Reciprocal change in Glucose metabolism of Cancer and Immune Cells mediated by different Glucose Transporters predicts Immunotherapy response

Glucose uptake in trophoblasts of GDM mice is regulated by the AMPK-CLUT3 signaling pathway

GDM, as a metabolic disease during pregnancy, regulates GLUT3 translocation by AMPK, thereby affecting glucose uptake in trophoblasts. It provides a new research idea and therapeutic target for alleviating intrauterine hyperglycemia in GDM. STZ was used to construct GDM mice, inject AICAR into pregnant mice, and observe fetal and placental weight; flow cytometry was employed for the detection of glucose uptake by primary trophoblast cells; immunofluorescence was applied to detect the localization of GLUT3 and AMPK in placental tissue; Cocofal microscope was used to detect the localization of GLUT3 in trophoblast cells;qRT-PCR and Western blot experiments were carried out to detect the expression levels of GLUT3 and AMPK in placental tissue; CO-IP was utilized to detect the interaction of GLUT3 and AMPK. Compared with the normal pregnancy group, the weight of the fetus and placenta of GDM mice increased (P < 0.001), and the ability of trophoblasts to take up glucose decreased (P < 0.001). In addition, AMPK activity in trophoblasts and membrane localization of GLUT3 in GDM mice were down-regulated compared with normal pregnant mice (P < 0.05). There is an interaction between GLUT3 and AMPK. Activating AMPK in trophoblasts can up-regulate the expression of GLUT3 membrane protein in trophoblasts of mice (P < 0.05) and increase the glucose uptake of trophoblasts (P < 0.05). We speculate that inhibition of AMPK activity in GDM mice results in aberrant localization of GLUT3, which in turn attenuates glucose uptake by placental trophoblast cells. AICAR activates AMPK to increase the membrane localization of GLUT3 and improve the glucose uptake capacity of trophoblasts.

Pan-cancer analysis reveals correlation between RAB3B expression and tumor heterogeneity, immune microenvironment, and prognosis in multiple cancers

RAB3B is essential for the transportation and secretion within cells. Its increased expression is linked to the development and progression of various malignancies. However, understanding of RAB3B's involvement in carcinogenesis is mostly limited to specific cancer subtypes. Hence, exploring RAB3B's regulatory roles and molecular mechanisms through comprehensive cancer datasets might offer innovative approaches for managing clinical cancer. To examine the potential involvement of RAB3B in the development of cancer, we analyzed data from various sources including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), cBioPortal, HPA, UALCAN, and tissue microarray (TAM). Using bioinformatics techniques, we examined the correlation between RAB3B expression and prognosis, tumor heterogeneity, methylation modifications, and immune microenvironment across different cancer types. Our findings indicate that elevated RAB3B expression can independently predict prognosis in many tumors and has moderate accuracy for diagnosing most cancers. In most cancer types, we identified RAB3B mutations that showed a significant correlation with tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and microsatellite instability (MSI). Abnormal DNA methylation patterns were also observed in most cancers compared to normal tissues. Additionally, we found significant correlations between RAB3B expression, immune cell infiltration, and immune scores across various cancers. Through pan-cancer analysis, we observed significant differences in RAB3B expression levels between tumors and normal tissues, making it a potential primary factor for cancer diagnosis and prognosis. The IHC results revealed that the expression of RAB3B in six types of tumors was consistent with the results of the pan-cancer analysis of the database. Furthermore, RAB3B showed potential associations with tumor heterogeneity and immunity. Thus, RAB3B can be utilized as an auxiliary diagnostic marker for early tumor detection and a prognostic biomarker for various tumor types.

Targeting metabolism of breast cancer and its implications in T cell immunotherapy

Breast cancer is a prominent health issue amongst women around the world. Immunotherapies including tumor targeted antibodies, adoptive T cell therapy, vaccines, and immune checkpoint blockers have rejuvenated the clinical management of breast cancer, but the prognosis of patients remains dismal. Metabolic reprogramming and immune escape are two important mechanisms supporting the progression of breast cancer. The deprivation uptake of nutrients (such as glucose, amino acid, and lipid) by breast cancer cells has a significant impact on tumor growth and microenvironment remodeling. In recent years, in-depth researches on the mechanism of metabolic reprogramming and immune escape have been extensively conducted, and targeting metabolic reprogramming has been proposed as a new therapeutic strategy for breast cancer. This article reviews the abnormal metabolism of breast cancer cells and its impact on the anti-tumor activity of T cells, and further explores the possibility of targeting metabolism as a therapeutic strategy for breast cancer.

Identification of SLC2A1 as a predictive biomarker for survival and response to immunotherapy in lung squamous cell carcinoma

BACKGROUND

As one of the common subtypes of non-small lung cancer, lung squamous cell carcinoma (LUSC) patients with advanced stage have few choices of treatment strategies. Therefore, it is urgent to discover genes that are associated with the survival and efficacy of immunotherapies.

METHOD

Differential gene expression analyses were conducted using TCGA LUSC bulk-sequencing and single-cell RNA-sequencing data. Prognostic genes were identified from the TCGA LUSC cohort. Protein expression validation and survival analyses were performed. Experiments were conducted to explore the underlying mechanisms. In addition, the correlation between gene expression and pathological response to adjuvant immunochemotherapy was also investigated.

