Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Accumulating evidence has highlighted that lncRNA acts as ceRNA and plays an important role in the occurrence and development of LUAD. Here, we comprehensively analyzed the lncRNAs, miRNAs, and mRNAs associated with LUAD from TCGA database. Then, differentially expressed lncRNAs (DElncRNA), miRNAs (DEmiRNA), and mRNAs (DEmRNA) were used to construct a lncRNA-miRNA-mRNA regulatory network according to interaction information from miRcode, TargetScan, miRTarBase, and miRDB. Finally, the RNAs of the network were analyzed for survival and submitted for Cox regression analysis to construct prognostic indicators. A total of 1,123 DElncRNAs, 95 DEmiRNAs, and 2,296 DEmRNAs were identified (|log₂FoldChange| (FC) > 2 and false discovery rate (FDR) < 0.01). The ceRNA network was established based on this and included 102 lncRNAs, 19 miRNAs, and 33 mRNAs. The DEmRNAs in the ceRNA network were found to be enriched in various cancer-related biological processes and pathways. We detected 22 lncRNAs, 12 mRNAs, and 1 miRNA in the ceRNA network that were significantly associated with the overall survival of patients with LUAD (P<0.05). We established three prognostic prediction models and calculated the area under the 1,3,5-year curve values of lncRNA, mRNA and miRNA, respectively. Among them, the prognostic index (PI) of lncRNA showed good predictive ability which was 0.737, 0.702 and 0.671 respectively, and eight lncRNAs can be used as candidate prognostic biomarkers for LUAD. In conclusion, our study provides a new perspective on the prognosis and diagnosis of LUAD on a genome-wide basis.

Previous studies have suggested a potential association between fibroblast growth factors (FGFs) and breast cancer (BC), but the evidence for the relationship between specific FGFs with BC is limited and controversial. To explore the interactions between 13 FGFs and 3 fibroblast growth factor receptors (FGFRs) with BC and its subtypes (ER+ and ER−), we conducted a Mendelian randomization (MR) analysis based on genome-wide association study summary statistics of European ancestry. Several techniques were used to ensure the stability of the causal effect, such as inverse-variance weighting, weighted median, MR-Egger regression, and Mendelian Randomization Pleiotropy Residual Sum and Outlier. Heterogeneity was assessed by calculating the Cochran’s Q value. The inverse-variance weighting analysis showed that for overall BC, FGF20 showed a genetically protective effect (odds ratio [OR] 0.996, 95% CI: 0.993–1.000, P =  .027), FGF4 can genetically promote the risk of BC (OR 1.004, 95% CI: 1.001–1.007, P =  .013). FGF1 (OR 1.055, 95% CI: 1.005–1.107, P =  .029) and FGF7 (OR 1.068, 95% CI: 1.007–1.133, P =  .028) were consistently associated with increased risk of ER+ BC, however FGF20 (OR 0.959, 95% CI: 0.920–0.999, P = .046) decreased the risk of ER+ BC. FGF23 (OR 1.077, 95% CI: 1.003–1.158, P =  .042) promote the risk of ER− BC. In the reverse MR study, ER+ BC tended to exhibit elevated levels of FGF7 (OR 1.072, 95% CI: 1.004–1.144, P = .037) and decreased levels of FGFR2 (OR 0.930, 95% CI: 0.872–0.992, P = .027). Our study results indicate that only specific types of FGFs and FGFRs may have a causal relationship with BC. Th research provides a new perspective on the mechanisms of action of different types of FGFs and FGFRs in BC, and offers potential genetic support for personalized medicine and precision therapy.

Background: Triple-negative breast cancer (TNBC) is an aggressive metastatic subtype of BC that frequently develops chemoresistance. Immune checkpoint blockers (ICB) have led to breakthroughs in TNBC treatment. This study aimed to explore research trends and public interest in ICB interventions for TNBC. Methods: We searched the Web of Science Core Collection (WoSCC) database for publications related to ICB for TNBC from 2003 to 2024. VOSviewer, CiteSpace, and R package “bibliometrix” were used to analyze the characteristics of ICB publications in TNBC from a quantitative and qualitative perspective and to visualize the results to comprehensively present the research trends in this field. Results: After removing duplicates, 2698 publications were included. The New England Journal of Medicine may be the leading and influential in the field of ICB in TNBC according to data on the total number of publications, number of citations, and impact factors. Its article entitled “Atezolizumab and Nab-Paclitaxel in Advanced TNBC” is 1 of the most cited articles. Keyword analysis showed that current research hotspots in this field are tumor microenvironment, complete pathological response, neoadjuvant chemotherapy, and PARP inhibitors. Future research hotspots may include the PD-L1 inhibitor durvalumab and antibody-drug conjugates (ADC). Conclusions: This study revealed that ICB therapy for TNBC is a rapidly evolving and high-profile topic. Future research should focus on the optimal selection of different targets for ICB in combination with neoadjuvant chemotherapy, ADC, and poly ADP-ribose polymerase inhibitors to treat TNBC.

(1) Background: Despite previous studies linking inflammatory cytokines to lung adenocarcinoma (LUAD), their causal mechanisms remain unclear. This study aims to explore the causal relationship between inflammatory cytokines and LUAD to fill this knowledge gap. (2) Methods: This study employs a comprehensive approach, integrating Mendelian randomization (MR) analysis, single-cell RNA sequencing (scRNA-seq), and transcriptomic sequencing (RNA-seq) data to investigate the relationship between inflammatory cytokines and LUAD. (3) Results: In forward MR analysis, elevated levels of hepatocyte growth factor (HGF), interleukin-1 receptor antagonist (IL-1RA), IL-5, monocyte chemoattractant protein-3, and monokine induced by interferon-γ were causally associated with an increased risk of LUAD. In reverse MR analysis, LUAD exhibited a positive causal relationship with the levels of regulated upon activation normal T cell expressed and secreted factor (RANTES) and stromal cell-derived factor-1α. The scRNA-seq data further identified specific cell populations that may influence LUAD onset and progression through the expression of particular inflammatory genes and intercellular communication. RNA-seq data analysis highlighted the role of the HGF gene in LUAD diagnosis, demonstrating its strong correlation with patient prognosis and immune cell infiltration within the tumor microenvironment. (4) Conclusions: The findings reveal a causal relationship between inflammatory cytokines and LUAD, with HGF emerging as a potential biomarker of significant clinical relevance. This study provides new insights into the molecular mechanisms underlying LUAD and lays the foundation for future therapeutic strategies.