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:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients. Gene expression was measured for 32 ovarian cancer cell lines using the GeneChip Human Exon 1.0 ST Array (Affymetrix). Morphological subtypes were assigned based on cell morphology, size, growth pattern and proliferation rate during culturing of the cell lines.
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:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients.
Project description:To elucidate the epithelial cell diversity within the nasal inferior turbinates, a comprehensive investigation was conducted comparing control subjects to individuals with house dust mite-induced allergic rhinitis. This study aimed to delineate the differential expression profiles and phenotypic variations of epithelial cells in response to allergic rhinitis. This research elucidated distinct subpopulations and rare cell types of epithelial cells within the nasal turbinates, discerning alterations induced by allergic rhinitis. Furthermore, by interrogating transcriptomic signatures, the investigation provided novel insights into the cellular dynamics and immune responses underlying allergic rhinitis pathogenesis
Project description:Epithelial ovarian cancer is morphologically and clinically heterogeneous. Transcriptional profiling has revealed molecular subtypes (referred to as M-bM-^@M-^\C-signaturesM-bM-^@M-^]) that correlate to biological as well as clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and to investigate similarities to the intrinsic molecular subtypes of breast cancer. Global gene expression profiling was performed using Illumina's HT12 Bead Arrays and applied to 59 fresh-frozen ovarian tumors. SAM analysis revealed enrichment of cell cycel processes among the malignant tumors, in line with malignant tumors being highly proliferative. The borderline tumors were split between the malignant and benign tumor clusters, indicating that borderline tumors have both malignant and benign features. Furthermore, nearest centroid classification was performed applying previously published gene profiles for the ovarian cancer C-signatures and the intrinsic breast cancer subtypes, respectively, and showed significant correlations between the malignant serous tumors and the highly aggressive C1, C2 and C4 ovarian cancer signatures, and the basal-like breast cancer subtype. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer C3 signature. The borderline tumors, on the other hand, correlated significantly to the Luminal A breast cancer subtype. These findings remained when analyzed in a large, independent dataset. The data in this study link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, including an aggressive phenotype, frequent TP53 mutations and a high degree of genomic instability, and suggest that biomarkers and targeted therapies may overlap between these subsets of ovarian and breast cancers. Finally, the link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers. Total RNA obtained from serous ovarian adenocarcinomas, adenomas and borderline tumors. Gene expression profiling using Illumina's HT12 v4 bead arrays. Application of ovarian cancer molecular subtypes and intrinsic breast cancer subtypes using nearest centroid classification. KRAS and BRAF mutation analyses in the malignant and borderline tumors.
Project description:Biologically and clinically meaningful tumor classification schemes have long been sought. Some malignant epithelial neoplasms, such as those in the thyroid and endometrium, exhibit more than one pattern of differentiation, each associated with distinctive clinical features and treatments. In other tissues, all carcinomas, regardless of morphological type, are treated as though they represent a single disease. To better understand the biological and clinical features seen in the four major histological types of ovarian carcinoma (OvCa), we analyzed gene expression in 113 ovarian epithelial tumors using oligonucleotide microarrays. Global views of the variation in gene expression were obtained using PCA. These analyses show that mucinous and clear cell OvCas can be readily distinguished from serous OvCas based on their gene expression profiles, regardless of tumor stage and grade. In contrast, endometrioid adenocarcinomas show significant overlap with other histological types. Although high-stage/grade tumors are generally separable from low-stage/grade tumors, clear cell OvCa has a molecular signature that distinguishes it from other poor-prognosis OvCas. Indeed, 73 genes, expressed 2- to 29-fold higher in clear cell OvCas compared with each of the other OvCa types, were identified. Collectively, the data indicate that gene expression patterns in ovarian adenocarcinomas reflect both morphological features and biological behavior. Moreover, these studies provide a foundation for the development of new type-specific diagnostic strategies and treatments for ovarian cancer. cho-00156 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Material Types: synthetic_RNA, organism_part, whole_organism, total_RNA Disease States: Ovary cancer
Project description:Biologically and clinically meaningful tumor classification schemes have long been sought. Some malignant epithelial neoplasms, such as those in the thyroid and endometrium, exhibit more than one pattern of differentiation, each associated with distinctive clinical features and treatments. In other tissues, all carcinomas, regardless of morphological type, are treated as though they represent a single disease. To better understand the biological and clinical features seen in the four major histological types of ovarian carcinoma (OvCa), we analyzed gene expression in 113 ovarian epithelial tumors using oligonucleotide microarrays. Global views of the variation in gene expression were obtained using PCA. These analyses show that mucinous and clear cell OvCas can be readily distinguished from serous OvCas based on their gene expression profiles, regardless of tumor stage and grade. In contrast, endometrioid adenocarcinomas show significant overlap with other histological types. Although high-stage/grade tumors are generally separable from low-stage/grade tumors, clear cell OvCa has a molecular signature that distinguishes it from other poor-prognosis OvCas. Indeed, 73 genes, expressed 2- to 29-fold higher in clear cell OvCas compared with each of the other OvCa types, were identified. Collectively, the data indicate that gene expression patterns in ovarian adenocarcinomas reflect both morphological features and biological behavior. Moreover, these studies provide a foundation for the development of new type-specific diagnostic strategies and treatments for ovarian cancer.
Project description:Transcriptional profiling of Homo sapiens inflammatory skin diseases (whole skin biospies): Psoriasis (Pso), vs Atopic Dermatitis (AD) vs Lichen planus (Li), vs Contact Eczema (KE), vs Healthy control (KO) In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation. In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation.