Citations

AbstractThis study used resting state functional magnetic resonance imaging (rsfMRI) to investigate whole brain networks in patients with persistent postural perceptual dizziness (PPPD). We compared rsfMRI data from 38 patients with PPPD and 38 healthy controls using whole brain and region of interest analyses. We examined correlations among connectivity and clinical variables and tested the ability of a machine learning algorithm to classify subjects using rsfMRI results. Patients with PPPD showed: (a) increased connectivity of subcallosal cortex with left superior lateral occipital cortex and left middle frontal gyrus, (b) decreased connectivity of left hippocampus with bilateral central opercular cortices, left posterior opercular cortex, right insular cortex and cerebellum, and (c) decreased connectivity between right nucleus accumbens and anterior left temporal fusiform cortex. After controlling for anxiety and depression as covariates, patients with PPPD still showed decreased connectivity between left hippocampus and right inferior frontal gyrus, bilateral temporal lobes, bilateral insular cortices, bilateral central opercular cortex, left parietal opercular cortex, bilateral occipital lobes and cerebellum (bilateral lobules VI and V, and left I–IV). Dizziness handicap, anxiety, and depression correlated with connectivity in clinically meaningful brain regions. The machine learning algorithm correctly classified patients and controls with a sensitivity of 78.4%, specificity of 76.9%, and area under the curve = 0.88 using 11 connectivity parameters. Patients with PPPD showed reduced connectivity among the areas involved in multisensory vestibular processing and spatial cognition, but increased connectivity in networks linking visual and emotional processing. Connectivity patterns may become an imaging biomarker of PPPD.

Mitochondria are dynamic organelles that are able to change their morphology and cellular distribution by either fission or fusion. However, the molecular mechanisms controlling mitochondrial dynamics in vascular endothelial cells (ECs) remain largely unknown. In this study, we observed that knockdown of microtubule‐associated tumor suppressor 1 (MTUS1) in ECs inhibited tube formation and migration, accompanied with decreased promigratory signalings. We showed that MTUS1 was localized in the outer membrane of mitochondria in ECs. Knockdown of MTUS1 disturbed the elongated mitochondrial network and induced the formation of perinuclear clusters of mitochondria. Importantly, mitochondrial motility and fusion were suppressed, whereas generation of reactive oxygen species was increased in MTUS1 knockdown ECs. Mechanistically, we showed that the N‐terminal coiled‐coil domain of MTUS1 interacted with the mitochondrial membrane proteins, mitofusin‐1 and mitofusin‐2, to maintain mitochondrial morphology in ECs. This study illustrated a novel role of MTUS1 in mitochondrial morphology and EC angiogenic responses.—Wang Y., Huang Y., Liu, Y., Li, J., Hao, Y., Yin, P., Liu, Z., Chen J., Wang Y., Wang N., Zhang P., Microtubule associated tumor suppressor 1 interacts with mitofusins to regulate mitochondrial morphology in endothelial cells. FASEB J . 32, 4504–4518 (2018). www.fasebj.org

SummaryThe landscape of oncology drug development has recently changed with the emergence of molecularly targeted agents and immunotherapies. These new therapeutic agents appear more likely to induce multiple low or moderate grade toxicities rather than dose limiting toxicities. Various model-based dose finding designs and toxicity severity scoring systems have been proposed to account for toxicity grades, but they are difficult to implement because of the use of complicated dose–toxicity models and the requirement to refit the model at each decision of dose escalation and de-escalation. We propose a generalized Bayesian optimal interval design, gBOIN, that accommodates various existing toxicity grade scoring systems under a unified framework. As a model-assisted design, gBOIN derives its optimal decision rule on the basis of the exponential family of distributions but is carried out in a simple way as the algorithm-based design: its decision of dose escalation and de-escalation involves only a simple comparison of the sample mean of the end point with two prespecified dose escalation and de-escalation boundaries. No model fitting is needed. We show that gBOIN has the desirable finite property of coherence and a large sample property of consistency. Numerical studies show that gBOIN yields good performance that is comparable with or superior to that of some existing, more complicated model-based designs. A Web application for implementing gBOIN is freely available from http://www.trialdesign.org.

