Small-Molecule Inhibitors of TIPE3 Protein Identified through Deep Learning Suppress Cancer Cell Growth In Vitro.

Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human cancers and has been established to significantly promote tumor cell proliferation, migration, and invasion and inhibit the apoptosis of cancer cells. Thus, inhibiting the function of TIPE3 is expected to be an effective strategy against cancer. The advancement of artificial intelligence (AI)-driven drug development has recently invigorated research in anti-cancer drug development. In this work, we incorporated DFCNN, Autodock Vina docking, DeepBindBC, MD, and metadynamics to efficiently identify inhibitors of TIPE3 from a ZINC compound dataset. Six potential candidates were selected for further experimental study to validate their anti-tumor activity. Among these, three small-molecule compounds (K784-8160, E745-0011, and 7238-1516) showed significant anti-tumor activity in vitro, leading to reduced tumor cell viability, proliferation, and migration and enhanced apoptotic tumor cell death. Notably, E745-0011 and 7238-1516 exhibited selective cytotoxicity toward tumor cells with high TIPE3 expression while having little or no effect on normal human cells or tumor cells with low TIPE3 expression. A molecular docking analysis further supported their interactions with TIPE3, highlighting hydrophobic interactions and their shared interaction residues and offering insights for designing more effective inhibitors. Taken together, this work demonstrates the feasibility of incorporating deep learning and MD simulations in virtual drug screening and provides inhibitors with significant potential for anti-cancer drug development against TIPE3-.

A deep learning based multi-model approach for predicting drug-like chemical compound's toxicity.

Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.

Radiomics model based on intratumoral and peritumoral features for predicting major pathological response in non-small cell lung cancer receiving neoadjuvant immunochemotherapy.

Objective: To establish a radiomics model based on intratumoral and peritumoral features extracted from pre-treatment CT to predict the major pathological response (MPR) in patients with non-small cell lung cancer (NSCLC) receiving neoadjuvant immunochemotherapy. Methods: A total of 148 NSCLC patients who underwent neoadjuvant immunochemotherapy from two centers (SRRSH and ZCH) were retrospectively included. The SRRSH dataset (n=105) was used as the training and internal validation cohort. Radiomics features of intratumoral (T) and peritumoral regions (P1 = 0-5mm, P2 = 5-10mm, and P3 = 10-15mm) were extracted from pre-treatment CT. Intra- and inter- class correlation coefficients and least absolute shrinkage and selection operator were used to feature selection. Four single ROI models mentioned above and a combined radiomics (CR: T+P1+P2+P3) model were established by using machine learning algorithms. Clinical factors were selected to construct the combined radiomics-clinical (CRC) model, which was validated in the external center ZCH (n=43). The performance of the models was assessed by DeLong test, calibration curve and decision curve analysis. Results: Histopathological type was the only independent clinical risk factor. The model CR with eight selected radiomics features demonstrated a good predictive performance in the internal validation (AUC=0.810) and significantly improved than the model T (AUC=0.810 vs 0.619, p<0.05). The model CRC yielded the best predictive capability (AUC=0.814) and obtained satisfactory performance in the independent external test set (AUC=0.768, 95% CI: 0.62-0.91). Conclusion: We established a CRC model that incorporates intratumoral and peritumoral features and histopathological type, providing an effective approach for selecting NSCLC patients suitable for neoadjuvant immunochemotherapy.

A New Co(II)-coordination Polymer: Fluorescence Performances, Loaded with Paclitaxel-hydrogel on Breast Cancer and Molecular Docking Study.

