Integrative analysis of ,multi-omics data identified EGFR and PTGS2 as key nodes in a gene regulatory network related to immune phenotypes in head and neck cancer

• Verfasst von: Feng, Bohai [VerfasserIn]
• Verfasst von: Shen, Ying [VerfasserIn]
• Verfasst von: Hostench, Xavier Pastor [VerfasserIn]
• Verfasst von: Bieg, Matthias [VerfasserIn]
• Verfasst von: Plath, Michaela [VerfasserIn]
• Verfasst von: Ishaque, Naveed [VerfasserIn]
• Verfasst von: Eils, Roland [VerfasserIn]
• Verfasst von: Freier, Kolja [VerfasserIn]
• Verfasst von: Weichert, Wilko [VerfasserIn]
• Verfasst von: Plath, Karim [VerfasserIn]
• Verfasst von: Heß, Jochen [VerfasserIn]
• Titel: Integrative analysis of ,multi-omics data identified EGFR and PTGS2 as key nodes in a gene regulatory network related to immune phenotypes in head and neck cancer
• Verf.angabe: Bohai Feng, Ying Shen, Xavier Pastor Hostench, Matthias Bieg, Michaela Plath, Naveed Ishaque, Roland Eils, Kolja Freier, Wilko Weichert, Karim Zaoui, and Jochen Hess
• E-Jahr: 2020
• Jahr: March 11, 2020
• Umfang: 13 S.
• Fussnoten: Gesehen am 07.09.2020
• Titel Quelle: Enthalten in: Clinical cancer research
• Ort Quelle: Philadelphia, Pa. [u.a.] : AACR, 1995
• Jahr Quelle: 2020
• Band/Heft Quelle: 26(2020), 14, Seite 3616-3628
• ISSN Quelle: 1557-3265
• DOI: doi:10.1158/1078-0432.CCR-19-3997
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1728967309

Abstract

Purpose: Malignant progression exhibits a tightly orchestrated balance between immune effector response and tolerance. However, underlying molecular principles that drive the establishment and maintenance of the tumor immune phenotype remain to be elucidated. - Experimental Design: We trained a novel molecular classifier based on immune cell subsets related to programmed death-ligand 1 (PD-L1) and interferon γ (IFNγ) expression, which revealed distinct subgroups with higher (cluster A) or lower (subcluster B3) cytotoxic immune phenotypes. Integrative analysis of multi-omics data was conducted to identify differences in genetic and epigenetic landscapes as well as their impact on differentially expressed genes (DEG) among immune phenotypes. A prognostic gene signature for immune checkpoint inhibition (ICI) was established by a least absolute shrinkage and selection operator (LASSO)-Cox regression model. - Results: Mutational landscape analyses unraveled a higher frequency of CASP8 somatic mutations in subcluster A1, while subcluster B3 exhibited a characteristic pattern of copy-number alterations affecting chemokine signaling and immune effector response. The integrative multi-omics approach identified EGFR and PTGS2 as key nodes in a gene regulatory network related to the immune phenotype, and several DEGs related to the immune phenotypes were affected by EGFR inhibition in tumor cell lines. Finally, we established a prognostic gene signature by a LASSO-Cox regression model based on DEGs between nonprogressive disease and progressive disease subgroups for ICI. - Conclusions: Our data highlight a complex interplay between genetic and epigenetic events in the establishment of the tumor immune phenotype and provide compelling experimental evidence that a patient with squamous cell carcinoma of the head and neck at higher risk for ICI treatment failure might benefit from a combination with EGFR inhibition.