@article{RascheKortuemRaabetal.2019, author = {Rasche, Leo and Kort{\"u}m, K. Martin and Raab, Marc S. and Weinhold, Niels}, title = {The impact of tumor heterogeneity on diagnostics and novel therapeutic strategies in multiple myeloma}, series = {International Journal of Molecular Sciences}, volume = {20}, journal = {International Journal of Molecular Sciences}, number = {5}, issn = {1422-0067}, doi = {10.3390/ijms20051248}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285402}, year = {2019}, abstract = {Myeloma is characterized by extensive inter-patient genomic heterogeneity due to multiple different initiating events. A recent multi-region sequencing study demonstrated spatial differences, with progression events, such as TP53 mutations, frequently being restricted to focal lesions. In this review article, we describe the clinical impact of these two types of tumor heterogeneity. Target mutations are often dominant at one site but absent at other sites, which poses a significant challenge to personalized therapy in myeloma. The same holds true for high-risk subclones, which can be locally restricted, and as such not detectable at the iliac crest, which is the usual sampling site. Imaging can improve current risk classifiers and monitoring of residual disease, but does not allow for deciphering the molecular characteristics of tumor clones. In the era of novel immunotherapies, the clinical impact of heterogeneity certainly needs to be re-defined. Yet, preliminary observations indicate an ongoing impact of spatial heterogeneity on the efficacy of monoclonal antibodies. In conclusion, we recommend combining molecular tests with imaging to improve risk prediction and monitoring of residual disease. Overcoming intra-tumor heterogeneity is the prerequisite for curing myeloma. Novel immunotherapies are promising but research addressing their impact on the spatial clonal architecture is highly warranted.}, language = {en} } @article{LoehrHaertigSchulzeetal.2022, author = {L{\"o}hr, Mario and H{\"a}rtig, Wolfgang and Schulze, Almut and Kroiß, Matthias and Sbiera, Silviu and Lapa, Constantin and Mages, Bianca and Strobel, Sabrina and Hundt, Jennifer Elisabeth and Bohnert, Simone and Kircher, Stefan and Janaki-Raman, Sudha and Monoranu, Camelia-Maria}, title = {SOAT1: A suitable target for therapy in high-grade astrocytic glioma?}, series = {International Journal of Molecular Sciences}, volume = {23}, journal = {International Journal of Molecular Sciences}, number = {7}, issn = {1422-0067}, doi = {10.3390/ijms23073726}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-284178}, year = {2022}, abstract = {Targeting molecular alterations as an effective treatment for isocitrate dehydrogenase-wildtype glioblastoma (GBM) patients has not yet been established. Sterol-O-Acyl Transferase 1 (SOAT1), a key enzyme in the conversion of endoplasmic reticulum cholesterol to esters for storage in lipid droplets (LD), serves as a target for the orphan drug mitotane to treat adrenocortical carcinoma. Inhibition of SOAT1 also suppresses GBM growth. Here, we refined SOAT1-expression in GBM and IDH-mutant astrocytoma, CNS WHO grade 4 (HGA), and assessed the distribution of LD in these tumors. Twenty-seven GBM and three HGA specimens were evaluated by multiple GFAP, Iba1, IDH1 R132H, and SOAT1 immunofluorescence labeling as well as Oil Red O staining. To a small extent SOAT1 was expressed by tumor cells in both tumor entities. In contrast, strong expression was observed in glioma-associated macrophages. Triple immunofluorescence labeling revealed, for the first time, evidence for SOAT1 colocalization with Iba1 and IDH1 R132H, respectively. Furthermore, a notable difference in the amount of LD between GBM and HGA was observed. Therefore, SOAT1 suppression might be a therapeutic option to target GBM and HGA growth and invasiveness. In addition, the high expression in cells related to neuroinflammation could be beneficial for a concomitant suppression of protumoral microglia/macrophages.}, language = {en} } @article{LoddeForschnerHasseletal.2021, author = {Lodde, Georg and Forschner, Andrea and Hassel, Jessica and Wulfken, Lena M. and Meier, Friedegund and Mohr, Peter and K{\"a}hler, Katharina and Schilling, Bastian and Loquai, Carmen and Berking, Carola and H{\"u}ning, Svea and Schatton, Kerstin and Gebhardt, Christoffer and Eckardt, Julia and Gutzmer, Ralf and Reinhardt, Lydia and Glutsch, Valerie and Nikfarjam, Ulrike and Erdmann, Michael and Stang, Andreas and Kowall, Bernd and Roesch, Alexander and Ugurel, Selma and Zimmer, Lisa and Schadendorf, Dirk and Livingstone, Elisabeth}, title = {Factors influencing the adjuvant therapy decision: results of a real-world multicenter data analysis of 904 melanoma patients}, series = {Cancers}, volume = {13}, journal = {Cancers}, number = {10}, issn = {2072-6694}, doi = {10.3390/cancers13102319}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-239583}, year = {2021}, abstract = {Adjuvant treatment of melanoma patients with immune-checkpoint inhibition (ICI) and targeted therapy (TT) significantly improved recurrence-free survival. This study investigates the real-world situation of 904 patients from 13 German skin cancer centers with an indication for adjuvant treatment since the approval of adjuvant ICI and TT. From adjusted log-binomial regression models, we estimated relative risks for associations between various influence factors and treatment decisions (adjuvant therapy yes/no, TT vs. ICI in BRAF mutant patients). Of these patients, 76.9\% (95\% CI 74-80) opted for a systemic adjuvant treatment. The probability of starting an adjuvant treatment was 26\% lower in patients >65 years (RR 0.74, 95\% CI 68-80). The most common reasons against adjuvant treatment given by patients were age (29.4\%, 95\% CI 24-38), and fear of adverse events (21.1\%, 95\% CI 16-28) and impaired quality of life (11.9\%, 95\% CI 7-16). Of all BRAF-mutated patients who opted for adjuvant treatment, 52.9\% (95\% CI 47-59) decided for ICI. Treatment decision for TT or ICI was barely associated with age, gender and tumor stage, but with comorbidities and affiliated center. Shortly after their approval, adjuvant treatments have been well accepted by physicians and patients. Age plays a decisive role in the decision for adjuvant treatment, while pre-existing autoimmune disease and regional differences influence the choice between TT or ICI.}, language = {en} } @article{BaurNietzerKunzetal.2020, author = {Baur, Florentin and Nietzer, Sarah L. and Kunz, Meik and Saal, Fabian and Jeromin, Julian and Matschos, Stephanie and Linnebacher, Michael and Walles, Heike and Dandekar, Thomas and Dandekar, Gudrun}, title = {Connecting cancer pathways to tumor engines: a stratification tool for colorectal cancer combining human in vitro tissue models with boolean in silico models}, series = {Cancers}, volume = {12}, journal = {Cancers}, number = {1}, issn = {2072-6694}, doi = {10.3390/cancers12010028}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193798}, pages = {28}, year = {2020}, abstract = {To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.}, language = {en} }