A Novel Mitochondrial-Related Gene Signature for the Tumor Immune Microenvironment Evaluation and Prognosis Prediction in Lung Adenocarcinoma

Impact of mitochondrial damage on tumor microenvironment and immune response: a comprehensive bibliometric analysis

Background

Mitochondrial damage contributes to apoptosis, oxidative stress, and inflammation, which collectively impact the immune system's function and the tumor microenvironment (TME). These processes, in turn, influence tumor cell growth, migration, and response to treatment.

Objective

We conducted a bibliometric analysis to elucidate the complex interactions between mitochondrial damage, the immune system, and the TME.

Methods

Data were sourced from the Science Citation Index Core Collection (WoSCC) and analyzed using advanced tools like VOSviewer and Citespace. Our focus was on literature published between 1999 and 2023 concerning the interactions between mitochondrial damage and the TME, as well as immune responses to tumors. The analysis included regional contributions, journal influence, institutional collaborations, authorship, co-cited authors, and keyword citation bursts.

Results

Our research encompassed 2,039 publications, revealing an increasing trend in annual output exploring the relationship between mitochondrial damage, TME dynamics, and immune responses. China, the United States, and South Korea emerged as the leading contributors. Prominent institutions included Institut National de la Santé et de la Recherche Médicale, University of Texas System, China Medical University, and Sun Yat-sen University. Key journals in this field are the International Journal of Molecular Sciences, Mitochondrion, and the European Journal of Pharmacology. Liang H and Wallace DC were identified as the most productive and co-cited authors, respectively. Keyword analysis highlighted the critical roles of inflammatory responses, oxidative stress, and the immune system in recent research.

Conclusion

This bibliometric analysis provides a comprehensive overview of historical and current research trends, underscoring the pivotal role of mitochondrial damage in the TME and immune system.

Association between strenuous sports or other exercises and lung cancer risk: a mendelian randomization study

Background

Studying the relationship between strenuous sports or other exercises (SSOE) and lung cancer risk remains underexplored. Traditional observational studies face challenges like confounders and inverse causation. However, Mendelian randomization (MR) provides a promising approach in epidemiology and genetics, using genetic variants as instrumental variables to investigate causal relationships. By leveraging MR, we have scrutinized the causal link between SSOE and lung cancer development.

Methods

Twelve single-nucleotide polymorphisms (SNPs) associated with SSOE, as identified in previously published genome-wide association studies, were utilized as instrumental variables in our investigation. Summary genetic data at the individual level were obtained from relevant studies and cancer consortia. The study encompassed a total of 11,348 cases and 15,861 controls. The statistical technique of inverse variance-weighting (IVW), commonly employed in meta-analyses and MR studies, was employed to assess the causal relationship between SSOE and lung cancer risk.

Results

The MR risk analysis indicated a causal relationship between SSOE and the incidence of lung cancer, with evidence of a reduced risk for overall lung cancer [odds ratio (OR) =0.129; 95% confidence interval (CI): 0.021-0.779; P=0.03], lung adenocarcinoma (OR =0.161; 95% CI: 0.012-2.102; P=0.16) and squamous cell lung cancer (OR =0.045; 95% CI: 0.003-0.677; P=0.03). The combined OR for lung cancer from SSOE (controlling for waist circumference and smoking status) was 0.054 (95% CI: 0.010-0.302, P<0.001).

Conclusions

Our MR analysis findings indicate a potential correlation between SSOE and a protective effect against lung cancer development. Further investigation is imperative to uncover the precise mechanistic link between them.

A mitochondria-related genes associated neuroblastoma signature - based on bulk and single-cell transcriptome sequencing data analysis, and experimental validation

Background

Neuroblastoma (NB), characterized by its marked heterogeneity, is the most common extracranial solid tumor in children. The status and functionality of mitochondria are crucial in regulating NB cell behavior. While the significance of mitochondria-related genes (MRGs) in NB is still missing in key knowledge.

