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In this note, we present an innovative approach called "homologous hypothesis tests" that focuses on cross-sectional comparisons of average tumor volumes at different time-points. By leveraging the correlation structure between time-points, our method enables highly efficient per time-point comparisons, providing inferences that are highly efficient as compared to those obtained from a standard two-sample t test. The key advantage of this approach lies in its user-friendliness and accessibility, as it can be easily employed by the broader scientific community through standard statistical software packages. [ABSTRACT FROM AUTHOR]

Motivation The transition from evaluating a single time point to examining the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and clustering challenging. Results We developed CONNECTOR, a data-driven framework able to analyze and inspect longitudinal data in a straightforward and revealing way. When used to analyze tumor growth kinetics over time in 1599 patient-derived xenograft growth curves from ovarian and colorectal cancers, CONNECTOR allowed the aggregation of time-series data through an unsupervised approach in informative clusters. We give a new perspective of mechanism interpretation, specifically, we define novel model aggregations and we identify unanticipated molecular associations with response to clinically approved therapies. Availability and implementation CONNECTOR is freely available under GNU GPL license at https://qbioturin.github.io/connector and https://doi.org/10.17504/protocols.io.8epv56e74g1b/v1. [ABSTRACT FROM AUTHOR]

In pre‐clinical oncology studies, tumor‐bearing animals are treated and observed over a period of time in order to measure and compare the efficacy of one or more cancer‐intervention therapies along with a placebo/standard of care group. A data analysis is typically carried out by modeling and comparing tumor volumes, functions of tumor volumes, or survival. Data analysis on tumor volumes is complicated because animals under observation may be euthanized prior to the end of the study for one or more reasons, such as when an animal's tumor volume exceeds an upper threshold. In such a case, the tumor volume is missing not‐at‐random for the time remaining in the study. To work around the non‐random missingness issue, several statistical methods have been proposed in the literature, including the rate of change in log tumor volume and partial area under the curve. In this work, an examination and comparison of the test size and statistical power of these and other popular methods for the analysis of tumor volume data is performed through realistic Monte Carlo computer simulations. The performance, advantages, and drawbacks of popular statistical methods for animal oncology studies are reported. The recommended methods are applied to a real data set. [ABSTRACT FROM AUTHOR]

Background: Nuclear receptor subfamily 1 group D member 1 (NR1D1), a nuclear receptor associated with a variety of physiological processes, has a low level in ovarian cancer tissues compared with adjacent normal tissues. However, its role in ovarian cancer remains unclear. Methods: The level of NR1D1 in ovarian cancer cells was determined by quantitative real-time PCR. Its role in ovarian cancer was explored through gain-of-function and lose-of-function. Cell growth was evaluated by CCK8 assay, immunofluorescence and flow cytometry. Western blot was conducted to assess the activation of JAK/STAT3 signaling pathway. A xenograft model of ovarian cancer was established to explore the role of NR1D1 in vivo. Results: Up-regulation of NR1D1 repressed the ovarian cancer cell proliferation and induced cell cycle arrest and apoptosis, while silencing NR1D1 promoted their proliferation and G1/S transition. In addition, the JAK/STAT3 signaling pathway, an intracellular signal transduction closely associated with cancer progression, was inhibited by NR1D1. Consistently, xenografts with NR1D1 over-expression grew more slowly in vivo than the controls. Furthermore, NR1D1 up-regulated the expression of suppressor of cytokine signaling 3 (SOCS3), an inhibitor of the JAK/STAT3 signaling pathway. Whereas, SOCS3 silencing abolished the function of NR1D1 over-expression on ovarian cancer growth and JAK/STAT3 signaling pathway. Conclusions: NR1D1 up-regulated the expression of SOCS3, resulting in suppression of the JAK/STAT3 signaling pathway, thus retarding the growth of ovarian cancer cells. This study highlights a profound role of NR1D1 in the treatment of ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: Nuclear receptor subfamily 1 group D member 1 (NR1D1), a nuclear receptor associated with a variety of physiological processes, has a low level in ovarian cancer tissues compared with adjacent normal tissues. However, its role in ovarian cancer remains unclear.Methods: The level of NR1D1 in ovarian cancer cells was determined by quantitative real-time PCR. Its role in ovarian cancer was explored through gain-of-function and lose-of-function. Cell growth was evaluated by CCK8 assay, immunofluorescence and flow cytometry. Western blot was conducted to assess the activation of JAK/STAT3 signaling pathway. A xenograft model of ovarian cancer was established to explore the role of NR1D1 in vivo.Results: Up-regulation of NR1D1 repressed the ovarian cancer cell proliferation and induced cell cycle arrest and apoptosis, while silencing NR1D1 promoted their proliferation and G1/S transition. In addition, the JAK/STAT3 signaling pathway, an intracellular signal transduction closely associated with cancer progression, was inhibited by NR1D1. Consistently, xenografts with NR1D1 over-expression grew more slowly in vivo than the controls. Furthermore, NR1D1 up-regulated the expression of suppressor of cytokine signaling 3 (SOCS3), an inhibitor of the JAK/STAT3 signaling pathway. Whereas, SOCS3 silencing abolished the function of NR1D1 over-expression on ovarian cancer growth and JAK/STAT3 signaling pathway.Conclusions: NR1D1 up-regulated the expression of SOCS3, resulting in suppression of the JAK/STAT3 signaling pathway, thus retarding the growth of ovarian cancer cells. This study highlights a profound role of NR1D1 in the treatment of ovarian cancer. [ABSTRACT FROM AUTHOR]

H2S is actual an endogenous signaling gas molecule and involved in a range of cell physiological processes. However, the mechanism of endogenous H2S regulating autophagy and apoptosis has not been thoroughly investigated. Here, we try to address this issue by using a H2S probe, (E)-2-(4-(4-(7-(diethylamino)-2-oxo-2H-chromene-3-carbonyl)-piperazin-1-yl)-styryl)-1, 3, 3-trimethyl-3H-indol-1-ium iodide (CPC), which could react with endogenous H2S. Herein, we reported that CPC inhibited autophagy and decreased the expression and activity of NF-E2-related factor 2 (Nrf2), then induced cell apoptosis. CPC inhibited autophagy and promoted apoptosis by inhibiting Nrf2 activation, which was H2S dependent. Furthermore, we found that CPC inhibited Nrf2 nucleus translocation by inhibiting glutathionylation of Kelch-like ECH-associated protein 1 (Keap1) at the Cys434 residue. CPC also inhibited various cancer cell growth, but had no effect on normal cell growth in vitro, and inhibited A549 cancer growth, but did not affect normal angiogenesis in vivo. Therefore, we not only found a new inhibitor of autophagy and Nrf2, but also suggested a novel mechanism that endogenous H2S could regulate autophagy, apoptosis and Nrf2 activity through regulating glutathionylation of Keap1 at the Cys434 residue. [ABSTRACT FROM AUTHOR]