest diseases developed through tumorigenesis and could be fatal if it reaches the metastatic phase. The novelty of the present investigation is to explore the prognostic biomarkers in hepatocellular carcinoma (HCC) that could develop glioblastoma multiforme (GBM) due to metastasis. The analysis was conducted using RNA-seq datasets for both HCC (PRJNA494560 and PRJNA347513) and GBM (PRJNA494560 and PRJNA414787) from Gene Expression Omnibus (GEO). This study identified 13 hub genes found to be overexpressed in both GBM and HCC. A promoter methylation study showed these genes to be hypomethylated. Validation through genetic alteration and missense mutations resulted in chromosomal instability, leading to improper chromosome segregation, causing aneuploidy. A 13-gene predictive model was obtained and validated using a KM plot. These hub genes could be prognostic biomarkers and potential therapeutic targets, inhibition of which could suppress tumorigenesis and metastasis.

ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG May Serve as Diagnostic and Prognostic Biomarkers in Endometrial Carcinoma

Uterine Corpus Endometrial Carcinoma (UCEC), the most common gynecologic malignancy in developed countries, remains to be a major public health problem. Further studies are surely needed to elucidate the tumorigenesis of UCEC. Herein, intersecting 203 differentially expressed genes (DEGs) were identified with the GSE17025, GSE63678, and The Cancer Genome Atlas-UCEC datasets. The Gene Ontology/Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis and protein-protein interaction (PPI) network were performed on those 203 DEGs. Intriguingly, 6 of the top 10 nodes in the PPI network were related to unfavorable prognosis, that is, ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG. The mRNA and protein expression levels of the 6 hub genes were elevated in UCEC tissues compared to normal tissues. Higher expression of the 6 hub genes was associated with poor prognostic clinicopathological characteristics. The receiver operating characteristic curve suggested the significant diagnostic ability of the 6 hub genes for UCEC. Then, underlying pathogeneses of UCEC including promoter methylation level, TP53 mutation status, genomic genetic variation, and immune cells infiltration were analyzed. The mRNA expression level of the 6 hub genes was also higher in cervical squamous cell carcinoma and endocervical adenocarcinoma, uterine carcinosarcoma, and ovarian serous cystadenocarcinoma tissues than in corresponding normal tissues. In conclusion, ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG may be considered diagnostic and prognostic biomarkers in UCEC.

The role of NCAPG in various of tumors

Non-SMC Condensin I complex subunit G (NCAPG), a mitosis-associated chromosomal condensation protein, is related to sister chromatid appropriate separation during the condensation and fusion of chromosomes and responsible for the condensation and stabilization of chromosomes during meiosis and mitosis. Studies have shown that NCAPG is highly adjusted in a variety of cancers, and its related molecular mechanism affects tumor cell proliferation, invasion, metastasis, and apoptosis including hepatocellular carcinoma, prostate cancer, breast cancer, gastric cancer, gliomas, lung adenocarcinoma, colorectal cancer, ovarian cancer, and endometrial cancer. Clinically, the expression of NCAPG is strongly correlated with N-classification, M-classification, and clinical stage, and NCAPG is valuable for the prognosis of patients with lung adenocarcinoma. In addition, NCAPG can also reduce the sensitivity of tumor cells such as breast cancer to reduce the reaction of the original chemotherapy, so that tumor cells are drug-resistance. In summary, NCAPG can serve as a new diagnosis and treatment target for a variety of cancers, and is also a very promising prognostic marker. Therefore, this review summarizes the critical role of NCAPG in the diagnosis, treatment, and prognosis for various cancers, and the mechanism by which NCAPG plays its pivotal roles.

AC099850.3/NCAPG Axis Predicts Poor Prognosis and is Associated with Resistance to EGFR Tyrosine-Kinase Inhibitors in Lung Adenocarcinoma

Background

TKI-acquired resistance markedly interferes with treatment of lung cancer patients with EGFR mutant features. Long non-coding RNAs (lncRNAs) modify EGFR-TKI resistance during tumor progression. Non-structural maintenance of chromosomes condensin I complex subunit G (NCAPG) is a mitosis-related protein that is involved in tumorigenesis. We investigated the potential regulatory lncRNAs of NCAPG in lung adenocarcinoma (LUAD) and assessed their roles in EGFR-TKI resistance.

Methods

Data for 1678 lung cancer patients were retrieved from TCGA and GEO databases and used to evaluate NCAPG and lncRNAs expressions, as well as their prognostic significance in LUAD. Protein levels of NCAPG in LUAD were validated by immuno-histochemistry. To assess the relationship between NCAPG levels and EGFR-TKIs sensitivity, a cohort of 57 LUAD patients administered with EGFR-TKIs was used.

Results

Both NCAPG and lncRNA AC099850.3 were over-expressed in LUAD tissues, and correlated with tumor progression and poor prognosis in LUAD. LncRNA AC099850.3 was identified as a potential regulator of NCAPG expressions. The AC099850.3/NCAGP axis was markedly correlated with EGFR mutations and IC₅₀ of EGFR-TKIs. Besides, elevated NCAPG levels were associated with EGFR-TKIs resistance in 57 LUAD patients undergoing TKIs treatment. Gene set enrichment analysis revealed that both AC099850.3 and NCAGP were abundant in the cell cycle and the p53 signaling pathway.

Conclusion

The AC099850.3/NCAPG axis is a potential prognostic predictor and therapeutic biomarker for EGFR-TKIs in LUAD.

Identification of Potential Biomarkers for Pan-Cancer Diagnosis and Prognosis Through the Integration of Large-Scale Transcriptomic Data

Cancer is one of the leading causes of death worldwide, bringing a significant burden to human health and society. Accurate cancer diagnosis and biomarkers that can be used as robust therapeutic targets are of great importance as they facilitate early and effective therapies. Shared etiology among cancers suggests the existence of pan-cancer biomarkers, performance of which could benefit from the large sample size and the heterogeneity of the studied patients. In this study, we conducted a systematic RNA-seq study of 9,213 tumors and 723 para-cancerous tissue samples of 28 solid tumors from the Cancer Genome Atlas (TCGA) database, and 7,008 normal tissue samples from the Genotype-Tissue Expression (GTEx) database. By differential gene expression analysis, we identified 214 up-regulated and 186 downregulated differentially expressed genes (DEGs) in more than 80% of the studied tumors, respectively, and obtained 20 highly linked up- and downregulated hub genes from them. These markers have rarely been reported in multiple tumors simultaneously. We further constructed pan-cancer diagnostic models to classify tumors and para-cancerous tissues using 10 up-regulated hub genes with an AUC of 0.894. Survival analysis revealed that these hub genes were significantly associated with the overall survival of cancer patients. In addition, drug sensitivity predictions for these hub genes in a variety of tumors obtained several broad-spectrum anti-cancer drugs targeting pan-cancer. Furthermore, we predicted immunotherapy sensitivity for cancers based on tumor mutational burden (TMB) and the expression of immune checkpoint genes (ICGs), providing a theoretical basis for the treatment of tumors. In summary, we identified a set of biomarkers that were differentially expressed in multiple types of cancers, and these biomarkers can be potentially used for diagnosis and used as therapeutic targets.

