TM-Score predicts immunotherapy efficacy and improves the performance of the machine learning prognostic model in gastric cancer.

Immunotherapy is becoming increasingly important, but the overall response rate is relatively low in the treatment of gastric cancer (GC). The application of tumor mutational burden (TMB) in predicting immunotherapy efficacy in GC patients is limited and controversial, emphasizing the importance of optimizing TMB-based patient selection. By combining TMB and major histocompatibility complex (MHC) related hub genes, we established a novel TM-Score. This score showed superior performance for immunotherapeutic selection (AUC = 0.808) compared to TMB, MSI status, and EBV status. Additionally, it predicted the prognosis of GC patients. Subsequently, a machine learning model adjusted by the TM-Score further improved the accuracy of survival prediction (AUC > 0.8). Meanwhile, we found that GC patients with low TM-Score had a higher mutation frequency, higher expression of HLA genes and immune checkpoint genes, and higher infiltration of CD8+ T cells, CD4+ helper T cells, and M1 macrophages. This suggests that TM-Score is significantly associated with tumor immunogenicity and tumor immune environment. Notably, based on the RNA-seq and scRNA-seq, it was found that AKAP5, a key component gene of TM-Score, is involved in anti-tumor immunity by promoting the infiltration of CD4+ T cells, NK cells, and myeloid cells. Additionally, siAKAP5 significantly reduced MHC-II mRNA expression in the GC cell line. In addition, our immunohistochemistry assays confirmed a positive correlation between AKAP5 and human leukocyte antigen (HLA) expression. Furthermore, AKAP5 levels were higher in patients with longer survival and those who responded to immunotherapy in GC, indicating its potential value in predicting prognosis and immunotherapy outcomes. In conclusion, TM-Score, as an optimization of TMB, is a more precise biomarker for predicting the immunotherapy efficacy of the GC population. Additionally, AKAP5 shows promise as a therapeutic target for GC.

The RNA-binding protein RBMS3 inhibits the progression of colon cancer by regulating the stability of LIMS1 mRNA.

BACKGROUND: The RNA-binding motif single-stranded interacting protein 3 (RBMS3) is a constituent of the RNA-binding motif (RBM) protein family, which assumes a pivotal role in governing cellular biogenesis processes such as the cell cycle and apoptosis. Despite an abundance of studies elucidating RBMS3's divergent roles in the genesis and advancement of various tumors, its involvement in colon cancer remains enigmatic. METHODS: The present investigation employed data analysis from TCGA and GTEx to unveil that RBMS3 expression demonstrated a diminished presence in colon cancer tissues when juxtaposed with normal colon tissues. The effect of RBMS3 and LIM zinc finger domain 1 (LIMS1) on colon cancer was substantiated via animal models and cellular experiments. The connection between RBMS3 and LIM zinc finger domain 1 (LIMS1) was verified by molecular biology methods. RESULTS: The study conclusively ascertained that augmenting RBMS3 expression quells the proliferation, migration, and invasion of colon cancer cells. Furthermore, the inquiry unveiled a plausible mechanism through which RBMS3 impacts the expression of LIMS1 by modulating its mRNA stability. The investigation ascertained that RBMS3 inhibits the progression of colon cancer by regulating LIMS1. The inhibitory function of LIMS1 and RBMS3 is closely intertwined in colon cancer, with knocking down LIMS1 being able to rescue the inhibitory effect of RBMS3 overexpression on the functionality of colon cancer cell CONCLUSIONS: The discernments delineate RBMS3 as a novel suppressor of cancer via LIMS1, thereby bestowing fresh therapeutic possibilities and illuminating the intricacies of colon cancer.

Bibliometric and visualized analysis of reporting and data systems from 2000 to 2022: research situation, global trends, and hotspots.

Background: The reporting and data system (RADS) has been researched across the world since it was first developed. This study used bibliometrics to analyze the research trends and current status of this field over the past almost 23 years and explored possible future research hotspots. Methods: We searched the Web of Science (WOS) literature on RADSs from January 1, 2000, to November 1, 2022, and evaluated the findings visually with VOSviewer (1.6.18), CiteSpace (6.1.3), and the "bibliometrix" package in R version 4.2.1. Results: We included 6,239 publications from 88 countries and regions. The number of published has shown an overall growth trend, especially since 2016. The United States was the country with the highest number of publications and citations. The top 10 most productive institutions in RADS research were mainly from South Korea and the United States. Kim EK was the most published author, and Turkbey B had the most cited publication. European Radiology had the most publications on the subject, while Radiology was the most influential journal. Magnetic resonance imaging, carcinoma, ultrasound, RADS, mammography, breast neoplasms, and diagnosis were the most common keywords. Artificial intelligence (AI) appears to be an emerging hotspot in the research of RADS. Conclusions: This study provides an overview of the development status of research into RADSs over the past 23 years. Research into RADSs has included various systems of the body, with the most studied being the breast, prostate, liver, and thyroid. In terms of auxiliary diagnosis, there is an increasing amount of research into the application of AI in RADSs, which along with the interpretability of AI, will be a hotspot of research in the following years.

RN0D, a galactoglucan from Panax notoginseng flower induces cancer cell death via PINK1/Parkin mitophagy.

Metabolic alterations within mitochondria, encompassing processes such as autophagy and energy metabolism, play a pivotal role in facilitating the swift proliferation, invasion, and metastasis of cancer cells. Despite this, there is a scarcity of currently available medications with proven anticancer efficacy through the modulation of mitochondrial dysfunction in a clinical setting. Here, we introduce the structural characteristics of RN0D, a galactoglucan isolated and purified from Panax notoginseng flowers, mainly composed of ß-1,4-galactan and ß-1,3/1,6-glucan. RN0D demonstrates the capacity to induce mitochondrial impairment in cancer cells, leading to the accumulation of reactive oxygen species, initiation of mitophagy, and reduction in both mitochondrial number and size. This sequence of events ultimately results in the inhibition of mitochondrial and glycolytic bioenergetics, culminating in the demise of cancer cells due to adenosine triphosphate (ATP) deprivation. Notably, the observed bioactivity is attributed to RN0D's direct targeting of Galectin-3, as affirmed by surface plasmon resonance studies. Furthermore, RN0D is identified as an activator of the PTEN-induced kinase 1 (PINK1)/Parkin pathway, ultimately instigating cytotoxic mitophagy in tumor cells. This comprehensive study substantiates the rationale for advancing RN0D as a potentially efficacious anticancer therapeutic.

Trends and Hotspots in Global Radiomics Research: A Bibliometric Analysis.

Objectives: The purpose of this research is to summarize the structure of radiomics-based knowledge and to explore potential trends and priorities by using bibliometric analysis. Methods: Select radiomics-related publications from 2012 to October 2022 from the Science Core Collection Web site. Use VOSviewer (version 1.6.18), CiteSpace (version 6.1.3), Tableau (version 2022), Microsoft Excel and Rstudio's free online platforms (http://bibliometric.com) for co-writing, co-citing, and co-occurrence analysis of countries, institutions, authors, references, and keywords in the field. The visual analysis is also carried out on it. Results: The study included 6428 articles. Since 2012, there has been an increase in research papers based on radiomics. Judging by publications, China has made the largest contribution in this area. We identify the most productive institutions and authors as Fudan University and Tianjie. The top three magazines with the most publications are《FRONTIERS IN ONCOLOGY》, 《EUROPEAN RADIOLOGY》, and 《CANCERS》. According to the results of reference and keyword analysis, "deep learning, nomogram, ultrasound, f-18-fdg, machine learning, covid-19, radiogenomics" has been determined as the main research direction in the future. Conclusion: Radiomics is in a phase of vigorous development with broad prospects. Cross-border cooperation between countries and institutions should be strengthened in the future. It can be predicted that the development of deep learning-based models and multimodal fusion models will be the focus of future research. Advances in knowledge: This study explores the current state of research and hot spots in the field of radiomics from multiple perspectives, comprehensively, and objectively reflecting the evolving trends in imaging-related research and providing a reference for future research.

