Francesca Pia Caruso1,2, Luciano Garofano1,3, Fulvio D'Angelo2,3, Kai Yu4, Fuchou Tang4, Jinzhou Yuan5,6, Jing Zhang3, Luigi Cerulo2,5, Stefano M Pagnotta5, Davide Bedognetti6,7, Peter A Sims8,9, Mario Suvà10,11, Xiao-Dong Su4, Anna Lasorella3,12, Antonio Iavarone3,12,13, Michele Ceccarelli1,2. 1. Department of Electrical Engineering and Information Technology (DIETI), University of Naples "Federico II", Via Claudio 21, 80128 Naples, Italy. 2. Bioinformatics Lab, BIOGEM, Via Camporeale, 83031 Ariano Irpino, Italy. 3. Institute for Cancer Genetics, Columbia University, 1130 St Nicholas Ave, New York, NY 10032, USA. 4. Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, 5 Yiheyuan Rd, Haidian District, 100871 Beijing, China. 5. Department of Science and Technologies, Università degli Studi del Sannio, Via de Sanctis, 82100 Benevento, Italy. 6. Cancer Program, Sidra Medicine, Al Luqta Street, Zone 52, Education City, 26999, Doha Qatar. 7. Department of Internal Medicine and Medical Specialties (Di.M.I.), University of Genoa, Viale Benedetto XV 10, 16132 Genoa, Italy. 8. Department of Systems Biology, Columbia University Irving Medical Center, 1130 St Nicholas Ave, New York , NY 10032, USA. 9. Department of Biochemistry and Molecular Biophysics, Columbia University Irving Medical Center, 1130 St Nicholas Ave, New York, NY 10032, USA. 10. Department of Pathology and Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, 55 Fruit St, Boston, MA 02114, USA. 11. Broad Institute of Harvard and MIT, 415 Main St, Cambridge, MA 02142, USA. 12. Department of Pathology and Cell Biology, Columbia University Medical Center, 1130 St Nicholas Ave, New York , NY 10032 USA. 13. Department of Neurology, Columbia University Medical Center, 1130 St Nicholas Ave, New York, NY 10032, USA.
Abstract
BACKGROUND: Single-cell RNA sequencing is the reference technique for characterizing the heterogeneity of the tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is of fundamental importance for the identification of immuno-oncology therapeutic targets. RESULTS: We present a novel method, single-cell Tumor-Host Interaction tool (scTHI), to identify significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand-receptor interactions in glioma using 6 publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma. CONCLUSIONS: Our results provide a complete map of the active tumor-host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumor.
BACKGROUND: Single-cell RNA sequencing is the reference technique for characterizing the heterogeneity of the tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is of fundamental importance for the identification of immuno-oncology therapeutic targets. RESULTS: We present a novel method, single-cell Tumor-Host Interaction tool (scTHI), to identify significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand-receptor interactions in glioma using 6 publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma. CONCLUSIONS: Our results provide a complete map of the active tumor-host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumor.
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Authors: O Martinho; A Longatto-Filho; M B K Lambros; A Martins; C Pinheiro; A Silva; F Pardal; J Amorim; A Mackay; F Milanezi; N Tamber; K Fenwick; A Ashworth; J S Reis-Filho; J M Lopes; R M Reis Journal: Br J Cancer Date: 2009-08-25 Impact factor: 7.640
Authors: Natalia Filippova; Jeffrey M Grimes; Jianmei W Leavenworth; David Namkoong; Xiuhua Yang; Peter H King; Michael Crowley; David K Crossman; L Burt Nabors Journal: Neurooncol Adv Date: 2022-09-15