Computed tomography-based radiomics improves non-invasive diagnosis of Pneumocystis jirovecii pneumonia in non-HIV patients: a retrospective study.

BACKGROUND: Pneumocystis jirovecii pneumonia (PCP) could be fatal to patients without human immunodeficiency virus (HIV) infection. Current diagnostic methods are either invasive or inaccurate. We aimed to establish an accurate and non-invasive radiomics-based way to identify the risk of PCP infection in non-HIV patients with computed tomography (CT) manifestation of pneumonia. METHODS: This is a retrospective study including non-HIV patients hospitalized for suspected PCP from January 2010 to December 2022 in one hospital. The patients were randomized in a 7:3 ratio into training and validation cohorts. Computed tomography (CT)-based radiomics features were extracted automatically and used to construct a radiomics model. A diagnostic model with traditional clinical and CT features was also built. The area under the curve (AUC) were calculated and used to evaluate the diagnostic performance of the models. The combination of the radiomics features and serum ß-D-glucan levels was also evaluated for PCP diagnosis. RESULTS: A total of 140 patients (PCP: N = 61, non-PCP: N = 79) were randomized into training (N = 97) and validation (N = 43) cohorts. The radiomics model consisting of nine radiomic features performed significantly better (AUC = 0.954; 95% CI: 0.898-1.000) than the traditional model consisting of serum ß-D-glucan levels (AUC = 0.752; 95% CI: 0.597-0.908) in identifying PCP (P = 0.002). The combination of radiomics features and serum ß-D-glucan levels showed an accuracy of 95.8% for identifying PCP infection (positive predictive value: 95.7%, negative predictive value: 95.8%). CONCLUSIONS: Radiomics showed good diagnostic performance in differentiating PCP from other types of pneumonia in non-HIV patients. A combined diagnostic method including radiomics and serum ß-D-glucan has the potential to provide an accurate and non-invasive way to identify the risk of PCP infection in non-HIV patients with CT manifestation of pneumonia. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05701631).

Species Distribution, Typical Clinical Features and Risk Factors for Poor Prognosis of Super-Elderly Patients with Bloodstream Infection in China.

Objective: Bloodstream infection (BSI) is characterized by high mortality, especially among these increasing super-elderly patients (≥85 years), and this study was conducted to understand the species distribution, typical clinical features and risk factors for poor prognosis of super-elderly patients with BSI. Methods: Based on previous work, this retrospective study was performed by reviewing an ongoing prospective medical database in a comprehensive tertiary center in China, and all super-elderly patients with BSI in the past 6 years were enrolled in this study. Results: Out of 5944 adult-patients with BSI, there were totally 431 super-elderly patients (≥85 years old) enrolled in this study and age ≥90 years accounted for 31.1% (134/431). Among these 431 super-elderly patients with BSI, 40 patients (9.3%) were diagnosed with BSI and the remained 401 super-elderly patients (90.7%) were defined as hospital-acquired BSI. The typical feature of these super-elderly patients with BSI was the high proportion of patients with various comorbidities, such as cardiovascular disease (83.8%), ischemic cerebrovascular disease (63.3%) and pulmonary infection (61.0%). The other typical feature was that most (60.1%) of these patients had been hospitalized for long time (≥28 days) prior to the onset of BSI, and most patients had received various invasive treatments, such as indwelling central venous catheter (53.1%) and indwelling urinary catheter (47.1%). Unfortunately, due to these adverse features above, both the 7-day short-term mortality (13.2%, 57/431) and the 30-day long-term mortality (24.8%, 107/431) were high. The multivariate analysis showed that both chronic liver failure (OR 7.9, 95% CI 2.3-27.8, P=0.001) and indwelling urinary catheter (OR 2.3, 95% CI 1.1-4.7, P=0.023) were independent risk factors for 7-day short-term mortality, but not for 30-day long-term mortality. In addition, the microbiology results showed that the most common species were associated with nosocomial infection or self-opportunistic infection, such as Staphylococcus hominis (18.3%), Staphylococcus epidermidis (11.8%), Escherichia coli (9.7%), Klebsiella pneumoniae (9.3%) and Candida albicans (8.6%, fungi). Conclusion: Super-elderly patients with BSI had typical features, regardless of the pathogenic species distribution and their drug resistance, or clinical features and their risk factors for poor prognosis. These typical features deserved attention and could be used for the prevention and treatment of BSI among super-elderly patients.

Establishing a predictive model for tumor mutation burden status based on CT radiomics and clinical features of non-small cell lung cancer patients.