Materials and methods

This study leverages consensus clustering and machine learning algorithms to construct and validate an MRGs-related signature in NB. Single-cell data analysis and experimental validation were employed to characterize the pivotal role of FEN1 within NB cells.

Results

MRGs facilitated the classification of NB patients into 2 distinct clusters with considerable differences. The constructed MRGs-related signature and its quantitative indicators, mtScore and mtRisk, effectively characterize the MRGs-related patient clusters. Notably, the MRGs-related signature outperformed MYCN in predicting NB patient prognosis and was adept at representing the tumor microenvironment (TME), tumor cell stemness, and sensitivity to the chemotherapeutic agents Cisplatin, Topotecan, and Irinotecan. FEN1, identified as the most contributory gene within the MRGs-related signature, was found to play a crucial role in the communication between NB cells and the TME, and in the developmental trajectory of NB cells. Experimental validations confirmed FEN1's significant influence on NB cell proliferation, apoptosis, cell cycle, and invasiveness.

Conclusion

The MRGs-related signature developed in this study offers a novel predictive tool for assessing NB patient prognosis, immune infiltration, stemness, and chemotherapeutic sensitivity. Our findings unveil the critical function of FEN1 in NB, suggesting its potential as a therapeutic target.

Identification of Hypoxia and Mitochondrial-related Gene Signature and Prediction of Prognostic Model in Lung Adenocarcinoma

Background: The correlation between hypoxia and tumor development is widely acknowledged. Meanwhile, the foremost organelle affected by hypoxia is mitochondria. This study aims to determine whether they possess prognostic characteristics in lung adenocarcinoma (LUAD). For this purpose, a bioinformatics analysis was conducted to assess hypoxia and mitochondrial scores related genes, resulting in the successful establishment of a prognostic model. Methods: Using the single sample Gene Set Enrichment Analysis algorithm, the hypoxia and mitochondrial scores were computed. Differential expression analysis and weighted correlation network analysis were employed to identify genes associated with hypoxia and mitochondrial scores. Prognosis-related genes were obtained through univariate Cox regression, followed by the establishment of a prognostic model using least absolute shrinkage and selection operator Cox regression. Two independent validation datasets were utilized to verify the accuracy of the prognostic model using receiver operating characteristic and calibration curves. Additionally, a nomogram was employed to illustrate the clinical significance of this study. Results: 318 differentially expressed genes associated with hypoxia and mitochondrial scores were identified for the construction of a prognostic model. The prognostic model based on 16 genes, including PKM, S100A16, RRAS, TUBA4A, PKP3, KCTD12, LPGAT1, ITPRID2, MZT2A, LIFR, PTPRM, LATS2, PDIK1L, GORAB, PCDH7, and CPED1, demonstrates good predictive accuracy for LUAD prognosis. Furthermore, tumor microenvironments analysis and drug sensitivity analysis indicate an association between risk scores and certain immune cells, and a higher risk scores suggesting improved chemotherapy efficacy. Conclusion: The research established a prognostic model consisting of 16 genes, and a nomogram was developed to accurately predict the prognosis of LUAD patients. These findings may contribute to guiding clinical decision-making and treatment selection for patients with LUAD, ultimately leading to improved treatment outcomes.

Identification of mitochondrial-related signature and molecular subtype for the prognosis of osteosarcoma

Mitochondria play a vital role in osteosarcoma. Therefore, the purpose of this study was to investigate the potential role of mitochondrial-related genes (MRGs) in osteosarcoma. Based on 92 differentially expressed MRGs, osteosarcoma samples were divided into two subtypes using the nonnegative matrix factorization (NMF). Ultimately, a univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analysis were performed to construct a prognostic risk model. The single-sample gene set enrichment analysis assessed the immune infiltration characteristics of osteosarcoma patients. Finally, we identified an osteosarcoma biomarker, malonyl-CoA decarboxylase (MLYCD), which showed downregulation. Osteosarcoma cells proliferation, migration, and invasion were effectively inhibited by the overexpression of MLYCD. Our findings will help us to further understand the molecular mechanisms of osteosarcoma and contribute to the discovery of new diagnostic biomarkers and therapeutic targets.

