Project description:In this study, we aim to identify and explore the diagnostic value of differentially expressed genes (DEGs) in the blood of patients with degenerative cervical myelopathy (DCM), cervical spondylotic radiculopathy (CSR), and healthy controls (HC).
2024-10-05 | GSE223227 | GEO
Project description:Neuromotor recovery is associated with gut dysbiosis following surgical decompression for Degenerative Cervical Myelopathy
| PRJNA1081852 | ENA
Project description:Degenerative Cervical Myelopathy (DCM) induces sex-specific dysbiosis in the mouse gut bacterial microbiome, altering abundance and function
Project description:Five human cervical cancer cell lines (HeLa, CaSki, SiHa, C-33A, SW756) and one human normal cervical epithelial cell line HcerEpic were included in the study. Microarray based circRNA expression profiles were acquired using the Arraystar Human circRNA Array (8x15K, Arraystar). We identified circRNAs differentially expressed in human cervical cancer cell lines compared to human normal cervical epithelial HcerEpic cells (control).
Project description:The patients with locally advanced squamous cervical cancer (SCC) were examined in this study. All patients received neoadjuvant chemotherapy followed by radical hysterectomy. Tumor response against NAC was determined based on RECIST criterior. Gene-expression profiles of SCC were determined using Human Genome GeneChip arrays U133. SCC patients who had undergone radical hysterectomy after NAC were studied. To identify molecular signatures to predict response to NAC using Irinotecan/Nedaplatin, gene expression profiles were compared between NAC Reponder and Non-responder.
Project description:Gene expression profiling of early stage cervical cancer tumours with and without lymph node metastasis, in order to predict lymph node metastasis before treatment. Subsequently, comparing gene expression profiles between healthy cervical tissue and early stage cervical cancer tissue. Keywords: Disease stage analysis
Project description:The aim of this study was to construct and validate a prognostic risk model to predict the overall survival (OS) of patients with cervical cancer, providing a reference for individualized clinical treatment that may lead to better clinical outcomes. HLA-G-driven DEG signature consisting of the eight most important prognostic genes CD46, LGALS9, PGM1, SPRY4, CACNB3, PLIN2, MSMO1, and DAGLB was identified as a key predictor of cervical cancer. To summarize, we developed and validated a novel prognostic risk model for cervical cancer based on HLA-G-driven DEGs, and the prognostic signature showed great ability in predicting the overall survival of patients with cervical cancer.
