Gene expression profile of primary ovarian tumors and matched metastasis
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA924335 | ENA |
REPOSITORIES: ENA
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Project description:Ovarian cancer is the most frequent cause of cancer death in women and the leading cause of death related to gynecological cancer, accounting for 5% of estimated cancer deaths. Due to its asymptomatic nature at early stages, most ovarian cancers were diagnosed at an advanced stage, with distant metastasis in the abdominal cavity. Cancer metastasis is the primary cause of morbidity, and contributes to 95% of cancer-related deaths. Metastatic ovarian cancer is closely related with recurrence and drug resistance, rendering metastasis as the major challenge in the course of ovarian cancer treatment. Thorough understanding of ovarian cancer metastasis is believed to contribute to improve cancer cure rates, while it is still not well elucidated. One important aspect of ovarian cancer metastasis research is the identification of driver molecular. To identify proteins required for ovarian cancer metastasis, we carried out unbiased high-throughput screening by comparing the expression profile of ovarian cancer primary and metastasis tissues.
2023-01-20 | GSE222982 | GEO
Project description:Profiling gene expression changes in primary ovarian tumors compared to matched metastasis
| PRJNA564846 | ENA
Project description:Ovarian cancer is the deadliest gynecologic malignancy and the fifth leading cause for cancer related deaths among women in USA. Most patients have metastatic disease at the time of diagnosis and this causes the poor prognosis. For a comprehensive understanding of the gene expression changes accompanying ovarian cancer metastasis, we isolated RNA from 11 pairs of matched primary tumors and metastasis from OC patients and sequenced them. Library preparation and next generation RNA sequencing was carried out at the Center for Genomics and Bioinformatics core facility, Indiana University, Bloomington. The library preparation was done using TruSeq Stranded mRNA HT Sample Prep kit (Illumina cat#RS-122-2103) according to the manufacturer’s protocol and 8-neucleotide barcodes were added for multiplexing. The barcoded libraries were cleaned by bead cut with AMPure XP beads (Beckman Coulter, cat#A63882), verified using Qubit3 fluorometer (ThermoFisher Scientific) and 2200 TapeStation bioanalyzer (Agilent Technologies), and then pooled. The pool was sequenced on NextSeq 500 (Illumina) with NextSeq75 High Output v2 kit (Illumina cat#FC-404-2005).
2019-10-18 | GSE137237 | GEO
Project description:Our aim was to decipher the underlying molecular mechanism of synchronous ovarian metastasis of gastric cancer. We hereby conducted transcriptome sequencing of triple-matched samples including normal gastric mucosa, primary gastric cancer and ovarian metastatic tumors from 3 individual patients with the application of Illumina sequencing platform with 150-bp paired-end. Follow-up analyses not only identified differentially expressed genes between different sample sets (a threshold of fold change >2 and adjusted P value <0.05) but also uncovered significantly enriched signaling pathways of individual type. To sum up, our comparative transcriptomic analyses of triple-matched fresh samples stored in liquid nitrogen profiled the molecular expression and revealed functionally enriched pathways underlying the ovarian metastasis of gastric cancer.
2022-06-20 | GSE206329 | GEO
Project description:Metastasis formation is the major cause for cancer-related deaths and the underlying mechanisms remain poorly understood. In this study we describe spontaneous metastasis xenograft mouse models of human neuroblastoma used for unbiased identification of metastasis-related proteins by applying an infrared laser (IR) for sampling primary tumor and metastatic tissues, followed by mass spectrometric proteome analysis. IR aerosol samples were obtained from ovarian and liver metastases, which were indicated by bioluminescence imaging (BLI), and matched subcutaneous primary tumors. Corresponding histology proved the human origin of metastatic lesions. Ovarian metastases were commonly larger than liver metastases indicating differential outgrowth capacities. Among ~1,700 proteins identified at each of the three sites, 89 proteins were differentially regulated in ovarian metastases while 290 proteins were regulated in liver metastases. There was an overlap of 26 and 10 proteins up- and down-regulated at both metastatic sites, respectively, most of which were so far not related to metastasis such as LYPLA2, ACTL8, EIF4B, LGALS7, GFAP, and ELAVL4. Moreover, we established in vitro sublines from primary tumor and metastases and demonstrate differences in cellular protrusions, migratory/invasive potential and glycosylation. Summarized, this work identified several novel putative drivers of metastasis formation that are tempting candidates for future functional studies.
