Survival models with preclustered gene groups as covariates

An important application of high dimensional gene expression measurements is the risk prediction and the interpretation of the variables in the resulting survival models. A major problem in this context is the typically large number of genes compared to the number of observations (individuals). Feature selection procedures can generate predictive models with high prediction accuracy and at the same time low model complexity. However, interpretability of the resulting models is still limited due to little knowledge on many of the remaining selected genes. Thus, we summarize genes as gene groups defined by the hierarchically structured Gene Ontology (GO) and include these gene groups as covariates in the hazard regression models. Since expression profiles within GO groups are often heterogeneous, we present a new method to obtain subgroups with coherent patterns. We apply preclustering to genes within GO groups according to the correlation of their gene expression measurements

Role of the progesterone receptor for paclitaxel resistance in primary breast cancer

Paclitaxel plays an important role in the treatment of primary breast cancer. However, a substantial proportion of patients treated with paclitaxel does not appear to derive any benefit from this therapy. We performed a prospective study using tumour cells isolated from 50 primary breast carcinomas. Sensitivity of primary tumour cells to paclitaxel was determined in a clinically relevant range of concentrations (0.85–27.2 μg ml−1 paclitaxel) using an ATP assay. Chemosensitivity data were used to study a possible association with immunohistochemically determined oestrogen and progesterone receptor (ER and PR) status, as well as histopathological parameters. Progesterone receptor (PR) mRNA expression was also determined by quantitative RT–PCR. We observed a clear association of the PR status with chemosensitivity to paclitaxel. Higher levels of immunohistochemically detected PR expression correlated with decreased chemosensitivity (P=0.008). Similarly, high levels of PR mRNA expression were associated with decreased paclitaxel chemosensitivity (P=0.007). Cells from carcinomas with T-stages 3 and 4 were less sensitive compared to stages 1 and 2 (P=0.013). Multiple regression analysis identified PR receptor status and T-stage as independent predictors of paclitaxel chemosensitivity, whereas the ER, N-stage, grading and age were not influential. In conclusion, in vitro sensitivity to paclitaxel was higher for PR-negative compared with PR-positive breast carcinoma cells. Thus, PR status should be considered as a possible factor of influence when designing new trials and chemotherapy protocols

The pyrrolizidine alkaloid senecionine induces CYP-dependent destruction of sinusoidal endothelial cells and cholestasis in mice

Pyrrolizidine alkaloids (PAs) are widely occurring phytotoxins which can induce severe liver damage in humans and other mammalian species by mechanisms that are not fully understood. Therefore, we investigated the development of PA hepatotoxicity in vivo, using an acutely toxic dose of the PA senecionine in mice, in combination with intravital two-photon microscopy, histology, clinical chemistry, and in vitro experiments with primary mouse hepatocytes and liver sinusoidal endothelial cells (LSECs). We observed pericentral LSEC necrosis together with elevated sinusoidal marker proteins in the serum of senecionine-treated mice and increased sinusoidal platelet aggregation in the damaged tissue regions. In vitro experiments showed no cytotoxicity to freshly isolated LSECs up to 500 µM senecionine. However, metabolic activation of senecionine by preincubation with primary mouse hepatocytes increased the cytotoxicity to cultivated LSECs with an EC50 of approximately 22 µM. The cytochrome P450 (CYP)-dependency of senecionine bioactivation was confirmed in CYP reductase-deficient mice where no PA-induced hepatotoxicity was observed. Therefore, toxic metabolites of senecionine are generated by hepatic CYPs, and may be partially released from hepatocytes leading to destruction of LSECs in the pericentral region of the liver lobules. Analysis of hepatic bile salt transport by intravital two-photon imaging revealed a delayed uptake of a fluorescent bile salt analogue from the hepatic sinusoids into hepatocytes and delayed elimination. This was accompanied by transcriptional deregulation of hepatic bile salt transporters like Abcb11 or Abcc1. In conclusion, senecionine destroys LSECs although the toxic metabolite is formed in a CYP-dependent manner in the adjacent pericentral hepatocytes.</p

Genome-wide expression changes induced by bisphenol A, F and S in human stem cell derived hepatocyte-like cells

Acknowledgments BLV and DCH were funded by an award from the Chief Scientist Office (TCS 16/37). This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 681002 (EU-ToxRisk) and from TransQST (no. 116030).Peer reviewedPublisher PD

Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer—comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial

Background: Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. Patients and methods: After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age 2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). Results: The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005). Conclusion: The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as O

Эпидемиологические исследования в сексологии

Представлены результаты эпидемиологического исследования, позволившие автору на примере обследования 1000 человек популяции из западного региона Украины сформулировать основные закономерности изменения отношения к браку и сексуального поведения мужчин и женщин в современном обществе.The findings of epidemiological study, which allowed the author to formulate main regularities of the changes in the attitude to the marriage and sexual behavior of men and women in the contemporary society on the example of the examination of 1000 persons from the western regions of Ukraine, are presented

Prognostic Impact of Immunoglobulin Kappa C (IGKC) in Early Breast Cancer

We studied the prognostic impact of tumor immunoglobulin kappa C (IGKC) mRNA expression as a marker of the humoral immune system in the FinHer trial patient population, where 1010 patients with early breast cancer were randomly allocated to either docetaxel-containing or vinorelbine-containing adjuvant chemotherapy. HER2-positive patients were additionally allocated to either trastuzumab or no trastuzumab. Hormone receptor-positive patients received tamoxifen. IGKC was evaluated in 909 tumors using quantitative real-time polymerase chain reaction, and the influence on distant disease-free survival (DDFS) was examined using univariable and multivariable Cox regression and Kaplan–Meier estimates. Interactions were analyzed using Cox regression. IGKC expression, included as continuous variable, was independently associated with DDFS in a multivariable analysis also including age, molecular subtype, grade, and pT and pN stage (HR 0.930, 95% CI 0.870–0.995, p = 0.034). An independent association with DDFS was also found in a subset analysis of triple-negative breast cancers (TNBC) (HR 0.843, 95% CI 0.724–0.983, p = 0.029), but not in luminal (HR 0.957, 95% CI 0.867–1.056, p = 0.383) or HER2-positive (HR 0.933, 95% CI 0.826–1.055, p = 0.271) cancers. No significant interaction between IGKC and chemotherapy or trastuzumab administration was detected (Pinteraction = 0.855 and 0.684, respectively). These results show that humoral immunity beneficially influences the DDFS of patients with early TNBC