Purpose To investigate the relationship between the expression of POSTN and NECTIN-3 in urothelial carcinoma(UC)and its clinicopathologic features and prognosis.Methods Clinical data of 115 UC patients were col-lected.EnVision two-step method was used for immunohistochemical analysis to determine the expression of POSTN and NECTIN-3 in UC and their correlation with clinicopathological features and prognosis.Transcriptomic data from TCGA database were used to analyze the correlation between the expression of POSTN and NECTIN-3 in bladder cancer and the pathological stage and prognosis of bladder cancer.qPCR and Western blot were used to detect the expression levels of POSTN and NECTIN-3 in tumor tissues and adjacent tissues of patients.Results TCGA database analysis showed that the expression level of NECTIN-3 in urinary bladder urothelial carcinoma(UBUC)was significantly lower than that in paracancer tissues,and POSTN expression was positively correlated with pathological stage.Prognostic a-nalysis showed that POSTN expression was negatively correlated with the overall survival of UBUC(P＞0.05),and NECTIN-3 expression was negatively correlated with disease-free survival of UBUC(P＞0.05).The experimental re-suits showed that patients with positive POSTN expression were more prone to perineural invasion[25 cases(86.2％)vs 4 cases(13.8％),P=0.019],vascular invasion[36 cases(83.7％)vs 7 cases(16.3％),P=0.007],and lymph node metastasis[24 cases(88.9％)vs 3 cases(11.1％),P=0.033].Additionally,the positive expression rate of POSTN in UBUC was significantly higher than that in upper tract urothelial carcinoma(UTUC)(75.0％vs 54.3％,P=0.028).Higher expression levels of POSTN and NECTIN-3 were associated with shorter overall survival,but the difference was not statistically significant(P＞0.05).Conclusion There is no significant correlation between NECTIN-3 and the clinicopathological features and prognosis of urothelial carcinoma,while the expression of POSTN is correlated with the invasive clinicopathological features of UC,which has certain suggestive significance for clinical stage and prognosis.

OBJECTIVE: Cigarette smoking exacerbates the progression of pulmonary tuberculosis (TB). The role of tertiary lymphoid structures (TLS) in chronic lung diseases has gained attention; however, it remains unclear whether smoking-exacerbated lung damage in TB is associated with TLS. This study aimed to analyze the characteristics of pulmonary TLS in smokers with TB and to explore the possible role of TLS in smoking-related lung injury in TB. METHODS: Lung tissues from 36 male patients (18 smokers and 18 non-smokers) who underwent surgical resection for pulmonary TB were included in this study. Pathological and immunohistological analyses were conducted to evaluate the quantity of TLS, and chest computed tomography (CT) was used to assess the severity of lung lesions. The correlation between the TLS quantity and TB lesion severity scores was analyzed. The immune cells and chemokines involved in TLS formation were also evaluated and compared between smokers and non-smokers. RESULTS: Smoker patients with TB had significantly higher TLS than non-smokers ( P < 0.001). The TLS quantity in both the lung parenchyma and peribronchial regions correlated with TB lesion severity on chest CT (parenchyma: r = 0.5767; peribronchial: r = 0.7373; both P < 0.001). Immunohistochemical analysis showed increased B cells, T cells, and C-X-C motif chemokine ligand 13 (CXCL13) expression in smoker patients with TB ( P < 0.001). CONCLUSION Smoker TB patients exhibited increased pulmonary TLS, which was associated with exacerbated lung lesions on chest CT, suggesting that cigarette smoking may exacerbate lung damage by promoting TLS formation.
Humans ; Male ; Tuberculosis, Pulmonary/immunology* ; Middle Aged ; Tertiary Lymphoid Structures/pathology* ; Adult ; Lung/pathology* ; Smoking/adverse effects* ; Smokers ; Aged ; Tomography, X-Ray Computed

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.

