The MQRG score: a novel prognostic tool for adrenocortical carcinoma patients based on mitochondrial quality.

Objectives: Adrenal tumors are common, but adrenocortical carcinomas (ACCs) are a rare and challenging form of cancer to diagnose and manage.This study aimed to explore the critical role of mitochondrial quality in maintaining cellular function and the implications of the abnormal expression of mitochondrial metabolism-related proteins observed in ACC patients. We focused on identifying the connection between mitochondrial quality and the development of ACC at molecular and genomic levels. Methods: We compared mitochondrial quality-related genes (MQRGs) across ACC subtypes using overall survival (OS) and disease-free survival (DFS) as evaluation indicators. Furthermore, a novel MQRG score was developed to predict clinical prognosis and guide immunotherapy responses accurately. Results: The majority of MQRGs were upregulated in the ACC samples, correlating to poor prognosis. The MQRG score was confirmed as an independent prognostic factor for ACC, with the high-risk MQRG score group showing a significantly shorter overall survival period. Conclusions: Multilayer alterations in MQRGs are associated with patient prognosis and immune cell infiltration characteristics. This comprehensive analysis of MQRGs can contribute to a deeper understanding of potential differences in ACC patients' tumor microenvironment. This can influence clinical decision-making and advanced prognosis prediction, thereby offering new insights into personalized treatments in ACC.

The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients.

OBJECTIVE: Although the tumor mutation burden (TMB) was reported as a biomarker for immunotherapy of various cancers, whether it can effectively predict the survival prognosis in breast cancer patients remains unclear. In this study, the prognostic value of TMB and its correlation with immune infiltration were explored by using multigroup studies. METHODS: The somatic mutation data of 986 breast cancer patients were obtained from TCGA database. Breast cancer patients were divided into a low-TMB group and a high-TMB group according to the quartile of TMB scores. The differentially expressed genes (DEGs) were identified by the "limma" R program. The CIBERSORT algorithm was utilized to estimate the immune cell fraction of each sample. The TIMER database was utilized to evaluate the association between CNVs of immune genes and tumor immune cell infiltration and the prognostic value of the immune cells in breast cancer. RESULTS: In breast cancer, TP53, PIK3CA, TTN, CDH1 and other genes were the most important mutated genes. Higher survival rate of patients was found in the low-TMB group. Among the top 10 DEGs, three of them belong to the KRT gene family. GSEA enrichment analysis showed that MAPK, Hedgehog, mTOR, TGF-bate and GnRH signaling pathways were enriched in the low-TMB group. The infiltration levels of the most of immune cells were higher in the low-TMB group (P < 0.01). Higher expression of CCL18 and TRGC1 was correlated with poor prognosis. Breast cancer patients with CCL18 copy number variations, especially arm-level gains, showed significantly decreased immune cell infiltration. In the low B cell infiltration group, the survival prognosis of breast cancer patients was poor. CONCLUSIONS: TMB is a potential prognosis marker in breast cancer. Immune-related gene CCL18 and TRGC1 are biomarkers of poor prognosis while immune (B cell) infiltration is a biomarker of good prognosis.

Identification of genes and pathways leading to poor prognosis of non-small cell lung cancer using integrated bioinformatics analysis.

Background: Non-small cell lung cancer (NSCLC) is a common malignancy with a high morbidity and mortality rate worldwide, but the driver genes and signaling pathways involved are largely unclear. Herein, our study aimed to identify significant genes with poor outcome and underlying mechanisms in NSCLC using bioinformatics analyses. Methods: Gene expression profiles (GSE33532, GSE19188, GSE102287, GSE27262), including 319 NSCLC and 232 adjacent lung tissues, were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by the GEO2R online tool. Functional and pathway enrichment analyses were performed via the DAVID database. The protein-protein interactions (PPIs) of these DEGs were constructed by the STRING website and visualized by the Cytoscape software platform. The expression of hub genes in NSCLC was validated through the GEPIA database. Kaplan-Meier plotter was used to analyse the survival rate with multivariate Cox regression. The expression of protein tyrosine kinase 2 (PTK2) in NSCLC and adjacent lung tissues was evaluated on the UALCAN database platform. Results: A total of 225 significant DEGs were obtained between NSCLC and adjacent lung tissues, containing 52 upregulated genes and 173 downregulated genes. The DEGs were clustered based on functions and signaling pathways that may be closely associated with NSCLC occurrence. A total of 174 DEGs were identified from the PPI network complex. Top 10 hub genes were selected by CytoHubba plugin. As independent predictors, seven genes (COL1A1, ADAM12, VWF, OGN, EDN1, CAV1, ITGA8) were associated with poor prognosis in NSCLC via multivariate Cox regression (P<0.01). Four genes (VWF, CAV1, ITGA8, COL1A1) were found to be significantly enriched in the focal adhesion pathway (P=1.04E-04) and to be upstream regulators of PTK2. PTK2 was upregulated in NSCLC and associated with poor survival prognosis in lung squamous cell carcinoma (LUSC). Conclusions: Taken together, the important genes and pathways in NSCLC were identified by using integrated bioinformatics analysis. PTK2 could be a key gene associated with the biological process of NSCLC formation and progression and a potential therapeutic target for NSCLC treatment.

