Human Mutation最新文献

Cancer stem cells (CSCs) are a unique category of cells located within tumors, characterized by their exceptional self-renewal abilities and capacity to differentiate into different types of tumor cells. These cells are crucial in processes such as tumor metastasis, recurrence, and resistance to treatment. Nevertheless, their particular roles in bladder urothelial carcinoma (BLCA) require deeper exploration. This investigation firstly assessed the relationships between genes associated with CSCs and both the prognostic outcomes and responses to immunotherapy in patients with BLCA using cluster analysis methods. Among the genes linked to stem cells, CALR was identified as the most notable prognostic marker by the XGBoost algorithm. Additionally, the study explored the correlation between CALR and immune cell infiltration, as well as its interaction with mitomycin using molecular docking methods. In vitro experiments further validated that CALR affects BLCA stem cells. Utilizing multiple machine learning approaches, this study identified 14 essential stem cell–associated genes, underscoring their significance for BLCA diagnosis and potential therapeutic targeting. Critically, CALR demonstrates a strong correlation with prognostic outcomes and immunotherapy responses in BLCA, consistent with experimental findings indicating its elevated expression in BLCA and association with poor prognosis. Laboratory investigations have demonstrated that reducing CALR expression can lessen the stemness features of BLCA. Our results highlight the critical role of genes related to stem cells in BLCA and identify CALR as a promising target associated with stem cell functionality.

The genetic basis of nonsyndromic orofacial cleft (NsOFC) remains elusive, although associations have been identified with various genetic loci. NsOFC has a less pronounced genetic background than syndromic orofacial cleft (SyOFC), albeit Mendelian inheritance has been identified. Our hypothesis was that genes related to spliceosome function may contribute to NsOFC pathophysiology, as they do for some syndromic cases. Exome sequencing was conducted on 224 unrelated NsOFC probands. We performed filtering and analyses of predicted pathogenicity of rare variants using Highlander. We focused on 26 genes encoding spliceosome proteins. Subsequently, bioinformatic tools, such as AlphaFold, and PyMol, were applied to generate three-dimensional structures to interpret the effects of the identified variants on protein structure and interaction domains. We found six likely damaging variants: three heterozygous missense variants in small nuclear ribonucleoprotein U5 200 kDa subunit (SNRNP200) in three multiplex NsOFC families, and two missense and one splice site variant in splicing factor 3b subunit 1 (SF3B1), 4 (SF3B4), and 2 (SF3B2) in two posterior CP families and a complete CP patient, respectively. These results suggest that variants in the spliceosome complex genes, observed in 2.7% of NsOFC cases in our cohort, may contribute to disease susceptibility as potential risk factors.

Hedgehog (HH) signaling plays a crucial role in cancer development. However, HH signaling–related molecular characteristics have not been comprehensively evaluated in pancreatic cancer (PC). This study dissected the characteristics of HH signaling in PC using integrated bulk and single-cell profiling. GSEA indicated that HH signaling is significantly enriched in PC tissue. Consensus clustering was utilized to classify PC samples into two HH signaling–related subtypes: HRGcluster A and HRGcluster B. In contrast with HRGcluster A, HRGcluster B has an earlier clinical stage, better outcome, less active level of HH signaling, higher infiltration level of CD8+ T cells and B cells, and a greater likelihood of benefiting from immunotherapy and gemcitabine chemotherapy. Moreover, an HH signaling–related prognostic model (including ANLN, SERPINB3, LY6D, and DCBLD2) with excellent prediction performance was established and validated. Further analysis indicated that ANLN, SERPINB3, LY6D, and DCBLD2 were significantly upregulated in PC and associated with poor prognosis. Single-cell analysis revealed that HH signaling is relatively more active in PC cells, and PC cells with DCBLD2 high expression had significantly higher HH signaling scores. In vitro assays further indicated that DCBLD2 knockdown downregulates HH signaling and inhibits the proliferation, migration, and invasion of PC cells. In conclusion, this study reveals that HH signaling characteristics in PC and DCBLD2 regulate HH signaling to drive PC progression, providing new perspectives and theories for the diagnosis and treatment of PC.

Sepsis arises from a dysregulated host response to infection, leading to multiorgan inflammatory injury. Early diagnosis and treatment necessitate the identification of reliable immune biomarkers. This study investigated the relationship between aging, immunity, and sepsis by analyzing six human aging-related gene sets (656 genes). We identified 16 aging-related differentially expressed genes (DEGs) in sepsis. Among these, ATP11B, RBBP7, DOCK10, and NUP160 demonstrated the strongest connectivity with other genes and exhibited significant predictive power. Functional enrichment analysis (GO and KEGG) revealed distinct signaling pathway profiles between high-risk and low-risk sepsis groups (stratified based on risk scores). These dysregulated pathways, associated with multiple immune cells, were primarily linked to transcriptional dysregulation in cellular processes and cancer-related pathways. Experimental validation assays corroborated the roles of ATP11B and RBBP7. Collectively, our bioinformatic and experimental findings indicate that ATP11B, RBBP7, DOCK10, and NUP160 are implicated in the pathogenesis and progression of sepsis. But their potential for sepsis biomarkers still requires further verification.

Periodontitis (PD) is a chronic inflammatory disorder marked by immune dysregulation and progressive tissue destruction. Cellular senescence and the senescence-associated secretory phenotype (SASP) have been increasingly recognized as pivotal drivers of chronic inflammation. However, their specific contributions to PD remain insufficiently clarified. In this study, integrative bioinformatic analyses were conducted across transcriptomic datasets, employing least absolute shrinkage and selection operator, support vector machine–recursive feature elimination, and eXtreme gradient boosting algorithms to identify SASP-related genes of significance. ICAM1, CXCL12, and MMP3 were found to be markedly upregulated in PD and demonstrated strong diagnostic potential through receiver operating characteristic and artificial neural network models. Functional enrichment analysis indicated their involvement in immune cell adhesion, migration, and infection-associated pathways. Immune infiltration profiling revealed disrupted immune landscapes, with ICAM1 exhibiting a negative correlation with resting mast cells. Experimental validation using real-time quantitative polymerase chain reaction and immunohistochemistry on clinical samples confirmed elevated expression of these genes at both the mRNA and protein levels. Moreover, dexamethasone was identified via molecular docking as a potential therapeutic compound targeting ICAM1 and CXCL12. Collectively, these findings advance the understanding of SASP associated with immune regulation in PD and suggest potential biomarkers and therapeutic targets for early diagnosis and intervention.