Bioinformatics Identification and Experimental Validation of a Prognostic Model for the Survival of Lung Squamous Cell Carcinoma Patients.

Lung squamous cell carcinoma (LUSC) kills more than four million people yearly. Creating more trustworthy tumor molecular markers for LUSC early detection, diagnosis, prognosis, and customized treatment is essential. Cuproptosis, a novel form of cell death, opened up a new field of study for searching for trustworthy tumor indicators. Our goal was to build a risk model to assess drug sensitivity, monitor immune function, and predict prognosis in LUSC patients. The 19 cuproptosis-related genes were found in the literature, and patient genomic and clinical information was collected using the Cancer Genomic Atlas (TCGA) database. The LUSC patients were grouped using unsupervised clustering techniques, and 7626 differentially expressed genes were identified. Using univariate COX analysis, LASSO regression analysis, and multivariate COX analysis, a prognostic model for LUSC patients was developed. The tumor immune escape was evaluated using the Tumor Immune Dysfunction and Exclusion (TIDE) method. The R packages 'pRRophetic,' 'ggpubr,' and 'ggplot2' were utilized to examine drug sensitivity. For modeling, a 6-cuproptosis-based gene signature was found. Patients with high-risk LUSC had significantly worse survival rates than those with low-risk conditions. The possibility of tumor immunological escape was increased in patients with higher risk scores due to more immune cell inactivation. For patients with high-risk LUSC, we discovered seven potent potential drugs (AZD6482, CHIR.99021, CMK, Embelin, FTI.277, Imatinib, and Pazopanib). In conclusion, the cuproptosis-based genes predictive risk model can be utilized to predict outcomes, track immune function, and evaluate medication sensitivity in LUSC patients.

MiR-1976/NCAPH/P65 axis inhibits the malignant phenotypes of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a malignancy with an abysmal survival rate. High metastasis is the leading cause of the low survival rate of LUAD. NCAPH, an oncogene, is involved in the carcinogenesis of LUAD. However, the regulation of NCAPH in LUAD remains controversial. In this work, we identified an up-regulation of NCAPH in LUAD tissues. Patients who expressed more NCAPH had shorter overall survival (OS). Furthermore, NCAPH overexpression promoted LUAD cell migration while inhibiting apoptosis. MiR-1976 and miR-133b were predicted to target NCAPH expression by searching TargetScan and linkedomics databases. Following that, we confirmed that miR-1976 suppressed NCAPH by directly targeting a 7-bp region of NCAPH 3' untranslated regions (UTR). In addition, increased expression of miR-1976 decreased the proliferation & migration and promoted apoptosis of LUAD cells, and the re-introduction of NCAPH reversed these influences. Furthermore, the xenograft and metastasis mouse models also confirmed that miR-1976 inhibited tumor growth and metastasis in vivo by targeting NCAPH. Finally, we found that MiR-1976 targeting NCAPH blocked the activation of NF-κB. In conclusion, miR-1976 inhibits NCAPH activity in LUAD and acts as a tumor suppressor. The miR-1976/NCAPH/NF-κB axis may, in the future, represent crucial diagnostic and prognostic biomarkers and promising therapeutic options.

Structural Basis of Conformational Dynamics in the PROTAC-Induced Protein Degradation.

Pronounced conformational dynamics is unveiled upon analyzing multiple crystal structures of the same proteins recruited to the same E3 ligases by PROTACs, and yet, is largely permissive for targeted protein degradation due to the intrinsic mobility of E3 assemblies creating a large ubiquitylation zone. Mathematical modelling of ternary dynamics on ubiquitylation probability confirms the experimental finding that ternary complex rigidification need not correlate with enhanced protein degradation. Salt bridges are found to prevail in the PROTAC-induced ternary complexes, and may contribute to a positive cooperativity and prolonged half-life. The analysis highlights the importance of presenting lysines close to the active site of the E2 enzyme while constraining ternary dynamics in PROTAC design to achieve high degradation efficiency.

The Science and Art of Structure-Based Virtual Screening.

Structure-based virtual screening has gained momentum again as the high attrition rate at every stage of drug discovery drives the need to explore a greater chemical space. From the Bayesian perspective, its shortcomings as a viable strategy for sustainable hit discovery are discussed, with regard to the prior hit rates of screening libraries and the performance of computational methods. Lessons are shared in selecting virtual hits for experimental validation learned from a series of eight successful campaigns, one of which impacted the discovery of a drug candidate currently in clinical trials.

