Project description:This project is the first application, which is applied as a single center project and applied according to the screening quantity. This project is a multi-omics approach to explore biomarkers associated with prognosis after secondary radical resection of recurrent and metastatic colorectal cancer.
Main research objectives: 1. To detect DNA mutation and methylation in tumor tissues by NGS detection technology (the methylation dimension should be detected in adjacent tissues at the same time), and to explore specific molecular markers related to prognosis; 2. Using NGS test technology of blood in patients with preoperative and postoperative blood ctDNA mutations and methylation double dimension testing, respectively, to explore the preoperative and postoperative ctDNA mutations and the correlation between methylation status and recurrence, including but not limited to predict patients with recurrence of sensitivity, specificity, positive predictive value, negative predictive value and recurrence warning time and other indicators.
Main contents: This study intends to include single site for the first time/organ metastasis after radical treatment and surgical indications again in patients with colorectal adenocarcinoma (including but not limited to spread to the liver, lung metastasis, peritoneal metastasis, lymph node metastasis and other organ metastasis), collected in patients with preoperative peripheral blood and tissue samples, tissue adjacent to carcinoma and postoperative peripheral blood, NGS detection technology was used to detect DNA and mutation in the relevant samples, combined with clinical treatment and prognosis information of patients, and then explore biomarkers for predicting recurrence risk.
Project description:In this study, we have identified a microRNA-based signature for the prediction of cervical cancer survival. MicroRNAs (miRNAs) are a newly identified family of small non-coding RNAs that are extensively involved in human cancers. Using our recently established PCR-based miRNA assays, we have analyzed 102 cervical cancers and identified two miRNAs (miR-200a and miR-9) that are likely to predict patient survival. A logistic regression model was developed based on these two miRNAs and the prognostic value of the model was subsequently validated with 42 independent cervical cancers. Furthermore, functional studies were performed to characterize the effect of miRNAs in cervical cancer cells. Our results suggest that both miR-200a and miR-9 could play important regulatory roles in cervical cancer control. In particular, miR-200a is likely to affect the metastatic potential of cervical cancer cells by simultaneously suppressing the expression of multiple genes that are important to cell motility.
Project description:Medullary thyroid carcinoma (MTC) is a rare and aggressive neuroendocrine tumor. Our study involves 482 retrospective MTC formalin-fixed, paraffin-embedded (FFPE) samples from 452 patients, collected from 10 Chinese clinical centers. Quantification of 10,092 proteins were achieved via diaPASEF, and 87.8% patients were found to harbor at least one mutation. International MTC grading system, concurrent papillary thyroid carcinoma (PTC), and lymph node metastasis were identified as significant risk factors. Notably, RET mutations M918T and S891A were associated with high recurrence risk in sporadic and hereditary MTC, respectively. Pathway analyses highlighted enhanced collagen biosynthesis linked to poor prognosis. Ubiquitinomics showed downregulated E3 ligases CUL4B and TRIM32 linked to structural recurrence. Unsupervised clustering identified three molecular subtypes with distinct clinical outcomes and characteristics. To address the need for precise risk stratification, we developed a machine learning model using clinical, genomic, and proteomic data to predict individualized recurrence risk. Our integrated model, comprising 20 features (2 clinical factors and 18 proteins), achieved 84.8% accuracy and an AUC of 0.87 in the independent test dataset. As a comprehensive multi-center, multi-omics study of MTC, our work provides critical insights into MTC heterogeneity and aggressiveness while offering a robust framework for personalized patient management and follow-up strategies.
Project description:This SuperSeries is composed of the following subset Series: GSE32691: Autoantibody profile timecourse of UNK GSE32874: Personal Omics Profiling Reveals Dynamic Molecular Phenotypes and Actionable Medical Risks Refer to individual Series
Project description:cervical cancer samples to test radiosensitivity Keywords: comparison between pre-irradiation and mid-irradiation status, correlation to prognosis
Project description:ObjectivesCervical Squamous Cell Carcinoma (CESC) is one of the most fatal female malignancies, and the underlying molecular mechanisms governing this disease have not been fully explored. In this research, we planned to conduct the analysis of Gene Expression Omnibus (GEO) cervical squamous cell carcinoma microarray datasets by a detailed in silico approach and to explore some novel biomarkers of CESC.MethodsThe top commonly differentially expressed genes (DEGs) from the GSE138080 and GSE113942 datasets were analyzed by Limma package-based GEO2R tool. The protein-protein interaction (PPI) network of the DEGs was drawn through Search Tool for the Retrieval of Interacting Genes (STRING), and top 6 hub genes were obtained from Cytoscape. Expression analysis and validation of hub genes expression in CESC samples and cell lines were done using UALCAN, OncoDB, GENT2, and HPA. Additionally, cBioPortal, Gene set enrichment analysis (GSEA) tool, Kaplan-Meier (KM) plotter, ShinyGO, and DGIdb databases were also used to check some important values of hub genes in CESC.ResultsOut of 79 DEGs, the minichromosome maintenance complex component 4 (MCM4), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle associated 5 (CDCA5), cell division cycle 45 (CDC45), denticleless E3 ubiquitin protein ligase homolog (DTL), and chromatin licensing and DNA replication factor 1 (CDT1) genes were regarded as hub genes in CESC. Further analysis revealed that the expressions of all these hub genes were significantly elevated in CESC cell lines and samples of diverse clinical attributes. In this study, we also documented some important correlations between hub genes and some other diverse measures, including DNA methylation, genetic alterations, and Overall Survival (OS). Last, we also identify hub genes associated ceRNA network and 31 important chemotherapeutic drugs.ConclusionThrough detailed in silico methodology, we identified 6 hub genes, including MCM4, NUSAP1, CDCA5, CDC45, DTL, and CDT1, which are likely to be associated with CESC development and diagnosis.
Project description:Joint profiling of chromatin accessibility and gene expression from the same single cell provides critical information about cell types in a tissue and cell states during a dynamic process. These emerging multi-omics techniques help the investigation of cell-type resolved gene regulatory mechanisms. Here, we developed in situ SHERRY after ATAC-seq (ISSAAC-seq), a highly sensitive and flexible single cell multi-omics method to interrogate chromatin accessibility and gene expression from the same single cell. We demonstrated that ISSAAC-seq is sensitive and provides high quality data with orders of magnitude more features than existing methods. Using the joint profiles from thousands of nuclei from the mouse cerebral cortex, we uncovered major and rare cell types together with their cell-type specific regulatory elements and expression profiles. Finally, we revealed distinct dynamics and relationships of transcription and chromatin accessibility during an oligodendrocyte maturation trajectory.