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.

Physiologically based pharmacokinetic (PBPK) models have been widely used to predict various stages of drug absorption, distribution, metabolism and excretion. Models based on machine learning (ML) and artificial intelligence (AI) can provide better ideas for the construction of PBPK models, which can accelerate the prediction speed and improve the prediction quality of PBPK. ML and AL can complement the advantages of PBPK model to accelerate the progress of drug research and development. This review introduces the application of machine learning and artificial intelligence in pharmacokinetics, summarizes the research progress of physiological pharmacokinetic models based on machine learning and artificial intelligence, and analyzes the limitations of machine learning and artificial intelligence applications and their application prospects and prospects.

Intestinal organoids are constructed by crypts or stem cells from the intestine under the 3D support of the culture matrix. They contain all mature cells of the intestine, and have become a new and efficient platform for studying the mechanism of intestinal diseases. Compared with 2D cell culture, organoids can not only more effectively simulate the physiological structure and function of the intestine, but also better restore the true ecology of the intestine in different external environments. Therefore, it is more widely used in the study of pathogenesis of different intestinal diseases. This article reviewed the new progress of intestinal organoids culture, and the application and progress of intestinal organoids in the pathogenesis of inflammatory bowel diseases, colorectal cancer and celiac disease in recent years, and also discussed the application of intestinal organoids in drug research and development and screening.

Bone organoids can simulate the complex structure and function of the bone tissues, which makes them a frontier technology in organoid researches. Bone organoids show a tremendous potential of applications in bone disease modeling, bone injury repair, and medicine screening. Although advancements have been made so far in constructing bone organoids with functional structures like mineralization, bone marrow, trabecular bone, callus, woven bone, etc, the researches in this field are confronted with numerous challenges such as lack of standardized construction strategies and unified evaluation criteria, which limits their further promotion and application. To standardize researches in bone organoids, the Orthopedic Expert Committee of Geriatric Branch of Chinese Association of Gerontology and Geriatrics, the Youth Osteoporosis Group of Orthopedic Branch of Chinese Medical Association, the Osteoporosis Group of Orthopedic Surgeon Branch of Chinese Medical Doctor Association, and the Osteoporosis Committee of Shanghai Association of Integrated Traditional Chinese and Western Medicine organized related experts to formulate Expert consensus on the construction, evaluation, and application of bone organoids ( version 2024) based on an evidence-based approach. A total of 17 recommendations were put forth, aiming to standardize researches and clinical applications of bone organoids and enhance their value in scientific research and clinical practice.

Background: Intrahepatic cholangiocarcinoma (ICC) is a highly desmoplastic tumor with poor prognosis even after curative resection. We investigated the associations between the composition of the ICC stroma and immune cell infiltration and aimed to develop a stromal-immune signature to predict prognosis in surgically treated ICC. Patients and methods: We recruited 359 ICC patients and performed immunohistochemistry to detect α-smooth muscle actin (α-SMA), CD3, CD4, CD8, Foxp3, CD68, and CD66b. Aniline was used to stain collagen deposition. Survival analyses were performed to detect prognostic values of these markers. Recursive partitioning for a discrete-time survival tree was applied to define a stromal-immune signature with distinct prognostic value. We delineated an integrated stromal-immune signature based on immune cell subpopulations and stromal composition to distinguish subgroups with different recurrence-free survival (RFS) and overall survival (OS) time. Results: We defined four major patterns of ICC stroma composition according to the distributions of α-SMA and collagen: dormant (α-SMAlow/collagenhigh), fibrogenic (α-SMAhigh/collagenhigh), inert (α-SMAlow/collagenlow), and fibrolytic (α-SMAhigh/collagenlow). The stroma types were characterized by distinct patterns of infiltration by immune cells. We divided patients into six classes. Class I, characterized by high CD8 expression and dormant stroma, displayed the longest RFS and OS, whereas Class VI, characterized by low CD8 expression and high CD66b expression, displayed the shortest RFS and OS. The integrated stromal-immune signature was consolidated in a validation cohort. Conclusion We developed and validated a stromal-immune signature to predict prognosis in surgically treated ICC. These findings provide new insights into the stromal-immune response to ICC.

