BackgroundFor early screening and diagnosis of non-small cell lung cancer (NSCLC), a robust model based on plasma proteomics and metabolomics is required for accurate and accessible non-invasive detection. Here we aim to combine TMT-LC-MS/MS and machine-learning algorithms to establish models with high specificity and sensitivity, and summarize a generalized model building scheme.MethodsTMT-LC-MS/MS was used to discover the differentially expressed proteins (DEPs) in the plasma of NSCLC patients. Plasma proteomics-guided metabolites were selected for clinical evaluation in 110 NSCLC patients who were going to receive therapies, 108 benign pulmonary diseases (BPD) patients, and 100 healthy controls (HC). The data were randomly split into training set and test set in a ratio of 80:20. Three supervised learning algorithms were applied to the training set for models fitting. The best performance models were evaluated with the test data set.ResultsDifferential plasma proteomics and metabolic pathways analyses revealed that the majority of DEPs in NSCLC were enriched in the pathways of complement and coagulation cascades, cholesterol and bile acids metabolism. Moreover, 10 DEPs, 14 amino acids, 15 bile acids, as well as 6 classic tumor biomarkers in blood were quantified using clinically validated assays. Finally, we obtained a high-performance screening model using logistic regression algorithm with AUC of 0.96, sensitivity of 92%, and specificity of 89%, and a diagnostic model with AUC of 0.871, sensitivity of 86%, and specificity of 78%. In the test set, the screening model achieved accuracy of 90%, sensitivity of 91%, and specificity of 90%, and the diagnostic model achieved accuracy of 82%, sensitivity of 77%, and specificity of 86%.ConclusionsIntegrated analysis of DEPs, amino acid, and bile acid features based on plasma proteomics-guided metabolite profiling, together with classical tumor biomarkers, provided a much more accurate detection model for screening and differential diagnosis of NSCLC. In addition, this new mathematical modeling based on plasma proteomics-guided metabolite profiling will be used for evaluation of therapeutic efficacy and long-term recurrence prediction of NSCLC.

BackgroundTo achieve potential financial savings and avoid exposing the patients to unnecessary risk, an optimal diagnostic strategy to identify low risk individual who may derive minimal benefit from further cardiac imaging testing (CIT) is important for patients with stable chest pain (SCP) suggestive of chronic coronary syndrome (CCS). Although several diagnostic strategies have been recommended by the most recent guidelines, few randomized controlled trials (RCTs) have prospectively investigated the actual effect of applying these strategies in clinical practice.MethodsOPERATE (OPtimal Evaluation of stable chest pain to Reduce unnecessAry utilization of cardiac imaging TEsting) trial is an investigator-initiated, multicenter, coronary computed tomography angiography (CCTA)-based, 2-arm parallel-group, double-blind, pragmatic and confirmative RCT planning to include 800 subjects with SCP suggestive of CCS. After enrollment, all subjects will be randomized to two arms (2016 U.K. National Institute of Health and Care Excellence guideline-determined and 2019 European Society of Cardiology guideline-determined diagnostic strategy) on a 1:1 basis. According to each strategy, CCTA should be referred and deferred for a subject in high and low risk group, respectively. The primary (effectiveness) endpoint is CCTA without obstructive coronary artery disease. Safety of each strategy will be mainly assessed by 1-year major adverse cardiovascular event rates.DiscussionThe OPERATE trial will provide comparative effectiveness and safety evidences for two different diagnostic strategies for patients with SCP suggestive of CCS, with the intension of improving the diagnostic yield of CCTA at no expense of safety.Clinical trial registrationClinicalTrial.org Identifier NCT05640752.

BackgroundMalakoplakia is a rare inflammatory disease of the urogenital tract. There have been no reports of malakoplakia expressing anaplastic lymphoma kinase (ALK) to date. Here, we present one case of malakoplakia with aberrant ALK expression by immunohistochemistry and discuss the clinical significance.Case presentationA 65-year-old Chinese woman with a history of diabetes presented with solid masses in the liver and kidney and elevated lesions on the mucosal surface of the colon. Right nephrectomy and partial liver resection were performed. Microscopically, sheets of histiocytes with poor intercellular adhesion were seen, with Michaelis–Gutmann bodies present in both the intracellular and extracellular interstitium. CD10-, CD68-, and CD163-positive cells were present, with Michaelis–Gutmann bodies confirmed by staining with Alcian blue, periodic acid-Schiff (PAS), periodic acid-Schiff with diastase, Von Kossa, and Prussian blue. Aberrant ALK1 and ALK (D5F3) expression was observed in the cytoplasm and nucleus of cells. However, ALK gene mutation was not detected by fluorescence in situ hybridization or whole exome next-generation sequencing. NGS revealed nine individual somatic gene mutations: GOT1L1, GLIS2, SPOUT1, TMEM97, MUC3A, NSD2, SFXN5, ADAD1 and RAD50. The significance of the somatic gene mutations detected in this study is not clear, and the relationship between them and malakoplakia cannot be clarified by existing scientific studies. The pathological diagnosis was malakoplakia with aberrant ALK expression by immunohistochemistry. The antibiotics imipenem and vancomycin were started based on the results of drug sensitivity analysis and the patient was subsequently discharged. She experienced no discomfort during 30 months of follow-up.ConclusionThis is the first reported case of malakoplakia with aberrant ALK expression, it should be differentiated from ALK-positive histiocytosis to avoid misdiagnosis.

