Cervical spine
Ontology highlight
ABSTRACT:
SUBMITTER: 
David Nickerson
PROVIDER: a61 | Physiome Model Repository |
REPOSITORIES: PMR
Similar Datasets
Project description:Comparable plasma lipid changes in patients with high-grade cervical intraepithelial neoplasia and patients with cervical cancer
2020-10-22 | MSV000086351 | GNPS
Project description:To investigate the differences in mRNA profiles specially related to metabolism in cervical cancer, 5 primary cervical cancer tissues and 6 normal cervical tissues were collected. The differential expression of metabolism-associated-mRNA was verified using qRT-PCR.
2021-07-14 | GSE173097 | GEO
Project description:mRNA, lncRNA, and miRNA signatures were identified to discriminate cervical adenocarcinoma from normal cervix by whole transcriptome sequencing. We confirmed the RNA-seq data in another cohort of clinical cervical tissue samples by qRT-PCR.We demonstrated that miR-192-5p/HNF1A-AS1/VIL1 panel could accurately discriminates adenocarcinoma from normal cervix. Moreover,we also identified the circRNA expression profiles in cervical adenocarcinoma tissues and explored the function roles and mechanisms of circular RNA circEYA1 and circSPIDR in cervical adenocarcinoma cells.
2020-10-13 | GSE145372 | GEO
Project description:Cervical cancer is characterized by a well-defined pre-malignant phase, cervical intraepithelial neoplasia (CIN). Identification of high grade CIN lesions by population-based screening programs and their subsequent treatment has led to a significant reduction of the incidence and mortality of cervical cancer. Cytology-based testing of cervical smears is the most widely used cervical cancer screening method, but is not ideal, as the sensitivity for detection of CIN2 and higher (CIN2+) is only ~55%. Therefore, more sensitive and specific biomarkers for cervical cancer and its precancerous stages are needed.
2018-05-03 | PXD008723 | Pride
Project description:Analysis of various of up-regulated and down-regulated genes in Normal Cervical mucosa, Cervical intraepithelial neoplasia and Cervical squamous cell carcinoma. The report provides a data analysis methodology for identification of co-expressed gene patterns, as emerging clusters, in global transcriptome of cervical mucosal pre-malignant and malignant conditions in comparison to their normal counterparts. Microarray based study of global gene expression is often used to extract molecular signatures underlying cancer progression. Such endeavors endorse self organizing map, a type of artificial neural network to analyze high dimensional pre-processed transcriptome data to segregate hotspot genes in component plane for disease subtypes. This report provides a data analysis methodology for identification of coexpressed gene patterns, as emerging clusters, in global transcriptome of oral and cervical mucosal premalignant and malignant conditions in comparison to their normal counterparts. Four exclusive cluster patterns, each involving 100 − 300 genes, were identified from component planes for oral study groups. Gene expression associated with each pattern belonged to 32 biological processes. Analysis on cervical biopsies, where cancer was compared to cervical interepithelial neoplasia and normal counterpart, it revealed three non-overlapping patterns for each condition. In cervical interepithelial neoplasia an intermediate pattern with nine different dominant functional processes was identified, whereas, in cervical squamous cell carcinoma pattern showed dominance for seven different functions. This analysis demonstrated utility of self organizing map to capture dominant enriched patterns as visual plots and revealed six common biological processes like transcription and RNA processing, cytoskeleton reorganization, angiogenesis, immunity, neuron signalling, and connective tissue remodelling in the pathogenesis of oral and cervical cancers. In fact it could provide an intuitive understanding of molecular course in carcinogenesis and may contribute for combinatorial biomarker discovery.
2016-02-01 | GSE64217 | GEO
Project description:Background. MicroRNAs (miRNAs) are short (~22 nt) non-coding regulatory RNAs that control gene expression at the translational level. Deregulation of miRNA expression has been discovered in a wide variety of tumours and it is now clear that they contribute to cancer development and progression. This prompted the development of miRNA-chips for cancer diagnosis or prognosis, opening a new door to understand carcinogenesis. Cervical cancer is one of the most common cancers in women worldwide. Therefore, there is a strong need for a non-invasive, fast and efficient method to diagnose the disease. We investigated miRNA expression profiles in cervical cancer using a microarray platform developed in house containing probes for mature miRNAs. Results. We have evaluated miRNA expression profiles of a heterogeneous set of cervical tissues from 25 different patients. This set included 19 normal cervical tissues, 4 squamous cell carcinoma, 5 high-grade squamous intraepithelial lesion (HSIL) and 9 low-grade squamous intraepithelial lesion (LSIL) samples. We observed high variability in miRNA expression especially among normal cervical samples, which prevented us from obtaining a unique miRNA expression signature for this tumour type. However, miRNAs deregulation in malignant and pre-malignant cervical tissues was detected after tackling the high variability observed. We were also able to identify putative targets of relevant candidate miRNAs. Conclusions. Our results show that miRNA deregulation may play an important role in the malignant transformation of cervical squamous cells. In addition, deregulated miRNAs highlight new candidate targets allowing a better understanding of the molecular mechanism of this tumour type.
2010-08-01 | GSE19611 | GEO
Project description:16 Long SAGE libraries Keywords: Various degrees of cervical dysplasia Normal Cervical Tissue (N1, N2, N3, N4) CIN III, severe dysplasia cervical tissue (C1, C2, C3, C4, C5, C6) CIN I, mild dysplasia, cervical tissue (M1, M2, M3) CIN II, moderate dysplasia, cervical tissue (M4, M5, M6)
2008-02-18 | E-GEOD-7433 | biostudies-arrayexpress
Project description:To explore the circRNA expression profiles during the development and progression of cervical cancer, we performed RNA sequencing analysis with ribosomal RNA-depleted in HPV negative normal cervical epithelium, HPV16 positive normal cervical epithelium, HPV16 positive high-grade squamous intraepithelial lesion (HSIL), and HPV16 positive cervical squamous cell carcinoma tissues,6 cases in each group.Totally 66868 circRNAs were identified (Back-spliced junctions reads≥1)
2020-12-21 | GSE147009 | GEO