2018-09-24 | PXD009744 | Pride
Project description:HGSOC, the most aggressive form of OC, is characterized by insidious onset, rapid intraperitoneal spread and development of massive ascites. Peritoneal adhesion was considered as the first step of abdominal metastasis, underscoring that only tumor cells gain access to peritoneal adherence contribute to metastasis. Studies on ovarian cancer progression were mainly focused on the primary and metastatic tumor cells, while understanding of the ascitic tumor cells is limited. We hypothesized that uncovering the gene expression profiles of ascitic tumor cells from high grade serous ovarian cancer patients will allow us to understand more specifically their unique phenotype which mediates the peritoneal adhesion. In this study, gene expression profiling was completed for 15 magnetic sorted tumor cells samples from matched primary tumors, ascites and metastases of 5 high grade serous ovarian cancer patients. By comparing the expression data from ascitic tumor cells with primary and metastasis tumor cells, we identified a set of differential expressed genes in ovarian ascitic tumor cells advantageous for peritoneal adhesion and metastasis. Further study revealed that ascites microenvironment modulated the ascitic tumor cells phenotype and contributed to ovarian cancer dissemination through facilitating CAFs in formation of compact spheroids with ascitic tumor cells. We used microarrays to profile the expression of 15 matched tumor cells samples in order to identify molecular alteration between primary tumor cells, ascitic tumor cells and metastatic tumor cells in high grade serous ovarian cancer.
2017-12-19 | GSE73064 | GEO
Project description:Matched high-grade serous ovarian carcinoma samples collected from the ovary (ov), omental metastasis (om-met), and non-omental intraperitoneal metastasis (met) from 10 patients at the time of primary debulking surgery were analyzed for RNA expression by RNA sequencing.
2020-07-02 | GSE133296 | GEO
Project description:We used unsupervised hierarchical clustering to analyse expression in primary ovarian tumors and associated abdominal deposits. GeneGo pathway analysis of differentially expressed genes between primary tumors and deposits revealed 4 of the top 10 pathways related to cytoskeleton remodeling and cell adhesion. Primary ovarian tumours and matched abdominal deposits were selected for RNA extraction and hybridization on Affymetrix microarrays.
2012-06-14 | E-GEOD-38734 | biostudies-arrayexpress
Project description:Differ from the aggressive nature of HGSOC (high grade serous ovarian cancer), LGSOC (low grade serous ovarian cancer) is characterized by an early age of disease onset, slow growth pattern, and poor response to chemotherapy. To understand more specifically the underlying gene profiling discrepancy that contributes to their behavior distinction, we performed parallel gene expression profiling in 9 magnetic sorted tumor cells samples from matched primary tumors, ascites and metastases of 3 LGSOC patients as in HGSOC. By comparing the expression data among primary tumor cells, ascitic tumor cells and metastasis tumor cells, we identified a set of differential expressed genes along LGSOC progression. Further study revealed that the gene phenotype perturbance along LGSOC progression was quite different from that of HGSOC patients. We used microarrays to profile the expression of 9 matched tumor cells samples in order to identify molecular alteration between primary tumor cells, ascitic tumor cells and metastatic tumor cells in low grade serous ovarian cancer.
2017-12-19 | GSE73091 | GEO
Project description:Profiling gene expression changes in primary ovarian tumors compared to matched normal fallopian tubes
| PRJNA564844 | ENA