Dysregulation of LINC00324 promotes poor prognosis in patients with glioma.

BACKGROUND: LINC00324 is a long-stranded non-coding RNA, which is aberrantly expressed in various cancers and is associated with poor prognosis and clinical features. It involves multiple oncogenic molecular pathways affecting cell proliferation, migration, invasion, and apoptosis. However, the expression, function, and mechanism of LINC00324 in glioma have not been reported. MATERIAL AND METHODS: We assessed the expression of LINC00324 of LINC00324 in glioma patients based on data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) to identify pathways involved in LINC00324-related glioma pathogenesis. RESULTS: Based on our findings, we observed differential expression of LINC00324 between tumor and normal tissues in glioma patients. Our analysis of overall survival (OS) and disease-specific survival (DSS) indicated that glioma patients with high LINC00324 expression had a poorer prognosis compared to those with low LINC00324 expression. By integrating clinical data and genetic signatures from TCGA patients, we developed a nomogram to predict OS and DSS in glioma patients. Gene set enrichment analysis (GSEA) revealed that several pathways, including JAK/STAT3 signaling, epithelial-mesenchymal transition, STAT5 signaling, NF-κB activation, and apoptosis, were differentially enriched in glioma samples with high LINC00324 expression. Furthermore, we observed significant correlations between LINC00324 expression, immune infiltration levels, and expression of immune checkpoint-related genes (HAVCR2: r = 0.627, P = 1.54e-77; CD40: r = 0.604, P = 1.36e-70; ITGB2: r = 0.612, P = 6.33e-7; CX3CL1: r = -0.307, P = 9.24e-17). These findings highlight the potential significance of LINC00324 in glioma progression and suggest avenues for further research and potential therapeutic targets. CONCLUSION: Indeed, our results confirm that the LINC00324 signature holds promise as a prognostic predictor in glioma patients. This finding opens up new possibilities for understanding the disease and may offer valuable insights for the development of targeted therapies.

Association Between Diverse Cell Death Patterns Related Gene Signature and Prognosis, Drug Sensitivity, and Immune Microenvironment in Glioblastoma.

Glioblastoma (GBM) is the most invasive type of glioma and is difficult to treat. Diverse programmed cell death (PCD) patterns have a significant association with tumor initiation and progression. A novel prognostic model based on PCD genes may serve as an effective tool to predict the prognosis of GBM. The study incorporated 11 PCD patterns, namely apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis, to develop the model. To construct and validate the model, both bulk and single-cell transcriptome data, along with corresponding clinical data from GBM cases, were obtained from the TCGA-GBM, REMBRANDT, CGGA, and GSE162631 datasets. A cell death-related signature containing 14 genes was constructed with the TCGA-GBM cohort and validated in the REMBRANDT and CGGA datasets. GBM patients with a higher cell death index (CDI) were significantly associated with poorer survival outcomes. Two separate clusters associated with clinical outcomes emerged from unsupervised analysis. A multivariate Cox regression analysis was conducted to examine the association of CDI with clinical characteristics, and a prognostic nomogram was developed. Drug sensitivity analysis revealed high-CDI GBM patients might be resistant to carmustine while sensitive to 5-fluorouracil. Less abundance of natural killer cells was found in GBM cases with high CDI and bulk transcriptome data. A cell death-related prognostic model that could predict the prognosis of GBM patients with good performance was established, which could discriminate between the prognosis and drug sensitivity of GBM.

Tumor Vascular Destruction and cGAS-STING Activation Induced by Single Drug-Loaded Nano-Micelles for Multiple Synergistic Therapies of Cancer.

