A novel signature of cuproptosis-related lncRNAs predicts prognosis in glioma: Evidence from bioinformatic analysis and experiments

Examination of the effects of capecitabine treatment on the HT-29 colorectal cancer cell line and HCG 11, HCG 15, and HCG 18 lncRNAs in CRC patients before and after chemotherapy

Colorectal cancer (CRC) is the third most common malignancy worldwide. Long noncoding RNAs (lncRNAs) are involved in several pathogenic pathways related to CRC. This study aimed to compare the expression profiles of HCG11, HCG15, and HCG18 genes in CRC patients before and after chemotherapy. Moreover, capecitabine's effects, which is a chemotherapeutic agent, were investigated on apoptosis, cell cycle, and the lncRNA expression in CRC using HT-29 cells. qRT-PCR was used to measure lncRNAs expression in patient and healthy tissues, and the HT-29 CRC cell line. Additionally, the diagnostic and prognostic utility of these lncRNAs were assessed using the ROC curve analysis. The MTT assay was used to evaluate the cytotoxicity of capecitabine, and by using flow cytometry, apoptosis induction and cell cycle progression were investigated. CRC patients expressed higher levels of HCG11 and HCG15 and lower levels of HCG18. Furthermore, those receiving capecitabine demonstrated a decrease in HCG11 and an increase in HCG18 expression. In the HT-29 cell line, capecitabine can also increase the expression of HCG18 and decrease the expression of HCG11 and HCG15. However, no statistically significant variations were determined in the expression of these lncRNAs in clinical variables. Additionally, the data show that HCG18 is a poor prognostic biomarker, and HCG11 and HCG18 are poor diagnostic biomarkers. Treatment with capecitabine caused an accumulation of sub-G1 cells, indicating a potent apoptotic effect on HT-29 cells. These findings confirmed capecitabine's anticancer effects and showed that it can increase HCG18 and reduce HCG11 and HCG15 expression.

Copper homeostasis and copper-induced cell death in tumor immunity: implications for therapeutic strategies in cancer immunotherapy

Copper is an important trace element for maintaining key biological functions such as cellular respiration, nerve conduction, and antioxidant defense. Maintaining copper homeostasis is critical for human health, and its imbalance has been linked to various diseases, especially cancer. Cuproptosis, a novel mechanism of copper-induced cell death, provides new therapeutic opportunities for metal ion regulation to interact with cell fate. This review provides insights into the complex mechanisms of copper metabolism, the molecular basis of cuproptosis, and its association with cancer development. We assess the role of cuproptosis-related genes (CRGs) associated with tumorigenesis, their importance as prognostic indicators and therapeutic targets, and the impact of copper homeostasis on the tumor microenvironment (TME) and immune response. Ultimately, this review highlights the complex interplay between copper, cuproptosis, and cancer immunotherapy.

Machine learning predicts cuproptosis-related lncRNAs and survival in glioma patients

Gliomas are the most common tumor in the central nervous system in adults, with glioblastoma (GBM) representing the most malignant form, while low-grade glioma (LGG) is a less severe. The prognosis for glioma remains poor even after various treatments, such as chemotherapy and immunotherapy. Cuproptosis is a newly defined form of programmed cell death, distinct from ferroptosis and apoptosis, primarily caused by the accumulation of the copper within cells. In this study, we compared the difference between the expression of cuproptosis-related genes in GBM and LGG, respectively, and conducted further analysis on the enrichment pathways of the exclusive expressed cuproptosis-related mRNAs in GBM and LGG. We established two prediction models for survival status using xgboost and random forest algorithms and applied the ROSE algorithm to balance the dataset to improve model performance.

Comprehensive analysis of POLH-AS1 as a prognostic biomarker in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC), a prevalent primary malignant tumor, is notorious for its high mortality rate. Despite advancements in HCC treatment, patient outcomes remain suboptimal. This study endeavors to assess the potential prognostic significance of POLH-AS1 in HCC.

METHODS

In this research, we gathered RNA-Seq information from individuals with HCC in The Cancer Genome Atlas (TCGA). We analyzed the levels of POLH-AS1 expression in both HCC cells and tissues using statistical tests. Additionally, we examined various prognostic factors in HCC using advanced methodologies. Furthermore, we employed Spearman's rank correlation analysis to examine the association between POLH-AS1 expression and the tumor's immune microenvironment. Finally, the functional roles of POLH-AS1 in HCC were validated in two HCC cell lines (HEP3B and HEPG2).

RESULTS

Our analysis revealed elevated POLH-AS1 expression across various cancers, including HCC, with heightened expression correlating with HCC progression. Notably, POLH-AS1 expression emerged as a potential biomarker for HCC patient survival and prognosis. Mechanistically, we identified the involvement of POLH-AS1 in tumorigenesis pathways such as herpes simplex virus 1 infection, interactions with neuroactive receptors, and the cAMP signaling pathway. Lastly, inhibition of POLH-AS1 was discovered to hinder the proliferation, invasion and migration of HEP3B and HEPG2 HCC cells.

CONCLUSIONS

POLH-AS1 emerges as a promising prognostic biomarker and therapeutic target for HCC, offering potential avenues for enhanced patient management and treatment strategies.

