Differential expression and prognostic significance of GLUT1 according to histologic type of non-small-cell lung cancer and its association with volume-dependent parameters

Energy metabolism as the hub of advanced non-small cell lung cancer management: a comprehensive view in the framework of predictive, preventive, and personalized medicine

Energy metabolism is a hub of governing all processes at cellular and organismal levels such as, on one hand, reparable vs. irreparable cell damage, cell fate (proliferation, survival, apoptosis, malignant transformation etc.), and, on the other hand, carcinogenesis, tumor development, progression and metastazing versus anti-cancer protection and cure. The orchestrator is the mitochondria who produce, store and invest energy, conduct intracellular and systemically relevant signals decisive for internal and environmental stress adaptation, and coordinate corresponding processes at cellular and organismal levels. Consequently, the quality of mitochondrial health and homeostasis is a reliable target for health risk assessment at the stage of reversible damage to the health followed by cost-effective personalized protection against health-to-disease transition as well as for targeted protection against the disease progression (secondary care of cancer patients against growing primary tumors and metastatic disease). The energy reprogramming of non-small cell lung cancer (NSCLC) attracts particular attention as clinically relevant and instrumental for the paradigm change from reactive medical services to predictive, preventive and personalized medicine (3PM). This article provides a detailed overview towards mechanisms and biological pathways involving metabolic reprogramming (MR) with respect to inhibiting the synthesis of biomolecules and blocking common NSCLC metabolic pathways as anti-NSCLC therapeutic strategies. For instance, mitophagy recycles macromolecules to yield mitochondrial substrates for energy homeostasis and nucleotide synthesis. Histone modification and DNA methylation can predict the onset of diseases, and plasma C7 analysis is an efficient medical service potentially resulting in an optimized healthcare economy in corresponding areas. The MEMP scoring provides the guidance for immunotherapy, prognostic assessment, and anti-cancer drug development. Metabolite sensing mechanisms of nutrients and their derivatives are potential MR-related therapy in NSCLC. Moreover, miR-495-3p reprogramming of sphingolipid rheostat by targeting Sphk1, 22/FOXM1 axis regulation, and A2 receptor antagonist are highly promising therapy strategies. TFEB as a biomarker in predicting immune checkpoint blockade and redox-related lncRNA prognostic signature (redox-LPS) are considered reliable predictive approaches. Finally, exemplified in this article metabolic phenotyping is instrumental for innovative population screening, health risk assessment, predictive multi-level diagnostics, targeted prevention, and treatment algorithms tailored to personalized patient profiles-all are essential pillars in the paradigm change from reactive medical services to 3PM approach in overall management of lung cancers. This article highlights the 3PM relevant innovation focused on energy metabolism as the hub to advance NSCLC management benefiting vulnerable subpopulations, affected patients, and healthcare at large.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00357-5.

Pan-cancer analysis of SLC2A family genes as prognostic biomarkers and therapeutic targets

Background

The major facilitator superfamily glucose transporters (GLUTs), encoded by solute carrier 2A (SLC2A) genes, mediate the transmembrane movement and uptake of glucose. To satisfy the improved energy demands, glycolysis flux is increased in cancers compared with healthy tissues. Multiple diseases, including cancer, have been associated with GLUTs. Nevertheless, not much research has been done on the functions of SLC2As in pan-cancer prognosis or their clinical treatment potential.

Methods

The SLC2A family genes' level of expression and prognostic values were analyzed in relation to pan-cancer. We then examined the association among SLC2As expression and TME, Stemness score, clinical characteristics, immune subtypes, and drug sensitivity. We merged bioinformatics analysis techniques with up-to-date public databases. Additionally, SLC2As from the KOBAS database were subjected to enrichment analysis.

Results

We discovered that SLC2As' gene expression differed significantly between normal tissues and many malignancies. A number of tumors from various databases demonstrate a relationship between prognosis and SLC2A family gene expression. For instance, SLC2A2 and SLC2A5 were associated with the overall survival (OS) of hepatocellular carcinoma. SLC2A1 was associated with the OS of lung adenocarcinoma and pancreatic adenocarcinoma. Moreover, the SLC2A family gene expression is significantly correlated with the pan-cancer stromal and immune scores, and the RNA and DNA stemness scores. Furthermore, we found that the majority of SLC2As had a strong correlation with the tumor stages in KIRC. The immunological subtypes and all members of the SLC2A gene family exhibited a substantial correlation. Moreover, pathways containing insulin resistance and adipocytokine signaling pathway may influence the progression of some cancers. Finally, there is a significant positive or negative connection between drug sensitivity and SLC2A1 expression.

Conclusion

Our research highlights the significant promise of SLC2As as prognostic indicators and offers insightful approaches for upcoming exploration of SLC2As as putative therapeutic targets in malignancies.

Machine Learning in Diagnosis and Prognosis of Lung Cancer by PET-CT

As a disease with high morbidity and high mortality, lung cancer has seriously harmed people's health. Therefore, early diagnosis and treatment are more important. PET/CT is usually used to obtain the early diagnosis, staging, and curative effect evaluation of tumors, especially lung cancer, due to the heterogeneity of tumors and the differences in artificial image interpretation and other reasons, it also fails to entirely reflect the real situation of tumors. Artificial intelligence (AI) has been applied to all aspects of life. Machine learning (ML) is one of the important ways to realize AI. With the help of the ML method used by PET/CT imaging technology, there are many studies in the diagnosis and treatment of lung cancer. This article summarizes the application progress of ML based on PET/CT in lung cancer, in order to better serve the clinical. In this study, we searched PubMed using machine learning, lung cancer, and PET/CT as keywords to find relevant articles in the past 5 years or more. We found that PET/CT-based ML approaches have achieved significant results in the detection, delineation, classification of pathology, molecular subtyping, staging, and response assessment with survival and prognosis of lung cancer, which can provide clinicians a powerful tool to support and assist in critical daily clinical decisions. However, ML has some shortcomings such as slightly poor repeatability and reliability.

Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma

OBJECTIVES

To develop and validate a machine learning model using 18F-FDG PET/CT radiomics signature and clinical features to predict the presence of micropapillary and solid (MP/S) components in lung adenocarcinoma.

METHODS

Eight hundred and forty-six patients who underwent preoperative PET/CT with pathologically confirmed adenocarcinoma were enrolled. After segmentation, 1688 radiomics features were extracted from PET/CT and selected to construct predictive models. Then, we developed a nomogram based on PET/CT radiomics integrated with clinical features. Receiver operating curves, calibration curves, and decision curve analysis (DCA) were performed for diagnostics assessment and test of the developed models for distinguishing patients with MP/S components from the patients without.

RESULTS

PET/CT radiomics-clinical combined model could well distinguish patients with MP/S components from those without MP/S components (AUC = 0.87), which performed better than PET (AUC = 0.829, p < 0.05) or CT (AUC = 0.827, p < 0.05) radiomics models in the training cohort. In test cohorts, radiomics-clinical combined model outperformed the PET radiomics model in test cohort 1 (AUC = 0.859 vs 0.799, p < 0.05) and the CT radiomics model in test cohort 2 (AUC = 0.880 vs 0.829, p < 0.05). Calibration curve indicated good coherence between all model prediction and the actual observation in training and test cohorts. DCA revealed PET/CT radiomics-clinical model exerted the highest clinical benefit.

CONCLUSION

18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of MP/S components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies. The PET/CT radiomics-clinical combined model performed best. CRITICAL RELEVANCE STATEMENT: 18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of micropapillary and solid components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies.

Ginsenoside Rg5 enhances the radiosensitivity of lung adenocarcinoma via reducing HSP90-CDC37 interaction and promoting client protein degradation

Ginsenoside Rg5 is a rare ginsenoside showing promising tumor-suppressive effects. This study aimed to explore its radio-sensitizing effects and the underlying mechanisms. Human lung adenocarcinoma cell lines A549 and Calu-3 were used for in vitro and in vivo analysis. Bioinformatic molecular docking prediction and following validation by surface plasmon resonance (SPR) technology, cellular thermal shift assay (CETSA), and isothermal titration calorimetry (ITC) were conducted to explore the binding between ginsenoside Rg5 and 90 kD heat shock protein alpha (HSP90α). The effects of ginsenoside Rg5 on HSP90-cell division cycle 37 (CDC37) interaction, the client protein stability, and the downstream regulations were further explored. Results showed that ginsenoside Rg5 could induce cell-cycle arrest at the G1 phase and enhance irradiation-induced cell apoptosis. It could bind to HSP90α with a high affinity, but the affinity was drastically decreased by HSP90α Y61A mutation. Co-immunoprecipitation (Co-IP) and ITC assays confirmed that ginsenoside Rg5 disrupts the HSP90-CDC37 interaction in a dose-dependent manner. It reduced irradiation-induced upregulation of the HSP90-CDC37 client proteins, including SRC, CDK4, RAF1, and ULK1 in A549 cell-derived xenograft (CDX) tumors. Ginsenoside Rg5 or MRT67307 (an IKKε/TBK1 inhibitor) pretreatment suppressed irradiation-induced elevation of the LC3-II/β ratio and restored irradiation-induced downregulation of p62 expression. In A549 CDX tumors, ginsenoside Rg5 treatment suppressed LC3 expression and enhanced irradiation-induced DNA damage. In conclusion, ginsenoside Rg5 may be a potential radiosensitizer for lung adenocarcinoma. It interacts with HSP90α and reduces the binding between HSP90 and CDC37, thereby increasing the ubiquitin-mediated proteasomal degradation of the HSP90-CDC37 client proteins.

