Exploration of Pharmacogenomic Biomarkers in Chronic Immune Diseases Using Single-Cell RNA Sequencing
Аутори
Gorenjak, MarioGoričan, Larisa
Gole, Boris
Prosenc, Uršula
Melén, Erik
Kabesch, Michael
Maitland-van der Zee, Anke H.
Reinartz, Susanne
J.H. Vijverberg, Susanne
Potočnik, Uroš
PERMEABLE consortium
Остала ауторства
Morić, IvanaĐorđević, Valentina
Конференцијски прилог (Објављена верзија)
,
© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
Метаподаци
Приказ свих података о документуАпстракт
Biological therapies have revolutionized management of the severe cases of Chronic Immune
Diseases refractory to the standard therapies. However, many patients do not respond
to the selected biological therapy, loose response over time, or develop adverse effects. A
personalized approach to treatment of these patients, based on reliable biomarkers is thus
clearly needed.
Non-invasive approaches, such as use of the peripheral blood immune cells, are favored for
novel biomarker discovery. However, the attention has shifted away from the bulk immune
cells and towards specific immune cell sub-populations. Thus, the single-cell RNA sequencing
(scRNA-seq) can prove highly valuable. By simultaneously capturing and profiling all the cells
in a sample, scRNA-seq allows the analysis of cellular heterogeneity and gene expression in
all immune cell sub-populations, targeted or adversely affected by the biological treatment.
In our ongoing research, scRNA-seq was utilized to analyze samp...les from Inflammatory
Bowel Disease and Childhood Asthma patients with varied response to the biological
therapy. Confounding effects of disease conditions and (biological) therapies on marker
genes were eliminated using computational integration in order to identify conserved
marker genes across all states. It turned out, that a reliable identification of the different
immune cell sub-populations in this setting is quite challenging due to subjective
cell-landscape clustering resolution. Several resolutions and automated annotation
approaches were subsequently tested and validated.A reference-based approach (Seurat-Azimuth) combined with manual cluster validation
proved superior. Alas, manual cluster validation is time consuming. Annotation validation
is important, especially to provide additional insights into unidentified clusters, which are
essential for the identification of predictive biomarkers for personalized therapies in the
vast heterogeneity of immune cell landscapes residing behind pathophysiology of chronic
immune diseases.
Кључне речи:
precision medicine / chronic immune diseases / biological therapy / Single-Cell RNA Sequencing / dentification of cell sub-populationsИзвор:
4th Belgrade Bioinformatics Conference, 2023, 4, 55-56Издавач:
- Belgrade : Institute of molecular genetics and genetic engineering
Финансирање / пројекти:
- This research was funded by the Slovenian Research Agency- Research core funding P3-0427; Research grant J3-9258; the Labena company with Grant challenge program and the PERMEABLE consortium.
- The PERMEABLE consortium is supported by the ZonMW (project number: 456008004), the Swedish Research Council (proj.nr. 2018-05619), the Ministry of Education, Science and Sport of the Republic of Slovenia (proj.nr. C3330-19-252012), and the German Ministry of Education and Research (BMBF) (proj.nr. FKZ01KU1909A), under the frame of the ERA PerMed JTC 2018 Call.
