Novel Oral Derivative UD-017, a Highly Selective CDK7 Inhibitor, Exhibits Anticancer Activity by Inducing Cell-Cycle Arrest and Apoptosis in Human Colorectal Cancer

Objective: This study aimed to investigate the anticancer profile of a new cyclin-dependent kinase 7 (CDK7) inhibitor, UD-017, by examining its mechanism of action using HCT-116 colorectal cancer cells. Methods: The anticancer properties of UD-017 were assessed using several assays, including in vitro kinase, proliferation, and apoptosis assays, western blot analysis, and an in vivo xenograft mouse model. Results: UD-017 significantly inhibited CDK7 activity (IC50 = 16 nM) with high selectivity in an in vitro kinase assay testing a panel of over 300 proteins and lipid kinases. UD-017 also inhibited the growth of HCT-116 cells (GI50 = 19 nM) and inhibited the phosphorylation of various downstream mediators of CDK7 signaling. In cell cycle and apoptosis assays using HCT-116 cells, UD-017 increased the number of cells in both G1 and G2/M phases and induced apoptosis. In vivo, UD-017 inhibited tumor growth in an HCT-116 xenograft mouse model by 33%, 64%, and 88% at doses of 25, 50, and 100 mg/kg, respectively, with clear dose-dependency. Co-administration of 5-FU and 50 mg/kg UD-017 had a strong synergistic effect, as reflected in the complete inhibition of tumor growth. Conclusion: CDK7 may play a major role in colorectal cancer growth by regulating the cell cycle and apoptosis. UD-017 is a promising candidate therapeutic agent for the treatment of cancer involving CDK7 signaling

Prediction of stroke patients’ bedroom-stay duration: machine-learning approach using wearable sensor data

Background: The importance of being physically active and avoiding staying in bed has been recognized in stroke rehabilitation. However, studies have pointed out that stroke patients admitted to rehabilitation units often spend most of their day immobile and inactive, with limited opportunities for activity outside their bedrooms. To address this issue, it is necessary to record the duration of stroke patients staying in their bedrooms, but it is impractical for medical providers to do this manually during their daily work of providing care. Although an automated approach using wearable devices and access points is more practical, implementing these access points into medical facilities is costly. However, when combined with machine learning, predicting the duration of stroke patients staying in their bedrooms is possible with reduced cost. We assessed using machine learning to estimate bedroom-stay duration using activity data recorded with wearable devices.Method: We recruited 99 stroke hemiparesis inpatients and conducted 343 measurements. Data on electrocardiograms and chest acceleration were measured using a wearable device, and the location name of the access point that detected the signal of the device was recorded. We first investigated the correlation between bedroom-stay duration measured from the access point as the objective variable and activity data measured with a wearable device and demographic information as explanatory variables. To evaluate the duration predictability, we then compared machine-learning models commonly used in medical studies.Results: We conducted 228 measurements that surpassed a 90% data-acquisition rate using Bluetooth Low Energy. Among the explanatory variables, the period spent reclining and sitting/standing were correlated with bedroom-stay duration (Spearman’s rank correlation coefficient (R) of 0.56 and −0.52, p < 0.001). Interestingly, the sum of the motor and cognitive categories of the functional independence measure, clinical indicators of the abilities of stroke patients, lacked correlation. The correlation between the actual bedroom-stay duration and predicted one using machine-learning models resulted in an R of 0.72 and p < 0.001, suggesting the possibility of predicting bedroom-stay duration from activity data and demographics.Conclusion: Wearable devices, coupled with machine learning, can predict the duration of patients staying in their bedrooms. Once trained, the machine-learning model can predict without continuously tracking the actual location, enabling more cost-effective and privacy-centric future measurements

An attenuated vaccinia vaccine encoding the severe acute respiratory syndrome coronavirus-2 spike protein elicits broad and durable immune responses, and protects cynomolgus macaques and human angiotensin-converting enzyme 2 transgenic mice from severe acute respiratory syndrome coronavirus-2 and its variants

As long as the coronavirus disease-2019 (COVID-19) pandemic continues, new variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) with altered antigenicity will emerge. The development of vaccines that elicit robust, broad, and durable protection against SARS-CoV-2 variants is urgently required. We have developed a vaccine consisting of the attenuated vaccinia virus Dairen-I (DIs) strain platform carrying the SARS-CoV-2 S gene (rDIs-S). rDIs-S induced neutralizing antibody and T-lymphocyte responses in cynomolgus macaques and human angiotensin-converting enzyme 2 (hACE2) transgenic mice, and the mouse model showed broad protection against SARS-CoV-2 isolates ranging from the early-pandemic strain (WK-521) to the recent Omicron BA.1 variant (TY38-873). Using a tandem mass tag (TMT)-based quantitative proteomic analysis of lung homogenates from hACE2 transgenic mice, we found that, among mice subjected to challenge infection with WK-521, vaccination with rDIs-S prevented protein expression related to the severe pathogenic effects of SARS-CoV-2 infection (tissue destruction, inflammation, coagulation, fibrosis, and angiogenesis) and restored protein expression related to immune responses (antigen presentation and cellular response to stress). Furthermore, long-term studies in mice showed that vaccination with rDIs-S maintains S protein-specific antibody titers for at least 6 months after a first vaccination. Thus, rDIs-S appears to provide broad and durable protective immunity against SARS-CoV-2, including current variants such as Omicron BA.1 and possibly future variants

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection

DOCK2 is involved in the host genetics and biology of severe COVID-19

「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target