Integration of Single-Cell and Bulk RNA-seq Data to Identify the Cancer-Associated Fibroblast Subtypes and Risk Model in Glioma.

Cancer-associated fibroblasts (CAFs) are an important component of the stroma. Studies showed that CAFs were pivotally in glioma progression which have long been considered a promising therapeutic target. Therefore, the identification of prognostic CAF markers might facilitate the development of novel diagnostic and therapeutic approaches. A total of 1333 glioma samples were obtained from the TCGA and CGGA datasets. The EPIC, MCP-counter, and xCell algorithms were used to evaluate the relative proportion of CAFs in glioma. CAF markers were identified by the single-cell RNA-seq datasets (GSE141383) from the Tumor Immune Single-Cell Hub database. Unsupervised consensus clustering was used to divide the glioma patients into different distinct subgroups. The least absolute shrinkage and selection operator regression model was utilized to establish a CAF-related signature (CRS). Finally, the prognostic CAF markers were further validated in clinical specimens by RT‒qPCR. Combined single-cell RNA-seq analysis and differential expression analysis of samples with high and low proportions of CAFs revealed 23 prognostic CAF markers. By using unsupervised consensus clustering, glioma patients were divided into two distinct subtypes. Subsequently, based on 18 differentially expressed prognostic CAF markers between the two CAF subtypes, we developed and validated a new CRS model (including PCOLCE, TIMP1, and CLIC1). The nomogram and calibration curves indicated that the CRS was an accurate prognostic marker for glioma. In addition, patients in the high-CRS score group had higher immune infiltration and tumor mutation burden levels. Moreover, the CRS score had the potential to predict the response to immune checkpoint blockade (ICB) therapy and chemotherapy. Finally, the expression profiles of three CAF markers were verified by RT‒qPCR. In general, our study classified glioma patients into distinct subgroups based on CAF markers, which will facilitate the development of individualized therapy. We also provided insights into the role of the CRS in predicting the response to ICB and chemotherapy in glioma patients.

Characterization of road-deposited sediment wash-off and accurate splitting of initial runoff pollution in heterogeneous urban spaces.

Particulate materials arising from road-deposited sediments (RDS) are an essential target for the control and management of surface runoff pollution. However, the heterogeneity of urban spaces hinders the identification and quantification of particulate pollution, which is challenging when formulating precise control measures. To elucidate the factors that drive particulate pollution in heterogeneous urban spaces, the accumulation of RDS on dry days and the total suspended solids during six natural rainfall events were investigated across three urban-rural spatial units (central urban, central suburban, and remote suburban). The underlying surface type (asphalt or cement roads) and particle size composition jointly determined the spatial heterogeneity in the static accumulation and dynamic output loads of RDS during rainfall. These two factors explained 59.6% and 18.9% of the spatial heterogeneity, respectively, according to principal component analysis. A novel CPSI exponential wash-off equation that incorporates particle size composition and underlying surface type was applied. It precisely described the spatial heterogeneity of RDS wash-off loads, the estimated values exhibiting event mean concentration errors of 10.8-18.2%. When coupled with the M(V) curve, this CPSI exponential wash-off equation more precisely split the initial volume of runoff: a lower total volume (17.6-38.0%) was shown to carry a higher proportion of the load (70.0-93.7%) compared to the traditional coupled exponential wash-off equation (volume: 31.6-49.0%, load: 37-90%). This study provides a new approach to characterizing RDS wash-off processes and splitting initial runoff in heterogeneous spaces.

Kinetic Modeling of PROTAC-Induced Protein Degradation.

Kinetics of the PROTAC-induced protein degradation were modelled using the equilibrium approximation, accounting for the protein recovery rate with a time lag. The simulated kinetic curves resemble what is experimentally observed, and the physical formulas of the half-maximal degradation concentration (DC50 ) were derived from them. The equations reveal that DC50 is proportional to the dissociation constant of the ternary complex (Kd ) and inversely proportional to the expression level of the E3 ligase and the effective ubiquitylation rate (kub ). The predicted relationships were rigorously confirmed by experimental evidences from a matched molecular pair analysis using a set of published PROTACs.

Monte Carlo-based optimization of glioma capsule design for enhanced brachytherapy.