NCAPG Promotes the Proliferation of Renal Clear Cell Carcinoma via Mediating with CDK1

Objective. Currently, lots of scholars have proved that the expression of NCAPG is associated with the prognosis of several cancers, while the relationship between NCAPG and renal clear cell carcinoma remains unclear, so the main aim of this research is to explore the effects of NCAPG on the progression of renal clear cell carcinoma. Methods. We observed the differential expression of NCAPG in several cancers from GEPIA online database, and the expression of NCAPG in renal clear cell carcinoma and normal tissue was compared and further verified by IHC assay. CCK-8 assay and clone formation experiment were conducted to observe the change of NCAPG on the proliferation. GraphPad was used for data analysis, and $t$ -test and ${\chi }^2$ analysis were used to analyze the correlation between NCAPG/CDK1 and renal clear cell carcinoma. Results. NCAPG was upregulated in renal clear cell carcinoma compared with the normal tissue, and the expression of NCAPG was associated with the clinical prognosis of pancreatic cancer especially with tumor size ( $P=0.010$ ). Knockdown NCAPG could restrain the proliferation of renal clear cell carcinoma. CDK1 was found to be tightly related with NCAPG, and the expression of CDK1 was also associated with the prognosis. Conclusions. NCAPG was upregulated in renal clear cell carcinoma, which was related with tumor size and overall survival. NCAPG might promote the proliferation of renal clear cell carcinoma via mediating CDK1. NCAPG/CDK1 complex might provide a new treatment strategy for lots of patients with renal clear cell carcinoma.

Prognostic comparative genes predict targets for sorafenib combination therapies in hepatocellular carcinoma

•

Large-scale comparative transcriptomics analysis of hepatocellular carcinoma reveals 664 prognostic comparative HCC (pcHCC) genes.

•

pcHCC genes included novel targets with potential utility in sorafenib combination therapies.

•

Knockdown of the selective pcHCC genes NCAPG and CENPW downregulated the p38/STAT3 axis to enhance sorafenib combination treatments.

With the increasing incidence and mortality of human hepatocellular carcinoma (HCC) worldwide, revealing innovative targets to improve therapeutic strategies is crucial for prolonging the lives of patients. To identify innovative targets, we conducted a comprehensive comparative transcriptome analysis of 5,410 human HCCs and 974 mouse liver cancers to identify concordantly expressed genes associated with patient survival. Among the 664 identified prognostic comparative HCC (pcHCC) genes, upregulated pcHCC genes were associated with prognostic clinical features, including large tumor size, vascular invasion and late HCC stages. Interestingly, after validating HCC patient prognoses in multiple independent datasets, we matched the 664 aberrant pcHCC genes with the sorafenib-altered genes in TCGA_LIHC patients and found these 664 pcHCC genes were enriched in sorafenib-related functions, such as downregulated xenobiotic and lipid metabolism and upregulated cell proliferation. Therapeutic agents targeting aberrant pcHCC genes presented divergent molecular mechanisms, including suppression of sorafenib-unrelated oncogenic pathways, induction of sorafenib-unrelated ferroptosis, and modulation of sorafenib transportation and metabolism, to potentiate sorafenib therapeutic effects in HCC combination therapy. Moreover, the pcHCC genes NCAPG and CENPW, which have not been targeted in combination with sorafenib treatment, were knocked down and combined with sorafenib treatment, which reduced HCC cell viability based on disruption to the p38/STAT3 axis, thereby hypersensitizing HCC cells. Together, our results provide important resources and reveal that 664 pcHCC genes represent innovative targets suitable for developing therapeutic strategies in combination with sorafenib based on the divergent synergistic mechanisms for HCC tumor suppression.

Identification of a metabolic reprogramming-related signature associated with prognosis and immune microenvironment of head and neck squamous cell carcinoma by in silico analysis

Background

Metabolic reprogramming is one of the essential features of tumorigenesis. Herein, this study aimed to develop a novel metabolism‐related gene signature for head and neck squamous cell carcinoma (HNSCC) patients.

Methods

The transcriptomic and clinical data of HNSCC samples were collected from The Cancer Genome Atlas (TCGA) and GSE65858 datasets. The metabolism‐related gene‐based prognostic signature (MRGPS) was constructed by the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The time‐dependent receiver operating characteristic (ROC) and Kaplan‐Meier (K‐M) survival curves were plotted for evaluating its predicting performance. At the same time, univariate along with multivariate analysis was carried out to explore its correlation with clinicopathologic factors. Furthermore, GSEA analysis was performed to explore the signaling pathways affected by MRGPS. We also analyzed the associations of MRGPS with the tumor immune microenvironment (TIME), as well as identified potential compounds via Connectivity Map (CMap) and molecular docking.

Results

A total of 12 differentially expressed metabolism‐related genes were identified and selected to construct the MRGPS. Notably, this signature performed well in predicting HNSCC patients’ survival and could serve as an independent prognostic factor in multiple datasets. In addition to the metabolism‐related pathway, this signature could also affect some immune‐related pathways. The results indicated that MRGPS is correlated with immune cells infiltration and anti‐cancer immune response. Furthermore, we identified cephaeline as a potential therapeutic compound for HNSCC.

Conclusion

Taken together, we established an MRGs‐based signature that has the potential to predict the clinical outcome and immune microenvironment, which help to search for potential combination immunotherapy compounds and provide a promising therapeutic strategy for treating HNSCC patients.

Acyl-CoA Binding Domain Containing 4 Polymorphism rs4986172 and Expression Can Serve as Overall Survival Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma Patients After Hepatectomy

Background

The aim of our study was to evaluate the potential of expression and single nucleotide polymorphism of Acyl-CoA binding domain containing 4 (ACBD4) gene as prognosis biomarkers in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after hepatectomy.

Methods

HBV-related HCC patients from the First Affiliated Hospital of Guangxi Medical University and GSE14520 were included in the current study, as well as The Cancer Genome Atlas (TCGA) HCC verification cohort. Prognostic analysis and multiple functional enrichment analysis methods were used to evaluate the prognostic value and potential biological functions of the ACBD4 gene in HBV-related HCC.

Results

We found that ACBD4 gene is highly expressed in normal liver tissues and markedly down-regulated in HBV-related HCC tissues. ACBD4 gene was significantly related to overall survival (OS) of HCC in TCGA and GSE14520 cohorts, and patients with low ACBD4 expression were markedly related to poor OS. Rs4986172 was observed as an OS biomarker after hepatectomy in the Guangxi HBV-related HCC cohort. The OS of rs4986172 GG genotype was worse than that of HCC patients with A allele (AA and AG genotypes). Multifunctional enrichment analysis suggested that ACBD4 gene is closely related to the metabolic, peroxisome proliferator-activated receptor and cytochrome P450 pathway. Through connectivity map, we also identified eight compounds that may be used as targeted therapeutic agents for ACBD4 gene in HBV-related HCC; these compounds were scopoletin, alfaxalone, bephenium hydroxynaphthoate, apramycin, 4,5-dianilinophthalimide, DL-thiorphan, aminohippuric acid and quinidine. Immune microenvironment analysis revealed that there were significant differences in immune scores of HBV-related HCC tumor tissues with different ACBD4 expression levels.

