The development of a prediction model based on random survival forest for the prognosis of non- Hodgkin lymphoma: A prospective cohort study in China.

Background and objective: The pathological staging of non-Hodgkin lymphoma (NHL) is complex, the clinical manifestations are varied, and the prognosis differ considerably. To provide a useful reference for early detection and effective treatment of NHL, we developed a random survival forest (RSF) prognostic model based on machine learning (ML) algorithms using prospective cohort data collected from Chongqing Cancer Hospital from Jan 1, 2017 to Dec 31, 2019 (n = 1449) to compare with the traditional cornerstone method Cox proportional hazards (CPH) model and evaluate the predictability of the model. Methods: Patients were randomly split into a training cohort (TC) and validation cohort (VC) based on 65/35 ratio. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to extracted the important features. And the RSF was modeled to explore the prognostic factors impacting the overall survival (OS) of patients with NHLs in the TC and validated in the VC. The C-index, the Integrated Brier Score (IBS), Kaplan-Meir method, the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) were selected to measure performances and discriminations of the models. In addition, individual survival probability predicted for NHL patients. Results: According to the features extracted by LASSO model and univariable Cox model, 16 variables were selected to develop the RSF model with log-rank splitting rule, which were age, ethnicity, medical insurance, Ann Arbor stage, pathology, targeted-therapy, chemo-therapy, peripheral blood neutrophil count to lymphocyte count ratio (NLR), peripheral blood platelet count to lymphocyte count ratio (PLR), serum lactate dehydrogenase (LDH), CD4/CD8, platelet (PLT), absolute neutrophil count (ANC), lymphocyte (LYM), B-symptoms, and (CPR) were important prognostic factors. Compared to the CPH model (C-index = 0.748, IBS = 0.166), the RSF model (C-index = 0.786, IBS = 0.165) is outperformed in predictability and accuracy. The AUC of the RSF model to estimate the 1-, 3-, and 5-year OS in TC were 0.847, 0.847, and 0.809, respectively; while those in the CPH were 0.816, 0.803, and 0.750, respectively. Conclusions: To provide practical implications for the implementation of individualized therapy, the study constructed a high-performed RSF model and reveal that it outperformed the traditional model CPH. And the RSF model ranked the risk variables. In addition, we stratified the risk of NHL patients and estimated individual survival probability based on the RSF model.

Knockdown of circ_0076305 decreases the paclitaxel resistance of non-small cell lung cancer cells by regulating TMPRSS4 via miR-936.

Background: Paclitaxel (PTX) is a commonly used as a chemotherapeutic drug for non-small cell lung cancer (NSCLC). Exploring the underlying mechanism of PTX resistance is of great significance for NSCLC treatment. Methods: The expression levels of RNA and protein were detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blot assays. The targeted relationship was confirmed by dual-luciferase reporter assay and RNA-pull down assay. The PTX resistance and cell proliferation were assessed by cell counting kit-8 (CCK-8) assay and 5-Ethynyl-2'-deoxyuridine (EDU) assay, respectively. Cell migration and invasion were analyzed by transwell assays. Cell apoptosis was analyzed by flow cytometry, and cell glycolysis was analyzed using the commercial kits. The role of circular RNA_0076305 (circ_0076305) in regulating the PTX sensitivity in vivo was explored in xenograft tumor model. Results: Circ_0076305 was up-regulated in PTX-resistant NSCLC tissues and cells. Mechanically, circ_0076305 bound to microRNA-936 (miR-936), and miR-936 targeted transmembrane serine protease 4 (TMPRSS4). Circ_0076305 could up-regulate TMPRSS4 expression by sponging miR-936 in NSCLC cells. miR-936 knockdown or TMPRSS4 overexpression reversed the anti-tumor effects of circ_0076305 knockdown in NSCLC cells with PTX treatment. Circ_0076305 silencing increased the PTX sensitivity of xenograft tumors in vivo. Conclusion: Circ_0076305 silencing promoted PTX sensitivity by targeting miR-936/TMPRSS4 axis in NSCLC cells.

Ectopic pleural thymoma with T-cell lymphocytosis and bone metastasis: a case report.

BACKGROUND: The diagnostic complexities that arise in radiographic distinction between ectopic pleural thymoma and other thoracic neoplasms are substantial, with instances of co-occurring T-cell lymphocytosis and osseous metastasis being exceedingly rare. CASE PRESENTATION: A 51-year-old woman was admitted to our hospital with dyspnea and chest pain. Upon imaging examination, she was found to have diffuse and nodular pleural thickening on the left side, collapse of the left lung and a compression in the second thoracic vertebrae. All lesions showed significant 18F-FDG uptake on 18F-FDG PET/CT examination. Furthermore, she exhibited T-cell lymphocytosis in her peripheral blood, lymph nodes, and bone marrow. After ruling out malignant pleural mesothelioma (MPM), lung cancer with pleural metastasis, and T-cell lymphoma, the definitive diagnosis asserted was ectopic pleural thymoma with T-cell lymphocytosis and bone metastasis. CONCLUSION: Physicians need to expand their knowledge of the imaging features of ectopic pleural thymoma. Cases with T-cell lymphocytosis may exhibit increased aggressiveness and prone to bone metastasis.