The use of radiotherapy in tumor treatment has become increasingly prominent and has emerged as one of the main tools for treating malignant tumors. Current radiation therapy for glioma employs 125I seeds for brachytherapy, which cannot be combined with radiotherapy and chemotherapy. To address this limitation, this paper proposes a dual-microcavity capsule structure that integrates radiotherapy and chemotherapy. The Monte Carlo simulation method is used to simulate the structure of the dual-microcavity capsule with a 125I liquid radioactive source. Based on the simulation results, two kinds of dual-microcavity capsule structures are optimized, and the optimized dual-microcavity capsule structure is obtained. Finally, the dosimetric parameters of the two optimized dual-microcavity capsule structures are analyzed and compared with those of other 125I seeds. The optimization tests show that the improved dual-capsule dual-microcavity structure is more effective than the single-capsule dual-microcavity structure. At an activity of 5 mCi, the average absorbed dose rate is 71.2 cGy/h in the center of the optimized dual-capsule dual-microcavity structure and 45.8 cGy/h in the center of the optimized single-capsule dual-microcavity structure. Although the radial dose function and anisotropy function exhibite variations from the data of other 125I seeds, they are generally similar. The absorbed dose rate decreases exponentially with increasing distance from the center of the capsule, which can reduce the damage to the surrounding tissues and organs while increasing the dose. The capsule structure has a better irradiation effect than conventional 125I seeds and can accomplish long-term, stable, low-dose continuous irradiation to form local high-dose radiation therapy for glioma.

Kinetic modelling of the P-glycoprotein mediated efflux with a large-scale matched molecular pair analysis.

P-glycoprotein (Pgp) mediated efflux impacts on the drug absorption, distribution, metabolism and excretion, and confers multidrug resistance to cancer cells. Kinetic modelling provides mechanistic insights into the relationship between the substrate-Pgp interactions and efflux, and bridges the gap between the preference of polar compounds as Pgp substrates and the hydrophobic nature of its drug-binding site. Matched molecular pair analysis supports the guidelines of controlling H-bond donors and polar surface area in the efflux mitigation, but also reveals insufficiency of this type of rule-based approach. Contrary to the rule-of-five compliant compounds, proteolysis-targeting chimeras (PROTACs) have shown the opposite preference of physicochemical properties to evade efflux. Our analysis reiterates the critical role of intrinsic passive permeability in the efflux ratio, and indeed, its mitigation is often driven by increased passive permeability. It is thus useful to separate the passive permeability from the structural context-specific substrate-Pgp interactions in the design cycle.

Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification.

Siamese networks, representing a novel class of neural networks, consist of two identical subnetworks sharing weights but receiving different inputs. Here we present a similarity-based pairing method for generating compound pairs to train Siamese neural networks for regression tasks. In comparison with the conventional exhaustive pairing, it reduces the algorithm complexity from O(n2) to O(n). It also results in a better prediction performance consistently on the three physicochemical datasets, using a multilayer perceptron with the circular fingerprint as a proof of concept. We further include into a Siamese neural network the transformer-based Chemformer, which extracts task-specific features from the simplified molecular-input line-entry system representation of compounds. Additionally, we propose a means to measure the prediction uncertainty by utilizing the variance in predictions from a set of reference compounds. Our results demonstrate that the high prediction accuracy correlates with the high confidence. Finally, we investigate implications of the similarity property principle in machine learning.

Using mixed reality technique combines multimodal imaging signatures to adjuvant glioma photodynamic therapy.

Background: Photodynamic therapy (PDT) promotes significant tumor regression and extends the lifetime of patients. The actual operation of PDT often relies on the subjective judgment of experienced neurosurgeons. Patients can benefit more from precisely targeting PDT's key operating zones. Methods: We used magnetic resonance imaging scans and created 3D digital models of patient anatomy. Multiple images are aligned and merged in STL format. Neurosurgeons use HoloLens to import reconstructions and assist in PDT execution. Also, immunohistochemistry was used to explore the association of hyperperfusion sites in PDT of glioma with patient survival. Results: We constructed satisfactory 3D visualization of glioma models and accurately localized the hyperperfused areas of the tumor. Tumor tissue taken in these areas was rich in CD31, VEGFA and EGFR that were associated with poor prognosis in glioma patients. We report the first study using MR technology combined with PDT in the treatment of glioma. Based on this model, neurosurgeons can focus PDT on the hyperperfused area of the glioma. A direct benefit was expected for the patients in this treatment. Conclusion: Using the Mixed Reality technique combines multimodal imaging signatures to adjuvant glioma PDT can better exploit the vascular sealing effect of PDT on glioma.

