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Dondi A, Lischetti U, Jacob F, Singer F, Borgsmüller N, Coelho R, Heinzelmann-Schwarz V, Beisel C, Beerenwinkel N. Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer. Nat Commun 2023; 14:7780. [PMID: 38012143 PMCID: PMC10682465 DOI: 10.1038/s41467-023-43387-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 11/07/2023] [Indexed: 11/29/2023] Open
Abstract
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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Affiliation(s)
- Arthur Dondi
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Ulrike Lischetti
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland.
| | - Francis Jacob
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
| | - Franziska Singer
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952, Schlieren, Switzerland
| | - Nico Borgsmüller
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Ricardo Coelho
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
| | - Viola Heinzelmann-Schwarz
- University Hospital Basel and University of Basel, Ovarian Cancer Research, Department of Biomedicine, Hebelstrasse 20, 4031, Basel, Switzerland
- University Hospital Basel, Gynecological Cancer Center, Spitalstrasse 21, 4031, Basel, Switzerland
| | - Christian Beisel
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
| | - Niko Beerenwinkel
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058, Basel, Switzerland.
- SIB Swiss Institute of Bioinformatics, Mattenstrasse 26, 4058, Basel, Switzerland.
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2
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Santinha AJ, Klingler E, Kuhn M, Farouni R, Lagler S, Kalamakis G, Lischetti U, Jabaudon D, Platt RJ. Transcriptional linkage analysis with in vivo AAV-Perturb-seq. Nature 2023; 622:367-375. [PMID: 37730998 PMCID: PMC10567566 DOI: 10.1038/s41586-023-06570-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 08/25/2023] [Indexed: 09/22/2023]
Abstract
The ever-growing compendium of genetic variants associated with human pathologies demands new methods to study genotype-phenotype relationships in complex tissues in a high-throughput manner1,2. Here we introduce adeno-associated virus (AAV)-mediated direct in vivo single-cell CRISPR screening, termed AAV-Perturb-seq, a tuneable and broadly applicable method for transcriptional linkage analysis as well as high-throughput and high-resolution phenotyping of genetic perturbations in vivo. We applied AAV-Perturb-seq using gene editing and transcriptional inhibition to systematically dissect the phenotypic landscape underlying 22q11.2 deletion syndrome3,4 genes in the adult mouse brain prefrontal cortex. We identified three 22q11.2-linked genes involved in known and previously undescribed pathways orchestrating neuronal functions in vivo that explain approximately 40% of the transcriptional changes observed in a 22q11.2-deletion mouse model. Our findings suggest that the 22q11.2-deletion syndrome transcriptional phenotype found in mature neurons may in part be due to the broad dysregulation of a class of genes associated with disease susceptibility that are important for dysfunctional RNA processing and synaptic function. Our study establishes a flexible and scalable direct in vivo method to facilitate causal understanding of biological and disease mechanisms with potential applications to identify genetic interventions and therapeutic targets for treating disease.
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Affiliation(s)
- Antonio J Santinha
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Esther Klingler
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
- VIB-KU Leuven Center for Brain & Disease Research, KU Leuven Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
| | - Maria Kuhn
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Pharma Research and Early Development (pRED), Roche, Basel, Switzerland
| | - Rick Farouni
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Sandra Lagler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Georgios Kalamakis
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Ulrike Lischetti
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Denis Jabaudon
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
| | - Randall J Platt
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
- Botnar Research Center for Child Health, Basel, Switzerland.
- Department of Chemistry, University of Basel, Basel, Switzerland.
- NCCR Molecular Systems Engineering, Basel, Switzerland.
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3
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Lischetti U, Tastanova A, Singer F, Grob L, Carrara M, Cheng PF, Martínez Gómez JM, Sella F, Haunerdinger V, Beisel C, Levesque MP. Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma. Commun Biol 2023; 6:830. [PMID: 37563418 PMCID: PMC10415364 DOI: 10.1038/s42003-023-05182-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 07/26/2023] [Indexed: 08/12/2023] Open
Abstract
Multi-omics profiling by CITE-seq bridges the RNA-protein gap in single-cell analysis but has been largely applied to liquid biopsies. Applying CITE-seq to clinically relevant solid biopsies to characterize healthy tissue and the tumor microenvironment is an essential next step in single-cell translational studies. In this study, gating of cell populations based on their transcriptome signatures for use in cell type-specific ridge plots allowed identification of positive antibody signals and setting of manual thresholds. Next, we compare five skin dissociation protocols by taking into account dissociation efficiency, captured cell type heterogeneity and recovered surface proteome. To assess the effect of enzymatic digestion on transcriptome and epitope expression in immune cell populations, we analyze peripheral blood mononuclear cells (PBMCs) with and without dissociation. To further assess the RNA-protein gap, RNA-protein we perform codetection and correlation analyses on thresholded protein values. Finally, in a proof-of-concept study, using protein abundance analysis on selected surface markers in a cohort of healthy skin, primary, and metastatic melanoma we identify CD56 surface marker expression on metastatic melanoma cells, which was further confirmed by multiplex immunohistochemistry. This work provides practical guidelines for processing and analysis of clinically relevant solid tissue biopsies for biomarker discovery.
