This study conducted a large-scale Mendelian randomization analysis using genome-wide single nucleotide polymorphisms (SNPs) as instrumental variables to investigate the causal relationships between 1400 circulating metabolites and oral cancer risk. The genetic data were derived from the Canadian Longitudinal Study on Aging (CLSA) cohort and the IEU OpenGWAS database. The study employed germline genetic variants captured in genome-wide association studies for causal inference, combined with mediation analysis and CAL-27 cell experimental validation. The results identified 61 metabolites with significant causal relationships with oral cancer through SNP instrumental variables (29 with protective effects and 32 increasing risk) and revealed 14 inflammatory factors as key mediating variables, with mediation effects accounting for 1.4%-17.4% of the total effects. Cell experiments further confirmed that aspartate significantly downregulates CCL11 expression and secretion and exerts anti-inflammatory effects by suppressing inflammatory factors, including IL-1β, IL-6, and TNF-α. Conversely, CCL11 overexpression promotes malignant cellular behavior, but these effects can be reversed by aspartate through inhibition of NF-κB and MAPK signaling pathways. This study elucidates a genetic variant-driven "metabolism-inflammation" carcinogenic pathway, providing novel insights into the mechanisms of oral cancer development and demonstrating significant translational potential for precision prevention and precision therapy.
Background: Cervical cancer (CC) remains one of the leading female malignancies. Epithelial cells (EpCs), primarily derived from the cervical squamous and glandular epithelium, are targeted by human papillomavirus to drive CC. Herein, we aimed to develop an EpC-specific risk model to improve clinical outcomes and unravel tumor immune microenvironment alterations in CC.
Methods: scRNA-seq data from GSE208653 were processed using Seurat (including SCTransform for normalization and Harmony for batch correction). EpC heterogeneity was analyzed via subclustering, pseudotime trajectory analysis with monocle2, and cell-cell communication inference with CellChat. The hdWGCNA package identified EpC-specific coexpression modules. Prognostic genes were screened by univariate Cox and LASSO regression, and a Riskscore model was built using multivariate Cox regression. Immune infiltration was assessed by ssGSEA, MCPCounter, and ESTIMATE algorithms. Drug sensitivity correlation was analyzed using pRRophetic. In vitro functional assays validated key gene roles in CC cells.
Results: Forty thousand four hundred fifty-seven cells were annotated into eight cell populations with a lower percentage of EpCs. Thereafter, EpCs were categorized into three subclusters with specifically highly expressed genes in peculiar biological pathways and with distinct trajectories of fate. A strong cell-cell communication network was observed, particularly involving Ep C3 and immune cells, via ligand-receptor pairs such as LGALS9-CD44 and HBEGF-EGFR. The hdWGCNA analysis revealed Ep C3-specific gene modules, from which a five-gene prognostic signature (FTH1, RIT1, WASL, NDRG2, and KIFC3) was constructed. The resulting risk model effectively stratified patients into high- and low-risk groups with significantly different overall survival in both TCGA-CESC and GSE52903 cohorts, supported by time-dependent ROC curves. The high-risk group exhibited lower immune/stromal scores and distinct immune cell infiltration patterns. The risk score significantly correlated with sensitivity to several chemotherapeutic agents. Crucially, in vitro experiments confirmed that FTH1 knockdown inhibited the proliferation, migration, and invasion of CC cells while enhancing the level of apoptosis in cancer cells.
Conclusion: A proposed EpC-specific gene signature for CC may be applicable to support clinical decision-making.
Most of pituitary adenomas are biologically benign, but some grow local-invasively and can invade important adjacent tissues, resulting in clinical symptoms such as hormone secretion disorders and visual field defects. MicroRNA-221/222 (miR-221/222) is tandemly encoded on the X chromosome in humans, mice and rats, and is highly conserved in vertebrates with the same seed sequence. To date, miR-221/222 has been reported as either a tumor suppressor or a tumor promoter in different tumors, however, its role in pituitary tumors has not been elucidated. Our study aimed to investigate the effect and mechanism of miRNA-221/222 in pituitary tumor cells. Results of real-time quantitative PCR showed that the expression level of miRNA-221/222 in plasma exosomes from patients with pituitary tumor was significantly higher than that from healthy people. Results of cell function experiments indicated that miRNA-221/222 significantly promoted cell proliferation and migration, inhibited apoptosis and significantly inhibited the expression of Cleaved-Caspase3 and E-cadherin, while promoted the expression level of N-cadherin. With transcriptome sequencing and comprehensive bioinformatics analysis, PHACTR4 was identified as the potential target gene of miRNA-221/222 in regulating biological functions of pituitary adenoma cells. Dual luciferase reporter assay confirmed that PHACTR4 was the direct target gene of miRNA-221/222 and overexpression of PHACTR4 gene reversed the regulatory effects of miRNA-221/222. In vivo experiment of subcutaneous tumor formation in nude mice verified that miRNA-221/222 promoted tumor growth by targeting PHACTR4. In conclusion, miRNA-221/222 played the role of proto-oncogene in the occurrence and development of pituitary tumors by targeting PHACTR4, which provided a new target for the diagnosis and molecular treatment of pituitary adenomas.
