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Biology subjects

Herold, N.

Publications and source records attributed to Herold, N..

2 recordsLinked to original sources

Principles of subclonal gene dosage across human cancer

Intratumor heterogeneity drives disease progression, but even though subclonal copy number variation (CNV) is a major contributor to this heterogeneity1, its impact on cell phenotype is not fully understood. Here, by applying high-quality joint whole genome sequencing and mRNA profiling in single cells (DNTR-seq2) to solid tumors and leukemias from 57 patients, we have analyzed the in vivo transcriptional effect of subclonal CNVs within a tumor. We found that gene dosage is generally additive in low and moderate copy states, but that cancer-type-specific compensation is common, and core promoter elements are associated with reduced additivity. We find that different classes of subclonal CNV impose varying degrees of transcriptional constraints on a cell, with highly amplified megabase-size regions associated with a strong effect both in cis and trans, while arm level CNVs generally exert a milder effect. We also describe a previously unappreciated class of tumors with transient clonality, where every cell is genetically highly distinct. We find that transient clonality is common in ovarian cancer and soft tissue sarcoma, that it is preceded by a whole genome duplication event, and that gene dosage in these tumors affects transcript abundance to a similar degree as in cancer with stable subclones.

cancer biology↗

Functionalist Oncology to Model the Contextuality of Dynamics and Treatment in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a disease with a high degree of intra- and interpatient heterogeneity. Current treatments almost uniformly employ the standardized 7+3 regimen, which is based on cytarabine combined with an anthracycline, with long-term survival rates below 30%. Our work specifically focuses on the cytarabine component of this regimen. Functionalist oncology utilizes edge-weighted digraphs as a representational tool to model the mathematical functional interdependencies of disease factors. This methodology enables a conceptual and mechanistic analysis of key factors influencing therapeutic success, providing a framework that can be parameterized to explore patient-specific treatment responses when suitable data are available. It incorporates the oligoclonal nature of AML to perform, in principle, comprehensive cost-benefit analyses regarding the addition of individual drugs to existing treatment regimens and the number and type of chemotherapy courses to be given. Extrapolating from experimental data, we investigate the therapeutic potential and risks of SAMHD1 inhibitors in AML treatment as a proof-of-concept. We also provide a web-based interactive application to visualize hypothetical AML treatment scenarios, which can be combined with ex vivo single-cell phenotypic (gene expression), genotypic (somatic mutations), and functional (drug responses) analyses. Functionalist oncology can thus be used to generate testable hypotheses that might contribute to improving oncological decision-making, e.g., by identifying the optimal number, nature and sequence of chemotherapy blocks, including both existing AML-directed blocks and additional drugs, such as SAMHD1 inhibitors.

systems biology↗