RESULTS

After a series of bioinformatic analyses, solute carrier family 2 member 1(SLC2A1), encoding glucose transporter-1 (GLUT1), was found to be differentially expressed between tumor and normal tissues. GLUT1 was subsequently identified as an independent prognostic factor for LUSC. GSEA analysis revealed the glycolysis metabolism pathway of KEGG enriched in SLC2A1high tumor tissues. LASSO analyses revealed that tumor tissues with high expression of SLC2A1 were associated with high levels of protein lactylation. We found that SLC2A1 was preferentially expressed by SPP1+ macrophages in the tumor microenvironment, and the expression of SLC2A1 was associated with the abundance of SPP1+ macrophages. Immunofluorescence demonstrated GLUT1 and HIF1α colocalization in tumor-infiltrating macrophages. In vitro experiments showed HIF-1α-induced macrophage polarization under hypoxia, and GLUT1 inhibition blocked this polarization. In addition, SLC2A1 was negatively associated with the common immune checkpoint molecules, such as programmed cell death 1(PD-1), T cell immunoreceptor with Ig and ITIM domains (TIGIT), cytotoxic T-lymphocyte associated protein 4 (CTLA4) and lymphocyte activating 3 (LAG3), while showed a positive association with CD44. Finally, we observed that there was a significant correlation between pre-adjuvant-treatment GLUT1 expression and the pathological response.

CONCLUSION

SLC2A1 expression was differentially upregulated in tumor tissues, and elevated GLUT1 expression was associated with worse survival and poor pathological response to adjuvant immunochemotherapy. Upregulation of GLUT1 promoted macrophage polarization into the M2 phenotype. The findings will contribute to guiding the treatment selection for LUSC patients and providing personalized immunotherapy strategies.

Metabolic Profiling to Assess Response to Targeted and Immune Therapy in Melanoma

There is currently no consensus to determine which advanced melanoma patients will benefit from targeted therapy, immunotherapy, or a combination of both, highlighting the critical need to identify early-response biomarkers to advanced melanoma therapy. The goal of this review is to provide scientific rationale to highlight the potential role of metabolic imaging to assess response to targeted and/or immune therapy in melanoma cancer. For that purpose, a brief overview of current melanoma treatments is provided. Then, current knowledge with respect to melanoma metabolism is described with an emphasis on major crosstalks between melanoma cell metabolism and signaling pathways involved in BRAF-targeted therapy as well as in immune checkpoint inhibition therapies. Finally, preclinical and clinical studies using metabolic imaging and/or profiling to assess response to melanoma treatment are summarized with a particular focus on PET (Positron Emission Tomography) imaging and 13C-MRS (Magnetic Resonance Spectroscopy) methods.

Characteristics of whole-body dynamic 18F-FDG PET/CT Patlak multi-parametric imaging in lung cancer and the influence of different delineation methods on quantitative parameters

Background

Dynamic course of flourine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) Patlak muti-parametric imaging spatial distribution in the targeted tissues may reveal highly useful clinical information about the tissue's metabolic properties. The characteristics of the Patlak multi-parametric imaging in lung cancer and the influence of different delineation methods on quantitative parameters may provide reference for the clinical application of this new technology.

Methods

A total of 27 patients with pathologically diagnosed lung cancer underwent whole-body dynamic 18F-FDG PET/CT examination before treatment. Parametric images of metabolic rate of FDG (MRFDG) and Patlak intercept (or distribution volume; DV) were generated using Patlak reconstruction. The values of primary lung cancer lesions, target-to-background ratio (TBR), and contrast-to-noise ratio (CNR) were investigated using contour delineation and boundary delineation. Statistical analysis was performed to analyze the relationship between multi-parametric images and clinicopathological features, and to compare the effects of contour delineation and boundary delineation on quantitative parameters.

Results

MRFDG images showed higher TBR and CNR than did standardized uptake value (SUV) images. There were significant differences in MRFDG-max, MRFDG-mean, and MRFDG-peak among groups with different tumor diameters and pathology types (P<0.05). Moreover, the metabolic parameters of MRFDG were higher in patients with tumor diameters ≥3 cm and squamous carcinoma. The differences of the maximum and peak values of MRFDG and DV were not statistically significant in the different outlining method subgroups (all P>0.05). However, the difference of the mean values of MRFDG and DV were statistically significant in the different outline method groupings (all P<0.05).

Conclusions

Dynamic 18F-FDG PET/CT Patlak multi-parametric imaging can obtain quantitative values for lung cancer with high TBR and CNR. Moreover, the multi-parameters are various from different pathology types to tumor size. Different delineation methods have a greater influence on the mean value of quantitative parameters.

Glucose transporter 3 (GLUT3) promotes lactylation modifications by regulating lactate dehydrogenase A (LDHA) in gastric cancer

OBJECTIVES

Glucose transporter 3 (GLUT3) plays a major role in glycolysis and glucose metabolism in cancer cells. We aimed to investigate the correlation between GLUT3 and histone lactylation modification in the occurrence and progression of gastric cancer.

MATERIALS AND METHODS

We initially used single-cell sequencing data to determine the expression levels of GLUT3 and lactate dehydrogenase A (LDHA) in primary tumor, tumor-adjacent normal, and metastasis tumor tissues. Immunohistochemistry analysis was conducted to measure GLUT3, LDHA, and L-lactyl levels in gastric normal and cancer tissues. Transwell and scratch assays were performed to evaluate the metastatic and invasive capacity of gastric cancer cell lines. Western blotting was used to measure L-lactyl and histone lactylation levels in gastric cancer cell lines.

