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Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequen...

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Autores principales: Dondi, Arthur, Lischetti, Ulrike, Jacob, Francis, Singer, Franziska, Borgsmüller, Nico, Coelho, Ricardo, Heinzelmann-Schwarz, Viola, Beisel, Christian, Beerenwinkel, Niko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682465/
https://www.ncbi.nlm.nih.gov/pubmed/38012143
http://dx.doi.org/10.1038/s41467-023-43387-9
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author Dondi, Arthur
Lischetti, Ulrike
Jacob, Francis
Singer, Franziska
Borgsmüller, Nico
Coelho, Ricardo
Heinzelmann-Schwarz, Viola
Beisel, Christian
Beerenwinkel, Niko
author_facet Dondi, Arthur
Lischetti, Ulrike
Jacob, Francis
Singer, Franziska
Borgsmüller, Nico
Coelho, Ricardo
Heinzelmann-Schwarz, Viola
Beisel, Christian
Beerenwinkel, Niko
author_sort Dondi, Arthur
collection PubMed
description Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.
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spelling pubmed-106824652023-11-30 Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer Dondi, Arthur Lischetti, Ulrike Jacob, Francis Singer, Franziska Borgsmüller, Nico Coelho, Ricardo Heinzelmann-Schwarz, Viola Beisel, Christian Beerenwinkel, Niko Nat Commun Article Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine. Nature Publishing Group UK 2023-11-27 /pmc/articles/PMC10682465/ /pubmed/38012143 http://dx.doi.org/10.1038/s41467-023-43387-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Dondi, Arthur
Lischetti, Ulrike
Jacob, Francis
Singer, Franziska
Borgsmüller, Nico
Coelho, Ricardo
Heinzelmann-Schwarz, Viola
Beisel, Christian
Beerenwinkel, Niko
Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer
title Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer
title_full Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer
title_fullStr Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer
title_full_unstemmed Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer
title_short Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer
title_sort detection of isoforms and genomic alterations by high-throughput full-length single-cell rna sequencing in ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682465/
https://www.ncbi.nlm.nih.gov/pubmed/38012143
http://dx.doi.org/10.1038/s41467-023-43387-9
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