TY - JOUR A1 - Rasche, Leo A1 - Kortüm, K. Martin A1 - Raab, Marc S. A1 - Weinhold, Niels T1 - The impact of tumor heterogeneity on diagnostics and novel therapeutic strategies in multiple myeloma JF - International Journal of Molecular Sciences N2 - 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. KW - multiple myeloma KW - spatial heterogeneity KW - risk stratification KW - minimal residual disease KW - targeted therapy KW - clinical imaging KW - immunotherapy KW - daratumumab Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-285402 SN - 1422-0067 VL - 20 IS - 5 ER - TY - JOUR A1 - Löhr, Mario A1 - Härtig, Wolfgang A1 - Schulze, Almut A1 - Kroiß, Matthias A1 - Sbiera, Silviu A1 - Lapa, Constantin A1 - Mages, Bianca A1 - Strobel, Sabrina A1 - Hundt, Jennifer Elisabeth A1 - Bohnert, Simone A1 - Kircher, Stefan A1 - Janaki-Raman, Sudha A1 - Monoranu, Camelia-Maria T1 - SOAT1: A suitable target for therapy in high-grade astrocytic glioma? JF - International Journal of Molecular Sciences N2 - 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. KW - SOAT1 KW - glioblastoma KW - astrocytoma KW - IDH1/2 KW - lipid droplets KW - mitotane KW - targeted therapy Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-284178 SN - 1422-0067 VL - 23 IS - 7 ER - TY - JOUR A1 - Lodde, Georg A1 - Forschner, Andrea A1 - Hassel, Jessica A1 - Wulfken, Lena M. A1 - Meier, Friedegund A1 - Mohr, Peter A1 - Kähler, Katharina A1 - Schilling, Bastian A1 - Loquai, Carmen A1 - Berking, Carola A1 - Hüning, Svea A1 - Schatton, Kerstin A1 - Gebhardt, Christoffer A1 - Eckardt, Julia A1 - Gutzmer, Ralf A1 - Reinhardt, Lydia A1 - Glutsch, Valerie A1 - Nikfarjam, Ulrike A1 - Erdmann, Michael A1 - Stang, Andreas A1 - Kowall, Bernd A1 - Roesch, Alexander A1 - Ugurel, Selma A1 - Zimmer, Lisa A1 - Schadendorf, Dirk A1 - Livingstone, Elisabeth T1 - Factors influencing the adjuvant therapy decision: results of a real-world multicenter data analysis of 904 melanoma patients JF - Cancers N2 - 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. KW - melanoma KW - adjuvant treatment KW - checkpoint blocker KW - targeted therapy KW - BRAF KW - PD-1 Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-239583 SN - 2072-6694 VL - 13 IS - 10 ER - TY - JOUR A1 - Baur, Florentin A1 - Nietzer, Sarah L. A1 - Kunz, Meik A1 - Saal, Fabian A1 - Jeromin, Julian A1 - Matschos, Stephanie A1 - Linnebacher, Michael A1 - Walles, Heike A1 - Dandekar, Thomas A1 - Dandekar, Gudrun T1 - Connecting cancer pathways to tumor engines: a stratification tool for colorectal cancer combining human in vitro tissue models with boolean in silico models JF - Cancers N2 - 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. KW - in silico simulation KW - 3D tissue models KW - colorectal cancer KW - BRAF mutation KW - targeted therapy KW - stratification Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193798 SN - 2072-6694 VL - 12 IS - 1 ER -