Plasma RNA sequencing of extracellular RNAs reveals potential biomarkers for non-small cell lung cancer

Construction of an anoikis-associated lncRNA-miRNA-mRNA network reveals the prognostic role of β-elemene in non-small cell lung cancer

β-Elemene is the main active ingredient in Curcumae Rhizoma that exerts antitumour effects. Anoikis affects tumour development through various biological pathways in non-small cell lung cancer (NSCLC), but the regulation between β-elemene and anoikis remains to be explored. First, we explored the molecular expression patterns of anoikis-associated genes (AAGs) using consensus clustering and characterized the impact of AAGs on patient prognosis, clinical characteristics, and genomic instability. In addition, we revealed that AAG regulatory genes have rich interactions with β-elemene targets, and established a lncRNA-miRNA-mRNA network to explain the effect of β-elemene on anoikis. Finally, to reveal the prognostic effect of their correlation, the prognostic scoring model and clinical nomogram of β-elemene and anoikis were successfully established by least absolute shrinkage and selection operator (LASSO) and random forest algorithms. This prognostic scoring model containing noncoding RNA (ncRNA) can indicate the immunotherapy and mutational landscape, providing a novel theoretical basis and direction for the study of the antitumour mechanism of β-elemene in NSCLC patients.

Roles of MT-ND1 in Cancer

The energy shift toward glycolysis is one of the hallmarks of cancer. Complex I is a vital enzyme complex necessary for oxidative phosphorylation. The mitochondrially encoded NADH: ubiquinone oxidoreductase core subunit 1 (MT-ND1) is the largest subunit coded by mitochondria of complex I. The present study summarizes the structure and biological function of MT-ND1. From databases and literature, the expressions and mutations of MT-ND1 in a variety of cancers have been reviewed. MT-ND1 may be a biomarker for cancer diagnosis and prognosis. It is also a potential target for cancer therapy.

Comprehensive analysis of circulating cell-free RNAs in blood for diagnosing non-small cell lung cancer

Early screening and detection of non-small cell lung cancer (NSCLC) is crucial due to the significantly low survival rate in advanced stages. Blood-based liquid biopsy is non-invasive test to assistant disease diagnosis, while cell-free RNA is one of the promising biomarkers in blood. However, the disease related signatures have not been explored completely for most cell-free RNA transcriptome sequencing (cfRNA-Seq) datasets. To address this gap, we developed a comprehensive cfRNA-Seq pipeline for data analysis and constructed a machine learning model to facilitate noninvasive early diagnosis of NSCLC. The results of our study have demonstrated the identification of differential mRNA, lncRNAs and miRNAs from cfRNA-Seq, which have exhibited significant association with development and progression of lung cancer. The classifier based on gene expression signatures achieved an impressive area under the curve (AUC) of up to 0.9, indicating high specificity and sensitivity in both cross-validation and independent test. Furthermore, the analysis of T cell and B cell immune repertoire extracted from cfRNA-Seq have provided insights into the immune status of cancer patients, while the microbiome analysis has revealed distinct bacterial and viral profiles between NSCLC and normal samples. In our future work, we aim to validate the existence of cancer associated T cell receptors (TCR)/B cell receptors (BCR) and microorganisms, and subsequently integrate all identified signatures into diagnostic model to improve the prediction accuracy. This study not only provided a comprehensive analysis pipeline for cfRNA-Seq dataset but also highlights the potential of cfRNAs as promising biomarkers and models for early NSCLC diagnosis, emphasizing their importance in clinical settings.

Multifaceted roles of extracellular RNAs in different diseases

Extracellular RNAs (exRNAs) are novel circulating factors that can be used as biomarkers in various diseases. Their unique and diverse kinds, as well as their role as biomarkers, make them significant biomarkers. There has been immense work carried out since the discovery of exRNAs in circulation and other biological fluids to catalog and determine whether exRNAs may be utilized as indicators for health and illness. In this review, we aim to understand the current state of exRNAs in relation to various diseases and their potential as biomarkers. We will also review current issues and challenges faced in using exRNAs, with clinical and lab trials, that can be used as viable markers for different diseases.