Cancer and its metastasis/recurrence still threaten human health, despite various advanced treatments being employed. It is of great significance to develop simple drug formulations to enhance the efficacy and synergistic integration of various monotherapies. Herein, DMXAA, a vasodestructive agent with cGAS-STING stimulation capacity, is integrated with polyethylene glycol grafted poly (lactic-co-glycolic) acid co-polymer (PLGA-PEG), obtaining PLGA-PEG/DMXAA (PPD) nanoparticles to induce the tumor-specific vascular destruction for multiple synergistic therapies of cancer. PPD could induce the formation of blood clots in the tumor after intravenous injection, which subsequently mediate photothermal therapy and further promote the release of oxygen for enhanced radiotherapy. Meanwhile, the enhanced vascular injury can induce perfect starvation therapy of tumor. More importantly, PPD-mediated therapies could trigger potent systemic anti-tumor immunity via inducing the immunogenic death of tumor cells and activating the cGAS-STING pathway. Together with anti-PD-L1, PPD-mediated therapies could not only remove the primary tumors, but also effectively eliminate the distant tumors, metastasis, and recurrence. Therefore, the modulation of tumor composition induced by a single drug-loaded nano-micelle could be utilized to enhance the therapeutic effect of multiple treatments for synergistic and systemic antitumor response, providing a practical strategy for cancer therapy.

SARS-CoV-2 Pattern Provides a New Scoring System and Predicts the Prognosis and Immune Therapeutic Response in Glioma.

OBJECTIVE: Glioma is the most common primary malignancy of the adult central nervous system (CNS), with a poor prognosis and no effective prognostic signature. Since late 2019, the world has been affected by the rapid spread of SARS-CoV-2 infection. Research on SARS-CoV-2 is flourishing; however, its potential mechanistic association with glioma has rarely been reported. The aim of this study was to investigate the potential correlation of SARS-CoV-2-related genes with the occurrence, progression, prognosis, and immunotherapy of gliomas. METHODS: SARS-CoV-2-related genes were obtained from the human protein atlas (HPA), while transcriptional data and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Glioma samples were collected from surgeries with the knowledge of patients. Differentially expressed genes were then identified and screened, and seven SARS-CoV-2 related genes were generated by LASSO regression analysis and uni/multi-variate COX analysis. A prognostic SARS-CoV-2-related gene signature (SCRGS) was then constructed based on these seven genes and validated in the TCGA validation cohort and CGGA cohort. Next, a nomogram was established by combining critical clinicopathological data. The correlation between SCRGS and glioma related biological processes was clarified by Gene set enrichment analysis (GSEA). In addition, immune infiltration and immune score, as well as immune checkpoint expression and immune escape, were further analyzed to assess the role of SCRGS in glioma-associated immune landscape and the responsiveness of immunotherapy. Finally, the reliability of SCRGS was verified by quantitative real-time polymerase chain reaction (qRT-PCR) on glioma samples. RESULTS: The prognostic SCRGS contained seven genes, REEP6, CEP112, LARP4B, CWC27, GOLGA2, ATP6AP1, and ERO1B. Patients were divided into high- and low-risk groups according to the median SARS-CoV-2 Index. Overall survival was significantly worse in the high-risk group than in the low-risk group. COX analysis and receiver operating characteristic (ROC) curves demonstrated excellent predictive power for SCRGS for glioma prognosis. In addition, GSEA, immune infiltration, and immune scores indicated that SCRGS could potentially predict the tumor microenvironment, immune infiltration, and immune response in glioma patients. CONCLUSIONS: The SCRGS established here can effectively predict the prognosis of glioma patients and provide a potential direction for immunotherapy.

Construction and Validation of a Necroptosis-Related lncRNA Signature in Prognosis and Immune Microenvironment for Glioma.

Background: Glioma is the most common primary brain tumor, representing approximately 80.8% of malignant tumors. Necroptosis triggers and enhances antitumor immunity and is expected to be a new target for tumor immunotherapy. The effectiveness of necroptosis-related lncRNAs as potential therapeutic targets for glioma has not been elucidated. Methods: We acquired RNA-seq data sets from LGG and GBM samples, and the corresponding clinical characteristic information is from TCGA. Normal brain tissue data is from GTEX. Based on TCGA and GTEx, we used univariate Cox regression to sort out survival-related lncRNAs. Lasso regression models were then built. Then, we performed a separate Kaplan-Meier analysis of the lncRNAs used for modeling. We validated different risk groups via OS, DFS, enrichment analysis, comprehensive immune analysis, and drug sensitivity. Results: We constructed a 12 prognostic lncRNAs model after bioinformatic analysis. Subsequently, the risk score of every glioma patient was calculated based on correlation coefficients and expression levels, and the patients were split into low- and high-risk groups according to the median value of the risk score. A nomogram was established for every glioma patient to predict prognosis. Besides, we found significant differences in OS, DFS, immune infiltration and checkpoints, and immune therapy between different risk subgroups. Conclusion: Predictive models of 12 necroptosis-related lncRNAs can facilitate the assessment of the prognosis and molecular characteristics of glioma patients and improve treatment modalities.