Membrane transporters in cell physiology, cancer metabolism and drug response

By controlling the passage of small molecules across lipid bilayers, membrane transporters influence not only the uptake and efflux of nutrients, but also the metabolic state of the cell. With more than 450 members, the Solute Carriers (SLCs) are the largest transporter super-family, clustering into families with different substrate specificities and regulatory properties. Cells of different types are, therefore, able to tailor their transporter expression signatures depending on their metabolic requirements, and the physiological importance of these proteins is illustrated by their mis-regulation in a number of disease states. In cancer, transporter expression is heterogeneous, and the SLC family has been shown to facilitate the accumulation of biomass, influence redox homeostasis, and also mediate metabolic crosstalk with other cell types within the tumour microenvironment. This Review explores the roles of membrane transporters in physiological and malignant settings, and how these roles can affect drug response, through either indirect modulation of sensitivity or the direct transport of small-molecule therapeutic compounds into cells.

Intrinsic features of the cancer cell as drivers of immune checkpoint blockade response and refractoriness

Immune checkpoint blockade represents the latest revolution in cancer treatment by substantially increasing patients' lifetime and quality of life in multiple neoplastic pathologies. However, this new avenue of cancer management appeared extremely beneficial in a minority of cancer types and the sub-population of patients that would benefit from such therapies remain difficult to predict. In this review of the literature, we have summarized important knowledge linking cancer cell characteristics with the response to immunotherapy. Mostly focused on lung cancer, our objective was to illustrate how cancer cell diversity inside a well-defined pathology might explain sensitivity and refractoriness to immunotherapies. We first discuss how genomic instability, epigenetics and innate immune signaling could explain differences in the response to immune checkpoint blockers. Then, in a second part we detailed important notions suggesting that altered cancer cell metabolism, specific oncogenic signaling, tumor suppressor loss as well as tight control of the cGAS/STING pathway in the cancer cells can be associated with resistance to immune checkpoint blockade. At the end, we discussed recent evidences that could suggest that immune checkpoint blockade as first line therapy might shape the cancer cell clones diversity and give rise to the appearance of novel resistance mechanisms.

Combination of Circulating Cell-Free DNA and Positron Emission Tomography to Distinguish Non-Small Cell Lung Cancer from Tuberculosis

OBJECTIVE

Non-small cell lung cancer (NSCLC) holds high metabolic tumor burden and circulating cell-free DNA (cfDNA) levels, and the relationship between metabolic tumor burden and cfDNA in NSCLC and the underlying mechanism of their interaction therein remain poorly characterized. Our aim was to evaluate the clinical value of cfDNA and metabolic tumor burden by positron emission tomography-computed tomography (PET/CT) for NSCLC differential diagnosis from tuberculosis in patients with solitary pulmonary nodules.

METHODS

Metabolic tumor burden values in humans (subjects with NSCLC, subjects with tuberculosis, and healthy control subjects) and relevant mouse models were detected by preoperative 18F-fluorodeoxyglucose PET (18F-FDG PET/CT) and [3H]-2-deoxy-DG uptake, respectively. The cfDNA levels were detected by quantifying serum cfDNA fragments from the ALU (115 bp) gene using reverse transcription-polymerase chain reaction. RNA sequence was performed to determine the underlying target genes and knocked down or inhibited the target genes in vivo and in vitro to determine the mechanism therein.

RESULTS

Metabolic tumor burden correlated with serum cfDNA levels in NSCLC subjects but not in tuberculosis subjects or healthy controls. Mouse models showed a similar phenomenon. In addition, the RNA sequence showed that glucose transporter 1 (GLU1), factor-related apoptosis ligand (FasL), caspase 8, and caspase 3 were significantly increased in NSCLC mouse tumors compared with those in tuberculosis mouse masses. Inhibiting the metabolic tumor burden by blocking or knocking down GLU1 markedly reduced the expression of FasL, the phosphorylation of caspase 8/caspase 3, and serum cfDNA levels/apoptosis percentage in vivo and in vitro. Furthermore, the use of a combination of cfDNA and metabolic tumor burden allowed better ability to distinguish NSCLC subjects from those with tuberculosis or healthy controls than either method used alone.

CONCLUSION

Metabolic tumor burden promotes the formation of circulating cfDNA through GLU1-mediated apoptosis in NSCLC, and the combination of cfDNA and metabolic tumor burden could be valuable for distinguishing NSCLC from tuberculosis.

Relationship between Systemic Inflammatory Markers, GLUT1 Expression, and Maximum 18F-Fluorodeoxyglucose Uptake in Non-Small Cell Lung Carcinoma and Their Prognostic Significance

BACKGROUND

Factors involved in inflammation and cancer interact in various ways with each other, and biomarkers of systemic inflammation may have a prognostic value in cancer. Glucose transporter 1 (GLUT1) plays a pivotal role in glucose transport and metabolism and it is aberrantly expressed in various cancer types. We evaluated the differential expression of GLUT1, along with 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) in non-small-cell lung cancer (NSCLC), and then analyzed their prognostic significance.

METHODS

A total of 163 patients with resectable NSCLC were included in this study. Tumor sections were immunohistochemically stained for GLUT1 and GLUT3. Maximum standardized uptake value (SUV_max) was measured by preoperative FDG-PET, and neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR) were derived from pretreatment blood count.

RESULTS

GLUT1 and GLUT3 was positively expressed in 74.8% and 6.1% of the NSCLC tissues, respectively. GLUT1 expression was significantly correlated with squamous cell carcinoma histology, poor differentiation, high pathologic stage, old age, male, smoking, and high SUV_max (>7) (all p < 0.05). The squamous cell carcinoma and smoker group also showed significantly higher SUV_max (both p < 0.001). Systemic inflammation markers, including NLR, PLR, and LMR, were positively correlated with high SUV_max (all p < 0.05). High GLUT1 expression, high SUV_max, high NLR, and low LMR, were significantly associated with poor overall survival in patients with NSCLC. However, in the multivariate survival analysis, LMR was an independent prognostic factor overall (HR 1.86, 95% CI 1.05-3.3) and for the stage I/II cohort (HR 2.3, 95% CI 1.24-4.3) (all p < 0.05).

CONCLUSIONS

Systemic inflammatory markers-NLR, PLR, and LMR are strongly correlated with the SUV_max and are indicators of aggressive tumor behavior. Specifically, LMR is a promising prognostic biomarker in NSCLC patients.

Identification of four metabolic subtypes and key prognostic markers in lung adenocarcinoma based on glycolytic and glutaminolytic pathways

BACKGROUND

Glucose and glutamine are the main energy sources for tumor cells. Whether glycolysis and glutaminolysis play a critical role in driving the molecular subtypes of lung adenocarcinoma (LUAD) is unknown. This study attempts to identify LUAD metabolic subtypes with different characteristics and key genes based on gene transcription profiling data related to glycolysis and glutaminolysis, and to construct prognostic models to facilitate patient outcome prediction.

METHODS

LUAD related data were obtained from the Cancer Genome Atlas and Gene Expression Omnibus, including TCGA-LUAD, GSE42127, GSE68465, GSE72094, GSE29013, GSE31210, GSE30219, GSE37745, GSE50081. Unsupervised consensus clustering was used for the identification of LUAD subtypes. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and CytoNCA App in Cytoscape 3.9.0 were used for the screening of key genes. The Cox proportional hazards model was used for the construction of the prognostic risk model. Finally, qPCR analysis, immunohistochemistry and immunofluorescence colocalization were used to validate the core genes of the model.

RESULT

This study identified four distinct characterized LUAD metabolic subtypes, glycolytic, glutaminolytic, mixed and quiescent types. The glycolytic type had a worse prognosis than the glutaminolytic type. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) were identified as hub genes driving the glycolytic/glutaminolytic LUAD. In addition, the risk assessment model constructed based on three genes (SPP1, SLC2A1 and AGER) had good predictive performance and could be validated in multiple independent external LUAD cohorts. These three genes were differentially expressed in LUAD and lung normal tissues, and might be potential prognostic markers for LUAD.

CONCLUSION

LUAD can be classified into four different characteristic metabolic subtypes based on the glycolysis- and glutaminolysis-related genes. Nine genes (CXCL8, CNR1, AGER, ALB, S100A7, SLC2A1, TH, SPP1, LEP) may play an important role in the subtype-intrinsic drive. This metabolic subtype classification, provides new biological insights into the previously established LUAD subtypes.

Metabolic classification of non-small cell lung cancer patient-derived xenografts by a digital pathology approach: A pilot study

Introduction

Genetically characterized patient-derived tumor xenografts (PDX) are a valuable resource to understand the biological complexity of cancer and to investigate new therapeutic approaches. Previous studies, however, lack information about metabolic features of PDXs, which may limit testing of metabolism targeting drugs.

Methods

In this pilot study, we investigated by immunohistochemistry (IHC) expression of five essential metabolism-associated markers in a set of lung adenocarcinoma PDX samples previously established and characterized. We exploited digital pathology to quantify expression of the markers and correlated results with tumor cell proliferation, angiogenesis and time of PDX growth in mice.