Conclusion

Our study reveals that ACBD4 expression and rs4986172 can be serve as biomarkers of OS in HBV-related HCC patients after hepatectomy.

Identification of UBE2I as a Novel Biomarker in ccRCC Based on a Large-Scale CRISPR-Cas9 Screening Database and Immunohistochemistry

Background: The genome-wide CRISPR-cas9 dropout screening has emerged as an outstanding approach for characterization of driver genes of tumor growth. The present study aims to investigate core genes related to clear cell renal cell carcinoma (ccRCC) cell viability by analyzing the CRISPR-cas9 screening database DepMap, which may provide a novel target in ccRCC therapy. Methods: Candidate genes related to ccRCC cell viability by CRISPR-cas9 screening from DepMap and genes differentially expressed between ccRCC tissues and normal tissues from TCGA were overlapped. Weighted gene coexpression network analysis, pathway enrichment analysis, and protein-protein interaction network analysis were applied for the overlapped genes. The least absolute shrinkage and selection operator (LASSO) regression was used to construct a signature to predict the overall survival (OS) of ccRCC patients and validated in the International Cancer Genome Consortium (ICGC) and E-MTAB-1980 database. Core protein expression was determined using immunohistochemistry in 40 cases of ccRCC patients. Results: A total of 485 essential genes in the DepMap database were identified and overlapped with differentially expressed genes in the TCGA database, which were enriched in the cell cycle pathway. A total of four genes, including UBE2I, NCAPG, NUP93, and TOP2A, were included in the gene signature based on LASSO regression. The high-risk score of ccRCC patients showed worse OS compared with these low-risk patients in the ICGC and E-MTAB-1980 validation cohort. UBE2I was screened out as a key gene. The immunohistochemistry indicated UBE2I protein was highly expressed in ccRCC tissues, and a high-level nuclear translocation of UBE2I occurs in ccRCC. Based on the area under the curve (AUC) values, nuclear UBE2I had the best diagnostic power (AUC = 1). Meanwhile, the knockdown of UBE2I can inhibit the proliferation of ccRCC cells. Conclusion: UBE2I, identified by CRISPR-cas9 screening, was a core gene-regulating ccRCC cell viability, which accumulated in the nucleus and acted as a potential novel promising diagnostic biomarker for ccRCC patients. Blocking the nuclear translocation of UBE2I may have potential therapeutic value with ccRCC patients.

Construction of a Prognosis-Related Gene Signature by Weighted Gene Coexpression Network Analysis in Ewing Sarcoma

Background

Ewing sarcoma (ES) is the second most common pediatric bone tumor with a high rate of metastasis, high recurrence, and low survival rate. Therefore, the identification of new biomarkers which can improve the prognosis of ES patients is urgently needed.

Methods

Here, GSE17679 dataset was downloaded from GEO databases. WGCNA method was used to identify one module associating with OVS (overall vital survival) and event. cytoHubba was used to screen out 50 hub genes from the module genes. Then, GSE17679 dataset was randomly divided into train cohort and test cohort. Next, univariate Cox analysis, LASSO regression analysis, and multivariate Cox analysis were conducted on 50 hub genes combined with train cohort data to select pivotal genes. Finally, an optimal 7-gene-based risk assessment model was established, which was verified by test cohort, entire GSE17679, and two independent datasets (GSE63157 and TCGA-SARC).

Results

The results of the functional enrichment analysis revealed that the OVS and event-associated module were mainly enriched in the protein transcription, cell proliferation, and cell-cycle control. And the train cohort was divided into high-risk and low-risk subgroups based on the median risk score; the results showed that the survival of the low-risk subgroup was significantly longer than high-risk. ROC analysis revealed that AUC values of 1, 3, and 5-year survival were 0.85, 0.94, and 0.88, and Kaplan-Meier analysis also revealed that P value < 0.0001, indicating that this model was accurate, which was also verified in the test, entire cohort, and two independent datasets (GSE63157 and TCGA-SARC). Then, we performed a comprehensive analysis (differential expression analysis, correlation analysis and survival analysis) of seven pivotal genes, and found that four genes (NCAPG, KIF4A, NUF2 and CDC20) plays a more crucial role in the prognosis of ES.

Conclusion

Taken together, this study established an optimal 7-gene-based risk assessment model and identified 4 potential therapeutic targets, to improve the prognosis of ES patients.

CCNB2, CDC20, AURKA, TOP2A, MELK, NCAPG, KIF20A, UBE2C, PRC1, and ASPM May Be Potential Therapeutic Targets for Hepatocellular Carcinoma Using Integrated Bioinformatic Analysis

Background

Hepatocellular carcinoma (HCC) is a highly malignant, recurrent and drug-resistant tumor, and patients often lose the opportunity for surgery when they are diagnosed. Abnormal gene expression is closely related to the occurrence of HCC. The aim of the present study was to identify the differentially expressed genes (DEGs) between tumor tissue and non-tumor tissue of HCC samples in order to investigate the mechanisms of liver cancer.

Methods

The gene expression profile (GSE62232, GSE89377, and GSE112790) was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the online tool GEO2R to identify differentially expressed genes (DEGs). Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery. Protein–protein interaction (PPI) of these DEGs was analyzed based on the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. In addition, we used the online Kaplan–Meier plotter survival analysis tool to evaluate the prognostic value of hub genes expression. HPA database was used to reveal the differences in protein level of hub genes.

Results

A total of 50 upregulated DEGs and 122 downregulated DEGs were identified. Among them, ten hub genes with a high degree of connectivity were picked out. Overexpression of these hub genes was associated with unfavorable prognosis of HCC.

Conclusion

Our study suggests that CCNB2, CDC20, AURKA, TOP2A, MELK, NCAPG, KIF20A, UBE2C, PRC1, and ASPM were overexpressed in HCC compared with normal liver tissue. Overexpression of these genes was an unfavorable prognostic factor of HCC patients. Further study is needed to explore the value of them in the diagnosis and treatment of HCC.

Point your SmartPhone at the code above. If you have a QR code reader the video abstract will appear. Or use:

https://youtu.be/6-kRy19SREg

Identification of the critical genes and miRNAs in hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is a global health problem with complex etiology and pathogenesis. Microarray data are increasingly being used as a novel and effective method for cancer pathogenesis analysis. An integrative analysis of genes and miRNA for HCC was conducted to unravel the potential prognosis of HCC. Two gene microarray datasets (GSE89377 and GSE101685) and two miRNA expression profiles (GSE112264 and GSE113740) were obtained from Gene Expression Omnibus database. A total of 177 differently expressed genes (DEGs) and 80 differently expressed miRNAs (DEMs) were screened out. Functional enrichment of DEGs was proceeded by Clue GO and these genes were significantly enriched in the chemical carcinogenesis pathway. A protein-protein interaction network was then established on the STRING platform, and ten hub genes (CDC20, TOP2A, ASPM, NCAPG, AURKA, CYP2E1, HMMR, PRC1, TYMS, and CYP4A11) were visualized via Cytoscape software. Then, a miRNA-target network was established to identify the hub dysregulated miRNA. A key miRNA (hsa-miR-124-3p) was filtered. Finally, the miRNA-target-transcription factor network was constructed for hsa-miR-124-3p. The network for hsa-miR-124-3p included two transcription factors (TFs) and five targets. These identified DEGs and DEMs, TFs, targets, and regulatory networks may help advance our understanding of the underlying pathogenesis of HCC.

