Adipocyte proteome and secretome influence inflammatory and hormone pathways in glioma

LncRNA ZNF667-AS1 Targets miR-523-3p/KIF5C Axis to Hinder Colon Cancer Progression

LncRNA ZNF667-AS1 plays an important role in the carcinogenesis and progression of various cancers. However, their role in colon cancer (CC) remains unclear. The expression of ZNF667-AS1, KIF5C, and miR-523-3p in CC cells and tissues was analyzed using RT-qPCR and western blotting. CCK-8 scratch-wound assay, western blotting, and flow cytometry were conducted to investigate the malignant activity of CC in vitro. Luciferase reporter, RNA pull-down, and Ago2 immunoprecipitation (RIP) experiments were conducted to ascertain the association of miR-523-3p with ZNF667-AS1 and KIF5C 3'UTR. Xenograft tumor experiments were also performed. CC cells and tissues showed low expression of NF667-AS1 and KIF5C and elevated expression of miR-523-3p. ZNF667-AS1 overexpression attenuates proliferation and migration of CC cells, restores inactivated apoptosis in vitro, and inhibits tumor growth in vivo. MiR-523-3p targets both ZNF667-AS1 and the KIF5C 3'UTR. ZNF667-AS1 overexpression in SW480 and SW620 cells attenuated the oncogenic effect of miR-523-3p in CC. However, this attenuating effect was counteracted by KIF5C overexpression. ZNF667-AS1 sequestered miR-523-3, reducing miR-523-3p-mediated inhibition of KIF5C expression, thereby repressing colon carcinogenesis in vitro. Our findings shed light on a novel anticancer strategy that could potentially combat CC.

High LYRM4-AS1 predicts poor prognosis in patients with glioma and correlates with immune infiltration

Background

Many researches proved that non-coding RNAs are important in glioma development. We screened the differentially expressed genes through The Cancer Genome Atlas (TCGA) database and identified the molecule LYRM4-AS1 associated with prognosis. As a lncRNA, the expression level and role of LYRM4-AS1 in glioma are inconclusive. Therefore, we attempted to assess the clinical significance, expression and related mechanisms of LYRM4-AS1 in glioma by employing cell experiments and an integrative in silico methodology.

Methods

RNA-seq data were obtained from UCSC XENA and TCGA datasets. The Gene Expression Omnibus (GEO) database was used to download glioma-related expression profile data. The LYRM4-AS1 expression level was evaluated. Survival curves were constructed by the Kaplan-Meier method. Cox regression analysis was used to analyze independent variables. Patients were divided into high and low expression group base on the median LYRM4-AS1 expression value in glioma tissues. The DESeq2 R package was used to identify differentially expressed genes (DEGs) between two different expression LYRM4-AS1 groups. Gene set enrichment analysis (GSEA) was conducted. Next, the single-sample Gene Set Enrichment Analysis (ssGSEA) was done to quantify the immune infiltration of immune cells in glioma tissues. Gene expression profiles for glioma tumor tissues were used to quantify the relative enrichment score for each immune cell. Spearman correlation analysis was used to analyze the correlation between LYRM4-AS1 and biomarkers of immune cells as well as immune checkpoints in glioma. Finally, assays for cell apoptosis, cell viability and wound healing were conducted to evaluate the function on U87 MG and U251 cells after knocking down LYRM4-AS1.

Results

We found that LYRM4-AS1 was upregulated and related to the grade and malignancy of glioma. Survival analyses showed that high expression LYRM4-AS1 patients had poor clinical outcomes (P < 0.01). Cox regression analyses demonstrated that LYRM4-AS1 was an independent risk factor for overall survival (OS) in glioma (HR: 274 1.836; CI [1.278-2.639]; P = 0.001). Enrichment and immune infiltration analysis showed interferon signaling and cytokine-cytokine receptor interaction enriched in the LYRM4-AS1 high-expression phenotype, and LYRM4-AS1 showed significantly positively related to immune infiltration as well as immune checkpoints (P < 0.01). The knockdown of LYRM4-AS1 in U87 MG and U251 cells can inhibit migration and proliferation of cells (P < 0.05).