Prediction of MiR-21-5p in Promoting the Development of Lung Adenocarcinoma via PDZD2 Regulation.

BACKGROUND Lung adenocarcinoma currently accounts for the highest cancer-related mortality rate worldwide. MiR-21-5p has a vital role in various types of cancers. We have analyzed the miR-21-5p expression level, prognosis, and associated molecular pathways in lung adenocarcinoma with multiple bioinformatics databases. MATERIAL AND METHODS The Cancer Genome Atlas (TCGA) database was employed to fetch the miR-21-5p expression profile in multiple tumors. We used the UALCAN platform to assess the differential regulation of the miR-21-5p in healthy tissue and lung adenocarcinoma. Also, the survival prognosis of the miR-21-5p in each stage of lung adenocarcinoma was done by the Kaplan-Meier database. The STARBASE and UALCAN databases were employed to predict the miR-21-5p target genes, and the levels of target genes and their prognostic value were analyzed. RESULTS MiR-21-5p was overexpressed in the majority of human cancers. MiR-21-5p demonstrated escalated expression in the lung adenocarcinoma tissue in contrast to the normal tissue (P<0.05). Poor prognosis was witnessed in the miR-21-5p high expression group as compared to the low expression group (hazard ratio [HR]= 1.59, P<0.05). PDZD2 was predicted as a miR-21-5p potential target. We found a negative correlation between PDZD2 and miR-21-5p (r=-0.255, P<0.05). PDZD2 was downregulated in lung adenocarcinoma (P<0.05). Overexpression of PDZD2 was associated with a better prognosis of survival in lung adenocarcinoma patients (HR=0.45, P<0.05). CONCLUSIONS MiR-21-5p exhibits the potential to act as a biomarker for the survival prognosis of lung adenocarcinoma. It might be responsible for the onset and progression of lung adenocarcinoma through PDZD2 regulation.

[Plasma miRNA-23a and miRNA-451 as candidate biomarkers for early diagnosis of nonsmall cell lung cancer: a case-control study].

OBJECTIVE: To study the value of plasma miRNA23-a and miRNA-451 as potential biomarkers for early diagnosis of non-small cell lung cancer (NSCLC). METHODS: Fifty patients with NSCLC and 50 healthy control subjects were recruited for testing the plasma levels of miRNA23-a and miRNA-451 and their expression levels in the tumor tissues using qRT-PCR. The correlations of the plasma levels of miRNA23-a and miRNA-451 with their expressions in the tumor tissues were analyzed. The diagnostic power of CEA, miRNA23-a and miRNA-451 for NSCLC was evaluated using the receiver-operating characteristics (ROC) curves and the area under the ROC curves (AUC). In the NSCLC cell line A549, we tested the effect of inhibition of miRNA-23a and miRNA-451 on the expression levels of SPRY2 and MIF mRNA using qRT-PCR. RESULTS: The expression levels of miRNA-23a and miRNA-451 in NSCLC tissues was significantly associated with smoking, tumor size, lymph node metastasis and TNM stage (P < 0.05). Compared with those in the control group, miRNA-23a level was significantly increased while miRNA-451 was significantly down-regulated in the tumor tissues and plasma of NSCLC patients. The plasma levels of miRNA-23a and miRNA-45 were strongly correlated with their expression levels in the tumor tissues. ROC analysis showed that for the diagnosis of NSCLC, the AUC, sensitivity and specificity of either miRNA-23a or miRNA-451 were significantly higher than those of CEA (P < 0.05). The combination of miRNA23-a and miRNA-451 markedly improved the AUC (0.900), sensitivity (78%) and specificity (86%) for the diagnosis. In A549 cells, inhibition of miRNA23-a and miRNA-451 resulted in significantly increased expression levels of SPRY2 mRNA and MIF mRNA, respectively. CONCLUSIONS: miRNA-23a and miRNA-451 can be used as potential biomarkers for early diagnosis of NSCLC, and their combined detection can be more effective for the diagnosis.