Identification of a lactate metabolism-related lncRNAs signature for predicting the prognosis in patients with kidney renal clear cell carcinoma.

Background: Lactate metabolism-related (LMR) long noncoding RNAs (lncRNAs) play significant roles in various cancers, but their impact on kidney renal clear cell carcinoma (KIRC) remains unclear. This study aimed to explore the value of LMR lncRNA and develop a risk model for KIRC. Methods: Data on KIRC patients were downloaded from The Cancer Genome Atlas (TCGA) database. LMR lncRNAs were identified by co-expression, univariate and multivariate analyses, and least absolute shrinkage selection operator (LASSO) regression analysis. Subsequently, a prognostic signature was constructed and its accuracy was verified. To predict the prognosis of KIRC effectively, we established a nomogram based on this information. Enrichment analysis, tumor mutational burden (TMB) analysis, immune status and the therapeutic sensitivities of KIRC patients were also investigated. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect the expression of lncRNAs. Results: We constructed and verified a predictive signature based on six LMR lncRNA (LINC00944, AC090772.3, Z83745.1, AP001267.3, AC092296.1, and AL162377.1) to assess the patient prognoses of KIRC. Survival analyses showed a more unfavorable outcome in high-risk patients (P<0.001). Enrichment analysis demonstrated that immune-related pathways were enriched in the high-risk group. Besides, patients classified by risk scores had distinguishable immune status, TMB, response to immunotherapy, and sensitivity to chemotherapy and targeted drugs. Conclusions: The LMR lncRNAs signature has significant implications for prognostic assessment and clinical treatment guidance in KIRC.

Clinical and prognostic role of sarcopenia based on masticatory muscle index on MR images in patients with extranodal natural killer/T cell lymphoma, nasal type.

Sarcopenia is known to be associated with an increased risk of adverse outcomes in a variety of malignancies, but its impact in extranodal natural killer/T cell lymphoma, nasal type (ENKTL-NT) is unknown. The aim of this study was to explore the prognostic relevance of sarcopenia defined by MRI-based masticatory muscle index in ENKTL-NT patients. A total of 112 patients with newly diagnosed ENKTL-NT who underwent cranial magnetic resonance imaging (MRI) were enrolled. The masticatory skeletal muscle index (M-SMI) was measured based on T2-weighted MR images and sarcopenia was defined by M-SMI<5.5 cm2/ m2. The median M-SMI was 5.47 (4.91-5.96) cm2/m2; 58 were identified with sarcopenia in this cohort. On multivariate analyses, sarcopenia was the only independently risk factor predicting overall survival (HR, 4.590; 95% CI, 1.657-12.715; p = 0.003), progression-free survival (HR, 3.048; 95% CI, 1.515-6.130; p = 0.002), and treatment response (HR, 0.112; 95% CI, 0.042-0.301; p < 0.001). In addition, we found that integrating sarcopenia into prognostic indices could improve the discriminative power of the corresponding original model. Stratification analysis showed that sarcopenia was able to further identify survival differences in patients that could not be distinguished by prognostic models. In summary, our study suggests that sarcopenia defined by MRI-based M-SMI represents a new and routinely applicable prognostic indicator of clinical outcome or predictor of treatment response in ENKTL-NT patients, and may aid in risk stratification and treatment decisions.

Aa-Z2 triggers ROS-induced apoptosis of osteosarcoma by targeting PDK-1.

BACKGROUND: Osteosarcoma (OS) is the most frequent cancer derived from bone, and the prognosis of OS is poor. Metabolic alterations have been previously reported to contribute to the development of OS, and arsenic compounds have been suggested to exhibit strong anti-OS effects. However, few studies have described the therapeutic efficiency of arsenic compounds by targeting metabolism in OS. METHODS: Here, we presented a novel organo-arsenic compound, Aa-Z2, and its antitumour efficacy against OS both in vitro and in vivo. RESULTS: Aa-Z2 induced OS cell apoptosis, G2/M phase arrest, and autophagy through the accumulation of reactive oxygen species (ROS). Elevated ROS functioned by promoting the mitochondrial-dependent caspase cascade and attenuating the PI3K/Akt/mTOR signalling pathway. N-acetylcysteine (NAC), a kind of ROS scavenger, could reverse the effects of Aa-Z2 treatment on 143B and HOS cells. Specifically, by targeting pyruvate dehydrogenase kinase 1 (PDK-1), Aa-Z2 induced changes in mitochondrial membrane potential and alterations in glucose metabolism to accumulate ROS. Overexpression of PDK-1 could partially desensitize OS cells to Aa-Z2 treatment. Importantly, Aa-Z2 suppressed tumour growth in our xenograft osteosarcoma model. CONCLUSION: The study provides new insights into the mechanism of Aa-Z2-related metabolic alterations in OS inhibition, as well as pharmacologic evidence supporting the development of metabolism-targeting therapeutics.

Construction and validation of a prognostic model for osteosarcoma patients based on autophagy-related genes.