Results

Our results indicate that the majority of the analyzed PDX models rely on oxidative phosphorylation (OXPHOS) metabolism, either alone or in combination with glucose metabolism. Double IHC enabled us to describe spatial expression of the glycolysis-associated monocarboxylate transporter 4 (MCT4) marker and the OXPHOS-associated glutaminase (GLS) marker. GLS expression was associated with cell proliferation and with expression of liver-kinase B1 (LKB1), a tumor suppressor involved in the regulation of multiple metabolic pathways. Acetyl CoA carboxylase (ACC) was associated with the kinetics of PDX growth.

Conclusion

Albeit limited by the small number of samples and markers analyzed, metabolic classification of existing collections of PDX by this mini panel will be useful to inform pre-clinical testing of metabolism-targeting drugs.

Targeting glycolysis in non-small cell lung cancer: Promises and challenges

Metabolic disturbance, particularly of glucose metabolism, is a hallmark of tumors such as non-small cell lung cancer (NSCLC). Cancer cells tend to reprogram a majority of glucose metabolism reactions into glycolysis, even in oxygen-rich environments. Although glycolysis is not an efficient means of ATP production compared to oxidative phosphorylation, the inhibition of tumor glycolysis directly impedes cell survival and growth. This review focuses on research advances in glycolysis in NSCLC and systematically provides an overview of the key enzymes, biomarkers, non-coding RNAs, and signaling pathways that modulate the glycolysis process and, consequently, tumor growth and metastasis in NSCLC. Current medications, therapeutic approaches, and natural products that affect glycolysis in NSCLC are also summarized. We found that the identification of appropriate targets and biomarkers in glycolysis, specifically for NSCLC treatment, is still a challenge at present. However, LDHB, PDK1, MCT2, GLUT1, and PFKM might be promising targets in the treatment of NSCLC or its specific subtypes, and DPPA4, NQO1, GAPDH/MT-CO1, PGC-1α, OTUB2, ISLR, Barx2, OTUB2, and RFP180 might be prognostic predictors of NSCLC. In addition, natural products may serve as promising therapeutic approaches targeting multiple steps in glycolysis metabolism, since natural products always present multi-target properties. The development of metabolic intervention that targets glycolysis, alone or in combination with current therapy, is a potential therapeutic approach in NSCLC treatment. The aim of this review is to describe research patterns and interests concerning the metabolic treatment of NSCLC.

Application of diffusion kurtosis imaging and 18F-FDG PET in evaluating the subtype, stage and proliferation status of non-small cell lung cancer

Background

Lung cancer has become one of the deadliest tumors in the world. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for approximately 80%-85% of all lung cancer cases. This study aimed to investigate the value of diffusion kurtosis imaging (DKI), diffusion-weighted imaging (DWI) and 2-[¹⁸F]-fluoro-2-deoxy-D-glucose positron emission tomography (¹⁸F-FDG PET) in differentiating squamous cell carcinoma (SCC) and adenocarcinoma (AC) and to evaluate the correlation of each parameter with stage and proliferative status Ki-67.

Methods

Seventy-seven patients with lung lesions were prospectively scanned by hybrid 3.0-T chest ¹⁸F-FDG PET/MR. Mean kurtosis (MK), mean diffusivity (MD), apparent diffusion coefficient (ADC), maximum standard uptake value (SUVmax), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. The independent samples t test or Mann–Whitney U test was used to compare and analyze the differences in each parameter of SCC and AC. The diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve analysis and compared with the DeLong test. A logistic regression analysis was used for the evaluation of independent predictors. Bootstrapping (1000 samples) was performed to establish a control model, and calibration curves and ROC curves were used to validate its performance. Pearson’s correlation coefficient and Spearman’s correlation coefficient were calculated for correlation analysis.

Results

The MK and ADC values of the AC group were significantly higher than those of the SCC group (all P< 0.05), and the SUVmax, MTV, and TLG values of the SCC group were significantly higher than those of the AC group (all P<0.05). There was no significant difference in the MD value between the two groups. Moreover, MK, SUVmax, TLG and MTV were independent predictors of the NSCLC subtype, and the combination of these parameters had an optimal diagnostic efficacy (AUC, 0.876; sensitivity, 86.27%; specificity, 80.77%), which was significantly better than that of MK (AUC = 0.758, z = 2.554, P = 0.011), ADC (AUC = 0.679, z = 2.322, P = 0.020), SUVmax (AUC = 0.740, z = 2.584, P = 0.010), MTV (AUC = 0.715, z = 2.530, P = 0.011) or TLG (AUC = 0.716, z = 2.799, P = 0.005). The ROC curve showed that the validation model had high accuracy in identifying AC and SCC (AUC, 0.844; 95% CI, 0.785-0.885);. The SUVmax value was weakly positively correlated with the Ki-67 index (r = 0.340, P< 0.05), the ADC and MD values were weakly negatively correlated with the Ki-67 index (r = -0.256, -0.282, P< 0.05), and the MTV and TLG values were weakly positively correlated with NSCLC stage (r = 0.342, 0.337, P< 0.05).

Conclusion

DKI, DWI and ¹⁸F-FDG PET are all effective methods for assessing the NSCLC subtype, and some parameters are correlated with stage and proliferation status.

The value of combined PET/MRI, CT and clinical metabolic parameters in differentiating lung adenocarcinoma from squamous cell carcinoma

Objective

This study aimed to study the diagnostic efficacy of positron emission tomography (PET)/magnetic resonance imaging (MRI), computed tomography (CT) and clinical metabolic parameters in predicting the histological classification of lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC).

Methods

PET/MRI, CT and clinical metabolic data of 80 patients with lung ADC or SCC were retrospectively collected. According to the pathological results from surgery or fiberscopy, the patients were diagnosed with lung ADC (47 cases) or SCC (33 cases). All 80 patients were divided into a training group (64 cases), an internal testing group (8 cases) and an external testing group (8 cases) in the ratio of 8:1:1. Nine models were constructed by integrating features from different modalities. The Gaussian classifier was used to differentiate ADC and SCC. The prediction ability was evaluated using the receiver operating characteristic curve. The area under the curve (AUC) of the models was compared using Delong’s test. Based on the best composite model, a nomogram was established and evaluated with a calibration curve, decision curve and clinical impact curve.

Results

The composite model (PET/MRI + CT + Clinical) owned the highest AUC values in the training, internal testing and external testing sets, respectively. In the training set, significant differences in the AUC were found between the composite model and other models except for the PET/MRI + CT model. The calibration curves showed good consistency between the predicted output and actual disease. The decision curve analysis and clinical impact curves demonstrated that the composite model increased the clinical net benefit for predicting lung cancer subtypes.

Conclusion

The composite prediction model of PET/MRI + CT + Clinical better distinguished ADC from SCC pathological subtypes preoperatively and achieved clinical benefits, thus providing an accurate clinical diagnosis.

Papillary Renal Cell Carcinomas Demonstrating Micropapillary Features: An Investigation Into the Diagnostic and Prognostic Implications

Aims: Papillary renal cell carcinoma (PRCC) with micropapillary carcinoma (MC) has been rarely described. We conducted a retrospective descriptive evaluation of the association of MC with PRCC and the possible prognostic implications.

Methods: A database search was made at the University of Southern California (USC) and Lenox Hill Hospital (LHH; New York City) in June 2016-June 2019 of PRCC cases with MC. Diagnosis of MC was made using routine histology, based on the presence of small clusters of cells without a vascular core. Features evaluated included: percent of MC, gross appearance, PRCC typing, nuclear grade, lymphovascular invasion, and lymph node metastasis.

Results: 848 RCC cases (690 from USC and 157 from LHH); 70 cases PRCC (54 from USC, 16 from LHH) of these cases, 13 had an MC, 12 were from radical nephrectomy, and 12 cases were male. Mean age was 68.3 years; seven were located in the right kidney. Average tumor size was 8.6 cm. MC ranged from 10% to 80% (average 37.5%), nine cases were PRCC type 2 and four type 1. Nuclear grade: three cases (grade 2), nine cases (grade 3), and one case (grade 4); 11 out of 13 tumors presented with extrarenal extension; nine cases that had lymph nodes submitted had metastatic carcinoma.

Conclusions: The presence of a micropapillary component in PRCC was found to be 18.5%, and it was predominantly associated with high pathologic stage and lymph node metastases. The clinical course of these tumors seems similar to MC in other tissues/organ systems. We advocate reporting this pattern when identified.

Texture features of primary tumor on 18F-FDG PET images in non-small cell lung cancer: The relationship between imaging and histopathological parameters

PURPOSE

The aims of this study were to evaluate the relationships between textural features of the primary tumor on FDG PET images and clinical-histopathological parameters which are useful in predicting prognosis in newly diagnosed non-small cell lung cancer (NSCLC) patients.

METHODS

PET/CT images of ninety (90) patients with NSCLC prior to surgery were analyzed retrospectively. All patients had resectable tumors. From the images we acquired data related to metabolism (SUVmax, MTV, TLG) and texture features of primary tumors. Histopathological tumor types and subgroups, degree of Ki-67 expression and necrosis rates of the primary tumor, mediastinal lymph node (MLN) status and nodal stages were recorded.

RESULTS

Among the two histologic tumor types (adenocarcinoma and squamous cell carcinoma) significant differences were present regarding metabolic parameters, Ki-67 index with higher values and kurtosis with lower values in the latter group. Textural heterogeneity was found to be higher in poorly differentiated tumors compared to moderately differentiated tumors in patients with adenocarcinoma. While Ki-67 index had significant correlations with metabolic parameters and kurtosis, tumor necrosis rate was only significantly correlated with textural features. By univariate and multivariate analyses of the imaging and histopathological factors examined, only gradient variance was significant predictive factor for the presence of MLN metastasis.

