The challenge of methotrexate (MTX) resistance among low-risk gestational trophoblastic neoplasia (GTN) patients has always been prominent. Despite the International Federation of Gynaecology and Obstetrics (FIGO) score of 0-4 patients comprising the majority of low-risk GTN patients, a comprehensive exploration of the prevalence and risk factors associated with MTX resistance has been limited. Therefore, we aimed to identify associated risk factors in GTN patients with a FIGO score of 0-4. Between January 2005 and December 2020, 310 low-risk GTN patients received primary MTX chemotherapy in two hospitals, with 265 having a FIGO score of 0-4. In the FIGO 0-4 subgroup, 94 (35.5%) were resistant to MTX chemotherapy, and 34 (12.8%) needed multi-agent chemotherapy. Clinicopathologic diagnosis of postmolar choriocarcinoma (OR = 17.18, 95% CI: 4.64-63.70, P < 0.001) and higher pretreatment human chorionic gonadotropin concentration on a logarithmic scale (log-hCG concentration) (OR = 18.11, 95% CI: 3.72-88.15, P < 0.001) were identified as independent risk factors associated with MTX resistance according to multivariable logistic regression. The decision tree model and regression model were developed to predict the risk of MTX resistance in GTN patients with a FIGO score of 0-4. Evaluation of model discrimination, calibration and net benefit revealed the superiority of the decision tree model, which comprised clinicopathologic diagnosis and pretreatment hCG concentration. The patients in the high- and medium-risk groups of the decision tree model had a higher probability of MTX resistance. This study represents the investigation into MTX resistance in GTN patients with a FIGO score of 0-4 and disclosed a remission rate of approximately 65% with MTX chemotherapy. Higher pretreatment hCG concentration and clinicopathologic diagnosis of postmolar choriocarcinoma were independent risk factors associated with resistance to MTX chemotherapy. The decision tree model demonstrated enhanced predictive capabilities regarding the risk of MTX resistance and can serve as a valuable tool to guide the clinical treatment decisions for GTN patients with a FIGO score of 0-4.

Osteosarcoma is one of the most common malignant bone tumors with high chemoresistance and poor prognosis, exhibiting abnormal gene regulation and epigenetic events. Methotrexate (MTX) is often used as a primary agent in neoadjuvant chemotherapy for osteosarcoma; However, the high dosage of methotrexate and strong drug resistance limit its therapeutic efficacy and application prospects. Studies have shown that abnormal expression and dysfunction of some coding or non-coding RNAs (e.g., DNA methylation and microRNA) affect key features of osteosarcoma progression, such as proliferation, migration, invasion, and drug resistance. Comprehensive multi-omics analysis is critical to understand its chemoresistant and pathogenic mechanisms. Currently, the network analysis-based non-negative matrix factorization (netNMF) method is widely used for multi-omics data fusion analysis. However, the effects of data noise and inflexible settings of regularization parameters affect its performance, while integrating and processing different types of genetic data is also a challenge. In this study, we introduced a novel adaptive total variation netNMF (ATV-netNMF) method to identify feature modules and characteristic genes by integrating methylation and gene expression data, which can adaptively choose an anisotropic smoothing scheme to denoise or preserve feature details based on the gradient information of the data by introducing an adaptive total variation constraint in netNMF. By comparing with other similar methods, the results showed that the proposed method could extract multi-omics fusion features more effectively. Furthermore, by combining the mRNA and miRNA data of methotrexate (MTX) resistance with the extracted feature genes, four genes, Carboxypeptidase E (CPE), LIM, SH3 protein 1 (LASP1), Pyruvate Dehydrogenase Kinase 1 (PDK1) and Serine beta-lactamase-like protein (LACTB) were finally identified. The results showed that the gene signature could reliably predict the prognostic status and immune status of osteosarcoma patients.

The mechanism by which redox metabolism regulates the fates of acute myeloid leukemia (AML) cells remains largely unknown. Using a highly sensitive, genetically encoded fluorescent sensor of nicotinamide adenine dinucleotide phosphate (NADPH), iNap1, we find three heterogeneous subpopulations of AML cells with different cytosolic NADPH levels in an MLL-AF9-induced murine AML model. The iNap1-high AML cells have enhanced proliferation capacities both in vitro and in vivo and are enriched for more functional leukemia-initiating cells than iNap1-low counterparts. The iNap1-high AML cells prefer localizing in the bone marrow endosteal niche and are resistant to methotrexate treatment. Furthermore, iNap1-high human primary AML cells have enhanced proliferation abilities both in vitro and in vivo. Mechanistically, the MTHFD1-mediated folate cycle regulates NADPH homeostasis to promote leukemogenesis and methotrexate resistance. These results provide important clues for understanding mechanisms by which redox metabolism regulates cancer cell fates and a potential metabolic target for AML treatments.

