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Predicting microenvironment in CXCR4- and FAP-positive solid tumors — a pan-cancer machine learning workflow for theranostic target structures

Please always quote using this URN: urn:nbn:de:bvb:20-opus-305036
  • (1) Background: C-X-C Motif Chemokine Receptor 4 (CXCR4) and Fibroblast Activation Protein Alpha (FAP) are promising theranostic targets. However, it is unclear whether CXCR4 and FAP positivity mark distinct microenvironments, especially in solid tumors. (2) Methods: Using Random Forest (RF) analysis, we searched for entity-independent mRNA and microRNA signatures related to CXCR4 and FAP overexpression in our pan-cancer cohort from The Cancer Genome Atlas (TCGA) database — representing n = 9242 specimens from 29 tumor entities. CXCR4- and(1) Background: C-X-C Motif Chemokine Receptor 4 (CXCR4) and Fibroblast Activation Protein Alpha (FAP) are promising theranostic targets. However, it is unclear whether CXCR4 and FAP positivity mark distinct microenvironments, especially in solid tumors. (2) Methods: Using Random Forest (RF) analysis, we searched for entity-independent mRNA and microRNA signatures related to CXCR4 and FAP overexpression in our pan-cancer cohort from The Cancer Genome Atlas (TCGA) database — representing n = 9242 specimens from 29 tumor entities. CXCR4- and FAP-positive samples were assessed via StringDB cluster analysis, EnrichR, Metascape, and Gene Set Enrichment Analysis (GSEA). Findings were validated via correlation analyses in n = 1541 tumor samples. TIMER2.0 analyzed the association of CXCR4 / FAP expression and infiltration levels of immune-related cells. (3) Results: We identified entity-independent CXCR4 and FAP gene signatures representative for the majority of solid cancers. While CXCR4 positivity marked an immune-related microenvironment, FAP overexpression highlighted an angiogenesis-associated niche. TIMER2.0 analysis confirmed characteristic infiltration levels of CD8+ cells for CXCR4-positive tumors and endothelial cells for FAP-positive tumors. (4) Conclusions: CXCR4- and FAP-directed PET imaging could provide a non-invasive decision aid for entity-agnostic treatment of microenvironment in solid malignancies. Moreover, this machine learning workflow can easily be transferred towards other theranostic targets.show moreshow less

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Author: André Marquardt, Philipp Hartrampf, Philip Kollmannsberger, Antonio G. Solimando, Svenja Meierjohann, Hubert Kübler, Ralf Bargou, Bastian Schilling, Sebastian E. Serfling, Andreas Buck, Rudolf A. Werner, Constantin Lapa, Markus Krebs
URN:urn:nbn:de:bvb:20-opus-305036
Document Type:Journal article
Faculties:Medizinische Fakultät / Klinik und Poliklinik für Nuklearmedizin
Medizinische Fakultät / Urologische Klinik und Poliklinik
Medizinische Fakultät / Pathologisches Institut
Medizinische Fakultät / Klinik und Poliklinik für Dermatologie, Venerologie und Allergologie
Fakultät für Biologie / Center for Computational and Theoretical Biology
Medizinische Fakultät / Comprehensive Cancer Center Mainfranken
Language:English
Parent Title (English):Cancers
ISSN:2072-6694
Year of Completion:2023
Volume:15
Issue:2
Article Number:392
Source:Cancers (2023) 15:2, 392. https://doi.org/10.3390/cancers15020392
DOI:https://doi.org/10.3390/cancers15020392
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Tag:angiogenesis; immune infiltration; mRNA; machine learning; miRNA; transcriptome; tumor microenvironment
Release Date:2023/12/13
Date of first Publication:2023/01/06
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International