CONCLUSIONS

Textural features had significant associations with histologic tumor types, degree of pathological differentiation, tumor proliferation and necrosis rates. Texture analysis has potential to differentiate tumor types and subtypes and to predict MLN metastasis in patients with NSCLC.

Is It Possible to Establish a Reliable Correlation between Maximum Standardized Uptake Value of 18-Fluorine Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography and Histological Types of Non-Small Cell Lung Cancer? Analysis of the Italian VATS Group Database

BACKGROUND

Although positron emission tomography/computed tomography, often integrated with 2-deoxy-2-[fluorine-18] fluorine-D-glucose (18F-FDG-PET/CT), is fundamental in the assessment of lung cancer, the relationship between metabolic avidity of different histotypes and maximum standardized uptake value (SUVmax) has not yet been thoroughly investigated. The aim of the study is to establish a reliable correlation between Suvmax and histology in non-small cell lung cancer (NSCLC), in order to facilitate patient management.

METHODS

We retrospectively assessed the data about lung cancer patients entered in the Italian Registry of VATS Group from January 2014 to October 2019, after establishing the eligibility criteria of the study. In total, 8139 patients undergoing VATS lobectomy were enrolled: 3260 females and 4879 males. The relationship between SUVmax and tumor size was also analyzed.

RESULTS

The mean values of SUVmax in the most frequent types of lung cancer were as follows: (a) 4.88 ± 3.82 for preinvasive adenocarcinoma; (b) 5.49 ± 4.10 for minimally invasive adenocarcinoma; (c) 5.87 ± 4.18 for invasive adenocarcinoma; and (d) 8.85 ± 6.70 for squamous cell carcinoma. Processing these data, we displayed a statistically difference (p < 0.000001) of FDG avidity between adenocarcinoma and squamous cell carcinoma. Moreover, by classifying patients into five groups based on tumor diameter and after evaluating the SUVmax value for each group, we noted a statistical correlation (p < 0.000001) between size and FDG uptake, also confirmed by the post hoc analysis.

CONCLUSIONS

There is a correlation between SUVmax, histopathology outcomes and tumor size in NSCLC. Further clinical trials should be performed in order to confirm our data.

Prognostic Radiological Tools for Clinical Stage IA Pure Solid Lung Cancer

In this study, we analyzed prognostic radiological tools and surgical outcomes for radiologically pure solid adenocarcinomas (AD) and squamous cell carcinoma (SQ) in clinical stage IA. We retrospectively investigated 130 patients who underwent surgical resections. We assessed the predictive risk factors for recurrence and pathological lymph node metastasis (LNM). There was no statistical difference in recurrence free survival (RFS) or cancer-specific survival (CSS) between AD and SQ groups (p = 0.642 and p = 0.403, respectively). In the whole cohort, tumor size on lung window and mediastinal settings, and tumor disappearance ratio using high-resolution computed tomography (HRCT) were not prognostic parameters (p = 0.127, 0.066, and 0.082, respectively). The maximal standardized uptake value (SUVmax) using positron emission tomography-CT was associated with recurrence (p = 0.016). According to the receiver operating characteristic curve, the cut-off value of SUVmax for recurrence was 4.6 (p = 0.016). The quantitative continuous variables using any radiological tools were not associated with LNM. However, tumor diameter on mediastinal setting ≥8 mm with SUVmax ≥2.4 could be a risk factor for LNM. Pure solid AD and SQ were equivalent for the RFS and CSS. SUVmax was useful to predict recurrence. The tumor diameter on a mediastinal setting and SUVmax were useful in predicting pathological LNM.

An Overview on the Role of miR-451 in Lung Cancer: Diagnosis, Therapy, and Prognosis

MicroRNAs (miRNAs) are highly conserved non-coding RNAs involved in many physiological processes such as cell proliferation, inhibition, development of apoptosis, differentiation, suppresses tumorigenicity, and regulating cell growth. The description of the alterations of miRNA expression patterns in cancers will be helpful to recognize biomarkers for early detection and possible therapeutic intervention in the treatment of cancers. Recent studies have shown that miR-451 is broadly dysregulated in lung cancer and is a crucial agent in lung tumor progression. This review summarizes recent advances of the potential role of miR-451 in lung cancer diagnosis, prognosis, and treatment and provides an insight into the potential use of miR-451 for the development of advanced therapeutic methods in lung cancer.

A requirement for autophagy in HMGA2-induced metabolic reprogramming to support Cd-induced migration

High mobility group A2 (HMGA2) is closely related to the occurrence, development and prognosis of tumors. But the mechanism is unclear. Metabolic reprogramming is a dominant way to meet anabolic and energy requirements of tumor cells for their survival, growth and proliferation. Here, we investigated the role of metabolic reprogramming from oxidative phosphorylation (OXPHOS) to glycolysis mediated by HMGA2/autophagy axis in cadmium (Cd, CdCl₂)-induced migration. First, we found that Cd induced glycolysis and reduced OXPHOS in vivo (0.5 and 1 mg/kg, i.p. or 0.8 and 1.6 μM, i.t.) and in vitro (2 μM in A549 cells and 0.05 μM in HELF cells). Then, genetic knockdown of HMGA2 restored Cd-reduced mitochondrial mass and OXPHOS and inhibited Cd-increased glycolysis, indicating that HMGA2 was involved in Cd-induced metabolic reprogramming. 2-Deoxy-d-glucose (2DG, 5 mM), the inhibitor of glycolysis decreased Cd/HMGA2-induced cell migration and restored Cd/HMGA2-decreased OXPHOS and mitochondrial mass. Inhibition of autophagy by 3-Methyladenine (3MA, 3 mM) elucidated an essential role of autophagy in HMGA2-induced glycolysis, migration, and HMGA2-reduced OXPHOS. Overall, our study demonstrated that autophagy was required for HMGA2-mediated metabolic reprogramming, which was critical for Cd-induced migration. Targeting HMGA2 and autophagy-dependent reprogrammed metabolism may be an effective way to inhibit Cd-induced cell migration.

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.

Metabolic Classification and Intervention Opportunities for Tumor Energy Dysfunction

A comprehensive view of cell metabolism provides a new vision of cancer, conceptualized as tissue with cellular-altered metabolism and energetic dysfunction, which can shed light on pathophysiological mechanisms. Cancer is now considered a heterogeneous ecosystem, formed by tumor cells and the microenvironment, which is molecularly, phenotypically, and metabolically reprogrammable. A wealth of evidence confirms metabolic reprogramming activity as the minimum common denominator of cancer, grouping together a wide variety of aberrations that can affect any of the different metabolic pathways involved in cell physiology. This forms the basis for a new proposed classification of cancer according to the altered metabolic pathway(s) and degree of energy dysfunction. Enhanced understanding of the metabolic reprogramming pathways of fatty acids, amino acids, carbohydrates, hypoxia, and acidosis can bring about new therapeutic intervention possibilities from a metabolic perspective of cancer.

Hexose Transporters in Cancer: From Multifunctionality to Diagnosis and Therapy

Cancer cells increase their metabolic activity by enhancing glucose uptake through overexpression of hexose transporters (Gluts). Gluts also have the capacity to transport other molecules besides glucose, including fructose, mannose, and dehydroascorbic acid (DHA), the oxidized form of vitamin C. The majority of research studies in this field have focused on the role of glucose transport and metabolism in cancer, leaving a substantial gap in our knowledge of the contribution of other hexoses and DHA in cancer biology. Here, we summarize the most recent advances in understanding the role that the multifunctional transport capacity of Gluts plays in biological and clinical aspects of cancer, and how these characteristics can be exploited in the search for novel diagnostic and therapeutic strategies.

Texture features of primary tumor on 18F-FDG PET images in non-small cell lung cancer: The relationship between imaging and histopathological parameters

OBJECTIVES

The aims of this study were to evaluate the relationships between textural features of the primary tumor on FDG PET images and clinical-histopathological parameters which are useful in predicting prognosis in newly diagnosed non-small cell lung cancer (NSCLC) patients.

MATERIAL AND METHODS

PET/CT images of ninety (90) patients with NSCLC prior to surgery were analyzed retrospectively. All patients had resectable tumors. From the images we acquired data related to metabolism (SUVmax, metabolic tumor volume [MTV] and total lesion glycolysis [TLG]) and texture features of primary tumors. Histopathological tumor types and subgroups, degree of Ki-67 expression and necrosis rates of the primary tumor, mediastinal lymph node (MLN) status and nodal stages were recorded.

RESULTS

Among the 2histologic tumor types (adenocarcinoma and squamous cell carcinoma) significant differences were present regarding metabolic parameters, Ki-67 index with higher values and kurtosis with lower values in the latter group. Textural heterogeneity was found to be higher in poorly differentiated tumors compared to moderately differentiated tumors in patients with adenocarcinoma. While Ki-67 index had significant correlations with metabolic parameters and kurtosis, tumor necrosis rate was only significantly correlated with textural features. By univariate and multivariate analyses of the imaging and histopathological factors examined, only gradient variance was significant predictive factor for the presence of MLN metastasis.

