Upregulation of SLC2A3 gene and prognosis in colorectal carcinoma: analysis of TCGA data

Towards precision oncology discovery: four less known genes and their unknown interactions as highest-performed biomarkers for colorectal cancer

The goal of this study was to use a new interpretable machine-learning framework based on max-logistic competing risk factor models to identify a parsimonious set of differentially expressed genes (DEGs) that play a pivotal role in the development of colorectal cancer (CRC). Transcriptome data from nine public datasets were analyzed, and a new Chinese cohort was collected to validate the findings. The study discovered a set of four critical DEGs - CXCL8, PSMC2, APP, and SLC20A1 - that exhibit the highest accuracy in detecting CRC in diverse populations and ethnicities. Notably, PSMC2 and CXCL8 appear to play a central role in CRC, and CXCL8 alone could potentially serve as an early-stage marker for CRC. This work represents a pioneering effort in applying the max-logistic competing risk factor model to identify critical genes for human malignancies, and the interpretability and reproducibility of the results across diverse populations suggests that the four DEGs identified can provide a comprehensive description of the transcriptomic features of CRC. The practical implications of this research include the potential for personalized risk assessment and precision diagnosis and tailored treatment plans for patients.

Identification of SLC2A3 as a prognostic indicator correlated with the NF-κB/EMT axis and immune response in head and neck squamous cell carcinoma

SLC2A3 is an important member of the glucose transporter superfamily. It has been recently suggested that upregulation of SLC2A3 is associated with poor survival and acts as a prognostic marker in a variety of tumors. Unfortunately, the prognostic role of SLC2A3 in head and neck squamous cell carcinoma (HNSC) is less known. In the present study, we analyzed SLC2A3 expression in HNSC and its correlation with prognosis using TCGA and GEO databases. The results showed that SLC2A3 mRNA expression was higher in HNSC compared with adjacent normal tissues, which was validated with our 9 pairs of HNSC specimens. Moreover, high SLC2A3 expression predicted poor prognosis in HNSC patients. Mechanistically, GSEA revealed that high expression of SLC2A3 was enriched in epithelial-mesenchymal transition (EMT) and NF-κB signaling. In HNSC cell lines, SLC2A3 knockdown inhibited cell proliferation and migration. In addition, NF-κB P65 and EMT-related gene expression was suppressed upon SLC2A3 knockdown, indicating that SLC2A3 may play a preeminent role in the progression of HNSC through the NF-κB/EMT axis. Meanwhile, the expression of SLC2A3 was negatively correlated with immune cells, suggesting that SLC2A3 may be involved in the immune response in HNSC. The correlation between SLC2A3 expression and drug sensitivity was further assessed. In conclusion, our study demonstrated that SLC2A3 could predict the prognosis of HNSC patients and mediate the progression of HNSC via the NF-κB/EMT axis and immune responses.

Natural killer cell-related prognosis signature predicts immune response in colon cancer patients

Background: Natural killer (NK) cells are crucial components of the innate immune system that fight tumors and viral infections. Patients with colorectal cancer (CRC) have a poor prognosis, and immunotherapeutic tools play a key role in the treatment of CRC. Methods: Public data on CRC patients was collected from the TCGA and the GEO databases. Tissue data of CRC patients were collected from Guangxi Medical University Affiliated Cancer Hospital. An NK-related prognostic model was developed by the least absolute shrinkage and selection operator (LASSO) and Cox regression method. Validation data were collected from different clinical subgroups and an external independent validation cohort to verify the model's accuracy. In addition, multiple external independent immunotherapy datasets were collected to further examine the value of NK-related risk scores (NKRS) in the prediction of immunotherapy response. Potential biological functions of key genes were examined by methods of cell proliferation, apoptosis and Western blotting. Results: A novel prognostic model for CRC patients based on NK-related genes was developed and NKRS was generated. There was a significantly poorer prognosis among the high-NKRS group. Based on immune response prediction, patients with low NKRS may be more suitable for immunotherapy and they are more sensitive to immunotherapy. The proliferation rate of CRC cells was significantly reduced and apoptosis of CRC cells was increased after SLC2A3 was knocked down. SLC2A3 was also found to be associated with the TGF-β signaling pathway. Conclusion: NKRS has potential applications for predicting prognostic status and response to immunotherapy in CRC patients. SLC2A3 has potential as a therapeutic target for CRC.

Correlations between class I glucose transporter expression patterns and clinical outcomes in non-small cell lung cancer

BACKGROUND

Glucose transporters (GLUTs) are highly expressed in various cancers. However, the implications of these variable expression patterns are unclear. This study aimed to clarify the correlation between class I GLUT expression patterns and clinical outcomes in non-small cell lung cancer (NSCLC), including their potential role in inflammatory signaling.

METHODS

Biopsy tissues from 132 patients with NSCLC (92 adenocarcinomas [ADC] and 40 squamous cell carcinomas [SQCC]) were analyzed. mRNA expression levels of class I GLUTs (solute carrier 2A [SLC2A]1, SLC2A2, SLC2A3, and SLC2A4) and inflammation-related molecules (toll-like receptors TLR4, RelA/p65, and interleukins IL8 and IL6) were measured. Cellular localization of GLUT3 and GLUT4 was investigated using immunofluorescence.

RESULTS

Single, combined, and negative GLUT (SLC2A) expression were observed in 27/92 (29.3%), 27/92 (29.3%), and 38/92 (41.3%, p < 0.001) of ADC and 8/40 (20.0%), 29/40 (72.5%, p < 0.001), and 3/40 (7.5%) of SQCC, respectively. In ADC, the single SLC2A3-expressed group had a significantly poorer prognosis, whereas the single SLC2A4-expressed group had a significantly better prognosis. The combined expression groups showed no significant difference. SLC2A expression was not correlated with SQCC prognosis. SLC2A4 expression correlated with lower IL8 expression. GLUT3 and GLUT4 expressions were localized in the tumor cytoplasm.

CONCLUSIONS

In lung ADC, single SLC2A3 expression correlated with poor prognosis, whereas single SLC2A4 expression correlated with better prognosis and lower IL8 expression. GLUT3 expression, which is increased by IL8 overexpression, may be suppressed by increasing the expression of GLUT4 through decreased IL8 expression.

Establishment and validation of a ferroptosis-related signature predicting prognosis and immunotherapy effect in colon cancer

Background

Ferroptosis, a novel form of regulating cell death, is related to various cancers. However, the role of ferroptosis-related genes (FRGs) on the occurrence and development of colon cancer (CC) needs to be further elucidated.

