Five metastasis-related mRNAs signature predicting the survival of patients with liver hepatocellular carcinoma

Construction of a Prognostic Model for Hepatocellular Carcinoma Based on Macrophage Polarization-Related Genes

Background

The progression of hepatocellular carcinoma (HCC) is related to macrophage polarization (MP). Our aim was to identify genes associated with MP in HCC patients and develop a prognostic model based on these genes.

Results

We successfully developed a prognostic model consisting of six MP-related genes (SCN4A, EBF3, ADGRB2, HOXD9, CLEC1B, and MSC) to calculate the risk score for each patient. Patients were then classified into high- and low-risk groups based on their median risk score. The performance of the MP-related prognostic model was evaluated using Kaplan-Meier and ROC curves, which yielded favorable results. Additionally, the nomogram demonstrated good clinical effectiveness and displayed consistent survival predictions with actual observations. Gene Set Enrichment Analysis (GSEA) revealed enrichment of pathways related to KRAS signaling downregulation, the G2M checkpoint, and E2F targets in the high-risk group. Conversely, pathways associated with fatty acid metabolism, xenobiotic metabolism, bile acid metabolism, and adipogenesis were enriched in the low-risk group. The risk score positively correlated with the number of invasion-related genes. Immune checkpoint expression differed significantly between the two groups. Patients in the high-risk group exhibited increased sensitivity to mitomycin C, cisplatin, gemcitabine, rapamycin, and paclitaxel, while those in the low-risk group showed heightened sensitivity to doxorubicin. These findings suggest that the high-risk group may have more invasive HCC with greater susceptibility to specific drugs. IHC staining revealed higher expression levels of SCN4A in HCC tissues. Furthermore, experiments conducted on HepG2 cells demonstrated that supernatants from cells with reduced SCN4A expression promoted M2 macrophage polarization marker, CD163 in THP-1 cells. Reduced SCN4A expression induced HCC-related genes, while increased SCN4A expression reduced their expression in HepG2 cells.

Conclusion

The MP-related prognostic model comprising six MPRGs can effectively predict HCC prognosis, infer invasiveness, and guide drug therapy. SCN4A is identified as a suppressor gene in HCC.

Glycolysis‑related lncRNA may be associated with prognosis and immune activity in grade II‑III glioma

Glucose metabolism, as a novel theory to explain tumor cell behavior, has been intensively studied in various tumors. The present study explored the long non-coding RNAs (lncRNAs) related to glycolysis in grade II-III glioma, aiming to provide a promising target for further research. Pearson correlation analysis was used to identify glycolysis-related lncRNAs. Univariate/multivariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator algorithm were applied to identify glycolysis-related lncRNAs to construct a prognosis prediction model. Subsequently, multi-dimensional evaluations were used to verify whether the risk model could predict the prognosis and survival rate of patients with grade II-III glioma. Finally, it was verified by functional experiments. The present study finally identified seven glycolysis-related lncRNAs (CRNDE, AC022034.1, RHOQ-AS1, AL159169.2, AL133215.2, AC007098.1 and LINC02587) to construct a prognosis prediction model. The present study further investigated the underlying immune microenvironment, somatic landscape and functional enrichment pathways. Additionally, individualized immunotherapeutic strategies and candidate compounds were identified to guide clinical treatment. The experimental results demonstrated that CRNDE could increase the proliferation of SHG-44 cells. In conclusion, a large sample of human grade II-III glioma in The Cancer Genome Atlas database was used to construct a risk model using glycolysis-related lncRNAs to predict the prognosis of patients with grade II-III glioma.

HOMER3 promotes liver hepatocellular carcinoma cancer progression by -upregulating EZH2 and mediating miR-361/GPNMB axis

Liver hepatocellular carcinoma (LIHC) is among the most lethal human cancers. Studies have shown that Homer scaffold protein 3 (HOMER3) plays important roles in various diseases and cancers, but its biological function and molecular mechanism in LIHC have never been investigated. Our study discovered the aberrantly high expression of HOMER3 and its promising diagnostic and prognostic significance in LIHC. Functionally, HOMER3 knockdown inhibited the proliferative and migrative abilities of LIHC cells and tumor growth in vivo. Mechanically, HOMER3 mediated the aggressiveness of LIHC cells via GPNMB. Meanwhile, miR-361 directly targeted GPNMB and attenuated LIHC progression by suppressing GPNMB expression. The regulatory effect of HOMER3 during LIHC progression was exerted through the miR-361/GPNMB axis. Furthermore, EZH2 supplementation or miR-361 depletion effectively abated the tumor-suppressive effect of HOMER3 knockdown on LIHC progression. In conclusion, HOMER3 mediated LIHC progression through the EZH2/miR-361/GPNMB axis.

