Active clinical trials for "Neoplasms"

Acute Core Binding Factor leukemias represent a specific category of acute myeloid leukemias that share prognostic factors, a specific mutational profile, and a favorable response to chemotherapy. Their management now follows the reference pattern from the French trial CBF-2006 closed to inclusions since November 2010. This includes intensive chemotherapy and intensification by allogeneic marrow transplant depending on the residual disease measured by RT qPCR . These leukemias have not been the subject of multicenter clinical trials since that date. The results of this treatment regimen need to be evaluated. Known prognostic factors such as signaling mutations, clonal interference or residual disease follow-up (MRD) will be analyzed and updated in this recent cohort. The interaction between residual disease and mutational profile will be evaluated on the prognosis. Treatment with gemtuzumab-ozogamycin and first-line allogeneic transplantation will be investigated, depending on prognostic factors including associated mutations and residual disease. The course and early treatment of molecular relapses will be analyzed. The treatment and prognosis of cytological relapses will be described with in particular the role of tyrosine kinase inhibitors and therapeutic intensification.

By uploading pre-operative patient information and patient CT data to RUS™, a virtual surgical environment with patient-specific relief prediction models can be provided. First, after uploading the CT and clinical information of a gastric cancer patient diagnosed with gastric cancer through an actual endoscopic biopsy and scheduled for robotic total gastrectomy, RUS™ will operate normally to check whether patient-specific surgical navigation is available before or during surgery. In particular, when using the patient-specific surgery simulation system provided by RUS™, the CT information provides a patient-specific 3D environment well, so it will be checked regarding whether the surgeon can use it before or during surgery without any particular problems. Using RUS™ software, navigation information is used before or during surgery, and among these, parts that can be quantitatively compared with actual measurements will be evaluated as a secondary research goal. After the surgery, the investigators plan to check the amount of bleeding, duration of hospitalization, and the rate of complications by performing robot gastrointestinal resection using the navigation system to ensure that there are no problems with patient safety.

4,972 patients who underwent surgery for primary CRC between January 2004 and December 2015 at Seoul National University Hospital were retrospectively reviewed. CA19-9 is a valuable prognostic and diagnostic marker for CRC when used adjunctively with CEA and can be a supplementary marker with CEA to improve sensitivity, especially with elevated preoperative CA19-9.

Currents strategies for cancer diagnosis consist of the extraction of a solid tissue from the affected area. This sample enables the study of specific biomarkers and the genetic nature of the tumor. However, the tissue extraction is risky and painful for the patient and in some cases is unavailable in inaccessible tumors. In addition, cancer is a dynamic disease and during the course of disease, cancers generally become more heterogeneous. As a result of this heterogeneity, the bulk tumour might include a diverse collection of cells harbouring distinct molecular signatures with differential levels of sensitivity to treatment. This heterogeneity might result in a non-uniform distribution of genetically distinct tumour-cell subpopulations across and within disease sites (spatial heterogeneity) or temporal variations in the molecular makeup of cancer cells (temporal heterogeneity). To overcome these drawbacks, new alternatives are rising up, such as liquid biopsy. A liquid biopsy is the analysis of biomarkers in a non-solid biological tissue, mainly blood, which has remarkable advantages over the traditional method; it has no risk, it is non-invasive and painless, it does not require surgery and reduces cost and diagnosis time. Of the various circulating biomarkers, circulating tumor cells (CTCs) have particularly opened new windows. Circulating tumor cells (CTCs) are released into the bloodstream from primary cancer, metastasis, and even from a disseminated tumor cell reservoir. CTCs may ideally replace tissue biopsies in the prediction and monitoring of therapeutic responses and tumor recurrence. CTCs can be used to guide therapeutic cancer management and serve as drug targets. There are a wide range of instruments and methods for capturing, enriching, and enumerating CTCs. However, none of them is considered optimal. To improve the purity of CTCs, the study consortium has developed a cutting-edge microfluidic device (LUTON) to reduce leukocytes contamination while preserving CTCs viability. The added-value of the study innovation has been validated on clinical cell lines. The aim of this study is now to determine the performance of the device using patients' blood samples. For this purpose, CTCs from non-small cell lung metastatic cancer patients will be isolated using ClearCellFX1 before injection into the LUTON workflow. Collected cells will then be either growth in vitro or in ovo and the added value of this extra step of purification determined.

To compare the prognosis of patients with hypertensive intracerebral hemorrhage treated by two different surgical methods, and to clarify the therapeutic effect of minimally invasive surgery, so as to find a better surgical method that can reduce surgical trauma and mortality and improve the prognosis of patients

Multi-omics and Clinical Data Analysis is potential to predict the prognosis of lung cancer patients.

To explore the feasibility, efficacy and safety of determining the treatment regimen based on genomic profiling in patients with locally advanced and advanced salivary gland cancer.

This study aims at evaluating the prevalence of trismus among maxillary cancer patients in the Egyptian population and the effect of radiotherapy on the occurrence of trismus.

The purpose of this study is to explore whether the imaging model based on RESOLVE-DWI sequence can exploiting the heterogeneity of nasopharyngeal carcinoma and indicate the prognosis, so as to provide intervention information for clinical decision-making. All patients were randomly divided into the training group and the validation group. Radiomics features extracted from T2-weighted, DWI, apparent diffusion coefficient (ADC), and contrast- enhanced T1-weighted were used to build a radiomics model. Patients'clinical variables were also obtained to build a clinical model. Model of training cohort was established using cross-validation for nasopharyngeal carcinoma prognosis by machine learning, including Logistics Regression, SVM, KNN, Decision Tree, Random Forest, XGBoost, and then, the model will be verified in the validation cohort. Area under the curve (AUC) of the Machine learning model was used as the main evaluation metric.

Oligodendrogliomas represent a distinct subgroup of adult gliomas characterized by specific molecular alterations (1p/19q codeletion, mutations of IDH, TERT promoter, CIC, FUBP1). These tumors account for 5 to 10% of adult gliomas and are of special relevance in the neuro-oncology field because of their frequent chemosensitivity (Louis et al. 2016). The genetics of oligodendrogliomas is relatively well characterized but the mechanisms of oncogenesis for these tumors are poorly understood. Although oligodendrogliomas prognosis is usually better than that of other adult glioma subtypes, it remains heterogeneous and there is no effective treatment at recurrence after radiotherapy and chemotherapy. Our recent work conducted within the INCa-funded national POLA network has related this clinical heterogeneity to inter-tumoral heterogeneity. Based on a transcriptomic analysis of a large series of oligodendroglial gliomas we identified 3 subgroups, the most aggressive group being characterized by aggressive clinical and molecular pattern. Recent studies, however, have shown a relatively low level of concordance between mRNA and protein expression, emphasizing the need to use proteomic-based approaches to better understand tumor biology. Taking advantage of the POLA cohort, we propose to expand our previous analysis by integrating a proteomic analysis of oligodendrogliomas. The aim of this project is to identify drivers of oligodendroglioma subgroups, among which potential druggable targets (i.e receptors, metabolism effectors). For this purpose, the proteomic profiles of 90 oligodendrogliomas will be generated and integrated with transcriptomic, genomic and methylation profiles in order to identify signaling pathways specifically associated with each subtype, especially with the most aggressive one. Associations will be explored between candidate signaling pathways expression and clinical outcomes (survival, progression-free survival, objective response). The relevance of the 2 most promising candidate signaling pathways will be assessed in vitro and in vivo using genetically relevant mouse and xenograft models. Our project will identify targetable oncogenic pathways associated with poor prognosis that could lead to new therapeutic strategies.