Method

CC transcriptomic and clinical data were downloaded from TCGA and GEO databases. The FRGs were obtained from the FerrDb database. The consensus clustering was performed to identify the best clusters. Then, the entire cohort was randomly divided into the training and testing cohorts. Univariate Cox, LASSO regression and multivariate Cox analyses were used to construct a novel risk model in training cohort. The testing and the merged cohorts were performed to validate the model. Moreover, CIBERSORT algorithm analyze TIME between high- and low- risk groups. The immunotherapy effect was evaluated by analyzing the TIDE score and IPS between high- and low- risk groups. Lastly, RT-qPCR were performed to analyze the expression of the three prognostic genes, and the 2-years OS and DFS between the high- and low- risk groups of 43 clinical CC samples to further validate the value of the risk model.

Results

SLC2A3, CDKN2A, and FABP4 were identified to construct a prognostic signature. Kaplan-Meier survival curves showed that OS between the high- and low-risk groups were statistically significant (p_merged<0.001, p_training<0.001, p_testing<0.001). TIDE score and IPS were higher in the high-risk group (p_TIDE<0.005, p_Dysfunction<0.005, p_Exclusion<0.001, p_mAb-CTLA-4 = 3e-08, p_mAb-PD-1 = 4.1e-10). The clinical samples were divided into high- and low- risk groups according to the risk score. There was a statistical difference in DFS (p=0.0108).

Conclusion

This study established a novel prognostic signature and provided more insight into the immunotherapy effect of CC.

Crosstalk between Mesenchymal Stem Cells and Cancer Stem Cells Reveals a Novel Stemness-Related Signature to Predict Prognosis and Immunotherapy Responses for Bladder Cancer Patients

Mesenchymal stem cells (MSCs) and cancer stem cells (CSCs) maintain bladder cancer (BCa) stemness and facilitate the progression, metastasis, drug resistance, and prognosis. Therefore, we aimed to decipher the communication networks, develop a stemness-related signature (Stem. Sig.), and identify a potential therapeutic target. BCa single-cell RNA-seq datasets (GSE130001 and GSE146137) were used to identify MSCs and CSCs. Pseudotime analysis was performed by Monocle. Stem. Sig. was developed by analyzing the communication network and gene regulatory network (GRN) that were decoded by NicheNet and SCENIC, respectively. The molecular features of the Stem. Sig. were evaluated in TCGA-BLCA and two PD-(L)1 treated datasets (IMvigor210 and Rose2021UC). A prognostic model was constructed based on a 101 machine-learning framework. Functional assays were performed to evaluate the stem traits of the hub gene. Three subpopulations of MSCs and CSCs were first identified. Based on the communication network, the activated regulons were found by GRN and regarded as the Stem. Sig. Following unsupervised clustering, two molecular subclusters were identified and demonstrated distinct cancer stemness, prognosis, immunological TME, and response to immunotherapy. Two PD-(L)1 treated cohorts further validated the performance of Stem. Sig. in prognosis and immunotherapeutic response prediction. A prognostic model was then developed, and a high-risk score indicated a poor prognosis. Finally, the hub gene SLC2A3 was found exclusively upregulated in extracellular matrix-related CSCs, predicting prognosis, and shaping an immunosuppressive tumor microenvironment. Functional assays uncovered the stem traits of SLC2A3 in BCa by tumorsphere formation and western blotting. The Stem. Sig. derived from MSCs and CSCs can predict prognosis and response to immunotherapy for BCa. Besides, SLC2A3 may serve as a promising stemness target facilitating cancer effective management.

Identification of Gene Signature-Related Oxidative Stress for Predicting Prognosis of Colorectal Cancer

Background

Colorectal cancer (CRC) is the third most common cancer. Nearly a decade of studies had shown that cancer regimens tailored to molecular and pathological features lead to improved overall survival. Oxidative stress (OS) refers to a state in which oxidation and antioxidant effects are unbalanced in the body. However, the molecular mechanism of OS-related CRC remains unclear.

Methods

Univariate Cox regression analysis gained OS signature genes related to CRC prognosis, and then, different CRC molecular subtypes were obtained by consensus clustering analysis. Differential expression analysis and least absolute shrinkage and selection operator (LASSO) algorithm were used to obtain prognostic-related signature genes. Significantly, risk score was calculated by RiskScore = Σβi × Expi. Moreover, the Kaplan-Meier survival analysis, immune cell infiltration, and sensitivity to treatment regimens were performed to assess the model's validity and adaptability. Finally, RiskScore incorporated clinicopathological features to further improve prognostic models and survival prediction.

Results

63 OS-related prognostic genes were obtained, and four distinct molecular subtypes of CRC were identified based on the expression characteristics. 230 differentially expressed genes (DEGs) between different molecular subtypes were compressed by LASSO algorithm, and finally, 6 OS-related genes were obtained. The Kaplan-Meier survival analysis indicated that the high RiskScore groups had poorer prognosis and the RiskScore model showed better predictive performance in all three other independent datasets. Moreover, immunotherapy/chemosensitivity analysis found that the low-risk group was more sensitive to different treatment options and could achieve better treatment outcomes.

Conclusion

Oxidative stress-related RiskScore model built in this work has good predictive performance for CRC.

The connection between innervation and metabolic rearrangements in pancreatic cancer through serine

Pancreatic cancer is a kind of aggressive tumor famous for its lethality and intractability, and pancreatic ductal adenocarcinoma is the most common type. Patients with pancreatic cancer often suffer a rapid loss of weight and abdominal neuropathic pain in their early stages and then go through cachexia in the advanced stage. These features of patients are considered to be related to metabolic reprogramming of pancreatic cancer and abundant nerve innervation responsible for the pain. With increasing literature certifying the relationship between nerves and pancreatic ductal adenocarcinoma (PDAC), more evidence point out that innervation's role is not limited to neuropathic pain but explore its anti/pro-tumor functions in PDAC, especially the neural-metabolic crosstalks. This review aims to unite pancreatic cancer's innervation and metabolic rearrangements with terminated published articles. Hopefully, this article could explore the pathogenesis of PDAC and further promote promising detecting or therapeutic measurements for PDAC according to the lavish innervation in PDAC.

