Unleashing the full potential of Hsp90 inhibitors as cancer therapeutics through simultaneous inactivation of Hsp90, Grp94, and TRAP1

Cancer therapeutics: Extending a drug's reach A new drug that blocks heat shock proteins (HSPs), helper proteins that are co-opted by cancer cells to promote tumor growth, shows promise for cancer treatment. Several drugs have targeted HSPs, since cancer cells are known to hijack these helper proteins to shield themselves from destruction by the body. However, the drugs have had limited success. Hye-Kyung Park and Byoung Heon Kang at Ulsan National Institutes of Science and Technology in South Korea and coworkers noticed that the drugs were not absorbed into mitochondria, a key cellular compartment, and HSPs in this compartment were therefore not being blocked. They identified a new HSP inhibitor that can reach every cellular compartment and inhibit all HSPs. Testing in mice showed that this inhibitor effectively triggered death of tumor cells, and therefore shows promise for anti-cancer therapy. The Hsp90 family proteins Hsp90, Grp94, and TRAP1 are present in the cell cytoplasm, endoplasmic reticulum, and mitochondria, respectively; all play important roles in tumorigenesis by regulating protein homeostasis in response to stress. Thus, simultaneous inhibition of all Hsp90 paralogs is a reasonable strategy for cancer therapy. However, since the existing pan-Hsp90 inhibitor does not accumulate in mitochondria, the potential anticancer activity of pan-Hsp90 inhibition has not yet been fully examined in vivo. Analysis of The Cancer Genome Atlas database revealed that all Hsp90 paralogs were upregulated in prostate cancer. Inactivation of all Hsp90 paralogs induced mitochondrial dysfunction, increased cytosolic calcium, and activated calcineurin. Active calcineurin blocked prosurvival heat shock responses upon Hsp90 inhibition by preventing nuclear translocation of HSF1. The purine scaffold derivative DN401 inhibited all Hsp90 paralogs simultaneously and showed stronger anticancer activity than other Hsp90 inhibitors. Pan-Hsp90 inhibition increased cytotoxicity and suppressed mechanisms that protect cancer cells, suggesting that it is a feasible strategy for the development of potent anticancer drugs. The mitochondria-permeable drug DN401 is a newly identified in vivo pan-Hsp90 inhibitor with potent anticancer activity

Inter-KD: Intermediate Knowledge Distillation for CTC-Based Automatic Speech Recognition

Recently, the advance in deep learning has brought a considerable improvement in the end-to-end speech recognition field, simplifying the traditional pipeline while producing promising results. Among the end-to-end models, the connectionist temporal classification (CTC)-based model has attracted research interest due to its non-autoregressive nature. However, such CTC models require a heavy computational cost to achieve outstanding performance. To mitigate the computational burden, we propose a simple yet effective knowledge distillation (KD) for the CTC framework, namely Inter-KD, that additionally transfers the teacher's knowledge to the intermediate CTC layers of the student network. From the experimental results on the LibriSpeech, we verify that the Inter-KD shows better achievements compared to the conventional KD methods. Without using any language model (LM) and data augmentation, Inter-KD improves the word error rate (WER) performance from 8.85 % to 6.30 % on the test-clean.Comment: Accepted by 2022 SLT Worksho

EM-Network: Oracle Guided Self-distillation for Sequence Learning

We introduce EM-Network, a novel self-distillation approach that effectively leverages target information for supervised sequence-to-sequence (seq2seq) learning. In contrast to conventional methods, it is trained with oracle guidance, which is derived from the target sequence. Since the oracle guidance compactly represents the target-side context that can assist the sequence model in solving the task, the EM-Network achieves a better prediction compared to using only the source input. To allow the sequence model to inherit the promising capability of the EM-Network, we propose a new self-distillation strategy, where the original sequence model can benefit from the knowledge of the EM-Network in a one-stage manner. We conduct comprehensive experiments on two types of seq2seq models: connectionist temporal classification (CTC) for speech recognition and attention-based encoder-decoder (AED) for machine translation. Experimental results demonstrate that the EM-Network significantly advances the current state-of-the-art approaches, improving over the best prior work on speech recognition and establishing state-of-the-art performance on WMT'14 and IWSLT'14.Comment: ICML 202

Comparison of on-Statin Lipid and Lipoprotein Levels for the Prediction of First Cardiovascular Event in Type 2 Diabetes Mellitus

