Publications by authors named "Sebastian Scheinost"
Article Synopsis
- Response to anticancer drugs varies among patients due to underlying biological differences, highlighting the need for identifying specific factors and biomarkers that predict drug efficacy.
- High-throughput screening platforms can help map cellular responses to anticancer agents, allowing researchers to investigate the mechanisms behind different reactions to these drugs.
- A proposed method uses ATP measurements to assess cell viability after drug treatment, facilitating the study of drug responses in both cell lines and primary cell cultures.
Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68).
View Article and Find Full Text PDFThe tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited and systematic analyses are lacking. Using chronic lymphocytic leukaemia (CLL) as a model disease, we investigated the influence of 17 microenvironmental stimuli on 12 drugs in 192 genetically characterised patient samples. Based on microenvironmental response, we identified four subgroups with distinct clinical outcomes beyond known prognostic markers.
View Article and Find Full Text PDFChronic Lymphocytic Leukemia (CLL) has a complex pattern of driver mutations and much of its clinical diversity remains unexplained. We devised a method for simultaneous subgroup discovery across multiple data types and applied it to genomic, transcriptomic, DNA methylation and ex-vivo drug response data from 217 Chronic Lymphocytic Leukemia (CLL) cases. We uncovered a biological axis of heterogeneity strongly associated with clinical behavior and orthogonal to the known biomarkers.
View Article and Find Full Text PDFArticle Synopsis
- The study investigates the functional consequences of mutations on cancer characteristics in chronic lymphocytic leukemia (CLL), with a focus on the limited understanding of its proteome.
- Researchers analyzed the proteome of CLL patient samples using advanced mass spectrometry, revealing that specific genetic variations, such as trisomy 12 and IGHV status, significantly influence protein expression in CLL.
- The findings suggest that protein expression data can provide crucial insights into tumor biology, particularly highlighting the role of B-cell receptor signaling and the potential for targeted drug responses in CLL patients.
Article Synopsis
- * Key chromosomal changes included deletions and trisomies, with a high rate of mutations in several genes like TP53 and MYD88; researchers identified three risk groups based on these genetic alterations.
- * The study suggests that using specific drug combinations targeting MYC may enhance treatment effectiveness, and that cytogenetic analysis can aid in diagnosing and predicting outcomes in B-PLL.
Oncogenic MYC activation promotes proliferation in Burkitt lymphoma, but also induces cell-cycle arrest and apoptosis mediated by p53, a tumor suppressor that is mutated in 40% of Burkitt lymphoma cases. To identify molecular dependencies in Burkitt lymphoma, we performed RNAi-based, loss-of-function screening in eight Burkitt lymphoma cell lines and integrated non-Burkitt lymphoma RNAi screens and genetic data. We identified 76 genes essential to Burkitt lymphoma, including genes associated with hematopoietic cell differentiation () or B-cell development and activation () and found a number of context-specific dependencies including oncogene addiction in cell lines with / or mutation.
View Article and Find Full Text PDFArticle Synopsis
- - The effectiveness of anticancer treatments varies among different patient subsets, and understanding the reasons for this variability is crucial for improving drug treatments.
- - High-throughput screening methods using cell lines and primary cell cultures can help identify biomarkers related to drug response and reveal mechanisms behind differing responses.
- - This text presents a straightforward method for measuring cell viability after drug exposure using ATP levels, which can help analyze how both cell lines and primary cells respond to anticancer agents.