Filtern
Volltext vorhanden
- ja (3)
Gehört zur Bibliographie
- ja (3) (entfernen)
Dokumenttyp
Sprache
- Englisch (3) (entfernen)
Schlagworte
- cancer (3) (entfernen)
Institut
- Urologische Klinik und Poliklinik (3) (entfernen)
Livin/BIRC7 is a member of the inhibitors of apoptosis proteins family, which are involved in tumor development through the inhibition of caspases. Aim was to investigate the expression of livin and other members of its pathway in adrenocortical tumors and in the adrenocortical carcinoma (ACC) cell line NCI-H295R.
The mRNA expression of livin, its isoforms α and β, XIAP, CASP3 and DIABLO was evaluated by qRT-PCR in 82 fresh-frozen adrenal tissues (34 ACC, 25 adenomas = ACA, 23 normal adrenal glands = NAG). Livin protein expression was assessed by immunohistochemistry in 270 paraffin-embedded tissues (192 ACC, 58 ACA, 20 NAG). Livin, CASP3 and cleaved caspase-3 were evaluated in NCI-H295R after induction of livin overexpression.
Relative livin mRNA expression was significantly higher in ACC than in ACA and NAG (0.060 ± 0.116 vs 0.004 ± 0.014 and 0.002 ± 0.009, respectively, p < 0.01), being consistently higher in tumors than in adjacent NAG and isoform β more expressed than α. No significant differences in CASP3, XIAP and DIABLO levels were found among these groups. In immunohistochemistry, livin was localized in both cytoplasm and nuclei. The ratio between cytoplasmic and nuclear staining was significantly higher in ACC (1.51 ± 0.66) than in ACA (0.80 ± 0.35) and NAG (0.88 ± 0.27; p < 0.0001). No significant correlations were observed between livin expression and histopathological parameters or clinical outcome. In NCI-H295R cells, the livin overexpression slightly reduced the activation of CASP3, but did not correlate with cell viability.
In conclusion, livin is specifically over-expressed in ACC, suggesting that it might be involved in adrenocortical tumorigenesis and represent a new molecular marker of malignancy.
Personalized oncology is a rapidly evolving area and offers cancer patients therapy options that are more specific than ever. However, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP)) on three datasets of metastases (n = 682 samples) with three different data transformations (unprocessed, log10 as well as log10 + 1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n = 616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between the site of resection and cluster formation outcome could be demonstrated, or for datasets consisting of solely metastasis or mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in the interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results highlight the need for a more thorough examination of parameters used in the analysis of clusters.
At the beginning of the COVID-19 pandemic, patients with primary and secondary immune disorders — including patients suffering from cancer — were generally regarded as a high-risk population in terms of COVID-19 disease severity and mortality. By now, scientific evidence indicates that there is substantial heterogeneity regarding the vulnerability towards COVID-19 in patients with immune disorders. In this review, we aimed to summarize the current knowledge about the effect of coexistent immune disorders on COVID-19 disease severity and vaccination response. In this context, we also regarded cancer as a secondary immune disorder. While patients with hematological malignancies displayed lower seroconversion rates after vaccination in some studies, a majority of cancer patients’ risk factors for severe COVID-19 disease were either inherent (such as metastatic or progressive disease) or comparable to the general population (age, male gender and comorbidities such as kidney or liver disease). A deeper understanding is needed to better define patient subgroups at a higher risk for severe COVID-19 disease courses. At the same time, immune disorders as functional disease models offer further insights into the role of specific immune cells and cytokines when orchestrating the immune response towards SARS-CoV-2 infection. Longitudinal serological studies are urgently needed to determine the extent and the duration of SARS-CoV-2 immunity in the general population, as well as immune-compromised and oncological patients.