Development and validation of prognostic models for colon adenocarcinoma based on combined immune-and metabolism-related genes

Background

The heterogeneity of tumor tissue is one of the reasons for the poor effect of tumor treatment, which is mainly affected by the tumor immune microenvironment and metabolic reprogramming. But more research is needed to find out how the tumor microenvironment (TME) and metabolic features of colon adenocarcinoma (COAD) are related.

Methods

We obtained the transcriptomic and clinical data information of COAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering analysis was used to identify different molecular subtypes, identify differentially expressed genes (DEGs) associated with immune-and metabolism-related genes (IMRGs) prognosis. Univariate and multivariable Cox regression analysis and Lasso regression analysis were applied to construct the prognostic models based on the IMRG risk score. The correlations between risk scores and TME, immune cell infiltration, and immune checkpoint genes were investigated. Lastly, potential appropriate drugs related to the risk score were screened by drug sensitivity analysis.

Results

By consensus clustering analysis, we identified two distinct molecular subtypes. It was also found that the multilayered IMRG subtypes were associated with the patient's clinicopathological characteristics, prognosis, and TME cell infiltration characteristics. Meanwhile, a prognostic model based on the risk score of IMRGs was constructed and its predictive power was verified internally and externally. Clinicopathological analysis and nomogram give it better clinical guidance. The IMRG risk score plays a key role in immune microenvironment infiltration. Patients in the high-risk groups of microsatellite instability (MSI) and tumor mutational burden (TMB) were found to, although with poor prognosis, actively respond to immunotherapy. Furthermore, IMRG risk scores were significantly associated with immune checkpoint gene expression. The potential drug sensitivity study helps come up with and choose a chemotherapy treatment plan.

Conclusion

Our comprehensive analysis of IMRG signatures revealed a broad range of regulatory mechanisms affecting the tumor immune microenvironment (TIME), immune landscape, clinicopathological features, and prognosis. And to explore the potential drugs for immunotherapy. It will help to better understand the molecular mechanisms of COAD and provide new directions for disease treatment.

Molecular mechanism(s) of regulations of cancer stem cell in brain cancer propagation

Brain tumors are most often diagnosed with solid neoplasms and are the primary reason for cancer-related deaths in both children and adults worldwide. With recent developments in the progression of novel targeted chemotherapies, the prognosis of malignant glioma remains dismal. However, the high recurrence rate and high mortality rate remain unresolved and are closely linked to the biological features of cancer stem cells (CSCs). Research on tumor biology has reached a new age with more understanding of CSC features. CSCs, a subpopulation of whole tumor cells, are now regarded as candidate therapeutic targets. Therefore, in the diagnosis and treatment of tumors, recognizing the biological properties of CSCs is of considerable significance. Here, we have discussed the concept of CSCs and their significant role in brain cancer growth and propagation. We have also discussed personalized therapeutic development and immunotherapies for brain cancer by specifically targeting CSCs.

Genomic Effect of DNA Methylation on Gene Expression in Colorectal Cancer

Simple Summary

Abnormal DNA methylation is known to regulate gene expression, and its features have been frequently observed in colorectal cancer (CRC) patients. In addition, alterations in DNA methylation can be proposed as biomarkers for cancer prognosis, as they occur in the early stage of carcinogenesis. Although numerous studies have attempted to shed light on the impacts of DNA methylation on gene expression, it is still unclear which specific regions regulate gene expression and how they are associated with patient survival. In this study, we elucidated the intricate relationship between DNA methylation and gene expression. Furthermore, we found genes that were influenced by DNA methylation and were associated with survival; these genes were mainly enriched in immune-related pathways.

Abstract

The aberrant expression of cancer-related genes can lead to colorectal cancer (CRC) carcinogenesis, and DNA methylation is one of the causes of abnormal expression. Although many studies have been conducted to reveal how DNA methylation affects transcription regulation, the ways in which it modulates gene expression and the regions that significantly affect DNA methylation-mediated gene regulation remain unclear. In this study, we investigated how DNA methylation in specific genomic areas can influence gene expression. Several regression models were constructed for gene expression prediction based on DNA methylation. Among these models, ElasticNet, which had the best performance, was chosen for further analysis. DNA methylation near transcription start sites (TSS), especially from 2 kb upstream to 7 kb downstream of TSS, had an essential regulatory role in gene expression. Moreover, methylation-affected and survival-associated genes were compiled and found to be mainly enriched in immune-related pathways. This study investigated genomic regions in which methylation changes can affect gene expression. In addition, this study proposed that aberrantly expressed genes due to DNA methylation can lead to CRC pathogenesis by the immune system.

Comprehensive Analysis of the Role of SLC2A3 on Prognosis and Immune Infiltration in Head and Neck Squamous Cell Carcinoma

Background. SLC2A3 is upregulated in various cancer types and promotes proliferation, invasion, and metabolism. However, its role in the prognosis and immune regulation of head and neck squamous cell carcinoma (HNSCC) is still obscure. This study is aimed at exploring the prognostic and immunotherapeutic potential of SLC2A3 in HNSCC. Methods. All data were downloaded from TCGA database and integrated via R software. SLC2A3 expression was evaluated using R software, TIMER, CPTAC, and HPA databases. The association between SLC2A3 expression and clinicopathologic characteristics was assessed by R software. The effect of SLC2A3 on survival was analyzed by R software and Kaplan-Meier Plotter. Genomic alterations in SLC2A3 were investigated using the cBioPortal database. Coexpression of SLC2A3 was studied using LinkedOmics and STRING, and enrichment analyses were performed with R software. The relationship between SLC2A3 expression and immune infiltration was determined using TIMER and TISIDB databases. Immune checkpoints and ESTIMATE score were analyzed via the SangerBox database. Results. SLC2A3 expression was upregulated in HNSCC tissues compared to normal tissues. It was significantly related to TNM stage, histological grade, and alcohol history. High SLC2A3 expression was associated with poor prognosis in HNSCC. Coexpression analysis indicated that SLC2A3 mostly participated in the HIF-1 signaling pathway and glycolysis. Furthermore, SLC2A3 expression strongly correlated with tumor-infiltrating lymphocytes in HNSCC. Conclusion. SLC2A3 could serve as a potential prognostic biomarker for tumor immune infiltration in HNSCC.

Identification of molecular mechanism and key biomarkers in membranous nephropathy by bioinformatics analysis

OBJECTIVES

Membranous nephropathy (MN) is an autoimmune nephropathy. The incidence of MN is increasing gradually in recent years. Previous studies focused on antibody production, complement activation and podocyte injury in MN. However, the etiology and underlying mechanism of MN remain to be further studied.

