Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

OBJECTIVES: To investigate the genomic characteristics and prognostic factors of juvenile myelomonocytic leukemia (JMML) with RAS mutations. METHODS: A retrospective analysis was conducted on the clinical data of JMML children with RAS mutations treated at the Hematology Hospital of Chinese Academy of Medical Sciences, from January 2008 to November 2022. RESULTS: A total of 34 children were included, with 17 cases (50%) having isolated NRAS mutations, 9 cases (27%) having isolated KRAS mutations, and 8 cases (24%) having compound mutations. Compared to children with isolated NRAS mutations, those with NRAS compound mutations showed statistically significant differences in age at onset, platelet count, and fetal hemoglobin proportion (P<0.05). Cox proportional hazards regression model analysis revealed that hematopoietic stem cell transplantation (HSCT) and hepatomegaly (≥2 cm below the costal margin) were factors affecting the survival rate of JMML children with RAS mutations (P<0.05); hepatomegaly was a factor affecting survival in the non-HSCT group (P<0.05). CONCLUSIONS Children with NRAS compound mutations have a later onset age compared to those with isolated NRAS mutations. At initial diagnosis, children with NRAS compound mutations have poorer peripheral platelet and fetal hemoglobin levels than those with isolated NRAS mutations. Liver size at initial diagnosis is related to the prognosis of JMML children with RAS mutations. HSCT can improve the prognosis of JMML children with RAS mutations.
Humans ; Leukemia, Myelomonocytic, Juvenile/therapy* ; Mutation ; Male ; Female ; Child, Preschool ; Retrospective Studies ; Child ; Infant ; GTP Phosphohydrolases/genetics* ; Membrane Proteins/genetics* ; Adolescent ; Hematopoietic Stem Cell Transplantation ; Proportional Hazards Models ; Proto-Oncogene Proteins p21(ras)/genetics* ; Prognosis

OBJECTIVE: To investigate the risk factors, clinical characteristics, and bacterial resistance of bloodstream infections caused by Streptococcus mitis in children with hematological disease, so as to provide a reference for infection control. METHODS: The clinical information and laboratory findings of pediatric patients complicated with blood cultures positive for Streptococcus mitis from January 2018 to December 2020 in the Institute of Hematology & Blood Diseases Hospital were searched and collected. The clinical characteristics, susceptibility factors, and antibiotic resistance of the children were retrospectively analyzed. RESULTS: Data analysis from 2018 to 2020 showed that the proportion of Streptococcus mitis isolated from bloodstream infections in children (≤14 years old) with hematological diseases was the highest (19.91%) and significantly higher than other bacteria, accounting for 38.64% of Gram-positive cocci, and presented as an increasing trend year by year. A total of 427 children tested positive blood cultures, including 85 children with bloodstream infections caused by Streptococcus mitis who tested after fever. Most children experienced a recurrent high fever in the early and middle stages (≤6 d) of neutropenia and persistent fever for more than 3 days. After adjusting the antibiotics according to the preliminary drug susceptibility results, the body temperature of most children (63.5%) returned to normal within 4 days. The 85 children were mainly diagnosed with acute myeloid leukemia (AML), accounting for 84.7%. The proportion of children in the neutropenia stage was 97.7%. The incidence of oral mucosal damage, lung infection, and gastrointestinal injury symptoms was 40%, 31.8%, and 27.1%, respectively. The ratio of elevated C-reactive protein (CRP) and procalcitonin was 65.9% and 9.4%, respectively. All isolated strains of Streptococcus mitis were not resistant to vancomycin and linezolid, and the resistance rate to penicillin, cefotaxime, levofloxacin, and quinupristin-dalfopristin was 10.6%, 8.2%, 9.4%, and 14.1%, respectively. None of children died due to bloodstream infection caused by Streptococcus mitis. CONCLUSION The infection rate of Streptococcus mitis is increasing year by year in children with hematological diseases, especially in children with AML. Among them, neutropenia and oral mucosal damage after chemotherapy are high-risk infection factors. The common clinical symptoms include persistent high fever, oral mucosal damage, and elevated CRP. Penicillin and cephalosporins have good sensitivity. Linezolid, as a highly sensitive antibiotic, can effectively control infection and shorten the course of disease.
Humans ; Child ; Streptococcal Infections/microbiology* ; Retrospective Studies ; Hematologic Diseases/complications* ; Streptococcus mitis ; Drug Resistance, Bacterial ; Risk Factors ; Microbial Sensitivity Tests ; Anti-Bacterial Agents ; Female ; Male ; Bacteremia/microbiology* ; Child, Preschool ; Adolescent