Choriocarcinoma is one of the most aggressive gestational trophoblastic neoplasias (GTN). Methotrexate (MTX) resistance is the main cause of treatment failure in choriocarcinoma. However, the mechanism of MTX resistance in choriocarcinoma is poorly known. This study aims to explore the function of Lectin galactoside-binding soluble 3 binding protein (LGALS3BP) in MTX-resistance in choriocarcinoma cells. Gradual dose escalation of MTX was used to establish MTX-resistant choriocarcinoma cells (JAR-MTX and JEG3-MTX cell lines). RNA-sequencing was used to explore the differentially expressed genes. Plasmids or SiRNA transfection was used to regulate the expression of LGALS3BP. ELISA was used to detect the concentrations of LGALS3BP in the serum of MTX-sensitive and MTX-resistant patients. qRT-PCR, Western blot, and CCK-8 assay were used to determine the effects of LGALS3BP on MTX-resistance in JAR and JEG3 cells. The results showed the relative resistance index (RI) of MTX is 791.50 and 1040.04 in JAR-MTX and JEG3-MTX, respectively. LGALS3BP was up-regulated in MTX-resistant cells compared to original cells in both RNA and protein level. The concentrations of LGALS3BP were higher in the sera of MTX-resistant patients than in MTX-sensitive patients. Knocking down LGALS3BP can reverse the MTX-resistance in JAR-MTX and JEG3-MTX cells. In summary, we preliminarily established two MTX-resistant cells, and performed RNA-sequencing, and found LGALS3BP may play important role in MTX-resistance. Our work not only provides a research tool (MTX-resistant cells) for other researchers, but gives some hint on how MTX resistance is regulated.

Rheumatoid arthritis (RA) is a systemic autoimmune disease, which is characterized by a chronic fluctuating course and immune dysfunction, resulting in affecting the health and life quality of RA patients. Methotrexate (MTX), as the standard gold treatment of RA, has received more and more clinical applications and basic pharmacological research. In several observational studies, MTXR, and treatment responses in RA patients show that the ratio of MTXR and non- response is about 30%-50%, namely MTX resistance (MTXR). Extensive efforts have been made into the investigation of the mechanism and effective biomarkers in MTXR of RA. In this paper, we discuss the recent findings regarding the critical signaling pathways of MTXR in RA. Provide research targets and directions for a drug therapy that develop preventive strategies and effective treatments of MTXR.

This prospective clinical study aimed to evaluate the vascularization characteristics of low-risk gestational trophoblastic neoplasia (GTN) using Doppler imaging and to develop a predictive model for resistance to methotrexate (MTX).
Patients with low-risk GTN receiving primary MTX treatment were enrolled from the Women\'s Hospital, Zhejiang University School of Medicine, Hangzhou, China, from September 2012 to August 2018. The primary endpoint was to develop and internally validate a predictive model for resistance to MTX therapy in these patients. In the training set, clinical features and Doppler hemodynamic parameters before MTX therapy were analyzed using logistic regression to identify independent predictors of MTX resistance, which were integrated into the model. The predictive performance of the model was evaluated by leave-one-out cross-validation in the training dataset and internal validation in an independent-sample test dataset.
The entire imaging protocol was completed by 147 eligible patients, of which 110 comprised the training set and 37 the test set. In the training set, cases with myometrial invasion (81.8%; 90/110) showed vascular-enriched areas in the myometrium and high velocity and low impedance ratios of the uterine artery (UtA) compared to cases without myometrial invasion (18.2%; 20/110). On multivariate logistic regression analysis, time-averaged mean velocity in UtA (UtA-TAmean) and the International Federation of Gynecology and Obstetrics (FIGO) score were identified as independent predictors (P = 0.009 and P = 0.043, respectively) of MTX resistance. The Doppler-based predictive model, developed based on the 90 cases with myometrial invasion, was y = -2.95332 + 0.41696 × FIGO score + 0.03551 × UtA-TAmean. The model showed an area under the curve of 0.757 (95% CI, 0.653-0.862) and the optimal cut-off value was 0.50622, which had 45.2% sensitivity and 96.6% specificity. The model stratified patients with low-risk GTN into low (< 10%), intermediate (10-90%) and high (> 90%) probability of MTX resistance, based on the threshold values of -1.59544 and 0.10046. The model had an accuracy of 74.4% (95% CI, 64.5-82.3%) in the cross-validation and 72.7% (95% CI, 55.8-84.9%) in the internal validation.
The Doppler-based predictive model, combining a non-invasive marker of tumor vascularity with the FIGO scoring system, can differentiate cases with low from those with high probability of developing MTX resistance and therefore has the potential to guide treatment options in patients with low-risk GTN and myometrial invasion. © 2020 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Long non-coding RNAs (lncRNAs) have been verified to participate in the tumorigenesis of multiple cancers. Nevertheless, the deepgoing role molecular mechanisms of lncRNAs on osteosarcoma chemoresistance remain unclear. In present study, we investigate the function of lncRNA LUCAT1 on osteosarcoma methotrexate (MTX) resistant phenotype and discover the potential regulatory mechanism. Results showed that LUCAT1 was up-regulated in MTX-resistant cells (MG63/MTX, HOS/MTX) compared to that in parental cells. LncRNA LUCAT1 and ABCB1 protein expression levels were both up-regulated when induced by different concentration of methotrexate. In vitro and vivo, LUCAT1 knockdown decreased the expression levels drug resistance related genes (MDR1, MRP5, LRP1), proliferation, invasion and tumor growth of osteosarcoma cells. Bioinformatics tools and luciferase assay reveled that miR-200c both targeted the 3\'-UTR of LUCAT1 and ABCB1 mRNA, suggesting the modulation of LUCAT1 on ABCB1 through sponging miR-200c. Rescue experiments confirmed the combined role of LUCAT1, miR-200c and ABCB1 on osteosarcoma proliferation, invasion and methotrexate resistance. Overall, results indicate the vital role of LUCAT1 in the methotrexate resistance regulation through miR-200c/ABCB1 pathway, providing a novel insight and treatment strategy for osteosarcoma drug resistance.