The regulation of chromatin configuration at AGAMOUS locus by LFR-SYD-containing complex is critical for reproductive organ development in Arabidopsis.

Switch defective/sucrose non-fermentable (SWI/SNF) chromatin remodeling complexes are evolutionarily conserved, multi-subunit machinery that play vital roles in the regulation of gene expression by controlling nucleosome positioning and occupancy. However, little is known about the subunit composition of SPLAYED (SYD)-containing SWI/SNF complexes in plants. Here, we show that the Arabidopsis thaliana Leaf and Flower Related (LFR) is a subunit of SYD-containing SWI/SNF complexes. LFR interacts directly with multiple SWI/SNF subunits, including the catalytic ATPase subunit SYD, in vitro and in vivo. Phenotypic analyses of lfr-2 mutant flowers revealed that LFR is important for proper filament and pistil development, resembling the function of SYD. Transcriptome profiling revealed that LFR and SYD shared a subset of co-regulated genes. We further demonstrate that the LFR and SYD interdependently activate the transcription of AGAMOUS (AG), a C-class floral organ identity gene, by regulating the occupation of nucleosome, chromatin loop, histone modification, and Pol II enrichment on the AG locus. Furthermore, the chromosome conformation capture (3C) assay revealed that the gene loop at AG locus is negatively correlated with the AG expression level, and LFR-SYD was functional to demolish the AG chromatin loop to promote its transcription. Collectively, these results provide insight into the molecular mechanism of the Arabidopsis SYD-SWI/SNF complex in the control of higher chromatin conformation of the floral identity gene essential to plant reproductive organ development.

Assessment of heavy metals mobilization in road-deposited sediments induced by COVID-19 disinfection.

Road-deposited sediments (RDS) on urban impervious surfaces are important carriers of heavy metals (HMs), and can contribute to urban runoff pollution. With the outbreak of COVID-19, chlorinated disinfectants (CDs) have been extensively sprayed on these surfaces. This practice may have a superposed or priming effect on HMs contaminants in RDS, yet this remains unknown. This study examined the effects of seven CDs concentration gradients (0, 250, 500, 1000, 2000, 5000, 60,000 mg/L) on the leaching and chemical forms of HMs (Cd, Cr, Ni, Pb, and Zn) in seven particle size fractions (<44, 44-63, 63-105, 105-149, 149-250, 250-450, 450-1000 µm). The results showed that CDs can promote the leaching of HMs in RDS, at the recommended CDs dose (2000 mg/L), except for Pb, the leaching amounts increased by 21.8%-237.2% compared with the untreated RDS. The alteration in the leaching were primarily attributed to the redistribution of chemical forms of HMs in RDS, specifically, the acid-extractable fractions percentage increased by 0.23%-24.39%, and the reducible fractions percentages decreased by 3.21%-38.35%. The lower oxidation-reduction potential (ORP) and alkalinity of CDs as strong oxidants were responsible for the redistribution of forms. The leaching and chemical forms of HMs vary among different particle sizes, but in any case, finer particle sizes (< 105 µm) still dominate their contribution. The current control measure of street sweeping is ineffective in removing these particles. These findings will facilitate the development of strategies for controlling urban diffuse pollution from RDS during the pandemic. Finally, this study suggests potential directions for future research.

Expression of intra-tumoral necrosis-associated cytokine pattern correlated with prognosis and immune status in glioma.

Intra-tumoral necrosis (ITN) is reported to be an independent prognostic factor in glioma. However, knowledge of ITN is mainly limited to pseudopalisadwe, while its other aspects were neglected. Therefore, a deeper understanding of ITN could be valuable for understanding its exact role in glioma. The only reliable ITN model was time-dependently achieved with the GL261 syngeneic mouse model. The ITN-associated expression pattern was enriched from RNA sequencing. TCGA glioma samples were clustered into a high-expression group (HEG) and a low-expression group (LEG) based on their pattern and their association with prognosis, clinical status, immune status, and therapeutic responsiveness were compared. Mouse glioma with ITN demonstrated invasive histology. Cytokine signaling was significantly enriched in necrotic mouse glioma compared with non-necrotic glioma tissues. Nine pro-inflammatory (IL6, PPBP, IL1A, TNFSF11, CXCL11, CXCL9, CXCL10, CXCL3, and CCL8) and two anti-inflammatory cytokine (IL1RN and IL10) genes were found to be related to ITN-associated cytokine patterns. Comparative analysis showed that HEG had a significantly shorter survival time, five differentially distributed clinical statuses, more infiltrated immune cells, greater expression of immune checkpoints, and better therapeutic responsiveness than LEG. In conclusion, the ITN-associated cytokine pattern is characteristically expressed in glioma with ITN and might indicate necrosis missed in histology diagnosis. Its expression pattern could predict the prognosis, tumor grade, immune status, and therapeutic responsiveness of glioma patients.