HOXD9/miR-451a/PSMB8 axis is implicated in the regulation of cell proliferation and metastasis via PI3K/AKT signaling pathway in human anaplastic thyroid carcinoma

Anaplastic thyroid carcinoma (ATC) is a deadly disease with a poor prognosis. Thus, there is a pressing need to determine the mechanism of ATC progression. The homeobox D9 (HOXD9) transcription factor has been associated with numerous malignancies but its role in ATC is unclear. In the present study, the carcinogenic potential of HOXD9 in ATC was investigated. We assessed the differential expression of HOXD9 on cell proliferation, migration, invasion, apoptosis, and epithelial-mesenchymal transition (EMT) in ATC and explored the interactions between HOXD9, microRNA-451a (miR-451a), and proteasome 20S subunit beta 8 (PSMB8). In addition, subcutaneous tumorigenesis and lung metastasis in mouse models were established to investigate the role of HOXD9 in ATC progression and metastasis in vivo. HOXD9 expression was enhanced in ATC tissues and cells. Knockdown of HOXD9 inhibited cell proliferation, migration, invasion, and EMT but increased apoptosis in ATC cells. The UCSC Genome Browser and JASPAR database identified HOXD9 as an upstream regulator of miR-451a. The direct binding of miR-451a to the untranslated region (3'-UTR) of PSMB8 was established using a luciferase experiment. Blocking or activation of PI3K by LY294002 or 740Y-P could attenuate the effect of HOXD9 interference or overexpression on ATC progression. The PI3K/AKT signaling pathway was involved in HOXD9-stimulated ATC cell proliferation and EMT. Consistent with in vitro findings, the downregulation of HOXD9 in ATC cells impeded tumor growth and lung metastasis in vivo. Our research suggests that through PI3K/AKT signaling, the HOXD9/miR-451a/PSMB8 axis may have significance in the control of cell proliferation and metastasis in ATC. Thus, HOXD9 could serve as a potential target for the diagnosis of ATC.

Identification of cuproptosis-related asthma diagnostic genes by WGCNA analysis and machine learning

OBJECTIVE

Cuproptosis is the latest novel form of cell death. However, the relationship between asthma and cuproptosis is not fully understood.

METHODS

In this study, we screened differentially expressed cuproptosis-related genes from the Gene Expression Omnibus (GEO) database and performed immune infiltration analysis. Subsequently, patients with asthma were typed and analyzed by Kyoto Encyclopedia of Genes and Genomes (KEGG). Weighted gene co-expression network analysis (WGCNA) was performed to calculate the module-trait correlations, and the hub genes of the intersection were taken to construct machine learning (XGB, SVM, RF, GLM). Finally, we used TGF-β to establish a BEAS-2B asthma model to observe the expression levels of hub genes.

RESULTS

Six cuproptosis-related genes were obtained. Immune-infiltration analysis shows that cuproptosis-related genes are associated with a variety of biological functions. We classified asthma patients into two subtypes based on the expression of cuproptosis-related genes and found significant Gene Ontology (GO) and immune function differences between the different subtypes. WGCNA selected 2 significant modules associated with disease features and typing. Finally, we identified TRIM25, DYSF, NCF4, ABTB1, CXCR1 as asthma biomarkers by taking the intersection of the hub genes of the 2 modules and constructing a 5-genes signature, which nomograph, decision curve analysis (DCA) and calibration curves, receiver operating characteristic curve (ROC) showed high efficiency in diagnosing the probability of survival of asthma patients. Finally, in vitro experiments have shown that DYSF and CXCR1 expression is up expressed in asthma.

CONCLUSIONS

Our study provides further directions for studying the molecular mechanism of asthma.

Ubiquitin-proteasome system-based signature to predict the prognosis and drug sensitivity of hepatocellular carcinoma