Role of mitochondrial alterations in human cancer progression and cancer immunity

Dysregulating cellular metabolism is one of the emerging cancer hallmarks. Mitochondria are essential organelles responsible for numerous physiologic processes, such as energy production, cellular metabolism, apoptosis, and calcium and redox homeostasis. Although the "Warburg effect," in which cancer cells prefer aerobic glycolysis even under normal oxygen circumstances, was proposed a century ago, how mitochondrial dysfunction contributes to cancer progression is still unclear. This review discusses recent progress in the alterations of mitochondrial DNA (mtDNA) and mitochondrial dynamics in cancer malignant progression. Moreover, we integrate the possible regulatory mechanism of mitochondrial dysfunction-mediated mitochondrial retrograde signaling pathways, including mitochondrion-derived molecules (reactive oxygen species, calcium, oncometabolites, and mtDNA) and mitochondrial stress response pathways (mitochondrial unfolded protein response and integrated stress response) in cancer progression and provide the possible therapeutic targets. Furthermore, we discuss recent findings on the role of mitochondria in the immune regulatory function of immune cells and reveal the impact of the tumor microenvironment and metabolism remodeling on cancer immunity. Targeting the mitochondria and metabolism might improve cancer immunotherapy. These findings suggest that targeting mitochondrial retrograde signaling in cancer malignancy and modulating metabolism and mitochondria in cancer immunity might be promising treatment strategies for cancer patients and provide precise and personalized medicine against cancer.

Construction of an endoplasmic reticulum stress-related signature in lung adenocarcinoma by comprehensive bioinformatics analysis

BACKGROUND

Lung Adenocarcinoma (LUAD) is a major component of lung cancer. Endoplasmic reticulum stress (ERS) has emerged as a new target for some tumor treatments.

METHODS

The expression and clinical data of LUAD samples were downloaded from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) database, followed by acquiring ERS-related genes (ERSGs) from the GeneCards database. Differentially expressed endoplasmic reticulum stress-related genes (DE-ERSGs) were screened and used to construct a risk model by Cox regression analysis. Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves were plotted to determine the risk validity of the model. Moreover, enrichment analysis of differentially expressed genes (DEGs) between the high- and low- risk groups was conducted to investigate the functions related to the risk model. Furthermore, the differences in ERS status, vascular-related genes, tumor mutation burden (TMB), immunotherapy response, chemotherapy drug sensitivity and other indicators between the high- and low- risk groups were studied. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to validate the mRNA expression levels of prognostic model genes.

RESULTS

A total of 81 DE-ERSGs were identified in the TCGA-LUAD dataset, and a risk model, including HSPD1, PCSK9, GRIA1, MAOB, COL1A1, and CAV1, was constructed by Cox regression analysis. K-M and ROC analyses showed that the high-risk group had a low survival, and the Area Under Curve (AUC) of ROC curves of 1-, 3- and 5-years overall survival was all greater than 0.6. In addition, functional enrichment analysis suggested that the risk model was related to collagen and extracellular matrix. Furthermore, differential analysis showed vascular-related genes FLT1, TMB, neoantigen, PD-L1 protein (CD274), Tumor Immune Dysfunction and Exclusion (TIDE), and T cell exclusion score were significantly different between the high- and low-risk groups. Finally, qRT-PCR results showed that the mRNA expression levels of 6 prognostic genes were consistent with the analysis.

CONCLUSION

A novel ERS-related risk model, including HSPD1, PCSK9, GRIA1, MAOB, COL1A1, and CAV1, was developed and validated, which provided a theoretical basis and reference value for ERS-related fields in the study and treatment of LUAD.