Inhibition of NCAPG expression inactivates the Wnt/β-catenin signal to suppresses endometrial cancer cell growth in vitro

Endometrial cancer (EC) ranks as the most prevalent malignancy occurring in the female genital tract. Non-SMC condensin I complex subunit G (NCAPG), a mitotic associated chromosomal condensing protein, is reported to be frequently abnormally expressed in several tumors and plays a vital role in carcinogenesis. Our study aimed to explore the effect of NCAPG on cell proliferation and apoptosis in EC cells and to determine the underlying mechanism. Expression and survival data of NCAPG in EC tissues were analyzed by bioinformatics methods. Cell proliferation was evaluated by EdU and CCK-8 assays. Apoptosis was assessed by flow cytometry analysis. Expression of NCAPG, proliferating cell nuclear antigen (PCNA), Ki67, Bcl-2, Bax, active caspase-3, active β-catenin, and c-Myc were determined by western blotting. NCAPG was highly expressed in EC tissues and cells and predicted poor survival for EC patients. NCAPG knockdown inhibited cell proliferation and induced apoptosis in EC cells. Additionally, NCAPG knockdown inactivated the Wnt/β-catenin pathway in EC cells. Mechanistically, β-catenin overexpression blocked the tumorigenic effects of NCAPG in EC cells. In conclusion, NCAPG silencing inhibited cell proliferation and induced apoptosis in EC cells via inhibiting the Wnt/β-catenin pathway.

Novel oncogenes and tumor suppressor genes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a very deadly disease. HCC initiation and progression involve multiple genetic events, including the activation of proto-oncogenes and disruption of the function of specific tumor suppressor genes. Activation of oncogenes stimulates cell growth and survival, while loss-of-function mutations of tumor suppressor genes result in unrestrained cell growth. In this review, we summarize the new findings that identified novel proto-oncogenes and tumor suppressors in HCC over the past five years. These findings may inspire the development of novel therapeutic strategies to improve the outcome of HCC patients.

Nanotechnology-based delivery of CRISPR/Cas9 for cancer treatment

CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-associated protein 9) is a potent technology for gene-editing. Owing to its high specificity and efficiency, CRISPR/Cas9 is extensity used for human diseases treatment, especially for cancer, which involves multiple genetic alterations. Different concepts of cancer treatment by CRISPR/Cas9 are established. However, significant challenges remain for its clinical applications. The greatest challenge for CRISPR/Cas9 therapy is how to safely and efficiently deliver it to target sites in vivo. Nanotechnology has greatly contributed to cancer drug delivery. Here, we present the action mechanisms of CRISPR/Cas9, its application in cancer therapy and especially focus on the nanotechnology-based delivery of CRISPR/Cas9 for cancer gene editing and immunotherapy to pave the way for its clinical translation. We detail the difficult barriers for CRISIR/Cas9 delivery in vivo and discuss the relative solutions for encapsulation, target delivery, controlled release, cellular internalization, and endosomal escape.

NCAPG promotes the progression of lung adenocarcinoma via the TGF-β signaling pathway

Background

Lung cancer has the highest case fatality rate among cancers because of uncontrolled proliferation and early metastasis of cancer cells in the lung tissue. This study aimed to clarify the role of the non-SMC condensin I complex, subunit G (NCAPG) in lung adenocarcinoma (LUAD), explore the mechanisms of its progression, and lay the foundation for the search for new biological markers.

Methods

We analyzed overlapping differentially expressed genes (DEGs) from three datasets; a protein–protein interaction (PPI) network was subsequently constructed and analyzed using Cytoscape. We then selected NCAPG for validation because of its poor prognosis and because it has not been sufficiently studied in the context of LUAD. Immunohistochemical analysis was used to detect the expression of NCAPG in LUAD tissues, and the relationships between NCAPG and clinical parameters were analyzed. In vitro and in vivo experiments were conducted to verify the role of NCAPG in LUAD. Finally, we studied the specific mechanism of action of NCAPG in LUAD.

Results

Through comprehensive analysis of the GSE43458, GSE75037, and The Cancer Genome Atlas databases, we identified 517 overlapping DEGs. Among them, NCAPG was identified as a hub gene. Immunohistochemical analysis revealed that NCAPG was strongly associated with the clinical stage, M-classification, and N-classification. Univariate and multivariate Cox regression analyses indicated that NCAPG was a prognostic risk factor for LUAD, while the in vitro experiments showed that NCAPG overexpression promoted proliferation, migration, invasion, and epithelial-mesenchymal transition. Furthermore, knockdown of NCAPG inhibited LUAD progression, both in vitro and in vivo. Mechanistically, NCAPG overexpression increased p-Smad2 and p-Smad3 expressions in the transforming growth factor β (TGF-β) signaling pathway. Additionally, rescue experiments indicated that TGF-β signaling pathway inhibitors could restore the effect of NCAPG overexpression in LUAD cells.

Conclusions

NCAPG may promote proliferation and migration via the TGF-β signaling pathway in LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02138-w.

miR-181c-5p mediates apoptosis of vascular endothelial cells induced by hyperoxemia via ceRNA crosstalk

Oxygen therapy has been widely used in clinical practice, especially in anesthesia and emergency medicine. However, the risks of hyperoxemia caused by excessive O₂ supply have not been sufficiently appreciated. Because nasal inhalation is mostly used for oxygen therapy, the pulmonary capillaries are often the first to be damaged by hyperoxia, causing many serious consequences. Nevertheless, the molecular mechanism by which hyperoxia injures pulmonary capillary endothelial cells (LMECs) has not been fully elucidated. Therefore, we systematically investigated these issues using next-generation sequencing and functional research techniques by focusing on non-coding RNAs. Our results showed that hyperoxia significantly induced apoptosis and profoundly affected the transcriptome profiles of LMECs. Hyperoxia significantly up-regulated miR-181c-5p expression, while down-regulated the expressions of NCAPG and lncRNA-DLEU2 in LMECs. Moreover, LncRNA-DLEU2 could bind complementarily to miR-181c-5p and acted as a miRNA sponge to block the inhibitory effect of miR-181c-5p on its target gene NCAPG. The down-regulation of lncRNA-DLEU2 induced by hyperoxia abrogated its inhibition of miR-181c-5p function, which together with the hyperoxia-induced upregulation of miR-181c-5p, all these significantly decreased the expression of NCAPG, resulting in apoptosis of LMECs. Our results demonstrated a ceRNA network consisting of lncRNA-DLEU2, miR-181c-5p and NCAPG, which played an important role in hyperoxia-induced apoptosis of vascular endothelial injury. Our findings will contribute to the full understanding of the harmful effects of hyperoxia and to find ways for effectively mitigating its deleterious effects.