In the current context of the increasing incidence of breast cancer, we aim to develop an efficient drug carrier for breast cancer by constructing an innovative complex consisting of a metal-organic framework (MOF) and a hydrogel. The aim of this initiative is to provide new ideas and tools for breast cancer treatment strategies through scientific research, so as to address the current challenges in breast cancer treatment. In the present study, by employment of a new Co(II)-based coordination polymer with the chemical formula of [Co(H2O)(CH3OH)L]n (1) (H2L = 5-(1 H-tetrazol-5-yl)nicotinic acid) was solvothermally synthesized by reaction of Co(NO3)2·6H2O a mixed solvent of MeOH and water. The characteristics of ligand-based absorption and emission, as unveiled by ultraviolet and fluorescence spectroscopy tests, offer insights into the distinctive electronic transitions and structural features originating from the ligand in compound 1. Using natural polysaccharide hyaluronic acid (HA) and carboxymethyl chitosan (CMCS) as raw materials, HA/CMCS hydrogels were successfully prepared by chemical method and their internal morphology was studied by scanning electron microscopy. Using paclitaxel as a drug model, we further designed and synthesized a novel metal gel particle-loaded paclitaxel drug and evaluated its inhibitory effect on breast cancer cells. Finally, the hypothesized interactions between the complex and the receptor have been confirmed through molecular docking simulation, and multiple polar interactions have been verified, which further proves the potential anti-cancer capability and excellent bioactivity. Based on this, this composite material prepared from a novel Co(II)-coordinated polymer with paclitaxel hydrogel could provide a useful pathway for the identification and treatment of breast cancer.

Prediction of microvascular invasion and pathological differentiation of hepatocellular carcinoma based on a deep learning model.

PURPOSE: To develop a deep learning (DL) model based on preoperative contrast-enhanced computed tomography (CECT) images to predict microvascular invasion (MVI) and pathological differentiation of hepatocellular carcinoma (HCC). METHODS: This retrospective study included 640 consecutive patients who underwent surgical resection and were pathologically diagnosed with HCC at two medical institutions from April 2017 to May 2022. CECT images and relevant clinical parameters were collected. All the data were divided into 368 training sets, 138 test sets and 134 validation sets. Through DL, a segmentation model was used to obtain a region of interest (ROI) of the liver, and a classification model was established to predict the pathological status of HCC. RESULTS: The liver segmentation model based on the 3D U-Network had a mean intersection over union (mIoU) score of 0.9120 and a Dice score of 0.9473. Among all the classification prediction models based on the Swin transformer, the fusion models combining image information and clinical parameters exhibited the best performance. The area under the curve (AUC) of the fusion model for predicting the MVI status was 0.941, its accuracy was 0.917, and its specificity was 0.908. The AUC values of the fusion model for predicting poorly differentiated, moderately differentiated and highly differentiated HCC based on the test set were 0.962, 0.957 and 0.996, respectively. CONCLUSION: The established DL models established can be used to noninvasively and effectively predict the MVI status and the degree of pathological differentiation of HCC, and aid in clinical diagnosis and treatment.

Quantitative detection of T315I mutations of BCR::ABL1 using digital droplet polymerase chain reaction.

BACKGROUND: T315I mutations of the BCR::ABL1 gene lead to resistance to tyrosine kinase inhibitors (TKIs). This study evaluated the performance of digital droplet polymerase chain reaction (ddPCR) in quantifying T315I mutations and their frequency in Philadelphia chromosome (Ph) positive hematological patients. METHODS: The course of disease and BCR::ABL1 fusion transcripts (e13a2, e14a2 and e1a2) were retrospectively reviewed in 21 patients with acute lymphoblastic leukemia (ALL) and 85 patients with chronic myeloid leukemia (CML). T315I mutation analysis was carried out using ddPCR and the limit of detection was assessed using mutant T315I DNA at varying variant allele fractions. RESULTS: T315I mutations were found in two ALL patients and one CML patient without remission in molecular biology and with mutation burdens of 29.20%, 40.85%, and 3.00%, respectively. The mutation burden of ALL patients was higher than that of CML patients, but there was no significant difference between the two (p-value = 0.0536). The test's limit of detection was 0.02% with a correlation coefficient greater than 0.99 between the expected and actual detection abundances. CONCLUSION: T315I mutations have a high incidence in Ph-positive ALL patients even if the course of disease is short. In molecular biology, T315I mutation detection is indicated for CML patients not in remission.

Cysteine protease inhibitor S promotes lymph node metastasis of esophageal cancer cells via VEGF-MAPK/ERK-MMP9/2 pathway.

