@article{SolimandoPalumboPragnelletal.2022,
  author    = {Solimando, Antonio G. and Palumbo, Carmen and Pragnell, Mary Victoria and Bittrich, Max and Argentiero, Antonella and Krebs, Markus},
  title     = {Aplastic anemia as a roadmap for bone marrow failure: an overview and a clinical workflow},
  series = {International Journal of Molecular Sciences},
  volume    = {23},
  journal   = {International Journal of Molecular Sciences},
  number    = {19},
  issn      = {1422-0067},
  doi       = {10.3390/ijms231911765},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-290440},
  year      = {2022},
  abstract  = {In recent years, it has become increasingly apparent that bone marrow (BM) failures and myeloid malignancy predisposition syndromes are characterized by a wide phenotypic spectrum and that these diseases must be considered in the differential diagnosis of children and adults with unexplained hematopoiesis defects. Clinically, hypocellular BM failure still represents a challenge in pathobiology-guided treatment. There are three fundamental topics that emerged from our review of the existing data. An exogenous stressor, an immune defect, and a constitutional genetic defect fuel a vicious cycle of hematopoietic stem cells, immune niches, and stroma compartments. A wide phenotypic spectrum exists for inherited and acquired BM failures and predispositions to myeloid malignancies. In order to effectively manage patients, it is crucial to establish the right diagnosis. New theragnostic windows can be revealed by exploring BM failure pathomechanisms.},
  language  = {en}
}
@article{SolimandoBittrichShahinietal.2023,
  author    = {Solimando, Antonio G. and Bittrich, Max and Shahini, Endrit and Albanese, Federica and Fritz, Georg and Krebs, Markus},
  title     = {Determinants of COVID-19 disease severity - lessons from primary and secondary immune disorders including cancer},
  series = {International Journal of Molecular Sciences},
  volume    = {24},
  journal   = {International Journal of Molecular Sciences},
  number    = {10},
  issn      = {1422-0067},
  doi       = {10.3390/ijms24108746},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-319412},
  year      = {2023},
  abstract  = {At the beginning of the COVID-19 pandemic, patients with primary and secondary immune disorders — including patients suffering from cancer — were generally regarded as a high-risk population in terms of COVID-19 disease severity and mortality. By now, scientific evidence indicates that there is substantial heterogeneity regarding the vulnerability towards COVID-19 in patients with immune disorders. In this review, we aimed to summarize the current knowledge about the effect of coexistent immune disorders on COVID-19 disease severity and vaccination response. In this context, we also regarded cancer as a secondary immune disorder. While patients with hematological malignancies displayed lower seroconversion rates after vaccination in some studies, a majority of cancer patients' risk factors for severe COVID-19 disease were either inherent (such as metastatic or progressive disease) or comparable to the general population (age, male gender and comorbidities such as kidney or liver disease). A deeper understanding is needed to better define patient subgroups at a higher risk for severe COVID-19 disease courses. At the same time, immune disorders as functional disease models offer further insights into the role of specific immune cells and cytokines when orchestrating the immune response towards SARS-CoV-2 infection. Longitudinal serological studies are urgently needed to determine the extent and the duration of SARS-CoV-2 immunity in the general population, as well as immune-compromised and oncological patients.},
  language  = {en}
}
@article{MarquardtHartrampfKollmannsbergeretal.2023,
  author    = {Marquardt, Andr{\´e} and Hartrampf, Philipp and Kollmannsberger, Philip and Solimando, Antonio G. and Meierjohann, Svenja and K{\"u}bler, Hubert and Bargou, Ralf and Schilling, Bastian and Serfling, Sebastian E. and Buck, Andreas and Werner, Rudolf A. and Lapa, Constantin and Krebs, Markus},
  title     = {Predicting microenvironment in CXCR4- and FAP-positive solid tumors — a pan-cancer machine learning workflow for theranostic target structures},
  series = {Cancers},
  volume    = {15},
  journal   = {Cancers},
  number    = {2},
  issn      = {2072-6694},
  doi       = {10.3390/cancers15020392},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-305036},
  year      = {2023},
  abstract  = {(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.},
  language  = {en}
}
@article{LodaKrebsDanhofetal.2019,
  author    = {Loda, Sophia and Krebs, Jonathan and Danhof, Sophia and Schreder, Martin and Solimando, Antonio G. and Strifler, Susanne and Rasche, Leo and Kort{\"u}m, Martin and Kerscher, Alexander and Knop, Stefan and Puppe, Frank and Einsele, Hermann and Bittrich, Max},
  title     = {Exploration of artificial intelligence use with ARIES in multiple myeloma research},
  series = {Journal of Clinical Medicine},
  volume    = {8},
  journal   = {Journal of Clinical Medicine},
  number    = {7},
  issn      = {2077-0383},
  doi       = {10.3390/jcm8070999},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197231},
  pages     = {999},
  year      = {2019},
  abstract  = {Background: Natural language processing (NLP) is a powerful tool supporting the generation of Real-World Evidence (RWE). There is no NLP system that enables the extensive querying of parameters specific to multiple myeloma (MM) out of unstructured medical reports. We therefore created a MM-specific ontology to accelerate the information extraction (IE) out of unstructured text. Methods: Our MM ontology consists of extensive MM-specific and hierarchically structured attributes and values. We implemented "A Rule-based Information Extraction System" (ARIES) that uses this ontology. We evaluated ARIES on 200 randomly selected medical reports of patients diagnosed with MM. Results: Our system achieved a high F1-Score of 0.92 on the evaluation dataset with a precision of 0.87 and recall of 0.98. Conclusions: Our rule-based IE system enables the comprehensive querying of medical reports. The IE accelerates the extraction of data and enables clinicians to faster generate RWE on hematological issues. RWE helps clinicians to make decisions in an evidence-based manner. Our tool easily accelerates the integration of research evidence into everyday clinical practice.},
  language  = {en}
}