XQZ3, a Chlorella pyrenoidosa polysaccharide suppresses cancer progression by restraining mitochondrial bioenergetics via HSP90/AKT signaling pathway.

The mitochondria are known to exert significant influence on various aspects of cancer cell physiology. The suppression of mitochondrial function represents a novel avenue for the advancement of anti-cancer pharmaceuticals. The heat shock protein HSP90 functions as a versatile regulator of mitochondrial metabolism in cancer cells, rendering as a promising target for anticancer interventions. In this work, a novel acid polysaccharide named as XQZ3 was extracted from Chlorella pyrenoidosa and purified by DEAE-cellulose and gel-filtration chromatography. The structural characteristic of XQZ3 was evaluated by monosaccharides composition, methylation analysis, TEM, FT-IR, and 2D-NMR. It was found that XQZ3 with a molecular weight of 29.13 kDa was a complex branched polysaccharide with a backbone mainly composed of galactose and mannose. It exhibited good antitumor activity in vitro and in vivo by patient-derived 3D organoid models and patient-derived xenografts models. The mechanistic investigations revealed that XQZ3 specifically interacted with HSP90, impeding the activation of the HSP90/AKT/mTOR signaling cascade. This, in turn, led to the induction of mitochondrial dysfunction, autophagy, and apoptosis, ultimately resulting in the demise of cancer cells due to nutrient deprivation. This study offers a comprehensive theoretical foundation for the advancement of XQZ3, a novel polysaccharide inhibitor targeting HSP90, with potential as an effective therapeutic agent against cancer.

Invertible and Variable Augmented Network for Pretreatment Patient-Specific Quality Assurance Dose Prediction.

Pretreatment patient-specific quality assurance (prePSQA) is conducted to confirm the accuracy of the radiotherapy dose delivered. However, the process of prePSQA measurement is time consuming and exacerbates the workload for medical physicists. The purpose of this work is to propose a novel deep learning (DL) network to improve the accuracy and efficiency of prePSQA. A modified invertible and variable augmented network was developed to predict the three-dimensional (3D) measurement-guided dose (MDose) distribution of 300 cancer patients who underwent volumetric modulated arc therapy (VMAT) between 2018 and 2021, in which 240 cases were randomly selected for training, and 60 for testing. For simplicity, the present approach was termed as "IVPSQA." The input data include CT images, radiotherapy dose exported from the treatment planning system, and MDose distribution extracted from the verification system. Adam algorithm was used for first-order gradient-based optimization of stochastic objective functions. The IVPSQA model obtained high-quality 3D prePSQA dose distribution maps in head and neck, chest, and abdomen cases, and outperformed the existing U-Net-based prediction approaches in terms of dose difference maps and horizontal profiles comparison. Moreover, quantitative evaluation metrics including SSIM, MSE, and MAE demonstrated that the proposed approach achieved a good agreement with ground truth and yield promising gains over other advanced methods. This study presented the first work on predicting 3D prePSQA dose distribution by using the IVPSQA model. The proposed method could be taken as a clinical guidance tool and help medical physicists to reduce the measurement work of prePSQA.

Combined BET and MEK Inhibition synergistically suppresses melanoma by targeting YAP1.

