Bladder cancer analysis by antibody array
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE69736 | GEO | 2015/06/11
SECONDARY ACCESSION(S): PRJNA286302
REPOSITORIES: GEO
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Project description:Expression profiling of a total of 656 proteins in 3 high grade non-muslce invasive bladder cancer cases/normal urothelial mucosa pairs In the study presented here, a consecutively operated, well-defined 3 HG NMIBC cases was used to acquire expression profiles of a total of 656 unique proteins, leading to the successful construction of supervised
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Project description:Using Affymetrix microarray technology we analyzed the gene expression profiles of the most important pathological categories of bladder cancer in order to detect potential marker genes. Applying an unsupervised cluster algorithm we observed clear differences between tumor and control samples, as well as between superficial and muscle invasive tumors. According to cluster results, the T1 high grade tumor type presented a global genetic profile which could not be distinguished from invasive cases. We described a new measure to classify differentially expressed genes and we compared it against the B-rank statistic as a standard method. According to this new classification method, the biological functions overrepresented in top differentially expressed genes when comparing tumor versus control samples were associated with growth, differentiation, immune system response, communication, cellular matrix and enzyme regulation. Comparing superficial versus invasive samples, the most important overrepresented biological category was growth and, specifically, DNA synthesis and mitotic cytoskeleton. On the other hand, some under expressed genes have been clearly related to muscular tissue contamination in control samples. Finally, we demonstrated that a pool strategy could be a good option to detect the best differentially expressed genes between two compared conditions. Experiment Overall Design: We analyzed gene expression profiles in normal bladder tissues (controls), low grade superficial tumor samples (pathologically classified as Ta low grade, named as Ta), high grade superficial tumors with an unclear clinical behavior (T1 high grade, named as T1) and high grade muscle invasive tumors (pathologically classified as T2, T3 or T4, named as T2+). We analyzed data using a sub-pooling strategy. The number of individual samples on every pool was: controls (4, 4, 4), Ta (5, 5, 5), T1 (5, 4, 4) and T2+ (5, 5, 5).
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Project description:Cystoscopic bladder biopsies were obtained from 19 patients and 11 controls between 2004 and 2005. Whole transcript based arrays were used to identify differences in expression profile between cancer and normal, muscle-invasive or non-muscle invasive cancer and normal, grade 1 and grade 3 bladder cancer.
2014-07-01 | E-MTAB-1560 | biostudies-arrayexpress
Project description:Total RNAs were subjected to RNA isolation and RNA-seq analyses were generated by deep sequencing using Illumina sequencing platform. We performed RNA sequencing on three matched muscle-invasive bladder cancer (MIBC) tissues with superficial tumor regions and deep infiltrating tumor regions in order to assess its potential as biomarkers. Quantitative real-time PCR were used to validate the expression pattern of mRNAs and lncRNAs in urine exosomes. Bioinformatic tools including Gene ontology, and KEGG pathway analysis were utilized.
2021-04-20 | GSE172359 | GEO
Project description:Using Affymetrix microarray technology we analyzed the gene expression profiles of the most important pathological categories of bladder cancer in order to detect potential marker genes. Applying an unsupervised cluster algorithm we observed clear differences between tumor and control samples, as well as between superficial and muscle invasive tumors. According to cluster results, the T1 high grade tumor type presented a global genetic profile which could not be distinguished from invasive cases. We described a new measure to classify differentially expressed genes and we compared it against the B-rank statistic as a standard method. According to this new classification method, the biological functions overrepresented in top differentially expressed genes when comparing tumor versus control samples were associated with growth, differentiation, immune system response, communication, cellular matrix and enzyme regulation. Comparing superficial versus invasive samples, the most important overrepresented biological category was growth and, specifically, DNA synthesis and mitotic cytoskeleton. On the other hand, some under expressed genes have been clearly related to muscular tissue contamination in control samples. Finally, we demonstrated that a pool strategy could be a good option to detect the best differentially expressed genes between two compared conditions. Keywords: disease state analysis
2007-07-01 | GSE7476 | GEO
Project description:At diagnosis approximately 75% of bladder urothelial carcinomas are non muscle invasive bladder cancers (Ta, T1 and Tis), 20% are muscle invasive bladder cancer (T2-T4) and 5% are already metastatic. Non muscle invasive bladder cancers are characterized by tumor recurrence in 60% to 85% of cases and, therefore, long-term followup is needed. The current standard methods to detect and monitor bladder cancer are cystoscopy and cytology. Cystoscopy is an invasive method and cytology is hampered by low sensitivity, especially for low grade tumors. So there is need to develop reliable and noninvasive methods to detect and predict bladder cancer biological behavior. So we have performed high density oligonucleotide microarray for discovery of new molecular markers to diagnose and predict the outcome of bladder cancer. Under an ethical guideline of Chhatrapati Shahuji Maharaj Medical University, India histologically confirmed seven bladder cancer patients were recruited from Department of Urology, Chhatrapati Shahuji Maharaj Medical University, Lucknow, India. Total RNA was extracted from tumor biopsies and hybridized on affymetrix Human Gene ST 1.1 array to determine differentially expressed genes in urinary bladder cancer with muscle invasion in comparison of normal human urinary bladder.
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