Identification of HCC-Related Genes Based on Differential Partial Correlation Network

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death, but its pathogenesis is still unclear. As the disease is involved in multiple biological processes, systematic identification of disease genes and module biomarkers can provide a better understanding of disease mechanisms. In this study, we provided a network-based approach to integrate multi-omics data and discover disease-related genes. We applied our method to HCC data from The Cancer Genome Atlas (TCGA) database and obtained a functional module with 15 disease-related genes as network biomarkers. The results of classification and hierarchical clustering demonstrate that the identified functional module can effectively distinguish between the disease and the control group in both supervised and unsupervised methods. In brief, this computational method to identify potential functional disease modules could be useful to disease diagnosis and further mechanism study of complex diseases.

Identification of hub genes associated with prognosis, diagnosis, immune infiltration and therapeutic drug in liver cancer by integrated analysis

BACKGROUND

Liver cancer is one of the most common cancers and causes of cancer death worldwide. The objective was to elucidate novel hub genes which were benefit for diagnosis, prognosis, and targeted therapy in liver cancer via integrated analysis.

METHODS

GSE84402, GSE101685, and GSE112791 were filtered from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified by using the GEO2R. The GO and KEGG pathway of DEGs were analyzed in the DAVID. PPI and TF network of the DEGs were constructed by using the STRING, TRANSFAC, and Harmonizome. The relationship between hub genes and prognoses in liver cancer was analyzed in UALCAN based on The Cancer Genome Atlas (TCGA). The diagnostic value of hub genes was evaluated by ROC. The relationship between hub genes and tumor-infiltrate lymphocytes was analyzed in TIMER. The protein levels of hub genes were verified in HPA. The interaction between the hub genes and the drug were identified in DGIdb.

RESULTS

In total, 108 upregulated and 60 downregulated DEGs were enriched in 148 GO terms and 20 KEGG pathways. The mRNA levels and protein levels of CDK1, HMMR, PTTG1, and TTK were higher in liver cancer tissues compared to normal tissues, which showed excellent diagnostic and prognostic value. CDK1, HMMR, PTTG1, and TTK were positively correlated with tumor-infiltrate lymphocytes, which might involve tumor immune response. The CDK1, HMMR, and TTK had close interaction with anticancer agents.

CONCLUSIONS

The CDK1, HMMR, PTTG1, and TTK were hub genes in liver cancer; hence, they might be potential biomarkers for diagnosis, prognosis, and targeted therapy of liver cancer.

Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC.

Methods

The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort.

Results

We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

Four Novel Prognostic Genes Related to Prostate Cancer Identified Using Co-expression Structure Network Analysis

Prostate cancer (PCa) is one of the most common malignancies for males, but very little is known about its pathogenesis. This study aimed to identify novel biomarkers associated with PCa prognosis and elucidate the underlying molecular mechanism. First, The Cancer Genome Atlas (TCGA) RNA-sequencing data were utilized to identify differentially expressed genes (DEGs) between tumor and normal samples. The DEGs were then applied to construct a co-expression and mined using structure network analysis. The magenta module that was highly related to the Gleason score (r = 0.46, p = 3e-26) and tumor stage (r = 0.38, p = 2e-17) was screened. Subsequently, all genes of the magenta module underwent function annotation. From the key module, CCNA2, CKAP2L, NCAPG, and NUSAP1 were chosen as the four candidate genes. Finally, internal (TCGA) and external data sets (GSE32571, GSE70770, and GSE141551) were combined to validate and predict the value of real hub genes. The results show that the above genes are up-regulated in PCa samples, and higher expression levels show significant association with higher Gleason scores and tumor T stage. Moreover, receiver operating characteristic curve and survival analysis validate the excellent value of hub genes in PCa progression and prognosis. In addition, the protein levels of these four genes also remain higher in tumor tissues when compared with normal tissues. Gene set enrichment analysis and gene set variation analysis for a single gene reveal the close relation with cell proliferation. Meanwhile, 11 small molecular drugs that have the potential to treat PCa were also screened. In conclusion, our research identified four potential prognostic genes and several candidate molecular drugs for treating PCa.

Identification of Core Genes Related to Progression and Prognosis of Hepatocellular Carcinoma and Small-Molecule Drug Predication

Background

Hepatocellular carcinoma (HCC) is one of the most leading causes of cancer death with a poor prognosis. However, the underlying molecular mechanisms are largely unclear, and effective treatment for it is limited. Using an integrated bioinformatics method, the present study aimed to identify the key candidate prognostic genes that are involved in HCC development and identify small-molecule drugs with treatment potential.

Methods and Results

In this study, by using three expression profile datasets from Gene Expression Omnibus database, 1,704 differentially expressed genes were identified, including 671 upregulated and 1,033 downregulated genes. Then, weighted co-expression network analysis revealed nine modules are related with pathological stage; turquoise module was the most associated module. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses (KEGG) indicated that these genes were enriched in cell division, cell cycle, and metabolic related pathways. Furthermore, by analyzing the turquoise module, 22 genes were identified as hub genes. Based on HCC data from gene expression profiling interactive analysis (GEPIA) database, nine genes associated with progression and prognosis of HCC were screened, including ANLN, BIRC5, BUB1B, CDC20, CDCA5, CDK1, NCAPG, NEK2, and TOP2A. According to the Human Protein Atlas and the Oncomine database, these genes were highly upregulated in HCC tumor samples. Moreover, multivariate Cox regression analysis showed that the risk score based on the gene expression signature of these nine genes was an independent prognostic factor for overall survival and disease-free survival in HCC patients. In addition, the candidate small-molecule drugs for HCC were identified by the CMap database.

Conclusion

In conclusion, the nine key gene signatures related to HCC progression and prognosis were identified and validated. The cell cycle pathway was the core pathway enriched with these key genes. Moreover, several candidate molecule drugs were identified, providing insights into novel therapeutic approaches for HCC.

NCAPG upregulation mediated by four microRNAs combined with activation of the p53 signaling pathway is a predictor of poor prognosis in patients with breast cancer

The role of non-SMC condensin I complex subunit G (NCAPG) in breast cancer remains unclear. The present study used online databases, reverse transcription-quantitative PCR, flow cytometry and western blotting to determine the expression levels, prognosis and potential molecular mechanisms underlying the role of NCAPG in breast cancer. The association between NCAPG expression and several different clinicopathological parameters in patients with breast cancer was determined, and the results revealed that NCAPG expression was negatively associated with estrogen receptor and progesterone receptor positive status, but was positively associated with HER2 positive status, Nottingham Prognostic Index score and Scarff-Bloom-Richardson grade status. Furthermore, upregulated expression levels of NCAPG resulted in a poor prognosis in patients with breast cancer. A total of 27 microRNAs (miRNAs/miRs) were predicted to target NCAPG, among which four miRNAs (miR-101-3p, miR-195-5p, miR-214-3p and miR-944) were predicted to most likely regulate NCAPG expression in breast cancer. A total of 261 co-expressed genes of NCAPG were identified, including cell division cyclin 25 homolog C (CDC25C), and pathway enrichment analysis indicated that these co-expressed genes were significantly enriched in the p53 signaling pathway. CDC25C expression was downregulated in breast cancer and was associated with a poor prognosis. These findings suggested that upregulated NCAPG expression may be a prognostic biomarker of breast cancer.