Conclusions

These findings indicated that the increased LYRM4-AS1 may be useful for the diagnosis and prognosis of glioma and might participate in the immune infiltration.

Characterization of tumor microenvironment in glioblastoma multiforme identifies ITGB2 as a key immune and stromal related regulator in glial cell types

Glioblastoma multiforme (GBM) is the most aggressive form of brain tumor characterized by inter and intra-tumor heterogeneity and complex tumor microenvironment. To uncover the molecular targets in this milieu, we systematically identified immune and stromal interactions at the glial cell type level that leverages on RNA-sequencing data of GBM patients from The Cancer Genome Atlas. The perturbed genes between the high vs low immune and stromal scored patients were subjected to weighted gene co-expression network analysis to identify the glial cell type specific networks in immune and stromal infiltrated patients. The intramodular connectivity analysis identified the highly connected genes in each module. Combining it with univariable and multivariable prognostic analysis revealed common vital gene ITGB2, between the immune and stromal infiltrated patients enriched in microglia and newly formed oligodendrocytes. We found following unique hub genes in immune infiltrated patients; COL6A3 (microglia), ITGAM (oligodendrocyte precursor cells), TNFSF9 (microglia), and in stromal infiltrated patients, SERPINE1 (microglia) and THBS1 (newly formed oligodendrocytes, oligodendrocyte precursor cells). To validate these hub genes, we used external GBM patient single cell RNA-sequencing dataset and this identified ITGB2 to be significantly enriched in microglia, newly formed oligodendrocytes, T-cells, macrophages and adipocyte cell types in both immune and stromal datasets. The tumor infiltration analysis of ITGB2 showed that it is correlated with myeloid dendritic cells, macrophages, monocytes, neutrophils, B-cells, fibroblasts and adipocytes. Overall, the systematic screening of tumor microenvironment components at glial cell types uncovered ITGB2 as a potential target in primary GBM.

The Labyrinthine Landscape of APP Processing: State of the Art and Possible Novel Soluble APP-Related Molecular Players in Traumatic Brain Injury and Neurodegeneration

Amyloid Precursor Protein (APP) and its cleavage processes have been widely investigated in the past, in particular in the context of Alzheimer’s Disease (AD). Evidence of an increased expression of APP and its amyloidogenic-related cleavage enzymes, β-secretase 1 (BACE1) and γ-secretase, at the hit axon terminals following Traumatic Brain Injury (TBI), firstly suggested a correlation between TBI and AD. Indeed, mild and severe TBI have been recognised as influential risk factors for different neurodegenerative diseases, including AD. In the present work, we describe the state of the art of APP proteolytic processing, underlining the different roles of its cleavage fragments in both physiological and pathological contexts. Considering the neuroprotective role of the soluble APP alpha (sAPPα) fragment, we hypothesised that sAPPα could modulate the expression of genes of interest for AD and TBI. Hence, we present preliminary experiments addressing sAPPα-mediated regulation of BACE1, Isthmin 2 (ISM2), Tetraspanin-3 (TSPAN3) and the Vascular Endothelial Growth Factor (VEGFA), each discussed from a biological and pharmacological point of view in AD and TBI. We finally propose a neuroprotective interaction network, in which the Receptor for Activated C Kinase 1 (RACK1) and the signalling cascade of PKCβII/nELAV/VEGF play hub roles, suggesting that vasculogenic-targeting therapies could be a feasible approach for vascular-related brain injuries typical of AD and TBI.

Maternal obesity and programming of metabolic syndrome in the offspring: searching for mechanisms in the adipocyte progenitor pool

BACKGROUND

It is now understood that it is the quality rather than the absolute amount of adipose tissue that confers risk for obesity-associated disease. Adipose-derived stem cells give rise to adipocytes during the developmental establishment of adipose depots. In adult depots, a reservoir of progenitors serves to replace adipocytes that have reached their lifespan and for recruitment to increase lipid buffering capacity under conditions of positive energy balance. MAIN: The adipose tissue expandability hypothesis posits that a failure in de novo differentiation of adipocytes limits lipid storage capacity and leads to spillover of lipids into the circulation, precipitating the onset of obesity-associated disease. Since adipose progenitors are specified to their fate during late fetal life, perturbations in the intrauterine environment may influence the rapid expansion of adipose depots that occurs in childhood or progenitor function in established adult depots. Neonates born to mothers with obesity or diabetes during pregnancy tend to have excessive adiposity at birth and are at increased risk for childhood adiposity and cardiometabolic disease.

