Combining gene expression analysis of gastric cancer cell lines and tumor specimens to identify biomarkers for anti-HER therapies—the role of HAS2, SHB and HBEGF
Karolin Ebert,
Ivonne Haffner,
Gwen Zwingenberger,
Simone Keller,
Elba Raimúndez,
Robert Geffers,
Ralph Wirtz,
Elena Barbaria,
Vanessa Hollerieth,
Rouven Arnold,
Axel Walch,
Jan Hasenauer,
Dieter Maier,
Florian Lordick,
Birgit Luber
Affiliations
Karolin Ebert
Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie
Ivonne Haffner
University Cancer Center Leipzig (UCCL), University Leipzig Medical Center
Gwen Zwingenberger
Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie
Simone Keller
Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie
Elba Raimúndez
Faculty of Mathematics and Natural Sciences, University of Bonn
Robert Geffers
Helmholtz Zentrum für Infektionsforschung
Ralph Wirtz
STRATIFYER Molecular Pathology GmbH
Elena Barbaria
Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie
Vanessa Hollerieth
Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie
Rouven Arnold
Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie
Axel Walch
Helmholtz Zentrum München-German Research Center for Environmental Health, Research Unit Analytical Pathology
Jan Hasenauer
Faculty of Mathematics and Natural Sciences, University of Bonn
Dieter Maier
Biomax Informatics AG
Florian Lordick
University Cancer Center Leipzig (UCCL), University Leipzig Medical Center
Birgit Luber
Technische Universität München, Fakultät für Medizin, Klinikum rechts der Isar, Institut für Allgemeine Pathologie und Pathologische Anatomie
Abstract Background The standard treatment for patients with advanced HER2-positive gastric cancer is a combination of the antibody trastuzumab and platin-fluoropyrimidine chemotherapy. As some patients do not respond to trastuzumab therapy or develop resistance during treatment, the search for alternative treatment options and biomarkers to predict therapy response is the focus of research. We compared the efficacy of trastuzumab and other HER-targeting drugs such as cetuximab and afatinib. We also hypothesized that treatment-dependent regulation of a gene indicates its importance in response and that it can therefore be used as a biomarker for patient stratification. Methods A selection of gastric cancer cell lines (Hs746T, MKN1, MKN7 and NCI-N87) was treated with EGF, cetuximab, trastuzumab or afatinib for a period of 4 or 24 h. The effects of treatment on gene expression were measured by RNA sequencing and the resulting biomarker candidates were tested in an available cohort of gastric cancer patients from the VARIANZ trial or functionally analyzed in vitro. Results After treatment of the cell lines with afatinib, the highest number of regulated genes was observed, followed by cetuximab and trastuzumab. Although trastuzumab showed only relatively small effects on gene expression, BMF, HAS2 and SHB could be identified as candidate biomarkers for response to trastuzumab. Subsequent studies confirmed HAS2 and SHB as potential predictive markers for response to trastuzumab therapy in clinical samples from the VARIANZ trial. AREG, EREG and HBEGF were identified as candidate biomarkers for treatment with afatinib and cetuximab. Functional analysis confirmed that HBEGF is a resistance factor for cetuximab. Conclusion By confirming HAS2, SHB and HBEGF as biomarkers for anti-HER therapies, we provide evidence that the regulation of gene expression after treatment can be used for biomarker discovery. Trial registration. Clinical specimens of the VARIANZ study (NCT02305043) were used to test biomarker candidates.