RESULTS

Single-cell sequencing data showed that GLUT3 expression was significantly increased in primary tumor and metastasis tumor tissues. In addition, GLUT3 expression was positively correlated with that of LDHA expression and lactylation-related pathways. Western blotting and immunohistochemistry analyses revealed that GLUT3 was highly expressed in gastric cancer tissues and cell lines. GLUT3 knockdown in gastric cancer cell lines inhibited their metastatic and invasive capacity to various degrees. Additionally, the levels of LDHA, L-lactyl, H3K9, H3K18, and H3K56 significantly decreased after GLUT3 knockdown, indicating that GLUT3 affects lactylation in gastric cancer cells. Moreover, LDHA overexpression in a GLUT3 knockdown cell line reversed the levels of lactylation and EMT-related markers, and the EMT functional phenotype induced by GLUT3 knockdown. The in vivo results were consistent with the in vitro results.

CONCLUSIONS

This study suggests the important role of histone lactylation in the occurrence and progression of gastric cancer, and GLUT3 may be a new diagnostic marker and therapeutic target for gastric cancer.

A Macrophage-Related Gene Signature for Identifying COPD Based on Bioinformatics and ex vivo Experiments

Background

This study aims to investigate the association between immune cells and the development of COPD, while providing a new method for the diagnosis of COPD according to the changes in immune microenvironment.

Methods

In this study, the "CIBERSORT" algorithm was used to estimate the tissue infiltration of 22 types of immune cells in GSE20257 and GSE10006. The "limma" package was used for differentially expressed analysis. The key modules associated with vital immune cells were identified using WGCNA. GO and KEGG enrichment analysis revealed the biological functions of the candidate genes. Ultimately, a novel diagnostic prediction model was constructed via machine learning methods and multivariate logistic regression analysis based on GSE20257. Furthermore, we examined the stability of the model on one internal test set (GSE10006), three external test sets (GSE8545, GSE57148 and GSE76925), one single-cell transcriptome dataset (GSE167295), macrophages (THP-M cells) and lung tissue from COPD patients.

Results

M0 macrophages (AUC > 0.7 in GSE20257 and GSE10006) were considered as the most important immune cells through exploring the immune microenvironment landscapes in COPD patients and healthy controls. The differentially expressed genes from GSE20257 and GSE10006 were divided into six and five modules via WGCNA, respectively. The green module in GSE20257 (cor = 0.41, P < 0.001) and the brown module in GSE10006 (cor = 0.67, P < 0.001) were highly correlated with M0 macrophages and were selected as key modules. Forty-one intersected genes obtained from two modules were primarily involved in regulation of cytokine production, regulation of innate immune response, specific granule, phagosome, lysosome, ferroptosis, and other biological processes. On the basis of the candidate genetic markers further characterized via the "Boruta" and "LASSO" algorithm for COPD, a diagnostic model comprising CLEC5A, FTL and SLC2A3 was constructed, which could accurately distinguish COPD patients from healthy controls in multiple datasets. GSE20257 as the training set has an AUC of 0.916. The AUCs of the internal test set and three external test sets were 0.873, 0.932, 0.675 and 0.688, respectively. Single-cell sequencing analysis suggested that CLEC5A, FTL and SLC2A3 were expressed in macrophages from COPD patients. The expressions of CLEC5A, FTL and SLC2A3 were up-regulated in THP-M cells and lung tissue from COPD patients.

Conclusion

According to the variations of immune microenvironment in COPD patients, we constructed and validated a novel macrophage M0-associated diagnostic model with satisfactory predictive value. CLEC5A, FTL and SLC2A3 are expected to be promising targets of immunotherapy in COPD.

Exploring the efficacy of 18F-FDG PET/CT in hepatocellular carcinoma diagnosis: role of Ki-67 index and tumor differentiation

PURPOSE

The sensitivity of [18F] fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) for detecting hepatocellular carcinoma (HCC) has not been clarified thoroughly. Our study seeks to explore the association between the Ki-67 index and FDG-avidity in HCC tumors using 18F-FDG PET/CT.

METHODS

112 HCC lesions from 109 patients detected by 18F-FDG PET/CT were included retrospectively between August 2017 and May 2022, comprising 82 lesions in the training cohort and 30 in the validation cohort to simulate prospective studies. In the training cohort, lesions were stratified by a lesion-to-liver maximum standardized uptake value (SUVmax) ratio cut-off of 1.59. The relationships between lesion-to-liver SUVmax ratios and several clinical factors including tumor differentiation, alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), hepatitis B virus (HBV) infection, Ki-67 index et al. were assessed. These findings were subsequently validated in the independent validation cohort.

RESULTS

In the training cohort, group A1 lesions demonstrated a higher Ki-67 index (%, 40.00 [30.00, 57.50] vs. 10.00 [5.00, 28.75], p<0.001) than group A0, the positive correlation between FDG-avidity and Ki-67 index was revealed by multivariate analysis, OR=1.040, 95% CI of OR [1.004-1.077], p=0.030. The calculated cut-off value was 17.5% using the receiver operating characteristic (ROC) curve, with an area under curve (AUC) of 0.834 and 95% CI [0.742-0.926], p<0.001. These findings were further validated in the independent validation cohort, with similar results (AUC=0.875, 95% CI [0.750-1.000], p<0.001).

CONCLUSION

In comparison to tumor differentiation, Ki-67 index demonstrates a stronger association with FDG-avidity in HCC tumors, and when the Ki-67 index exceeds 17.5%, 18F-FDG PET/CT might serve as a useful indicator for HCC.