Lung cancer (LC) patients frequently develop infectious pneumonia, often leading to suspension of anticancer therapy, yet the impact of LC on pneumonia progression remains unclear. This study employed a multidimensional approach to investigate whether LC constitutes a critical factor contributing to pulmonary infection onset and adverse short-term outcomes. Data from two intensive care unit databases were analyzed to assess the association between LC and pneumonia incidence and prognosis from a real-world perspective, with Mendelian randomization (MR) applied to validate causality. Additionally, post-GWAS analyses were conducted to explore comorbidity interaction patterns and potential shared therapeutic targets. Cross-sectional and cohort analyses identified LC as an independent risk factor for infectious pneumonia development and 28-day mortality, findings corroborated by sensitivity analyses across multiple models and datasets. Meta-analysis of MR results demonstrated causal relationships between genetically predicted LC and both pneumonia risk (OR = 1.103, 95% CI: 1.031-1.181, p = 0.004) and short-term mortality (OR = 1.219, 95% CI: 1.100-1.350, p < 0.001), with consistency across histological subtypes. After adjustment for comorbidities including chronic obstructive pulmonary disease (COPD), LC retained independent effects, while a strong LC-COPD genetic correlation was observed. Subgroup and mediation analyses revealed a two-way interplay between LC and COPD in driving pneumonia progression. Drug-target analyses suggested that modulation of the complement and coagulation cascades may benefit pneumonia patients with comorbid LC or COPD, highlighting CFB, SERPINA1, and SERPING1 as key candidates and pointing to monocyte-centered pathways as promising therapeutic directions. These findings indicate that infection-related pulmonary inflammation in LC patients may be partly tumor-driven, challenging routine cessation of anticancer therapy and underscoring the need for comorbidity-oriented treatment strategies.
Lung cancer and Type 1 myocardial infarction (T1MI) increasingly co-occur, yet the molecular basis underlying their interaction remains unclear. In this study, we combined multiomics profiling, in vivo and in vitro models and human clinical samples to investigate the regulatory role of the exosomal long noncoding RNA FENDRR in cancer–cardiovascular comorbidity. We found that FENDRR was markedly elevated in thrombus-derived exosomes from T1MI patients and promoted cardiomyocyte ferroptosis and ferritinophagy through the NCOA4–GPX4–P62 axis, thereby exacerbating myocardial injury. Silencing FENDRR significantly alleviated cardiac damage in the T1MI rat model. In contrast, FENDRR was consistently downregulated across multiple cancers, particularly lung adenocarcinoma (LUAD). Higher FENDRR expression was associated with favourable patient survival, and time-dependent ROC analysis demonstrated robust prognostic performance in LUAD (5 − year AUC = 0.990). Multiomics and immunogenomic analyses further revealed that FENDRR expression correlated with distinct remodelling of the tumour immune microenvironment, including alterations in immune cell infiltration, immune activation scores, chemokine and HLA gene expression and antigen-presentation capacity. These findings were supported by single-cell analyses and by enhanced CD8+ T-cell and Treg infiltration in thrombi from patients with LUAD and T1MI. Collectively, our results identify FENDRR as a context-dependent regulator that promotes myocardial injury but may exert tumour-suppressive and immune-modulatory functions in lung cancer. These insights provide a mechanistic framework for cancer–cardiovascular comorbidity and highlight FENDRR as a potential biomarker and therapeutic target across disease contexts.
