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6 results on '"Lischetti, Ulrike"'

4. Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing for personalized oncology

Author

Dondi, Arthur, Lischetti, Ulrike, Jacob, Francis, Singer, Franziska, Borgsmüller, Nico, Tumor Profiler Consortium, Heinzelmann-Schwarz, Viola, Beisel, Christian, and Beerenwinkel, Niko

Subjects
Full-length single-cell RNA sequencing, Long-read PacBio sequencing, Transcript concatenation, Isoforms, Mutations, Gene fusions, Ovarian cancer
Abstract

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Long-read single-cell RNA sequencing (scRNA-seq), capturing full-length transcripts, lacked the depth to provide this information so far. Here, we increased the PacBio sequencing depth to 12,000 reads per cell, leveraging multiple strategies, including artifact removal and transcript concatenation, and applied the technology to samples from three human ovarian cancer patients. Our approach captured 152,000 isoforms, of which over 52,000 were novel, detected cell type- and cell-specific isoform usage, and revealed differential isoform expression in tumor and mesothelial cells. Furthermore, we identified gene fusions, including a novel scDNA sequencing-validated IGF2BP2::TESPA1 fusion, which was misclassified as high TESPA1 expression in matched short-read data, and called somatic and germline mutations, confirming targeted NGS cancer gene panel results. With multiple new opportunities, especially for cancer biology, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine., bioRxiv

Published
2022
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5. gExcite: a start-to-end framework for single-cell gene expression, hashing, and antibody analysis.

Author

Grob, Linda, Bertolini, Anne, Carrara, Matteo, Lischetti, Ulrike, Tastanova, Aizhan, Beisel, Christian, Levesque, Mitchell P, Stekhoven, Daniel J, and Singer, Franziska

Subjects
GENE expression, GENE expression profiling, PROTEIN expression, IMMUNOGLOBULINS
Abstract

Summary Recently, CITE-seq emerged as a multimodal single-cell technology capturing gene expression and surface protein information from the same single cells, which allows unprecedented insights into disease mechanisms and heterogeneity, as well as immune cell profiling. Multiple single-cell profiling methods exist, but they are typically focused on either gene expression or antibody analysis, not their combination. Moreover, existing software suites are not easily scalable to a multitude of samples. To this end, we designed gExcite, a start-to-end workflow that provides both gene and antibody expression analysis, as well as hashing deconvolution. Embedded in the Snakemake workflow manager, gExcite facilitates reproducible and scalable analyses. We showcase the output of gExcite on a study of different dissociation protocols on PBMC samples. Availability and implementation gExcite is open source available on github at https://github.com/ETH-NEXUS/gExcite%5fpipeline. The software is distributed under the GNU General Public License 3 (GPL3). [ABSTRACT FROM AUTHOR]

Published
2023
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6. Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia.

Author

Wegmann R, Bonilla X, Casanova R, Chevrier S, Coelho R, Esposito C, Ficek-Pascual J, Goetze S, Gut G, Jacob F, Jacobs A, Kuipers J, Lischetti U, Mena J, Milani ES, Prummer M, Del Castillo JS, Singer F, Sivapatham S, Toussaint NC, Vilinovszki O, Wildschut MHE, Thavayogarajah T, Malani D, Aebersold R, Bacac M, Beerenwinkel N, Beisel C, Bodenmiller B, Heinzelmann-Schwarz V, Koelzer VH, Levesque MP, Moch H, Pelkmans L, Rätsch G, Tolnay M, Wicki A, Wollscheid B, Manz MG, Snijder B, and Theocharides APA

Subjects
Humans, CD36 Antigens metabolism, CD36 Antigens genetics, Female, Male, Antineoplastic Agents pharmacology, Antineoplastic Agents therapeutic use, Middle Aged, Proto-Oncogene Proteins c-bcl-2 metabolism, Proto-Oncogene Proteins c-bcl-2 genetics, Proto-Oncogene Proteins c-bcl-2 antagonists & inhibitors, Aged, Leukemia, Myeloid, Acute drug therapy, Leukemia, Myeloid, Acute genetics, Leukemia, Myeloid, Acute metabolism, Drug Resistance, Neoplasm genetics, Drug Resistance, Neoplasm drug effects, Single-Cell Analysis, Sulfonamides pharmacology, Sulfonamides therapeutic use, Bridged Bicyclo Compounds, Heterocyclic pharmacology, Bridged Bicyclo Compounds, Heterocyclic therapeutic use
Abstract

Deep single-cell multi-omic profiling offers a promising approach to understand and overcome drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML). Here, we combine single-cell ex vivo drug profiling (pharmacoscopy) with single-cell and bulk DNA, RNA, and protein analyses, alongside clinical data from 21 rrAML patients. Unsupervised data integration reveals reduced ex vivo response to the Bcl-2 inhibitor venetoclax (VEN) in patients treated with both a hypomethylating agent (HMA) and VEN, compared to those pre-exposed to chemotherapy or HMA alone. Integrative analysis identifies both known and unreported mechanisms of innate and treatment-related VEN resistance and suggests alternative treatments, like targeting increased proliferation with the PLK inhibitor volasertib. Additionally, high CD36 expression in VEN-resistant blasts associates with sensitivity to CD36-targeted antibody treatment ex vivo. This study demonstrates how single-cell multi-omic profiling can uncover drug resistance mechanisms and treatment vulnerabilities, providing a valuable resource for future AML research., (© 2024. The Author(s).)

Published
2024
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