The ninth edition of TNM staging for lung cancer has been announced at the 2023 World Lung Cancer Congress and implemented from January 1, 2024. The focus of the ninth TNM staging change is dividing N2 into N2a and N2b, as well as M1c into M1c1 and M1c2. Although the T staging has not changed, it has played an important role in verifying the eighth edition of the T staging. The subdivision of stage N2 has led some patients with ⅢA of the eighth edition to experience ascending or descending stages, which will more accurately help to assess the condition and prognosis of patients with mediastinal lymph node metastasis, as well as the design of related clinical studies. Modifying the M1c staging will help define oligometastasis and explore new treatment models in the future. The ninth edition of the TNM staging system provides a more detailed division of different tumor loads, but there is no clear explanation for the staging of lung cancer after neoadjuvant therapy. Further data analysis is needed, and it is expected to be answered in the tenth edition of TNM staging.

Objective The critical genes associated with exhausted CD8+T cells were screened and validated by mapping the single-cell transcriptome profile of high-grade serous ovarian cancer(HGSOC).Methods The specific subtypes of T cells in the tumor microenvironment were analyzed using the single-cell sequencing data from the early stage of laboratory(SRA database:PRJNA756768)and integrating 5 HGSOC sequencing from the database,and the differentiation trajectory of T cell subsets was ex-plored through pseudotime analysis.Differential gene enrichment was used to determine immunosuppressed CD8+IL-2Low and CD8+IFN-γLow T cell subsets and differential genes,and candidate molecules closely related to exhausted CD8+T cells were screened based on patient prognosis.Flow cytometry was used to analyze the expression of PHLDA1 on CD8+T cells,CD4+T cells and Treg cells dur-ing the activation to exhaustion process of T cells in human PBMCs.ELISA was used to detect the levels of IFN-γ and IL-2 secreted by CD8+T cells in PHLDA1High and PHLDA1Low.Finally,flow cytometry was used to analyze the association between PHLDA1 and ex-hausted markers PD-1 and TIM-3.Results The results showed that T cells were grouped in three ways:(1)IL-2High and IL-2Low;(2)IFN-γHigh and IFN-γLow;and(3)exhausted and cytotoxic CD8+T cells.Subsequently,the intersection of its differentially expressed genes was taken,and the key gene PHLDA1 was ultimately screened.Flow cytometry analysis suggested that during the process of T cell activation to exhaustion,the expression of PHLDA1 continued to increase on CD8+T cells,CD4+T cells and Treg cells;The ELISA results showed that the levels of IFN-γ and IL-2 secreted by CD8+PHLDA1High T cells were significantly lower than those of CD8+PHLDA1Low T cells.Meanwhile,the CD8+PHLDA1High T cell subset could simultaneously cover the exhausted T cell types of CD8+TIM-3+and CD8+PD-1+.Conclusion Based on single-cell sequencing data,this study identified PHLDA1 as a key molecule responsi-ble for CD8+T cell exhaustion in OC,providing new insights for immunotherapy of OC.

[Objective] To understand the resistance mechanisms, virulence characteristics, and pathogenicity of hypervirulent Klebsiella pneumoniae (hvKp), which causes pyogenic liver abscess (PLA), and to provide related data for clinical treatment of infection caused by this type of bacteria. [Methods] We collected three strains of Klebsiella pneumoniae isolated from the liver abscess fluid of patients with liver abscesses in various departments of The First Affiliated Hospital of Xi’an Jiaotong University. The hypervirulent phenotypes were determined by the wire test, and drug sensitivity was assessed using the VITEK 2 compact automatic microbiological analyzer. Molecular characteristics such as podocarp serotypes, multi-locus sequence typing (MLST), virulence genes, and drug resistance genes were identified through whole-genome sequencing. Additionally, a mouse infection model was established to evaluate pathogenicity. [Results] The isolates were sticky, with mucous thread pulling length >5 mm, all of which exhibited high viscosity phenotypes. Except 146007, which is a multidrug-resistant bacterium, the other two strains had higher antibiotic sensitivity. Whole genome sequencing revealed that the isolates were of high-virulence type, carrying the toxin plasmid rmpADC/rmpA2, iron uptake system, bacterial hairs, secretion system, and other virulence factors. All the three isolates tested positive for rmpA/rmpA2 combined with iucA/iutA, indicating they could be classified as hvKp. Multiple resistance genes were detected, such as β-lactamase like blaTEM, blaSHV, and blaCTX-M. The isolates were highly pathogenic to mice, as evidenced by the diseased organs of the deceased mice observed on autopsy. [Conclusion] The three strains of hvKp isolated in this study carried multiple drug-resistant genes and were highly pathogenic, which suggests that in laboratories and clinical practices it is imperative to promptly identify and adopt necessary disposal strategies to prevent further spread of hvKp.