METHODS

GSE104948 and GSE108109 of glomerular expression profile were downloaded from Gene Expression Omnibus (GEO) database, GSE47184, GSE99325, GSE104954, GSE108112, GSE133288 of renal tubule expression profile, and GSE73953 of peripheral blood mononuclear cells (PBMCs) expression profile. After data integration by Networkanalyst, differentially expressed genes (DEGs) between MN and healthy samples were obtained. DEGs were enriched in gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG), and protein-protein interaction (PPI) networks of these genes were constructed through Metascape, etc. We further understood the function of hub genes through gene set enrichment analysis (GSEA). The diagnostic value of DEGs in MN was evaluated by receiver operating characteristic (ROC) analysis.

RESULTS

A total of 3 genes (TP53, HDAC5, and SLC2A3) were screened out. Among them, the up-regulated TP53 expression may be closely related to MN renal pathological changes. However, the expression of MN podocyte target antigen was not significantly different from that of healthy controls. In addition, the changes of Wnt signaling pathway in PBMCs and the effects of SLC2A3 on the differentiation of M2 monocyte need further study.

CONCLUSION

It is difficult to unify a specific mechanism for the changes of glomerulus, renal tubules and PBMCs in MN patients. This may be related to the pathogenesis, pathology and immune characteristics of MN. MN podocyte target antigen may not be the root cause of the disease, but a stage result in the pathogenesis process.

Construction of a combined hypoxia and EMT index for head and neck squamous cell carcinoma

Objectives: In head and neck squamous cell carcinoma (HNSCC), the interaction between epithelial-mesenchymal transformation (EMT) and hypoxia has been confirmed, and corresponding treatment methods have been investigated. Few studies have examined its combined effects and its potential clinical use, however. As a result, we developed a new scoring system based on EMT and hypoxia.

Methods: We combined 200 hypoxia-related genes with 1184 EMT-related genes and finally constructed a score risk model containing 14 characteristic factors named the comprehensive index of EMT and hypoxia (CIEH) by the Lasso-Cox regression and univariate Cox regression method, which is used to predict prognosis and to guide treatment planning in HNSCC patients. Furthermore, we examined HNSCC expression of CIEH-related genes using the human protein atlas database.

Results: Based on survival analysis results, CIEH value had a high prognostic value in HNSCC patients, a high CIEH value carries a poor prognostic significance in HNSCC. It is noteworthy that the CIEH value was correlated with tumor immune infiltration. Moreover, the CIEH had significant differences in age, stage, N, laterality, and peripheral nerve invasion, and that the CIEH could be an independent prognostic factor.

Conclusions: This study constructed a CIEH model containing 14 characteristic factors, including hypoxia-related genes and EMT genes, that may be able to serve as potential biomarkers for HNSCC. According to the 14 characteristic factors in the CIEH model, a diagnostic kit can be packaged in the future to evaluate the survival of patients before tumor surgery and guide the subsequent treatment plan.

Prognostic value of the ferroptosis-related gene SLC2A3 in gastric cancer and related immune mechanisms

SLC2A3 is a ferroptosis marker engaged in transmembrane glucose transport. However, the effect of SLC2A3 on the prognosis of patients with cancer remains unclear. This study aimed to explore the prognostic implications of SLC2A3 and its underlying immune mechanisms in gastric cancer. The mRNA expression profiles and corresponding clinical data of patients with gastric cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Differentially expressed genes related to SLC2A3 were identified using the R package “limma.” Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, gene set enrichment analysis, and gene set variation analysis were used to explore the underlying mechanisms. The protein–protein and miRNA interaction networks were analyzed using Cytoscape software. Immune cell infiltration was assessed using single-sample gene set enrichment analysis. Univariate and multivariate Cox regression analyses revealed the relationship between SLC2A3 expression and prognosis. SLC2A3 was found to be highly expressed in tumor tissues and was associated with an unfavorable prognosis in patients with gastric cancer. Functional enrichment analysis showed that SLC2A3 is related to cytokine–cytokine receptor interaction, epithelial–mesenchymal transition, T cell receptor signaling pathway, B cell receptor signaling pathway, and immune checkpoints. SLC2A3 is also involved in immune response regulation and is regulated by multiple miRNAs, including miR-195-5p, miR-106a-5p, miR-424-5p, and miR-16-5p. Univariate and multivariate Cox regression analyses indicated that SLC2A3 can be used as an independent prognostic factor for predicting the outcome in patients with gastric cancer. SLC2A3 and related miRNAs are potential prognostic biomarkers and therapeutic targets.

Integration of Bulk RNA Sequencing and Single-Cell RNA Sequencing to Reveal Uveal Melanoma Tumor Heterogeneity and Cells Related to Survival

Molecular classification based on transcriptional characteristics is often used to study tumor heterogeneity. Human cancer has different cell populations with distinct transcription in tumors, and their heterogeneity is the focus of tumor therapy. Our purpose was to explore the tumor heterogeneity of uveal melanoma (UM) through RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq). Based on the consensus clustering assays of the prognosis-related immune gene set, the immune subtype (IS) of UM and its corresponding immune characteristics were comprehensively analyzed. The heterogeneous cell groups and corresponding marker genes of UM were identified from GSE138433 using scRNA-seq analysis. Pseudotime trajectory analysis and SCENIC analysis were conducted to explore the trajectory of cell differentiation and the regulatory network of single-cell transcription factors (TFs). Based on 37 immune gene sets, UM was divided into two different immune subtypes (IS1 and IS2). The two kinds of ISs have different characteristics in prognosis, immune-related molecules, immune score, and immune cell infiltration. According to 11,988 cells of scRNA-seq data from six UM samples, 11 cell clusters and 10 cell types were identified. The subsets of C1, C4, C5, C8, and C9 were related to the prognosis of UM, and different TF–target gene regulatory networks were involved. These five cell subsets differentiated into 3 different states. Our results provided valuable information about the heterogeneity of UM tumors and the expression patterns of TFs in different cell types.

