This meta-analysis indicates that short and long sleep duration was significantly associated with increased risk of depression in adults.

systems that incorporate features of the tumor microenvironment and model the dynamic response to immune checkpoint blockade (ICB) may facilitate efforts in precision immuno-oncology and the development of effective combination therapies. Here, we demonstrate the ability to interrogate response to ICB using murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). MDOTS/PDOTS isolated from mouse and human tumors retain autologous lymphoid and myeloid cell populations and respond to ICB in short-term three-dimensional microfluidic culture. Response and resistance to ICB was recapitulated using MDOTS derived from established immunocompetent mouse tumor models. MDOTS profiling demonstrated that TBK1/IKKε inhibition enhanced response to PD-1 blockade, which effectively predicted tumor response Systematic profiling of secreted cytokines in PDOTS captured key features associated with response and resistance to PD-1 blockade. Thus, MDOTS/PDOTS profiling represents a novel platform to evaluate ICB using established murine models as well as clinically relevant patient specimens. Resistance to PD-1 blockade remains a challenge for many patients, and biomarkers to guide treatment are lacking. Here, we demonstrate feasibility of profiling of PD-1 blockade to interrogate the tumor immune microenvironment, develop therapeutic combinations, and facilitate precision immuno-oncology efforts..

BackgroundAcute renal failure from ischemia significantly contributes to morbidity and mortality in clinical settings, and strategies to improve renal resistance to ischemia are urgently needed. Here, we identified a novel pathway of renal protection from ischemia using ischemic preconditioning (IP).Methods and FindingsFor this purpose, we utilized a recently developed model of renal ischemia and IP via a hanging weight system that allows repeated and atraumatic occlusion of the renal artery in mice, followed by measurements of specific parameters or renal functions. Studies in gene-targeted mice for each individual adenosine receptor (AR) confirmed renal protection by IP in A1−/−, A2A−/−, or A3AR−/− mice. In contrast, protection from ischemia was abolished in A2BAR−/− mice. This protection was associated with corresponding changes in tissue inflammation and nitric oxide production. In accordance, the A2BAR-antagonist PSB1115 blocked renal protection by IP, while treatment with the selective A2BAR-agonist BAY 60–6583 dramatically improved renal function and histology following ischemia alone. Using an A2BAR-reporter model, we found exclusive expression of A2BARs within the reno-vasculature. Studies using A2BAR bone-marrow chimera conferred kidney protection selectively to renal A2BARs.ConclusionsThese results identify the A2BAR as a novel therapeutic target for providing potent protection from renal ischemia.

Tamoxifen, a selective oestrogen receptor modulator, has been used in the treatment of all stages of hormone-responsive breast cancer. However, tamoxifen shows partial oestrogenic activity in the uterus and its use has been associated with an increased incidence of endometrial cancer. The molecular explanation for these observations is not known. Here we show that tamoxifen and oestrogen have distinct but overlapping target gene profiles. Among the overlapping target genes, we identify a paired-box gene, PAX2, that is crucially involved in cell proliferation and carcinogenesis in the endometrium. Our experiments show that PAX2 is activated by oestrogen and tamoxifen in endometrial carcinomas but not in normal endometrium, and that this activation is associated with cancer-linked hypomethylation of the PAX2 promoter.

Therapies targeting estrogen receptor α (ERα, encoded by ESR1) have transformed the treatment of breast cancer. However, large numbers of women relapse, highlighting the need for the discovery of new regulatory targets modulating ERα pathways. An siRNA screen identified kinases whose silencing alters the estrogen response including those previously implicated in regulating ERα activity (such as mitogen-activated protein kinase and AKT). Among the most potent regulators was lemur tyrosine kinase-3 (LMTK3), for which a role has not previously been assigned. In contrast to other modulators of ERα activity, LMTK3 seems to have been subject to Darwinian positive selection, a noteworthy result given the unique susceptibility of humans to ERα+ breast cancer. LMTK3 acts by decreasing the activity of protein kinase C (PKC) and the phosphorylation of AKT (Ser473), thereby increasing binding of forkhead box O3 (FOXO3) to the ESR1 promoter. LMTK3 phosphorylated ERα, protecting it from proteasomal degradation in vitro. Silencing of LMTK3 reduced tumor volume in an orthotopic mouse model and abrogated proliferation of ERα+ but not ERα- cells, indicative of its role in ERα activity. In human cancers, LMTK3 abundance and intronic polymorphisms were significantly associated with disease-free and overall survival and predicted response to endocrine therapies. These findings yield insights into the natural history of breast cancer in humans and reveal LMTK3 as a new therapeutic target.

Purpose: In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series. Methods: Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols. Results: Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use of the previous normal-dose scan via the presented ndiNLM algorithm is noticeable as compared to a similar approach without using the previous normal-dose scan. Conclusions: For low-dose CT image restoration, the presented ndiNLM method is robust in preserving the spatial resolution and identifying the low-contrast structure. The authors can draw the conclusion that the presented ndiNLM algorithm may be useful for some clinical applications such as in perfusion imaging, radiotherapy, tumor surveillance, etc.

The outcomes of patients with SCLC have not yet been substantially impacted by the revolution in precision oncology, primarily owing to a paucity of genetic alterations in actionable driver oncogenes. Nevertheless, systemic therapies that include immunotherapy are beginning to show promise in the clinic. Although, these results are encouraging, many patients do not respond to, or rapidly recur after, current regimens, necessitating alternative or complementary therapeutic strategies. In this review, we discuss ongoing investigations into the pathobiology of this recalcitrant cancer and the therapeutic vulnerabilities that are exposed by the disease state. Included within this discussion, is a snapshot of the current biomarker and clinical trial landscapes for SCLC. Finally, we identify key knowledge gaps that should be addressed to advance the field in pursuit of reduced SCLC mortality. This review largely summarizes work presented at the Third Biennial International Association for the Study of Lung Cancer SCLC Meeting.

Long non-coding RNAs (lncRNAs) have been demonstrated to be a critical role in cancer progression and prognosis. However, little is known about the pathological role of lncRNA HOXA transcript at the distal tip (HOTTIP) in tongue squamous cell carcinoma (TSCC) patients. The aim of this study is to measure the expression of lncRNA HOTTIP in TSCC patients and to explore the clinical significance of the lncRNA HOTTIP. The expression of lncRNA HOTTIP was measured in 86 TSCC tissues and 14 adjacent non-malignant tissues using qRT-PCR. In our study, results indicated that lncRNA HOTTIP was highly expressed in TSCC compared with adjacent non-malignant tissues (P < 0.001) and positively correlated with T stage (T1-2 vs. T3-4, P = 0.023), clinical stage (I-II stages vs. III-IV stages, P = 0.018), and distant metastasis (absent vs. present, P = 0.031) in TSCC patients. Furthermore, we also found that lncRNA HOTTIP overexpression was an unfavorable prognostic factor in TSCC patients (P < 0.001), regardless of T stage, distant metastasis, and clinical stage. Finally, overexpression of lncRNA HOTTIP was supposed to be an independent poor prognostic factor for TSCC patients through multivariate analysis (P = 0.023). In conclusion, increased lncRNA HOTTIP expression may be serve as an unfavorable prognosis predictor for TSCC patients. Nevertheless, further investigation with a larger sample size is needed to support our results.