Knockdown of CD44 inhibits proliferation, migration and invasion of osteosarcoma cells accompanied by downregulation of cathepsin S.

BACKGROUND: Osteosarcoma (OS) is a malignant bone tumour of mesenchymal origin. These tumours are characterised by rich vascularisation, therefore promoting rapid proliferation and facilitating metastasis. CD44 has been reported to be involved in OS, but its role and molecular mechanisms in the pathogenesis of the disease are not fully determined. METHODS: In this study, we investigated the antitumor effect of CD44 on the development of OS and further explored the molecular mechanisms. The expression of CD44, cathepsin S and MMP-9 was detected by Western blot (WB) and reverse transcription-polymerase chain reaction (RT-qPCR) in different cell lines (MG63, U2OS OS and hFOB 1.19). To elucidate the role of CD44 in OS, MG63 and U2OS cells were treated with small interference RNA (siRNA) to knock down CD44, and the knockdown efficiency was validated with GFP and RT-qPCR. Furthermore, cell proliferation was assayed using Cell Counting Kit­8 (CCK-8) and colony formation assays, and cell migration and invasion were assayed by transwell and wound-healing assays. RESULTS: We found that CD44 expression in the MG63 and U2OS OS cell lines was markedly increased compared to that of the human osteoblast hFOB 1.19 cell line. Knockdown of CD44 inhibited proliferation, migration and invasion of MG63 and U2OS cells. Cathepsin S expression in the MG63 and U2OS OS cell lines was increased compared to that of the human osteoblast hFOB 1.19 cell line. When CD44 was knocked down, its expression level went down. CONCLUSION: Taken together, our data reinforced the evidence that CD44 knockdown inhibited cell proliferation, migration and invasion of OS cells accompanied by altered expression of cathepsin S. These findings offer new clues for OS development and progression, suggesting CD44 as a potential therapeutic target for OS.

Immune-related lncRNA pairs as novel signature to predict prognosis and immune landscape in melanoma patients.

ABSTRACT: To investigate immune-related long non-coding RNA (irlncRNA) signatures for predicting survival and the immune landscape in melanoma patients.We retrieved gene expression files from The Cancer Genome Atlas and the Genotype-Tissue Expression database and extracted all the long non-coding RNAs from the original data. Then, we selected immune-related long non-coding RNAs (irlncRNAs) using co-expression networks and screened differentially expressed irlncRNAs (DEirlncRNAs) to form pairs. We also performed univariate analysis and Least absolute shrinkage and selection operator (LASSO) penalized regression analysis to identify prognostic DEirlncRNA pairs, constructed receiver operating characteristic curves, compared the areas under the curves, and calculated the optimal cut-off point to divide patients into high-risk and low-risk groups. Finally, we performed multivariate Cox regression analysis, Kaplan-Meier (K-M) survival analysis, clinical correlation analysis, and investigated correlations with tumor-infiltrating immune cells, chemotherapeutic effectiveness, and immunogene biomarkers.A total of 297 DEirlncRNAs were identified, of which 16 DEirlncRNA pairs were associated with prognosis in melanoma. After grouping patients by the optimal cut-off value, we could better distinguish melanoma patients with different survival outcomes, clinical characteristics, tumor immune status changes, chemotherapeutic drug sensitivity, and specific immunogene biomarkers.The DEirlncRNA pairs showed potential as novel biomarkers to predict the prognosis of melanoma patients. Furthermore, these DEirlncRNA pairs could be used to evaluate treatment efficacy in the future.

m6A regulator-mediated methylation modification patterns and tumor immune microenvironment in sarcoma.