The ninth edition of TNM staging for lung cancer has been announced at the 2023 World Lung Cancer Congress and implemented from January 1, 2024. The focus of the ninth TNM staging change is dividing N2 into N2a and N2b, as well as M1c into M1c1 and M1c2. Although the T staging has not changed, it has played an important role in verifying the eighth edition of the T staging. The subdivision of stage N2 has led some patients with ⅢA of the eighth edition to experience ascending or descending stages, which will more accurately help to assess the condition and prognosis of patients with mediastinal lymph node metastasis, as well as the design of related clinical studies. Modifying the M1c staging will help define oligometastasis and explore new treatment models in the future. The ninth edition of the TNM staging system provides a more detailed division of different tumor loads, but there is no clear explanation for the staging of lung cancer after neoadjuvant therapy. Further data analysis is needed, and it is expected to be answered in the tenth edition of TNM staging.

Objective:To establish a nomogram for preoperative differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) based on clinical, ultrasound, and contrast-enhanced ultrasound (CEUS) data.Methods:A retrospective analysis was conducted on ultrasound and CEUS data of 462 patients who underwent hepatectomy in Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from January 2016 to December 2023, including 262 cases of HCC (56.7%) and 200 cases of ICC (43.3%). The data were randomly divided into training set ( n=324) and validation set ( n=138) in a 7∶3 ratio. Univariate analysis was used to initially screen for variables with statistically significant differences between HCC and ICC groups in the training set, and LASSO regression was performed to select the variables with higher coefficients. Logistic regression analyses were then used to predict independent risk factors for ICC. A nomogram was drawn using R software. The performance of the nomogram was then validated using ROC curve, calibration curve, and decision curve analysis (DCA). Results:Univariate analysis showed that there were significant differences in age, gender, liver cirrhosis, HBsAg (+ ), ALP >185 U/L, CA19-9 >27 kU/L, CA242>10 kU/L, irregular shape, border, cholangiectasis, portal vein tumor thrombus, enhanced pattern in arterial phase, clearance time <60 s, intra-tumoral vein between ICC and HCC groups (all P<0.05). The top 10 features were selected for LASSO regression analysis. Logistic regression analysis revealed that gender, cirrhosis, CA19-9>27 kU/L, CA242>10 kU/L, cholangiectasis, clearance time <60 s, intra-tumoral vein and enhanced pattern in arterial phase were risk factors for ICC (all P<0.05). The area under the ROC curve in the training and validation groups were 0.963 and 0.914, respectively. In the training group, the specificity and sensitivity of the nomogram were 0.926 and 0.917, respectively, and in the validation group, they were 0.875 and 0.871, respectively. The calibration curve showed that the prediction effect of the model was in good agreement with the actual situation. DCA showed that the nomogram could increase the net benefit to the different diagnosis of ICC in patients. Conclusions:The nomogram based on clinical, ultrasound and CEUS features has a good predictive value for preoperative identification of ICC and provides reliable evidence for clinical practice.

Objective:To establish and evaluate a clinical and ultrasound parameters-based nomogram for the preoperative differentiating diagnosis of intrahepatic cholangiocarcinoma (ICC).Methods:A total of 723 patients undergoing hepatectomy in Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from January 2016 to August 2022 were retrospectively screened. A total of 399 patients with hepatocellular carcinoma (HCC, 198 cases) or ICC (201 cases) were enrolled in this study, including 284 males and 115 females, aged (60.5±10.5) years. Through random sampling using computer-generated random numbers, patients were divided into training ( n=279) and validation groups ( n=120) in a ratio of 7∶3. Univariate and multivariate logistic regression were performed to identify factors differentiating ICC, and a nomogram was established using R software based on independent risk factors for ICC. The accuracy of the nomogram was evaluated by receiver operating characteristic curve and calibration curves. Decision curve analysis was performed to assess the net benefit of the model. Results:Multivariate logistic regression analysis showed that irregular shape, cholangiectasis, female, cirrhosis, carbohydrate antigen 242 >10 U/ml, carbohydrate antigen 125 >30 U/ml and alpha-fetoprotein >10 μg/L were independent differentiating factors for ICC (all P<0.05). A nomogram was constructed based on those factors. The nomogram showed a better discrimination between ICC and HCC. The area under the curve of the training group and the validation group were 0.966 and 0.956, respectively. The calibration curve showed that the prediction effect of the model is in good agreement with the actual situation. Decision curve analysis showed that the nomogram was more effective than diagnosing all patients as either HCC or ICC, which yielded a net benefit at the most reasonable threshold probabilities. Conclusion:The nomogram for the preoperative diagnosis of ICC based on clinical and ultrasound features showed a good diagnostic performance.

