Ontology highlight
ABSTRACT:
PROVIDER: PRJEB53061 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| ERR9792290.fastq.gz | Fastqsanger.gz | |||
| ERR9792300.fastq.gz | Fastqsanger.gz | |||
| ERR9792310.fastq.gz | Fastqsanger.gz | |||
| ERR9792291.fastq.gz | Fastqsanger.gz |
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Project description:In metastatic cancer, the degree of heterogeneity of the tumor-immune microenvironment and its molecular underpinnings remain largely unstudied. To characterize the tumor-immune interface at baseline and during neoadjuvant chemotherapy in high-grade serous ovarian cancer (HGSOC), we performed immunogenomics analysis of treatment-naive and paired pre/post-chemotherapy treated samples. In treatment-naive HGSOC, we find that immune cell-excluded and inflammatory microenvironments co-exist within the same individuals and within the same tumor sites, indicating ubiquitous variability in immune cell infiltration. Analysis of tumor microenvironment cell composition, DNA copy number, mutations and gene expression showed that immune cell exclusion was associated with amplification of Myc target genes and increased expression of canonical Wnt signaling in treatment-naive HGSOC. Following neoadjuvant chemotherapy, increased natural killer cell infiltration and oligoclonal expansion of T cells were detected. We demonstrate that the tumor-immune microenvironment of advanced HGSOC is intrinsically heterogeneous and that chemotherapy induces local immune activation, suggesting that chemotherapy can potentiate the immunogenicity of immune-excluded HGSOC tumors. The goal of this particular experiment was quantify RNA expression using microarray technology, and then evaluate differences in the trasncirptomic landscape of treatment naïve metastatic high grade serous ovarian cancer.
2020-03-14 | GSE146964 | GEO
Project description:In metastatic cancer, the degree of heterogeneity of the tumor-immune microenvironment and its molecular underpinnings remain largely unstudied. To characterize the tumor-immune interface at baseline and during neoadjuvant chemotherapy in high-grade serous ovarian cancer (HGSOC), we performed immunogenomics analysis of treatment-naive and paired pre/post-chemotherapy treated samples. In treatment-naive HGSOC, we find that immune cell-excluded and inflammatory microenvironments co-exist within the same individuals and within the same tumor sites, indicating ubiquitous variability in immune cell infiltration. Analysis of tumor microenvironment cell composition, DNA copy number, mutations and gene expression showed that immune cell exclusion was associated with amplification of Myc target genes and increased expression of canonical Wnt signaling in treatment-naive HGSOC. Following neoadjuvant chemotherapy, increased natural killer cell infiltration and oligoclonal expansion of T cells were detected. We demonstrate that the tumor-immune microenvironment of advanced HGSOC is intrinsically heterogeneous and that chemotherapy induces local immune activation, suggesting that chemotherapy can potentiate the immunogenicity of immune-excluded HGSOC tumors. The goal of this particular experiment was quantify RNA expression using microarray technology, and then evaluate differences in the trasncirptomic landscape of treatment naïve metastatic high grade serous ovarian cancer.
2020-03-14 | GSE146963 | GEO
Project description:The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types. Expression data accompaniment to CSHL ROMA and MOMA3 human ovarian analysis. Correlation of expression to Methylation and Copy Number Variation in ovarian cancer.
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Project description:MicroRNAs (miRNAs) have been recently detected in the circulation of cancer patients, where they are associated with clinical parameters. Discovery profiling of circulating small RNAs has not been previously reported in breast cancer (BC), and was carried out in this study to identify blood-based small RNA markers of BC clinical outcome. The pre-treatment sera of 42 stage II–III locally advanced and inflammatory BC patients who received neoadjuvant chemotherapy (NCT) followed by surgical tumor resection were analyzed for marker identification by deep sequencing all circulating small RNAs.
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Project description:The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types. Expression data accompaniment to CSHL ROMA and MOMA3 human ovarian analysis.
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Project description:The high rate of recurrence and chemoresistance necessitates in ovarian cancer warrants further research into tumor markers characterizing the resistant population. The proportion of drug-resistant tissue cells in residual lesions after neoadjuvant chemotherapy increases, and drug-resistant markers are enriched. However, there is a lack of comprehensive understanding of tumor marker predoninance pre- and post- neoadjuvant chemotherapy. Here we performed quantitative proteomic analysis of TMT in three patients with matched pretreatment biopsies and post-NACT ovarian cancer tissues. This study highlights a dominant molecular subpopulation that persists in the ovary after neoadjuvant chemotherapy exposure in order to elucidate how it is involved in mediating chemotherapy response, which will lay the foundation for the development.
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Project description:The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types.
2011-10-17 | GSE27940 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE10128: Genomic copy number alterations as predictive markers of systemic recurrence in breast cancer GSE10129: Genomic copy number alterations as predictive markers of neoadjuvant chemotherapy response in breast cancer Refer to individual Series
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Project description:There is a great need of non-invasive tools that inform of an early molecular response to cancer therapeutic treatment. Here, we have tested the hypothesis that proteolytically resistant proteins could be candidate circulating tumor biomarkers for cancer therapy. Proteins resistant to proteolysis are drastically under-sampled by current proteomic workflows. These proteins could be reliable sensors for the response to therapy since they are likely to stay longer in circulation. We selected Manganese superoxide dismutase (SOD2), a mitochondrial redox enzyme, from a screening of proteolytic resistant proteins in breast cancer (BC). First, we confirmed the robustness of SOD2 and determined that its proteolytic resistance is mediated by its quaternary protein structure. We also proved that the release of SOD2 upon chemotherapy treatment correlates with cell death in BC cells. Then, after confirming that SOD2 is very stable in human serum, we sought to measure its circulating levels in a cohort of BC patients undergoing neoadjuvant therapy. The results showed that circulating levels of SOD2 increased when patients respond to the treatment according to the tumor shrinkage during neoadjuvant chemotherapy. Therefore, the measurement of SOD2 levels in plasma could improve the non-invasive monitoring of the therapeutic treatment in breast cancer patients. The identification of circulating biomarkers linked to the tumor cell death induced by treatment could be a useful for monitoring the action of the large number of cancer drugs currently used in the clinic. We envision that our approach could help uncover candidate tumor biomarkers to measure a tumor’s response to cancer therapy in real time by sampling the tumor throughout the course of treatment.
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Project description:Changes in cellular lipid metabolism are a common feature in most solid tumors, which occur already in early stages of the tumor progression. However, it remains unclear if the tumor-specific lipid changes can be detected at the level of systemic lipid metabolism. The objective of this study was to perform comprehensive analysis of lipids in breast cancer patient serum samples. Lipidomic profiling using an established analytical platform was performed in two cohorts of breast cancer patients receiving neoadjuvant chemotherapy. The analyses were performed for 142 patients before and after neoadjuvant chemotherapy, and the results before chemotherapy were validated in an independent cohort of 194 patients. The analyses revealed that in general the tumor characteristics are not reflected in the serum samples. However, there was an association of specific triacylglycerols (TGs) in patients' response to chemotherapy. These TGs containing mainly oleic acid (C18:1) were found in lower levels in those patients showing pathologic complete response before receiving chemotherapy. Some of these TGs were also associated with estrogen receptor status and overall or disease-free survival of the patients. The results suggest that the altered serum levels of oleic acid in breast cancer patients are associated with their response to chemotherapy.
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