Over the past decade, the field of urological and male reproductive system pathology has experienced rapid development. Numerous accomplishments were achieved in clinical diagnosis and molecular research in this area in China, gradually gaining international recognition. As the most influential academic journal in the field of pathology in China, the Chinese Journal of Pathology has witnessed the vigorous growth and innovation in this domain. On the occasion of the journal′s 70th anniversary, a summary on the developments in this field have been provided, along with an outlook for the future.

Objective:To investigate the clinicopathological features, immunophenotype, molecular characteristics, and differential diagnosis of MED15-TFE3 gene fusion renal cell carcinoma (MED15-TFE3 RCC).Methods:A total of 12 MED15-TFE3 RCCs, diagnosed from 2016 to 2023, were collected from the Department of Pathology of Nanjing Jinling Hospital, Nanjing University School of Medicine, Nanjing, China for clinicopathologic, immunohistochemical, fluorescence in situ hybridization (FISH) and RNA sequencing (RNA-seq) analyses and follow-up. In addition, its diagnosis and differential diagnosis were also explored.Results:There were five males and seven females. The patients′ ages ranged from 16 to 60 years, with an average age of 40.4 years. The follow-up time ranged from 15 to 92 months, and no recurrence or metastasis was observed. Histologically, 6 cases exhibited extensive cystic structures with almost no solid sheet components, while the remaining 6 cases displayed a cysto-solid growth pattern. The cytoplasm of the tumor cells appeared flocculent, with a clear or faintly eosinophilic appearance, and nucleoli were inconspicuous. Psammoma bodies were observed in 12 cases. There was deposition of basement membrane-like material in 5 cases. All cases showed strong expression of TFE3, GPNMB, Cathepsin K, Melan A, and PAX8, while no expression of CAⅨ or CK7. FISH analyses showed that all 12 cases were positive for the MED15-TFE3 fusion, while the MED15-TFE3 fusion gene and specific fusion sites were detected in 2 cases using RNA-seq.Conclusions:MED15-TFE3 RCC is a type of TFE3-rearranged renal cell carcinoma that exhibits both identifiable diagnostic characteristics and highly deceptive morphology. Its distinct extensive cystic structure can be easily confused with multilocular cystic renal neoplasm of low malignant potential, necessitating careful differentiation in routine practice.

Collagen, a vital matrix protein for various tissue and functions in animals, is widely applied in biomaterials. In type Ⅰ collagen, missense mutations of glycine (Gly) in the Gly-Xaa-Yaa triplet of the triple helix are a major cause of osteogenesis imperfecta (OI). Clinical manifestations exhibit marked heterogeneity, spanning a broad disease spectrum from mild skeletal fragility (Type Ⅰ) to severe limb deformities (Type Ⅲ) and perinatal lethal forms (Type Ⅱ). This study utilized recombinant collagen as a model to further elucidate whether Gly→Ala/Val mutations at the N-terminus of the integrin-binding sequence GFPGER affect collagen structure and function, and to explore the underlying mechanisms by which missense mutations impact the biological function of collagen. By introducing Ala and Val substitutions at seven Gly positions N-terminal to the GFPGER sequence, we systematically assessed the effects of these amino acid replacements on the triple-helical structure, thermal stability, integrin-binding ability, and cell adhesion of recombinant collagen. All constructs formed a stable triple-helix structure, with slightly compromised thermal stability. Gly→Val substitutions increased the susceptibility of recombinant collagen to trypsin, which suggested local conformational perturbations in the triple helix. In addition, Gly→Val substitutions significantly reduced the integrin-binding affinity and decreased HT1080 cell adhesion, with the effects stronger than Gly→Ala substitutions. Compared with Gly→Ala substitutions, substitution of Gly with the larger residue Val had enhanced negative effects on the structure and function of recombinant collagen. These findings provide new insights into the molecular mechanisms of osteogenesis imperfecta and offer theoretical references and experimental foundations for the design of collagen sequences and the development of collagen-based biomaterials.
Recombinant Proteins/biosynthesis* ; Glycine/genetics* ; Humans ; Osteogenesis Imperfecta/genetics* ; Integrins/metabolism* ; Collagen/metabolism* ; Collagen Type I/metabolism* ; Amino Acid Substitution ; Mutation ; Mutation, Missense