A five-cuproptosis-related LncRNA Signature: predicting prognosis, assessing immune function & drug sensitivity in lung squamous cell carcinoma.

Lung squamous cell carcinoma has so far lacked effective targets for diagnosis and treatment. In cancer research, long noncoding RNAs (LncRNAs) emerge as novel therapeutic targets and biomarkers. Cuprophosis is a new death type involving multiple biological processes in tumor cells. Here, we aimed to explore whether Cuprophosis-related lncRNAs could be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients. The Cancer Genome Map (TCGA) was used to obtain genome and clinical data, and Cuprophosis-relevant genes were found in the literature. A cuproptosis-related lncRNA risk model was built using co-expression analysis, univariate/multivariate Cox regression, and LASSO analysis. The survival analysis was used to assess the model's prognostic value. The univariate and multivariate Cox regression analyses were performed to determine whether risk score, age, gender, or clinical stages could be used as independent prognostic factors. Gene Set Enrichment Analysis and mutation analysis were performed on differentially expressed mRNA between high-risk and low-risk groups. The (TIDE) algorithm was used to conduct immunological functional analysis and drug sensitivity testing. Five cuproptosis-related LncRNAs were identified, and the selected LncRNAs constructed a prognosis model. According to the Kaplan-Meier survival analysis, the overall survival time for patients in the high-risk group was shorter than for those in the low-risk group. For LUSC patients, the risk score serves as an independent prognostic indicator. The GO and KEGG enrichment analysis revealed that the differentially expressed mRNAs between the high- and low-risk groups were enriched in several immune-related processes. The enrichment score of differentially expressed mRNAs in the high-risk group is higher than that of the low-risk group in multiple immune function pathways, including the IFN-γ and MHC I pathways. The Tumor Immune Dysfunction and Exclusion (TIDE) test revealed that the high-risk group was more likely to experience immune escape. The drug sensitivity analysis showed that patients with low-risk ratings were likely to respond to GW441756 and Salubrinal. In contrast, patients with higher risk scores were more responsive to dasatinib and Z-LLNIe CHO. The 5-Cuprophosis-related lncRNA signature can be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients.

The Role of Allylic Strain for Conformational Control in Medicinal Chemistry.

It is axiomatic in medicinal chemistry that optimization of the potency of a small molecule at a macromolecular target requires complementarity between the ligand and target. In order to minimize the conformational penalty on binding, both enthalpically and entropically, it is therefore preferred to have the ligand preorganized in the bound conformation. In this Perspective, we highlight the role of allylic strain in controlling conformational preferences. Allylic strain was originally described for carbon-based allylic systems, but the same principles apply to other types of structure with sp2 or pseudo-sp2 arrangements. These systems include benzylic (including heteroaryl methyl) positions, amides, N-aryl groups, aryl ethers, and nucleotides. We have derived torsion profiles from small molecule X-ray structures for these systems. Through multiple examples, we show how these effects have been applied in drug discovery and how they can be used prospectively to influence conformation in the design process.

Genome-wide identification of genes encoding SWI/SNF components in soybean and the functional characterization of GmLFR1 in drought-stressed plants.

ATP-dependent SWI/SNF chromatin remodeling complexes (CRCs) are evolutionarily conserved multi-component machines that regulate transcription, replication, and genome stability in eukaryotes. SWI/SNF components play pivotal roles in development and various stress responses in plants. However, the compositions and biological functions of SWI/SNF complex subunits remain poorly understood in soybean. In this study, we used bioinformatics to identify 39 genes encoding SWI/SNF subunit distributed on the 19 chromosomes of soybean. The promoter regions of the genes were enriched with several cis-regulatory elements that are responsive to various hormones and stresses. Digital expression profiling and qRT-PCR revealed that most of the SWI/SNF subunit genes were expressed in multiple tissues of soybean and were sensitive to drought stress. Phenotypical, physiological, and molecular genetic analyses revealed that GmLFR1 (Leaf and Flower-Related1) plays a negative role in drought tolerance in soybean and Arabidopsis thaliana. Together, our findings characterize putative components of soybean SWI/SNF complex and indicate possible roles for GmLFR1 in plants under drought stress. This study offers a foundation for comprehensive analyses of soybean SWI/SNF subunit and provides mechanistic insight into the epigenetic regulation of drought tolerance in soybean.

