Spatial tumour gene signature discriminates neoplastic from non-neoplastic compartments in colon cancer: unravelling predictive biomarkers for relapse
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Published:2023-08-05
Issue:1
Volume:21
Page:
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ISSN:1479-5876
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Container-title:Journal of Translational Medicine
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language:en
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Short-container-title:J Transl Med
Author:
Sallinger KatjaORCID, Gruber Michael, Müller Christin-Therese, Bonstingl Lilli, Pritz Elisabeth, Pankratz Karin, Gerger Armin, Smolle Maria Anna, Aigelsreiter Ariane, Surova Olga, Svedlund Jessica, Nilsson Mats, Kroneis Thomas, El-Heliebi AminORCID
Abstract
Abstract
Background
Opting for or against the administration of adjuvant chemotherapy in therapeutic management of stage II colon cancer remains challenging. Several studies report few survival benefits for patients treated with adjuvant therapy and additionally revealing potential side effects of overtreatment, including unnecessary exposure to chemotherapy-induced toxicities and reduced quality of life. Predictive biomarkers are urgently needed. We, therefore, hypothesise that the spatial tissue composition of relapsed and non-relapsed colon cancer stage II patients reveals relevant biomarkers.
Methods
The spatial tissue composition of stage II colon cancer patients was examined by a novel spatial transcriptomics technology with sub-cellular resolution, namely in situ sequencing. A panel of 176 genes investigating specific cancer-associated processes such as apoptosis, proliferation, angiogenesis, stemness, oxidative stress, hypoxia, invasion and components of the tumour microenvironment was designed to examine differentially expressed genes in tissue of relapsed versus non-relapsed patients. Therefore, FFPE slides of 10 colon cancer stage II patients either classified as relapsed (5 patients) or non-relapsed (5 patients) were in situ sequenced and computationally analysed.
Results
We identified a tumour gene signature that enables the subclassification of tissue into neoplastic and non-neoplastic compartments based on spatial expression patterns obtained through in situ sequencing. We developed a computational tool called Genes-To-Count (GTC), which automates the quantification of in situ signals, accurately mapping their position onto the spatial tissue map and automatically identifies neoplastic and non-neoplastic tissue compartments. The GTC tool was used to quantify gene expression of biological processes upregulated within the neoplastic tissue in comparison to non-neoplastic tissue and within relapsed versus non-relapsed stage II colon patients. Three differentially expressed genes (FGFR2, MMP11 and OTOP2) in the neoplastic tissue compartments of relapsed patients in comparison to non-relapsed patients were identified predicting recurrence in stage II colon cancer.
Conclusions
In depth spatial in situ sequencing showed potential to provide a deeper understanding of the underlying mechanisms involved in the recurrence of disease and revealed novel potential predictive biomarkers for disease relapse in colon cancer stage II patients. Our open-access GTC-tool allowed us to accurately capture the tumour compartment and quantify spatial gene expression in colon cancer tissue.
Funder
Doctoral school Translational Molecular and Cellular Biosciences of Medical University of Graz K1 COMET Competence Center CBmed Bundesministerium für Klimaschutz, Umwelt, Energie, Mobilität, Innovation und Technologie Bundesministerium für Wissenschaft, Forschung und Wirtschaft Steirische Wirtschaftsförderungsgesellschaft Wirtschaftsagentur Wien Österreichische Forschungsförderungsgesellschaft
Publisher
Springer Science and Business Media LLC
Subject
General Biochemistry, Genetics and Molecular Biology,General Medicine
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