Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1208547 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The JGOG3025 study was conducted by the Japanese Gynecologic Oncology Group (JGOG) on 710 patients with epithelial ovarian cancer (NCT03159572). In the JGOG3025-TR2 study, fresh frozen tumor tissues from 274 and 15 cases diagnosed as stage II or higher high-grade serous carcinoma (HGSC) or high-grade endometrioid carcinoma (HGEC) in the central pathological review were submitted to SNP array, total RNA-sequencing, and DNA methylation array analyses.
2024-08-31 | GSE263437 | GEO
Project description:The JGOG3025 study was conducted by the Japanese Gynecologic Oncology Group (JGOG) on 710 patients with epithelial ovarian cancer (NCT03159572). In the JGOG3025-TR2 study, fresh frozen tumor tissues from 274 and 15 cases diagnosed as stage II or higher high-grade serous carcinoma (HGSC) or high-grade endometrioid carcinoma (HGEC) in the central pathological review were submitted to SNP array, total RNA-sequencing, and DNA methylation array analyses.
2024-08-31 | GSE263083 | GEO
Project description:The JGOG3025 study was conducted by the Japanese Gynecologic Oncology Group (JGOG) on 710 patients with epithelial ovarian cancer (NCT03159572). In the JGOG3025-TR2 study, fresh frozen tumor tissues from 274 and 15 cases diagnosed as stage II or higher high-grade serous carcinoma (HGSC) or high-grade endometrioid carcinoma (HGEC) in the central pathological review were submitted to SNP array, total RNA-sequencing, and DNA methylation array analyses.
2024-08-31 | GSE263434 | GEO
Project description:Improving Risk Assessment for Metastatic Disease in Endometrioid Endometrial Cancer Patients Using Molecular and Clinical Features: an NRG Oncology / Gynecologic Oncology Group Study
| PRJNA493185 | ENA
Project description:INTRODUCTION. Liquid biopsies are a minimally invasive collection of a patient body fluid sample. In oncology, they offer several advantages compared to traditional tissue biopsies. However, potential of this method in endometrial cancer (EC) remains poorly explored. We studied the utility of tumor educated platelets (TEPs) and circulating tumor DNA (ctDNA) for preoperative EC diagnosis, including histology determination. MATERIALS AND METHODS. TEPs from 297 subjects (53 EC patients, 40 patients with benign gynecologic conditions and 204 healthy women) were RNA-sequenced. DNA sequencing was performed in 519 primary tumor tissue samples and in16 plasma samples. Artificial intelligence was applied to sample classification. RESULTS. Platelet-dedicated classifier yielded AUC of 93.1% in test set when discriminating between healthy subjects and cancer patients. However, the discrimination between endometrial cancer and benign gynecologic conditions was relatively low, with AUC of 60.7%. ctDNA-dedicated classifier discriminated primary tumor tissue samples with AUC of 91.4% and ctDNA blood samples with AUC of 87.5%. CONCLUSIONS Liquid biopsies show potential in EC diagnosis. Both TEPs and ctDNA profiles coupled with artificial intelligence constitute a source of useful information. Further work, involving more cases, is warranted.
2021-12-01 | GSE184904 | GEO
Project description:This ordinary differential equation model simulating the mechanisms that govern cancer-immune dynamics and their role in tumor responses to immunotherapy is described by the publication:
Creemers JHA, Lesterhuis WJ, Mehra N, et al.
"A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery."
Journal for ImmunoTherapy of Cancer 2021;9:e002032.
doi:10.1136/jitc-2020-002032
Comment:
Simulation parameters in supplementary table 1 mismatch with figure 1 in manuscript. Therefore, to clarify, the following parameter values were used:
Reproduction of Fig. 1(C), xi = 0.0005
Reproduction of Fig. 1(D), xi = 0.00025
Abstract:
Background: Predicting treatment response or survival of cancer patients remains challenging in immuno-oncology. Efforts to overcome these challenges focus, among others, on the discovery of new biomarkers. Despite advances in cellular and molecular approaches, only a limited number of candidate biomarkers eventually enter clinical practice.
Methods: A computational modeling approach based on ordinary differential equations was used to simulate the fundamental mechanisms that dictate tumor-immune dynamics and to investigate its implications on responses to immune checkpoint inhibition (ICI) and patient survival. Using in silico biomarker discovery trials, we revealed fundamental principles that explain the diverging success rates of biomarker discovery programs.
Results: Our model shows that a tipping point—a sharp state transition between immune control and immune evasion—induces a strongly non-linear relationship between patient survival and both immunological and tumor-related parameters. In patients close to the tipping point, ICI therapy may lead to long-lasting survival benefits, whereas patients far from the tipping point may fail to benefit from these potent treatments.
Conclusion: These findings have two important implications for clinical oncology. First, the apparent conundrum that ICI induces substantial benefits in some patients yet completely fails in others could be, to a large extent, explained by the presence of a tipping point. Second, predictive biomarkers for immunotherapy should ideally combine both immunological and tumor-related markers, as a patient’s distance from the tipping point can typically not be reliably determined from solely one of these. The notion of a tipping point in cancer-immune dynamics helps to devise more accurate strategies to select appropriate treatments for patients with cancer.
2024-09-02 | BIOMD0000001022 | BioModels
Project description:Vaginal Microbiota in Gynecologic Cancer Patients Pre- and Post-Radiation Therapy
| PRJNA446033 | ENA