Identification of a Solute Carrier Family-Based Signature for Predicting Overall Survival in Osteosarcoma

Given the important role of SLC family in essential physiological processes including nutrient uptake, ion transport, and waste removal, and that their dysregulation was found in distinct forms of cancer, here we identified a novel gene signature of SLC family for patient risk stratification in osteosarcoma. Gene expression data and relevant clinical materials of osteosarcoma samples were retrieved from The Cancer Genome Atlas (TCGA) database. Prognosis-related SLC genes were identified by performing univariate Cox regression analysis and were utilized to construct a four-SLC gene signature in osteosarcoma. It allowed patients to be classified into high- and low-risk groups, and Kaplan-Meier survival analysis in the training, testing, entire, and external GSE21257 cohorts suggested that the overall survival of patients in high-risk group was consistently worse than that in low-risk group, suggesting the promising accuracy and generalizability of the SLC-based signature in predicting the prognosis of patients with osteosarcoma. Moreover, univariate and multivariate Cox regression analyses indicated that the derived risk score was the only independent prognostic factor for osteosarcoma patients in TCGA and GSE21257 cohorts. Besides, a prognostic nomogram comprising the derived risk score and clinical features including gender and age was developed for clinical decision-making. Functional enrichment analyses of the differentially expressed genes between high- and low-risk group revealed that immune-related biological processes and pathways were significantly enriched. Estimation of tumor immune microenvironment using ESTIMATE algorithm revealed that patients with lower risk score had higher stromal, immune, and ESTIMATE score, and lower tumor purity. ssGSEA analyses indicated that the scores of various immune subpopulations including CD8+ T cells, DCs, and TIL were lower in high-risk group than these in low-risk group in both cohorts. As for the related immune functions, the scores of APC co-inhibition, CCR, check-point, T cell co-stimulation, and Type II IFN response were lower in high-risk group than these in low-risk group in both cohorts. In all, we identified a novel prognostic signature based on four SLC family genes that accurately predicted overall survival in osteosarcoma patients. Furthermore, the signature is linked to differences in immunological status and immune cell infiltrations in the tumor microenvironment.

Exploring the Role of Metabolites in Cancer and the Associated Nerve Crosstalk

Since Otto Warburg's first report on the increased uptake of glucose and lactate release by cancer cells, dysregulated metabolism has been acknowledged as a hallmark of cancer that promotes proliferation and metastasis. Over the last century, studies have shown that cancer metabolism is complex, and by-products of glucose and glutamine catabolism induce a cascade of both pro- and antitumorigenic processes. Some vitamins, which have traditionally been praised for preventing and inhibiting the proliferation of cancer cells, have also been proven to cause cancer progression in a dose-dependent manner. Importantly, recent findings have shown that the nervous system is a key player in tumor growth and metastasis via perineural invasion and tumor innervation. However, the link between cancer-nerve crosstalk and tumor metabolism remains unclear. Here, we discuss the roles of relatively underappreciated metabolites in cancer-nerve crosstalk, including lactate, vitamins, and amino acids, and propose the investigation of nutrients in cancer-nerve crosstalk based on their tumorigenicity and neuroregulatory capabilities. Continued research into the metabolic regulation of cancer-nerve crosstalk will provide a more comprehensive understanding of tumor mechanisms and may lead to the identification of potential targets for future cancer therapies.

Identification of metastasis-associated exoDEPs in colorectal cancer using label-free proteomics

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Exosomes play essential role in the metastasis of colorectal cancer from TME aspect.

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Finding out the prominent regulating exoDEPs by label-free proteomics in this research provided a lot of key information of CRC metastases.

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Metabolism, cytoskeleton-related pathways and immunosuppression are two key mechanisms by which exosomes regulate CRC malignant behavior.

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The discovery of the “all or none” exoDEPs was of great significance. The exoDEPs expressed only in SW620 cells can more clearly show their ability to promote the invasion and metastasis of CRC cells.

Exosomes are secreted nanovesicles consisting of biochemical molecules, including proteins, RNAs, lipids, and metabolites that play a prominent role in tumor progression. In this study, we performed a label-free proteomic analysis of exosomes from a pair of homologous human colorectal cancer cell line with different metastatic abilities. A total of 115 exoDEPs were identified, with 31 proteins upregulated and 84 proteins downregulated in SW620 exosome. We also detected 30 proteins expressed only in SW620 exosomes and 60 proteins expressed only in SW480 exosomes. Bioinformatics analysis enriched the components and pathways associated with the extracellular matrix, cytoskeleton-related pathways, and immune system changes of colorectal cancer (CRC). Cellular function experiments confirmed the role of SW620 exosomes in promoting the proliferation, migration, and invasion of SW480 cells. Further verifications were performed on six upregulated exoDEPs (FGFBP1, SIPA1, THBS1, TGFBI, COL6A1, and RPL10), three downregulated exoDEPs (SLC2A3, MYO1D, and RBP1), and three exoDEPs (SMOC2, GLG1, and CEMIP) expressed only in SW620 by WB and IHC. This study provides a complete and novel basis for exploring new drug targets to inhibit the invasion and metastasis of CRC.

Angiopoietin-like 4 promotes glucose metabolism by regulating glucose transporter expression in colorectal cancer

PURPOSE

Angiopoietin-like 4 (ANGPTL4) was recently shown to be associated with cancer progression but little is known about its contribution to cancer metabolism. The purpose of this study was to elucidate the role of ANGPTL4 in glucose metabolism in colorectal cancer (CRC).

METHODS

Immunohistochemical staining of CRC specimens classified 84 patients into two groups according to ANGPTL4 expression. Clinicopathological characteristics, gene mutation status obtained by next-generation sequencing, and fluorodeoxyglucose (FDG) uptake measured by positron emission tomography/computed tomography (PET/CT) were compared between the two groups. Furthermore, the impact of ANGPTL4 expression on cancer metabolism was investigated by a subcutaneous xenograft mouse model using the ANGPTL4 knockout CRC cell line, and glucose transporter (GLUT) expression was evaluated.

RESULTS

There were significantly more cases of T3/4 tumours (94.3% vs. 57.1%, P < 0.001) and perineural invasion (42.9% vs. 22.4%, P = 0.046) in the ANGPTL4-high group than in the low group. Genetic exploration revealed a higher frequency of KRAS mutation (54.3% vs. 22.4%, P = 0.003) in the ANGPTL4-high tumours. All the FDG uptake parameters were significantly higher in ANGPTL4-high tumours. In vivo analysis showed a significant reduction in tumour size due to ANGPTL4 knockout with lower expression of GLUT1 and GLUT3, and suppression of AKT phosphorylation.

CONCLUSION

ANGPTL4 regulates the expression of GLUTs by activating the PI3K-AKT pathway and thereby promoting glucose metabolism in CRC. These findings establish a new functional role of ANGPTL4 in cancer progression and lay the foundation for developing a novel therapeutic target.