BACKGROUND: Studies have shown that the RNA N6-methyladenosine (m6A) modification patterns are extensively involved in the development of multiple tumors. However, the association between the m6A regulator expression patterns and the sarcoma tumor immune microenvironment (TIME) remains unclear. METHODS: We systematically evaluated the m6A regulator expression patterns in patients with sarcoma based on known 23 m6A regulators. Different m6A regulator expression patterns were analyzed using gene set variation analysis and a single-sample gene set enrichment analysis algorithm. According to the results of consensus clustering, we classified the patients into four different clusters. Next, we subjected the four clusters to differential genetic analysis and established m6A-related differentially expressed genes (DEGs). We then calculated the m6A-related DEGs score and constructed the m6A-related gene signature, named m6A score. Finally, the 259 sarcoma samples were divided into high- and low-m6A score groups. We further evaluated the TIME landscape between the high- and low-m6A score groups. RESULTS: We identified four different m6A modification clusters and found that each cluster had unique metabolic and immunological characteristics. Based on the 19 prognosis-related DEGs, we calculated the principal component analysis scores for each patient with sarcoma and classified them into high- and low-m6A score groups. CONCLUSIONS: The m6A regulator expression patterns and complexity of the sarcoma TIME landscape are closely related to each other. Systematic evaluation of m6A regulator expression patterns and m6A scores in patients with sarcoma will enhance our understanding of TIME characteristics.

Ultrasensitive electrochemiluminescence sensor based on perovskite quantum dots coated with molecularly imprinted polymer for prometryn determination.

A highly effective molecularly imprinted electrochemiluminescence sensor was constructed for prometryn determination in environmental and biological samples by using perovskite quantum dots coated with a molecularly imprinted silica layer (MIP/CsPbBr3-QDs) as the recognition and response element. MIP/CsPbBr3-QDs were immobilized on a glassy carbon electrode (GCE) through electropolymerization, and the electrochemiluminescence (ECL) response of MIP/CsPbBr3-QDs could be motivated under the condition of H2O2 as co-reactant. ECL signal was selectively quenched with prometryn by hindering electron transfer and directly proportional to the logarithm of prometryn concentration (0.10-500.0 µg/L) with a correlation coefficient of 0.9960. Limits of detection in fish and seawater samples were 0.010 µg/kg and 0.050 µg/L, respectively. Excellent recoveries of 88.0%-106.0% were acquired for fish and seawater samples with a relative standard deviation below 4.2%. The constructed MIECL sensor based on MIP/CsPbBr3-QDs showed good stability, accuracy, and precision for sensitive detection of prometryn in aquaculture products and environmental samples.

Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis.

BACKGROUND: This study sought to assess the prognostic factors for leiomyosarcoma (LMS) patients with lung metastasis and construct web-based nomograms to predict overall survival (OS) and cancer-specific survival (CSS). METHOD: Patients diagnosed with LMS combined with lung metastasis between 2010 and 2016 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into a training set and a testing set. The X-tile analysis provides the best age and tumor size cut-off point, and changes continuous variables into categorical variables. The independent prognostic factors were determined by Cox regression analysis, and 2 nomograms were established. Receiver operating characteristic curves and calibration curves were used to evaluate the nomograms. Based on the nomograms, 2 web-based nomograms were established. RESULTS: Two hundred and twenty-eight cases were included in the OS nomogram construction, and were randomly divided into a training set (n=160) and a validation set (n=68). Age, T stage, bone metastasis, surgery, chemotherapy, marital status, tumor size, and tumor site were found to be correlated with OS. One hundred and eighty-three cases were enrolled in the CSS nomogram construction, and randomly divided into a training set (n=129) and a validation set (n=54). Age, bone metastasis, surgery, chemotherapy, tumor size, and tumor site were found to be correlated with CSS. Two nomograms were established to predict OS and CSS. In the training set, the areas under the curve of the nomogram for predicting 1-, 2-, and 3-year OS were 0.783, 0.830, and 0.832, respectively, and those for predicting 1-, 2-, and 3-year CSS were 0.889, 0.777, and 0.884, respectively. Two web-based nomograms were established to predict OS (https://wenn23.shinyapps.io/lmslmosapp/), and CSS (https://wenn23.shinyapps.io/lmslmcssapp/). CONCLUSION: The developed web-based nomogram is a useful tool for accurately analyzing the prognosis of LMS patients with lung metastasis, and could help clinical doctors to make personalized clinical decisions.