Traditional Chinese medicine(TCM) capable of clearing heat and removing toxin is most commonly used in clinical practice and has the effect of removing fire-heat and toxin. Studies have shown that most of the Ilex plants have the effect of clearing heat and removing toxin, among which the varieties of I. cornuta, I. pubescens, I. rotunda, I. latifolia, and I. chinensis are most widely used. These plants generally contain triterpenoids and their glycosides, alkaloids, flavonoids, phenylpropanoids, and other chemical components, especially pentacyclic triterpenoids. According to their skeletons, pentacyclic triterpenoids can be divided into the oleanane type, the ursane type, the lupinane type, etc. Among them, ursane-type components are the most abundant, and 136 species have been found so far. These components have been proved to have pharmacological effects such as anti-inflammatory, anti-tumor, hypolipidemic, anti-thrombosis, cardiomyocyte-protective, antibacterial, and hepatoprotective effects. Therefore, this paper systematically reviews the domestic and foreign literature on Ilex plants with a focus on the research progress on pentacyclic triterpenoids and their pharmacological activities, aiming to provide reference for the development of TCM resources with the effect of clearing heat and removing toxin.
Ilex/chemistry* ; Plants, Medicinal/chemistry* ; Pentacyclic Triterpenes/pharmacology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Animals

Recent data suggest that vascular endothelial growth factor receptor inhibitor (VEGFRi) can enhance the anti-tumor activity of the anti-programmed cell death-1 (anti-PD-1) antibody in colorectal cancer (CRC) with microsatellite stability (MSS). However, the comparison between this combination and standard third-line VEGFRi treatment is not performed, and reliable biomarkers are still lacking. We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi (combination group, n=54) or VEGFRi alone (VEGFRi group, n=32), and their efficacy and safety were evaluated. We additionally examined the immune characteristics of the MSS CRC tumor microenvironment (TME) through single-cell and spatial transcriptomic data, and an MSS CRC immune cell-related signature (MCICRS) that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort. Compared with VEGFRi alone, the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit (median progression-free survival: 4.4 vs. 2.0 months, P=0.0024; median overall survival: 10.2 vs. 5.2 months, P=0.0038) and a similar adverse event incidence. Through single-cell and spatial transcriptomic analysis, we determined ten MSS CRC-enriched immune cell types and their spatial distribution, including naive CD4⁺ T, regulatory CD4⁺ T, CD4⁺ Th17, exhausted CD8⁺ T, cytotoxic CD8⁺ T, proliferated CD8⁺ T, natural killer (NK) cells, plasma, and classical and intermediate monocytes. Based on a systemic meta-analysis and ten machine learning algorithms, we obtained MCICRS, an independent risk factor for the prognosis of MSS CRC patients. Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation, and hence a significant relation with the superior efficacy of pan-cancer immunotherapy. More importantly, the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort. Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity. MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.
Humans ; Colorectal Neoplasms/drug therapy* ; Male ; Female ; Immunotherapy ; Middle Aged ; Aged ; Tumor Microenvironment/immunology* ; Retrospective Studies ; Microsatellite Instability ; Transcriptome ; Single-Cell Analysis ; Programmed Cell Death 1 Receptor/immunology* ; Gene Expression Profiling ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; Receptors, Vascular Endothelial Growth Factor/antagonists & inhibitors*

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.

Over the past decade, the field of urological and male reproductive system pathology has experienced rapid development. Numerous accomplishments were achieved in clinical diagnosis and molecular research in this area in China, gradually gaining international recognition. As the most influential academic journal in the field of pathology in China, the Chinese Journal of Pathology has witnessed the vigorous growth and innovation in this domain. On the occasion of the journal′s 70th anniversary, a summary on the developments in this field have been provided, along with an outlook for the future.