A Novel Prognostic Model Based on Ferroptosis-Related Gene Signature for Bladder Cancer

Background

Bladder cancer (BC) is a molecular heterogeneous malignant tumor; the treatment strategies for advanced-stage patients were limited. Therefore, it is vital for improving the clinical outcome of BC patients to identify key biomarkers affecting prognosis. Ferroptosis is a newly discovered programmed cell death and plays a crucial role in the occurrence and progression of tumors. Ferroptosis-related genes (FRGs) can be promising candidate biomarkers in BC. The objective of our study was to construct a prognostic model to improve the prognosis prediction of BC.

Methods

The mRNA expression profiles and corresponding clinical data of bladder urothelial carcinoma (BLCA) patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. FRGs were identified by downloading data from FerrDb. Differential analysis was performed to identify differentially expressed genes (DEGs) related to ferroptosis. Univariate and multivariate Cox regression analyses were conducted to establish a prognostic model in the TCGA cohort. BLCA patients from the GEO cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were used to explore underlying mechanisms.

Results

Nine genes (ALB, BID, FADS2, FANCD2, IFNG, MIOX, PLIN4, SCD, and SLC2A3) were identified to construct a prognostic model. Patients were classified into high-risk and low-risk groups according to the signature-based risk score. Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) survival analysis confirmed the superior predictive performance of the novel survival model based on the nine-FRG signature. Multivariate Cox regression analyses showed that risk score was an independent risk factor associated with overall survival (OS). GO and KEGG enrichment analysis indicated that apart from ferroptosis-related pathways, immune-related pathways were significantly enriched. ssGSEA analysis indicated that the immune status was different between the two risk groups.

Conclusion

The results of our study indicated that a novel prognostic model based on the nine-FRG signature can be used for prognostic prediction in BC patients. FRGs are potential prognostic biomarkers and therapeutic targets.

A Prognosis Marker SLC2A3 Correlates With EMT and Immune Signature in Colorectal Cancer

SLC2A3 is a membrane transporter that belongs to the solute carrier family, whose function includes transmembrane transport and glucose transmembrane transport activity. To clarify the expression and role of SLC2A3 in colorectal cancer (CRC), we analyzed the TCGA and GEO databases and found that SLC2A3 mRNA levels were significantly higher in CRC tissues than that in adjacent non-tumor tissues. Furthermore, high expression of SLC2A3 predicted poor overall survival and disease free survival for CRC patients. For validation, we collected 174 CRC samples and found that SLC2A3 expression was higher in CRC tissues than that in adjacent non-tumor colorectal mucosa tissues by immunohistochemistry staining. Further study showed that high expression of SLC2A3 was enriched in epithelial–mesenchymal transition (EMT) classical pathway, interferon-γ pathway by GSEA analysis enrichment, indicating that SLC2A3 may play a key role in the progression of CRC through EMT and immune response, which also has been validated by the global gene expression profiling of human CRC cell lines. The expression of SLC2A3 was positively correlated with CD4 and CD8+T cells by using TIMER and EPIC algorithm, respectively. SLC2A3 knockdown suppressed migration and inhibited the expression of Vimentin and MMP9 in CRC cell line SW480 and RKO. Meanwhile, PD-L1 expression was also significantly attenuated in SW480 and RKO cells transfected with SLC2A3 siRNA. The result suggests that SLC2A3 may be involved in the immune response of CRC by regulating PD-L1 immune checkpoint. In our series, SLC2A3 and PD-L1 positive expression was 74% (128/174) and 22% (39/174) of CRC, respectively. SLC2A3 expression was significantly associated with perineural invasion in CRC patients. In conclusion, SLC2A3 may play an important role in progression of CRC by regulating EMT and PD-L1 mediated immune responses.

Identification and validation of a hypoxia-related prognostic and immune microenvironment signature in bladder cancer

Background

Bladder cancer is the leading causes of cancer-associated mortality and seriously affects population health. Hypoxia plays a key role in tumor development and immune escape, which contributes to malignant behaviors.

Methods

In this study, we analyzed the RNA-seq and clinical information of bladder cancer patients from The Cancer Genome Atlas (TCGA) database. To investigate the hypoxia-related prognostic and immune microenvironment in bladder cancer, we constructed a hypoxia-related risk model for overall survival (OS). The RNA-seq and clinical data of bladder cancer patients from the Gene Expression Omnibus (GEO) database were used as validation sets.

Results

The hypoxia-related risk signature was significantly correlated with clinical outcomes and could independently predict OS outcomes. Furthermore, the hypoxia-related risk signature could effectively reflected the levels of immune cell type fractions and the expression of critical immune checkpoint genes were higher in the high-risk group compared to the low-risk group. We also validated the expression levels of the prognostic genes in bladder cancer and paracancerous tissue samples through qRT-PCR analysis.

Conclusion

We established a 7 hypoxia-related gene (HRG) signature that can be used as an independent clinical predictor and provided a potential mechanism in bladder cancer immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01954-4.

A Novel Analysis Method for Evaluating the Interplay of Oxygen and Ionizing Radiation at the Gene Level

Whilst the impact of hypoxia and ionizing radiations on gene expression is well-understood, the interplay of these two effects is not. To better investigate this aspect at the gene level human bladder, brain, lung and prostate cancer cell lines were irradiated with photons (6 Gy, 6 MV LINAC) in hypoxic and normoxic conditions and prepared for the whole genome analysis at 72 h post-irradiation. The analysis was performed on the obtained 20,000 genes per cell line using PCA and hierarchical cluster algorithms to extract the most dominant genes altered by radiation and hypoxia. With the help of the introduced novel radiation-in-hypoxia and oxygen-impact profiles, it was possible to overcome cell line specific gene regulation patterns. Based on that, 37 genes were found to be consistently regulated over all studied cell lines. All DNA-repair related genes were down-regulated after irradiation, independently of the oxygen state. Cell cycle-dependent genes showed up-regulation consistent with an observed change in cell population in the S and G2/M phases of the cell cycle after irradiation. Genes behaving oppositely in their regulation behavior when changing the oxygen concentration and being irradiated, were immunoresponse and inflammation related genes. The novel analysis method, and by consequence, the results presented here have shown how it is important to consider the two effects together (oxygen and radiation) when analyzing gene response upon cancer radiation treatment. This approach might help to unrevel new gene patterns responsible for cancer radioresistance in patients.