Identification and validation of a prognostic signature and combination drug therapy for immunotherapy of head and neck squamous cell carcinoma

Immunotherapy has become a promising therapeutic option for Head and neck squamous cell carcinoma (HNSC). However, only a small percentage of patients could benefit from it, and the overall prognosis was far from satisfactory. In this study, by comprehensively computational analyses of hundreds of HNSC samples, a prognostic signature composed of 13 immune-related genes (IRGs) was constructed. The results of the analyses in multiple datasets indicated that our signature had high predictive accuracy and could serve as an independent prognostic predictor. Based on this signature and multiple clinical variables, we also established a prognostic nomogram to quantitatively predict the survival risk of individual patients. Moreover, this signature could accurately predict survival, reflect the immune microenvironment, and predict immunotherapy efficacy among HNSC patients. Two potential drugs (doxorubicin and daunorubicin) were also identified via Connectivity Map and molecular docking, which could be used for HNSC combination therapy. Taken together, we developed and validated a robust IRG-based prognostic signature to monitor the prognosis of HNSC, which could provide a solid foundation for individualized cancer immunotherapy.

DEG 15, an update of the Database of Essential Genes that includes built-in analysis tools

Essential genes refer to genes that are required by an organism to survive under specific conditions. Studies of the minimal-gene-set for bacteria have elucidated fundamental cellular processes that sustain life. The past five years have seen a significant progress in identifying human essential genes, primarily due to the successful use of CRISPR/Cas9 in various types of human cells. DEG 15, a new release of the Database of Essential Genes (www.essentialgene.org), has provided major advancements, compared to DEG 10. Specifically, the number of eukaryotic essential genes has increased by more than fourfold, and that of prokaryotic ones has more than doubled. Of note, the human essential-gene number has increased by more than tenfold. Moreover, we have developed built-in analysis modules by which users can perform various analyses, such as essential-gene distributions between bacterial leading and lagging strands, sub-cellular localization distribution, enrichment analysis of gene ontology and KEGG pathways, and generation of Venn diagrams to compare and contrast gene sets between experiments. Additionally, the database offers customizable BLAST tools for performing species- and experiment-specific BLAST searches. Therefore, DEG comprehensively harbors updated human-curated essential-gene records among prokaryotes and eukaryotes with built-in tools to enhance essential-gene analysis.

Identification of Hub Genes Associated With Immune Infiltration and Predict Prognosis in Hepatocellular Carcinoma via Bioinformatics Approaches

Aims

In the cancer-related research field, there is currently a major need for a greater number of valuable biomarkers to predict the prognosis of hepatocellular carcinoma (HCC). In this study, we aimed to screen hub genes related to immune cell infiltration and explore their prognostic value for HCC.

Methods

We analyzed five datasets (GSE46408, GSE57957, GSE74656, GSE76427, and GSE87630) from the Gene Expression Omnibus database to screen the differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes; then, the hub genes were identified. Functional enrichment of the genes was performed on the Metascape website. Next, the expression of these hub genes was validated in several databases, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Human Protein Atlas. We explored the correlations between the hub genes and infiltrated immune cells in the TIMER2.0 database. The survival curves were generated in GEPIA2, and the univariate and multivariate Cox regression analyses were performed using TIMER2.0.

Results

The top ten hub genes [DNA topoisomerase II alpha (TOP2A), cyclin B2 (CCNB2), protein regulator of cytokinesis 1 (PRC1), Rac GTPase-activating protein 1 (RACGAP1), aurora kinase A (AURKA), cyclin-dependent kinase inhibitor 3 (CDKN3), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle-associated 5 (CDCA5), abnormal spindle microtubule assembly (ASPM), and non-SMC condensin I complex subunit G (NCAPG)] were identified in subsequent analysis. These genes are most markedly enriched in cell division, suggesting their close association with tumorigenesis. Multi-database analyses validated that the hub genes were upregulated in HCC tissues. All hub genes positively correlated with several types of immune infiltration, including B cells, CD4⁺ T cells, macrophages, and dendritic cells. Furthermore, these hub genes served as independent prognostic factors, and the expression of these hub genes combing with the macrophage levels could help predict an unfavorable prognosis of HCC.

Conclusion

In sum, these hub genes (TOP2A, CCNB2, PRC1, RACGAP1, AURKA, CDKN3, NUSAP1, CDCA5, ASPM, and NCAPG) may be pivotal markers for prognostic prediction as well as potentially work as targets for immune-based intervention strategies in HCC.

HDAC5 Loss Impairs RB Repression of Pro-Oncogenic Genes and Confers CDK4/6 Inhibitor Resistance in Cancer

The tumor-suppressor protein RB acts as a transcription repressor via interaction of its pocket domain with an LXCXE motif in histone deacetylase (HDAC) proteins such as HDAC1. Here, we demonstrate that HDAC5 deficient for the LXCXE motif interacts with both RB-N (via an FXXXV motif) and RB-C segments, and such interactions are diminished by phosphorylation of RB serine-249/threonine-252 and threonine-821. HDAC5 was frequently downregulated or deleted in human cancers such as prostate cancer. Loss of HDAC5 increased histone H3 lysine 27 acetylation (H3K27-ac) and circumvented RB-mediated repression of cell-cycle-related pro-oncogenic genes. HDAC5 loss also conferred resistance to CDK4/6 inhibitors such as palbociclib in prostate and breast cancer cells in vitro and prostate tumors in vivo, but this effect was overcome by the BET-CBP/p300 dual inhibitor NEO2734. Our findings reveal an unknown role of HDAC5 in RB-mediated histone deacetylation and gene repression and define a new mechanism modulating CDK4/6 inhibitor therapeutic sensitivity in cancer cells. SIGNIFICANCE: This study defines a previously uncharacterized role of HDAC5 in tumor suppression and provides a viable strategy to overcome CDK4/6 inhibitor resistance in HDAC5-deficent cancer.

Correlation of NUF2 Over-expression with Poorer Patient Survival in Multiple Cancers

Purpose

NUF2 has been implicated in multiple cancers recently, suggesting NUF2 may play a role in the common tumorigenesis process. In this study, we aim to perform comprehensive meta-analysis of NUF2 expression in the cancer types included in the Cancer Genome Atlas (TCGA).

Materials and Methods

RNA-sequencing data in 31 cancer types in the TCGA data and 11 independent datasets were used to examine NUF2 expression. Silencing NUF2 using targeting shRNAs in hepatocellular carcinoma (HCC) cell lines was used to evaluate NUF2’s role in HCC in vitro and in vivo.

Results

NUF2 up-regulation is significantly observed in 23 out of the 31 cancer types in the TCGA datasets and validated in 13 major cancer types using 11 independent datasets. NUF2 overexpression was clinically important as high NUF2 was significantly associated with tumor stages in eight different cancers. High NUF2 was also associated with significantly poorer patient overall survival and disease-free survival in eight and six cancers, respectively. We proceeded to validate NUF2 overexpression and its negative association with overall survival at the protein level in an independent cohort of 40 HCC patients. Compared to the non-targeting controls, NUF2 knockdown cells showed significantly reduced ability to grow, migrate into a scratch wound and invade the 8 μm porous membrane in vitro. Moreover, NUF2 knockdown cells also formed significantly smaller tumors than control cells in mouse xenograft assays in vivo.