CONCLUSION

In this narrative review, we synthesize current knowledge in the fields of obesity and developmental biology together with literature from the field of the developmental origins of health and disease (DOHaD) to put forth the hypothesis that the intrauterine milieu of pregnancies complicated by maternal metabolic disease disturbs adipogenesis in the fetus, thereby accelerating the trajectory of adipose expansion in early postnatal life and predisposing to impaired adipose plasticity.

Coordinated reprogramming of renal cancer transcriptome, metabolome and secretome associates with immune tumor infiltration

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. The molecules (proteins, metabolites) secreted by tumors affect their extracellular milieu to support cancer progression. If secreted in amounts detectable in plasma, these molecules can also serve as useful, minimal invasive biomarkers. The knowledge of ccRCC tumor microenvironment is fragmentary. In particular, the links between ccRCC transcriptome and the composition of extracellular milieu are weakly understood. In this study, we hypothesized that ccRCC transcriptome is reprogrammed to support alterations in tumor microenvironment. Therefore, we comprehensively analyzed ccRCC extracellular proteomes and metabolomes as well as transcriptomes of ccRCC cells to find molecules contributing to renal tumor microenvironment.

METHODS

Proteomic and metabolomics analysis of conditioned media isolated from normal kidney cells as well as five ccRCC cell lines was performed using mass spectrometry, with the following ELISA validation. Transcriptomic analysis was done using microarray analysis and validated using real-time PCR. Independent transcriptomic and proteomic datasets of ccRCC tumors were used for the analysis of gene and protein expression as well as the level of the immune infiltration.

RESULTS

Renal cancer secretome contained 85 proteins detectable in human plasma, consistently altered in all five tested ccRCC cell lines. The top upregulated extracellular proteins included SPARC, STC2, SERPINE1, TGFBI, while downregulated included transferrin and DPP7. The most affected extracellular metabolites were increased 4-hydroxy-proline, succinic acid, cysteine, lactic acid and downregulated glutamine. These changes were associated with altered expression of genes encoding the secreted proteins (SPARC, SERPINE1, STC2, DPP7), membrane transporters (SLC16A4, SLC6A20, ABCA12), and genes involved in protein trafficking and secretion (KIF20A, ANXA3, MIA2, PCSK5, SLC9A3R1, SYTL3, and WNTA7). Analogous expression changes were found in ccRCC tumors. The expression of SPARC predicted the infiltration of ccRCC tumors with endothelial cells. Analysis of the expression of the 85 secretome genes in > 12,000 tumors revealed that SPARC is a PanCancer indicator of cancer-associated fibroblasts' infiltration.

CONCLUSIONS

Transcriptomic reprogramming of ccRCC supports the changes in an extracellular milieu which are associated with immune infiltration. The proteins identified in our study represent valuable cancer biomarkers detectable in plasma.

Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research

Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative "omics" approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis.

Construction of an immune-related gene signature for the prognosis and diagnosis of glioblastoma multiforme

Background

Increasing evidence has suggested that inflammation is related to tumorigenesis and tumor progression. However, the roles of immune-related genes in the occurrence, development, and prognosis of glioblastoma multiforme (GBM) remain to be studied.

Methods

The GBM-related RNA sequencing (RNA-seq), survival, and clinical data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Immune-related genes were obtained from the Molecular Signatures Database (MSigDB). Differently expressed immune-related genes (DE-IRGs) between GBM and normal samples were identified. Prognostic genes associated with GBM were selected by Kaplan–Meier survival analysis, Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and multivariate Cox analysis. An immune-related gene signature was developed and validated in TCGA and CGGA databases separately. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore biological functions of the signature. The correlation between immune cell infiltration and the signature was analyzed by single-sample gene set enrichment analysis (ssGSEA), and the diagnostic value was investigated. The gene set enrichment analysis (GSEA) was performed to explore the potential function of the signature genes in GBM, and the protein–protein interaction (PPI) network was constructed.