Utilizing Bioinformatics Technology to Explore the Potential Mechanism of Danggui Buxue Decoction against NSCLC

While lung cancer poses a serious threat to human health, non-small-cell lung cancer (NSCLC) is the most common type of lung cancer. Danggui Buxue Decoction (DBD) is a classical traditional antitumor medicine commonly used in China. However, the potential mechanism of DBD against NSCLC has not yet been expounded. Therefore, this study clarified the potential molecular mechanism and key targets of DBD in NSCLC treatment through several technological advances, such as network pharmacology, molecular docking, and bioinformatics. Firstly, the relative active ingredients and key DBD targets were analyzed, and subsequently, a drug-ingredient-target-disease network diagram was constructed for NSCLC treatment with DBD, resulting in the identification of five main active ingredients and ten core targets according to the enrichment degree. The enrichment analysis revealed that DBD can achieve the purpose of treating NSCLC through the AGE-RAGE signaling pathway in diabetic complications. Secondly, the molecular docking approach predicted that quercetin and hederagenin have the best working mechanisms with PDE3A and PTGS1, while the survival analysis results depicted that high PDE3A gene expression has a relatively poor prognosis for NSCLC patients (p < 0.05). Additionally, PDE3A is mainly distributed in the LU65 cell line that originated from Asian population. In summary, our study results showed that DBD can treat NSCLC through the synergistic correlation between multiple ingredients, multiple targets, and multiple pathways, thus effectively improving NSCLC prognosis. This study not only reflected the medicinal value of DBD but also provided a solid structural basis for future new drug developments and targeted therapies.

tRNA Metabolism and Lung Cancer: Beyond Translation

Lung cancer, one of the most malignant tumors, has extremely high morbidity and mortality, posing a serious threat to global health. It is an urgent need to fully understand the pathogenesis of lung cancer and provide new ideas for its treatment. Interestingly, accumulating evidence has identified that transfer RNAs (tRNAs) and tRNA metabolism–associated enzymes not only participate in the protein translation but also play an important role in the occurrence and development of lung cancer. In this review, we summarize the different aspects of tRNA metabolism in lung cancer, such as tRNA transcription and mutation, tRNA molecules and derivatives, tRNA-modifying enzymes, and aminoacyl-tRNA synthetases (ARSs), aiming at a better understanding of the pathogenesis of lung cancer and providing new therapeutic strategies for it.

Genomic alteration profiles of lung cancer and their relationship to clinical features and prognosis value using individualized genetic testing

Background

This study aimed to use a panel targeting 197 genes and 38 fusions to observe the features of gene variations in lung cancer patients, as well as their prognostic values.

Methods

Patients admitted to our hospital between 2016 and 2017 were enrolled. All patients received OseqTM-Drug genetic testing using peripheral venous blood, followed by 1–2 years of observation.

Results

For all included patients, 32 genes were observed with mutations. EGFR exhibited the highest mutation rate (46.5%), followed by TP53. The majority of patients carried only one mutant gene. Interestingly, 18 (41.8%) patients showed no mutations, and some cases carried mutations in six genes simultaneously. There was no statistical relationship between mutations and demographic influence. Pathological subtypes were associated with mutations including FLI1, IGF1R, and NOTCH1. A significant correlation was observed between mutant genes and stage at diagnosis, however this requires further confirmation as there was only one case in these mutations: AKT2, AR, STK11, VEGFA, HDAC6, and ASPSCR. For the 33 patients with lymph node metastases at the time of diagnosis, no correlation with any gene mutant was found. Finally, no associations between the survival or prognosis indices (1-year survival, 1-year progression, progression free survival (PFS), and overall survival (OS)) were observed with gene mutations.

Conclusions

Together, individualized genetic testing is a feasible and minimally invasive approach in cancer genetic analysis. However, gene mutation detection has a limited efficacy in the prediction of prognosis.