Claudin 18.2 (CLDN18.2)-targeting chimeric antigen receptor (CAR)-modified T cells are one of the few cell therapies currently producing an impressive therapeutic effect in treating solid tumors; however, their long-term therapeutic efficacy is not satisfactory with a short duration of response. Transgenic expression of interleukin (IL)-15 has been reported to promote T-cell expansion, survival, and function and enhance the antitumor activity of engineered T cells in vitro and in vivo. Therefore, this study aimed to explore whether IL-15 modification would increase the antitumor activity of CLDN18.2-targeting CAR-modified T (CAR-T) cells in immunocompetent murine tumor models. CLDN18.2-specific CAR-T cells with (H9 CAR-IL15) or without transgenic IL-15 expression (H9 CAR) were generated by retroviral transduction of mouse splenic T cells. In vitro, compared with H9 CAR T cells, H9 CAR-IL15 T cells exhibited better expansion and viability in the absence of antigen stimulation, with a less differentiated and T-cell exhausted phenotype; although IL-15 modification did not affect the production of effector cytokines and cytotoxic activity in the short-term killing assay, it moderately improved the in vitro recursive killing activity of CAR-T cells against CLDN18.2-expressing tumor cells. In vivo, H9 CAR T cells showed no antitumor activity against CLDN18.2-expressing pancreatic tumors in immunocompetent mice without lymphodepleting pretreatment; however, H9 CAR-IL15 T cells produced significant tumor-suppressive effects. Furthermore, H9 CAR-IL15 T cells exhibited greater in vivo expansion and tumor infiltration when combined with lymphodepleting preconditioning, resulting in superior antitumor activity in two murine tumor models and a survival advantage in one tumor model. We further demonstrated that recurrent tumors following H9 CAR-IL15 T-cell therapy downregulated CLDN18.2 expression, suggesting immune escape through the selection of antigen-negative cells under persistent CAR-T-cell immune pressure. In conclusion, our findings provide preclinical evidence supporting the clinical evaluation of IL-15-expressing CLDN18.2 CAR-T cells in patients with CLDN18.2-positive tumors.

ObjectiveUmbilical cord mesenchymal stem cells (UCMSCs) have significant regenerative, tissue repair, and immunomodulatory properties that can help reduce inflammatory responses in patients with ankylosing spondylitis (AS). In this study, we used a combination of bovine proteoglycan and dimethyldioctadecylammonium (DDA) to establish a mouse model of proteoglycan-induced spondylitis (PGISp). To evaluate the therapeutic effects of UCMSCs, we treated PGISp mice with different doses of hUCMSCs via tail vein injection.MethodsAt week 13, the PGISp mice exhibited thickened, erythematous paws, erythema in the extremities, and lameness. CT scans revealed necrotic lysis of chondrocytes, formation of fissures, visible hemorrhage, connective tissue hyperplasia, and focal infiltration of lymphocytes in the intervertebral discs. At week 14, the PGISp mice were randomly divided into three groups and administered different doses of hUCMSCs (0.25, 0.5, and 1.0×107 cells/kg, iv, QOW×2, n=10). To assess the therapeutic effects of hUCMSCs, we evaluated Th cell subsets in the spleen, spleen and thymus coefficients, peripheral blood inflammatory factors, and pathological and imaging observations of the spines and lumbar spines in the PGISp mice.ResultsThe results demonstrated that injection of hUCMSCs shifted the balance axis between Th1 and Th2 cells in the spleen towards Th2 cells. Moreover, the spleen coefficient and levels of inflammatory cytokines (TNF-α and CCL-2) in the serum decreased after hUCMSC injection. CT imaging and pathological analysis indicated that hUCMSC treatment inhibited ectopic osteogenesis and maintained clear small joint gaps, which slowed down the progression of structural lesions in the disc, nucleus pulposus, fibrous ring, and cartilage in PGISp mice.ConclusionAdministering hUCMSCs at the 14th week after modeling proved to be an effective treatment for PGISp mice. This experiment offers a valuable reference for the pre-clinical use of hUCMSCs in the treatment of AS.

Background and objectiveThe CHOICE-01 trial showed that toripalimab plus chemotherapy achieved satisfactory outcomes compared with chemotherapy in patients with advanced non-small cell lung cancer (NSCLC) who were negative for driver genes, but the economics of this regimen is unclear. Therefore, this study aimed to evaluate the cost-effectiveness of toripalimab in combination with chemotherapy in advanced NSCLC with negative driver genes from the perspective of the Chinese healthcare system.Materials and methodsA three-state partitioned survival model was developed to simulate the costs and outcomes associated with adding toripalimab to first-line chemotherapy. The clinical data in the model came from the CHOICE-01 trial, only direct medical costs were included, and utility values were referred to the literature. Four models were applied to explore the differences in the results of fitting and extrapolating K-M curves from different models, and cost-effectiveness subgroup analysis was performed. The incremental cost-effectiveness ratio (ICER) was used as the main outcome measure. Sensitivity analysis was performed to assess the impact of parameter uncertainty on the model.ResultsThe baseline analysis showed that toripalimab coupled with chemotherapy cost $21,052 more than chemotherapy ($43,197 vs. $22,145) and also gained 0.71 QALYs more (1.75 QALYs vs. 1.03 QALYs), with an ICER of $29,478/QALYs. At the current willingness-to-pay threshold ($35,108/QALY), the extra cost was well worth it. The results of fitting and extrapolating the survival curves using other models were consistent with the results of the standard parametric model. Subgroup analysis demonstrated that the addition of toripalimab to chemotherapy was economical. Sensitivity analysis showed that the utility values of PD and PFS stages had the greatest impact on the model.ConclusionFrom the viewpoint of the Chinese healthcare system, toripalimab combined with chemotherapy in the treatment of advanced NSCLC with negative driver genes was likely to be cost-effective compared with chemotherapy.