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

Chen, Erbao; He, Yu; Jiang, Jing; Yi, Jing; Zou, Zhilin; Song, Qiuzi; Ren, Qingqi; Lin, Zewei; Lü, Yi; Liu, Jikui; Zhang, Jian

doi:10.1186/s40164-022-00366-y

Cited by 13 publications

(11 citation statements)

References 44 publications

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“…The cell clone formation assay is an important method for detecting cell proliferation ability . Adherent cells may not all proliferate and do form clones, and the cells that form clones must be both adherent and proliferative cells .…”

Section: Resultsmentioning

confidence: 99%

“…The cell clone formation assay is an important method for detecting cell proliferation ability. 28 Adherent cells may not all proliferate and do form clones, and the cells that form clones must be both adherent and proliferative cells. 29 Therefore, cell clone formation ability reflects the cell population dependence, proliferative capacity, and indirectly reflects the malignancy of the tumor.…”

Section: Fmb-bbti Inhibits the Proliferation Of Crc Cellsmentioning

confidence: 99%

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Expression and Purification of Recombinant Bowman–Birk Trypsin Inhibitor from Foxtail Millet Bran and Its Anticolorectal Cancer Effect In Vitro and In Vivo

Zhang,

Qiao,

Zhao

et al. 2024

J. Agric. Food Chem.

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Trypsin inhibitors derived from plants have various pharmacological activities and promising clinical applications. In our previous study, a Bowman–Birk-type major trypsin inhibitor from foxtail millet bran (FMB-BBTI) was extracted with antiatherosclerotic activity. Currently, we found that FMB-BBTI possesses a prominent anticolorectal cancer (anti-CRC) activity. Further, a recombinant FMB-BBTI (rFMB-BBTI) was successfully expressed in a soluble manner in host strain Escherichia coli. BL21 (DE3) was induced by isopropyl-β- d-thiogalactoside (0.1 mM) at 37 °C for 3.5 h by the pET28a vector system. Fortunately, a purity greater than 93% of rFMB-BBTI with anti-CRC activity was purified by nickel-nitrilotriacetic acid affinity chromatography. Subsequently, we found that rFMB-BBTI displays a strikingly anti-CRC effect, characterized by the inhibition of cell proliferation and clone formation ability, cell cycle arrest at the G2/M phase, and induction of cell apoptosis. It is interesting that the rFMB-BBTI treatment had no obvious effect on normal colorectal cells in the same concentration range. Importantly, the anti-CRC activity of rFMB-BBTI was further confirmed in the xenografted nude mice model. Taken together, our study highlights the anti-CRC activity of rFMB-BBTI in vitro and in vivo, uncovering the clinical potential of rFMB-BBTI as a targeted agent for CRC in the future.

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Section: Resultsmentioning

confidence: 99%

Section: Fmb-bbti Inhibits the Proliferation Of Crc Cellsmentioning

confidence: 99%

Expression and Purification of Recombinant Bowman–Birk Trypsin Inhibitor from Foxtail Millet Bran and Its Anticolorectal Cancer Effect In Vitro and In Vivo

Zhang,

Qiao,

Zhao

et al. 2024

J. Agric. Food Chem.

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“…Notably, all these signature genes have been reported in HCC, although investigations into specific mechanism in the disease remained limited. For instance, CDCA8 has been associated with promoting cancer progression by binding with NF-YA and has been considered a potential therapeutic target for HCC patients [ 37 ]. Increased SEPHS1 expression has been linked to poor prognosis in HCC patients [ 38 ].…”

Section: Discussionmentioning

confidence: 99%

A hypoxia–glycolysis–lactate-related gene signature for prognosis prediction in hepatocellular carcinoma

Qin,

Sun,

et al. 2024

BMC Med Genomics

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Background Liver cancer ranks sixth in incidence and third in mortality globally and hepatocellular carcinoma (HCC) accounts for 90% of it. Hypoxia, glycolysis, and lactate metabolism have been found to regulate the progression of HCC separately. However, there is a lack of studies linking the above three to predict the prognosis of HCC. The present study aimed to identify a hypoxia–glycolysis–lactate-related gene signature for assessing the prognosis of HCC. Methods This study collected 510 hypoxia-glycolysis-lactate genes from Molecular Signatures Database (MSigDB) and then classified HCC patients from TCGA-LIHC by analyzing their hypoxia-glycolysis-lactate genes expression. Differentially expressed genes (DEGs) were screened out to construct a gene signature by LASSO-Cox analysis. Univariate and multivariate regression analyses were used to evaluate the independent prognostic value of the gene signature. Analyses of immune infiltration, somatic cell mutations, and correlation heatmap were conducted by “GSVA” R package. Single-cell analysis conducted by “SingleR”, “celldex”, “Seurat”, and “CellCha” R packages revealed how signature genes participated in hypoxia/glycolysis/lactate metabolism and PPI network identified hub genes. Results We classified HCC patients from TCGA-LIHC into two clusters and screened out DEGs. An 18-genes prognostic signature including CDCA8, CBX2, PDE6A, MED8, DYNC1LI1, PSMD1, EIF5B, GNL2, SEPHS1, CCNJL, SOCS2, LDHA, G6PD, YBX1, RTN3, ADAMTS5, CLEC3B, and UCK2 was built to stratify the risk of HCC. The risk score of the hypoxia-glycolysis-lactate gene signature was further identified as a valuable independent factor for estimating the prognosis of HCC. Then we found that the features of clinical characteristics, immune infiltration, somatic cell mutations, and correlation analysis differed between the high-risk and low-risk groups. Furthermore, single-cell analysis indicated that the signature genes could interact with the ligand-receptors of hepatocytes/fibroblasts/plasma cells to participate in hypoxia/glycolysis/lactate metabolism and PPI network identified potential hub genes in this process: CDCA8, LDHA, YBX1. Conclusion The hypoxia–glycolysis–lactate-related gene signature we built could provide prognostic value for HCC and suggest several hub genes for future HCC studies.

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“…We performed RNA isolation and qRT-PCR as described previously ( 17 ). Supplementary Table S1 shows the primer sequences.…”

Section: Methodsmentioning

confidence: 99%

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies

Chen,

Zou,

Wang

et al. 2024

Front. Immunol.

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ObjectiveSignificant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy.MethodsWe retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the “one-class logistic regression (OCLR)” algorithm to obtain the mRNAsi of patients with HCC. We performed “unsupervised consensus clustering” to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient’s prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC.ResultsWe screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient’s prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines.ConclusionThe novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

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

Cited by 13 publications

References 44 publications

Expression and Purification of Recombinant Bowman–Birk Trypsin Inhibitor from Foxtail Millet Bran and Its Anticolorectal Cancer Effect In Vitro and In Vivo

Expression and Purification of Recombinant Bowman–Birk Trypsin Inhibitor from Foxtail Millet Bran and Its Anticolorectal Cancer Effect In Vitro and In Vivo

A hypoxia–glycolysis–lactate-related gene signature for prognosis prediction in hepatocellular carcinoma

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies

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