CONCLUSIONS

Textural features had significant associations with histologic tumor types, degree of pathological differentiation, tumor proliferation and necrosis rates. Texture analysis has potential to differentiate tumor types and subtypes and to predict MLN metastasis in patients with NSCLC.

High SLC2A1 expression associated with suppressing CD8 T cells and B cells promoted cancer survival in gastric cancer

High expression of glucose transporter family members, which augment glucose uptake and glycolytic flux, has been shown to play a pivotal role in the proliferation and survival of tumor cells, contributing to the energy supply, biosynthesis and homeostasis of cancer cells. Among the many members, solute carrier family 2 member 1 (SLC2A1) encodes a glucose transporter, GLUT1, that is critical in the metabolism of glucose, which is an energy source for cell growth that contributes to cancer progression and development. The aim of this study was to analyze the survival and genetic changes/immune profiles in patients with gastric cancer with high SLC2A1 expression and to provide treatment for improving prognosis. This study investigated the clinicopathologic parameters, the proportion of immune cells and gene sets affecting SLC2A1 expression in 279 and 415 patients with gastric cancer from the Eulji Hospital cohort and The Cancer Genome Atlas, respectively. We assessed the response to conventional chemotherapy drugs, including fluorouracil, a compound of fluoropyrimidine S-1, oxaliplatin, and all−trans−retinoic acid (ATRA), in gastric cancer cell lines with high SLC2A1 expression. High SLC2A1 expression was associated with poor prognosis, cancer cell proliferation, decreased immune cells, including CD8 T cells and B cells, and a low prognostic nutrition index, representing body nutrition-related status. In pathway network analysis, SLC2A1 was indirectly linked to the retinoic signaling pathway and negatively regulated immune cells/receptors. In the drug response analysis, the drug ATRA inhibited gastric cancer cell lines with high SLC2A1 expression. Treatment involving the use of SLC2A1 could contribute to better clinical management/research for patients with gastric cancer.

Prognostic significance of genetic variants in GLUT1 in stage III non-small cell lung cancer treated with radiotherapy

Background

To examine the impact of polymorphisms of glucose transporter 1 (GLUT1) gene on the prognosis of patients with stage III non‐small cell lung cancer (NSCLC) who received radiotherapy.

Methods

Five single nucleotide polymorphisms (SNPs) (rs4658C>G, rs1385129G>A, rs3820589A>T, rs3806401A>C and rs3806400C>T) in GLUT1 gene were evaluated in 90 patients with pathologically confirmed stage III NSCLC. A total of 21 patients were treated with radiotherapy alone, 25 with sequential chemoradiotherapy, and 44 with concurrent chemoradiotherapy. The association of the genetic variations of five SNPs with overall survival (OS) and progression‐free survival (PFS) was analyzed.

Results

Two SNPs (rs1385129 and rs3806401) were significant risk factors for OS. Three SNPs (rs1385129, rs3820589 and rs3806401) were in linkage disequilibrium. In Cox proportional hazard models, GAA haplotype was a good prognostic factor for OS (hazard ratio [HR] = 0.57, 95% confidence interval [CI]: 0.39–0.81, p = 0.002) and PFS (HR = 0.68, 95% CI: 0.47–0.99, p = 0.043), compared to variant haplotypes. The GAA/GAA diplotype was observed in 46.7% of patients; these patients showed significantly better OS (HR = 0.38, 95% CI: 0.22–0.65, p < 0.001) and PFS (HR = 0.51, 95% CI: 0.31–0.85, p = 0.009) compared to those with other diplotypes.

Conclusions

These results suggest that polymorphisms of GLUT1 gene could be used as a prognostic marker for patients with stage III NSCLC treated with radiotherapy.

Identification of theranostic factors for patients developing metastasis after surgery for early-stage lung adenocarcinoma

Rationale: Lung adenocarcinoma (LUAD) is an aggressive disease with high propensity of metastasis. Among patients with early-stage disease, more than 30% of them may relapse or develop metastasis. There is an unmet medical need to stratify patients with early-stage LUAD according to their risk of relapse/metastasis to guide preventive or therapeutic approaches. In this study, we identified 4 genes that can serve both therapeutic and diagnostic (theranostic) purposes.

Methods: Three independent datasets (GEO, TCGA, and KMPlotter) were used to evaluate gene expression profile of patients with LUAD by unbiased screening approach. Upon significant genes uncovered, functional enrichment analysis was carried out. The predictive power of their expression on patient prognosis were evaluated. Once confirmed their theranostic roles by integrated bioinformatics, we further conducted in vitro and in vivo validation.

Results: We found that four genes (ADAM9, MTHFD2, RRM2, and SLC2A1) were associated with poor patient outcomes with an increased hazard ratio in LUAD. Knockdown of them, both separately and simultaneously, suppressed lung cancer cell proliferation and migration ability in vitro and prolonged survival time in metastatic tumor mouse models. Moreover, these four biomarkers were found to be overexpressed in tumor tissues from LUAD patients, and the total immunohistochemical staining scores correlated with poor prognosis.

Conclusions: These results suggest that these four identified genes could be theranostic biomarkers for stratifying high-risk patients who develop relapse/metastasis in early-stage LUAD. Developing therapeutic approaches for the four biomarkers may benefit early-stage LUAD patients after surgery.

Stage-Specific PET Radiomic Prediction Model for the Histological Subtype Classification of Non-Small-Cell Lung Cancer

Purpose

To investigate the impact of staging on differences in glucose metabolic heterogeneity between lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) by ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) textural analysis and to develop a stage-specific PET radiomic prediction model to distinguish lung ADC from SCC.

Patients and Methods

Patients who were histologically diagnosed with lung ADC or SCC and underwent pretreatment ¹⁸F-FDG PET/CT scans were retrospectively identified. Radiomic features were extracted from a semiautomatically outlined tumor region in the Chang-Gung Image Texture Analysis (CGITA) software package. The differences in radiomic parameters between lung ADC and SCC were compared stage-by-stage in 253 consecutive NSCLC patients with stages I to III disease. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature selection. A radiomic signature for each stage was subsequently constructed and evaluated. Then, an individual nomogram incorporating the radiomic signature and clinical risk factors was established and evaluated. The performance of the constructed models was assessed by receiver operating characteristic (ROC) curve analysis, and the nomogram was further validated by calibration curve analysis.

Results

The performance of the radiomic signature for distinguishing lung ADC and SCC in both the training and validation cohorts was good, with AUCs of 0.883, 0.854, and 0.895 in the training cohort and 0.932, 0.944, and 0.886 in the validation cohort for stages I, II, and III NSCLC, respectively. The radiomic-clinical nomogram integrating radiomic features with independent clinical predictors exhibited more favorable discriminative performance, with AUCs of 0.982, 0.963, and 0.979 in the training cohort and 0.989, 0.984, and 0.978 in the validation cohort for stages I, II, and III, respectively.

Conclusion

Differences in PET radiomic features between lung ADC and SCC varied in different stages. Stage-specific PET radiomic prediction models provided more favorable performance for discriminating the histological subtype of NSCLC.

Randomized phase II study of platinum-based chemotherapy plus controlled diet with or without metformin in patients with advanced non-small cell lung cancer

OBJECTIVES

Accumulating evidence indicates anti-diabetic drug metformin has anti-cancer effect by controlling cancer metabolism. We evaluated whether addition of metformin to chemotherapy improved survival of lung cancer patients.

MATERIALS AND METHODS

This randomized phase II study enrolled 164 patients with chemo-native, EGFR-ALK wild-type, stage IIIB/IV non-small-cell lung cancer (NSCLC). Patients were randomized to receive chemotherapy either with metformin (1000 mg twice daily) or alone every 3 weeks for six cycles. The patients received gemcitabine (1000 mg/m²) on days 1 and 8 and carboplatin (5 area under the curve) on day 1. Exploratory studies included serum metabolic panels, positron-emission tomography (PET) imaging, and genetic mutation tests for metabolism-related genes.

RESULTS

Metformin group showed no significant difference in the risk of progression and death compared to control group (progression: hazard ratio [HR] = 1.01 [95% confidence interval (CI) = 0.72 - 1.42], P = 0.935; death: HR = 0.95 [95% CI = 0.67-1.34], P = 0.757). Squamous cell carcinoma (SqCC) had significantly higher fluorodeoxyglucose (FDG) uptake on baseline PET image than non-SqCC NSCLC (P = 0.004). In the SqCC with high FDG uptake, the addition of metformin significantly decreased the risk of progression and death (progression: HR = 0.31 [95% CI = 0.12-0.78], P = 0.013; death: HR = 0.42 [95% CI = 0.18-0.94], P = 0.035). The HDL-cholesterol level was significantly increased after the treatment in metformin group compared to control group (P = 0.011). The metformin group showed no survival benefit in the patients with hyperinsulinemia or patients whose insulin level was decreased after treatment.

CONCLUSIONS

Addition of metformin to chemotherapy provided no survival benefit in unselected NSCLC patients. However, it significantly improved the survival of the selected patients with SqCC showing high FDG uptake. It suggests metformin shows the synergistic anti-tumor effect in the tumor which are highly dependent on glucose metabolism.