Background: Tumor mutation burden (TMB) is one of the biomarkers for efficacy of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC). Due to the potential of radiomic signatures to identify microscopic genetic and molecular differences, thus radiomics is considered a suitable tool for judging the TMB status probably. In this paper, the radiomics method was applied to analyze the TMB status of NSCLC patients, so as to construct a prediction model for distinguishing between TMB-high and TMB-low status. Methods: A total of 189 NSCLC patients with TMB detection result were retrospectively included between 30 November 2016 and 1 January 2021, and were divided into two groups: TMB-high (≥10/Mb, 46 patients) and TMB-low (<10/Mb, 143 patients). Some clinical features related to TMB status were screened out in 14 clinical features and 2,446 radiomic features were extracted. All patients were randomly divided into a training set (n=132) and a validation set (n=57). Univariate analysis and least absolute shrinkage and selection operator (LASSO) were used for radiomics feature screening. A clinical model, radiomics model, and nomogram were constructed with the above screened features and compared. Decision curve analysis (DCA) was used to evaluate the clinical value of the established models. Results: Two clinical features (smoking history, pathological type) and 10 radiomics features were significantly correlated with the TMB status. The prediction efficiency of the intra-tumoral model was better than that of the peritumoral model (AUC: 0.819 vs. 0.816; accuracy: 0.773 vs. 0.632, specificity: 0.767 vs. 0.558). The efficacy of the prediction model based on radiomic features was significantly better than that of the clinical model (AUC: 0.822 vs. 0.683; specificity: 0.786 vs. 0.643). The nomogram, established by combining smoking history, pathologic type, and rad-score, showed the best diagnostic efficacy (AUC =0.844) and had potential clinical value in assessing the TMB status of NSCLC. Conclusions: The radiomics model based on CT images of NSCLC patients performed well in distinguishing the status of TMB-high and TMB-low, and the nomogram could provide additional information on the timing and regimen of immunotherapy.

Z-guggulsterone induces PD-L1 upregulation partly mediated by FXR, Akt and Erk1/2 signaling pathways in non-small cell lung cancer.

Programmed death-ligand 1 (PD-L1) is an immune checkpoint molecule, that is overexpressed in non-small cell lung cancer (NSCLC) and has been associated with the response to anti-PD-1/PD-L1 immunotherapy. Z-guggulsterone (Z-GS), an active compound extracted from the gumresin of the Commiphora mukul tree, has been shown to have anti-tumor effects in NSCLC in our previous study. However, whether Z-GS could affect PD-L1 expression levels in tumor cells remains unknown. In this study, we verified the inhibitory effects of Z-GS on NSCLC cell viability and cell cycle progression in vitro, and mouse Lewis lung carcinoma (LLC) tumor growth in vivo. Notably, Z-GS treatment increased PD-L1 surface and mRNA expression levels, and gene transcription in NSCLC cells, in a dose- and time-dependent manner. Mechanistic experiments showed that the upregulation of PD-L1 was mediated, partly by farnesoid X receptor inhibition, and partly by the activation of the Akt and Erk1/2 signaling pathways in Z-GS-treated NSCLC cells. In vivo, Z-GS treatment dose-dependently increased PD-L1 expression levels in mouse LLC tumor models. Overall, our findings demonstrated a promoting role for Z-GS in PD-L1 expression in NSCLC and provided mechanistic insights, that may be used for further investigation into synergistic combined therapies.

Glycyrrhizin suppresses epithelial-mesenchymal transition by inhibiting high-mobility group box1 via the TGF-ß1/Smad2/3 pathway in lung epithelial cells.

BACKGROUND: Epithelial-mesenchymal transition (EMT) plays an important role in fibrosis, chronic inflammation, tumor metastasis, etc. Glycyrrhizin, an active component extracted from licorice plant, has been reported to treat a variety of inflammatory reactions through inhibiting high-mobility group box1 (HMGB1), which has been suggested to be a significant mediator in EMT process. However, whether glycyrrhizin affects the EMT process or not remains unclear. METHODS: Human alveolar epithelial cell line A549 and normal human bronchial epithelial cell line BEAS-2B were treated with extrinsic TGF-ß1 to induce EMT. Elisa was used to detect HMGB1 concentrations in cell supernatant. RNA interference and lentivirus infection experiments were performed to investigate the involvement of HMGB1 in EMT process. Cell Counting Kit-8 (CCK-8) was used to detect the viability of A549 and BEAS-2B cells treated with glycyrrhizin. Finally, the effects of glycyrrhizin on EMT changes, as well as the underlying mechanisms, were evaluated via Western blot, immunofluorescence and transwell assays. RESULTS: Our results showed that HMGB1 expression was increased by TGF-ß1, and knockdown of HMGB1 expression reversed TGF-ß1-induced EMT in A549 and BEAS-2B cells. Ectopic HMGB1 expression or TGF-ß1 treatment caused a significant increase in HMGB1 release. Notably, we found that glycyrrhizin treatment effectively suppressed TGF-ß1-induced EMT process by inhibiting HMGB1. Also, glycyrrhizin significantly inhibited the migration of both A549 and BEAS-2B cells promoted by TGF-ß1. Mechanistically, HMGB1 overexpression could activate Smad2/3 signaling in A549 and BEAS-2B cells. Glycyrrhizin significantly blocked the phosphorylation of Smad2/3 stimulated either by TGF-ß1 or by ectopic HMGB1 in A549 and BEAS-2B cells. CONCLUSIONS: HMGB1 is a vital mediator of EMT changes induced by TGF-ß1 in lung epithelial cells. Importantly, glycyrrhizin can effectively block Smad2/3 signaling pathway through inhibiting HMGB1, thereby suppressing the EMT progress.