A genome-wide association study uncovers a ZmRap2.7-ZCN9/ZCN10 module to regulate ABA signalling and seed vigour in maize.

Seed vigour, including rapid, uniform germination and robust seedling establishment under various field conditions, is becoming an increasingly essential agronomic trait for achieving high yield in crops. However, little is known about this important seed quality trait. In this study, we performed a genome-wide association study to identify a key transcription factor ZmRap2.7, which regulates seed vigour through transcriptionally repressing expressions of three ABA signalling genes ZmPYL3, ZmPP2C and ZmABI5 and two phosphatidylethanolamine-binding genes ZCN9 and ZCN10. In addition, ZCN9 and ZCN10 proteins could interact with ZmPYL3, ZmPP2C and ZmABI5 proteins, and loss-of-function of ZmRap2.7 and overexpression of ZCN9 and ZCN10 reduced ABA sensitivity and seed vigour, suggesting a complex regulatory network for regulation of ABA signalling mediated seed vigour. Finally, we showed that four SNPs in ZmRap2.7 coding region influenced its transcriptionally binding activity to the downstream gene promoters. Together with previously identified functional variants within and surrounding ZmRap2.7, we concluded that the distinct allelic variations of ZmRap2.7 were obtained independently during maize domestication and improvement, and responded separately for the diversities of seed vigour, flowering time and brace root development. These results provide novel genes, a new regulatory network and an evolutional mechanism for understanding the molecular mechanism of seed vigour.

Ferrocene-functionalized polydopamine film timely mediates M1-to-M2 macrophage polarization through adaptive wettability.

Dynamical control of macrophage polarization from M1 (pro-inflammatory) to M2 (anti-inflammatory) at implant surfaces is essential for balancing innate immunity and tissue repair. In this aspect, the design of orthopedic implant that can response to inflammation microenvironment with transformation in surface properties has shown promising in timely driving M1-to-M2 macrophage transition. Considering excessive reactive oxygen species (ROS) contribute to macrophage M1 polarization and progression of inflammation, in this study, ferrocene modified polydopamine (PDA-Fc) films were deposited on plasma sprayed Ti coatings to endow the implants with ROS-responsive and -scavenging abilities. Plasma sprayed Ti (PST) coating and PDA modified PST coating (PST/PDA) served as control. The presence of PDA endowed PST/PDA and PST/PDA-Fc with free-radical scavenging abilities. Moreover, PST/PDA-Fc showed adaptive wettability as evidenced by increased hydrophilicity under H2O2 treatment. With respect to PST/PDA, PST/PDA-Fc exerted greater effects on inducing lipopolysaccharides-induced M1 macrophages to adopt M2-type macrophage phenotype, characterized by higher percentage of CD206-positive cells, increased cell elongation rate and higher expression level of anti-inflammatory cytokine arginase type 1. The results obtained in our study may provide a prospective approach for manipulating an appropriate immune response at implant surfaces.

Development and validation of a nomogram model for predicting the risk of venous thromboembolism in lymphoma patients undergoing chemotherapy: a prospective cohort study conducted in China.

BACKGROUND: The mechanism of Venous thromboembolism (VTE) is complicated and difficult to prevent due to factors such as bone marrow invasion, therapy, and immune-mediated effects. This study aims to establish a nomogram model for predicting the risk of thrombosis in lymphoma patients undergoing chemotherapy, which has been increasing over the past 30 years. METHODS: The data of lymphoma patients from the Affiliated Cancer Hospital of Chongqing University in China between 2018 and 2020 were analyzed. This included age, sex, body mass index, ECOG score, histological type, Ann Arbour Stage, white blood cells count, haemoglobin level, platelet count, D-dimer level, and chemotherapy cycle. Univariate and multivariate cox analysis was used to determine the risk factors for VTE. Characteristic variables were selected to construct a nomogram model which was then evaluated using ROC curve and calibration. RESULTS: Age, sex, PLT, D-dimer and chemotherapy cycle were considered as independent influencing factors of VTE. The mean (standard deviation) of the C index, AUC and Royston D statistics of 1000 cross-validations of the Nomogram model were 0.78 (0.01), 0.81 (0.01) and 1.61(0.07), respectively. It indicates a good calibration degree and applicability value as shown by the calibration curve. The DCA curve showed a rough threshold range of 0.05-0.60 with a good model. CONCLUSIONS: We have established and validated a nomogram model for predicting the risk of thrombosis in lymphoma patients. This model can assess the risk of thrombosis in each individual patient, enabling the identification of high-risk groups and targeted preventive treatment.