RGL2 as an age-dependent factor regulates colon cancer progression

Colon cancer is the fourth leading cause of cancer-related death, and exhibited clinical differences among patients of different ages, including malignancy, metastasis, and mortality rate. Few studies, however, focus on the communications between aging and colon cancer. Here we identified age-dependent differentially expressed genes (DEGs) in colon cancer using TCGA transcriptome data. Through analyzing multi-omics high throughput data, including ATAC-Seq, DNaseI-Seq and ChIP-Seq, we obtained six age-dependent transcription factors in colon cancer, and their age-dependent targets, significantly affecting patients' overall survivals. Transcription factor ETS1 potentially functioned in both aging process and colon cancer progression through regulating its targets, RGL2 and SLC2A3. In addition, comparing with its relative lower expression levels in elderly patients, higher levels of RGL2 were detected in young patients, and significantly associated with larger tumor size, higher metastasis, and invasions of colon cancer, consistent with the clinical traits that young patients' colon cancer exhibited late stages with more aggressiveness. Thus, these elements may serve as keys linking aging and colon cancer, and providing new insights and basis for mechanism researches, as well as diagnosis and therapies of colon cancer, especially in young patients.

Blocking Aerobic Glycolysis by Targeting Pyruvate Dehydrogenase Kinase in Combination with EGFR TKI and Ionizing Radiation Increases Therapeutic Effect in Non-Small Cell Lung Cancer Cells

Simple Summary

Non-small cell lung cancer (NSCLC) patients harboring oncogenic mutations in the epidermal growth factor receptor (EGFR) inevitably develop resistance to targeted EGFR tyrosine kinase inhibitors (TKI) therapy. To support malignant features associated with cancer development and therapy resistance, the cancer cells adapt their metabolic rate and pathways. As an example, aerobic glycolysis, where the cells use glycolysis in the presence of oxygen, is frequently seen. Here we show that targeting aerobic glycolysis represents a promising strategy in cancer therapeutics.

Abstract

Increased glycolytic activity is a hallmark of cancer initiation and progression and is often observed in non-small cell lung cancer (NSCLC). Pyruvate dehydrogenase (PDH) complex acts as a gatekeeper between glycolysis and oxidative phosphorylation, and activation of PDH is known to inhibit glycolytic activity. As part of a standard therapeutic regimen, patients with NSCLC harboring oncogenic mutations in the epidermal growth factor receptor (EGFR) are treated with EGFR tyrosine kinase inhibitors (EGFR TKIs). Independent of good initial response, development of resistance to this therapy is inevitable. In the presented work, we propose that inhibition of glycolysis will add to the therapeutic effects and possibly prevent development of resistance against both EGFR TKIs and ionizing radiation in NSCLC. Analysis of transcriptome data from two independent NSCLC patient cohorts identified increased expression of pyruvate dehydrogenase kinase 1 (PDHK1) as well as upregulated expression of genes involved in glucose metabolism in tumors compared to normal tissue. We established in vitro models of development of resistance to EGFR TKIs to study metabolism and determine if targeting PDHK would prevent development of resistance to EGFR TKIs in NSCLC cells. The PDHK1 inhibitor dichloroacetate (DCA) in combination with EGFR TKIs and/or ionizing radiation was shown to increase the therapeutic effect in our NSCLC cell models. This mechanism was associated with redirected metabolism towards pyruvate oxidation and reduced lactate production, both in EGFR TKI sensitive and resistant NSCLC cells. Using DCA, the intracellular pool of pyruvate available for lactic fermentation becomes limited. Consequently, pyruvate is redirected to the mitochondria, and reinforces mitochondrial activity. Addition of DCA to cell culture deacidifies the extracellular microenvironment as less lactate is produced and excreted. In our study, we find that this redirection of metabolism adds to the therapeutic effect of EGFR TKI and ionizing radiation in NSCLC.

Long Non-coding RNA LINC01094 Promotes the Development of Clear Cell Renal Cell Carcinoma by Upregulating SLC2A3 via MicroRNA-184

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC. Compelling evidence has highlighted the crucial role of long non-coding RNA (lncRNA) in ccRCC. Our current study aims to explore the regulatory mechanism of LINC01094 in the development of ccRCC. Dual-luciferase reporter experiment verified the targeting relationship among miR-184, LINC01094, and SLC2A3. Furthermore, the interaction between LINC01094 and miR-184 was confirmed by RNA immunoprecipitation (RIP) and RNA pull-down. Biological behaviors of ccRCC cells were investigated through cell counting kit-8 (CCK8), scratch test, Transwell, and flow cytometry. The effect of SLC2A3 on the tumorigenicity of nude mice was evaluated in vivo. In ccRCC cells and clinical tissues, LINC01094 and SLC2A3 were highly expressed while miR-184 was lowly expressed. Besides, miR-184 was verified to be a direct target of LINC01094. Silencing LINC01094, up-regulating miR-184, or reducing SLC2A3 inhibited the growth, migration, and invasion of ccRCC cells. Tumor growth was suppressed by silenced LINC01215 via reducing the expression of SLC2A3 via miR-184. Taken together, silencing LINC01094 inhibited SLC2A3 expression by up-regulating miR-184, thereby inhibiting the development of ccRCC.

Identification of ATP8B1 as a Tumor Suppressor Gene for Colorectal Cancer and Its Involvement in Phospholipid Homeostasis

Homeostasis of membrane phospholipids plays an important role in cell oncogenesis and cancer progression. The flippase ATPase class I type 8b member 1 (ATP8B1), one of the P4-ATPases, translocates specific phospholipids from the exoplasmic to the cytoplasmic leaflet of membranes. ATP8B1 is critical for maintaining the epithelium membrane stability and polarity. However, the prognostic values of ATP8B1 in colorectal cancer (CRC) patients remain unclear. We analyzed transcriptomics, genomics, and clinical data of CRC samples from The Cancer Genome Atlas (TCGA). ATP8B1 was the only potential biomarker of phospholipid transporters in CRC. Its prognostic value was also validated with the data from the Gene Expression Omnibus (GEO). Compared to the normal group, the expression of ATP8B1 was downregulated in the tumor group and the CRC cell lines, which declined with disease progression. The lower expression level of ATP8B1 was also significantly associated with worse survival outcomes in both the discovery samples (359 patients) and the validation samples (566 patients). In multivariate analyses, low ATP8B1 levels predicted unfavorable OS (adjusted HR 1.512, 95% CI: 1.069-2.137; P = 0.019) and were associated with poor progress-free interval (PFI) (adjusted HR: 1.62, 95% CI: 1.207-2.174; P = 0.001). The pathway analysis results showed that the underexpression of ATP8B1 was negatively associated with phospholipid transport, phospholipid metabolic process, and cell-cell adherent junction and positively associated with the epithelial-mesenchymal transition in CRC. Our analysis suggests that ATP8B1 is a potential cancer suppressor in CRC patients and may offer new strategies for CRC therapy.