Phytochemicals, Nutrition, Metabolism, Bioavailability, and Health Benefits in Lettuce-A Comprehensive Review.

Lettuce is one of the most famous leafy vegetables worldwide with lots of applications from food to other specific uses. There are different types in the lettuce group for consumers to choose from. Additionally, lettuce is an excellent source of bioactive compounds such as polyphenols, carotenoids, and chlorophyll with related health benefits. At the same time, nutrient composition and antioxidant compounds are different between lettuce varieties, especially for green and red lettuce types. The benefit of lettuce consumption depends on its composition, particularly antioxidants, which can function as nutrients. The health benefits rely on their biochemical effect when reaching the bloodstream. Some components can be released from the food matrix and altered in the digestive system. Indeed, the bioaccessibility of lettuce is measuring the quantity of these compounds released from the food matrix during digestion, which is important for health-promoting features. Extraction of bioactive compounds is one of the new trends observed in lettuce and is necessarily used for several application fields. Therefore, this review aims to demonstrate the nutritional value of lettuce and its pharmacological properties. Due to their bioaccessibility and bioavailability, the consumer will be able to comprehensively understand choosing a healthier lettuce diet. The common utilization pattern of lettuce extracted nutrients will also be summarized for further direction.

Photo-Driven Delivery of 125I-Labeled Nanomicelles for Nucleus-Targeted Internal Conversion Electron-Based Cancer Therapy.

As a kind of high linear energy transfer (LET) radiation, internal conversion electrons are emitted from some radionuclides, such as 125I, triggering severe DNA damage to tumor cells when transported into the nucleus. Herein, we develop a curcumin-loaded nanomicelle composed of a photosensitizer chlorin e6 (Ce6) and amphiphilic poly(ethylene glycol) (poly(maleic anhydride-alt-1-octadecene)-poly(ethylene glycol) (C18-PMH-PEG)) to deliver 125I into the nucleus under 660 nm laser irradiation, leading to the optimized imaging-guided internal conversion electron therapy of cancer. Ce6-containing nanomicelles (Ce6-C18-PEG) self-assemble with nucleus-targeted curcumin (Cur), obtaining Ce6-C18-PEG/Cur nanoparticles. After labeling Cur with 125I, Ce6-C18-PEG/Cur enables single-photon emission computed tomography and fluorescence imaging of the tumor, serving as a guide for follow-up laser irradiation. Notably, the 660 nm laser-triggered photodynamic reaction of Ce6 optimizes the delivery of Ce6-C18-PEG/125I-Cur at various stages, including tumor accumulation, cellular uptake, and lysosome escape, causing plenty of 125I-Cur to enter the nucleus. By this strategy, Ce6-C18-PEG/125I-Cur showed optimal antitumor efficacy and high biosafety in mice treated with local 660 nm laser irradiation using efficient energy deposition of internally converted electrons over short distances. Therefore, our work provides a novel strategy to optimize 125I delivery for tumor treatment.

Quantitative proteomic analysis of glycosylated proteins enriched from urine samples with magnetic ConA nanoparticles identifies potential biomarkers for small cell lung cancer.

Lung cancer has high morbidity and mortality and small cell lung cancer (SCLC) is a highly invasive malignant tumor with a very unfavorable survival rate. Early diagnosis and treatment can result in better prognosis for the SCLC patients but current diagnostic methods are either invasive or incapable for large-scale screen. Therefore, discovering biomarkers for early diagnosis of SCLC is of importance. In this work, we covalently coupled Concanavalin A (ConA) to functionalized magnetic nanoparticles to obtain magnetic ConA-nanoparticles (ConA-NPs) for the enrichment of glycosylated proteins. We then purified glycosylated proteins in 36 urine samples from 9 healthy controls, 9 SCLC patients, 9 lung adenocarcinoma (LUAD) patients, and 9 lung squamous cell carcinoma (LUSC) patients. The purified glycosylated proteins were digested and analyzed by LC-MS/MS for identification and quantification. Among the 398 identified proteins, 20, 15, and 1 glycosylated protein(s), respectively, were upregulated in the urine of SCLC, LUAD, and LUSC patients. Immunoblotting experiments further demonstrated that cathepsin C and transferrin were significantly upregulated in the ConA-NP purified urine of SCLC patients. This work suggests that glycosylated cathepsin C and transferrin might be able to serve as potential biomarkers for the noninvasive diagnosis of SCLC patients.