BACKGROUND: Thymic carcinomas (TCs) and thymic neuroendocrine neoplasms (TNENs) are two aggressive subtypes of thymic malignancy. Traditional therapy for advanced TCs and TNENs has limited outcome. New genomic profiling of TCs and TNENs might provide insights that contribute to the development of new treatment approaches. METHODS: We used gene panel sequencing technologies to investigate the genetic aberrations of 32 TC patients and 15 TNEN patients who underwent surgery at Shanghai Chest Hospital between 2015 and 2017. Patient samples were sequenced using a 324-gene platform with licensed technologies. In this study, we focused on clinically relevant genomic alterations (CRGAs), which are previously proven to be pathogenic alterations, to identify the pathology-specific mutational patterns, prognostic signatures of TCs and TNENs. RESULTS: The mutational profiles between TCs and TNENs were diverse. The genetic alterations that ranked highest in TCs were in CDKN2A, TP53, ASXL1, CDKN2B, PIK3C2G, PTCH1, and ROS1 , while those in TNENs were in MEN1, MLL2, APC, RB1 , and TSC2 . Prognostic analysis showed that mutations of ROS1, CDKN2A, CDKN2B, BRAF, and BAP1 were significantly associated with worse outcomes in TC patients, and that mutation of ERBB2 indicated shortened disease-free survival (DFS) and overall survival (OS) in TNEN patients. Further investigation found that the prognosis-related genes were focused on signal pathways of cell cycle control, chromatin remodeling/DNA methylation, phosphoinositide 3-kinases (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR), and receptor tyrosine kinase (RTK)/RAS/mitogen-activated protein kinase (MAPK) signaling. CONCLUSION We profiled the mutational features of 47 Chinese patients with thymic malignancy of diverse pathologic phenotypes to uncover the integrated genomic landscape of these rare tumors, and identified the pathology-specific mutational patterns, prognostic signatures, and potential therapeutic targets for TCs and TNENs.
Humans ; Thymoma ; Protein-Tyrosine Kinases/genetics* ; Proto-Oncogene Proteins/genetics* ; China ; Thymus Neoplasms/pathology* ; Prognosis ; Neuroendocrine Tumors/pathology* ; Mutation/genetics*

Objective The aim of this study was to draw single-cell transcriptome profiles of high-grade serous ovarian cancer(HGSOC),borderline ovarian cancer(OC),and normal ovaries in order to identify biomarkers that can diagnose and predict the prognosis of OC.Methods The differentially expressed genes between HGSOC,borderline OC,and normal ovarian tissues were ana-lyzed using single-cell data sequenced(SRA database:PRJNA756768).The cell subsets associated with tumor progression were screened by functional enrichment,cell communication between different subsets was analyzed by Cellchat,and cell differentiation traj-ectories were explored by pseudotime analysis to finally determine the subsets most relevant to tumor progression.Combined with OC transcriptome data of OC from the Cancer Genome Atlas(TCGA)with patient prognosis,biomarkers for diagnosing and predicting sur-vival of OC patients were ultimately screened.Results After using t-distribution stochastic neighbor embedding(t-SNE)for di-mensionality reduction,nine cell subpopulations were obtained:endothelial cells,myeloid cells,fibroblasts,T cells,stromal cells,B cells,and 3 epithelial cell subpopulations(C1,C4,and C7).Further analysis revealed that copy number variation(CNV)in the C4 group had the highest score in HGSOC,higher than those of borderline OC and normal ovaries,and was negatively correlated with prognosis.DMKN was a key marker gene in this group.Transcriptome analysis of OC in the TCGA database showed a close correlation between DMKN and poor prognosis(P=0.026),and the diagnostic efficacy of DMKN for OC was significant(A UC=0.906).Con-clusion This study is based on single-cell sequencing data to screen for DMKN,which can effectively diagnose and predict the prognosis of OC.This study provides new ideas for the diagnosis and prognosis prediction of OC.