Glycolysis-cholesterol metabolic axis in immuno-oncology microenvironment: emerging role in immune cells and immunosuppressive signaling

Cell proliferation and function require nutrients, energy, and biosynthesis activity to duplicate repertoires for each daughter. It is therefore not surprising that tumor microenvironment (TME) metabolic reprogramming primarily orchestrates the interaction between tumor and immune cells. Tumor metabolic reprogramming affords bioenergetic, signaling intermediates, and biosynthesis requirements for both malignant and immune cells. Different immune cell subsets are recruited into the TME, and these manifestations have distinct effects on tumor progression and therapeutic outcomes, especially the mutual contribution of glycolysis and cholesterol metabolism. In particularly, glycolysis-cholesterol metabolic axis interconnection plays a critical role in the TME modulation, and their changes in tumor metabolism appear to be a double-edged sword in regulating various immune cell responses and immunotherapy efficacy. Hence, we discussed the signature manifestation of the glycolysis-cholesterol metabolic axis and its pivotal role in tumor immune regulation. We also highlight how hypothetical combinations of immunotherapy and glycolysis/cholesterol-related metabolic interventions unleash the potential of anti-tumor immunotherapies, as well as developing more effective personalized treatment strategies.

Tumor aerobic glycolysis confers immune evasion through modulating sensitivity to T cell-mediated bystander killing via TNF-α

Metabolic reprogramming toward glycolysis is a hallmark of cancer malignancy. The molecular mechanisms by which the tumor glycolysis pathway promotes immune evasion remain to be elucidated. Here, by performing genome-wide CRISPR screens in murine tumor cells co-cultured with cytotoxic T cells (CTLs), we identified that deficiency of two important glycolysis enzymes, Glut1 (glucose transporter 1) and Gpi1 (glucose-6-phosphate isomerase 1), resulted in enhanced killing of tumor cells by CTLs. Mechanistically, Glut1 inactivation causes metabolic rewiring toward oxidative phosphorylation, which generates an excessive amount of reactive oxygen species (ROS). Accumulated ROS potentiate tumor cell death mediated by tumor necrosis factor alpha (TNF-α) in a caspase-8- and Fadd-dependent manner. Genetic and pharmacological inactivation of Glut1 sensitizes tumors to anti-tumor immunity and synergizes with anti-PD-1 therapy through the TNF-α pathway. The mechanistic interplay between tumor-intrinsic glycolysis and TNF-α-induced killing provides new therapeutic strategies to enhance anti-tumor immunity.

FDG uptake reflects an immune-enriched subtype of thyroid cancer: Clinical implications of imaging-based molecular characterization

INTRODUCTION

Iodine and FDG uptakes have been established as methods to define the biological properties of thyroid cancer. As various cells in the tumor microenvironment (TME) affect tumor metabolism, we investigated the association between glucose metabolism in thyroid cancer and the TME using transcriptomic analyses.

METHODS

We used F-18 FDG PET and RNA sequencing data of thyroid cancer to find associations between TME cell types and glucose metabolism. In addition, publicly available single-cell RNA sequencing data of papillary thyroid cancer was used to investigate glucose metabolism in cell types of the TME. The correlations between the FDG uptake and biological properties of the TME, including glucose metabolism and tumor differentiation score (TDS) were evaluated. Estimation of the proportions of immune and cancer cells (EPIC) was performed. The biological properties of each cell type were also assessed in the single-cell RNA sequencing data.

RESULTS

FDG uptake showed a positive correlation with the enrichment score of macrophages and glycolysis activity. In single-cell RNA sequencing, immune cells had both high glucose transporters (GLUTs) and glycolysis signatures, while thyrocytes including cancer cells showed relatively low GLUTs and glycolysis signatures, suggesting that FDG uptake mainly occurred in immune cells of the TME. Moreover, the high GLUTs of myeloid cells were negatively associated with TDS.

CONCLUSIONS

Our findings suggest that thyroid cancer with high FDG uptake can be mediated by enriched immune cells of the TME. We suggest that FDG uptake in thyroid cancer could be a marker for the immune-rich type and provide clinical implications for treatment stratification.

Unveiling tumor immune evasion mechanisms: abnormal expression of transporters on immune cells in the tumor microenvironment

The tumor microenvironment (TME) is a crucial driving factor for tumor progression and it can hinder the body's immune response by altering the metabolic activity of immune cells. Both tumor and immune cells maintain their proliferative characteristics and physiological functions through transporter-mediated regulation of nutrient acquisition and metabolite efflux. Transporters also play an important role in modulating immune responses in the TME. In this review, we outline the metabolic characteristics of the TME and systematically elaborate on the effects of abundant metabolites on immune cell function and transporter expression. We also discuss the mechanism of tumor immune escape due to transporter dysfunction. Finally, we introduce some transporter-targeted antitumor therapeutic strategies, with the aim of providing new insights into the development of antitumor drugs and rational drug usage for clinical cancer therapy.

Tumor cell membrane-coated continuous electrochemical sensor for GLUT1 inhibitor screening

Glucose transporter 1 (GLUT1) overexpression in tumor cells is a potential target for drug therapy, but few studies have reported screening GLUT1 inhibitors from natural or synthetic compounds. With current analysis techniques, it is difficult to accurately monitor the GLUT1 inhibitory effect of drug molecules in real-time. We developed a cell membrane-based glucose sensor (CMGS) that integrated a hydrogel electrode with tumor cell membranes to monitor GLUT1 transmembrane transport and screen for GLUT1 inhibitors in traditional Chinese medicines (TCMs). CMGS is compatible with cell membranes of various origins, including different types of tumors and cell lines with GLUT1 expression knocked down by small interfering RNA or small molecules. Based on CMGS continuous monitoring technique, we investigated the glucose transport kinetics of cell membranes with varying levels of GLUT1 expression. We used CMGS to determine the GLUT1-inhibitory effects of drug monomers with similar structures from Scutellaria baicalensis and catechins families. Results were consistent with those of the cellular glucose uptake test and molecular-docking simulation. CMGS could accurately screen drug molecules in TCMs that inhibit GLUT1, providing a new strategy for studying transmembrane protein-receptor interactions.