Cysteine protease inhibitor S (CST4) plays a pivotal role in the regulation of growth, invasion, and metastasis of a variety of malignancies. However, the potential mechanism behind how CST4 contributes to CST4 in lymph node metastasis (LNM) and tumor-associated lymphangiogenesis of esophageal cancer (EC) cells has not been elucidated previously. Short hairpin RNA technique was utilized to upregulate the CST4 gene expression. Different experiments, including the tubule formation assay and immunofluorescence, were conducted to observe the cellular behavior. Enzyme-linked immunosorbent assay (ELISA) and Western blot analyses were employed to determine the expression levels of relevant proteins. In our study, we discovered that high expression of CST4 in EC cells had multiple effects. It stimulated cell proliferation, invasion, and migration and caused epithelial-mesenchymal transition (EMT). Moreover, it also inhibited the apoptosis of EC cells and caused them to stagnate in the G2/M phase. High expression of CST4 promoted the secretion of lymphangiogenic markers (TGFß1, VEGF, VEGF-C/D) in EC cells. In addition, high expression of CST4 in EC cells not only enhanced the proliferation and migration of HLECs, but also stimulated the lumen formation and F-actin expression and rearrangement of HLECs. The elevated expression of CST4 also facilitated the secretion of p-ERK1/2, MMP9, and MMP-2 in HLECs. However, various tumor-promoting effects of high expression of CST4 on HLECs could be inhibited by VEGF inhibitors in EC cells. Overall, our findings indicate that CST4 plays a significant role in the accumulation, migration, and EMT of EC cells. CST4 can activate the VEGF-MAPK/ERK-MMP9/2 signaling axis to promote LNM and lymphangiogenesis in EC.

A new method to estimate the histological stage of primary biliary cholangitis.

OBJECTIVE: To analyze the diagnostic efficacy of the periportal hypoechoic band (PHB) in the histological stage of patients with primary biliary cholangitis (PBC). METHODS: We prospectively included 77 cases of PBC pathologically or clinically confirmed, and high-frequency ultrasound (HFUS) measurements of the PHB were performed in all included patients. Ludwig staging system of histopathology was used as the gold standard. RESULTS: The width of the PHB was positively correlated with histological staging (r = 0.844, p < 0.001). By area under the receiving operating characteristic curve (AUROC), the best cutoff value for PHB for advanced stage (≥ stage 3) was 2.4 mm (AUROC: 0.934; 95%CI: 0.841-0.981) and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The correct rate for early-stage PBC was 87.9% and for the progressive stage was 93.1%. After multi-factor regression analysis, the PHB (OR = 1.331, CI = 1.105-1.603, p = 0.003) and total bilirubin (OR = 1.156, CI = 1.041-1.285, p = 0.007) were independent influencing factors for progressive PBC. CONCLUSIONS: Measurement of the PHB to assess advanced PBC is a simple and effective method. This method may complement current methods for the histological staging assessment of patients with PBC. REGISTRATION: Clinical trial registration: ChiCTR 2000032053, 2020/04/19. CLINICAL RELEVANCE STATEMENT: The measurement of periportal hypoechoic band (PHB) provides a simple and easy assessment of the degree of disease progression in patients with PBC and provides an important clinical reference in predicting the histological staging of PBC from an ultrasound perspective. KEY POINTS: • The PHB is correlated with histological staging in the patient with PBC. • The area under the ROC curves of PHB for detecting advanced stage (≥ stage 3) were 0.934 and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The application of PHB can better assess the advanced PBC. • Measurement of the PHB to assess advanced PBC is a simple and effective method that can significantly reduce the need for liver biopsy.

Covalent and non-covalent interaction of myofibrillar protein and cyanidin-3-O-glucoside: focus on structure, binding sites and in vitro digestion properties.