Rationale: The response rate to the MEK inhibitor trametinib in BRAF-mutated melanoma patients is less than 30%, and drug resistance develops rapidly, but the mechanism is still unclear. Yes1-associated transcriptional regulator (YAP1) is highly expressed in melanoma and may be related to MEK inhibitor resistance. The purpose of this study was to investigate the mechanism of YAP1 in MEK inhibitor resistance in melanoma and to screen YAP1 inhibitors to further determine whether YAP1 inhibition reverses MEK inhibitor resistance. Methods: On the one hand, we analyzed paired melanoma and adjacent tissue samples using RNA-seq and found that the Hippo-YAP1 signaling pathway was the top upregulated pathway. On the other hand, we evaluated the transcriptomes of melanoma samples from patients before and after trametinib treatment and investigated the correlation between YAP1 expression and trametinib resistance. Then, we screened for inhibitors that repress YAP1 expression and investigated the mechanisms. Finally, we investigated the antitumor effect of YAP1 inhibition combined with MEK inhibition both in vitro and in vivo. Results: We found that YAP1 expression levels upon trametinib treatment in melanoma patients were correlated with resistance to trametinib. YAP1 was translocated into the nucleus after trametinib treatment in melanoma cells, which could render resistance to MEK inhibition. Thus, we screened for inhibitors that repress YAP1 expression and identified multiple bromodomain and extra-terminal (BET) inhibitors, including NHWD-870, as hits. BET inhibition repressed YAP1 expression by decreasing BRD4 binding to the YAP1 promoter. Consistently, YAP1 overexpression was sufficient to reverse the proliferation defect caused by BRD4 depletion. In addition, the BET inhibitor NHWD-870 acted synergistically with trametinib to suppress melanoma growth in vitro and in vivo. Conclusions: We identified a new vulnerability for MEK inhibitor-resistant melanomas, which activated Hippo pathway due to elevated YAP1 activity. Inhibition of BRD4 using BET inhibitors suppressed YAP1 expression and led to blunted melanoma growth when combined with treatment with the MEK inhibitor trametinib.

Methionine Promotes Milk Synthesis through the BRCC36-BRG1-mTOR Signaling Axis in Mammary Epithelial Cells.

Methionine (Met) functions as a key stimulator on the mTOR signaling pathway and milk synthesis, but the molecular mechanism remains incompletely understood. We investigated the regulatory roles of BRCC36 in Met-stimulated milk lipid and protein synthesis, cell proliferation, and the mTOR signaling pathway. Knockdown of BRCC36 promoted milk lipid and protein synthesis in HC11 cells as well as cell proliferation by increasing the levels of mTOR gene transcription and protein phosphorylation. Conversely, the gene activation of BRCC36 had opposite effects. Furthermore, BRCC36 gene activation completely blocked Met stimulation on the BRG1 protein level and mTOR mRNA level and protein phosphorylation. BRCC36 bound to BRG1, and BRCC36 and BRG1 bound to the same region on the mTOR promoter. BRCC36 inhibited the BRG1 protein level and the binding of BRG1 to the mTOR promoter. Met decreased the BRCC36 protein level, and this effect was significantly attenuated by MG132 but not affected by cycloheximide or chloroquine. We further showed that Met increased BRCC36 ubiquitination degradation. Our findings reveal that Met promotes milk lipid and protein synthesis in MECs through the BRCC36-BRG1-mTOR signaling axis.

PTPN9 dephosphorylates FGFR2 pY656/657 through interaction with ACAP1 and ameliorates pemigatinib effect in cholangiocarcinoma.

ABSTRACT AND AIM: Cholangiocarcinoma (CCA) is a highly aggressive and lethal cancer that originates from the biliary epithelium. Systemic treatment options for CCA are currently limited, and the first targeted drug of CCA, pemigatinib, emerged in 2020 for CCA treatment by inhibiting FGFR2 phosphorylation. However, the regulatory mechanism of FGFR2 phosphorylation is not fully elucidated. APPROACH AND RESULTS: Here we screened the FGFR2-interacting proteins and showed that protein tyrosine phosphatase (PTP) N9 interacts with FGFR2 and negatively regulates FGFR2 pY656/657 . Using phosphatase activity assays and modeling the FGFR2-PTPN9 complex structure, we identified FGFR2 pY656/657 as a substrate of PTPN9, and found that sec. 14p domain of PTPN9 interacts with FGFR2 through ACAP1 mediation. Coexpression of PTPN9 and ACAP1 indicates a favorable prognosis for CCA. In addition, we identified key amino acids and motifs involved in the sec. 14p-APCP1-FGFR2 interaction, including the "YRETRRKE" motif of sec. 14p, Y471 of PTPN9, as well as the PH and Arf-GAP domain of ACAP1. Moreover, we discovered that the FGFR2 I654V substitution can decrease PTPN9-FGFR2 interaction and thereby reduce the effectiveness of pemigatinib treatment. Using a series of in vitro and in vivo experiments including patient-derived xenografts (PDX), we showed that PTPN9 synergistically enhances pemigatinib effectiveness and suppresses CCA proliferation, migration, and invasion by inhibiting FGFR2 pY656/657 . CONCLUSIONS: Our study identifies PTPN9 as a negative regulator of FGFR2 phosphorylation and a synergistic factor for pemigatinib treatment. The molecular mechanism, oncogenic function, and clinical significance of the PTPN9-ACAP1-FGFR2 complex are revealed, providing more evidence for CCA precision treatment.