LAT-1 and GLUT-1 Carrier Expression and Its Prognostic Value in Gastroenteropancreatic Neuroendocrine Tumors

Simple Summary

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) represent about 70% of all NETs; however, improvement in their outcomes has yet to be achieved. Here, we aimed to analyze the role of metabolic players such as the amino acid transporter 1 (LAT-1) and glucose transporter 1 (GLUT-1), regulated by the oxygen-sensing mechanism Von Hippel Lindau-hypoxia-inducible factor (VHL-HIF), in gastroenteropancreatic neuroendocrine tumors (GEP-NET). We also aimed to correlate them with tumor malignancy and progression. We confirmed that specific mechanisms that increase nutrient uptake, such as LAT-1 and GLUT-1, are increased in GEP-NETs, whereas pVHL is decreased. Our results suggest that these biomarkers could have a potential role in NET pathophysiology which might be related to their proliferation and metastatic capacity.

Abstract

Cancer cells develop mechanisms that increase nutrient uptake, including key nutrient carriers, such as amino acid transporter 1 (LAT-1) and glucose transporter 1 (GLUT-1), regulated by the oxygen-sensing Von Hippel Lindau-hypoxia-inducible factor (VHL-HIF) transcriptional pathway. We aimed to analyze these metabolic players in gastroenteropancreatic neuroendocrine tumors (GEP-NET) and correlate them with tumor malignancy and progression. LAT-1, GLUT-1, and pVHL expression was analyzed in 116 GEP-NETs and 48 peritumoral tissue samples by immunohistochemistry. LAT-1 was stably silenced using specific shRNA in the human NET BON cell line. LAT-1 expression was significantly increased in tumor tissue compared to non-tumor tissue in both gastrointestinal (67% vs. 44%) and pancreatic NETs (54% vs. 31%). Similarly, GLUT-1 was substantially elevated in gastrointestinal (74% vs. 19%) and pancreatic (58% vs. 4%) NETs. In contrast, pVHL expression was decreased (85% vs. 58%) in pancreatic NETs. Tumors with metastases at diagnosis displayed increased LAT-1 and GLUT-1 and decreased pVHL expression (p < 0.001). In accordance with these data, silencing LAT-1 curtailed cell proliferation in BON cells. These findings suggest that specific mechanisms that increase nutrient uptake, such as LAT-1 and GLUT-1, are increased in GEP-NETs, whereas pVHL is decreased. These markers might be related to the proliferation and metastatic capacity of these tumors.

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.

The lncRNA PVT1 promotes invasive growth of lung adenocarcinoma cells by targeting miR-378c to regulate SLC2A1 expression

As an oncogene, plasmacytoma variant translocation 1 (PVT1) has been found to be highly expressed in several cancers. However, its specific role in lung adenocarcinoma (ADC) has not been fully elucidated. In this study, the expression of PVT1, miR-378c, and solute carrier family 2 member 1 (SLC2A1) was determined by quantitative real-time PCR and western blot. Dual-luciferase reporter assay was used to explore the relationship between PVT1 and miR-378c, as well as miR-378c and SLC2A1. The effects of PVT1 on the lung ADC cells proliferation, invasion, and migration were detected using MTT, wound-healing, and transwell assays. The results revealed that PVT1 was highly expressed in lung ADC cells, and the overexpression of PVT1 promoted the proliferation, migration, and invasion of lung ADC cells. In lung ADC cells, PVT1 negatively regulated miR-378c expression, and miR-378c negatively regulated SLC2A1 expression through binding to its 3'-untranslated coding regions. Knocking down of PVT1 inhibited the abilities of cell proliferation, migration, and invasion, while miR-378c inhibitor or SLC2A1 Vector diminished the effect. Together, silencing PVT1 downregulated SLC2A1 expression via targeting miR-378c, and then repressed lung ADC cells growth, migration, and invasion.

HPV16 E6/E7 promote the translocation and glucose uptake of GLUT1 by PI3K/AKT pathway via relieving miR-451 inhibitory effect on CAB39 in lung cancer cells

Background

HPV16 E6/E7 proteins are the main oncogenes and only long-term persistent infection causes lung cancer. Our previous studies have shown that HPV16 E6/E7 protein up-regulates the expression of GLUT1 in lung cancer cells. However, whether E6 and E7 protein can promote the glucose uptake of GLUT1 and its molecular mechanism are unclear.

Methods

The regulatory relationships of E6 or E7, miR-451, CAB39, PI3K/AKT, and GLUT1 were detected by double directional genetic manipulations in lung cancer cell lines. Immunofluorescence and flow cytometry were used to detect the effect of CAB39 on promoting the translocation to the plasma membrane of GLUT1. Flow cytometry and confocal microscopy were performed to detect the glucose uptake levels of GLUT1.

Results

The overexpression both E6 and E7 proteins significantly down-regulated the expression level of miR-451, and the loss of miR-451 further up-regulated the expression of its target gene CAB39 at both protein and mRNA levels. Subsequently, CAB39 up-regulated the expression of GLUT1 at both protein and mRNA levels. Our results demonstrated that HPV16 E6/E7 up-regulated the expression and activation of GLUT1 through the HPV-miR-451-CAB39-GLUT1 axis. More interestingly, we found that CAB39 prompted GLUT1 translocation to the plasma membrane and glucose uptake, and this promotion depended on the PI3K/AKT pathway.

Conclusion

Our findings provide new evidence to support the critical roles of miR-451 and CAB39 in the pathogenesis of HPV-related lung cancer.

Heterogeneity of Glucose Transport in Lung Cancer

Increased glucose uptake is a known hallmark of cancer. Cancer cells need glucose for energy production via glycolysis and the tricarboxylic acid cycle, and also to fuel the pentose phosphate pathway, the serine biosynthetic pathway, lipogenesis, and the hexosamine pathway. For this reason, glucose transport inhibition is an emerging new treatment for different malignancies, including lung cancer. However, studies both in animal models and in humans have shown high levels of heterogeneity in the utilization of glucose and other metabolites in cancer, unveiling a complexity that is difficult to target therapeutically. Here, we present an overview of different levels of heterogeneity in glucose uptake and utilization in lung cancer, with diagnostic and therapeutic implications.

Glucose Transporter-1 Cooperating with AKT Signaling Promote Gastric Cancer Progression

Objective

High expression of GLUT1 has been observed in numerous solid cancers, facilitating glucose consumption for supporting tumor cell survival. The altered metabolic activity is regulated by series of signaling pathways, including AKT signaling that acts as a key role in glucose metabolism and shows close correlation with the malignant transformation. In this study, we aimed to elucidate the effect of GLUT1 on gastric cancer (GC) and to explore the relation between GLUT1 and AKT signaling.

Materials and Methods

GLUT1, p-AKT, and p-S6k1 expression were investigated by immunohistochemistry and semi-quantitative analysis in 57 paired-GC samples. The relationship of GLUT1 with clinical indexes in GC tissues was investigated. The effects of GLUT1 on the prognosis of GC patients and the underlying mechanism involved were studied by subgroup analysis.

Results

In GC tissues, an obvious increase in GLUT1 expression was observed when compared with that of normal tissues (P<0.001). Advanced clinicopathological factors (tumor size P=0.019, invasion depth P=0.002, lymph node metastasis P<0.001, differentiation P=0.024, neural invasion P=0.003, and TNM staging P=0.001) correlated with high GLUT1 levels. GLUT1 was an independent risk factor resulting in poor prognosis (P=0.002, HR=5.132). GLUT1 increased the activation ratio of p-AKT (P<0.01) and p-S6K1 (P<0.001) in GC. The expression of p-S6K1 and GLUT1 was positively correlated. (P=0.001, R=0.173). The survival probability of GC patients with GLUT1(+)/p-S6K1(+) was worse when compared to that of GLUT1(+)/p-S6K1(-) or GLUT1(-)/p-S6K1(+) (P<0.001).

Conclusion

High expression of GLUT1 facilitated GC progression, leading to poor prognosis. Overexpression of GLUT1 activated AKT-S6K1 axis, resulting in adverse outcomes of GC. GLUT1 is novel indicator of GC prognosis and GLUT1 targeted metabolic treatment that has potential therapeutic value.

A NAG-Guided Nano-Delivery System for Redox- and pH-Triggered Intracellularly Sequential Drug Release in Cancer Cells

Aim

Sequential treatment with paclitaxel (PTXL) and gemcitabine (GEM) is considered clinically beneficial for non-small-cell lung cancer. This study aimed to investigate the effectiveness of a nano-system capable of sequential release of PTXL and GEM within cancer cells.

Methods

PTXL-ss-poly(6-O-methacryloyl-d-galactopyranose)-GEM (PTXL-ss-PMAGP-GEM) was designed by conjugating PMAGP with PTXL via disulfide bonds (-ss-), while GEM via succinic anhydride (PTXL:GEM=1:3). An amphiphilic block copolymer N-acetyl-d-glucosamine(NAG)-poly(styrene-alt-maleic anhydride)₅₈-b-polystyrene₁₃₀ acted as a targeting moiety and emulsifier in formation of nanostructures (NLCs).

Results

The PTXL-ss-PMAGP-GEM/NAG NLCs (119.6 nm) provided a sequential in vitro release of, first PTXL (redox-triggered), then GEM (pH-triggered). The redox- and pH-sensitive NLCs readily distributed homogenously in the cytoplasm. NAG augmented the uptake of NLCs by the cancer cells and tumor accumulation. PTXL-ss-PMAGP-GEM/NAG NLCs exhibited synergistic cytotoxicity in vitro and strongest antitumor effects in tumor-bearing mice compared to NLCs lacking pH/redox sensitivities or free drug combination.

