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.

OBJECTIVES: This study aimed to explore the expression of lysosomal-associated membrane protein 5 (LAMP5) and microRNA (miR)-302a-3p in oral squamous cell carcinoma (OSCC) and their functional mechanism on the invasion and metastasis of OSCC. METHODS: The expression of LAMP5 in OSCC and its sensitivity as a prognostic indicator were analyzed on the basis of The Cancer Genome Atlas database. Western blot, quantitative reverse transcription polymerase chain reaction, and cell immunocytochemistry were used to detect the expression of LAMP5 in OSCC tissues and cells. The effect of LAMP5 on the proliferation, migration, and invasion of OSCC cells was evaluated through cell counting kit-8, immunocytochemistry, migration, and invasion assays, respectively. The miRNA targeting prediction websites were used to predict the miR that regulates LAMP5 and verify the targeted regulatory effect of miR-302a-3p on LAMP5. The effect of LAMP5 knockdown on OSCC tumor growth was evaluated in a nude mouse tumorigenesis model. RESULTS: LAMP5 was highly expressed in OSCC tissues and cells. It showed high sensitivity in the early diagnosis of OSCC. LAMP5 knockdown significantly inhibited the proliferation, migration, and invasion of OSCC cells, whereas LAMP5 overexpression increased these cell activities. The expression of LAMP5 was regulated by miR-302a-3p. In vivo, LAMP5 knockdown significantly inhibited the growth of OSCC tumor. CONCLUSIONS LAMP5 promotes the malignant progression of OSCC by enhancing the proliferation, migration, and invasion of OSCC cells. The expression of LAMP5 is negatively regulated by miR-302a-3p.
MicroRNAs/metabolism* ; Mouth Neoplasms/metabolism* ; Humans ; Animals ; Carcinoma, Squamous Cell/genetics* ; Neoplasm Invasiveness ; Cell Proliferation ; Mice, Nude ; Cell Movement ; Lysosomal Membrane Proteins/genetics* ; Mice ; Cell Line, Tumor ; Neoplasm Metastasis

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.

Objective To investigate the effects of angelica polysaccharides on diabetic retinopathy(DR)and possi-ble mechanisms of action.Methods DR mouse models were established by injecting streptozotocin into 18 C57BL/6J mice.The mice were then divided randomly into an Angelica polysaccharide group(given 289 mg·kg-1 Angelica polysac-charides),a positive control group(given 217 mg·kg-1 calcium hydroxybenzenesulfonate),and a model group(given an equal volume of saline),6 mice in each group.6 normal mice were selected as a blank group(given an equal volume of sa-line).The drug was administered by gavage once a day for 28 consecutive days.ARPE-19 cells were exposed to a high-glu-cose(25 mmol·L-1)culture medium to establish DR cell models,which were divided into a negative control group(con-trol vector),a lncRNA MEG3 group(lncRNA MEG3 overexpression vector),and a model group(DR cells without vector transfection).Cells not treated with 25 mmol·L-1glucose were taken as a blank group.All cells were cultured for 24 h.Fasting blood glucose levels were detected in mice.Hematoxylin-Eosin(HE)staining was performed to study the his-topathological changes in the retinal tissue of mice.Quantitative polymerase chain reaction(qPCR)was performed to de-tect the expression level of lncMEG3 mRNAs in the retinal tissue of mice.CCK-8 assay was used to measure the activity of ARPE-19 cells.Enzyme linked immunosorbent assay(ELISA)was used to detect IL-1β and IL-6 levels in mouse retinal tis-sues and ARPE-19 cells.The Western blot analysis was made to detect the levels of cellular pyroptosis-related proteins(in-cluding Caspase-1,Cleaved-Caspase-1,GSDMD,GSDMD-N,NLRP3,IL-1 β,and IL-18)in mouse retinal tissues and ARPE-19 cells.Results Blood glucose levels in the mice of the model group were higher than those in the mice of the blank group and lower than those in the mice of Angelica polysaccharide and positive control groups(all P＜0.05).HE staining results showed that compared with those of the blank group,the mice in the mode group had significantly damaged retinal tissues and disordered and loose cell arrangement.The retinal tissue of the mice in Angelica polysaccharide and positive control groups was arranged more orderly and densely and suffered less damage,compared with that of the mice in the model group.The relative expression levels of lncMEG3 mRNAs in the retinal tissue of mice in the blank,model group,An-gelica polysaccharide,and positive control groups were 1.005±0 114,0.423±0.054,0.701±0.101 and 0.593±0.084,re-spectively.The retinal expression levels of lncMEG3 mRNAs in the mice of Angelica polysaccharide and positive control groups were significantly higher than those in the mice of the model group(both P＜0.01).CCK-8 results showed that the survival rates of ARPE-19 cells in the lncRNA MEG3 group at 48 and 72 h were higher than those in the negative control group(both P＜0.05).ELISA and Western blot results showed that the retinal expression levels of IL-1 β,IL-6 and cellular pyroptosis-related proteins in the mice of the model group were significantly higher than those in the mice of the blank group(all P＜0.01)and higher than those in the mice of Angelica polysaccharide group and positive control group(all P＜0.05).The expression levels of IL-1 β,IL-6,and cellular pyroptosis-related proteins in ARPE-19 cells of the model group were significantly higher than those in the blank group(all P＜0.01).The expression levels of IL-1 β,IL-6,and cellular py-roptosis-related proteins in ARPE-19 cells of the lncRNA MEG3 group were lower than those in the negative control group(all P＜0.05).Conclusion Angelica polysaccharides can improve DR by promoting lncRNA MEG3 expression and down-regulating IL-1 β,IL-6,Caspase-1,Cleaved-Caspase-1,GSDMD,GSDMD-N,NLRP3,IL-1β,and IL-18 protein ex-pression.