Colorectal cancer (CRC) ranks among the leading causes of cancer-related mortality worldwide. Hydrogen sulfide (H2S) has been found to possess a characteristic of anticancer, which may offer a potential novel treatment for CRC. Here, we discover the potential targets and mechanism of H2S intervention in CRC employing multiomics analysis and experimental validation. The key targets of H2S intervention in CRC were identified by integrating differentially expressed genes (DEGs) from tumor and normal tissues, the CRC-associated genes, and the targets of H2S. The STRING and Cytoscape tools were explored to obtain hub genes. Functional enrichment analysis, assessment of diagnostic and prognostic significance, single-cell datasets, and cell experiments were used to explore the impact of core targets on CRC and the potential mechanism through which H2S exerts regulatory effects on CRC. Our results identified 9250 genes closely linked to CRC from DEGs and CRC-associated genes, 505 targets for H2S, and 322 potential targets of H2S intervention in CRC. Subsequently, five hub genes were filtered, including MAPK1, MAPK3, JUN, ESR1, and AKT1. The 322 common targets were enriched in the cellular stress responses and IL-17 signaling pathway. Additionally, MAPK3 had good diagnostic and prognostic value for CRC. JUN was highly expressed in immune cells. Cell experiments showed that sodium hydrosulfide (NaHS), a donor of H2S, prominently inhibited cell proliferation, promoted cell apoptosis for CRC, and downregulated the expression of MAPK1, MAPK3, AKT1, and JUN. Taken together, this study elucidates the possible genes and therapeutic mechanisms underlying exogenous H2S intervention in CRC, thereby laying a foundation for the further development of H2S-based therapeutic strategies in CRC management.
The various cellular composition of the tumor microenvironment (TME) comprises the fundamental units of tumor tissue. The types of stromal cells in the TME are genetically stable, with reduced risk of tumor recurrence and drug resistance. More and more evidence shows their clinicopathological significance and therapeutic effect in predicting prognosis. Therefore, we performed an integrated analysis of the breast cancer TME, correlating it with genomic landscapes and clinical profiles. In this work, we first conducted unsupervised hierarchical clustering on 830 tumors in the breast cancer cohort. Then, we defined three TME phenotypes and applied principal component analysis to construct a TMEscore for quantifying TME. Analysis revealed that patients stratified into the high TMEscore cohort exhibited superior survival compared to the low-scoring group. Additionally, a high TMEscore is associated with an improved response to immunotherapy. Through TME gene signature analysis, KIF15 was identified as a pivotal driver of the immunosuppressive microenvironment in breast cancer. KIF15 knockdown may promote dendritic cell infiltration and function, thereby inducing CD8+ T cell recruitment. In summary, the immune microenvironment-derived TMEscore represents an independent prognostic biomarker in breast cancer, while KIF15 emerges as a crucial molecular determinant of its immunosuppressive niche.
As a common gynecological malignancy, cervical cancer has a rising incidence rate and mortality, which has brought huge pressure to global public health. Although immunotherapy has been applied in clinical practice, its therapeutic effect is still far from satisfactory.
InferCNV was used to calculate the CNV score and the ssGSE, which is an algorithm to calculate the abundance of samples. CellChat analysis and pseudotime analysis were used to observe the evolution and interaction relationships between different clusters. Establish a prognostic model for CC patients using univariate, LASSO, and Cox analysis, and evaluate copy number variation and TME in low-risk groups. Finally, ssGSEA was applied to calculate the relationship between the hallmark gene sets and immune cycle steps and to calculate drug sensitivity in different risk groups using “oncopredict.” A series of experiments including CCK-8 assay, clone formation, EdU assay, and Transwell assay were performed to detect the role of COL4A1 in CC.
The epithelial cells were divided into nine clusters. Among them, Cluster 8 has a lower CNV score, a lower degree of variation, and a better prognosis. After that, Cluster 8 sends a signal to fibroblasts through the PTN signaling pathway. A cervical cancer–related model (CCM) was constructed based on the marker genes of Cluster 8, and it can effectively distinguish the prognosis. There is a great difference in standardized TMB, immune cell infiltration, and ESTIMATE scores between the groups. Nine drugs were identified which may achieve better therapeutic effects when applied to low-risk patients. Finally, knockdown of COL4A1 inhibits the proliferation and metastatic ability of CC cells.
Our study revealed different interactions between subgroups in the tumor microenvironment of CC epithelial cells. We established an effective prognostic model. Ultimately, through a series of in vitro function experiments, COL4A1 was recognized as a new potential target for the therapeutic intervention of CC.
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