BTG2 and SerpinB5, a novel gene pair to evaluate the prognosis of lung adenocarcinoma

Introduction

Lung adenocarcinoma (LUAD), as the most frequent pathological subtype of non−small cell lung cancer, is often characterized by poor prognosis and low 5-year survival rate. Exploriton of new biomarkers and accurate molecular mechanisms for effectively predicting the prognosis of LUAD patients is still necessary. Presently, BTG2 and SerpinB5, which play important roles in tumors, are studied as a gene pair for the first time with the aim of exploring whether they can be used as potential prognostic markers.

Methods

Using the bioinformatics method to explore whether BTG2 and SerpinB5 can become independent prognostic factors, and explore their clinical application value and whether they can be used as immunotherapeutic markers. In addition, we also verify the conclusions obtained from external datasets, molecular docking, and SqRT-PCR.

Results

The results show that compared with normal lung tissue, BTG2 expression level was down-regulated and SerpinB5 was up-regulated in LUAD. Additionally, Kaplan–Meier survival analysis demonstrate that the prognosis of low expression level of BTG2 was poor, and that of high expression level of SerpinB5 was poor, suggesting that both of them can be used as independent prognostic factors. Moreover, the prognosis models of the two genes were constructed respectively in this study, and their prediction effect was verified by external data. Besides, ESTIMATE algorithm reveals the relationship between this gene pair and the immune microenvironment. Furthermore, patients with a high expression level of BTG2 and a low expression level of SerpinB5 have higher immunophenoscore for CTLA-4 and PD-1 inhibitors than patients with a low expression level of BTG2 and a high expression level of SerpinB5, indicating that such patients have a more obvious effect of immunotherapy.

Discussion

Collectively, all the results demonstrate that BTG2 and SerpinB5 might serve as potential prognostic biomarkers and novel therapeutic targets for LUAD.

A novel signature model based on mitochondrial-related genes for predicting survival of colon adenocarcinoma

Background

Colon cancer is the foremost reason of cancer-related mortality worldwide. Colon adenocarcinoma constitutes 90% of colon cancer, and most patients with colon adenocarcinoma (COAD) are identified until advanced stage. With the emergence of an increasing number of novel pathogenic mechanisms and treatments, the role of mitochondria in the development of cancer, has been studied and reported with increasing frequency.

Methods

We systematically analyzed the effect of mitochondria-related genes in COAD utilizing RNA sequencing dataset from The Cancer Genome Atlas database and 1613 mitochondrial function-related genes from MitoMiner database. Our approach consisted of differentially expressed gene, gene set enrichment analysis, gene ontology terminology, Kyoto Encyclopedia of Genes and Genomes, independent prognostic analysis, univariate and multivariate analysis, Kaplan–Meier survival analysis, immune microenvironment correlation analysis, and Cox regression analysis.

Results

Consequently, 8 genes were identified to construct 8 mitochondrial-related gene model by applying Cox regression analysis, CDC25C, KCNJ11, NOL3, P4HA1, QSOX2, Trap1, DNAJC28, and ATCAY. Meanwhile, we assessed the connection between this model and clinical parameters or immune microenvironment. Risk score was an independent predictor for COAD patients’ survival with an AUC of 0.687, 0.752 and 0.762 at 1-, 3- and 5-year in nomogram, respectively. The group with the highest risk score had the lowest survival rate and the worst clinical stages. Additionally, its predictive capacity was validated in GSE39582 cohort.

Conclusion

In summary, we established a prognostic pattern of mitochondrial-related genes, which can predict overall survival in COAD, which may enable a more optimized approach for the clinical treatment and scientific study of COAD. This gene signature model has the potential to improve prognosis and treatment for COAD patients in the future, and to be widely implemented in clinical settings. The utilization of this mitochondrial-related gene signature model may be benefit in the treatments and medical decision-making of COAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-02020-3.