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Affiliation(s)
- Ulrike Lischetti
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058, Basel, Switzerland
- Department of Biomedicine, University Hospital Basel, University of Basel, 4031, Basel, Switzerland
| | - Aizhan Tastanova
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Franziska Singer
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952, Schlieren, Switzerland
- SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Linda Grob
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952, Schlieren, Switzerland
- SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Matteo Carrara
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952, Schlieren, Switzerland
- SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Phil F Cheng
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Julia M Martínez Gómez
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Federica Sella
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Veronika Haunerdinger
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Christian Beisel
- Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Mitchell P Levesque
- Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
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4
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Grob L, Bertolini A, Carrara M, Lischetti U, Tastanova A, Beisel C, Levesque MP, Stekhoven DJ, Singer F. gExcite - A start-to-end framework for single-cell gene expression, hashing, and antibody analysis. Bioinformatics 2023:7176365. [PMID: 37220897 PMCID: PMC10229235 DOI: 10.1093/bioinformatics/btad329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 03/28/2023] [Accepted: 05/22/2023] [Indexed: 05/25/2023] Open
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 focussed 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 gExcite is open source available on github at https://github.com/ETH-NEXUS/gExcite_pipeline. The software is distributed under the GNU General Public License 3 (GPL3). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Linda Grob
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952 Schlieren, Switzerland; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Anne Bertolini
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952 Schlieren, Switzerland; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Matteo Carrara
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952 Schlieren, Switzerland; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Ulrike Lischetti
- Department of Biomedicine, University Hospital Basel and University of Basel, Basel, 4031, Switzerland
| | - Aizhan Tastanova
- Department of Dermatology, University of Zurich, University of Zurich Hospital, Schlieren, 8952, Switzerland
| | - Christian Beisel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland
| | - Mitchell P Levesque
- Department of Dermatology, University of Zurich, University of Zurich Hospital, Schlieren, 8952, Switzerland
| | - Daniel J Stekhoven
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952 Schlieren, Switzerland; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| | - Franziska Singer
- ETH Zurich, NEXUS Personalized Health Technologies, Wagistrasse 18, 8952 Schlieren, Switzerland; SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
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5
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Eichhoff OM, Stoffel CI, Käsler J, Briker L, Turko P, Karsai G, Zila N, Paulitschke V, Cheng PF, Leitner A, Bileck A, Zamboni N, Irmisch A, Balazs Z, Tastanova A, Pascoal S, Johansen P, Wegmann R, Mena J, Othman A, Viswanathan VS, Wenzina J, Aloia A, Saltari A, Dzung A, Aebersold R, Ak M, Al-Quaddoomi FS, Albert SI, Albinus J, Alborelli I, Andani S, Attinger PO, Bacac M, Baumhoer D, Beck-Schimmer B, Beerenwinkel N, Beisel C, Bernasconi L, Bertolini A, Bodenmiller B, Bonilla X, Bosshard L, Calgua B, Casanova R, Chevrier S, Chicherova N, Coelho R, D'Costa M, Danenberg E, Davidson N, Drãgan MA, Dummer R, Engler S, Erkens M, Eschbach K, Esposito C, Fedier A, Ferreira P, Ficek J, Frei AL, Frey B, Goetze S, Grob L, Gut G, Günther D, Haberecker M, Haeuptle P, Heinzelmann-Schwarz V, Herter S, Holtackers R, Huesser T, Immer A, Irmisch A, Jacob F, Jacobs A, Jaeger TM, Jahn K, James AR, Jermann PM, Kahles A, Kahraman A, Koelzer VH, Kuebler W, Kuipers J, Kunze CP, Kurzeder C, Lehmann KV, Levesque M, Lischetti U, Lugert S, Maass G, Manz MG, Markolin P, Mehnert M, Mena J, Metzler JM, Miglino N, Milani ES, Moch H, Muenst S, Murri R, Ng CK, Nicolet S, Nowak M, Lopez MN, Pedrioli PG, Pelkmans L, Piscuoglio S, Prummer M, Rimmer N, Ritter M, Rommel C, Rosano-González ML, Rätsch G, Santacroce N, Del Castillo JS, Schlenker R, Schwalie PC, Schwan S, Schär T, Senti G, Shao W, Singer F, Sivapatham S, Snijder B, Sobottka B, Sreedharan VT, Stark S, Stekhoven DJ, Tanna T, Theocharides AP, Thomas TM, Tolnay M, Tosevski V, Toussaint NC, Tuncel MA, Tusup M, Van Drogen A, Vetter M, Vlajnic T, Weber S, Weber WP, Wegmann R, Weller M, Wendt F, Wey N, Wicki A, Wildschut MH, Wollscheid B, Yu S, Ziegler J, Zimmermann M, Zoche M, Zuend G, Krauthammer M, Schreiber SL, Hornemann T, Distel M, Snijder B, Dummer R, Levesque MP. ROS Induction Targets Persister Cancer Cells with Low Metabolic Activity in NRAS-Mutated Melanoma. Cancer Res 2023; 83:1128-1146. [PMID: 36946761 DOI: 10.1158/0008-5472.can-22-1826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 10/04/2022] [Accepted: 01/24/2023] [Indexed: 03/23/2023]