Background: Ubiquitin-proteasome system (UPS) is implicated in cancer occurrence and progression. Targeting UPS is emerging as a promising therapeutic target for cancer treatment. Nevertheless, the clinical significance of UPS in hepatocellular carcinoma (HCC) has not been entirely elucidated. Methods: Differentially expressed UPS genes (DEUPS) were screened from LIHC-TCGA datasets. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate regression analysis were conducted to establish a UPS-based prognostic risk model. The robustness of the risk model was further validated in HCCDB18, GSE14520, and GSE76427 cohorts. Subsequently, immune features, clinicopathologic characteristics, enrichment pathways, and anti-tumor drug sensitivity of the model were further evaluated. Moreover, a nomogram was established to improve the predictive ability of the risk model. Results: Seven UPS-based signatures (ATG10, FBXL7, IPP, MEX3A, SOCS2, TRIM54, and PSMD9) were developed for the prognostic risk model. Individuals with HCC with high-risk scores presented a more dismal prognosis than those with low-risk scores. Moreover, larger tumor size, advanced TNM stage, and tumor grade were observed in the high-risk group. Additionally, cell cycle, ubiquitin-mediated proteolysis, and DNA repair pathways were intimately linked to the risk score. In addition, obvious immune cell infiltration and sensitive drug response were identified in low-risk patients. Furthermore, both nomogram and risk score showed a significant prognosis-predictive ability. Conclusion: Overall, we established a novel UPS-based prognostic risk model in HCC. Our results will facilitate a deep understanding of the functional role of UPS-based signature in HCC and provide a reliable prediction of clinical outcomes and anti-tumor drug responses for patients with HCC.

Characterization of protein-based risk signature to predict prognosis and evaluate the tumor immune environment in breast cancer

BACKGROUND

Proteomics profiles have enabled a systematic insight into the prognosis of cancer. This study aimed to establish a valuable protein-based risk signature to assess the prognosis and immune status in patients with breast cancer (BC).

METHODS

Protein expression profile, RNA expression data, and clinical information were acquired from The Cancer Genome Atlas (TCGA). The whole cohort was randomly split into two cohorts, one for establishing the risk signature and the other for testing. Univariate Cox analysis and Least absolute shrinkage and selection operator (LASSO) Cox regression were utilized to construct the protein-based risk signature. All cohorts were divided into high- and low-risk groups, which were applied to investigate the clinical relevance, tumor microenvironment, and therapeutic response.

RESULTS

The prognostic proteomics signature was established based on prognostic proteins, thus categorizing patients into low-risk and high-risk groups with different prognoses. A predictive nomogram was also developed to predict 1, 3, and 5-year survival possibility for BC patients, and the calibration curves confirmed the predictive significance of this signature. Afterward, the low-risk group displayed higher immune activities, immune checkpoint expression, and immunotherapeutic response. Moreover, GSEA analysis indicated that immune-associated pathways were rich in the low-risk group. Additionally, this prognostic signature demonstrated potential predict significance for chemotherapeutic agents.

CONCLUSION

This study established an effective prognostic proteomics signature with reliable predictive performance for survival, immune activity, and drug sensitivity. It might provide a novel perspective into the protein function in BC, and guide the individual treatment strategies for BC patients.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Significance of HOXD transcription factors family in progression, migration and angiogenesis of cancer

The transcription factors (TFs) of the HOX family play significant roles during early embryonic development and cellular processes. They also play a key role in tumorigenesis as tumor oncogenes or suppressors. Furthermore, TFs of the HOXD geFIne cluster affect proliferation, migration, and invasion of tumors. Consequently, dysregulated activity of HOXD TFs has been linked to clinicopathological characteristics of cancer. HOXD TFs are regulated by non-coding RNAs and methylation of DNA on promoter and enhancer regions. In addition, HOXD genes modulate the biological function of cancer cells via the MEK and AKT signaling pathways, thus, making HOXD TFs, a suitable molecular marker for cancer prognosis and therapy. In this review, we summarized the roles of HOXD TFs in different cancers and highlighted its potential as a diagnostic and therapeutic target.

Characterization of chromatin regulators identified prognosis and heterogeneity in hepatocellular carcinoma

Liver carcinogenesis is a multiprocess that involves complicated interactions between genetics, epigenetics, and transcriptomic alterations. Aberrant chromatin regulator (CR) expressions, which are vital regulatory epigenetics, have been found to be associated with multiple biological processes. Nevertheless, the impression of CRs on tumor microenvironment remodeling and hepatocellular carcinoma (HCC) prognosis remains obscure. Thus, this study aimed to systematically analyze CR-related patterns and their correlation with genomic features, metabolism, cuproptosis activity, and clinicopathological features of patients with HCC in The Cancer Genome Atlas, International Cancer Genome Consortium-LIRI-JP cohort, and GSE14520 that utilized unsupervised consensus clustering. Three CR-related patterns were recognized, and the CRs phenotype-related gene signature (CRsscore) was developed using the least absolute shrinkage and selection operator-Cox regression and multivariate Cox algorithms to represent the individual CR-related pattern. Additionally, the CRsscore was an independent prognostic index that served as a fine predictor for energy metabolism and cuproptosis activity in HCC. Accordingly, describing a wide landscape of CR characteristics may assist us to illustrate the sealed association between epigenetics, energy metabolism, and cuproptosis activity. This study may discern new tumor therapeutic targets and exploit personalized therapy for patients.