Schizophrenia mediating the effect of smoking phenotypes on antisocial behavior: A Mendelian randomization analysis.

AIMS: Previous studies have indicated that smoking is linked to an increased risk of developing schizophrenia, and that individuals with schizophrenia are more prone to engaging in antisocial behavior. However, the causal effects of smoking behaviors on antisocial behavior and the potential mediating role of schizophrenia remains largely unclear. METHODS: In the present study, using the summary data from genome wide association studies of smoking phenotypes (N = 323,386-805,431), schizophrenia (Ncases = 53,386, Ncontrols = 77,258), and antisocial behavior (N = 85,359), we assessed bidirectional causality between smoking phenotypes and schizophrenia by the Mendelian randomization (MR) approach. Using a two-step MR approach, we further examined whether causal effects of smoking phenotypes/schizophrenia on antisocial behavior were mediated by schizophrenia/smoking phenotypes. RESULTS: The results showed that smoking initiation (SmkInit) and age of smoking initiation (AgeSmk) causally increase the risk of schizophrenia (SmkInit: OR = 2.06, 95% CI = 1.77-2.39, p = 4.36 × 10-21 ; AgeSmk: OR = 0.32, 95% CI = 0.16-0.62, p = 8.11 × 10-4 , Bonferroni corrected). However, there was no causal effect that liability to schizophrenia leads to smoking phenotypes. MR evidence also revealed causal influences of SmkInit and the amount smoked (CigDay) on antisocial behavior (SmkInit: OR = 1.28, 95% CI = 1.17-1.41, p = 2.53 × 10-7 ; CigDay: OR = 1.16, 95% CI = 1.06-1.27, p = 1.60 × 10-3 , Bonferroni corrected). Furthermore, the mediation analysis indicated that the relationship between SmkInit and antisocial behavior was partly mediated by schizophrenia (mediated proportion = 6.92%, 95% CI = 0.004-0.03, p = 9.66 × 10-3 ). CONCLUSIONS: These results provide compelling evidence for taking smoking interventions as a prevention strategy for schizophrenia and its related antisocial behavior.

Novel insights from spatial transcriptome analysis in solid tumors.

Since its first application in 2016, spatial transcriptomics has become a rapidly evolving technology in recent years. Spatial transcriptomics enables transcriptomic data to be acquired from intact tissue sections and provides spatial distribution information and remedies the disadvantage of single-cell RNA sequencing (scRNA-seq), whose data lack spatially resolved information. Presently, spatial transcriptomics has been widely applied to various tissue types, especially for the study of tumor heterogeneity. In this review, we provide a summary of the research progress in utilizing spatial transcriptomics to investigate tumor heterogeneity and the microenvironment with a focus on solid tumors. We summarize the research breakthroughs in various fields and perspectives due to the application of spatial transcriptomics, including cell clustering and interaction, cellular metabolism, gene expression, immune cell programs and combination with other techniques. As a combination of multiple transcriptomics, single-cell multiomics shows its superiority and validity in single-cell analysis. We also discuss the application prospect of single-cell multiomics, and we believe that with the progress of data integration from various transcriptomics, a multilayered subcellular landscape will be revealed.

Met stimulates ARID1A degradation and activation of the PI3K-SREBP1 signaling to promote milk fat synthesis in bovine mammary epithelial cells.

