Hsp90 is a ubiquitous chaperone with important roles in the organization and maturation of client proteins that are involved in the progression and survival of cancer cells. Multiple oncogenic pathways can be affected by inhibition of Hsp90 function through degradation of its client proteins. That makes Hsp90 a therapeutic target for cancer treatment. 17-allylamino-17-demethoxy-geldanamycin (17-AAG) is a potent Hsp90 inhibitor that binds to Hsp90 and inhibits its chaperoning function, which results in the degradation of Hsp90's client proteins. There have been several preclinical studies of 17-AAG as a single agent or in combination with other anticancer agents for a wide range of human cancers. Data from various phases of clinical trials show that 17-AAG can be given safely at biologically active dosages with mild toxicity. Even though 17-AAG has suitable pharmacological potency, its low water solubility and high hepatotoxicity could significantly restrict its clinical use. Nanomaterials-based drug delivery carriers may overcome these drawbacks. In this paper, we review preclinical and clinical research on 17-AAG as a single agent and in combination with other anticancer agents. In addition, we highlight the potential of using nanocarriers and nanocombination therapy to improve therapeutic effects of 17-AAG.

Spotlight on 17-AAG as an Hsp90 inhibitor for molecular targeted cancer treatment.

We are now witnessing significant progress of deep learning methods in a variety of tasks (or datasets) of proteins. However, there is a lack of a standard benchmark to evaluate the performance of different methods, which hinders the progress of deep learning in this field. In this paper, we propose such a benchmark called PEER, a comprehensive and multi-task benchmark for Protein sEquence undERstanding. PEER provides a set of diverse protein understanding tasks including protein function prediction, protein localization prediction, protein structure prediction, protein-protein interaction prediction, and protein-ligand interaction prediction. We evaluate different types of sequence-based methods for each task including traditional feature engineering approaches, different sequence encoding methods as well as large-scale pre-trained protein language models. In addition, we also investigate the performance of these methods under the multi-task learning setting. Experimental results show that large-scale pre-trained protein language models achieve the best performance for most individual tasks, and jointly training multiple tasks further boosts the performance. The datasets and source codes of this benchmark are all available at https://github.com/DeepGraphLearning/PEER_Benchmark

PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding

OBJECTIVES The aim of the study was to compare the postoperative and oncologic outcomes of laparoscopic versus open surgery for gastric gastrointestinal stromal tumors (gGISTs). BACKGROUND The feasibility of the laparoscopic approach for gGIST resection has been demonstrated; however, its impact on outcomes, particularly its oncologic safety for tumors greater than 5 cm, remains unknown. METHODS Among 1413 patients treated for a GIST in 61 European centers between 2001 and 2013, patients who underwent primary resection for a gGIST smaller than 20 cm (N = 666), by either laparoscopy (group L, n = 282) or open surgery (group O, n = 384), were compared. Multivariable analyses and propensity score matching were used to compensate for differences in baseline characteristics. RESULTS In-hospital mortality and morbidity rates in groups L and O were 0.4% versus 2.1% (P = 0.086) and 11.3% vs 19.5% (P = 0.004), respectively. Laparoscopic resection was independently protective against in-hospital morbidity (odds ratio 0.54, P = 0.014). The rate of R0 resection was 95.7% in group L and 92.7% in group O (P = 0.103). After 1:1 propensity score matching (n = 224), the groups were comparable according to age, sex, tumor location and size, mitotic index, American Society of Anesthesiology score, and the extent of surgical resection. After adjustment for BMI, overall morbidity (10.3% vs 19.6%; P = 0.005), surgical morbidity (4.9% vs 9.8%; P = 0.048), and medical morbidity (6.2% vs 13.4%; P = 0.01) were significantly lower in group L. Five-year recurrence-free survival was significantly better in group L (91.7% vs 85.2%; P = 0.011). In tumors greater than 5 cm, in-hospital morbidity and 5-year recurrence-free survival were similar between the groups (P = 0.255 and P = 0.423, respectively). CONCLUSIONS Laparoscopic resection for gGISTs is associated with favorable short-term outcomes without compromising oncologic results.

Laparoscopic Versus Open Surgery for Gastric Gastrointestinal Stromal Tumors: What Is the Impact on Postoperative Outcome and Oncologic Results?

Conventional photothermal therapy (PTT) irradiates the tumor tissues by elevating the temperature above 48 °C to exert thermal ablation, killing tumor cells. However, thermal ablation during PTT harmfully damages the surrounding normal tissues, post-treatment inflammatory responses, rapid metastasis due to the short-term mass release of tumor-cellular contents, or other side effects. To circumvent this limitation, mild-temperature photothermal therapy (MTPTT) was introduced to replace PTT as it exerts its activity at a therapeutic temperature of 42–45 °C. However, the significantly low therapeutic effect comes due to the thermoresistance of cancer cells as MTPTT figures out some of the side-effects issues. Herein, our current review suggested the mechanism and various strategies for improving the efficacy of MTPTT. Especially, heat shock proteins (HSPs) are molecular chaperones overexpressed in tumor cells and implicated in several cellular heat shock responses. Therefore, we introduced some methods to inhibit activity, reduce expression levels, and hinder the function of HSPs during MTPTT treatment. Moreover, other strategies also were emphasized, including nucleus damage, energy inhibition, and autophagy mediation. In addition, some therapies, like radiotherapy, chemotherapy, photodynamic therapy, and immunotherapy, exhibited a significant synergistic effect to assist MTPTT. Our current review provides a basis for further studies and a new approach for the clinical application of MTPTT.

