Project description:Colorectal cancer (CRC) is the third leading cause of cancer mortality worldwide. Different pathological pathways and molecular drivers have been described and some of the associated markers are used to select effective anti-neoplastic therapy. This dataset is part of ColPortal, a platform that integrates transcriptomic, microtranscriptomic, methylomic and microbiota data of patients with colorectal cancer. ColPortal also includes information of histological features and digital histological slides from the study cases.
Project description:Although meningiomas are one of the most frequent primary intracranial tumors, there are only a few studies dealing with gene regulation processes in meningiomas. MiRNAs are key regulators of gene expression and regulation and miRNA profiles offer themselves as biomarkers for cancer development and progression. To investigate the role of miRNAs during meningioma growth and progression, we compared expression of 1205 miRNAs in 55 meningioma samples of different tumor grades and histological subtypes. We were able to classify histological subtypes in WHO grade I meningiomas with up to 97% accuracy (meningothelial versus fibroblastic) and different WHO grades with up to 93% accuracy (WHO I versus WHO III). We found significant downregulation of miRNAs on chromosome 1p36 and within two large miRNA clusters on 14q32 in high grade meningiomas, two regions that are yet associated with meningioma progression. We also identified several miRNAs associated with epithelial to mesenchymal transition differentially expressed in meningothelial meningioma compared to fibroblastic meningioma. Combined, our data show that meningiomas of different WHO grades and histological subtypes show a specific miRNA expression profile. Some individual miRNAs can also serve as potential biomarkers for meningioma progression.
Project description:Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicate potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.
Project description:To search for potential miRNAs associated with prognosis in colorectal carcinoma, miRNA expression profiles were analyzed in patients with stage III colorectal carcinoma. miRNA expression levels were compared between long and short time survival after surgery with standard chemotherapy. Two groups of colorectal carcinoma tissues for miRNA array. Long time (L) survival (≥5 years) group and short time survival (S) (<5 years) group.
Project description:To search for potential miRNAs associated with prognosis in colorectal carcinoma, miRNA expression profiles were analyzed in patients with stage III colorectal carcinoma. miRNA expression levels were compared between long and short time survival after surgery with standard chemotherapy.
Project description:Background: It has been shown that based on gene expression profiles, subgroups within epithelial ovarian cancers (EOC) can be identified. We studied a well characterized series of ovarian carcinomas from patients treated at our institute using gene expression profiling to better define clinically significant subgroups. Methods: Gene expression profiling was performed using RNA of 90 primary fresh frozen EOC samples representing all histological subtypes and stages (FIGO I-IV). Patients underwent either primary or interval debulking surgery and if indicated taxane-based chemotherapy. Pathology was reviewed for all cased and complete follow-up, including treatment response and recurrences was available for all patients. Results: Unsupervised and supervised analysis of gene expression data showed distinct subtypes correlating with histology. Mucinous carcinoma was the most distinct subtype based on gene expression profile. No significant differences in gene expression profile between high and low grade serous carcinomas could be observed. No gene expression signatures associated with survival or treatment response could be identified. Conclusion: Histological subtypes of ovarian adenocarcinomas are characterized by distinct gene expression profiles. In order to find signatures correlated to outcome of treatment it is essential that gene expression profiling studies are performed in histological homogeneous groups.
Project description:Despite recent different molecular classifications for colorectal cancer (CRC) have been proposed, CRCs are currently diagnosed based their histology [Hamilton] and just a few biomarkers are used to determine the most suitable treatment. It is for this reason important to correlate molecular profiling with histological features. This issue is especially critical in the serrated pathway for colorectal carcinogenesis since it is not as clearly discerned as the conventional adenoma-carcinoma. Furthermore, making the immune surveillance awake against tumor is now considered as a breakthrough in cancer treatment and the serrated pathological pathway comprises two CRC subtypes with typical weak (SAC) and abundant (hMSI-H) immune responses. Therefore, it is crucial to characterize the biology of these tumors since no previous studies have compared their molecular signatures.
Project description:Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC) subtypes. Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human high grade NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: More than 1.700 genes were found to be differentially expressed. Experiment Overall Design: The NSCLC patient collective was composed of the histological subtype adenocarcinoma (n=40) and squamous cell carcinoma (n=18). We subjected gene expression profiles of 40 AC and 18 SCC samples into further analysis. Unsupervised hierarchical clustering of all 58 NSCLC tumors using the 500 most variably expressed transcripts revealed two different clusters, which were strongly associated with the histological subtypes AC and SCC of NSCLC. Our result indicated that the major impact on global transcriptional changes was due to the NSCLC histology.
Project description:Aberrant methylation of DNA is supposed to be a major and early driver of colonic adenoma development and may also lead to colorectal cancer (CRC) formation. While gene methylation assays are used already for CRC screening, differential epigenetic alterations of recurring and non-recurring colorectal adenomas have yet not been systematically investigated. Here, we collected a sample set (n=72) of formalin-fixed paraffin-embedded (FFPE) primary colorectal adenomas without recurrence (n=30), primary adenomas with recurrence at the same location (n=19), so-called “matched pair samples” (n=10; comprising the primary adenoma and the recurrent adenoma) and normal mucosa specimens (n=3). We aimed to unveil differentially methylated CpG positions (DMPs) across the methylome of the selected samples using the Illumina HumanMethylation 450K BeadChip array. Unsupervised hierarchical clustering exhibited a significant association of methylation patterns with the histological subtypes. No significant DMPs were identified comparing primary adenomas with and without recurrence. Despite that, a total of 5,094 DMPs (FDR<0.05, fold change>10%) were identified in the comparisons of recurrent adenomas vs. (non-) matched primary adenomas with recurrence (674; 98% hypermethylated), recurrent adenomas vs. primary adenomas with and without recurrence (241; 99% hypermethylated) and adenomas vs. normal mucosae (4,179; 46% hypermethylated). DMPs in CpG islands were frequently hypermethylated whereas open sea and shelves exhibited hypomethylation. Gene ontological analysis demonstrated enrichment of genes associated with the immune system, inflammatory processes, and cancer-pathways. We conclude that methylation data is helpful to contribute to a more stable and reproducible histological adenoma classification which is a prerequisite to establishing profound surveillance guidelines