Automatic Lung Cancer Segmentation in [18F]FDG PET/CT Using a Two-Stage Deep Learning Approach

Purpose

Since accurate lung cancer segmentation is required to determine the functional volume of a tumor in [18F]FDG PET/CT, we propose a two-stage U-Net architecture to enhance the performance of lung cancer segmentation using [18F]FDG PET/CT.

Methods

The whole-body [18F]FDG PET/CT scan data of 887 patients with lung cancer were retrospectively used for network training and evaluation. The ground-truth tumor volume of interest was drawn using the LifeX software. The dataset was randomly partitioned into training, validation, and test sets. Among the 887 PET/CT and VOI datasets, 730 were used to train the proposed models, 81 were used as the validation set, and the remaining 76 were used to evaluate the model. In Stage 1, the global U-net receives 3D PET/CT volume as input and extracts the preliminary tumor area, generating a 3D binary volume as output. In Stage 2, the regional U-net receives eight consecutive PET/CT slices around the slice selected by the Global U-net in Stage 1 and generates a 2D binary image as the output.

Results

The proposed two-stage U-Net architecture outperformed the conventional one-stage 3D U-Net in primary lung cancer segmentation. The two-stage U-Net model successfully predicted the detailed margin of the tumors, which was determined by manually drawing spherical VOIs and applying an adaptive threshold. Quantitative analysis using the Dice similarity coefficient confirmed the advantages of the two-stage U-Net.

Conclusion

The proposed method will be useful for reducing the time and effort required for accurate lung cancer segmentation in [18F]FDG PET/CT.

Relevance of Sugar Transport across the Cell Membrane

Sugar transport through the plasma membrane is one of the most critical events in the cellular transport of nutrients; for example, glucose has a central role in cellular metabolism and homeostasis. The way sugars enter the cell involves complex systems. Diverse protein systems participate in the membrane traffic of the sugars from the extracellular side to the cytoplasmic side. This diversity makes the phenomenon highly regulated and modulated to satisfy the different needs of each cell line. The beautiful thing about this process is how evolutionary processes have diversified a single function: to move glucose into the cell. The deregulation of these entrance systems causes some diseases. Hence, it is necessary to study them and search for a way to correct the alterations and utilize these mechanisms to promote health. This review will highlight the various mechanisms for importing the valuable sugars needed to create cellular homeostasis and survival in all kinds of cells.

Effect of metabolism on the immune microenvironment of breast cancer

Breast cancer (BC) is a highly prevalent primary malignancy worldwide with poor prognosis. Despite the development of aggressive interventions, mortality due to BC remains high. BC cells reprogram nutrient metabolism to adapt to the energy acquisition and progression of the tumor. The metabolic changes in cancer cells are closely related to the abnormal function and effect of immune cells and immune factors, including chemokines, cytokines, and other related effector molecules in the tumor microenvironment (TME), leading to tumor immune escape, whereby the complex crosstalk between immune cells and cancer cells has been considered the key mechanism regulating cancer progression. In this review, we summarized the latest findings on metabolism-related processes in the immune microenvironment during BC progression. Our findings showing the impact of metabolism on the immune microenvironment may suggest new strategies for regulating the immune microenvironment and attenuating BC through metabolic interventions.

ImmuneScore of eight-gene signature predicts prognosis and survival in patients with endometrial cancer

Background

Endometrial cancer (EC) is a common gynecological cancer worldwide and the sixth most common female malignant tumor. A large number of studies conducted through database mining have identified many biomarkers that may be related to survival and prognosis. However, the predictive ability of single-gene biomarkers is not sufficiently accurate. In recent years, tumors have been shown to interact closely with their microenvironment, and tumor-infiltrating immune cells in the tumor microenvironment were associated with therapeutic effects. Furthermore, sequencing technology has evolved and allowed the identification of genetic signatures that may improve prediction results. The purpose of this research was to discover the Cancer Genome Atlas (TCGA) data to evaluate new genetic features that can predict the prognosis of EC.

Methods

mRNA expression profiling was analyzed in patients with EC identified in the TCGA database (n = 530). Differentially expressed genes at different stages of EC were screened using the immune cell enrichment score (ImmuneScore). Univariate and multivariate Cox regression analyses was applied to evaluate genes significantly related to overall survival and establish the prognostic risk parameter formula. Kaplan-Meier survival curves and the logarithmic rank method were applied to verify the importance of risk parameters for the prognostic forecast. The accuracy of survival prediction was confirmed using the nomogram and Receiver Operating Characteristic (ROC) curve analysis. The mRNA expression of eight genes were measured by qRT-PCR. According to COX and HR values, NBAT1, a representative gene among 8 genes, was selected for CCK-8 assay, colony formation assay and transwell invasion assay to verify the effect on survival.

Results

Eight related genes (NBAT1, GFRA4, PTPRT, DLX4, RANBP3L, UNQ6494, KLRB1, and PRAC1) were discovered to be significantly associated with the overall survival rate. According to these eight-gene signatures, 530 patients with EC were assigned to high- and low-risk subgroups. The prognostic capability of the eight-gene signature was not influenced by other elements.

Conclusions

Eight related gene markers were identified using ImmuneScore, which could predict prognosis and survival in patients with EC. These findings provide a basis for understanding the application of biological information in tumors and identifying the poor prognosis of EC.

