@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{LuekeHallerUtpateletal.2022, author = {L{\"u}ke, Florian and Haller, Florian and Utpatel, Kirsten and Krebs, Markus and Meidenbauer, Norbert and Scheiter, Alexander and Spoerl, Silvia and Heudobler, Daniel and Sparrer, Daniela and Kaiser, Ulrich and Keil, Felix and Schubart, Christoph and T{\"o}gel, Lars and Einhell, Sabine and Dietmaier, Wolfgang and Huss, Ralf and Dintner, Sebastian and Sommer, Sebastian and Jordan, Frank and Goebeler, Maria-Elisabeth and Metz, Michaela and Haake, Diana and Scheytt, Mithun and Gerhard-Hartmann, Elena and Maurus, Katja and Br{\"a}ndlein, Stephanie and Rosenwald, Andreas and Hartmann, Arndt and M{\"a}rkl, Bruno and Einsele, Hermann and Mackensen, Andreas and Herr, Wolfgang and Kunzmann, Volker and Bargou, Ralf and Beckmann, Matthias W. and Pukrop, Tobias and Trepel, Martin and Evert, Matthias and Claus, Rainer and Kerscher, Alexander}, title = {Identification of disparities in personalized cancer care — a joint approach of the German WERA consortium}, series = {Cancers}, volume = {14}, journal = {Cancers}, number = {20}, issn = {2072-6694}, doi = {10.3390/cancers14205040}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-290311}, year = {2022}, abstract = {(1) Background: molecular tumor boards (MTBs) are crucial instruments for discussing and allocating targeted therapies to suitable cancer patients based on genetic findings. Currently, limited evidence is available regarding the regional impact and the outreach component of MTBs; (2) Methods: we analyzed MTB patient data from four neighboring Bavarian tertiary care oncology centers in W{\"u}rzburg, Erlangen, Regensburg, and Augsburg, together constituting the WERA Alliance. Absolute patient numbers and regional distribution across the WERA-wide catchment area were weighted with local population densities; (3) Results: the highest MTB patient numbers were found close to the four cancer centers. However, peaks in absolute patient numbers were also detected in more distant and rural areas. Moreover, weighting absolute numbers with local population density allowed for identifying so-called white spots—regions within our catchment that were relatively underrepresented in WERA MTBs; (4) Conclusions: investigating patient data from four neighboring cancer centers, we comprehensively assessed the regional impact of our MTBs. The results confirmed the success of existing collaborative structures with our regional partners. Additionally, our results help identifying potential white spots in providing precision oncology and help establishing a joint WERA-wide outreach strategy.}, language = {en} } @article{KotlyarKrebsSolimandoetal.2023, author = {Kotlyar, Mischa J. and Krebs, Markus and Solimando, Antonio Giovanni and Marquardt, Andr{\´e} and Burger, Maximilian and K{\"u}bler, Hubert and Bargou, Ralf and Kneitz, Susanne and Otto, Wolfgang and Breyer, Johannes and Vergho, Daniel C. and Kneitz, Burkhard and Kalogirou, Charis}, title = {Critical evaluation of a microRNA-based risk classifier predicting cancer-specific survival in renal cell carcinoma with tumor thrombus of the inferior vena cava}, series = {Cancers}, volume = {15}, journal = {Cancers}, number = {7}, issn = {2072-6694}, doi = {10.3390/cancers15071981}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311040}, year = {2023}, abstract = {(1) Background: Clear cell renal cell carcinoma extending into the inferior vena cava (ccRCC\(^{IVC}\)) represents a clinical high-risk setting. However, there is substantial heterogeneity within this patient subgroup regarding survival outcomes. Previously, members of our group developed a microRNA(miR)-based risk classifier — containing miR-21-5p, miR-126-3p and miR-221-3p expression — which significantly predicted the cancer-specific survival (CSS) of ccRCC\(^{IVC}\) patients. (2) Methods: Examining a single-center cohort of tumor tissue from n = 56 patients with ccRCC\(^{IVC}\), we measured the expression levels of miR-21, miR-126, and miR-221 using qRT-PCR. The prognostic impact of clinicopathological parameters and miR expression were investigated via single-variable and multivariable Cox regression. Referring to the previously established risk classifier, we performed Kaplan-Meier analyses for single miR expression levels and the combined risk classifier. Cut-off values and weights within the risk classifier were taken from the previous study. (3) Results: miR-21 and miR-126 expression were significantly associated with lymphonodal status at the time of surgery, the development of metastasis during follow-up, and cancer-related death. In Kaplan-Meier analyses, miR-21 and miR-126 significantly impacted CSS in our cohort. Moreover, applying the miR-based risk classifier significantly stratified ccRCC\(^{IVC}\) according to CSS. (4) Conclusions: In our retrospective analysis, we successfully validated the miR-based risk classifier within an independent ccRCC\(^{IVC}\) cohort.}, language = {en} }