Abstract
Clinical management of melanomas with NRAS mutations is challenging. Targeting MAPK signaling is only beneficial to a small subset of patients due to resistance that arises through genetic, transcriptional, and metabolic adaptation. Identification of targetable vulnerabilities in NRAS-mutated melanoma could help improve patient treatment. Here, we used multiomics analyses to reveal that NRAS-mutated melanoma cells adopt a mesenchymal phenotype with a quiescent metabolic program to resist cellular stress induced by MEK inhibition. The metabolic alterations elevated baseline reactive oxygen species (ROS) levels, leading these cells to become highly sensitive to ROS induction. In vivo xenograft experiments and single-cell RNA sequencing demonstrated that intratumor heterogeneity necessitates the combination of a ROS inducer and a MEK inhibitor to inhibit both tumor growth and metastasis. Ex vivo pharmacoscopy of 62 human metastatic melanomas confirmed that MEK inhibitor-resistant tumors significantly benefited from the combination therapy. Finally, oxidative stress response and translational suppression corresponded with ROS-inducer sensitivity in 486 cancer cell lines, independent of cancer type. These findings link transcriptional plasticity to a metabolic phenotype that can be inhibited by ROS inducers in melanoma and other cancers. SIGNIFICANCE Metabolic reprogramming in drug-resistant NRAS-mutated melanoma cells confers sensitivity to ROS induction, which suppresses tumor growth and metastasis in combination with MAPK pathway inhibitors.
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Affiliation(s)
- Ossia M Eichhoff
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Corinne I Stoffel
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Jan Käsler
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Luzia Briker
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Patrick Turko
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Gergely Karsai
- Institute for Clinical Chemistry, University Hospital Zurich, Zurich, Switzerland; Zurich Center for Integrative Human Physiology (ZIHP), University of Zurich, Zurich, Switzerland
| | - Nina Zila
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Verena Paulitschke
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Phil F Cheng
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | | | - Andrea Bileck
- Joint Metabolome Facility, Faculty of Chemistry, University of Vienna, Vienna, Austria
- Department of Analytical Chemistry, University of Vienna, Vienna, Austria
| | - Nicola Zamboni
- Institute for Molecular Systems Biology, ETH Zurich, Switzerland
| | - Anja Irmisch
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Zsolt Balazs
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Biomedical Informatics, University Hospital of Zurich, Zurich, Switzerland
| | - Aizhan Tastanova
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Susana Pascoal
- St. Anna Children's Cancer Research Institute, Vienna, Austria
| | - Pål Johansen
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Rebekka Wegmann
- Institute for Molecular Systems Biology, ETH Zurich, Switzerland
| | - Julien Mena
- Institute for Molecular Systems Biology, ETH Zurich, Switzerland
| | - Alaa Othman
- Institute for Molecular Systems Biology, ETH Zurich, Switzerland
| | | | - Judith Wenzina
- Skin and Endothelium Research Division, Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Andrea Aloia
- Institute for Molecular Systems Biology, ETH Zurich, Switzerland
| | - Annalisa Saltari
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Andreas Dzung
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
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- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Biomedical Informatics, University Hospital of Zurich, Zurich, Switzerland
| | | | - Thorsten Hornemann
- Institute for Clinical Chemistry, University Hospital Zurich, Zurich, Switzerland; Zurich Center for Integrative Human Physiology (ZIHP), University of Zurich, Zurich, Switzerland
| | - Martin Distel
- St. Anna Children's Cancer Research Institute, Vienna, Austria
| | - Berend Snijder
- Institute for Molecular Systems Biology, ETH Zurich, Switzerland
| | - Reinhard Dummer
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Mitchell P Levesque
- Department of Dermatology, University of Zurich, University Hospital Zurich, Zurich, Switzerland
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