Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses.

Background: Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated. Methods: We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes. Results: Through our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator-the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines. Conclusion: This study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.

To investigate the mechanism of Yiwei Decoction in the treatment of premature ovarian insufficiency-related osteoporosis using transcriptomics, network pharmacology and molecular docking techniques.

To investigate the molecular mechanism of Yiwei Decoction (YWD) in preventing Premature ovarian insufficiency (POI)-related osteoporosis from the hypothalamic perspective , and to screen for the key active and acting molecules in YWD. Cyclophosphamide was used to create the POI rat model. Groups A, B, and C were established. The Model + YWD group was group A, the model control group was group B, and the normal control group was group C. ELISA was used to determine serum GnRH and FSH levels after gavage. The transcription levels of mRNAs in each group's hypothalamus tissues were examined using RNA-seq sequencing technology. The GSEA method was used to enrich pathways based on the gene expression levels of each group. The TCM-active ingredient-target-disease network map was created using differentially expressed mRNAs (DEmRNAs) and network pharmacology. The molecular docking method was employed to investigate the affinity of the active ingredient with key targets. GnRH and FSH levels in POI rats' serum were reduced by YWD. Between groups A and B, there were 638 DEmRNAs (P < 0.05) and 55 high-significance DEmRNAs (P-adjust < 0.01). The MAPK, Hedgehog, Calcium, and B cell receptor pathways are primarily enriched in DEmRNAs from Group A and Group B. The GSEA pathway enrichment analysis indicates that YWD may regulate Long-term potentiation, Amphetamine addiction, and the Renin-angiotensin system and play a role in preventing osteoporosis. The Chinese herbal medicine (CHM)-Active ingredient-Target-disease network map includes 137 targets, 4 CHMs, and 22 active ingredients. The result of docking indicated that Stigmasterol, interacts well with the core proteins ALB, VCL and KAT5. Following the screening, we identified the targets, active components, and key pathways associated with YWD osteoporosis prevention. Most of these key targets and pathways are associated with osteoporosis, but further experimental validation is required.

Necroptosis-Related LncRNA Signatures for Prognostic Prediction in Uterine Corpora Endometrial Cancer.

Necroptosis is one of the common modes of apoptosis, and it has an intrinsic association with cancer prognosis. However, the role of the necroptosis-related long non-coding RNA LncRNA (NRLncRNAs) in uterine corpora endometrial cancer (UCEC) has not yet been fully elucidated at present. Therefore, the present study is designed to investigate the potential prognostic value of necroptosis-related LncRNAs in UCEC. In the present study, the expression profiles and clinical data of UCEC patients were downloaded from TCGA database to identify the differentially expressed NRLncRNAs associated with overall survival. A LncRNA risk model was constructed via Cox regression analysis, and its prognostic value was evaluated. We have also further evaluated the relationships between the LncRNA features and the related cellular function, related pathways, immune status, and immune checkpoints m6A-related genes. Seven signatures, including PCAT19, CDKN2B-AS1, LINC01936, LINC02178, BMPR1B-DT, LINC00237, and TRPM2-AS, were established to assess the overall survival (OS) of the UCEC in the present study. Survival analysis and ROC curves indicated that the correlated signature has good predictable performance. The normogram could accurately predict the overall survival of the patients with an excellent clinical practical value. Enrichment analysis of gene sets indicated that risk signals were enriched in several immune-related pathways. In addition, the risk characteristics were significantly correlated with immune cells, immune function, immune cell infiltration, immune checkpoints, and some m6A-related genes. This study has identified seven necroptosis-related LncRNA signatures for the first time, providing a valuable basis for a more accurate prognostic prediction of UCEC.

Research into the mechanism of intervention of SanQi in endometriosis based on network pharmacology and molecular docking technology.

BACKGROUND: By using network pharmacology and molecular docking technology, we have explored the mechanism of action of Sanqi in the treatment of endometriosis (EMS), in order to provide reference for clinical studies of Chinese medicine treatment of Ems and Chinese medicine pharmacology. METHODS: There are 123 intersecting targets between the active ingredients of Sanqi and disease targets. In the Protein-Protein Interaction network, Jun proto-oncogene, AP-1 transcription factor subunit, tumor necrosis factor, interleukin 6, etc., are the core proteins. The top 20 genes ranked by degree have been analyzed according to the Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analysis, and 20 pathways have been identified. RESULTS: On the Kyoto Encyclopedia of Genes and Genomes pathway, the most important part is the phosphatidylinositol 3'-kinase-Akt signaling pathway, and on the Gene Ontology pathway, it is the Heme binding. The top 3 targets docked to quercetin have a certain affinity when it is docked to their degree value. Among the chemical components of Sanqi, quercetin has the most targets, suggesting that it may play a major role in the treatment of EMS. CONCLUSION: The results of molecular docking provide further evidence of the potential role of Sanqi for EMS. Overall, our study provides a new direction for the treatment of EMS and provides the basis for Sanqi as a drug for the treatment of EMS.