BACKGROUND: The aim of this study was to investigate the effects of covalent and non-covalent interactions between myofibrillar protein (MP) and cyanidin-3-O-glucoside (C3G) on protein structure, binding sites, and digestion properties. Four methods of inducing covalent cross-linking were used in the preparation of MP-C3G conjugates, including tyrosinase-catalyzed oxidation, alkaline pH shift treatment, free radical grafting, and ultrasonic treatment. A comparison was made between MP-C3G conjugates and complexes, and the analysis included sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), C3G binding ratio, liquid chromatography-tandem mass spectrometry (LC-MS/MS), protein side-chain amino acids, circular dichroism spectroscopy, three-dimensional fluorescence, particle size, and in vitro simulated digestion. RESULTS: Covalent bonding between C3G and amino acid side chains in MP was confirmed by LC-MS/MS. In covalent bonding, tryptophan residues, free amino groups and sulfhydryl groups were all implicated. Among the 22 peptides covalently modified by C3G, 30 modification sites were identified, located in lysine, histidine, tryptophan, arginine and cysteine. In vitro simulated digestion experiments showed that the addition of C3G significantly reduced the digestibility of MP, with the covalent conjugate showing lower digestibility than the non-covalent conjugate. Moreover, the digestibility of protein decreased more during intestinal digestion, possibly because covalent cross-linking of C3G and MP further inhibited trypsin targeting sites (lysine and arginine). CONCLUSION: Covalent cross-linking of C3G with myofibrillar proteins significantly affected protein structure and reduced protein digestibility by occupying more trypsin binding sites. © 2023 Society of Chemical Industry.

Fascin actin-bundling protein 1 regulates non-small cell lung cancer progression by influencing the transcription and splicing of tumorigenesis-related genes.

Background: High mortality rates are prevalent among patients with non-small-cell lung cancer (NSCLC), and effective therapeutic targets are key prognostic factors. Fascin actin-bundling protein 1 (FSCN1) promotes NSCLC; however, its role as an RNA-binding protein in NSCLC remains unexplored. Therefore, we aimed to explore FSCN1 expression and function in A549 cells. Method: We screened for alternative-splicing events and differentially expressed genes (DEGs) after FSCN1 silence via RNA-sequencing (RNA-seq). FSCN1 immunoprecipitation followed by RNA-seq were used to identify target genes whose mRNA expression and pre-mRNA alternative-splicing levels might be influenced by FSCN1. Results: Silencing FSCN1 in A549 cells affected malignant phenotypes; it inhibited proliferation, migration, and invasion, and promoted apoptosis. RNA-seq analysis revealed 2,851 DEGs and 3,057 alternatively spliced genes. Gene ontology-based functional enrichment analysis showed that downregulated DEGs and alternatively splicing genes were enriched for the cell-cycle. FSCN1 promoted the alternative splicing of cell-cycle-related mRNAs involved in tumorigenesis (i.e., BCCIP, DLGAP5, PRC1, RECQL5, WTAP, and SGO1). Combined analysis of FSCN1 RNA-binding targets and RNA-seq data suggested that FSCN1 might affect ACTG1, KRT7, and PDE3A expression by modulating the pre-mRNA alternative-splicing levels of NME4, NCOR2, and EEF1D, that were bound to long non-coding RNA transcripts (RNASNHG20, NEAT1, NSD2, and FTH1), which were highly abundant. Overall, extensive transcriptome analysis of gene alternative splicing and expression levels was performed in cells transfected with FSCN1 short-interfering RNA. Our data provide global insights into the regulatory mechanisms associated with the roles of FSCN1 and its target genes in lung cancer.

Nuclear cGAS restricts L1 retrotransposition by promoting TRIM41-mediated ORF2p ubiquitination and degradation.

Cyclic GMP-AMP synthase (cGAS), initially identified as a cytosolic DNA sensor, detects DNA fragments to trigger an innate immune response. Recently, accumulating evidence reveals the presence of cGAS within the nucleus. However, the biological functions of nuclear cGAS are not fully understood. Here, we demonstrate that nuclear cGAS represses LINE-1 (L1) retrotransposition to preserve genome integrity in human cells. Mechanistically, the E3 ligase TRIM41 interacts with and ubiquitinates ORF2p to influence its stability, and cGAS enhances the association of ORF2p with TRIM41, thereby promoting TRIM41-mediated ORF2p degradation and the suppression of L1 retrotransposition. In response to DNA damage, cGAS is phosphorylated at serine residues 120 and 305 by CHK2, which promotes cGAS-TRIM41 association, facilitating TRIM41-mediated ORF2p degradation. Moreover, we show that nuclear cGAS mediates the repression of L1 retrotransposition in senescent cells induced by DNA damage agents. We also identify several cancer-associated cGAS mutations that abolish the suppressive effect on L1 retrotransposition by disrupting the CHK2-cGAS-TRIM41-ORF2p regulatory axis. Together, these findings indicate that nuclear cGAS exhibits an inhibitory function in L1 retrotransposition which could provide avenues for future interventions in both aging and tumorigenesis.

