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

Telomere-methylation genes: Novel prognostic biomarkers for hepatocellular carcinoma

BACKGROUND

Since telomere length and DNA methylation both correlate with hepatocellular carcinoma (HCC) prognosis, telomere-methylation genes could be novel prognostic markers for HCC.

METHOD

This study first investigated the interaction between telomere length and DNA methylation in HCC through Mendelian randomization analysis. Then, this study identified telomere-methylation genes in HCC by employing the TCGA-LIHC cohort, and explored the expression patterns of these genes in the tumor microenvironment of HCC and potential underlying mechanisms. Finally, the HCC risk-scoring model and prognostic model based on these genes were established, and the performance of the model was assessed.

RESULT

The findings revealed a bidirectional relationship between telomere length and DNA methylation in HCC. Fifty telomere-methylation genes were identified, and the prognosis-related telomere-methylation genes were closely associated with Treg and Tprolif cell subsets within the HCC tumor microenvironment. Telomere-methylation genes could potentially impact the prognosis of HCC patients by modulating chromosome stability and regulating the cell cycle. Additionally, the constructed risk scoring model and prognostic prediction model showcased compelling clinical applicability, as evidenced by the receiver operating characteristic curve, the decision curve analysis, and the calibration curves.

CONCLUSION

This study elucidated the potential of telomere-methylation genes as prognostic biomarkers for HCC and paves the way for novel approaches in prognostication and treatment management for HCC patients.

Overexpression of CDCA8 predicts poor prognosis and drug insensitivity in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) accounts for the highest proportion of lung cancers; however, specific biomarkers are lacking for diagnosis, treatment, and prognostic assessment. Cell division cycle-associated 8 (CDCA8) is a cell cycle regulator with elevated expression in various cancers. However, the association between CDCA8 expression and LUAD prognosis remains unclear.

METHODS

The association between CDCA8 and LUAD prognosis was evaluated based on the The Cancer Genome Atlas (TCGA) dataset, and CDCA8 related functions were determined using gene enrichment and gene ontology analyses. We also analyzed the association between CDCA8 expression and immune cell infiltration. Immunohistochemistry was used to determine the differential expression of CDCA8 in tumors and controls. Finally, we evaluated the differences in the sensitivity of different levels of CDCA8 to different anticancer drugs in LUAD.

RESULTS

CDCA8 expression was significantly higher in primary LUAD tumors than in normal tissues (P < 0.001). Moreover, Kaplan-Meier survival analysis demonstrated that high CDCA8 expression predicted poor survival in patients with LUAD (P = 0.006). The receiver operating characteristic (ROC) curves indicated that CDCA8 was an effective guide for the diagnosis of LUAD. Functional annotation indicated that CDCA8 might be involved in functions such as p53 stabilization, nucleotide metabolism, RNA-mediated gene silencing, and the G2/M phase checkpoint. Immune infiltration results suggested that CDCA8 was positively correlated with Th2 cells and Tgd and negatively correlated with Eosinophils and Mast cells (P < 0.01). In addition, elevated expression of CDCA8 may increase the sensitivity of patients to certain anticancer drugs.

CONCLUSIONS

CDCA8 upregulation is significantly associated with poor survival and immune infiltration in patients with LUAD. Our study suggests that CDCA8 can be used as a biomarker for LUAD prognosis and a reference for personalized medication.

Role of cell division cycle-associated proteins in regulating cell cycle and promoting tumor progression

The cell division cycle-associated protein (CDCA) family is important in regulating cell division. High CDCA expression is significantly linked to tumor development. This review summarizes clinical and basic studies on CDCAs conducted in recent decades. Furthermore, it systematically introduces the molecular expression and function, key mechanisms, cell cycle regulation, and roles of CDCAs in tumor development, cell proliferation, drug resistance, invasion, and metastasis. Additionally, it presents the latest research on tumor diagnosis, prognosis, and treatment targeting CDCAs. These findings are pivotal for further in-depth studies on the role of CDCAs in promoting tumor development and provide theoretical support for their application as new anti-tumor targets.

Noncoding RNAs and programmed cell death in hepatocellular carcinoma: Significant role of epigenetic modifications in prognosis, chemoresistance, and tumor recurrence rate

Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high death rate in the world. The molecular mechanisms related to the pathogenesis of HCC have not been precisely defined so far. Hence, this review aimed to address the potential cross-talk between noncoding RNAs (ncRNAs) and programmed cell death in HCC. All related papers in the English language up to June 2023 were collected and screened. The searched keywords in scientific databases, including Scopus, PubMed, and Google Scholar, were HCC, ncRNAs, Epigenetic, Programmed cell death, Autophagy, Apoptosis, Ferroptosis, Chemoresistance, Tumor recurrence, Prognosis, and Prediction. According to the reports, ncRNAs, comprising long ncRNAs, microRNAs, circular RNAs, and small nucleolar RNAs can affect cell proliferation, migration, invasion, and metastasis, as well as cell death-related processes, such as autophagy, ferroptosis, necroptosis, and apoptosis in HCC by regulating cancer-associated genes and signaling pathways, for example, phosphoinositide 3-kinase/Akt, extracellular signal-regulated kinase/MAPK, and Wnt/β-catenin signaling pathways. It seems that ncRNAs, as epigenetic regulators, can be utilized as biomarkers in diagnosis, prognosis, survival and recurrence rates prediction, chemoresistance, and evaluation of therapeutic response in HCC patients. However, more scientific evidence is suggested to be accomplished to confirm these results.

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

Background

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

Methods

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

Results

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

Conclusion

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

Characterization of molecular subtypes based on chromatin regulators and identification of the role of NPAS2 in lung adenocarcinoma

BACKGROUND

Chromatin regulators (CRs) are critical epigenetic modifiers and have been reported to play critical roles during the progression of various tumors, but their role in lung adenocarcinoma (LUAD) has not been comprehensively studied.

METHODS

Differential expression and univariate Cox regression analyses were conducted to identify the prognostic CRs. Consensus clustering was applied to classify the subtypes of LUAD based on prognostic CRs. LASSO-multivariate Cox regression method was used for construction of a prognostic signature and development of chromatin regulator-related gene index (CRGI). The capacity of CRGI to distinguish survival was evaluated via Kaplan-Meier method in multiple datasets. Relationship between CRGI and tumor microenvironment (TME) was evaluated. Additionally, clinical variables and CRGI were incorporated to create a nomogram. The role of the prognostic gene NPAS2 in LUAD was elucidated via clinical samples validation and a series of in vitro and in vivo experiments.

RESULTS

Two subtypes of LUAD were classified based on 46 prognostic CRs via consensus clustering which had significantly different survival and TME. A prognostic signature consisting of six CRs (MOCS, PBK, CBX3, A1CF, NPAS2, and CTCFL) was developed and proved to be an effective survival predictor in multiple independent datasets. The prognostic signature was also demonstrated to be an indicator of TME and sensitivity to immunotherapy and chemotherapy. The nomogram was suggested to be a simple tool that can predict survival accurately. Clinical samples show that NPAS2 is highly expressed in LUAD tissues, and in vitro and in vivo experiments demonstrated that inhibition of NPAS2 impeded malignant progression of LUAD cells.

CONCLUSIONS

Our study comprehensively unveiled the functions of CRs in LUAD, developed a classifier to predict survival and response to treatments, and suggested that NPAS2 promoted LUAD progression for the first time.