Conclusion

NUF2 up-regulation is a common feature of many cancers. The prognostic potential and functional impact of NUF2 up-regulation warrant further studies.

APCCDC20-mediated degradation of PHD3 stabilizes HIF-1a and promotes tumorigenesis in hepatocellular carcinoma

CDC20 regulates cell cycle progression by targeting key substrates for destruction, but its role in hepatocellular carcinoma (HCC) tumorigenesis remains to be explored. Here, by using weighted gene co-expression network analysis (WGCNA), we identified CDC20 as a hub gene in HCC. We demonstrated that CDC20 expression is correlated with HIF-1 activity and overall survival (OS) of clinic HCC patients. The activity of HIF-1 is regulated by the stability of HIF-1a subunit, which is hydroxylated by oxygen-dependent prolyl hydroxylase enzymes, the PHDs. In addition, we show that genetic ablation or pharmacological inhibition of CDC20 can accelerate the degradation of HIF-1a and impair VEGF secretion in HCC cells. Mechanistically, we found that CDC20 binds to the destruction-box (D-box) motif present in the PHD3 protein to promote its polyubiquitination and degradation. The depletion of endogenous PHD3 in CDC20 knockdown HCC cells greatly attenuated the decline of HIF-1a protein and restored the secretion of VEGF. In contrast, overexpression of a non-degradable PHD3 mutant significantly inhibited the proliferation of HCC cells both in vitro and in vivo. Collectively, our findings indicate that CDC20 plays a crucial role in the development of HCC by governing PHD3 protein.

CRISPR/Cas9: A powerful genome editing technique for the treatment of cancer cells with present challenges and future directions

Cancer is one of the most leading causes of death and a major public health problem, universally. According to accumulated data, annually, approximately 8.5 million people died because of the lethality of cancer. Recently, a novel RNA domain-containing endonuclease-based genome engineering technology, namely the clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein-9 (Cas9) have been proved as a powerful technique in the treatment of cancer cells due to its multifunctional properties including high specificity, accuracy, time reducing and cost-effective strategies with minimum off-target effects. The present review investigates the overview of recent studies on the newly developed genome-editing strategy, CRISPR/Cas9, as an excellent pre-clinical therapeutic option in the reduction and identification of new tumor target genes in the solid tumors. Based on accumulated data, we revealed that CRISPR/Cas9 significantly inhibited the robust tumor cell growth (breast, lung, liver, colorectal, and prostate) by targeting the oncogenes, tumor-suppressive genes, genes associated to therapies by inhibitors, genes associated to chemotherapies drug resistance, and suggested that CRISPR/Cas9 could be a potential therapeutic target in inhibiting the tumor cell growth by suppressing the cell-proliferation, metastasis, invasion and inducing the apoptosis during the treatment of malignancies in the near future. The present review also discussed the current challenges and barriers, and proposed future recommendations for a better understanding.

NCAPG Induces Cell Proliferation in Cardia Adenocarcinoma via PI3K/AKT Signaling Pathway

Purpose

Previous studies have shown that non-SMC condensin I complex subunit G (NCAPG) overexpression is correlated to poor prognosis of multiple cancer types. Herein, we explored the underlying mechanism of NCAPG-mediated cardia adenocarcinoma (CA) proliferation and cell cycle regulation.

Methods

The protein profiling technology was used to analyze the gene expression in 20 CA and adjacent tissue samples. Differential genes were identified by bioinformatic analysis. Western blot and qRT-PCR-based analysis assessed the NCAPG expression levels in multiple CA cell lines. CA cell lines, SGC-7901 and AGS, were transfected with Lip 2000, and stably transfected cell lines were screened for NCAPG overexpression and downregulation. MTT and clone formation assays were employed to detect cell proliferation, and cell cycle phases were analyzed using flow cytometry. Western blot was performed to determine the NCAPG gene expression levels. Finally, we studied the tumorigenic effects of NCAPG in the mouse model and validated the cell experiment results using immunohistochemistry.

Results

A significant overexpression of NCAPG was found in CA tissues and CA cell lines. The outcomes of MTT and clone formation assays showed that NCAPG upregulation promoted cell proliferation. The outcomes of these analyses were further validated using nude mice as an in vivo tumor model. As per the outcome of Western blot and flow cytometry analysis, NCAPG regulated the G1 phase through the cyclins (CDK4, CDK6, and cyclin D1) overexpression and cell cycle inhibitors (P21 and P27) downregulation. Overexpressed NCAPG and silenced NCAPG, both in vitro and in vivo, resulted in abnormal activation of the PI3K/AKT signaling pathway in CA cells. We observed that NCAPG overexpression increased the levels of phosphorylated PI3K, AKT, and GSK3β; however, their total protein levels remained unchanged in CA cells.

Conclusion

As a CA oncogene, NCAPG promoted cell proliferation and regulated cell cycle through PI3K/AKT signaling pathway activation.

An immune-related gene signature for predicting survival and immunotherapy efficacy in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) ranks the fourth in terms of cancer-related mortality globally. Herein, in this research, we attempted to develop a novel immune-related gene signature that could predict survival and efficacy of immunotherapy for HCC patients.

METHODS

The transcriptomic and clinical data of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) and GSE14520 datasets, followed by acquiring immune-related genes from the ImmPort database. Afterwards, an immune-related gene-based prognostic index (IRGPI) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. Kaplan-Meier survival curves as well as time-dependent receiver operating characteristic (ROC) curve were performed to evaluate its predictive capability. Besides, both univariate and multivariate analyses on overall survival for the IRGPI and multiple clinicopathologic factors were carried out, followed by the construction of a nomogram. Finally, we explored the possible correlation of IRGPI with immune cell infiltration or immunotherapy efficacy.

RESULTS

Analysis of 365 HCC samples identified 11 differentially expressed immune-related genes, which were selected to establish the IRGPI. Notably, it can predict the survival of HCC patients more accurately than published biomarkers. Furthermore, IRGPI can predict the infiltration of immune cells in the tumor microenvironment of HCC, as well as the response of immunotherapy.

CONCLUSION

Collectively, the currently established IRGPI can accurately predict survival, reflect the immune microenvironment, and predict the efficacy of immunotherapy among HCC patients.

Overexpression of NCAPG inhibits cardia adenocarcinoma apoptosis and promotes epithelial-mesenchymal transition through the Wnt/β-catenin signaling pathway

BACKGROUND

Cardia adenocarcinoma (CA) is a distinct form of gastric cancer, and the optimal means of treating it remains controversial. At present, the role of the condensation complex gene non-SMC condensin I complex subunit G (NCAPG) in CA is uncertain, and as such the present study was designed to elucidate its importance in this oncogenic context.

