Double minutes (DMs), extrachromosomal gene fragments found within certain tumors, have been noted to carry onco- and drug resistance genes contributing to tumor pathogenesis and progression. After screening for SUMO-related molecule expression within various tumor sample and cell line databases, we found that SUMO-conjugating enzyme UBC9 has been associated with genome instability and tumor cell DM counts, which was confirmed both in vitro and in vivo. Karyotyping determined DM counts post-UBC9 knockdown or SUMOylation inhibitor 2-D08, while RT-qPCR and Western blot were used to measure DM-carried gene expression in vitro. In vivo, fluorescence in situ hybridization (FISH) identified micronucleus (MN) expulsion. Western blot and immunofluorescence staining were then used to determine DNA damage extent, and a reporter plasmid system was constructed to detect changes in homologous recombination (HR) and non-homologous end joining (NHEJ) pathways. Our research has shown that UBC9 inhibition is able to attenuate DM formation and lower DM-carried gene expression, in turn reducing tumor growth and malignant phenotype, via MN efflux of DMs and lowering NHEJ activity to increase DNA damage. These findings thus reveal a relationship between heightened UBC9 activity, increased DM counts, and tumor progression, providing a potential approach for targeted therapies, via UBC9 inhibition.

Background: Thoracic aortic aneurysm (TAA) occurs due to pathological aortal dilation, and both individuals with normal tricuspid aortic valves (TAV) or abnormal bicuspid aortic valves (BAV), the latter being a congenital condition, are at risk. However, some differences are present between TAA/BAV and TAA/TAV with respect to their pathophysiological processes and molecular mechanisms, but their exact nature is still mostly unknown. Therefore, it is necessary to elucidate TAA developmental differences among BAV vs. TAV patients. Methods: Publically-available gene expression datasets, aortic tissue derived from TAA/BAV and TAA/TAV individuals, were analyzed by weighted gene co-expression network analysis (WGCNA) to identify gene modules associated with those conditions. Gene Ontology (GO) enrichment analysis was performed on those modules to identify the enriched genes within those modules, which were verified by Gene Set Variation Analysis (GSVA) on a dataset derived from aortic smooth muscle cell gene expression between TAA/TAV and TAV/BAV patients. Immune cell infiltration patterns were then analyzed by CIBERSORT, and a protein-protein interaction (PPI) network was constructed based on WGCNA and enrichment analysis results to identify hub genes, followed by validation via stepwise regression analysis. Three signatures most strongly associated with TAA/TAV were confirmed by receiver operating characteristic (ROC) and decision curve analyses (DCA) between prior-established training and testing gene sets. Results: WGCNA delineated 2 gene modules being associated with TAA/TAV vs. TAA/BAV; both were enriched for immune-associated genes, such as those relating to immune responses, etc., under enrichment analysis. TAA/TAV and TAA/BAV tissues also had differing infiltrating immune cell proportions, particularly with respect to dendritic, mast and CD4 memory T cells. Identified three signatures, CD86, integrin beta 2 (ITGB2) and alpha M (ITGAM), as yielding the strongest associations with TAA/TAV onset, which was verified by areas under the curve (AUC) at levels approximating 0.8 or above under ROC analysis, indicating their predictive value for TAA/TAV onset. However, we did not examine possible confounding variables, so there are many alternative explanations for this association. Conclusions: TAA/TAV pathogenesis was found to be more associated with immune-related gene expression compared to TAA/BAV, and the identification of three strongly-associated genes could facilitate their usage as future biomarkers for diagnosing the likelihood of TAA/TAV onset vs. TAA/BAV, as well as for developing future treatments.