[Effectiveness of one-stage posterior eggshell osteotomy and long-segment pedicle screw fixation for ankylosing spondylitis kyphosis combined with acute thoracolumbar vertebral fracture].

Objective: To explore the safety and effectiveness of one-stage posterior eggshell osteotomy and long-segment pedicle screw fixation in the treatment of ankylosing spondylitis kyphosis combined with acute thoracolumbar vertebral fracture. Methods: A clinical data of 20 patients with ankylosing spondylitis kyphosis combined with acute thoracolumbar spine fracture, who were treated with one-stage posterior eggshell osteotomy and long-segment pedicle screw fixation between April 2016 and January 2022, was retrospectively analyzed. Among them, 16 cases were male and 4 cases were female; their ages ranged from 32 to 68 years, with an average of 45.9 years. The causes of injury included 10 cases of sprain, 8 cases of fall, and 2 cases of falling from height. The time from injury to operation ranged from 1 to 12 days, with an average of 7.1 days. The injured segment was T 11 in 2 cases, T 12 in 2 cases, L 1 in 6 cases, and L 2 in 10 cases. X-ray film and CT showed that the patients had characteristic imaging manifestations of ankylosing spondylitis, and the fracture lines were involved in the anterior, middle, and posterior columns and accompanied by different degrees of kyphosis and vertebral compression; and MRI showed that 12 patients had different degrees of nerve injuries. The operation time, intraoperative bleeding, intra- and post-operative complications were recorded. The visual analogue scale (VAS) score and Oswestry disability index (ODI) were used to evaluate the low back pain and quality of life, and the American spinal cord injury association (ASIA) classification was used to evaluate the neurological function. X-ray films were taken, and local Cobb angle (LCA) and sagittal vertical axis (SVA) were measured to evaluate the correction of the kyphosis. Results: All operations were successfully completed and the operation time ranged from 127 to 254 minutes (mean, 176.3 minutes). The amount of intraoperative bleeding ranged from 400 to 950 mL (mean, 722.5 mL). One case of dural sac tear occurred during operation, and no cerebrospinal fluid leakage occurred after repair, and the rest of the patients did not suffer from neurological and vascular injuries, cerebrospinal fluid leakage, and other related complications during operation. All incisions healed by first intention without infection or fat liquefaction. All patients were followed up 8-16 months (mean, 12.5 months). The VAS score, ODI, LCA, and SVA at 3 days after operation and last follow-up significantly improved when compared with those before operation ( P<0.05), and the difference between 3 days after operation and last follow-up was not significant ( P>0.05). The ASIA grading of neurological function at last follow-up also significantly improved when compared with that before operation ( P<0.05), including 17 cases of grade E and 3 cases of grade D. At last follow-up, all bone grafts achieved bone fusion, and no complications such as loosening, breaking of internal fixation, and pseudoarthrosis occurred. Conclusion: One-stage posterior eggshell osteotomy and long-segment pedicle screw fixation is an effective surgical procedure for ankylosing spondylitis kyphosis combined with acute thoracolumbar vertebral fracture. It can significantly relieve patients' clinical symptoms and to some extent, alleviate the local kyphotic deformity.

Ultrasound imaging findings in primary biliary cholangitis.

BACKGROUND: Our study aimed to analyze the characteristics of ultrasound images corresponding to each histological stage of primary biliary cholangitis (PBC). METHODS: We prospectively analyzed 75 confirmed cases of PBC and used liver biopsy as the gold standard to determine the disease stage. RESULTS: The typical ultrasound images of patients with PBC were characterized by a thickening of the portal vein wall (PVW) and periportal hypoechoic band (PHB) width with increasing histological stages, and significant increases in the left hepatic lobe diameter (LHLD) in stage II (by 64.0%) and stage III (by 69.2%). PHB width (r = 0.857, p < 0.001), PVW thickness (r = 0.488, p < 0.001), and spleen area (r = 0.8774, p < 0.001) were positively correlated with the histological stage. Significant changes were noted in the liver surface, echo texture, and edge between different stages. The areas under the receiver operating characteristic curve of composite indicators were 0.965 for predicting progressive PBC(≥ stage 2), and 0.926 for predicting advanced PBC(≥ stage 3). CONCLUSIONS: The ultrasound imaging characteristics of patients with PBC varied according to the histological staging. LHLD, PVW thickness, and PHB width were significantly correlated with the histological stage. A combination of high- and low-frequency ultrasound imaging can provide relevant cues regarding the degree of PBC progression and important clinical reference values. The application of all the ultrasound image findings as the composite indicators can better predict progressive and advanced PBC, providing important clinical reference values.