Background A substantial cardiovascular disease risk remains even after optimal statin therapy. Comparative predictiveness of major lipid and lipoprotein parameters for cardiovascular events in patients with type 2 diabetes mellitus (T2DM) who are treated with statins is not well documented. Methods From the Korean Nationwide Cohort, 11,900 patients with T2DM (≥40 years of age) without a history of cardiovascular disease and receiving moderate- or high-intensity statins were included. The primary outcome was the first occurrence of major adverse cardiovascular events (MACE) including ischemic heart disease, ischemic stroke, and cardiovascular death. The risk of MACE was estimated according to on-statin levels of low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and non-HDL-C. Results MACE occurred in 712 patients during a median follow-up period of 37.9 months (interquartile range, 21.7 to 54.9). Among patients achieving LDL-C levels less than 100 mg/dL, the hazard ratios for MACE per 1-standard deviation change in on-treatment values were 1.25 (95% confidence interval [CI], 1.07 to 1.47) for LDL-C, 1.31 (95% CI, 1.09 to 1.57) for non-HDL-C, 1.05 (95% CI, 0.91 to 1.21) for TG, and 1.16 (95% CI, 0.98 to 1.37) for HDL-C, after adjusting for potential confounders and lipid parameters mutually. The predictive ability of on-statin LDL-C and non-HDL-C for MACE was prominent in patients at high cardiovascular risk or those with LDL-C ≥70 mg/dL. Conclusion On-statin LDL-C and non-HDL-C levels are better predictors of the first cardiovascular event than TG or HDL-C in patients with T2DM

PPM1A Controls Diabetic Gene Programming through Directly Dephosphorylating PPAR?? at Ser273

Peroxisome proliferator-activated receptor gamma (PPAR gamma) is a master regulator of adipose tissue biology. In obesity, phosphorylation of PPAR gamma at Ser273 (pSer273) by cyclin-dependent kinase 5 (CDK5)/extracellular signal-regulated kinase (ERK) orchestrates diabetic gene reprogramming via dysregulation of specific gene expression. Although many recent studies have focused on the development of non-classical agonist drugs that inhibit the phosphorylation of PPAR gamma at Ser273, the molecular mechanism of PPAR gamma dephosphorylation at Ser273 is not well characterized. Here, we report that protein phosphatase Mg2+/Mn2+-dependent 1A (PPM1A) is a novel PPAR gamma phosphatase that directly dephosphorylates Ser273 and restores diabetic gene expression which is dysregulated by pSer273. The expression of PPM1A significantly decreases in two models of insulin resistance: diet-induced obese (DIO) mice and db/db mice, in which it negatively correlates with pSer273. Transcriptomic analysis using microarray and genotype-tissue expression (GTEx) data in humans shows positive correlations between PPM1A and most of the genes that are dysregulated by pSer273. These findings suggest that PPM1A dephosphorylates PPAR gamma at Ser273 and represents a potential target for the treatment of obesity-linked metabolic disorders

Serum fibroblast growth factor 1 and its association with pancreatic beta cell function and insulin sensitivity in adults with glucose intolerance

BackgroundBeneficial role of fibroblast growth factor 1 (FGF1) in the regulation of glucose metabolism and adipose tissue remodeling was suggested in rodents. This study aimed to investigate the association between serum FGF1 levels and metabolic parameters in adults with glucose intolerance.MethodsSerum FGF1 levels were examined using an enzyme-linked immunosorbent assay in 153 individuals with glucose intolerance. Associations between serum FGF1 levels and metabolic parameters, including body mass index (BMI), glycated hemoglobin (HbA1c), and 75 g oral glucose tolerance test-derived parameters, including insulinogenic index (IGI), Matsuda insulin sensitivity index (ISI), and disposition index (DI), were examined.ResultsSerum FGF1 was detected in 35 individuals (22.9%), possibly due to the autocrine/paracrine nature of the peptide. IGI and DI levels were significantly lower in individuals with higher FGF1 levels than in those with lower FGF1 levels or undetectable FGF1 (p=0.006 and 0.005 for IGI and DI, respectively, after adjustment for age, sex, and BMI). Univariable and multivariable analyses using the Tobit regression model also revealed a negative association between FGF1 levels and IGI and DI. The regression coefficients per 1-SD of log-transformed IGI and DI were −0.461 (p=0.013) and −0.467 (p=0.012), respectively, after adjustment for age, sex, and BMI. In contrast, serum FGF1 levels were not significantly associated with ISI, BMI, or HbA1c.ConclusionsThe serum concentration of FGF1 was significantly elevated in individuals with low insulin secretion, suggesting a possible interaction between FGF1 and beta cell function in humans

Activation of spleen tyrosine kinase is required for TNF-α-induced endothelin-1 upregulation in human aortic endothelial cells

AbstractEndothelin-1 (ET-1) promotes atherosclerosis. We tested whether spleen tyrosine kinase (Syk) mediates tumor necrosis factor-α (TNF-α)-induced ET-1 upregulation in human aortic endothelial cells (HAECs) and sought to identify the signal pathways involved. TNF-α-induced reactive oxygen species (ROS) activated Syk and phosphatidylinositol 3-kinase (PI3K), which was required for the activation of AP-1 and subsequent ET-1 gene transcription. ROS mediated c-Jun NH2-terminal kinase (JNK) is also required for AP-1 activation, but Syk and PI3K regulated AP-1 activation independently of JNK. Through regulation of ET-1 production, Syk could be implicated in atherosclerosis