Conclusion

This study demonstrated the abilities of PTXL-ss-PMAGP-GEM/NAG NLCs to achieve synergistic antitumor effect by targeted intracellularly sequential drug release.

GLUT1 expression in high-risk prostate cancer: correlation with 18F-FDG-PET/CT and clinical outcome

BACKGROUND

Tumour ¹⁸F-FDG-uptake is of prognostic value in high-risk and metastatic prostate cancer (PCa). The aim of this study is to investigate the underlying glucose metabolism mechanisms of ¹⁸F-FDG-uptake on PET/CT imaging in PCa.

METHODS

Retrospective analysis was conducted for 94 patients diagnosed with a Gleason sum ≥8 adenocarcinoma of the prostate at biopsy between July 2011 and July 2014 who underwent ¹⁸F-FDG-PET/CT imaging before radical prostatectomy (RP). ¹⁸F-FDG-uptake in primary lesion was measured by a blinded reader using maximum standardised uptake value (SUV_max). GLUT1, GLUT12 and HK2 expression were blindly scored after immunohistochemistry on specimens RP by three pathologists. Correlations between GLUT1, GLUT12 and HK2, and SUV_max were assessed using Spearman's rank correlation test. Survival probabilities were based on the Kaplan-Meier method.

RESULTS

With a median follow-up of 4.5 years, 56% (n = 53) of patients had biochemical recurrence (BCR), 7% (n = 7) progressed to castration-resistant prostate cancer (CRPC) disease, 13% (n = 12) developed metastasis and 6% (n = 6) died. Correlation was found between GLUT1 expression and SUVmax level (r = 0.25, p = 0.02). In addition, SUV_max was significantly higher in tumours with high GLUT1 expression (n = 17, 5.74 ± 1.67) than tumours with low GLUT1 expression (n = 71, 2.68 ± 0.31, p = 0.004). Moreover, a significant association was found between GLUT1 expression levels and SUV_max level (p = 0.005), lymph node status (p = 0.05), volume of cancer (p = 0.01), CRPC disease progression (p = 0.02) and metastasis development (p = 0.04). No significant difference between GLUT12 and HEX2 expression and SUV_max have been found.

CONCLUSIONS

GLUT1 expression in PCa tumours correlates with ¹⁸F-FDG-uptake and poor prognostic factors. These results suggest that this transporter is involved in the molecular mechanism of ¹⁸F-FDG-uptake in high-risk PCa and raise interest in targeting metabolic dependencies of PCa cells as a selective anticancer strategy.

A Machine-Learning Approach Using PET-Based Radiomics to Predict the Histological Subtypes of Lung Cancer

PURPOSE

We sought to distinguish lung adenocarcinoma (ADC) from squamous cell carcinoma using a machine-learning algorithm with PET-based radiomic features.

METHODS

A total of 396 patients with 210 ADCs and 186 squamous cell carcinomas who underwent FDG PET/CT prior to treatment were retrospectively analyzed. Four clinical features (age, sex, tumor size, and smoking status) and 40 radiomic features were investigated in terms of lung ADC subtype prediction. Radiomic features were extracted from the PET images of segmented tumors using the LIFEx package. The clinical and radiomic features were ranked, and a subset of useful features was selected based on Gini coefficient scores in terms of associations with histological class. The areas under the receiver operating characteristic curves (AUCs) of classifications afforded by several machine-learning algorithms (random forest, neural network, naive Bayes, logistic regression, and a support vector machine) were compared and validated via random sampling.

RESULTS

We developed and validated a PET-based radiomic model predicting the histological subtypes of lung cancer. Sex, SUVmax, gray-level zone length nonuniformity, gray-level nonuniformity for zone, and total lesion glycolysis were the 5 best predictors of lung ADC. The logistic regression model outperformed all other classifiers (AUC = 0.859, accuracy = 0.769, F1 score = 0.774, precision = 0.804, recall = 0.746) followed by the neural network model (AUC = 0.854, accuracy = 0.772, F1 score = 0.777, precision = 0.807, recall = 0.750).

CONCLUSIONS

A machine-learning approach successfully identified the histological subtypes of lung cancer. A PET-based radiomic features may help clinicians improve the histopathologic diagnosis in a noninvasive manner.

Radioimmunoimaging of 125I-labeled anti-CD93 monoclonal antibodies in a xenograft model of non-small cell lung cancer

Lung cancer, especially non-small cell lung cancer (NSCLC), is the most common malignant tumor associated with poor prognosis. Angiogenesis plays a vital role in NSCLC, and could be used in tumor staging and therapy evaluation. CD93 (C1q receptor) is reportedly a key regulator of tumor angiogenesis. In the present study, the efficacy and specificity of a ¹²⁵I-labeled CD93-specific monoclonal antibody (¹²⁵I-anti-CD93 mAb) in detecting NSCLC xenografts were analyzed, and the association between CD93 expression and ¹²⁵I-anti-CD93 mAb uptake by tumors was evaluated. The targeting ability of ¹²⁵I-anti-CD93 mAb enabled its rapid, continuous and highly specific accumulation in CD93-expressing tumors in vivo. These results revealed the potential applicability of ¹²⁵I-anti-CD93 mAb for non-invasive imaging diagnosis of CD93-positive NSCLC.

Glucose Transporter 1 Promotes the Malignant Phenotype of Non-Small Cell Lung Cancer through Integrin β1/Src/FAK Signaling

Background: Glucose transporter 1 (GLUT1) is the main factor of Warburg effect, which is associated with poor prognosis in many tumors. However, the underlying molecular mechanism of GLUT1 in the progression of non-small cell lung cancer (NSCLC) is unclear.

Methods: We used quantitative real-time PCR to detect GLUT1 mRNA expression in bronchial brushing samples and performed Western Blot and biological behavior testing to check the effect of GLUT1 on NSCLC cell proliferation, migration, invasion and apoptosis.

Results: We found that the C(t) normalized value of GLUT1 in malignant bronchial brushing samples was significantly higher than that in benign samples (P<0.05). GLUT1 significantly increased the expressions of cyclin A, cyclin D1, cyclin E, cyclin dependent kinase 2 (CDK2), CDK4, CDK6 and matrix metalloproteinase 2 (MMP2), but decreased the expressions of p53 and p130 in NSCLC cells. The biological behavior testing indicated that GLUT1 enhanced NSCLC cell proliferation, invasion and migration but inhibited cell apoptosis. In addition, GLUT1 upregulated the expression of integrin β1 and promoted the phosphorylation of focal adhesion kinase (FAK, phosphorylation at Tyr576/577) and Src (Src phosphorylation at Tyr530). siRNA knock down of integrin β1 expression suppressed GLUT1 induced NSCLC cell biological behavior, as well as the phosphorylation of FAK and Src.

Conclusion: Taken together, our data confirms that GLUT1 promotes the malignant phenotype of NSCLC through integrin β1/Src/FAK signaling, which provides a new therapeutic target for the treatment and research of lung cancer.

Drugging cancer metabolism: Expectations vs. reality

As compared to their normal counterparts, neoplastic cells exhibit a variety of metabolic changes that reflect not only genetic and epigenetic defects underlying malignant transformation, but also the nutritional and immunobiological conditions of the tumor microenvironment. Such alterations, including the so-called Warburg effect (an increase in glucose uptake largely feeding anabolic and antioxidant metabolism), have attracted considerable attention as potential targets for the development of novel anticancer therapeutics. However, very few drugs specifically conceived to target bioenergetic cancer metabolism are currently approved by regulatory agencies for use in humans. This reflects the elevated degree of heterogeneity and redundancy in the metabolic circuitries exploited by neoplastic cells from different tumors (even of the same type), as well as the resemblance of such metabolic pathways to those employed by highly proliferating normal cells. Here, we summarize the major metabolic alterations that accompany oncogenesis, the potential of targeting bioenergetic metabolism for cancer therapy, and the obstacles that still prevent the clinical translation of such a promising therapeutic paradigm.

Protein kinase C-iota-mediated glycolysis promotes non-small-cell lung cancer progression

Purpose

To determine whether protein kinase C-iota (PKC-iota) is associated with glucose metabolism in non-small-cell lung cancer (NSCLC) and whether its regulatory effect on metabolic and biological changes observed in NSCLC can be mediated by glucose transporter 1 (GLUT1).

Patients and methods

Forty-five NSCLC patients underwent combined ¹⁸F-fludeoxyglucose (¹⁸F-FDG) positron emission tomography and computed tomography (PET/CT) before surgery, and another eighty-one NSCLC patients were followed-up for 1–91 months after tumor resection. The rate of glucose metabolism in NSCLC was quantified by measuring the maximum standardized uptake value (SUVmax) by ¹⁸F-FDG PET/CT. PKC-iota and GLUT1 in NSCLC were detected by immunostaining. In vitro, PKC-iota was knocked down, whereas GLUT1 was silenced with or without PKC-iota overexpression to identify the role of PKC-iota in glycolysis. Spearman’s rank correlation coefficient was used in the correlation analysis. Kaplan-Meier analysis was used to assess survival duration.