Results

Three DE-IRGs [Pentraxin 3 (PTX3), TNFSF9, and bone morphogenetic protein 2 (BMP2)] were used to construct an immune-related gene signature. Receiver operating characteristic (ROC) curves and Cox analyses confirmed that the 3-gene-based prognostic signature was a good independent prognostic factor for GBM patients. We found that the signature was mainly involved in immune-related biological processes and pathways, and multiple immune cells were disordered between the high- and low-risk groups. GSEA suggested that PTX3 and TNFSF9 were mainly correlated with interleukin (IL)-17 signaling pathway, nuclear factor kappa B (NF-κB) signaling pathway, tumor necrosis factor (TNF) signaling pathway, and Toll-like receptor signaling pathway, and the PPI network indicated that they could interact directly or indirectly with inflammatory pathway proteins. Quantitative real-time PCR (qRT-PCR) indicated that the three genes were significantly different between target tissues.

Conclusion

The signature with three immune-related genes might be an independent prognostic factor for GBM patients and could be associated with the immune cell infiltration of GBM patients.

Body mass index and glioma risk: A prospective multicenter study

BACKGROUND

The association between glioma risk and body mass index (BMI) remains obscure.

METHODS

This study aimed to assess the association between glioma risk and BMI in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs).

RESULTS

The onset of a total of 269 gliomas was observed during a median follow-up period of 12.04 years. Compared with the normal weight, overweight (HR: 1.05; 95% CI: 0.80, 1.39) and obesity (HR: 0.91; 95% CI: 0.56, 1.39) were not significantly associated with glioma risk. Further analysis showed a nonlinear relationship between glioma risk and BMI in men but not women. The multivariable-adjusted HRs per unit increase in BMI were 0.94 (95% CI: 0.89, 1.00; P = 0.037) in men with BMI >25 kg/m² and 1.16 (95% CI: 0.98, 1.38; P = 0.075) in men with BMI <25 kg/m².

CONCLUSION

The present data provide evidence that there may be a nonlinear association between BMI and glioma risk in men. The risk of glioma decreased with increasing BMI among men with BMI >25 kg/m². Future studies are needed to validate our observation.

ITGB2 as a prognostic indicator and a predictive marker for immunotherapy in gliomas

PURPOSE

Glioma is the most common primary tumor in the brain, accounting for 81% of intracranial malignancies. Nowadays, cancer immunotherapy has become a novel and revolutionary treatment for patients with advanced, highly aggressive tumors. However, to date, there are no effective biomarkers to reflect the response of glioma patients to immunotherapy. In this study, we aimed to assess the clinical predictive value of ITGB2 in patients with glioma.

METHODS

The correlation between ITGB2 expression levels and glioma progression was explored and validated using data from CGGA, TCGA, GEO datasets, and patient samples from our hospital. Univariate and multivariate cox regression models were developed to determine the predictive role of ITGB2 on the prognosis of patients with glioma. The relationship between ITGB2 and immune activation was then analyzed. Finally, we predicted the immunotherapy response in both high and low ITGB2 expression subgroups.

RESULTS

ITGB2 was significantly elevated in gliomas with higher malignancy and predicted poor prognosis. In multivariate analysis, the hazard ratio for ITGB2 expression (low versus high) was 0.71 with 95% CI (0.59-0.85) (P < 0.001). Furthermore, we found that ITGB2 stratified glioma patients into high and low ITGB2 expression subgroups, exhibiting different clinical outcomes and immune activation status. At last, we demonstrated that glioma patients with high ITGB2 expression levels had better immunotherapy response.

CONCLUSIONS

This study demonstrated ITGB2 as a novel predictor for clinical prognosis and response to immunotherapy in gliomas. Assessing expression levels of ITGB2 is a promising method to discover patients that may benefit from immunotherapy.