Emerging strategies based on nanomaterials for ionizing radiation-optimized drug treatment of cancer.

Drug-radiotherapy is a common and effective combinational treatment for cancer. This study aimed to explore the ionizing radiation-optimized drug treatment based on nanomaterials so as to improve the synergistic efficacy of drug-radiotherapy against cancer and limit the adverse effect on healthy organs. In this review, these emerging strategies were divided into four parts. First, the delivery of the drug-loaded nanoparticles was optimized owing to the strengthened passive targeting process, active targeting process, and cell targeting process of nanoparticles after ionizing radiation exposure. Second, nanomaterials were designed to respond to the ionizing radiation, thus leading to the release of the loading drugs controllably. Third, radiation-activated pro-drugs were loaded onto nanoparticles for radiation-triggered drug therapy. In particular, nontoxic nanoparticles with radiosensitization capability and innocuous radio-dynamic contrast agents can be considered as radiation-activated drugs, which were discussed in this review. Fourth, according to the various synergetic mechanisms, radiotherapy could improve the drug response of cancer, obtaining optimized drug-radiotherapy. Finally, relative suggestions were provided to further optimize these aforementioned strategies. Therefore, a novel topic was selected and the emerging strategies in this region were discussed, aiming to stimulate the inspiration for the development of ionizing radiation-optimized drug treatment based on nanomaterials.

Diagnostic Radionuclides Labeled on Biomimetic Nanoparticles for Enhanced Follow-Up Photothermal Therapy of Cancer.

Imaging-guided local therapy is the most effective strategy to treat primary cancers in patients. However, the local therapeutic effect should be further improved under the premise of absence of induction of additional side effects. It would be meaningful to analyze the potential assistance of nuclear imaging to the follow-up treatments. In this study,cancer-targeted copper sulfide nanoparticles with 99m Tc labeling (99m Tc-M-CuS-PEG) are prepared using-cancer cell membranes as a synthesis reactor and applied for the potential single-photon emission computed tomography/photoacoustic imaging-guided and 99m Tc-amplified photothermal therapy of cancer. Owing to the homologous targeting capability of the cancer cell membrane, M-CuS-PEG selectively accumulates in homologous tumor sites. After labeling with 99m Tc, M-CuS-PEG with a high near-infrared light absorbance can realize bimodal imaging-guided photothermal therapy of cancer. Furthermore, the labeled 99m Tc significantly enhances the cell uptake of M-CuS-PEG by inducing G2/M arrest of the cell cycle, further improving the photothermal antitumor effect, which is positively correlated with endocytosis of the photothermal conversion reagent. Therefore, a novel cancer-targeted theranostic nanoplatform is developed and it is revealed that the labeled 99m Tc can not only guide but also amplify the subsequent therapy of cancer, providing a conceptual strategy for cancer theranostics with a high biosafety.

Validation and comparison of three newly-released Thyroid Imaging Reporting and Data Systems for cancer risk determination.