Results

There was a positive relationship between PKC-iota expression and SUVmax in NSCLC (r=0.649, P<0.001). PKC-iota expression also showed a positive relationship with GLUT1 in NSCLC tissues (r=0.686, P<0.001). Patients whose NSCLC tissues highly co-expressed PKC-iota and GLUT1 had worse prognosis compared with patients without high co-expression of PKC-iota and GLUT1. In vitro, PKC-iota silencing significantly decreased the expression of GLUT1 and inhibited glucose uptake and glycolysis; c-Myc silencing restrained PKC-iota-mediated GLUT1 elevation; GLUT1 knockdown remarkably suppressed PKC-iota-mediated glycolysis and cell growth.

Conclusion

In NSCLC, the rate of glucose metabolism was positively correlated with PKC-iota expression. PKC-iota increased glucose accumulation and glycolysis by upregulating c-Myc/GLUT1 signaling and is thus involved in tumor progression.

Exploiting metabolic vulnerabilities of Non small cell lung carcinoma

Lung cancer is the main cause of cancer death worldwide. Non-Small Cell Lung Carcinoma (NSCLC) is the most common subtype of lung cancer, and the prognosis of NSCLC patients in advanced stages is still very poor. Given the need for new therapies, the metabolism of NSCLC has been widely studied in the past two decades to identify vulnerabilities that could be translated into novel anti-metabolic therapeutic approaches. A number of studies have highlighted the role of glucose and mitochondrial metabolism in the development of NSCLC. The metabolic properties of lung tumors have been characterized in detail in vivo, and they include high glucose and lactate use and high heterogeneity regarding the use of nutrients and mitochondrial pathways. This heterogeneity has also been observed in patients infused with labeled nutrients. We will summarize here the knowledge about the use of amino acids, fatty acids and carbohydrates in NSCLC that could lead to new combination treatments.

The clinicopathologic impacts and prognostic significance of GLUT1 expression in patients with lung cancer: A meta-analysis

BACKGROUND

Accumulating studies have reported that GLUT1 is aberrantly expressed in lung cancer; nevertheless, the clinicopathologic significance and the prognostic role of GLUT1 still remain controversial. The aim of this meta-analysis was to identify the clinicopathologic and prognostic implications of the GLUT1 expression in lung cancer patients.

MATERIALS AND METHODS

Databases with literature published in English, including Cochrane Library, Embase, Web of Science, and PubMed, and the China National Knowledge Infrastructure (CNKI) and WanFang database in Chinese were searched comprehensively for relevant studies in August 2017. The pooled odds ratio (OR) or hazard ratio (HR) with 95% confidence intervals (CIs) were calculated to evaluate the clinicopathologic significance and prognostic value of GLUT1 in lung cancer.

RESULTS

A total of 26 studies (2653 cases) were included in the current study. Totally, 1423 patients from nineteen studies were included to assess the relationships between GLUT1 and clinicopathological parameters, the pooled OR indicated that positive GLUT1 expression was significantly related with classification (adenocarcinomas vs. squamous carcinomas, OR = 0.276, 95% CIs: 0.117-0.651, P = 0.003), tumor differentiation (G3-4 vs. G2~1, OR = 1.944, 95% CIs: 1.384-2.730; P < 0.001), lymph node metastasis (positive vs. negative, OR = 3.65, 95% CIs: 1.82-7.32, P < 0.001),tumor size (large tumor size vs. small tumor size, OR = 2.03, 95% CI: 1.42-2.91, P < 0.001), and advanced tumor stages (OR = 2.527, 95% CIs: 1.325-4.820). Regarding the significance of GLUT1 in the overall survival (OS) of lung cancer, the pooled HRs with 1731 lung cancer patients was 1.41 (P = 0.002; 95% CIs: 1.13-1.76). Additionally, the overexpression of GLUT1 could significantly predict the shorter disease-free survival (HR = 1.68, 95% CIs: 1.01-2.79) and disease-specific survival (HR = 1.59, 95% CIs: 1.11-2.29).

CONCLUSIONS

A positive expression of GLUT1 significantly predicts a poor prognosis in lung cancer patients. GLUT1 may server as a helpful biomarker and a potential target for the treatment strategies of lung cancer.

Predictive Value of Preoperative Volume-Based 18F-2-Fluoro-2-Deoxy-d-Glucose Positron Emission Tomography/Computed Tomography Parameters in Patients with Resectable Lung Adenocarcinoma

Purpose

This study aimed to investigate the prognostic value of metabolic tumor volume (MTV) and total lesion glycolysis (TLG), which are volume-based PET parameters, using ¹⁸F-2-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in patients with surgically resectable lung adenocarcinoma.

Methods

We retrospectively evaluated 149 patients with lung adenocarcinoma who underwent ¹⁸F-FDG PET/CT before surgical resection. Maximum standardized uptake value (SUVmax), MTV, and TLG of the primary tumor with threshold value of SUVmax 30, 40, and 50% were calculated, respectively. To compare the predictive performance of volume-based PET parameters, recurrence-free survival was assessed using the Kaplan-Meier method.

Results

The study included 70 males and 79 females with an average age of 65.8 years. The median follow-up time was 45.4 months. Recurrence was observed in 53 patients (35.6%). The mean ± SD SUVmax, MTV_30%, and TLG_30% of the entire cohort were 4.79 ± 2.94, 19.45 ± 24.85, and 56.43 ± 101.88, respectively. The cut-off values of MTV_30% and TLG_30% for recurrence were 11.07 ad 30.56, respectively. The 1-year recurrence-free survival (RFS) rate was 96.5% in low-MTV_30% patients compared with 86.2% in high-MTV_30% patients (p = 0.018) and 96.0% in low-TLG_30% patients compared with 88.5% in high-TLG_30% patients (p < 0.001). On univariate and multivariate analysis, TLG_30% (HR, 2.828, p < 0.001; HR, 2.738, p < 0.001, respectively) was an independent prognostic factor for predicting recurrence-free survival (RFS).

Conclusion

TLG_30% value was observed to be a significant prognostic factor for RFS in patients with lung adenocarcinoma treated by surgical resection.

LDHA upregulation independently predicts poor survival in lung adenocarcinoma, but not in lung squamous cell carcinoma

Aim: To investigate the potential prognostic value of LDHA in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Patients & methods: Molecular, clinicopathological and survival data in Cancer Genome Atlas-Lung Cancer were obtained for secondary analysis. Results: LDHA expression was significantly upregulated in both LUAD and LUSC compared with normal lung tissues. LUSC tissues had even higher LDHA expression compared with LUAD tissues. Increased LDHA expression was an independent prognostic indicator in terms of overall survival (hazard ratio: 1.547, 95% CI: 1.253–1.911; p < 0.001) and recurrence-free survival (hazard ratio: 1.486, 95% CI: 1.161–1.900; p = 0.002) in LUAD, but not in LUSC. Conclusion: LDHA expression might only serve as an independent prognostic indicator of unfavorable overall survival and recurrence-free survival in LUAD, but not in LUSC.

Assessment of the Mutational Status of NSCLC Using Hypermetabolic Circulating Tumor Cells

Molecular characterization is currently a key step in NSCLC therapy selection. Circulating tumor cells (CTC) are excellent candidates for downstream analysis, but technology is still lagging behind. In this work, we show that the mutational status of NSCLC can be assessed on hypermetabolic CTC, detected by their increased glucose uptake. We validated the method in 30 Stage IV NSCLC patients: peripheral blood samples were incubated with a fluorescent glucose analog (2-NBDG) and analyzed by flow cytometry. Cells with the highest glucose uptake were sorted out. EGFR and KRAS mutations were detected by ddPCR. In sorted cells, mutated DNA was found in 85% of patients, finding an exact match with primary tumor in 70% of cases. Interestingly, in two patients multiple KRAS mutations were detected. Two patients displayed different mutations with respect to the primary tumor, and in two out of the four patients with a wild type primary tumor, new mutations were highlighted: EGFR p.746_750del and KRAS p.G12V. Hypermetabolic CTC can be enriched without the need of dedicated equipment and their mutational status can successfully be assessed by ddPCR. Finally, the finding of new mutations supports the possibility of probing tumor heterogeneity.

The assessment of correlation and prognosis among 18F-FDG uptake parameters, Glut1, pStat1 and pStat3 in surgically resected non-small cell lung cancer patients

Introduction

To assess the correlation among ¹⁸F-FDG uptake, Glut1, pStat1 and pStat3, and to investigate the relationship between the prognosis and ¹⁸F-FDG uptake and these molecular markers in surgically resected non-small cell lung cancer (NSCLC) patients.

Results

Knockdown of Glut1 led to a significant increase in pStat1 expression. Glut1 expression positively correlated with the SUVmax, SUVmean, and TLG significantly (P<0.001). pStat3 expression negatively correlated with all PET parameters significantly (P<0.001). pStat1 had positive weak correlations with the SUVmax and SUVmean. All PET parameters and Glut1 were significantly associated with DFS (P<0.05). TLG, MTV, Glut1 and pStat1 were significantly associated with OS (P<0.05).

Conclusion

pStat3 and Glut1 may be associated with ¹⁸F-FDG uptake mechanism. TLG, MTV, and Glut1 may be independent prognostic factors.

Methods

The SUVmax, SUVmean, MTV and TLG of primary lesions were calculated in 140 patients. The expressions of Glut1 and Stat pathway proteins in NSCLC cell lines were examined by immune blots. Excised tumor tissue was analyzed by immunohistochemistry. OS and DFS were evaluated by the Kaplan-Meier method. The difference in survival between subgroups was analyzed by log-rank test. The prognostic significance of clinicopathological, molecular and PET parameters was assessed by Cox proportional hazard regression analysis.