OPA1 supports mitochondrial dynamics and immune evasion to CD8+ T cell in lung adenocarcinoma

Mitochondrial dynamics in pulmonary disease: Implications for the potential therapeutics

Mitochondria are dynamic organelles that continuously undergo fusion/fission to maintain normal cell physiological activities and energy metabolism. When mitochondrial dynamics is unbalanced, mitochondrial homeostasis is broken, thus damaging mitochondrial function. Accumulating evidence demonstrates that impairment in mitochondrial dynamics leads to lung tissue injury and pulmonary disease progression in a variety of disease models, including inflammatory responses, apoptosis, and barrier breakdown, and that the role of mitochondrial dynamics varies among pulmonary diseases. These findings suggest that modulation of mitochondrial dynamics may be considered as a valid therapeutic strategy in pulmonary diseases. In this review, we discuss the current evidence on the role of mitochondrial dynamics in pulmonary diseases, with a particular focus on its underlying mechanisms in the development of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS), chronic obstructive pulmonary disease (COPD), asthma, pulmonary fibrosis (PF), pulmonary arterial hypertension (PAH), lung cancer and bronchopulmonary dysplasia (BPD), and outline effective drugs targeting mitochondrial dynamics-related proteins, highlighting the great potential of targeting mitochondrial dynamics in the treatment of pulmonary disease.

Clinically relevant stratification of lung squamous carcinoma patients based on ubiquitinated proteasome genes for 3P medical approach

Relevance

The proteasome is a crucial mechanism that regulates protein fate and eliminates misfolded proteins, playing a significant role in cellular processes. In the context of lung cancer, the proteasome's regulatory function is closely associated with the disease's pathophysiology, revealing multiple connections within the cell. Therefore, studying proteasome inhibitors as a means to identify potential pathways in carcinogenesis and metastatic progression is crucial in in-depth insight into its molecular mechanism and discovery of new therapeutic target to improve its therapy, and establishing effective biomarkers for patient stratification, predictive diagnosis, prognostic assessment, and personalized treatment for lung squamous carcinoma in the framework of predictive, preventive, and personalized medicine (PPPM; 3P medicine).

Methods

This study identified differentially expressed proteasome genes (DEPGs) in lung squamous carcinoma (LUSC) and developed a gene signature validated through Kaplan-Meier analysis and ROC curves. The study used WGCNA analysis to identify proteasome co-expression gene modules and their interactions with the immune system. NMF analysis delineated distinct LUSC subtypes based on proteasome gene expression patterns, while ssGSEA analysis quantified immune gene-set abundance and classified immune subtypes within LUSC samples. Furthermore, the study examined correlations between clinicopathological attributes, immune checkpoints, immune scores, immune cell composition, and mutation status across different risk score groups, NMF clusters, and immunity clusters.

Results

This study utilized DEPGs to develop an eleven-proteasome gene-signature prognostic model for LUSC, which divided samples into high-risk and low-risk groups with significant overall survival differences. NMF analysis identified six distinct LUSC clusters associated with overall survival. Additionally, ssGSEA analysis classified LUSC samples into four immune subtypes based on the abundance of immune cell infiltration with clinical relevance. A total of 145 DEGs were identified between high-risk and low-risk score groups, which had significant biological effects. Moreover, PSMD11 was found to promote LUSC progression by depending on the ubiquitin-proteasome system for degradation.

Conclusions

Ubiquitinated proteasome genes were effective in developing a prognostic model for LUSC patients. The study emphasized the critical role of proteasomes in LUSC processes, such as drug sensitivity, immune microenvironment, and mutation status. These data will contribute to the clinically relevant stratification of LUSC patients for personalized 3P medical approach. Further, we also recommend the application of the ubiquitinated proteasome system in multi-level diagnostics including multi-omics, liquid biopsy, prediction and targeted prevention of chronic inflammation and metastatic disease, and mitochondrial health-related biomarkers, for LUSC 3PM practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00352-w.

Multi-omics analysis of the oncogenic role of optic atrophy 1 in human cancer

OBJECTIVE

To investigate the prognostic significance of optic atrophy 1 (OPA1) in pan-cancer and analyze the relationship between OPA1 and immune infiltration in cancer.

RESULTS

OPA1 exhibited high expression levels or mutations in various types of tumor cells, and its expression levels were significantly correlated with the survival rate of tumor patients. In different tumor tissues, there was a notable positive correlation between OPA1 expression levels and the infiltration of cancer-associated fibroblasts in the immune microenvironment. Additionally, OPA1 and its related genes were found to be involved in several crucial biological processes, including protein phosphorylation, protein import into the nucleus, and protein binding.

CONCLUSION

OPA1 is highly expressed or mutated in numerous tumors and is strongly associated with protein phosphorylation, patient prognosis, and immune cell infiltration. OPA1 holds promise as a novel prognostic marker with potential clinical utility across various tumor types.

METHODS

We examined OPA1 expression in pan-cancer at both the gene and protein levels using various databases, including Tumor Immune Estimation Resource 2.0 (TIMER 2.0), Gene Expression Profiling Interactive Analysis (GEPIA2), UALCAN, and The Human Protein Atlas (HPA). We utilized the Kaplan-Meier plotter and GEPIA datasets to analyze the relationship between OPA1 expression levels and patient prognosis. Through the cBioPortal database, we detected OPA1 mutations in tumors and examined their relationship with patient prognosis. We employed the TIMER 2.0 database to explore the correlation between OPA1 expression levels in tumor tissue and the infiltration of cancer-associated fibroblasts in the immune microenvironment. Furthermore, we conducted a gene search associated with OPA1 and performed enrichment analysis to identify the main signaling pathways and biological processes linked to them.

Ovarian Cancer: A Landscape of Mitochondria with Emphasis on Mitochondrial Dynamics

Ovarian cancer (OC) represents the main cause of death from gynecological malignancies in western countries. Altered cellular and mitochondrial metabolism are considered hallmarks in cancer disease. Several mitochondrial aspects have been found altered in OC, such as the oxidative phosphorylation system, oxidative stress and mitochondrial dynamics. Mitochondrial dynamics includes cristae remodeling, fusion, and fission processes forming a dynamic mitochondrial network. Alteration of mitochondrial dynamics is associated with metabolic change in tumour development and, in particular, the mitochondrial shaping proteins appear also to be responsible for the chemosensitivity and/or chemoresistance in OC. In this review a focus on the mitochondrial dynamics in OC cells is presented.