Cancer stem cells (CSCs) account for tumor initiation, invasiveness, metastasis, and recurrence in a broad range of human cancers. Although being a key player in cancer development and progression by stimulating proliferation and metastasis and preventing apoptosis, the role of the transcription factor NF-κB in cancer stem cells is still underestimated. In the present review, we will evaluate the role of NF-κB in CSCs of glioblastoma multiforme, ovarian cancer, multiple myeloma, lung cancer, colon cancer, prostate cancer, as well as cancer of the bone. Next to summarizing current knowledge regarding the presence and contribution of CSCs to the respective types of cancer, we will emphasize NF-κB-mediated signaling pathways directly involved in maintaining characteristics of cancer stem cells associated to tumor progression. Here, we will also focus on the status of NF-κB-activity predominantly in CSC populations and the tumor mass. Genetic alterations leading to NF-κB activity in glioblastoma, ependymoma, and multiple myeloma will be discussed.

Cells of glioblastoma, the most frequent primary malignant brain tumor, are characterized by their rapid growth and infiltration of adjacent healthy brain parenchyma, which reflects their aggressive biological behavior. In order to maintain their excessive proliferation and invasion, glioblastomas exploit the innate biological capacities of the patients suffering from this tumor. The pathways involved in cell cycle regulation and apoptosis are the mechanisms most commonly affected. The following work reviews the regulatory pathways of cell growth in general as well as the dysregulated cell cycle and apoptosis relevant mechanisms observed in glioblastomas. We then describe the molecular targeting of the current established adjuvant therapy and present ongoing trials or completed studies on specific promising therapeutic agents that induce cell cycle arrest and apoptosis of glioblastoma cells.

Molecularly targeted therapies using receptor inhibitors, small molecules or monoclonal antibodies are routinely applied in oncology. Verification of target expression should be mandatory prior to initiation of therapy, yet, determining the expression status is most challenging in recurrent glioblastoma (GBM) where most patients are not eligible for second-line surgery. Because very little is known on the consistency of expression along the clinical course we here explored common drug targets in paired primary vs. recurrent GBM tissue samples. Paired surgical tissue samples were derived from a homogeneously treated cohort of 34 GBM patients. All patients received radiotherapy and temozolomide chemotherapy. Verification of common drug targets included immunohistological analysis of PDGFR-β, FGFR-2, FGFR-3, and mTOR-pathway component (phospho-mTORSer2448) as well as molecular, MLPA-based analysis of specific copy number aberrations at the gene loci of ALK, PDGFRA, VEGFR2/KDR, EGFR, MET, and FGFR1. Paired tumor tissue exhibited significant changes of expression in 9 of the 10 investigated druggable targets (90%). Only one target (FGFR1) was found “unchanged”, since dissimilar expression was observed in only one of the 34 paired tumor tissue samples. All other targets were variably expressed with an 18–56% discordance rate between primary and recurrent tissue. The high incidence of dissimilar target expression status in clinical samples from primary vs. recurrent GBM suggests clinically relevant heterogeneity along the course of disease. Molecular target expression, as determined at primary diagnosis, may not necessarily present rational treatment clues for the clinical care of recurrent GBM. Further studies need to analyze the therapeutic impact of longitudinal heterogeneity in GBM.

The computational capabilities of neuronal networks are fundamentally constrained by their specific connectivity. Previous studies of cortical connectivity have mostly been carried out in rodents; whether the principles established therein also apply to the evolutionarily expanded human cortex is unclear. We studied network properties within the human temporal cortex using samples obtained from brain surgery. We analyzed multineuron patch-clamp recordings in layer 2-3 pyramidal neurons and identified substantial differences compared with rodents. Reciprocity showed random distribution, synaptic strength was independent from connection probability, and connectivity of the supragranular temporal cortex followed a directed and mostly acyclic graph topology. Application of these principles in neuronal models increased dimensionality of network dynamics, suggesting a critical role for cortical computation.