/pdf/enhancing-the-efficiency-of-mild-temperature-photothermal-2oyv9oy7.pdf

Enhancing the Efficiency of Mild-Temperature Photothermal Therapy for Cancer Assisting with Various Strategies

https://escholarship.org/content/qt3r57m761/qt3r57m761.pdf?t=ok33r7

Pharmacological induction of the 70-kDa heat shock protein protects against brain injury.

Purpose:We conducted a meta-analysis to compare surgical and oncologic outcomes of patients with gastric gastrointestinal stromal tumors (GISTs) undergoing laparoscopic resection surgery (LAP) and open resection surgery (OPEN).Methods:PubMed, Ovid, Web of Science, Cochrane, CNKI, and Chinese Biomedi

Laparoscopic versus open gastric resections for gastric gastrointestinal stromal tumors: a meta-analysis

eo scence Chang’e-5 lunar samples shed new light on the Moon Yi Chen, Sen Hu, Jin-Hua Li, Qiu-Li Li, Xiongyao Li, Yang Li, Yang Liu, Yuqi Qian, Wei Yang, Qin Zhou, Yangting Lin,2,* Chunlai Li,6,* and Xian-Hua Li1,* *Correspondence: linyt@mail.iggcas.ac.cn (Y.L.); licl@nao.cas.cn (C.L.); lixh@gig.ac.cn (X.-H.L.) Received: May 20, 2023; Accepted: June 22, 2023; Published Online: June 23, 2023; https://doi.org/10.59717/j.xinn-geo.2023.100014 © 2023 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

http://www.the-innovation.org/geoscience/main/bdueditor/asp/file/202306/TIG1-0619-CE5-Review-011.pdf

Chang’e-5 lunar samples shed new light on the Moon

The aim of this study was to investigate the effects of 17-Allylamino-17-demethoxygeldanamycin (17-AAG), a heat shock protein 90 (HSP90) inhibitor, on the proliferation, cell cycle, and apoptosis of human cholangiocarcinoma (CCA) cells. Cell proliferation and cell cycle distribution were measured by the MTT assay and flow cytometry analysis, respectively. Induction of apoptosis was determined by flow cytometry and Hoechst staining. The expressions of cleaved poly ADP-ribose polymerase (PARP), Bcl-2, Survivin, and Cyclin B1 were detected by Western blot analysis. The activity of caspase-3 was also examined. We found that 17-AAG inhibited cell growth and induced G2/M cell cycle arrest and apoptosis in CCA cells together with the down-regulation of Bcl-2, Survivin and Cyclin B1, and the up-regulation of cleaved PARP. Moreover, increased caspase-3 activity was also observed in CCA cells treated with 17-AAG. In conclusion, our data suggest that the inhibition of HSP90 function by 17-AAG may provide a promising therapeutic strategy for the treatment of human CCA.

The heat shock protein 90 inhibitor 17-AAG suppresses growth and induces apoptosis in human cholangiocarcinoma cells

Predicting the secondary structure of a protein from its amino acid sequence alone is a challenging prediction task for each residue in bioinformatics. Recent work has mainly used deep models based on the profile feature derived from multiple sequence alignments to make predictions. However, the existing state-of-the-art predictors usually have higher computational costs due to their large model sizes and complex network architectures. Here, we propose a simple yet effective deep centroid model for sequence-to-sequence secondary structure prediction based on deep metric learning. The proposed model adopts a lightweight embedding network with multibranch topology to map each residue in a protein chain into an embedding space. The goal of embedding learning is to maximize the similarity of each residue to its target centroid while minimizing its similarity to nontarget centroids. By assigning secondary structure types based on the learned centroids, we bypass the need for a time-consuming k -nearest neighbor search. Experimental results on six test sets demonstrate that our method achieves state-of-the-art performance with a simple architecture and smaller model size than existing models. Moreover, we also experimentally show that the embedding feature from the pretrained protein language model ProtT5-XL-U50 is superior to the profile feature in terms of prediction accuracy and feature generation speed. Code and datasets are available at https://github.com/fengtuan/DML_SS . 

Deep metric learning for accurate protein secondary structure prediction

The Chang’e‐5 (CE‐5) mission has successfully returned samples from a site that is much younger than the sites of all previous lunar sampling missions. Sample analysis results reported so far have revealed a more complex sampling area than previously thought, casting uncertainties over the interpretation of remote sensing spectral data and the U and Th abundance derived from the orbital data. Laboratory spectral measurement of the returned samples can serve as validation of remote sensing observations and thus help refine our understanding of the geological evolution of the landing region. In this study we report detailed micro mid‐infrared (MIR) spectral characteristics of individual soil grains of CE‐5 samples. The spectral analysis results show that the CE‐5 olivine grains have low Fo (molar Mg/[Mg + Fe] × 100) consistent with previous studies, indicating a Fe‐rich source region of the mantle or a highly evolved magma. These olivine grains show high level of crystallinity, implying low degree of space weathering. Most of the CE‐5 glasses analyzed are spectrally consistent with mare impact glasses, despite that a few of them may have a volcanic origin. These laboratory spectral analysis of CE‐5 samples in the MIR wavelengths at a micro scale, together with the derived MIR optical constants of the olivine, pyroxene, plagioclase, and glass grains, provide important input for the modeling and interpretation of thermal remote sensing data of the Moon.

A Micro Mid‐Infrared Spectroscopic Study of Chang’e‐5 Sample

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