Medication reconciliation plays a key role in improving patient medication safety,reducing inappropriate polypharmacy,and promoting the high-quality development of pharmaceutical services.Compared to advanced international guidelines,China's medication reconciliation service standards have deficiencies in areas such as definition and process design,and multidisciplinary team building.There is a need to establish a comprehensive medication reconciliation effect evaluation index system,develop pharmacist-led multidisciplinary teams,promote the advancement of artificial intelligence and big data technologies,and strengthen outpatient and community medication reconciliation coverage,thereby contributing to the high-quality development of pharmaceutical services in China.

Objective:To investigate the predictive value of 18F-FDG PET related metabolic parameters on microsatellite instability-high (MSI-H) and human epidermal growth factor receptor-2(HER2) expression in colorectal cancer (CRC). Methods:The 18F-FDG PET imaging, clinical and pathological data of 101 CRC patients (58 males, 43 females; age 68.0(58.0, 75.0) years) admitted to Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from January 2016 to March 2024 were retrospectively collected, including 17 cases in MSI-H group, 84 cases in microsatellite stability/microsatellite instability-low (MSS/MSI-L) group, 23 cases in HER2 expression group, 34 cases in non-HER2 expression group, and 44 patients without HER2 detection. Univariate analyses (independent-sample t test, Mann-Whitney U test, χ2 test) and multivariate logistic regression analysis were used to screen out independent risk factors, and ROC curve was used to evaluate the predictive efficacy. Bootstrap method was used to verify the model internally. Results:There were significant differences in metabolic tumor volume (MTV) 80% between MSI-H group and MSS/MSI-L group (2.1(1.6, 4.0) vs 1.4(1.0, 2.7) cm 3;Z=-2.10, P=0.036), and total lesion glycolysis (TLG) 80% and carcinoembryonic antigen (CEA) were significantly different between those 2 groups ( Z=-2.27, χ2=6.40, both P<0.05). There were significant differences in TLG 80% (29.0(16.1, 41.0) vs 14.3(9.4, 22.9) g; Z=-2.80, P=0.005) between HER2 expression group and non-HER2 expression group, and significant differences were also found in MTV 80%, heterogeneity index (HI) and CV ( Z=-2.24, t values: -2.26, 2.54, all P<0.05). The independent risk factors for MSI-H were MTV 80% (odds ratio ( OR)=1.326, 95% CI: 1.015-1.733, P=0.038) and CEA ( OR=0.200, 95% CI: 0.056-0.706, P=0.012), with the AUC for the combined model of 0.730 (95% CI: 0.605-0.856), and the concordance index (C-index) of 0.716. The independent risk factors for HER2 expression were TLG 80% ( OR=1.037, 95% CI: 1.001-1.073, P=0.041) and CV ( OR=1.467, 95% CI: 1.073-2.005, P=0.016), with the AUC for the combined model of 0.775 (95% CI: 0.645-0.875), and the C-index of 0.757. Conclusions:18F-FDG PET can be used as a noninvasive tool to evaluate CRC microsatellite status and HER2 gene amplification. MTV 80% and CEA are independent risk factors for MSI-H; TLG 80% and CV are independent risk factors for HER2 expression.