Identification of a ferroptosis-related prognostic signature and validation of ITGA6-AS1 in enhancing cell proliferation, migration and invasion in glioma

Glioma is the most common malignant tumor of the adult central nervous system. In this study, we aimed to identify a novel model for predicting glioma prognosis and a potential therapeutic target. Here, lncRNAs related to prognosis and ferroptosis were analyzed and screened through R software and online websites. A nomogram model was established and evaluated with calibration curve, receiver operating characteristic curve and decision curve analysis. Further, an enrichment analysis and immune infiltration analysis were performed. In addition, the expression level and biological function of ITGA6-AS1 were verified in vitro. We obtained a ferroptosis-related 7-lncRNA signature, and constructed a nomogram prognostic model with good predictability for 1-, 3- and 5-year overall survival of glioma patients. The enrichment analysis indicated potential involvement of certain pathways and suggested a correlation between the high-risk group and infiltration of M2 macrophages and MDSCs. Furthermore, the expression level of ITGA6-AS1 in the U118, U87, and LN229 cells was upregulated compared to the H1800 cell. Interestingly, knockdown of ITGA6-AS1 may inhibit U118 cells' proliferation, migration and invasion in vitro. while overexpression of ITGA6-AS1 in LN229 cells plays a promoting role. This study implies that the 7-lncRNA signature may contribute to the stratification of glioma prognosis, and the immune suppressive microenvironment may be associated with macrophage-ferroptosis crosstalk. Furthermore, ITGA6-AS1 may be a potential therapeutic target for patients with glioma.

Integrating bioinformatics and experimental validation to unveil disulfidptosis-related lncRNAs as prognostic biomarker and therapeutic target in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) stands as a prevalent malignancy globally, characterized by significant morbidity and mortality. Despite continuous advancements in the treatment of HCC, the prognosis of patients with this cancer remains unsatisfactory. This study aims at constructing a disulfidoptosis‑related long noncoding RNA (lncRNA) signature to probe the prognosis and personalized treatment of patients with HCC.

METHODS

The data of patients with HCC were extracted from The Cancer Genome Atlas (TCGA) databases. Univariate, multivariate, and least absolute selection operator Cox regression analyses were performed to build a disulfidptosis-related lncRNAs (DRLs) signature. Kaplan-Meier plots were used to evaluate the prognosis of the patients with HCC. Functional enrichment analysis was used to identify key DRLs-associated signaling pathways. Spearman's rank correlation was used to elucidate the association between the DRLs signature and immune microenvironment. The function of TMCC1-AS1 in HCC was validated in two HCC cell lines (HEP3B and HEPG2).

RESULTS

We identified 11 prognostic DRLs from the TCGA dataset, three of which were selected to construct the prognostic signature of DRLs. We found that the survival time of low-risk patients was considerably longer than that of high-risk patients. We further observed that the composition and the function of immune cell subpopulations were significantly different between high- and low-risk groups. Additionally, we identified that sorafenib, 5-Fluorouracil, and doxorubicin displayed better responses in the low-score group than those in the high-score group, based on IC50 values. Finally, we confirmed that inhibition of TMCC1-AS1 impeded the proliferation, migration, and invasion of hepatocellular carcinoma cells.

CONCLUSIONS

The DRL signatures have been shown to be a reliable prognostic and treatment response indicator in HCC patients. TMCC1-AS1 showed potential as a novel prognostic biomarker and therapeutic target for HCC.

Leveraging a disulfidptosis‑related lncRNAs signature for predicting the prognosis and immunotherapy of glioma

BACKGROUND

Gliomas, a prevalent form of primary brain tumors, are linked with a high mortality rate and unfavorable prognoses. Disulfidptosis, an innovative form of programmed cell death, has received scant attention concerning disulfidptosis-related lncRNAs (DRLs). The objective of this investigation was to ascertain a prognostic signature utilizing DRLs to forecast the prognosis and treatment targets of glioma patients.

METHODS

RNA-seq data were procured from The Cancer Genome Atlas database. Disulfidptosis-related genes were compiled from prior research. An analysis of multivariate Cox regression and the least absolute selection operator was used to construct a risk model using six DRLs. The risk signature's performance was evaluated via Kaplan-Meier survival curves and receiver operating characteristic curves. Additionally, functional analysis was carried out using GO, KEGG, and single-sample GSEA to investigate the biological functions and immune infiltration. The research also evaluated tumor mutational burden, therapeutic drug sensitivity, and consensus cluster analysis. Reverse transcription quantitative PCR was conducted to validate the expression level of DRLs.

RESULTS

A prognostic signature comprising six DRLs was developed to predict the prognosis of glioma patients. High-risk patients had significantly shorter overall survival than low-risk patients. The robustness of the risk model was validated by receiver operating characteristic curves and subgroup survival analysis. Risk model was used independently as a prognostic indicator for the glioma patients. Notably, the low-risk patients displayed a substantial decrease in the immune checkpoints, the proportion of immune cells, ESTIMATE and immune score. IC50 values from the different risk groups allowed us to discern three drugs for the treatment of glioma patients. Lastly, the potential clinical significance of six DRLs was determined.

CONCLUSIONS

A novel six DRLs signature was developed to predict prognosis and may provide valuable insights for patients with glioma seeking novel immunotherapy and targeted therapy.