Introduction: Women with advanced maternal age (AMA) face a higher risk of pregnancy complications including preeclampsia, fetal growth restriction, and preterm birth. While placental dysfunction is implicated, the underlying mechanisms remain unclear. This study employs high-throughput sequencing-based transcriptomics to investigate AMA-associated dysregulation in placental angiogenesis, exploring links to redox imbalance. Our goal is to establish mechanistic and functional links between altered gene expression and perinatal complications.Methods: Placental pathology from 129 cases was analyzed to identify risk factors for maternal vascular malperfusion (MVM), a key pathological condition known to impair placental function. Building upon this pathological context, placental RNA-seq data from AMA and control pregnancies, combined with public datasets, were analyzed to identify differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to identify functional pathways of dysregulated genes. Weighted gene co-expression network analysis (WGCNA) was utilized to detect AMA-related modules and hub genes, which were subsequently validated via Western blotting, qPCR, and immunohistochemistry (IHC).Results: Analysis of placental pathology (n = 129) identified advanced maternal age (AMA) as an independent risk factor for maternal vascular malperfusion (MVM) (OR = 3.022, 95% CI 1.337–6.832). RNA-seq revealed 731 differentially expressed genes (DEGs) in AMA placentas, which were enriched in energy metabolism, oxidative stress, angiogenesis, and NAD(P)H metabolic pathways. Weighted gene co-expression network analysis (WGCNA) identified six co-expression modules, of which the black module (most strongly AMA-associated) contained six hub genes (SIRT3, TLR6, AOX1, ARG1, CRYAB, HGF) exhibiting high intramodular connectivity. Functional studies confirmed that placental SIRT3 expression was markedly reduced in AMA (P < 0.05), while both impaired vascular perfusion and oxidative stress were significantly more severe.Conclusion: Our findings indicate that reduced placental SIRT3 expression is a key molecular feature in advanced maternal age. This reduction may be related to increased risk of maternal vascular malperfusion and adverse pregnancy outcomes, potentially through mechanisms involving exacerbated oxidative stress and impaired placental vascular function; however, further studies are needed to clarify these associations.

The NOD-like receptor (NLR) signaling pathway may influence human immunodeficiency virus (HIV) clearance and CD4⁺ T cell recovery through inflammatory responses, but its specific mechanism requires further investigation. A deeper understanding of genetic variations can provide new insights into the biological mechanisms underlying the occurrence and development of immunodeficiency syndrome (AIDS). By utilizing multiple bioinformatic analyses and functional annotations, we identified single-nucleotide polymorphisms (SNPs) in the NLR signaling pathway that may affect HIV-1 infection and AIDS progression. Then, a case–control study was performed to screen risk-related variants by genotyping candidate SNPs in a sample of 500 men who have sex with men (MSM) with HIV-1 and 500 healthy controls from the Han population in Northern China. The results revealed significant association between five SNPs (NLRP3 rs4612666, MAVS rs17857295, MAVS rs6084497, MAVS rs16989000, and JAK1 rs4244165) and HIV-1 infection. Interestingly, the gene–gene interaction model composed of five SNPs exhibited a cumulative effect on the disease. Specially, the increase in risk alleles carried by the samples elevated the risk of contracting HIV-1. In addition, three SNPs (IL1B rs1143623, STAT1 rs1467199 and STAT1 rs2066804) were associated with CD4⁺ T cell counts in patients with AIDS. Three SNPs (OAS1 rs1131454, NLRP3 rs10754558, and MAVS rs867335) were found to be related to the clinical staging of AIDS. This finding provides insights into the genetic variants in NLR signaling pathway genes in HIV-1 infection and AIDS progression among MSM in Northern China.

Background The clinical prognostic factors for ovarian clear cell carcinoma (OCCC) are limited, and we aim to construct a model to predict the survival of OCCC patients. Methods Data were extracted from the SEER database for patients diagnosed with OCCC. Cox regression analyses were used to identify independent risk factors for OCCC. Two nomograms were developed, and the results were evaluated comprehensively by C-index, ROC curve, calibration curve, and DCA curve. Patients diagnosed with OCCC were used as the validation set to verify the model. Results A total of 1855 OCCC patients from the SEER database were used as the training set, and 101 patients from our hospital were used as the validation set. Cox regression analysis of the independent risk factors affecting the prognosis of OCCC was used to construct nomograms. The C-index of the training set OS was 0.76, and the validation set OS was 0.75. The AUC of the training set OS is 0.803, 0.794, and 0.802 for 1, 3, and 5 years, and 0.774, 0.800, and 0.923 for the validation set. The calibration curve and DCA curve also showed that OS and CSS have good predictive power. Conclusions A nomogram based on 8 prognostic factors analyzed by Cox regression can predict the prognosis of OCCC patients effectively.