SLC2A3 promotes macrophage infiltration by glycolysis reprogramming in gastric cancer

Background

Tumors display a high rate of glucose metabolism and the SLC2A (also known as GLUT) gene family may be central regulators of cellular glucose uptake. However, roles of SLC2A family in mechanism of metabolite communication with immunity in gastric cancer remains unknown.

Methods

Bioinformatics analysis and IHC staining were used to reveal the expression of SLC2A3 in gastric cancer and the correlation with survival prognosis. Real-time PCR, western blots, OCR, ECAR, lactate production and glucose uptake assays were applied to determine the effect of SLC2A3 on glycolysis reprogramming. We then investigated the consequences of SLC2A3 upregulation or inhibition on aerobic glycolysis, also explored the underlying mechanism. Bioinformatics analysis and in vitro and in vivo research were used to reveal the role of SLC2A3 in macrophage infiltration and transition.

Results

Here, we show that SLC2A3 acts as a tumor promoter and accelerates aerobic glycolysis in GC cells. Mechanistically, the SLC2A3-STAT3-SLC2A3 feedback loop could promote phosphorylation of the STAT3 signaling pathway and downstream glycolytic targeting genes. Moreover, SLC2A3 potentially contributes to M2 subtype transition of macrophage infiltration in the GC microenvironment.

Conclusions

SLC2A3 could be used as a prognostic biomarker to determine prognosis and immune infiltration in GC and may provide an intervention strategy for GC therapy.

Development of an Immune Infiltration-Related Eight-Gene Prognostic Signature in Colorectal Cancer Microenvironment

Objective

Stromal cells and immune cells have important clinical significance in the microenvironment of colorectal cancer (CRC). This study is aimed at developing a CRC gene signature on the basis of stromal and immune scores.

Methods

A cohort of CRC patients (n = 433) were adopted from The Cancer Genome Atlas (TCGA) database. Stromal/immune scores were calculated by the ESTIMATE algorithm. Correlation between prognosis/clinical characteristics and stromal/immune scores was assessed. Differentially expressed stromal and immune genes were identified. Their potential functions were annotated by functional enrichment analysis. Cox regression analysis was used to develop an eight-gene risk score model. Its predictive efficacies for 3 years, 5 years, overall survival (OS), and progression-free survival interval (PFI) were evaluated using time-dependent receiver operating characteristic (ROC) curves. The correlation between the risk score and the infiltering levels of six immune cells was analyzed using TIMER. The risk score was validated using an independent dataset.

Results

Immune score was in a significant association with prognosis and clinical characteristics of CRC. 736 upregulated and two downregulated stromal and immune genes were identified, which were mainly enriched into immune-related biological processes and pathways. An-eight gene prognostic risk score model was conducted, consisting of CCL22, CD36, CPA3, CPT1C, KCNE4, NFATC1, RASGRP2, and SLC2A3. High risk score indicated a poor prognosis of patients. The area under the ROC curves (AUC) s of the model for 3 years, 5 years, OS, and PFI were 0.71, 0.70, 0.73, and 0.66, respectively. Thus, the model possessed well performance for prediction of patients' prognosis, which was confirmed by an external dataset. Moreover, the risk score was significantly correlated with immune cell infiltration.

Conclusion

Our study conducted an immune-related prognostic risk score model, which could provide novel targets for immunotherapy of CRC.

Tumor cell-derived angiopoietin-like protein 2 establishes a preference for glycolytic metabolism in lung cancer cells

We previously revealed that tumor cell‐derived angiopoietin‐like protein 2 (ANGPTL2) accelerates the metastatic capacity of tumors in an autocrine/paracrine manner by activating tumor cell motility and invasiveness and the epithelial‐mesenchymal transition. However, the effects of ANGPTL2 on cancer cell glycolytic metabolism, which is a hallmark of tumor cells, are unknown. Here we report evidence supporting a role for tumor cell‐derived ANGPTL2 in establishing a preference for glycolytic metabolism. We report that a highly metastatic lung cancer cell subline expressing abundant ANGPTL2 showed upregulated expression of the glucose transporter GLUT3 as well as enhanced glycolytic metabolism relative to a less metastatic parental line. Most notably, ANGPTL2 overexpression in the less metastatic line activated glycolytic metabolism by increasing GLUT3 expression. Moreover, ANGPTL2 signaling through integrin α5β1 increased GLUT3 expression by increasing transforming growth factor‐β (TGF‐β) signaling and expression of the downstream transcription factor zinc finger E‐box binding homeobox 1 (ZEB1). Conversely, ANGPTL2 knockdown in the highly metastatic subline decreased TGF‐β1, ZEB1, and GLUT3 expression and antagonized glycolytic metabolism. In primary tumor cells from patients with lung cancer, ANGPTL2 expression levels correlated with GLUT3 expression. Overall, this work suggests that tumor cell‐derived ANGPTL2 accelerates activities associated with glycolytic metabolism in lung cancer cells by activating TGF‐β‐ZEB1‐GLUT3 signaling.

Glucose Transporter 3 is Essential for the Survival of Breast Cancer Cells in the Brain

Breast cancer brain metastasis commonly occurs in one-fourth of breast cancer patients and is associated with poor prognosis. Abnormal glucose metabolism is found to promote cancer metastasis. Moreover, the tumor microenvironment is crucial and plays an active role in the metabolic adaptations and survival of cancer cells. Glucose transporters are overexpressed in cancer cells to increase glucose uptake. The glucose transporter 3 (GLUT3) is a high-affinity glucose transporter that is highly expressed in mammalian neurons. GLUT3 is also overexpressed in several malignant brain tumors. However, the role of GLUT3 in breast cancer brain metastasis remains unknown. The results of the present study demonstrated that GLUT3 is highly overexpressed in brain metastatic breast cancers and mediates glucose metabolic reprogramming. Furthermore, knockdown of cAMP-response element binding protein (CREB) could directly regulate GLUT3 expression in brain metastatic breast cancer cells. Notably, we verified and provided a novel role of GLUT3 in mediating glucose metabolism and assisting breast cancer cells to survive in the brain to promote brain metastasis.