@article{MarquardtSolimandoKerscheretal.2021,
  author    = {Marquardt, Andr{\´e} and Solimando, Antonio Giovanni and Kerscher, Alexander and Bittrich, Max and Kalogirou, Charis and K{\"u}bler, Hubert and Rosenwald, Andreas and Bargou, Ralf and Kollmannsberger, Philip and Schilling, Bastian and Meierjohann, Svenja and Krebs, Markus},
  title     = {Subgroup-Independent Mapping of Renal Cell Carcinoma — Machine Learning Reveals Prognostic Mitochondrial Gene Signature Beyond Histopathologic Boundaries},
  series = {Frontiers in Oncology},
  volume    = {11},
  journal   = {Frontiers in Oncology},
  issn      = {2234-943X},
  doi       = {10.3389/fonc.2021.621278},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232107},
  year      = {2021},
  abstract  = {Background: Renal cell carcinoma (RCC) is divided into three major histopathologic groups—clear cell (ccRCC), papillary (pRCC) and chromophobe RCC (chRCC). We performed a comprehensive re-analysis of publicly available RCC datasets from the TCGA (The Cancer Genome Atlas) database, thereby combining samples from all three subgroups, for an exploratory transcriptome profiling of RCC subgroups. Materials and Methods: We used FPKM (fragments per kilobase per million) files derived from the ccRCC, pRCC and chRCC cohorts of the TCGA database, representing transcriptomic data of 891 patients. Using principal component analysis, we visualized datasets as t-SNE plot for cluster detection. Clusters were characterized by machine learning, resulting gene signatures were validated by correlation analyses in the TCGA dataset and three external datasets (ICGC RECA-EU, CPTAC-3-Kidney, and GSE157256). Results: Many RCC samples co-clustered according to histopathology. However, a substantial number of samples clustered independently from histopathologic origin (mixed subgroup)—demonstrating divergence between histopathology and transcriptomic data. Further analyses of mixed subgroup via machine learning revealed a predominant mitochondrial gene signature—a trait previously known for chRCC—across all histopathologic subgroups. Additionally, ccRCC samples from mixed subgroup presented an inverse correlation of mitochondrial and angiogenesis-related genes in the TCGA and in three external validation cohorts. Moreover, mixed subgroup affiliation was associated with a highly significant shorter overall survival for patients with ccRCC—and a highly significant longer overall survival for chRCC patients. Conclusions: Pan-RCC clustering according to RNA-sequencing data revealed a distinct histology-independent subgroup characterized by strengthened mitochondrial and weakened angiogenesis-related gene signatures. Moreover, affiliation to mixed subgroup went along with a significantly shorter overall survival for ccRCC and a longer overall survival for chRCC patients. Further research could offer a therapy stratification by specifically addressing the mitochondrial metabolism of such tumors and its microenvironment.},
  language  = {en}
}
@article{JessenKressBaluapurietal.2020,
  author    = {Jessen, Christina and Kreß, Julia K. C. and Baluapuri, Apoorva and Hufnagel, Anita and Schmitz, Werner and Kneitz, Susanne and Roth, Sabine and Marquardt, Andr{\´e} and Appenzeller, Silke and Ade, Casten P. and Glutsch, Valerie and Wobser, Marion and Friedmann-Angeli, Jos{\´e} Pedro and Mosteo, Laura and Goding, Colin R. and Schilling, Bastian and Geissinger, Eva and Wolf, Elmar and Meierjohann, Svenja},
  title     = {The transcription factor NRF2 enhances melanoma malignancy by blocking differentiation and inducing COX2 expression},
  series = {Oncogene},
  volume    = {39},
  journal   = {Oncogene},
  issn      = {0950-9232},
  doi       = {10.1038/s41388-020-01477-8},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-235064},
  pages     = {6841-6855},
  year      = {2020},
  abstract  = {The transcription factor NRF2 is the major mediator of oxidative stress responses and is closely connected to therapy resistance in tumors harboring activating mutations in the NRF2 pathway. In melanoma, such mutations are rare, and it is unclear to what extent melanomas rely on NRF2. Here we show that NRF2 suppresses the activity of the melanocyte lineage marker MITF in melanoma, thereby reducing the expression of pigmentation markers. Intriguingly, we furthermore identified NRF2 as key regulator of immune-modulating genes, linking oxidative stress with the induction of cyclooxygenase 2 (COX2) in an ATF4-dependent manner. COX2 is critical for the secretion of prostaglandin E2 and was strongly induced by H\(_2\)O\(_2\) or TNFα only in presence of NRF2. Induction of MITF and depletion of COX2 and PGE2 were also observed in NRF2-deleted melanoma cells in vivo. Furthermore, genes corresponding to the innate immune response such as RSAD2 and IFIH1 were strongly elevated in absence of NRF2 and coincided with immune evasion parameters in human melanoma datasets. Even in vitro, NRF2 activation or prostaglandin E2 supplementation blunted the induction of the innate immune response in melanoma cells. Transcriptome analyses from lung adenocarcinomas indicate that the observed link between NRF2 and the innate immune response is not restricted to melanoma.},
  language  = {en}
}