OBJECTIVE: To establish venetoclax-resistant acute myeloid leukemia (AML) cell lines, assess the sensitivity of venetoclax-resistant cell lines to the BCL-2 protein family, and investigate their resistance mechanisms. METHODS: CCK-8 method was used to screen AML cell lines (MV4-11, MOLM13, OCI-AML2) that were relatively sensitive to venetoclax. Low concentrations of venetoclax continuously induced drug-resistance development in the cell lines. Changes in cell viability and apoptosis rate before and after resistance development were measured using the CCK-8 method and flow cytometry. BH3 profiling assay was performed to anayze the transform of mitochondrion-dependent apoptosis pathway as well as the sensitivity of resistant cell lines to BCL-2 family proteins and small molecule inhibitors. Real-time fluorescence quantitative PCR (RT-qPCR) was utilized to examine changes in the expression levels of BCL-2 protein family members in both venetoclax-resistant cell lines and multidrug-resistant patients. RESULTS: Venetoclax-resistant cell lines of MV4-11, MOLM13, and OCI-AML2 were successfully established, with IC₅₀ values exceeding 10-fold. Under the same concentration of venetoclax, the apoptosis rate of resistant cells decreased significantly (P < 0.05). BH3 profiling assay revealed that the drug-resistant cell lines showed increased sensitivity to many pro-apoptotic proteins (such as BIM,BID and NOXA). RT-qPCR showed significantly upregulated MCL1 and downregulated NOXA1 were detected in drug-resistant cell lines. Expression changes in MCL1 and NOXA1 in venetoclax-resistant patients were consistent with our established drug-resistant cell line results. CONCLUSION The venetoclax-resistant AML cell lines were successfully established through continuous induction with low concentrations of venetoclax. The venetoclax resistance resulted in alterations in the mitochondrial apoptosis pathway of the cells and an increased sensitivity of cells to pro-apoptotic proteins BIM, BID, and NOXA, which may be associated with the upregulation of MCL1 expression and downregulation of NOXA1 expression in the drug-resistant cells.
Humans ; Sulfonamides/pharmacology* ; Drug Resistance, Neoplasm ; Bridged Bicyclo Compounds, Heterocyclic/pharmacology* ; Leukemia, Myeloid, Acute/pathology* ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; Cell Line, Tumor ; Apoptosis ; Antineoplastic Agents/pharmacology*

Analyze the changes in phenolic components and gene expression profiles of Tetrastigma hemsleyanum leaves with supplemental blue light, and screen differentially expressed genes related to phenolic metabolism, providing a basis for improving the quality of T. hemsleyanum leaves. Using the leaves of T. hemsleyanum under supplemental blue light and visible light as research materials, the content of phenolic components such as neochlorogenic acid, chlorogenic acid, and 3-O-coumaroyl quinic acid was significantly increased by supplemental blue light. A total of 102 949 unigenes were obtained from the transcriptome, including 14 564 differentially expressed unigenes. They can be divided into 52 subclasses by gene ontology (GO) function, kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis showed that these differentially expressed unigenes were significantly enriched in phenolic metabolic pathways such as phenylpropane biosynthesis, flavonoid biosynthesis and isoflavone biosynthesis. A total of 63 differentially expressed unigenes were identified in the pathways related to the biosynthesis of phenolic cpmponents, including 19 key enzymes such as phenylalanine ammonia-lyase (PAL), cinnamyl-alcohol dehydrogenase (CAD), flavonol synthase (FLS), and so on. This study greatly enriched the genetic data information of T. hemsleyanum and laid a foundation for analyzing the mechanism of blue light promoting the biosynthesis of phenols and molecular breeding of T. hemsleyanum.

Objective To investigate the efficacy and safety of camrelizumab monoclonal antibody combined with molecular-targeted therapy in elderly patients with unresectable or advanced hepatocellular carcinoma(HCC).Methods A retrospective analysis was performed for the patients with unresectable/advanced HCC who attended six hospitals from January 1,2019 to March 31,2021,and all patients received camrelizumab monoclonal antibody treatment,among whom 84.8%also received targeted therapy.According to the age of the patients,they were divided into elderly group(≥65 years)and non-elderly group(＜65 years).The two groups were assessed in terms of overall survival(OS),progression-free survival(PFS),objective response rate(ORR),disease control rate(DCR),and immune-related adverse events(irAE).The chi-square test or the Fisher's exact test was used for comparison of categorical data between groups;the independent samples t-test was used for comparison of normally distributed continuous data,and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups.The Kaplan-Meier method was used for survival analysis,and the log-rank test was used for comparison of survival curves.Univariate and multivariate Cox proportional hazards regression analyses were used to determine the independent influencing factors for PFS and DCR at 6 months.Results A total of 99 HCC patients were enrolled,with 27 in the elderly group and 72 in the non-elderly group.The elderly group had an OS rate of 67.8%,an ORR of 44.4%,and a DCR of 74.1%at 12 months and a median PFS of 6.4(95%confidence interval[CI]:3.0-12.4)months,with no significant differences compared with the non-elderly group(all P＞0.05).The median OS was unavailable for the elderly group,while the non-elderly group had an OS of 18.9(95%CI:13.0-24.8)months;there was no significant difference between the two groups(P=0.485).The univariate and multivariate Cox regression analyses showed that major vascular invasion(MVI)was an independent risk factor for PFS(hazard ratio[HR]=2.603,95%CI:1.136-5.964,P=0.024)and DCR(HR=3.963,95%CI:1.671-9.397,P=0.002)at 6 months,while age,sex,etiology of HBV infection,presence of extrahepatic metastasis,Child-Pugh class B,and alpha-fetoprotein＞400 ng/mL were not associated with PFS or DCR at 6 months.For the elderly group,the incidence rates of any irAE and grade 3/4 irAE were 51.9%and 25.9%,respectively,with no significant differences compared with the non-elderly group(P＞0.05),and skin disease was the most common irAE in both groups(39.4%).Conclusion Camrelizumab monoclonal antibody combined with molecular-targeted therapy has similar efficacy and safety in patients with unresectable/advanced HCC aged≥65 years and those aged＜65 years.MVI is associated with suboptimal response to immunotherapy and poor prognosis.