METHODS

We first used bioinformatics approaches to assess NCAPG expression profiles in CA using public databases. Protein profiling was also used to examine the expression of this protein in CA tumors and adjacent tissues from 20 patients. Then the expression of NCAPG in CA samples was quantified via qRT-PCR and Western blotting. NCAPG knockdown and overexpression in the SGC-7901 and AGS cell lines were subsequently performed, after which the expression of key proteins associated with epithelial-mesenchymal transition (EMT; E-cadherin, vimentin, N-cadherin, Snail, Slug) and the regulation of apoptotic responses (caspase-3, Bax, Bcl-2) was measured. The mechanistic role of NCAPG in CA was additionally studied by analyzing proteins associated with Wnt/β-catenin signaling including Wnt1, phosphorylated GSK3β, β-catenin, and phosphorylated β- catenin. The impact of NCAPG on the migration, survival, and invasion of CA cells was further examined.

RESULTS

CA samples exhibited high NCAPG expression. When this gene was overexpressed in cell lines, it reduced caspase-3, Bax, and E-cadherin levels whereas it elevated Bcl-2, vimentin, N-cadherin, Snail, and Slug levels. NCAPG overexpression also resulted in the enhanced expression of Wnt1, phosphorylated GSK3β, and total β-catenin and the reduced expression of phosphorylated β-catenin. The knockdown of NCAPG, in contrast, yielded the opposite phenotype. At a functional level, the overexpression of NCAPG improved the apoptotic resistance of CA cells while driving them to undergo EMT and to become more invasive and migratory.

CONCLUSIONS

NCAPG overexpression can promote EMT and suppress tumor cell apoptosis via the activation of Wnt/β-catenin signaling.

Identification and Verification of Biomarker in Clear Cell Renal Cell Carcinoma via Bioinformatics and Neural Network Model

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer, which represents the 9th most frequently diagnosed cancer. However, the molecular mechanism of occurrence and development of ccRCC is indistinct. Therefore, the research aims to identify the hub biomarkers of ccRCC using numerous bioinformatics tools and functional experiments.

METHODS

The public data was downloaded from the Gene Expression Omnibus (GEO) database, and the differently expressed genes (DEGs) between ccRCC and normal renal tissues were identified with GEO2R. Protein-protein interaction (PPI) network of the DEGs was constructed, and hub genes were screened with cytoHubba. Then, ten ccRCC tumor samples and ten normal kidney tissues were obtained to verify the expression of hub genes with the RT-qPCR. Finally, the neural network model was constructed to verify the relationship among the genes.

RESULTS

A total of 251 DEGs and ten hub genes were identified. AURKB, CCNA2, TPX2, and NCAPG were highly expressed in ccRCC compared with renal tissue. With the increasing expression of AURKB, CCNA2, TPX2, and NCAPG, the pathological stage of ccRCC increased gradually (P < 0.05). Patients with high expression of AURKB, CCNA2, TPX2, and NCAPG have a poor overall survival. After the verification of RT-qPCR, the expression of hub genes was same as the public data. And there were strong correlations between the AURKB, CCNA2, TPX2, and NCAPG with the verification of the neural network model.

CONCLUSION

After the identification and verification, AURKB, CCNA2, TPX2, and NCAPG might be related to the occurrence and malignant progression of ccRCC.

NCAPG Is a Promising Therapeutic Target Across Different Tumor Types

Background

With the advent of CRISPR-Cas9 genome editing tool in gene therapy, identification of aberrantly expressed genes is of great value across various cancer types. Since a large number of patients may benefit from molecular targeted gene therapy. The purpose of this study was to identify aberrantly expressed genes across various cancer types, analyze prospective mechanisms and their correlation with survival outcomes.

Results

NCAPG was highly expressed in The Cancer Genome Atlas (TCGA) database, which includes the transcriptomes of 6,647 cancer and 647 normal tissue samples from 16 cancer types. Furthermore, a predicted NCAPG overexpression rate was also observed at the protein level in 16 tumor types. Importantly, high NCAPG level was significantly associated with unfavorable survival in various cancer types such as hepatocellular carcinoma (HCC), breast, lung or ovarian cancer. The multivariate analyses demonstrated that NCAPG, TNM, and Barcelona Clinic Liver Cancer (BCLC) staging were independent risk factors for mortality of patients with HCC. Moreover, functional and pathway enrichment analysis suggested that NCAPG was closely correlated with the pathways of cell cycle, cellular senescence, and mismatch repair. By weighted gene co-expression network analysis (WGCNA), we identified NCAPG as a hub gene in the turquoise module mostly related to the survival time of HCC samples.

Conclusion

To our knowledge, this study represents a comprehensive RNA-Seq analysis of several tumor types, revealing NCAPG as a promising molecular target. NCAPG overexpression may play important roles in carcinogenesis and progression of tumors via regulating tumor-related pathways, thereby broadening the understanding of the pathogenic mechanisms and highlighting the possibility of developing novel targeted therapeutics.

An outcome model for human bladder cancer: A comprehensive study based on weighted gene co-expression network analysis

The precision evaluation of prognosis is crucial for clinical treatment decision of bladder cancer (BCa). Therefore, establishing an effective prognostic model for BCa has significant clinical implications. We performed WGCNA and DEG screening to initially identify the candidate genes. The candidate genes were applied to construct a LASSO Cox regression analysis model. The effectiveness and accuracy of the prognostic model were tested by internal/external validation and pan‐cancer validation and time‐dependent ROC. Additionally, a nomogram based on the parameter selected from univariate and multivariate cox regression analysis was constructed. Eight genes were eventually screened out as progression‐related differentially expressed candidates in BCa. LASSO Cox regression analysis identified 3 genes to build up the outcome model in E‐MTAB‐4321 and the outcome model had good performance in predicting patient progress free survival of BCa patients in discovery and test set. Subsequently, another three datasets also have a good predictive value for BCa patients' OS and DFS. Time‐dependent ROC indicated an ideal predictive accuracy of the outcome model. Meanwhile, the nomogram showed a good performance and clinical utility. In addition, the prognostic model also exhibits good performance in pan‐cancer patients. Our outcome model was the first prognosis model for human bladder cancer progression prediction via integrative bioinformatics analysis, which may aid in clinical decision‐making.

Data mining of the expression and regulatory role of BCAT1 in hepatocellular carcinoma

Branched chain amino acid transaminase 1 (BCAT1) catalyzes the production of glutamates and branched-chain α-ketoacids from branched chain amino acids, and a normal BCAT1 expression is associated with tumorigenesis. Sequencing data from public databases, including The Cancer Genome Atlas, was used to analyze BCAT1 expression and regulation networks for hepatocellular carcinoma (HCC). Expression and methylation were assessed using UALCAN analysis, and data from multiple datasets concerning the BCAT1 expression level and associated survival rates were further analyzed using HCCDB; interaction networks of biological function were constructed using GeneMANIA. LinkedOmics was used to indicate correlations between BCAT1 and any identified differentially expressed genes. Gene enrichment analysis of BCAT-associated genes was conducted using the Web-based Gene SeT AnaLysis Toolkit. The expression levels of BCAT1 were increased in patients with HCC and in most cases, the level of BCAT1 promoter methylation was reduced. Interaction network analysis suggested that BCAT1 was involved in ‘metabolism’, ‘carcinogenesis’ and the ‘immune response’ via numerous cancer-associated pathways. The present study revealed the expression patterns and potential function networks of BCAT1 in HCC, providing insights for future research into the role of BCAT1 in hepatocarcinogenesis. In addition, the study provided researchers with a way to analyze the genes of interest so they can continue their research in the right direction.