Associations of General and Abdominal Obesity with the Risk of Glioma Development

Simple Summary

While obesity is a well-known risk factor for the development of various types of cancer, conflicting results have been reported concerning the relationship between obesity and the risk of glioma. To date, no studies have evaluated the association between obesity and risk of glioma development in Eastern Asian populations, who usually have greater fat mass and less muscle and are more likely to develop several metabolic diseases than Western populations of the same body mass index (BMI) category. In this nationwide population-based study, we suggest, for the first time, positive associations of general and central obesity with the risk of glioma development. In addition, we demonstrate a stronger association between abdominal obesity and the risk of glioma development than BMI and the risk of glioma development.

Abstract

The association between obesity and the risk of glioma remains unclear. We sought to evaluate the potential association between general and abdominal obesity and the risk of glioma based on a nationwide population-based cohort study of Koreans. Using data from the Korean National Health Insurance System cohort, 6,833,744 people older than 20 years who underwent regular national health examination in both 2009 and 2011 were followed until the end of 2017. We documented 4771 glioma cases based on an ICD-10 code of C71 during the median follow-up period of 7.30 years. Individuals with a body mass index (BMI) ≥ 25.0 kg/m² were at significantly higher risk of developing glioma than those with a BMI < 25.0 kg/m² (HR 1.08 CI 1.02–1.15). Individuals with a waist circumference (WC) ≥ 90 cm (males)/85 cm (females) also had a significantly higher risk of glioma than those with a WC < 90 cm (males)/85 cm (females) (HR 1.16 CI 1.09–1.24). In the group with a BMI ≥ 25.0 kg/m², individuals with abdominal obesity were at significantly higher risk of developing glioma (HR 1.18 CI 1.09–1.27) than those without abdominal obesity. The role of abdominal obesity in this association was stronger in women than in men. To the best of our knowledge, this is the first demonstration that obese people may be at higher risk of glioma, especially centrally obese people from an Asian population with a BMI ≥ 25.0 kg/m². Loss of visceral fat in people with abdominal obesity may reduce their risk of developing glioma.

Putting Proteomics Into Immunotherapy for Glioblastoma

In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not effectively prolong the survival of patients, due to the unique location and heterogeneous characteristics of glioblastoma. Immunotherapy has shown a promising effect for many other tumors, but its application for glioma still has some challenges. The recent breakthrough of high-throughput liquid chromatography-mass spectrometry (LC-MS/MS) systems has allowed researchers to update their strategy for identifying and quantifying thousands of proteins in a much shorter time with lesser effort. The protein maps can contribute to generating a complete map of regulatory systems to elucidate tumor mechanisms. In particular, newly developed unicellular proteomics could be used to determine the microenvironment and heterogeneity. In addition, a large scale of differentiated proteins provides more ways to precisely classify tumor subtypes and construct a larger library for biomarkers and biotargets, especially for immunotherapy. A series of advanced proteomic studies have been devoted to the different aspects of immunotherapy for glioma, including monoclonal antibodies, oncolytic viruses, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) T cells. Thus, the application of proteomics in immunotherapy may accelerate research on the treatment of glioblastoma. In this review, we evaluate the frontline applications of proteomics strategies for immunotherapy in glioblastoma research.

The Adipose Tissue at the Crosstalk Between EDCs and Cancer Development

Obesity is a major public health concern at the origin of many pathologies, including cancers. Among them, the incidence of gastro-intestinal tract cancers is significantly increased, as well as the one of hormone-dependent cancers. The metabolic changes caused by overweight mainly with the development of adipose tissue (AT), insulin resistance and chronic inflammation induce hormonal and/or growth factor imbalances, which impact cell proliferation and differentiation. AT is now considered as the main internal source of endocrine disrupting chemicals (EDCs) representing a low level systemic chronic exposure. Some EDCs are non-metabolizable and can accumulate in AT for a long time. We are chronically exposed to low doses of EDCs able to interfere with the endocrine metabolism of the body. Importantly, several EDCs have been involved in the genesis of obesity affecting profoundly the physiology of AT. In parallel, EDCs have been implicated in the development of cancers, in particular hormone-dependent cancers (prostate, testis, breast, endometrium, thyroid). While it is now well established that AT secretes adipocytokines that promote tumor progression, it is less clear whether they can initiate cancer. Therefore, it is important to better understand the effects of EDCs, and to investigate the buffering effect of AT in the context of progression but also initiation of cancer cells using adequate models recommended to uncover and validate these mechanisms for humans. We will review and argument here the potential role of AT as a crosstalk between EDCs and hormone-dependent cancer development, and how to assess it.