PURPOSE: To validate and compare diagnostic value of three newly-released Thyroid Imaging Reporting and Data Systems (TIRADS) for cancer risk determination. METHODS: Total 2031 patients with 2465 thyroid nodules were recruited for this study. Ultrasound (US) images were categorized based on three TIRADS editions established by Korean Society of Thyroid Radiology (KSThR), European Thyroid Association (ETA) and American College of Radiology (ACR). ROC curves were established to compare diagnostic value. RESULTS: Total 1460 benign and 1005 malignant nodules were enrolled. The malignancy rates of each category in KSThR-TIRADS were 2.8%, 5.1%, 33.7% and 79.6%, respectively. For European-TIRADS, 0, 3.1, 22.8, and 73.5% of nodules categorized as 2 to 5 were malignant. Distribution of carcinomas among ACR-TIRADS categories was 0%, 2.3%, 7.5%, 40.1% and 81.4%, respectively. In terms of diagnostic value, KSThR-TIRADS had highest AUC (0.855) and specificity (87.4%), while lowest (71.4%) sensitivity. ACR-TIRADS showed best sensitivity (96.6%) with lowest specificity (52.9%) and the AUC (0.846) was slightly lower than KSThR-TIRADS. Total 56.1, 45.4, and 37.4% fine-needle aspiration biopsy (FNAB) were recommended by KSThR, ETA and ACR, revealing 42.8%, 44.5% and 53.6% malignant lesions, respectively. The rate of unnecessary FNAB was lowest with the ACR (17.3%), followed by ETA (25.2%) and KSThR (32.1%). CONCLUSION: All these US models showed great value in predicting thyroid malignancy. Among them, KSThR-TIRADS showed the most effective diagnostic performance in specificity, while ACR-TIRADS yielded best sensitivity. As for FNAB criteria, ACR-TIRADS showed the lowest rate of unnecessary FNAB and highest rate of malignancy in FNAB.

miR-146a rs2910164 Polymorphism and Risk of Papillary Thyroid Carcinoma: A Meta-Analysis.

Aims: The presence of single nucleotide polymorphisms contributes to genetic diversity, and some are associated with cancer progression. Recent studies concerning the relationship between polymorphisms in miR-146a and the risk of papillary thyroid carcinoma (PTC) have produced conflicting results. Here, a meta-analysis of previous studies was performed to evaluate this relationship. Materials and Methods: Electronic databases, including PubMed, China National Knowledge Infrastructure, Cochrane Library, Embase, and Web of Science, were searched for studies concerning miR-146a and PTC published between January 1, 2000 and January 1, 2018. Fixed/random-effects models were used to calculate the pooled odds ratios (ORs) estimated in each study according to the level of heterogeneity. Results: Eight studies involving 3993 cases and 9919 controls were assessed. Pooled results showed no association between the miR-146a rs2910164 polymorphism and PTC (OR = 1.001, 95% confidence interval [CI] 0.893-1.121). Subgroup analysis showed that the GG/GC genotype did not significantly increase PTC risk versus CC among Asians (OR = 0.939; 95% CI 0.828-1.066). Similarly, the combination of the GG and GC genotypes did not increase the risk of PTC for Caucasians (OR = 1.571, 95% CI 0.949-2.601). Conclusions: The results of our meta-analysis indicated that the miR-146a rs2910164 variant genotype has no effect on susceptibility to PTC.

Thyroid nodule sizes influence the diagnostic performance of TIRADS and ultrasound patterns of 2015 ATA guidelines: a multicenter retrospective study.

To evaluate the impact of thyroid nodule sizes on the diagnostic performance of thyroid imaging reporting and data system (TIRADS) and ultrasound patterns of 2015 American Thyroid Association (ATA) guidelines. Total 734 patients with 962 thyroid nodules were recruited in this retrospective study. All nodules were divided into three groups according to the maximal diameter (d < 10 mm, d = 10-20 mm and d > 20 mm). The ultrasound images were categorized based on TIRADS and ATA ultrasound patterns, respectively. A total of 931 (96.8%) and 906 (94.2%) patterns met the criteria for TIRADS and ATA ultrasound patterns. The AUC (0.849) and sensitivity (85.3%) of TIRADS were highest in d = 10-20 mm group. However, ATA had highest AUC (0.839) and specificity (89.8%) in d > 20 mm group. ATA ultrasound patterns had higher specificity (P = 0.04), while TI-RADS had higher sensitivity (P = 0.02). In nodules d > 20 mm, the specificity of ATA patterns was higher than TIRADS (P = 0.003). Our results indicated that nodule sizes may influence the diagnostic performance of TIRADS and ATA ultrasound patterns. The ATA patterns may yield higher specificity than TIRADS, especially in nodules larger than 20 mm.