Abstract Background. Dysregulation of the estrogen receptor gene (ESR1) is an established mechanism of inducing endocrine therapy resistance. We previously discovered a chromosomal translocation event generating an estrogen receptor gene fused in-frame to C-terminal sequences of YAP1 (ESR1-YAP1) that contributed to endocrine therapy resistance in estrogen receptor positive (ER+) breast cancer models. This study compares functional, transcriptional, and pharmacological properties of additional ESR1 gene fusion events of both early stage (ESR1-NOP2) late stage (ESR1-YAP1 and ESR1-PCDH11x) breast cancers to gain a better understanding of therapeutic resistance and metastasis. Understanding the role of ESR1 fusions in inducing metastasis is critical, since the primary cause of death in breast cancer patients is through metastasis to distant sites. Methods. RNA-seq screens identified ESR1 fusions from early and late stage, endocrine therapy resistant breast tumor samples. Functional experiments were conducted using ER+ breast cancer cell lines, xenograft, and PDX models to test the ability of ESR1 fusions to induce therapeutic resistance and metastasis. ChIP-seq and RNA-seq were performed to examine transcriptional properties and differential gene expression induced by the fusions which directed subsequent pharmacological experiments with a CDK4/6 inhibitor. Results. ESR1-YAP1 and ESR1-PCDH11x promoted estrogen-independent and fulvestrant-resistant growth in vitro and induced greater tumor growth and increased metastatic capacity to the lungs of xenografted mice. In contrast, the ESR1-NOP2 fusion was sensitive to low estrogen conditions in vitro, and did not promote tumor growth. RNA-seq profiling revealed E2F targets pathway as the most highly enriched pathway induced by the ESR1 fusions. IHC revealed higher levels of pRb in ESR1-YAP1 and ESR1-PCDH11x xenograft tumors and subsequent CDK4/6 inhibition completely blocked tumor growth in an ESR1-YAP1 PDX model. Integrating RNA-seq with ChIP-seq data, we discovered a set of EMT and metastasis genes bound by all ESR1 fusions and WT-ER, but whose expression was strongly and uniquely up-regulated only by the ESR1-YAP1 and ESR1-PCDH11x fusions. These studies also revealed gained sites bound only by the ESR1-YAP1 and ESR1-PCDH11x fusions, not bound by WT-ER nor ESR1-NOP2. Genes mapping to these sites have a role in metastatic biology and were highly up-regulated by the YAP1 and PCDH11x fusions, potentially mediated by long range transcriptional activation. Conclusion. ESR1-YAP1 and ESR1-PCDH11x are driver fusions that occur in drug-resistant, advanced stage breast cancer and are a new class of recurrent somatic mutation that can cause acquired endocrine therapy resistance, yet can be treated with CDK4/6 inhibition. These driver fusions also confer increased metastatic ability through their ability to drive expression of genes that contribute to EMT and metastasis. In contrast, ESR1-NOP2 did not produce functional protein and appears to be a passenger event. These studies may provide pre-clinical rationale for targeting ESR1 translocated breast tumors, since the presence of an ESR1 driver fusion places a patient in a therapeutic category where none of the currently available endocrine therapies are likely to be effective. Citation Format: Lei JT, Shao J, Zhang J, Iglesia M, Chan DW, Cao J, Anurag M, Singh P, Haricharan S, Kavuri SM, Matsunuma R, Schmidt C, Kosaka Y, Crowder R, Hoog J, Phommaly C, Goncalves R, Ramalho S, Rodrigues-Peres RM, Lai W-C, Hampton O, Rogers A, Tobias E, Parikh P, Davies S, Ma C, Suman V, Hunt K, Watson M, Hoadley KA, Thompson A, Perou CM, Creighton CJ, Maher C, Ellis MJ. ESR1 gene fusions drive endocrine therapy resistance and metastasis in breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD8-03.