Distinct tumor microenvironment landscapes in gastric cancer classified by cuproptosis-related lncRNAs

Performance comparison between multi-level gene expression data in cancer subgroup classification

Cancer is a serious disease that can affect various parts of the body such as breast, colon, lung or stomach. Each of these cancers has their own treatment dependent historical subgroups. Hence, the correct identification of cancer subgroup has almost same importance as the timely diagnosis of cancer. This is still a challenging task and a system with highest accuracy is essential. Current researches are moving towards analyzing the gene expression data of cancer patients for various purposes including biomarker identification and studying differently expressed genes, using gene expression data measured in a single level (selected from different gene levels including genome, transcriptome or translation). However, previous studies showed that information carried by one level of gene expression is not similar to another level. This shows the importance of integrating multi-level omics data in these studies. Hence, this study uses tumor gene expression data measured from various levels of gene along with the integration of those data in the subgroup classification of nine different cancers. This is a comprehensive analysis where four different gene expression data such as transcriptome, miRNA, methylation and proteome are used in this subgrouping and the performances between models are compared to reveal the best model.

The functions of cuproptosis in gastric cancer: therapy, diagnosis, prognosis

Gastric cancer (GC) is the fifth most prevalent type of cancer in the whole world. Cuproptosis is discovered as a programmed cell death pathway and connected to cells' growth and death, as well as tumorigenesis. The relationship between cuproptosis and GC is still elusive. Two aspects of this study will elaborate the relationship between cuproptosis and immunotherapy as well as biomarkers in GC. Notably, the herein review is intended to highlight what has been accomplished regarding the cuproptosis for the diagnosis, immunotherapy, and prognosis in GC. The aim of this study is to offer a potential directions and the strategies for future research regarding cuproptosis inside the GC.

LncRNAs: Emerging biomarkers and therapeutic targets in rectal cancer

According to findings, long non-coding RNAs (lncRNAs) have an important function in the onset and growth of various cancers, including rectal cancer (RC). RC offers unique issues in terms of diagnosis, treatment, and results, needing a full understanding of the cellular mechanisms that cause it to develop. This thorough study digs into the various functions that lncRNAs perform in RC, giving views into their multiple roles as well as possible therapeutic consequences. The function of lncRNAs in RC cell proliferation, apoptosis, migratory and infiltrating capacities, epithelial-mesenchymal shift, and therapy tolerance are discussed. Various lncRNA regulatory roles are investigated in depth, yielding information on their effect on essential cell functions such as angiogenesis, death, immunity, and growth. Systemic lncRNAs are currently acknowledged as potential indications for the initial stages of identification of cancer, with the ability to diagnose as well as forecast. Besides adding to their diagnostic utility, lncRNAs offer therapeutic opportunities as actors, contributing to the expanding landscape of cancer research. Moreover, the investigation looks into the assessment and predictive utility of lncRNAs as RC markers. The article also offers insight into lncRNAs as chemoresistance and drug resistance facilitators in the setting of RC.

Clinical Significance and Immune Infiltration Analyses of a Novel Nerve-Related lncRNA Signature in Gastric Cancer

Gastric cancer (GC) is a progressive disease with high morbidity and mortality. Accumulating evidence indicated that nervous system-cancer crosstalk can affect the occurrence and progression of GC. However, the role of nerve-related lncRNAs (NRLs) in GC remains largely unexplored. In this study, a total of 441 nerve-related genes were collected from the KEGG database, and two approaches, unsupervised clustering and WGCNA, were employed to identify NRLs. Lasso regression analysis was then used to construct the nerve-related lncRNA signature (NRLS). Based on the expression profiles of 5 lncRNAs, we developed a stable NRLS to predict survival in GC patients, and survival analyses showed significantly shorter overall survival (OS) in patients with high NRLS. In addition, the NRLS was found to be positively correlated with immune characteristics, including tumor-infiltrating immune cells, immune modulators, cytokines and chemokines. We then analyzed the role of NRLS in predicting chemotherapy and immunotherapy responses, and constructed the OS nomogram combining NRLS and other clinical features. In conclusion, we constructed a robust NRLS model to stratify GC patients and predict the outcomes of chemotherapy and immunotherapy. This study can provide a new perspective for future individualized treatment of GC.

Comprehensive analysis of disulfidptosis related genes and prognosis of gastric cancer

BACKGROUND

Gastric cancer (GC) is a common malignant tumor of the digestive system. Disulfidptosis is a new programmed cell death mechanism, although its specific mechanism in GC is incompletely understood.

AIM

In this study, we used bioinformatics analysis to explore a disulfidptosis-based predictive model related to GC prognosis and to identify potential therapeutic targets and sensitive drugs for GC.