Efficacy and safety of camrelizumab plus apatinib during the perioperative period in resectable hepatocellular carcinoma: a single-arm, open label, phase II clinical trial

Objective

This study aimed to assess the efficacy and safety of camrelizumab plus apatinib in patients with resectable hepatocellular carcinoma (HCC) as neoadjuvant therapy.

Methods

Initially, 20 patients with HCC were screened and 18 patients with resectable HCC were enrolled in this open-label, single-arm, phase II clinical trial. Patients received three cycles of neoadjuvant therapy including three doses of camrelizumab concurrent with apatinib for 21 days followed by surgery. Four to 8 weeks after surgery, patients received eight cycles of adjuvant therapy with camrelizumab in combination with apatinib. Major pathological reactions (MPR), complete pathological reactions (pCR), objective response rate (ORR), relapse-free survival (RFS), and adverse events (AE) were assessed. In addition, cancer tissue and plasma samples were collected before and after treatment, and genetic differences between responding and non-responding lesions were compared by tumor immune microenvironment (TIME) analysis, circulating tumor DNA (ctDNA) analysis and proteomics analysis.

Results

In 18 patients with HCC who completed neoadjuvant therapy, 3 (16.7%) and 6 (33.3%) patients with HCC reached ORR based on Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1 and modified RECIST criteria, respectively. Of the 17 patients with HCC who received surgical resection, 3 (17.6%) patients with HCC reported MPR and 1 (5.9%) patient with HCC achieved pCR. The 1-year RFS rate of the enrolled patients was 53.85% (95% CI: 24.77% to 75.99%). Grade 3/4 AEs were reported in 3 (16.7%) of the 18 patients, with the most common AEs being rash (11.1%), hypertension (5.6%), drug-induced liver damage (5.6%), and neutropenia (5.6%) in the preoperative phase. The 289 NanoString panel RNA sequencing showed that TIME cell infiltration especially dendritic cells (DCs) infiltration was better in responding tumors than in non-responding tumors. Our results of ctDNA revealed a higher positive rate (100%) among patients with HCC with stage IIb–IIIa disease. When comparing patients with pCR/MPR and non-MPR, we observed more mutations in patients who achieved pCR/MPR at baseline (6 mutations vs 2.5 mutations, p=0.025). Patients who were ctDNA positive after adjuvant therapy presented a trend of shorter RFS than those who were ctDNA negative. Proteomic analysis suggested that abnormal glucose metabolism in patients with multifocal HCC might be related to different sensitivity of treatment in different lesions.

Conclusion

Perioperative camrelizumab plus apatinib displays a promising efficacy and manageable toxicity in patients with resectable HCC. DCs infiltration might be a predictive marker of response to camrelizumab and apatinib as well as patients’ recurrence. ctDNA as a compose biomarker can predict pathological response and relapse. Abnormal glucose metabolism in patients with multifocal HCC may be related to different sensitivity of treatment in different lesions.

Trial registration number

NCT04297202.

Glucose transporters as markers of diagnosis and prognosis in cancer diseases

The primary metabolic substrate for cells is glucose, which acts as both a source of energy and a substrate in several processes. However, being lipophilic, the cell membrane is impermeable to glucose and specific carrier proteins are needed to allow transport. In contrast to normal cells, cancer cells are more likely to generate energy by glycolysis; as this process generates fewer molecules of adenosine triphosphate (ATP) than complete oxidative breakdown, more glucose molecules are needed. The increased demand for glucose in cancer cells is satisfied by overexpression of a number of glucose transporters, and decreased levels of others. As specific correlations have been observed between the occurrence of cancer and the expression of glucose carrier proteins, the presence of changes in expression of glucose transporters may be treated as a marker of diagnosis and/or prognosis for cancer patients.

Different Glucose Metabolic Features According to Cancer and Immune Cells in the Tumor Microenvironment

Background

A close metabolic interaction between cancer and immune cells in the tumor microenvironment (TME) plays a pivotal role in cancer immunity. Herein, we have comprehensively investigated the glucose metabolic features of the TME at the single-cell level to discover feasible metabolic targets for the tumor immune status.

Methods

We examined expression levels of glucose transporters (GLUTs) in various cancer types using The Cancer Genome Atlas (TCGA) data and single-cell RNA-seq (scRNA-seq) datasets of human cancer tissues including melanoma, head and neck, and breast cancer. In addition, scRNA-seq data of immune cells in the TME acquired from human melanoma after immune checkpoint inhibitors were analyzed to investigate the dynamics of glucose metabolic profiles of specific immune cells.

Results

Pan-cancer bulk RNA-seq showed that the GLUT3-to-GLUT1 ratio was positively associated with immune cell enrichment score. The scRNA-seq datasets of various human cancer tissues showed that GLUT1 was highly expressed in cancer cells, while GLUT3 was highly expressed in immune cells in TME. The scRNA-seq data obtained from human melanoma tissues pre- and post-immunotherapy showed that glucose metabolism features of myeloid cells, particularly including GLUTs expression, markedly differed according to treatment response.

Conclusions

Differently expressed GLUTs in TME suggest that GLUT could be a good candidate a surrogate of tumor immune metabolic profiles and a target for adjunctive treatments for immunotherapy.

Glucose Metabolism Reprogramming of Primary Tumor and the Liver Is Associated With Disease-Free Survival in Patients With Early NSCLC

Purpose

Tumor promote disease progression by reprogramming their metabolism and that of distal organs, so it is of great clinical significance to study the changes in glucose metabolism at different tumor stages and their effect on glucose metabolism in other organs.