Objective:To investigate changes of intestinal flora and the mechanism of NLRP3 inflammasome in elderly mice with cognitive dysfunction induced by sevoflurane anesthesia.Methods:Eighteen fourteen-month-old male SPF grade C57BL/6J mice were randomly divided into control and sevoflurane groups, with 9 mice in each group. The mice of sevoflurane group inhaled 3% sevoflurane for 2 hours daily for three days. Fecal samples were collected post-exposure 24 hours for 16S rRNA sequencing. Morris water maze was then used to test the cognitive ability. Western blot was used to detect the expressions of synapse-associated proteins, NLRP3 inflammasome-related proteins of hippocampus, and NLRP3 inflammasome-related proteins of colon. Golgi staining was used to observe the number of dendritic spines in the hippocampus. qPCR was used to detect the expression of inflammatory cytokines IL-1β, IL-18, TNF-α mRNA in mice colon and hippocampal tissues.Results:(1) The Morris water maze test showed that the escape latency of the sevoflurane group was longer than the control group, but there was statistical difference only on the fifth day ( P<0.05). In the spatial exploration test, escape latency of the sevoflurane group was higher than that of the control group((49.50±9.99)s, (18.67±7.63)s, t=6.005, P<0.001), and platform crossing frequency was less than that of the control group((0.83±0.75)times, (2.33±1.03)times, t=2.87, P=0.017). (2) Western blot and Golgi staining results showed that the expression of hippocampal synaptic-related proteins and the number of dendritic spines in the sevoflurane group were significantly reduced compared with those in control group (all P<0.05). (3) 16S rRNA sequencing showed significant β-diversity difference between the two groups ( P<0.05). Compared with the control group, potential pathogens that p_Desulfobacterota and g_Desulfovibrio increased significantly in the sevoflurane group (both P<0.05), and beneficial bacteria that p_Verrucomicrobiota and g_Akkermansia decreased significantly (both P<0.05). (4) Compared with the control group, the results of qPCR showed increased expression of inflammatory cytokines TNF-α, IL-1β mRNA in the colon and hippocampal tissues of the sevoflurane group (all P<0.05). Western blot results showed increased expression of NLRP3 inflammasome-related proteins in the colon and hippocampal tissues of the sevoflurane group (both P<0.05). Immunofluorescence results showed the higher fluorescence intensity of ASC in the DG region of the hippocampus of the sevoflurane group compared with the control group ( P<0.01). Conclusion:The cognitive dysfunction model induced by sevoflurane in elderly mice shows neuroinflammatory reactions and synaptic damage, which may be related to intestinal microbiota imbalance and activation of NLRP3 inflammasome.

Chronic obstructive pulmonary disease (COPD) is an important healthcare problem worldwide. Often, glucocorticoid (GC) resistance develops during COPD treatment. As a classic hypoglycemic drug, metformin (MET) can be used as a treatment strategy for COPD due to its anti-inflammatory and antioxidant effects, but its specific mechanism of action is not known. We aimed to clarify the role of MET on COPD and cigarette smoke extract (CSE)-induced GC resistance. Through establishment of a COPD model in rats, we found that MET could improve lung function, reduce pathological injury, as well as reduce the level of inflammation and oxidative stress in COPD, and upregulate expression of nuclear factor E2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), multidrug resistance protein 1 (MRP1), and histone deacetylase 2 (HDAC2). By establishing a model of GC resistance in human bronchial epithelial cells stimulated by CSE, we found that MET reduced secretion of interleukin-8, and could upregulate expression of Nrf2, HO-1, MRP1, and HDAC2. MET could also increase the inhibition of MRP1 efflux by MK571 significantly, and increase expression of HDAC2 mRNA and protein. In conclusion, MET may upregulate MRP1 expression by activating the Nrf2/HO-1 signaling pathway, and then regulate expression of HDAC2 protein to reduce GC resistance.