METHODS

We extracted GC-related data from The Cancer Genome Atlas and Gene Expression Omnibus databases. R software (version 4.2.1) was used for correlation analysis.

RESULTS

Through the above analysis, we found that the disulfidptosis related gene may be related to the prognosis of GC. Six genes, namely, PLS3, GRP, APOD, SGCE, COL8A1, and VAMP7, were found to constitute a predictive model for GC prognosis. APOD is a potential therapeutic target for treating GC. Bosutinib and other drugs are sensitive for the treatment of GC.

CONCLUSION

The results of this study indicate that disulfidptosis is related to the prognosis and treatment of GC, while APOD represents a potential therapeutic target for GC.

A novel copper-induced cell death-related lncRNA prognostic signature associated with immune infiltration and clinical value in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most important malignancies and has a poor prognosis. Copper-induced cell death, recently termed cuproptosis, may directly affect the outcome of GC. Long noncoding RNAs (lncRNAs), possessing stable structures, can influence the prognosis of cancer and may serve as potential prognostic prediction factors for various cancers. However, the role of copper cell death-related lncRNAs (CRLs) in GC has not been thoroughly investigated. Here, we aim to elucidate the role of CRLs in predicting prognosis, diagnosis, and immunotherapy in GC patients.

METHODS

RNA expression data for 407 GC patients from The Cancer Genome Atlas (TCGA) were gathered, and differentially expressed CRLs were identified. Subsequently, the researchers applied univariate, LASSO, and multivariate Cox regression to construct a prognostic signature consisting of 5 lncRNAs based on the CRLs. Stratified by the median CRLSig risk score, Kaplan-Meier analysis was utilized to compare overall survival (OS) between the high- and low-risk groups. Among the two groups, gene set enrichment analysis (GSEA), tumor microenvironment (TME), drug sensitivity analysis, and immune checkpoint analysis were conducted. In addition, consensus clustering and nomogram analysis were performed to predict OS. Cell experiments and 112 human serum samples were employed to verify the effect of lncRNAs on GC. Furthermore, the diagnostic value of the CRLSig in the serum of GC patients was analyzed by the receiver operating characteristic (ROC) curve.

RESULTS

A prognostic signature for GC patients was constructed based on CRLs, composed of AC129926.1, AP002954.1, AC023511.1, LINC01537, and TMEM75. According to the K-M survival analysis, high-risk GC patients had a lower OS rate and progression-free survival rate than low-risk GC patients. Further support for the model's accuracy was provided by ROC, principal component analysis, and the validation set. The area under the curve (AUC) of 0.772 for GC patients showed a better prognostic value than any other clinicopathological variable. Furthermore, immune infiltration analysis showed that the high-risk group had greater antitumor immune responses in the tumor microenvironment. In the high-risk subgroup, 23 immune checkpoint genes had significantly higher expression levels than in the low-risk subgroup (p < 0.05). The half-maximal inhibitory concentrations (IC50) of 86 drugs were found to be significantly different in the two groups. Accordingly, the model is capable of predicting the effectiveness of immunotherapy. In addition, the five CRLs in GC serum exhibited statistically significant expression levels. The AUC of this signature in GC serum was 0.894, with a 95% CI of 0.822-0.944. Moreover, lncRNA AC129926.1 was significantly overexpressed in GC cell lines and the serum of GC patients. Importantly, colony formation, wound healing, and transwell assays further confirmed the oncogenic role of AC129926.1 in GC.

CONCLUSION

In this study, a prognostic signature model consisting of five CRLs was developed to improve OS prediction accuracy in GC patients. The model also has the potential to predict immune infiltration and immunotherapy effectiveness. Furthermore, the CRLSig might serve as a novel serum biomarker to differentiate GC patients from healthy individuals.

Novel targets for gastric cancer: The tumor microenvironment (TME), N6-methyladenosine (m6A), pyroptosis, autophagy, ferroptosis and cuproptosis

Gastric cancer (GC) is a fatal illness, and its mortality rate is very high all over the world. At present, it is a serious health problem for any country. It is a multifactorial disease due to the rising drug resistance and the increasing global cancer burden, the treatment of GC still faces many obstacles and problems. In recent years, research on GC is being carried out continuously, and we hope to address the new targets of GC treatment through this review. At the same time, we also hope to discover new ways to fight GC and create more gospel for clinical patients. First, we discuss the descriptive tumor microenvironment (TME), N6-methyladenosine (m6A), pyroptosis, autophagy, ferroptosis, and cuproptosis. Finally, we expounded on the new or potential targets of GC treatment.