Mycobacterium tuberculosis suppresses host DNA repair to boost its intracellular survival.

Mycobacterium tuberculosis (Mtb) triggers distinct changes in macrophages, resulting in the formation of lipid droplets that serve as a nutrient source. We discover that Mtb promotes lipid droplets by inhibiting DNA repair responses, resulting in the activation of the type-I IFN pathway and scavenger receptor-A1 (SR-A1)-mediated lipid droplet formation. Bacterial urease C (UreC, Rv1850) inhibits host DNA repair by interacting with RuvB-like protein 2 (RUVBL2) and impeding the formation of the RUVBL1-RUVBL2-RAD51 DNA repair complex. The suppression of this repair pathway increases the abundance of micronuclei that trigger the cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway and subsequent interferon-ß (IFN-ß) production. UreC-mediated activation of the IFN-ß pathway upregulates the expression of SR-A1 to form lipid droplets that facilitate Mtb replication. UreC inhibition via a urease inhibitor impaired Mtb growth within macrophages and in vivo. Thus, our findings identify mechanisms by which Mtb triggers a cascade of cellular events that establish a nutrient-rich replicative niche.

Tumor-derived exosomes RNA expression profiling identifies the prognosis, immune characteristics, and treatment in HR+/HER2-breast cancer.

Exosomes play crucial roles in intercellular communication and are involved in the onset and progression of various types of cancers, including breast cancer. However, the RNA composition of breast cancer-derived exosomes has not been comprehensively explored. We conducted microarray assays on exosomes isolated from breast cancer and healthy breast epithelial cells from three patients with hormone receptor (HR) +/ human epidermal growth factor receptor (HER2) - breast cancer and identified 817 differentially expressed genes (DEGs). Among these, 315 upregulated tumor-derived exosome genes (UTEGs) were used to classify HR+/HER2- breast cancers into two categories, revealing a difference in survival rates between the groups. We developed and validated a novel prognostic exosome score (ES) model consisting of four UTEGs that provides a refined prognosis prediction in HR+/HER2-breast cancer. ES reflects various immune-related features, including somatic variation, immunogenicity, and tumor immune infiltrate composition. Our findings indicate a considerable positive correlation between the ES and drug sensitivity values for vincristine, paclitaxel, and docetaxel. However, ES was remarkably higher in the endocrine therapy non-responder group than in the responder group. Immunohistochemistry confirmed the remarkable expression of the four model genes in tumor tissues, and their expression in MCF-7 cell exosomes was higher than that in MCF10A cells, as verified via qPCR. In summary, tumor-derived exosome genes provide novel insights into the subtyping, prognosis, and treatment of HR+/HER2-breast cancer.

Deep learning-assisted LI-RADS grading and distinguishing hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT: a two-center study.

OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting and Data System (LI-RADS) grading of high-risk liver lesions and distinguish hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT. METHODS: This retrospective study included 1049 patients with 1082 lesions from two independent hospitals that were pathologically confirmed as HCC or non-HCC. All patients underwent a four-phase CT imaging protocol. All lesions were graded (LR 4/5/M) by radiologists and divided into an internal (n = 886) and external cohort (n = 196) based on the examination date. In the internal cohort, Swin-Transformer based on different CT protocols were trained and tested for their ability to LI-RADS grading and distinguish HCC from non-HCC, and then validated in the external cohort. We further developed a combined model with the optimal protocol and clinical information for distinguishing HCC from non-HCC. RESULTS: In the test and external validation cohorts, the three-phase protocol without pre-contrast showed κ values of 0.6094 and 0.4845 for LI-RADS grading, and its accuracy was 0.8371 and 0.8061, while the accuracy of the radiologist was 0.8596 and 0.8622, respectively. The AUCs in distinguishing HCC from non-HCC were 0.865 and 0.715 in the test and external validation cohorts, while those of the combined model were 0.887 and 0.808. CONCLUSION: The Swin-Transformer based on three-phase CT protocol without pre-contrast could feasibly simplify LI-RADS grading and distinguish HCC from non-HCC. Furthermore, the DL model have the potential in accurately distinguishing HCC from non-HCC using imaging and highly characteristic clinical data as inputs. CLINICAL RELEVANCE STATEMENT: The application of deep learning model for multiphase CT has proven to improve the clinical applicability of the Liver Imaging Reporting and Data System and provide support to optimize the management of patients with liver diseases. KEY POINTS: • Deep learning (DL) simplifies LI-RADS grading and helps distinguish hepatocellular carcinoma (HCC) from non-HCC. • The Swin-Transformer based on the three-phase CT protocol without pre-contrast outperformed other CT protocols. • The Swin-Transformer provide help in distinguishing HCC from non-HCC by using CT and characteristic clinical information as inputs.

Use of IDEAL-IQ in Quantifying Femoral Bone Marrow Involvement in Gaucher Disease.

OBJECTIVE: To quantitatively measure femoral bone marrow involvement in patients with Gaucher disease (GD) by using fat fraction (FF) derived from the iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) technique. METHODS: Bilateral femora of 23 patients with type 1 GD receiving low-dose imiglucerase treatment were prospectively scanned using structural magnetic resonance imaging sequences and an IDEAL-IQ sequence. Femoral bone marrow involvement was evaluated by both semiquantification (bone marrow burden [BMB] score based on magnetic resonance imaging structural images) and quantification (FF derived from IDEAL-IQ) methods. These patients were further divided into subgroups according to whether they underwent splenectomy or had bone complications. The interreader agreement of measurements and the correlation between FF and clinical status were statistically analyzed. RESULTS: In patients with GD, both BMB and FF evaluation of femora showed good interreader concordance (intraclass correlation coefficient = 0.98 and 0.99, respectively), and FF highly correlated with BMB score ( P < 0.001). The longer the duration of disease, the lower the FF ( P = 0.026). Femoral FF was lower in subgroups with splenectomy or bone complications than those without splenectomy or bone complications (0.47 ± 0.08 vs 0.60 ± 0.15, 0.51 ± 0.10 vs 0.61 ± 0.17, respectively, both P < 0.05). CONCLUSION: Femoral FF derived from IDEAL-IQ could be used to quantify femoral bone marrow involvement in patients with GD, and low bone marrow FF may predict worse outcomes of GD patients in this small-scale study.

Identification and validation of IgG N-glycosylation biomarkers of esophageal carcinoma.

Introduction: Altered Immunoglobulin G (IgG) N-glycosylation is associated with aging, inflammation, and diseases status, while its effect on esophageal squamous cell carcinoma (ESCC) remains unknown. As far as we know, this is the first study to explore and validate the association of IgG N-glycosylation and the carcinogenesis progression of ESCC, providing innovative biomarkers for the predictive identification and targeted prevention of ESCC. Methods: In total, 496 individuals of ESCC (n=114), precancerosis (n=187) and controls (n=195) from the discovery population (n=348) and validation population (n=148) were recruited in the study. IgG N-glycosylation profile was analyzed and an ESCC-related glycan score was composed by a stepwise ordinal logistic model in the discovery population. The receiver operating characteristic (ROC) curve with the bootstrapping procedure was used to assess the performance of the glycan score. Results: In the discovery population, the adjusted OR of GP20 (digalactosylated monosialylated biantennary with core and antennary fucose), IGP33 (the ratio of all fucosylated monosyalilated and disialylated structures), IGP44 (the proportion of high mannose glycan structures in total neutral IgG glycans), IGP58 (the percentage of all fucosylated structures in total neutral IgG glycans), IGP75 (the incidence of bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral IgG glycans), and the glycan score are 4.03 (95% CI: 3.03-5.36, P<0.001), 0.69 (95% CI: 0.55-0.87, P<0.001), 0.56 (95% CI: 0.45-0.69, P<0.001), 0.52 (95% CI: 0.41-0.65, P<0.001), 7.17 (95% CI: 4.77-10.79, P<0.001), and 2.86 (95% CI: 2.33-3.53, P<0.001), respectively. Individuals in the highest tertile of the glycan score own an increased risk (OR: 11.41), compared with those in the lowest. The average multi-class AUC are 0.822 (95% CI: 0.786-0.849). Findings are verified in the validation population, with an average AUC of 0.807 (95% CI: 0.758-0.864). Discussion: Our study demonstrated that IgG N-glycans and the proposed glycan score appear to be promising predictive markers for ESCC, contributing to the early prevention of esophageal cancer. From the perspective of biological mechanism, IgG fucosylation and mannosylation might involve in the carcinogenesis progression of ESCC, and provide potential therapeutic targets for personalized interventions of cancer progression.