Methods

A retrospective single-centre study was conducted on 253 NSCLC (non-small cell lung cancer) patients with negative lymph nodes and no distant metastasis. According to the AJCC criteria, the patients were divided into different groups based on tumor size: stage IA, less than 3 cm (group 1, n = 121); stage IB, greater than 3-4 cm (group 2, n = 64); stage IIA, greater than 4-5 cm (group 3, n = 36); and stage IIB, greater than 5-7 cm (group 4, n = 32). All of the patients underwent baseline ¹⁸F-FDG PET/CT scans, and the primary lesion SUVmax (maximum standardized uptake value), liver SUVmean (mean standardized uptake value), spleen SUVmean, TLR (Tumor-to-liver SUV ratio) and TSR (Tumor-to-spleen SUV ratio) were included in the study, combined with clinical examination indicators to evaluate DFS (disease free survival).

Results

In NSCLC patients, with the increase in the maximum diameter of the tumor, the SUVmax of the primary lesion gradually increased, and the SUVmean of the liver gradually decreased. The primary lesion SUVmax, liver SUVmean, TLR and TSR were related to disease recurrence or death. The best predictive parameters were different when the tumor size differed. SUVmax had the highest efficiency when the tumor size was less than 4 cm (AUC:0.707 (95% CI, 0.430-0.984) tumor size < 3 cm), (AUC:0.726 (95% CI, 0.539-0.912) tumor size 3-4 cm), liver SUVmean had the highest efficiency when the tumor size was 4-5 cm (AUC:0.712 (95% CI, 0.535-0.889)), and TLR had the highest efficiency when the tumor size was 5-7 cm [AUC:0.925 (95%CI, 0.820-1.000)].

Conclusions

In patients with early NSCLC, glucose metabolism reprogramming occurs in the primary lesion and liver. With the increase in tumor size, different metabolic parameters should be selected to evaluate the prognosis of patients.

GLUT1, GLUT3 Expression and 18FDG-PET/CT in Human Malignant Melanoma: What Relationship Exists? New Insights and Perspectives

BACKGROUND

Malignant melanoma is the most aggressive of skin cancers and the 19th most common cancer worldwide, with an estimated age-standardized incidence rate of 2.8-3.1 per 100,000; although there have been clear advances in therapeutic treatment, the prognosis of MM patients with Breslow thickness greater than 1 mm is still quite poor today. The study of how melanoma cells manage to survive and proliferate by consuming glucose has been partially addressed in the literature, but some rather interesting results are starting to be present.

METHODS

A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and a search of PubMed and Web of Sciences (WoS) databases was performed until 27 September 2021 using the terms: glucose transporter 1 and 3 and GLUT1/3 in combination with each of the following: melanoma, neoplasm and immunohistochemistry.

RESULTS

In total, 46 records were initially identified in the literature search, of which six were duplicates. After screening for eligibility and inclusion criteria, 16 publications were ultimately included.

CONCLUSIONS

the results discussed regarding the role and expression of GLUT are still far from definitive, but further steps toward understanding and stopping this mechanism have, at least in part, been taken. New studies and new discoveries should lead to further clarification of some aspects since the various mechanisms of glucose uptake by neoplastic cells are not limited to the transporters of the GLUT family alone.

Habitat Imaging-Based 18F-FDG PET/CT Radiomics for the Preoperative Discrimination of Non-small Cell Lung Cancer and Benign Inflammatory Diseases

Purpose

To propose and evaluate habitat imaging-based ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) radiomics for preoperatively discriminating non-small cell lung cancer (NSCLC) and benign inflammatory diseases (BIDs).

Methods

Three hundred seventeen ¹⁸F-FDG PET/CT scans were acquired from patients who underwent aspiration biopsy or surgical resection. All volumes of interest (VOIs) were semiautomatically segmented. Each VOI was separated into variant subregions, namely, habitat imaging, based on our adapted clustering-based habitat generation method. Radiomics features were extracted from these subregions. Three feature selection methods and six classifiers were applied to construct the habitat imaging-based radiomics models for fivefold cross-validation. The radiomics models whose features extracted by conventional habitat-based methods and nonhabitat method were also constructed. For comparison, the performances were evaluated in the validation set in terms of the area under the receiver operating characteristic curve (AUC). Pairwise t-test was applied to test the significant improvement between the adapted habitat-based method and the conventional methods.

Results

A total of 1,858 radiomics features were extracted. After feature selection, habitat imaging-based ¹⁸F-FDG PET/CT radiomics models were constructed. The AUC of the adapted clustering-based habitat radiomics was 0.7270 ± 0.0147, which showed significantly improved discrimination performance compared to the conventional methods (p <.001). Furthermore, the combination of features extracted by our adaptive habitat imaging-based method and non-habitat method showed the best performance than the other combinations.

Conclusion

Habitat imaging-based ¹⁸F-FDG PET/CT radiomics shows potential as a biomarker for discriminating NSCLC and BIDs, which indicates that the microenvironmental variations in NSCLC and BID can be captured by PET/CT.

The Effect of GLUT1 on Survival Rate and the Immune Cell Infiltration of Lung Adenocarcinoma and Squamous Cell Carcinoma: A Meta and Bioinformatics Analysis

BACKGROUND

Lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are two major subtypes of non-small cell lung cancer (NSCLC). Studies have shown that abnormal expression of glucose transport type 1 (GLUT1) in NSCLC patients has been associated with progression, aggressiveness, and poor clinical outcome. However, the clinical effect of GLUT1 expression on LUAD and LUSC is unclear.