Arabidopsis LFR, a SWI/SNF complex component, interacts with ICE1 and activates ICE1 and CBF3 expression in cold acclimation.

Low temperatures restrict the growth and geographic distribution of plants, as well as crop yields. Appropriate transcriptional regulation is critical for cold acclimation in plants. In this study, we found that the mutation of Leaf and flower related (LFR), a component of SWI/SNF chromatin remodeling complex (CRC) important for transcriptional regulation in Arabidopsis (Arabidopsis thaliana), resulted in hypersensitivity to freezing stress in plants with or without cold acclimation, and this defect was successfully complemented by LFR. The expression levels of CBFs and COR genes in cold-treated lfr-1 mutant plants were lower than those in wild-type plants. Furthermore, LFR was found to interact directly with ICE1 in yeast and plants. Consistent with this, LFR was able to directly bind to the promoter region of CBF3, a direct target of ICE1. LFR was also able to bind to ICE1 chromatin and was required for ICE1 transcription. Together, these results demonstrate that LFR interacts directly with ICE1 and activates ICE1 and CBF3 gene expression in response to cold stress. Our work enhances our understanding of the epigenetic regulation of cold responses in plants.

Spatial and temporal dynamics of base flow in semi-arid montane watersheds and the effects of landscape patterns and topography.

Base flow (BF) is harder to predict than other hydrological signatures. The lack of hydrologically relevant information or adequately broad spectrum of typically selected catchment attributes (particularly landscape and topography) hinders the explanatory power. Our goals were to identify the most influential controls on base flow spatially and temporally and to elucidate the response relationships. Base flow in 19 semi-arid sub-watersheds was separated by digital filtering. One hundred and fourteen sub-watershed attributes were related to base flow using random forest regression. The main results were as follows: (1) Annual BF significantly declined since 1999 due to decreased precipitation, increased air temperature, afforestation, urban expansion, and increasing water consumption. Annual base flow index (BFI), varying between 0.319 and 0.695, showed less noticeable temporal trends. (2) Precipitation (P) and underlying carbonate rocks primarily controlled the spatial variation of annual BF and total flow (TF), with the impacts being positive. Landscape was less influential. After the abrupt runoff decline, landscape composition rather than configuration exerted greater impacts on spatial BF and TF, and the importance of forest increased, whereas landscape configuration was decisive for BFI during the whole observation period. The absence of significant links between landscape configuration and water quantity may result from a scale issue. Concave profile curvatures were found to be topographic variables more important than slopes. The impact of soil was the least. This study would benefit the selection of catchment attributes and spatial extents to quantify these attributes in building BF predicting models in future studies.

Integrative analysis to screen novel pyroptosis-related LncRNAs for predicting clinical outcome of glioma and validation in tumor tissue.

BACKGROUND: Pyroptosis, also known as inflammatory necrosis, is a programmed cell death that manifests itself as a continuous swelling of cells until the cell membrane breaks, leading to the liberation of cellular contents, which triggers an intense inflammatory response. Pyroptosis might be a panacea for a variety of cancers, which include immunotherapy and chemotherapy-insensitive tumors such as glioma. Several findings have observed that long non-coding RNAs (lncRNAs) modulate the bio-behavior of tumor cells by binding to RNA, DNA and protein. Nevertheless, there are few studies reporting the effect of lncRNAs in pyroptosis processes in glioma. METHODS: The principal goal of this study was to identify pyroptosis-related lncRNAs (PRLs) utilizing bioinformatic algorithm and to apply PCR techniques for validation in human glioma tissues. The second goal was to establish a prognostic model for predicting the overall survival patients with glioma. Predict algorithm was used to construct prognosis model with good diagnostic precision for potential clinical translation. RESULTS: Noticeably, molecular subtypes categorized by the PRLs were not distinct from any previously published subtypes of glioma. The immune and mutation landscapes were obviously different from previous subtypes of glioma. Analysis of the sensitivity (IC50) of patients to 30 chemotherapeutic agents identified 22 agents as potential therapeutic agents for patients with low riskscores. CONCLUSIONS: We established an exact prognostic model according to the expression profile of PRLs, which may facilitate the assessment of patient prognosis and treatment patterns and could be further applied to clinical.