Tumor-associated macrophages based signaling pathway analysis and hub genes identification in glioma

Tumor-associated macrophages (TAMs) play a crucial role in the immune response to many malignancies, but the signaling pathways by which the glioma microenvironment cross-talk with TAMs are poorly understood. The aim of this study was to uncover the potential signaling pathways of the regulation of TAMs and identify candidate targets for therapeutic intervention of glioma through bioinformatics analysis.Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets were used to download RNA-Seq data and microarray data of human glioma specimen. Differentially expressed genes (DEGs) between CD68-high samples and CD68-low samples were sorted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs was conducted. Protein-protein interaction (PPI) network were formed to identify the hub genes.The prognostic value of TAMs in glioma patients was confirmed. A total of 477 specific DEGs were sorted. The signaling pathway was identified in pathway enrichment and the DEGs showed prominent representations of immune response networks in glioma. The hub genes including C3, IL6, ITGB2, PTAFR, TIMP1 and VAMP8 were identified form the PPI network and they were all correlated positively with the expression of CD68 and showed the excellent prognostic value in glioma patients.TAMs can be used as a good prognostic indicator in glioma patients. By analyzing comprehensive bioinformatics data, we uncovered the underlying signaling pathway of the DEGs between glioma patients with high and low expression level of CD68. Furthermore, the 6 hub genes identified were closely associated with TAMs in glioma microenvironment and need further investigation.

NAMPT, GRN, and SERPINE1 signature as predictor of disease progression and survival in gliomas

Adipose tissue is an important source of adipokines involved in anti- and pro-inflammatory effects. Their involvement in certain cancers such as breast and colon cancer is known but in gliomas it remains unexplored till date. The aim of this study was to assess the status of adipokines as prognostic markers of gliomas (low grade gliomas [LGG] and glioblastoma mutiforme [GBM]). Expression status (messenger RNA [mRNA]), overall survival (OS) and disease-free survival (DFS) was identified using gene expression profiling interactive analysis server. Clinicopathological analysis and correlation between different adipokines was performed using Xena server. Protein expression status was analyzed using tissue sections from the Human Protein Atlas. Out of 11 adipokines studied visfatin (NAMPT), apelin (APLN), granulin (GRN), serpin peptidase inhibitor/plasminogen activator inhibitor type 1 (PAI-1) member 1 (SERPINE1), and chemokine (C-C motif) ligand 2 (CCL2) mRNA levels were significantly upregulated in both LGG and GBM. Interleukin 6 (IL6) mRNA was found be significantly upregulated only in GBM. NAMPT, GRN, SERPINE1, and IL6 showed reduced OS as well as worst DFS for patients having higher mRNA expression in LGG. Increased expression of CCL2 showed worst OS in LGG patients while resistin (RETN) and GRN showed the worst OS in GBM patients. Higher expression of RETN, GRN, IL6, SERPINE1, and CCL2 were found to be positively correlated with shorter DFS in GBM. In the clinicopathological analysis, NAMPT, GRN, IL6, SERPINE1, and CCL2 expressions were significantly associated between the neoplasm histological G2 and G3 grades. Furthermore, expression of NAMPT, GRN, tumor necrosis factor, IL6, SERPINE1, and CCL2 were significantly associated with histological type in LGG patients. NAMPT, GRN, SERPINE1, CCL2, and RETN expression were found to be correlated with each other in gliomas. Finally, NAMPT, GRN, and SERPINE1 were also found to be upregulated using immunohistochemistry in a lower grade and high grade gliomas as compared to normal cells. In conclusion, we have identified key adipokines, namely NAMPT, GRN, and SERPINE1 as potential diagnostic and prognostic markers that might be instrumental in the development and progression of gliomas.