Methionine (Met) can promote milk fat synthesis in bovine mammary epithelial cells (BMECs), but the potential molecular mechanism is largely unknown. In this report, we aim to explore the role and molecular mechanism of AT-rich interaction domain 1A (ARID1A) in milk fat synthesis stimulated by Met. ARID1A knockdown and activation indicated that ARID1A negatively regulated the synthesis of triglycerides, cholesterol and free fatty acids and the formation of lipid droplets in BMECs. ARID1A also negatively regulated the phosphorylation of PI3K and AKT proteins, as well as the expression and maturation of SREBP1. Met stimulated the phosphorylation of PI3K and AKT proteins, as well as the expression and maturation of SREBP1, while ARID1A gene activation blocked the stimulatory effects of Met. We further found that ARID1A was located in the nucleus of BMECs, and Met reduced the nuclear localization and expression of ARID1A. ARID1A gene activation blocked the stimulation of PI3K and SREBP1 mRNA expression by Met. In summary, our data suggests that ARID1A negatively regulates milk fat synthesis stimulated by Met in BMECs through inhibiting the PI3K-SREBP1 signaling pathway, which may provide some new perspectives for improving milk fat synthesis.

Towards Connectivity-Aware Pulmonary Airway Segmentation.

Detailed pulmonary airway segmentation is a clinically important task for endobronchial intervention and treatment of peripheral pulmonary lesions. Convolutional Neural Networks (CNNs) are promising for automated analysis of medical imaging, which however performs poorly on airway segmentation. Specifically, breakage of small bronchi distals cannot be effectively eliminated in the prediction results of CNNs, which is detrimental to use as a reference for bronchoscopic-assisted surgery. In this paper, we proposed a connectivity-aware segmentation framework to improve the performance of airway segmentation. A Connectivity-Aware Surrogate (CAS) module is first proposed to balance the training progress within-class distribution. Furthermore, a Local-Sensitive Distance (LSD) module is designed to identify the breakage and minimize the variation of the distance map between the prediction and ground-truth. The proposed method is validated with the publically available reference airway segmentation datasets. The detected rate of branch and length on public EXACT'09 and BAS datasets are 82.1%/79.6% and 96.5%/91.5% respectively, demonstrating the effectiveness of the method in terms of improving the connectedness of the segmentation performance. The source code is available at: https://github.com/Puzzled-Hui/Connectivity-Aware-Airway-Segmentation.

HOXD8 suppresses renal cell carcinoma growth by upregulating SHMT1 expression.

Amplification of amino acids synthesis is reported to promote tumorigenesis. The serine/glycine biosynthesis pathway is a reversible conversion of serine and glycine catalyzed by cytoplasmic serine hydroxymethyltransferase (SHMT)1 and mitochondrial SHMT2; however, the role of SHTM1 in renal cell carcinoma (RCC) is still unclear. We found that low SHMT1 expression is correlated with poor survival of RCC patients. The in vitro study showed that overexpression of SHMT1 suppressed RCC proliferation and migration. In the mouse tumor model, SHMT1 significantly retarded RCC tumor growth. Furthermore, by gene network analysis, we found several SHMT1-related genes, among which homeobox D8 (HOXD8) was identified as the SHMT1 regulator. Knockdown of HOXD8 decreased SHMT1 expression, resulting in faster RCC growth, and rescued the SHMT1 overexpression-induced cell migration defects. Additionally, ChIP assay found the binding site of HOXD8 to SHMT1 promoter was at the -456~-254 bp region. Taken together, SHMT1 functions as a tumor suppressor in RCC. The transcription factor HOXD8 can promote SHMT1 expression and suppress RCC cell proliferation and migration, which provides new mechanisms of SHMT1 in RCC tumor growth and might be used as a potential therapeutic target candidate for clinical treatment.

Activation of CTNNB1 by deubiquitinase UCHL3-mediated stabilization facilitates bladder cancer progression.