OBJECTIVE

This study aims to learn more about the character of GLUT1 in LUAD and LUSC.

METHODS

A meta-analysis was performed to evaluate the GLUT1 protein level, and bioinformatics analysis was used to detect the GLUT1 mRNA expression level, survival differences, and the infiltration abundance of immune cells in samples from TCGA. Meanwhile, functional and network analysis was conducted to detect important signaling pathways and key genes with the Gene Expression Omnibus (GEO) dataset.

RESULTS

Our results showed that GLUT1 was over-expressed both in LUAD and LUSC. LUAD patients with high GLUT1 expression had a poor prognosis. Additionally, GLUT1 was related to B cell and neutrophil infiltration of LUAD. In LUSC, GLUT1 was correlated with tumor purity, B cell, CD8⁺ T cell, CD4⁺ T cell, macrophage, neutrophil, and dendritic cell infiltration. The GEO dataset analysis results suggested GLUT1 potentially participated in the p53 signaling pathway and metabolism of xenobiotics by cytochrome P450 and was associated with KDR, TOX3, AGR2, FOXA1, ERBB3, ANGPT1, and COL4A3 gene in LUAD and LUSC.

CONCLUSION

GLUT1 might be a potential biomarker for aggressive progression and poor prognosis in LUAD, and a therapeutic biomarker in LUSC.

Overexpression of GLUT3 promotes metastasis of triple-negative breast cancer by modulating the inflammatory tumor microenvironment

Triple-negative breast cancer (TNBC) exhibits a higher level of glycolytic capacity and are commonly associated with an inflammatory microenvironment, but the regulatory mechanism and metabolic crosstalk between the tumor and tumor microenvironment (TME) are largely unresolved. Here, we show that glucose transporter 3 (GLUT3) is particularly elevated in TNBC and associated with metastatic progression and poor prognosis in breast cancer patients. Expression of GLUT3 is crucial for promoting the epithelial-to-mesenchymal transition and enhancing invasiveness and distant metastasis of TNBC cells. Notably, GLUT3 is correlated with inflammatory gene expressions and is associated with M1 tumor-associated macrophages (TAMs), at least in part by C-X-C Motif Chemokine Ligand 8 (CXCL8). We found that expression of GLUT3 regulates CXCL8 production in TNBC cells. Secretion of CXCL8 participates in GLUT3-overexpressing TNBC cells-elicited activation of inflammatory TAMs, which further enhances GLUT3 expression and mobility of TNBC cells. Our findings demonstrate that aerobic glycolysis in TNBC not only promotes aggressiveness of tumor cells but also initiates a positive regulatory loop for enhancing tumor progression by modulating the inflammatory TME.

Comprehensive Analysis of GLUT1 Immune Infiltrates and ceRNA Network in Human Esophageal Carcinoma

Background

Glucose transporter 1 (GLUT1) is encoded by the solute carrier family 2A1 (SLC2A1) gene and is one of the glucose transporters with the greatest affinity for glucose. Abnormal expression of GLUT1 is associated with a variety of cancers. However, the biological role of GLUT1 in esophageal carcinoma (ESCA) remains to be determined.

Methods

We analyzed the expression of GLUT1 in pan-cancer and ESCA as well as clinicopathological analysis through multiple databases. Use R and STRING to perform GO/KEGG function enrichment and PPI analysis for GLUT1 co-expression. TIMER and CIBERSORT were used to analyze the relationship between GLUT1 expression and immune infiltration in ESCA. The TCGA ESCA cohort was used to analyze the relationship between GLUT1 expression and m6A modification in ESCA, and to construct a regulatory network in line with the ceRNA hypothesis.

Results

GLUT1 is highly expressed in a variety of tumors including ESCA, and is closely related to histological types and histological grade. GO/KEGG functional enrichment analysis revealed that GLUT1 is closely related to structural constituent of cytoskeleton, intermediate filament binding, cell-cell adheres junction, epidermis development, and P53 signaling pathway. PPI shows that GLUT1 is closely related to TP53, GIPC1 and INS, and these three proteins all play an important role in tumor proliferation. CIBERSORT analysis showed that GLUT1 expression is related to the infiltration of multiple immune cells. When GLUT1 is highly expressed, the number of memory B cells decreases. ESCA cohort analysis found that GLUT1 expression was related to 7 m6A modifier genes. Six possible crRNA networks in ESCA were constructed by correlation analysis, and all these ceRNA networks contained GLUT1.

Conclusion

GLUT1 can be used as a biomarker for the diagnosis and treatment of ESCA, and is related to tumor immune infiltration, m6A modification and ceRNA network.

Yes associated protein 1 promotes resistance to 5-fluorouracil in gastric cancer by regulating GLUT3-dependent glycometabolism reprogramming of tumor-associated macrophages

The antimetabolite 5-fluorouracil (5-FU) is a widely used chemotherapy regimen for the treatment of gastric cancer (GC). However, resistance to 5-FU remains a major drawback in the clinical use. The treatments of anti-tumor chemo-agents recruit tumor associated macrophages (TAMs) which are highly implicated in the chemoresistance development, but the underlying molecular mechanism is unclear. Here, we demonstrate that YAP1 is overexpressed in resistant GC tissues compared to sensitive GC tissues. Further, IL-3 secreted by YAP1-overexpressed GC could skew macrophage polarization to M2-like phenotype and inducing GLUT3-depended glycolysis program. Meanwhile, polarized M2 macrophages enhance 5-FU resistance in tumor cells by secreting CCL8 and activating phosphorylation of JAK1/STAT3 signaling pathway.