Prognostic Value and Potential Mechanism of MTFR2 in Lung Adenocarcinoma

The potential value of the Purinergic pathway in the prognostic assessment and clinical application of kidney renal clear cell carcinoma

The Purinergic pathway is involved in a variety of important physiological processes in living organisms, and previous studies have shown that aberrant expression of the Purinergic pathway may contribute to the development of a variety of cancers, including kidney renal clear cell carcinoma (KIRC). The aim of this study was to delve into the Purinergic pathway in KIRC and to investigate its potential significance in prognostic assessment and clinical treatment. 33 genes associated with the Purinergic pathway were selected for pan-cancer analysis. Cluster analysis, targeted drug sensitivity analysis and immune cell infiltration analysis were applied to explore the mechanism of Purinergic pathway in KIRC. Using the machine learning process, we found that combining the Lasso+survivalSVM algorithm worked well for predicting survival accuracy in KIRC. We used LASSO regression to pinpoint nine Purinergic genes closely linked to KIRC, using them to create a survival model for KIRC. ROC survival curve was analyzed, and this survival model could effectively predict the survival rate of KIRC patients in the next 5, 7 and 10 years. Further univariate and multivariate Cox regression analyses revealed that age, grading, staging, and risk scores of KIRC patients were significantly associated with their prognostic survival and were identified as independent risk factors for prognosis. The nomogram tool developed through this study can help physicians accurately assess patient prognosis and provide guidance for developing treatment plans. The results of this study may bring new ideas for optimizing the prognostic assessment and therapeutic approaches for KIRC patients.

Signature and Molecular Mechanism of Mitochondrial Energy Metabolism Pathway-Related Genes in Lung Adenocarcinoma

Objective

The mitochondrial energy metabolic pathway (MEMP) is the primary energy metabolism of tumor cells, and its disruption may promote cancer emergence, spreading, and immune escape. However, there is a lack of studies to determine the relationship between relevant functional mechanisms and lung adenocarcinoma (LUAD) prognosis.

Methods

Gene set enrichment analysis (GSEA) was employed to determine MEMP pathway-related genes. Then, a prognostic model was created using the MEMP key genes that were found by LASSO-Cox regression analysis. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided the training and validation sets. Furthermore, the infiltration of immune cells was examined by ssGSEA. Finally, a screening of candidate therapeutic compounds for LUAD patients was performed using DrugBank, Protein Data Bank (PDB), and AutoDock Vina databases.

Results

First, 266 MEMP pathway-related genes that exhibited aberrant activity in tumors were identified. Then, 19 MEMP key genes were used to build a prognostic model, which can successfully predict the survival rates of LUAD patients after 1, 3, and 5 years, respectively. The Kaplan-Meier curve showed that patients in the high-risk group had considerably lower survival outcomes than those in the low-risk group. Furthermore, it was discovered that the high-risk group had the majority of activated T cells, while the low-risk group tended to have more other activated immune cells. The majority of immunological checkpoints expressed themselves more strongly in the high-risk group as well. Finally, 11 prospective medication small molecules were obtained from the projected potential therapeutic drugs, with DB0980 being regarded as the most promising of them for the treatment of LUAD.

Conclusion

This current study developed reliable prognostic signature, called MEMP score, which provides new guidance for prognostic assessment, immunotherapy, and drug development in LUAD. Thereby, DB0980 appears to be the most likely approach for the treatment of LUAD.