BACKGROUND: The catenin beta 1 gene (CTNNB1) plays a crucial role in the malignant progression of various cancers. Recent studies have suggested that CTNNB1 hyperactivation is closely related to the occurrence and development of bladder cancer (BCa). As a member of the deubiquitinating enzyme (DUB) family, ubiquitin C-terminal hydrolase L3 (UCHL3) is abnormally expressed in various cancers. In this study, we discovered that UCHL3 is a novel oncogene in bladder cancer, suggesting it is a promising target against bladder cancer. METHODS: We utilized CRISPR‒Cas9 technology to construct cell lines with UCHL3 stably overexpressed or knocked out. The successful overexpression or knockout of UCHL3 was determined using Western blotting. Then, we performed CCK-8, colony formation, soft agar and Transwell migration assays to determine the impact of the UCHL3 gene on cell phenotype. RNA-seq was performed with UCHL3-depleted T24 cells (established via CRISPR-Cas9-mediated genomic editing). We analyzed differences in WNT pathway gene expression in wild-type and UCHL3-deficient T24 cell lines using a heatmap and by gene set enrichment analysis (GSEA). Then, we validated the effect of UCHL3 on the Wnt pathway using a dual fluorescence reporter. We then analyzed the underlying mechanisms involved using Western blots, co-IP, and immunofluorescence results. We also conducted nude mouse tumor formation experiments. Moreover, conditional UCHL3-knockout mice and bladder cancer model mice were established for research. RESULTS: We found that the overexpression of UCHL3 boosted bladder cancer cell proliferation, invasion and migration, while the depletion of UCHL3 in bladder cancer cells delayed tumor tumorigenesis in vitro and in vivo. UCHL3 was highly associated with the Wnt signaling pathway and triggered the activation of the Wnt signaling pathway, which showed that its functions depend on its deubiquitination activity. Notably, Uchl3-deficient mice were less susceptible to bladder tumorigenesis. Additionally, UCHL3 was highly expressed in bladder cancer cells and associated with indicators of advanced clinicopathology. CONCLUSION: In summary, we found that UCHL3 is amplified in bladder cancer and functions as a tumor promoter that enhances proliferation and migration of tumor cells in vitro and bladder tumorigenesis and progression in vivo. Furthermore, we revealed that UCHL3 stabilizes CTNNB1 expression, resulting in the activation of the oncogenic Wnt signaling pathway. Therefore, our findings strongly suggest that UCHL3 is a promising therapeutic target for bladder cancer.

TransQA: deep hybrid transformer network for measurement-guided volumetric dose prediction of pre-treatment patient-specific quality assurance.

Objective. Performing pre-treatment patient-specific quality assurance (prePSQA) is considered an essential, time-consuming, and resource-intensive task for volumetric modulated arc radiotherapy (VMAT) which confirms the dose accuracy and ensure patient safety. Most current machine learning and deep learning approaches stack excessive convolutional/pooling operations (CPs) to predict prePSQA with two-dimensional or one-dimensional information input. However, these models generally present limitations in explicitly modeling long-range dependency for volumetric dose prediction due to the loss of spatial dose features and the inherent locality of CPs. The purpose of this work is to construct a deep hybrid network by combining the self-attention mechanism-based Transformer with modified U-Net for predicting measurement-guided volumetric dose (MDose) of prePSQA.Approach. The enrolled 307 cancer patients underwent VMAT were randomly divided into 246 and 61 cases for training and testing the model. The input data included computed tomography images, radiotherapy dose images exported from the treatment planning system, as well as the MDose distribution from the verification system. The output was the predicted high-quality voxel-wise prePSQA dose distribution.Main results: qualitative and quantitative experimental results show that the proposed prediction method could achieve comparable or better performance on MDose prediction over other approaches in terms of spatial dose distribution, dose-volume histogram metrics, gamma passing rates, mean absolute error, root mean square error, and structural similarity.Significance. The preliminary results on multiple cancer sites show that our approach can be taken as a clinical guidance tool and help medical physicists to reduce the measurement work of prePSQA.

[Retracted] MicroRNA­616 promotes the growth and metastasis of non­small cell lung cancer by targeting SOX7.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that the cell formation assay data shown in Figs. 3D, 4D, 8D and 9D were strikingly similar to data that had already appeared in another article written by different authors at different research institutes [Wang Z, Jiang C, Chen W, Zhang G, Luo D, Cao Y Wu J, Ding Y and Liu B: Baicalein induces apoptosis and autophagy via endoplasmic reticulum stress in hepatocellular carcinoma. Biomed Res Int: 732516, 2014]. Owing to the fact that the contentious data in the above article had already been published prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 38: 2078­2086, 2017; DOI: 10.3892/or.2017.5854].