Deep Learning-Based Bioactive Therapeutic Peptide Generation and Screening.

Many bioactive peptides demonstrated therapeutic effects over complicated diseases, such as antiviral, antibacterial, anticancer, etc. It is possible to generate a large number of potentially bioactive peptides using deep learning in a manner analogous to the generation of de novo chemical compounds using the acquired bioactive peptides as a training set. Such generative techniques would be significant for drug development since peptides are much easier and cheaper to synthesize than compounds. Despite the limited availability of deep learning-based peptide-generating models, we have built an LSTM model (called LSTM_Pep) to generate de novo peptides and fine-tuned the model to generate de novo peptides with specific prospective therapeutic benefits. Remarkably, the Antimicrobial Peptide Database has been effectively utilized to generate various kinds of potential active de novo peptides. We proposed a pipeline for screening those generated peptides for a given target and used the main protease of SARS-COV-2 as a proof-of-concept. Moreover, we have developed a deep learning-based protein-peptide prediction model (DeepPep) for rapid screening of the generated peptides for the given targets. Together with the generating model, we have demonstrated that iteratively fine-tuning training, generating, and screening peptides for higher-predicted binding affinity peptides can be achieved. Our work sheds light on developing deep learning-based methods and pipelines to effectively generate and obtain bioactive peptides with a specific therapeutic effect and showcases how artificial intelligence can help discover de novo bioactive peptides that can bind to a particular target.

Human cytomegalovirus glycoprotein B genotypic distributions and viral load in symptomatic infants.

INTRODUCTION: HCMV infection is widespread in humans. This retrospective study aimed to explore the relationship between human cytomegalovirus (HCMV) glycoprotein B (gB) genotype distribution, viral load, and the demographic and clinical features of symptomatic infants. The detection rate of HCMV in blood and urine samples was also compared. METHODOLOGY: Retrospective data from 265 infants who underwent urine HCMV DNA testing were analyzed. The viral load and gB genotype were detected in 91 HCMV positive infants by quantitative fluorescence polymerase chain reaction (PCR) and DNA sequencing, respectively. RESULTS: The positive rate of HCMV infection was 46.04% (122/265) in all infants, and increased rapidly with age. Among the 91 infants investigated, liver function abnormality was the most common diagnosis (34/91, 37.36%), followed by pneumonia (21/91, 23.07%). Sequence analysis of gB yielded two genetic subtypes: the most prevalent gB3 (47/91, 51.65%), followed by gB1 (44/91, 48.35%). The gB3 HCMV infection was more prevalent in infants aged 0-2 months than in infants aged 3-12 months (χ2 = 4.38, p = 0.0364). The data showed that ALT and AST levels were significantly higher in the anti-HCMV IgM+IgG- group than in the anti-HCMV IgM+IgG+ and IgM-IgG+ groups. In addition, this study showed that the detection rate of HCMV DNA in the blood was significantly lower than that in the urine (χ2 = 6.7131, p = 0.0096). CONCLUSIONS: This study presents the HCMV infection status of infants and its relationship with their demographic characteristics and clinical manifestations. In addition, this study suggests that urinary PCR is the most appropriate assay for detecting HCMV infections.