Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma

Targeting JUNB to modulate M2 macrophage polarization in preeclampsia

Preeclampsia (PE) is a complex disorder affecting pregnant women, leading to significant maternal and fetal morbidity and mortality. Understanding the cellular dynamics and molecular mechanisms underlying PE is crucial for developing effective therapeutic strategies. This study utilized single-cell RNA sequencing (scRNA-seq) to delineate the cellular landscape of the placenta in PE, identifying 11 distinct cell subpopulations, with macrophages playing a pivotal role in mediating cell-cell communication. Specifically, the transcription factor JUNB was found to be a key gene in macrophages from PE samples, influencing the interaction between macrophages and both epithelial and endothelial cells. Functional experiments indicated that interference with JUNB expression promoted macrophage polarization towards an M2 phenotype, which facilitated trophoblast invasion, migration, and angiogenesis. Mechanistically, JUNB regulated the MIIP/PI3K/AKT pathway, as evidenced by gene expression analysis following JUNB knockdown. The study further demonstrated that targeting JUNB could activate the PI3K/AKT pathway by transcriptionally activating MIIP, thus promoting M2 polarization and potentially delaying the onset of PE. These findings present new insights into the pathogenesis of PE and suggest a novel therapeutic approach by modulating macrophage polarization.

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncRNAs) in the pathobiology of lung adenocarcinoma (LUAD), research into lncRNAs specifically associated with disulfidptosis in LUAD, termed disulfidptosis-related lncRNAs (DRLs), remains insufficiently explored. Using The Cancer Genome Atlas (TCGA)-LUAD dataset, we implemented ten machine learning techniques, resulting in 101 distinct model configurations. To assess the predictive accuracy of our model, we employed both the concordance index (C-index) and receiver operating characteristic (ROC) curve analyses. For a deeper understanding of the underlying biological pathways, we referred to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) for functional enrichment analysis. Moreover, we explored differences in the tumor microenvironment between high-risk and low-risk patient cohorts. Additionally, we thoroughly assessed the prognostic value of the DRLs signatures in predicting treatment outcomes. The Kaplan-Meier (KM) survival analysis demonstrated a significant difference in overall survival (OS) between the high-risk and low-risk cohorts (p < 0.001). The prognostic model showed robust performance, with an area under the ROC curve exceeding 0.75 at one year and maintaining a value above 0.72 in the two and three-year follow-ups. Further research identified variations in tumor mutational burden (TMB) and differential responses to immunotherapies and chemotherapies. Our validation, using three GEO datasets (GSE31210, GSE30219, and GSE50081), revealed that the C-index exceeded 0.67 for GSE31210 and GSE30219. Significant differences in disease-free survival (DFS) and OS were observed across all validation cohorts among different risk groups. The prognostic model offers potential as a molecular biomarker for LUAD prognosis.

Progress in the treatment of lung adenocarcinoma by integrated traditional Chinese and Western medicine

Non-small cell lung cancer (NSCLC) overwhelmingly represents the predominant histological subtype of lung cancer, with lung adenocarcinoma emerging as the most prevalent form. Conventional Western medical treatments encompass a spectrum of modalities, including surgical interventions, cytotoxic chemotherapy, radiotherapy, targeted pharmacotherapy, and immunotherapy. In contrast, Traditional Chinese Medicine (TCM) methodologies encompass traditional Chinese medicine treatments, acupuncture therapies, and tuina treatments. While conventional Western medicine has made remarkable strides in the treatment of lung cancer, it is important to acknowledge the limitations inherent in singular treatment approaches. Consequently, the quest for a more comprehensive and integrative therapeutic paradigm becomes imperative. A deficiency of evaluation criteria specific to lung adenocarcinoma treatment in the realm of TCM represents an outstanding challenge in need of resolution. Nonetheless, in the backdrop of the continuous evolution of lung adenocarcinoma treatment modalities, the amalgamation of Chinese and Western medical approaches for treating this condition has exhibited a promising trajectory. It not only contributes to mitigating toxicity and augmenting efficacy but also serves to reduce a spectrum of postoperative complications, thereby enhancing the quality of patients' survival and extending life expectancy. This article furnishes a comprehensive survey of the research advancements in the integration of Chinese and Western medical approaches for treating lung adenocarcinoma. It elucidates the merits and demerits of individual and combined therapeutic strategies, surmounts current limitations, underscores the virtues of amalgamating Chinese and Western medical paradigms, and offers a more holistic, integrated, and efficacious treatment blueprint.