Напомена:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Колекције
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Gorenjak, Mario AU - Goričan, Larisa AU - Gole, Boris AU - Prosenc, Uršula AU - Melén, Erik AU - Kabesch, Michael AU - Maitland-van der Zee, Anke H. AU - Reinartz, Susanne AU - J.H. Vijverberg, Susanne AU - Potočnik, Uroš AU - PERMEABLE consortium PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/1996 AB - Biological therapies have revolutionized management of the severe cases of Chronic Immune Diseases refractory to the standard therapies. However, many patients do not respond to the selected biological therapy, loose response over time, or develop adverse effects. A personalized approach to treatment of these patients, based on reliable biomarkers is thus clearly needed. Non-invasive approaches, such as use of the peripheral blood immune cells, are favored for novel biomarker discovery. However, the attention has shifted away from the bulk immune cells and towards specific immune cell sub-populations. Thus, the single-cell RNA sequencing (scRNA-seq) can prove highly valuable. By simultaneously capturing and profiling all the cells in a sample, scRNA-seq allows the analysis of cellular heterogeneity and gene expression in all immune cell sub-populations, targeted or adversely affected by the biological treatment. In our ongoing research, scRNA-seq was utilized to analyze samples from Inflammatory Bowel Disease and Childhood Asthma patients with varied response to the biological therapy. Confounding effects of disease conditions and (biological) therapies on marker genes were eliminated using computational integration in order to identify conserved marker genes across all states. It turned out, that a reliable identification of the different immune cell sub-populations in this setting is quite challenging due to subjective cell-landscape clustering resolution. Several resolutions and automated annotation approaches were subsequently tested and validated.A reference-based approach (Seurat-Azimuth) combined with manual cluster validation proved superior. Alas, manual cluster validation is time consuming. Annotation validation is important, especially to provide additional insights into unidentified clusters, which are essential for the identification of predictive biomarkers for personalized therapies in the vast heterogeneity of immune cell landscapes residing behind pathophysiology of chronic immune diseases. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - Exploration of Pharmacogenomic Biomarkers in Chronic Immune Diseases Using Single-Cell RNA Sequencing EP - 56 SP - 55 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_1996 ER -
@conference{ author = "Gorenjak, Mario and Goričan, Larisa and Gole, Boris and Prosenc, Uršula and Melén, Erik and Kabesch, Michael and Maitland-van der Zee, Anke H. and Reinartz, Susanne and J.H. Vijverberg, Susanne and Potočnik, Uroš and PERMEABLE consortium", year = "2023", abstract = "Biological therapies have revolutionized management of the severe cases of Chronic Immune Diseases refractory to the standard therapies. However, many patients do not respond to the selected biological therapy, loose response over time, or develop adverse effects. A personalized approach to treatment of these patients, based on reliable biomarkers is thus clearly needed. Non-invasive approaches, such as use of the peripheral blood immune cells, are favored for novel biomarker discovery. However, the attention has shifted away from the bulk immune cells and towards specific immune cell sub-populations. Thus, the single-cell RNA sequencing (scRNA-seq) can prove highly valuable. By simultaneously capturing and profiling all the cells in a sample, scRNA-seq allows the analysis of cellular heterogeneity and gene expression in all immune cell sub-populations, targeted or adversely affected by the biological treatment. In our ongoing research, scRNA-seq was utilized to analyze samples from Inflammatory Bowel Disease and Childhood Asthma patients with varied response to the biological therapy. Confounding effects of disease conditions and (biological) therapies on marker genes were eliminated using computational integration in order to identify conserved marker genes across all states. It turned out, that a reliable identification of the different immune cell sub-populations in this setting is quite challenging due to subjective cell-landscape clustering resolution. Several resolutions and automated annotation approaches were subsequently tested and validated.A reference-based approach (Seurat-Azimuth) combined with manual cluster validation proved superior. Alas, manual cluster validation is time consuming. Annotation validation is important, especially to provide additional insights into unidentified clusters, which are essential for the identification of predictive biomarkers for personalized therapies in the vast heterogeneity of immune cell landscapes residing behind pathophysiology of chronic immune diseases.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "Exploration of Pharmacogenomic Biomarkers in Chronic Immune Diseases Using Single-Cell RNA Sequencing", pages = "56-55", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_1996" }
Gorenjak, M., Goričan, L., Gole, B., Prosenc, U., Melén, E., Kabesch, M., Maitland-van der Zee, A. H., Reinartz, S., J.H. Vijverberg, S., Potočnik, U.,& PERMEABLE consortium. (2023). Exploration of Pharmacogenomic Biomarkers in Chronic Immune Diseases Using Single-Cell RNA Sequencing. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 55-56. https://hdl.handle.net/21.15107/rcub_imagine_1996
Gorenjak M, Goričan L, Gole B, Prosenc U, Melén E, Kabesch M, Maitland-van der Zee AH, Reinartz S, J.H. Vijverberg S, Potočnik U, PERMEABLE consortium. Exploration of Pharmacogenomic Biomarkers in Chronic Immune Diseases Using Single-Cell RNA Sequencing. in 4th Belgrade Bioinformatics Conference. 2023;4:55-56. https://hdl.handle.net/21.15107/rcub_imagine_1996 .
Gorenjak, Mario, Goričan, Larisa, Gole, Boris, Prosenc, Uršula, Melén, Erik, Kabesch, Michael, Maitland-van der Zee, Anke H., Reinartz, Susanne, J.H. Vijverberg, Susanne, Potočnik, Uroš, PERMEABLE consortium, "Exploration of Pharmacogenomic Biomarkers in Chronic Immune Diseases Using Single-Cell RNA Sequencing" in 4th Belgrade Bioinformatics Conference, 4 (2023):55-56, https://hdl.handle.net/21.15107/rcub_imagine_1996 .