Objective:To evaluate the clinical prognostic value of intratumoral metabolic heterogeneity parameters of baseline 18F-FDG PET/CT in primary cutaneous malignant melanoma (CMM). Methods:From October 2015 to July 2023, the clinical data of 35 patients (24 males, 11 females, age (66.6±13.1) years) diagnosed with primary CMM who underwent baseline 18F-FDG PET/CT in Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School were retrospectively analyzed. Conventional metabolic parameters (SUV max, metabolic tumor volume (MTV), total lesion glycolysis (TLG)) and PET intratumoral metabolic heterogeneity parameters (area under the cumulative SUV histograms curve (AUC-CSH), linear regression slope, SUV max/ SUV mean) were assessed. Using thresholds of 30%, 40%, 50%, 60%, 70%, and 80% SUV max or thresholds of 40%, 60%, and 80% SUV max to delineate MTV, linear regression was performed, with the slopes being heterogeneity index-1 (HI-1) and heterogeneity index-2 (HI-2), respectively. Using SUV thresholds of 2.5, and 40%, 50%, 60%, and 70%SUV max to calculate AUC-CSH and SUV max/SUV mean. Kaplan-Meier survival curves and Cox proportional hazards models were used to analyze the prognostic value of primary lesion PET metabolic parameters on overall survival (OS) and progression-free survival (PFS). Results:The median follow-up time of 35 patients was 20 months, with 25 patients (71%) experiencing disease progression and 16 patients (46%) deceased. Multivariate Cox regression analysis revealed that HI-1, HI-2, MTV, SUV max/SUV mean2.5, and SUV max were the independent prognostic factors for PFS (hazard rate ( HR) (95% CI): 0.32(0.13-0.82), 0.32(0.13-0.82), 3.86(1.34-11.12), 4.61(1.33-16.02), 4.06(1.55-10.61), all P<0.05), whereas SUV max and SUV max/SUV mean2.5 were the independent prognostic factors for OS ( HR: 8.04(1.96-32.87), 2.87(1.09-7.51), P values: 0.004, 0.032). Conclusion:HI-1, HI-2, and SUV max/SUV mean2.5 have prognostic value for CMM, while the value of AUC-CSH heterogeneity parameters are not significant.

Objective:To establish a combined model of tumor heterogeneity metabolic parameters using 18F-FDG PET/CT and explore its value in differentiating benign from malignant pulmonary lesions. Methods:A total of 251 patients (157 males, 94 females; age 15-88 years) who were diagnosed with malignant lung lesions by 18F-FDG PET/CT and with definitive pathological results at Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from February 2017 to February 2024 were retrospectively enrolled. Analysis was conducted on clinical data, traditional parameters (SUV max, metabolic tumor volume (MTV), total lesion glycolysis (TLG)) of primary lesions on 18F-FDG PET/CT, and intra-tumoral metabolic heterogeneity index (HI; such as cumulative SUV volume histogram AUC (AUC-CSH), linear regression slope, CV). AUC-CSH and CV were calculated using SUV thresholds of 2.5 and 40%SUV max. Logistic univariate and multivariate regression analyses were used to extract independent predictors in clinical features and PET/CT parameters for the differential diagnosis of pulmonary lesions. A multi-parameter combined model was established through logistic regression and validated for diagnostic efficacy using ROC curve analysis. Results:Among 251 patients, 101 were benign and 150 were malignant. In univariate analysis, gender, age, tumor markers, spiculation sign, lobulation sign, vessel convergence sign, air bronchogram, long diameter, short diameter, SUV max, AUC-CSH 2.5, AUC-CSH 40%, CV2.5, and CV40% were predictive factors for the diagnosis of benign and malignant tumors (odds ratio ( OR): 0.57-17.39, all P<0.05). In multivariate analysis, gender, age, tumor markers, lobulation sign, vessel convergence sign, SUV max, AUC-CSH 40%, and CV40% were independent predictors for the diagnosis of benign and malignant tumors ( OR: 2.30-13.18, all P<0.05). The AUC, sensitivity, specificity, and accuracy of the multi-parameter combined model established with the above independent predictors were 0.89, 77.33%(116/150), 84.16%(85/101), 80.08%(201/251), respectively. Conclusion:18F-FDG PET/CT multi-parameter combined model has high value in the differentiation of benign and malignant pulmonary lesions.

Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

Objective:To evaluate the prognostic value of 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT metabolic parameters in small cell lung cancer (SCLC) . Methods:A retrospective analysis was conducted on the clinical and imaging data of 156 SCLC patients, who underwent 18F-FDG PET/CT imaging and were diagnosed by histopathological examination at Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School from September 2013 to February 2024. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), linear regression slope, area under the curve of cumulative standard uptake value (SUV) volume histogram (AUC-CSH), and coefficient of variation (CV) were calculated using LIFEx software with different SUV thresholds. Univariate and multivariate analyses were performed using Cox proportional hazards model. Patient stratification was based on the critical values determined by receiver operator characteristic (ROC) curve analysis. The survival curve was plotted using the Kaplan-Meier method and log-rank test was performed. Results:Univariate analysis showed that MTV 40% ( HR=2.91, 95% CI: 1.55-5.47, P=0.001), MTV 60% ( HR=2.31, 95% CI: 1.29-4.17, P=0.005), TLG 40% ( HR=2.07, 95% CI: 1.19-3.60, P=0.010), linear regression slope ( HR=0.45, 95% CI: 0.26-0.79, P=0.005), and CV 40% ( HR=0.27, 95% CI: 0.08-0.84, P=0.024) were factors affecting progression-free survival (PFS) in SCLC patients. MTV 40% ( HR=1.98, 95% CI: 1.22-3.22, P=0.005), MTV 60% ( HR=1.80, 95% CI: 1.12-2.88, P=0.015), MTV 80% ( HR=1.71, 95% CI: 1.08-2.74, P=0.024), TLG 40% ( HR=3.68, 95% CI: 1.59-8.49, P=0.002), linear regression slope ( HR=0.49, 95% CI: 0.30-0.80, P=0.004), and AUC-CSH 80% ( HR=0.44, 95% CI: 0.23-0.84, P=0.013) were found to be factors affecting overall survival (OS) in SCLC patients. Multivariate analysis revealed that MTV 40% ( HR=4.76, 95% CI: 1.11-20.50, P=0.036) was an independent factor influencing PFS, and TLG 40% ( HR=3.19, 95% CI: 1.02-9.92, P=0.046) was an independent factor influencing OS in SCLC patients. ROC curve analysis identified the optimal cutoff value for MTV 40% in predicting PFS as 5.5cm 3 and the optimal cutoff value for TLG 40% in predicting OS as 41.5 g in SCLC patients. Survival analysis showed that patients with MTV 40%≤5.5 cm 3 ( n=33) had a median PFS that was not reached, while patients with MTV 40%>5.5 cm 3 ( n=123) had a median PFS of 10.3 months, with a statistically significant difference ( χ2=12.09, P=0.001). For patients with TLG 40%≤41.5 g ( n=35), the median OS was not reached, whereas for TLG 40%>41.5 g ( n=121), the median OS was 31.6 months, with a statistically significant difference ( χ2=10.55, P=0.001) . Conclusions:The 18F-FDG PET/CT metabolic parameter MTV 40% is an independent factor influencing PFS, while TLG 40% is an independent factor influencing OS in SCLC patients. The above two parameters may serve as indicators for assessing the prognosis of SCLC patients.