BACKGROUND: Osteosarcoma is the most frequent primary bone malignancy with a poor prognosis because of pulmonary metastasis. Autophagy is strongly associated with tumor metastasis, and it is valuable to construct an autophagy-related gene risk model for predicting the prognosis of osteosarcoma. METHODS: We obtained ARGs from the Human Autophagy Database and RNA-sequencing data of osteosarcoma patients from the Gene Expression Omnibus (GEO) database. Subsequently, univariate and multivariate cox regression analyses were performed to construct a three-gene prognostic model and its accuracy was further confirmed in the Therapeutic Applications Research to Generate Effective Treatments (TARGET) database. Afterward, we detected the expression levels and effects on osteosarcoma cells metastasis of MYC and MBTPS2, which were involved in the model. RESULTS: In both training and verification cohorts, patients with lower risk scores had longer OS, and the model was identified as an independent prognostic factor in osteosarcoma. Besides, the ROC curve demonstrated the reliability of the model. Furthermore, RT-qPCR, Western Blotting and IHC results indicated that MYC and MBTPS2 were differently expressed in osteosarcoma tissues and cell lines. MYC knockdown or MBTPS2 overexpression prevented the capacity of migration and invasion in osteosarcoma cell lines through inhibiting cellular autophagy. CONCLUSION: The risk model based on three ARGs had a strong ability to predict the prognosis of osteosarcoma patients. Our findings also suggested that MYC and MBTPS2 were two major factors regulating autophagy in osteosarcoma, and could serve as potential therapeutic targets for osteosarcoma.

The effect of (H2O)n (n = 1-3) clusters on the reaction of HONO with HCl: a mechanistic and kinetic study.

The reaction between HONO and HCl is a possible pathway for the generation of ClNO, which is prone to photolyze, produce chlorine radicals, and accelerate the oxidation of tropospheric VOCs. Current experimental and theoretical studies have significant differences in rate constants under similar conditions. This study aims to examine the reasons for this difference. In this study, the effects of a single water molecule, water dimer, water trimer, excess HCl and excess HONO on the reaction mechanism of HONO + HCl were studied at the CCSD(T)/aug-cc-pVTZ//M06-2X/6-311+G(2df,2p) level and the rate constants of each reaction channel were calculated. Our results showed that the reaction potential barrier of HONO with HCl was the lowest only when the water dimer was present, and the reaction rate constants were close to the experimental results, and both the cis-HONO⋯(H2O)2 + HCl and the trans-HONO⋯(H2O)2 + HCl reaction paths are likely to occur. We think that the reason for the inconsistency between experimental and theoretical results is that the water dimer is involved in the reaction in experiments.

The Predictive Value of Tumor Mutation Burden on Clinical Efficacy of Immune Checkpoint Inhibitors in Melanoma: A Systematic Review and Meta-Analysis.

Background: Tumor mutational burden (TMB) is a genomic biomarker that can predict favorable responses to immune checkpoint inhibitors (ICIs). Although we have better understanding of TMB in cancer immunity and cancer immunotherapy, the relationship between TMB and the clinical efficacy of ICIs remains unknown in the treatment of melanoma patients. Here, we conduct a systematic review and meta-analysis to evaluate the predictive value of TMB on the efficacy of ICIs in patients with melanoma. Methods: We systematically collected data from PubMed, Embase, Cochrane Library, CNKI, China Biomedical Database (CBM), and Wanfang Database. The end date was set to 26 June 2021. We included retrospective studies or clinical trials of ICIs that reported hazard ratios (HRs) for overall survival and/or progression-free survival according to TMB. Data for 1,493 patients from 15 studies were included. In addition, pooled effect size, heterogeneity analysis, sensitivity analysis, publication bias detection, and subgroup analysis were performed based on the included data. Results: Patients with high TMB showed significantly improved OS (HR = 0.49, 95% CI: 0.33, 0.73; p = 0.001) and PFS (HR = 0.47, 95% CI: 0.33, 0.68; p < 0.001) compared with patients with low TMB. This association was very good in patients treated with monotherapy, that is, anti-CTLA-4 or anti-PD-(L)-1 inhibitors, but not for the patients treated with a combination of the two drugs. The subgroup analysis results showed that heterogeneity was substantial in the targeted next-generation sequencing (NGS) group. Publication bias was detected, and the results were visualized using the funnel chart. And sensitivity analysis and trim-and-fill method analysis showed that our results were stable and reliable. Conclusion: High TMB is associated with improved OS and PFS in melanoma patients treated with mono-drug ICIs. TMB determined by NGS should be standardized to eliminate heterogeneity. Therefore, the role of TMB in identifying melanoma patients who may benefit from ICI should be further determined in more randomized controlled trials in the future.

Symmetric Graphene Dielectric Nanowaveguides as Ultra-Compact Photonic Structures.

A symmetric graphene plasmon waveguide (SGPWG) is proposed here to achieve excellent subwavelength waveguiding performance of mid-infrared waves. The modal properties of the fundamental graphene plasmon mode are investigated by use of the finite element method. Due to the naturally rounded tips, the plasmon mode in SGPWG could achieve a normalized mode field area of ~10-5 (or less) and a figure of merit over 400 by tuning the key geometric structure parameters and the chemical potential of graphene. In addition, results show that the modal performance of SGPWG seems to improve over its circular counterparts. Besides the modal properties, crosstalk analysis indicates that the proposed waveguide exhibits extremely low crosstalk, even at a separation distance of 64 nm. Due to these excellent characteristics, the proposed waveguide has promising applications in ultra-compact integrated photonic components and other intriguing nanoscale devices.