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Background: Hereditary spastic paraplegias (HSPs) are characterised by lower limb spasticity due to degeneration of the corticospinal tract. We set out for an electrophysiological characterisation of motor and sensory tracts in patients with HSP.
Methods: We clinically and electrophysiologically examined a cohort of 128 patients with genetically confirmed or clinically probable HSP. Motor evoked potentials (MEPs) to arms and legs, somato-sensory evoked potentials of median and tibial nerves, and nerve conduction studies of tibial, ulnar, sural, and radial nerves were assessed.
Results: Whereas all patients showed clinical signs of spastic paraparesis, MEPs were normal in 27% of patients and revealed a broad spectrum with axonal or demyelinating features in the others. This heterogeneity can at least in part be explained by different underlying genotypes, hinting for distinct pathomechanisms in HSP subtypes. In the largest subgroup, SPG4, an axonal type of damage was evident. Comprehensive electrophysiological testing disclosed a more widespread affection of long fibre tracts involving peripheral nerves and the sensory system in 40%, respectively. Electrophysiological abnormalities correlated with the severity of clinical symptoms.
Conclusions: Whereas HSP is primarily considered as an upper motoneuron disorder, our data suggest a more widespread affection of motor and sensory tracts in the central and peripheral nervous system as a common finding in HSP. The distribution patterns of electrophysiological abnormalities were associated with distinct HSP genotypes and could reflect different underlying pathomechanisms. Electrophysiological measures are independent of symptomatic treatment and may therefore serve as a reliable biomarker in upcoming HSP trials.
Deregulated expression of MYC is a driver of colorectal carcinogenesis, necessitating novel strategies to inhibit MYC function. The ubiquitin ligase HUWE1 (HECTH9, ARF-BP1, MULE) associates with both MYC and the MYC-associated protein MIZ1. We show here that HUWE1 is required for growth of colorectal cancer cells in culture and in orthotopic xenograft models. Using high-throughput screening, we identify small molecule inhibitors of HUWE1, which inhibit MYC-dependent transactivation in colorectal cancer cells, but not in stem and normal colon epithelial cells. Inhibition of HUWE1 stabilizes MIZ1. MIZ1 globally accumulates on MYC target genes and contributes to repression of MYC-activated target genes upon HUWE1 inhibition. Our data show that transcriptional activation by MYC in colon cancer cells requires the continuous degradation of MIZ1 and identify a novel principle that allows for inhibition of MYC function in tumor cells.
(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.