Cd542519-c8f2-48e8-aa35-cd6e7e88c671 - samples
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ABSTRACT:
PROVIDER: EGAD00001006922 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:To characterize transcriptional patterns of chemotherapy resistance in HGSOC, we prospectively collected tissue samples before and after chemotherapy from 11 patients and analyzed their transcriptomic profiles at single-cell resolution.
| EGAS00001005010 | EGA
Project description:We characterized transcriptional patterns of chemotherapy resistance in high-grade serous ovarian cancer (HGSOC) using patient-derived prospective tissue sample pairs before and after treatment at single-cell resolution. Our cohort consists of scRNA-seq data from treatment-naïve and post-neoadjuvant chemotherapy (post-NACT) pairs from 11 homogeneously treated HGSOC patients. After quality control, we obtained 51,786 cells, including 8,806 malignant epithelial (tumor), 8,045 stromal and 34,935 immune cells. Our unbiased analysis reveals how chemotherapy modulates cancer cell states by both subclonal selection and microenvironment boosted transcriptional induction across the homogeneously treated sample cohort. Our results define a cell state that allows biomarker-based prediction and targeting of chemoresistance.
2021-12-24 | GSE165897 | GEO
Project description:Ribba2012 - Low-grade gliomas, tumour growth inhibition model
Using longitudinal mean tumour diameter (MTD) data, this model describe the size evolution of low-grade glioma (LGG) in patients treated with chemotherapy or radiotherapy.
This model is described in the article:
A tumour growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy
Ribba B, Kaloshi G, Peyre M, Ricard D, Calvez V, Tod M, Cajavec-Bernard B, Idbaih A, Psimaras D, Dainese L, Pallud J, Cartalat-Carel S, Delattre JY, Honnorat J, Grenier E, Ducray F.
Clin. Cancer Res. 2012 Sep; 18(18): 5071-5080
Abstract:
PURPOSE: To develop a tumor growth inhibition model for adult diffuse low-grade gliomas (LGG) able to describe tumor size evolution in patients treated with chemotherapy or radiotherapy.
EXPERIMENTAL DESIGN: Using longitudinal mean tumor diameter (MTD) data from 21 patients treated with first-line procarbazine, 1-(2-chloroethyl)-3-cyclohexyl-l-nitrosourea, and vincristine (PCV) chemotherapy, we formulated a model consisting of a system of differential equations, incorporating tumor-specific and treatment-related parameters that reflect the response of proliferative and quiescent tumor tissue to treatment. The model was then applied to the analysis of longitudinal tumor size data in 24 patients treated with first-line temozolomide (TMZ) chemotherapy and in 25 patients treated with first-line radiotherapy.
RESULTS: The model successfully described the MTD dynamics of LGG before, during, and after PCV chemotherapy. Using the same model structure, we were also able to successfully describe the MTD dynamics in LGG patients treated with TMZ chemotherapy or radiotherapy. Tumor-specific parameters were found to be consistent across the three treatment modalities. The model is robust to sensitivity analysis, and preliminary results suggest that it can predict treatment response on the basis of pretreatment tumor size data.
CONCLUSIONS: Using MTD data, we propose a tumor growth inhibition model able to describe LGG tumor size evolution in patients treated with chemotherapy or radiotherapy. In the future, this model might be used to predict treatment efficacy in LGG patients and could constitute a rational tool to conceive more effective chemotherapy schedules.
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2024-09-02 | BIOMD0000000521 | BioModels
Project description:Background: High-grade serous ovarian cancer (HGSOC) is the most lethal gynaecological malignancy, exhibiting marked heterogeneity that complicates treatment. The implications of intratumoral androgen metabolism and signalling, particularly involving 11-oxygenated androgens, in HGSOC remains poorly understood. Methods: We analysed expression of key androgen-metabolizing enzymes and androgen receptor (AR) in relation to tumor site, chemotherapy response, and survival using two public HGSOC cohorts. Quantitative gene expression and steroid metabolism assays upon incubation with classic and 11-oxyandrogen precursors were performed in six HGSOC cell lines and one normal ovarian epithelial line. Untargeted transcriptomic and metabolomic profiling were performed to assess cellular responses to potent classic and 11-oxygenated androgens in the AR-positive OVSAHO cell line. Results: Differential expression of steroid-metabolizing enzymes and AR were observed between primary and metastatic tumors and chemo-sensitive and chemo-resistant tumors. Higher intra-tumoral expression of HSD11B2, HSD17B2, and AR correlated with improved survival, whereas elevated PAPSS1/2 and HSD17B4 predicted poorer outcomes. In vitro, classic androgen precursors showed limited conversion to bioactive androgens and did not generate 11-oxyandrogens. In contrast, 11-oxyandrogen precursors were efficiently converted to the potent AR agonist 11KT in chemo-sensitive HGSOC cell lines, but not in chemo-refractory or control lines. Potent classic and 11-oxyandrogens induced stress-adaptive and proliferative transcriptional responses and reduced intracellular amino acid content. These changes were associated with a trend toward reduced cell proliferation. Conclusions: Our findings offer mechanistic insight into local androgen and 11-oxyandrogen metabolism and signalling in HGSOC and reveal steroid-induced cellular vulnerabilities that may synergize with chemotherapy or molecularly targeted therapies. These results further support the therapeutic potential of modulating steroid pathways in HGSOC.
