7351 results for "canc*"

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• Tumor Profiler AML Study

  Multi-omics data generated from 22 samples from the Tumor Profiler AML cohort

  Study EGAS50000000577

• TransNEO neoadjuvant breast cancer study

  Study EGAS00001004582

• Neoadjuvant nivolumab or nivolumab plus ipilimumab in early-stage triple negative breast cancer: phase 2 adaptive BELLINI trial. RNA-Seq

  The adaptive BELLINI trial explored whether short combination ICI induces immune activation (primary endpoint: two-fold increase in CD8+ T cells or IFNG), providing rationale for neoadjuvant ICI without chemotherapy. In window of opportunity cohorts A (4 weeks anti-PD1) and B (4 weeks anti-PD1 + anti-CTLA4), we observed immune activation in 53% (8/15) and 60% (9/15) of patients, respectively. High tumor-infiltrating lymphocytes (TILs) correlated with response. Based on these data, we opened cohort C for patients with high TILs (≥50%) who received 6 weeks neoadjuvant anti-PD1 + anti-CTLA4 followed by surgery (primary endpoint: pathological complete response, pCR). 53% (8/15) of patients had major pathological response (< 10% viable tumor) at resection, with 33% (5/15) having pCR. All cohorts met Simon’s two-stage threshold for expansion to stage II. In conclusion, neoadjuvant immunotherapy without chemotherapy demonstrates potential efficacy and warrants further investigation in patients with early TNBC.

  Study EGAS50000000567

• Single-cell targeted DNA-sequencing and protein sequencing

  We performed single-cell targeted DNA sequencing (MissionBio) on 13 high hyperdiploid B-ALL patients at diagnosis to study the genetic heterogeneity. For a number of patients single-cell surface protein antibody sequencing was added (DAB-seq) to better characterize the different cell types. Furthermore, additional samples during treatment were collected and analysed for some patients. In this way we want to study the clonal heterogeneity of these B-ALL samples, based both on mutations and CNVs, and identify resistant clones that could be targeted after relapse.

  Study EGAS50000000580

• Lactate metabolism in cancer stem cell fate regulation

  Tumors arise as a result of uncontrolled cell proliferation driven by mutations in the signaling pathways that regulate the balance between cell division and differentiation. Despite of that, in the tumor, cancer stem cells seem to retain their capability to differentiate, which can lead to differential chemotherapy response. We previously showed that intestinal stem cells and differentiated cells display specific metabolic features and that they interact through metabolites. Moreover, we found that altering mitochondrial metabolism is sufficient to lead and define stem cell differentiation. In cancer, cellular metabolism is highly derailed. However, how metabolic changes in the cancer cell contribute to cell fate decisions remains unknown. Recently, the crosstalk between metabolism and epigenetics has emerged as one of the players in tumor development. Here we aim to address the impact of the altered metabolism of cancer cells on their epigenome as a regulatory axis of cell identity and fate. We use human-derived tumor organoids where we introduce genetic encoded fluorescent-based reporters to visualize cell identity and metabolism at single cell level. We combine 4D live imaging with a recently developed machine learning method to re-construct cell-lineages, trace stem cell state and metabolic changes during tumor organoid development. We find that, mimicking the tumor metabolic microenvironment (Warburg effect-driven low-glucose high-lactate) leads to changes cellular metabolism and histone acetylation. Strikingly, these alterations provoke profound changes in tumor development by increasing the population of cancer stem cells and their proliferation and differentiation dynamics.

  Study EGAS50000000063

• Selective Elimination of Immunosuppressive T cells in Patients with Multiple Myeloma

  Study EGAS00001004915

• Characterization of copy number quiet oral cancer

  Copy number quiet head and neck squamous cell carcinoma are a distinct subset with relatively good prognosis. Previous work has indicated this subset is most commonly found in the oral cavity and is highly enriched for HRAS and CASP8 mutations. TP53 mutations are much less common than in CNA-quiet oral cancers. In this study we corroborate the validity of CNA-quiet tumors as a distinct subset in a large OSCC cohort and further chart clinical, genomic, and immunological characteristics of this subset.

  Study EGAS50000000558

• Cancer cell and tumor microenvironment biomarkers associated with disease-free survival with adjuvant nivolumab in the phase 3 CheckMate 274 trial

  In the CheckMate 274 trial, adjuvant nivolumab versus placebo demonstrated an improvement in the primary endpoint of disease-free survival (DFS) in patients with high-risk muscle-invasive urothelial carcinoma after radical resection. An extensive analysis of tumor biomarkers, including their associations with DFS, was performed. Analysis of genome-wide differential gene expression and known gene signatures found that immune-related genes and pathways, in particular an IFNγ signature, were predictive of DFS in nivolumab-treated patients. Predictive and prognostic associations, respectively, were found for tumor-infiltrating CD4 and CD8 T cells. Analysis of a composite predictive model suggested that CD4 gene expression and tumor cell PD-L1 expression had the greatest contributions to predicting outcomes in nivolumab-treated patients. These results reinforce recent studies establishing the importance of biomarkers of adaptive immunity, and in particular CD4 T cells, in influencing response to PD-1/PD-L1 blockade and establish the potential predictive rather than solely prognostic nature of such findings.

  Study EGAS50000000560

• Ex vivo modeling of precision immuno-oncology responses in lung cancer

  Single-cell RNA-sequencing (scRNA-seq) data from paired lung cancer organoids and immune cells. The experiment was performed using the Single Cell 5' solution of 10X Genomics. The dataset includes 15 samples from 4 multiplexed experiments. The multiplexing was performed using the Feature Barcoding technology of 10X Genomics.

  Study EGAS50000000593

• Targeted gene panel sequencing of leiomyosarcoma

  We conducted MSK-IMPACT sequencing of leiomyosarcoma.

  Study EGAS50000000595