Huocao(a traditional Chinese herbal medicine) moxibustion is a characteristic technology in Yi medicine suitable for cold-dampness diseases. Huocao, as the moxibustion material, is confusedly used in clinical practice and little is known about its quality control. In this study, UPLC method was used to establish the chemical fingerprint of non-volatile components in Huocao, and the contents of eight phenolic acids such as chlorogenic acid were determined. Multivariate statistical analysis was performed to obtain the indicator components of Huocao for quality evaluation, and thus a comprehensive evaluation system for the quality of Huocao was built. The UPLC fingerprints of 49 batches of Huocao were established, and there were 20 common peaks, of which eight phenolic acids including neochlorogenic acid and chlorogenic acid were identified. Except for three batches of Huocao, the similarity of the other 46 batches was higher than 0.89, suggesting that the established fingerprint method could be used for quality control of the medicinal herb. The correlation coefficient between entropy weight score of the eight phenolic acids and comprehensive fingerprint score in Huocao was 0.875(P<0.01), which indicated that the eight phenolic acids could be used as indicator components for the quality evaluation of Huocao. Furthermore, in multivariate statistical analysis on the common peaks of fingerprint and the contents of the eight phenolic acids, chlorogenic acid, isochlorogenic acid A and isochlorogenic acid C were screened to be the indicator components. The results revealed that the proposed method achieved a simple and accurate quality control of Huocao based on UPLC fingerprint and multi-component content determination, which provided useful data for establishing the quality standard of Huocao.
Chlorogenic Acid ; Entropy ; Hydroxybenzoates ; Quality Control

Humans ; Pulmonary Alveolar Proteinosis/pathology*

In this study, UPLC-Q-Exactive-MS/MS was used to rapidly analyze the chemical constituents of Meconopsis quintupli-nervia, and the anti-liver fibrosis mechanism of M. quintuplinervia was preliminarily analyzed by network pharmacology, molecular docking, and cell experiments. The chemical constituents of M. quintuplinervia were identified according to the information of MS~1 and MS~2, as well as the data in the literature and databases. SwissTargetPrediction and TargetNet were used to predict the potential targets. The targets related to liver fibrosis were collected from GeneCards and OMIM. The protein-protein interaction(PPI) network was constructed by STRING. Cytoscape 3.6.1 was used to construct and analyze the "constituent-target-disease" network to obtain key targets and their corresponding constituents in the network. DAVID 6.8 was used for GO analysis and KEGG signaling pathway enrichment analysis. Finally, the preliminary verification was carried out by molecular docking and cell experiments. As a result, 106 chemical constituents were identified from M. quintuplinervia, including 66 flavonoids, 16 alkaloids, 18 phenolic acids, 1 anthocyanin, and 5 other constituents. Among them, 3 constituents were identified as potential new compounds, and 59 constituents were reported in M. quintuplinervia for the first time. Network pharmacology analysis showed that M. quintuplinervia presumably acted on AKT1, SRC, JUN, EGFR, STAT3, HSP90 AA1, MAPK3, and other core targets through luteolin, isorhamnetin, quercetin, apigenin, kaempferide, amurine, 2-methylflavinantine, allocryptopine, the multi and other active compounds, thereby regulating the PI3 K/AKT signaling pathway, pathways in cancer, proteoglycans in cancer, FoxO signaling pathway, and other pathways to exert anti-liver fibrosis effects. M. quintuplinervia extract(MQE) could significantly down-regulate PI3 K and AKT protein levels in the HSC-T6 cell model induced by TGF-β1, suggesting that MQE may have the ability to regulate the PI3 K/AKT signaling pathway. The findings of this study indicated that the anti-liver fibrosis effect of M. quintuplinervia had multi-constituent, multi-target, and multi-pathway characteristics, which may provide a scientific basis for the research on the pharmacodynamic materials, action mechanism, and quality markers of M. quintupli-nervia.
Tandem Mass Spectrometry ; Molecular Docking Simulation ; Network Pharmacology ; Proto-Oncogene Proteins c-akt ; Papaveraceae ; Liver Cirrhosis ; Drugs, Chinese Herbal/pharmacology*