2025-07-17 | GSE302881 | GEO
Project description:High-grade serous ovarian cancer (HGSOC) exhibits significant genomic heterogeneity within a patient at presentation. Recent work has suggested that this heterogeneity is linked to the development of resistance and disease progression in that chemotherapy selects for minor resistant subclones embodied in presentation disease leading to short progression-free survival and resistant relapse. Cell line models support this by showing that relapse is not an immediate descendant of presentation disease, but so far no immediate clinical evidence has been provided that convincingly demonstrates the origin of relapse. It is further still unclear what evolutionary processes shape the mutational landscape of HGSOC in vivo and to what extent the degree of genomic heterogeneity impacts a patient's clinical outcome. We address these questions by inferring evolutionary trees of metastatic disease from structural variations between 138 cancer samples obtained from 17 patients undergoing neoadjuvant chemotherapy for HGSOC. Using novel phylogenetic methods, we quantify genomic changes in the course of chemotherapy and the degree of clonal expansion and show that these indices determine patient outcome with high accuracy. We demonstrate that relapse is indeed a minor subclone of presentation disease by verifying that the focal NF1 deletion of a relapse case was already present at biopsy. By leveraging the information contained in the evolutionary trees, we unveil the etiology of genetic heterogeneity and the tumorigenic potential of HGSOC cell populations. This is the first comprehensive study showing the origin, strength and effect of genetic heterogeneity in HGSOC in a clinical setting. In addition to its immediate clinical significance, it strengthens previous statements that single sample biopsies are seemingly insufficient to predict disease progression and stresses the importance of establishing multiple sampling as a routine approach in the clinic. Clinical data and tissue samples were collected on the prospective CTCR-OV03 and CTCR-OV04 clinical studies designed to identify biomarkers of heterogeneity.
2014-10-01 | E-GEOD-40546 | biostudies-arrayexpress
Project description:Prostate cancers with clinical features of small cell prostate carcinomas (SCPC) but diverse morphologies share chemotherapy responsiveness with SCPC. We prospectively collected tumor tissues from clinically defined, morphologically diverse, aggressive variant prostate cancers (AVPCa) to determine if they also share molecular features with SCPC
2015-10-10 | GSE73902 | 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: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:We conducted single-cell RNA sequencing (scRNAseq) of tumor-infiltrating immune cells in high-grade serous ovarian cancer (HGSOC) omental biopsies to identify potential targets that could enhance response to neo-adjuvant chemotherapy (NACT). Analysis of 64,097 cells identified NACT-induced overexpression of stabilin-1 (clever-1) on macrophages and FOXP3 in Tregs and these were validated at the protein level. STAB1 inhibition in vitro induced anti-tumor macrophages. FOXP3 anti-sense oligonucleotide (FOXP3-ASO), repolarised Tregs to an effector T cell phenotype. ScRNAseq on 69,781 cells from an HGSOC syngeneic mouse model recapitulated the patients’ data. Combining chemotherapy with anti-stabilin1 antibody and/or Foxp3-ASO significantly increased survival of mice with established peritoneal disease in two HGSOC syngeneic models and progression-free survival in a third model. Long-term survivors (300 days+) were resistant to tumor rechallenge. Anti-stabilin1 antibody enriched the tumors with CXCL9+ macrophages and Foxp3-ASO increased TBET cell infiltration. Our results suggest targeting these molecules may improve chemotherapy response in patients.
2024-10-11 | GSE224392 | GEO
Project description:We conducted single-cell RNA sequencing (scRNAseq) of tumor-infiltrating immune cells in high-grade serous ovarian cancer (HGSOC) omental biopsies to identify potential targets that could enhance response to neo-adjuvant chemotherapy (NACT). Analysis of 64,097 cells identified NACT-induced overexpression of stabilin-1 (clever-1) on macrophages and FOXP3 in Tregs and these were validated at the protein level. STAB1 inhibition in vitro induced anti-tumor macrophages. FOXP3 anti-sense oligonucleotide (FOXP3-ASO), repolarised Tregs to an effector T cell phenotype. ScRNAseq on 69,781 cells from an HGSOC syngeneic mouse model recapitulated the patients’ data. Combining chemotherapy with anti-stabilin1 antibody and/or Foxp3-ASO significantly increased survival of mice with established peritoneal disease in two HGSOC syngeneic models and progression-free survival in a third model. Long-term survivors (300 days+) were resistant to tumor rechallenge. Anti-stabilin1 antibody enriched the tumors with CXCL9+ macrophages and Foxp3-ASO increased TBET cell infiltration. Our results suggest targeting these molecules may improve chemotherapy response in patients.
2024-10-11 | GSE224389 | GEO