Comparison of GLUT-1, SGLT-1, and SGLT-2 expression in false-negative and true-positive lymph nodes during the 18F-FDG PET/CT mediastinal nodal staging of non-small cell lung cancer

Value of glucose transport protein 1 expression in detecting lymph node metastasis in patients with colorectal cancer

BACKGROUND

There are limited data on the use of glucose transport protein 1 (GLUT-1) expression as a biomarker for predicting lymph node metastasis in patients with colorectal cancer. GLUT-1 and GLUT-3, hexokinase (HK)-II, and hypoxia-induced factor (HIF)-1 expressions may be useful biomarkers for detecting primary tumors and lymph node metastasis when combined with fluorodeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT).

AIM

To evaluate GLUT-1, GLUT-3, HK-II, and HIF-1 expressions as biomarkers for detecting primary tumors and lymph node metastasis with 18F-FDG-PET/CT.

METHODS

This retrospective study included 169 patients with colorectal cancer who underwent colectomy and preoperative 18F-FDG-PET/CT at Chungbuk National University Hospital between January 2009 and May 2012. Two tissue cores from the central and peripheral areas of the tumors were obtained and were examined by a dedicated pathologist, and the expressions of GLUT-1, GLUT-3, HK-II, and HIF-1 were determined using immunohistochemical staining. We analyzed the correlations among their expressions, various clinicopathological factors, and the maximum standardized uptake value (SUVmax) of PET/CT.

RESULTS

GLUT-1 was found at the center or periphery of the tumors in 109 (64.5%) of the 169 patients. GLUT-1 positivity was significantly correlated with the SUVmax of the primary tumor and lymph nodes, regardless of the biopsy site (tumor center, P < 0.001 and P = 0.012; tumor periphery, P = 0.030 and P = 0.010, respectively). GLUT-1 positivity and negativity were associated with higher and lower sensitivities of PET/CT, respectively, for the detection of lymph node metastasis, regardless of the biopsy site. GLUT3, HK-II, and HIF-1 expressions were not significantly correlated with the SUVmax of the primary tumor and lymph nodes.

CONCLUSION

GLUT-1 expression was significantly correlated with the SUVmax of 18F-FDG-PET/CT for primary tumors and lymph nodes. Clinicians should consider GLUT-1 expression in preoperative endoscopic biopsy in interpreting PET/CT findings.

Comparison between an SGLT2 inhibitor and insulin in tumor-to-tissue contrasts in 18F-FDG PET imaging of diabetic mice

18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has been widely utilized for tumor diagnosis. Hyperglycemia affects the 18F-FDG uptake and reduces tumor-to-tissue contrasts, however, ideal hypoglycemic drugs are lacking. This study compared the role of insulin with the novel widely used hypoglycemic drug, sodium-glucose cotransporter 2 (SGLT2) inhibitor, on 18F-FDG PET imaging in diabetic conditions. The streptozotocin (STZ)-induced diabetic C57BL/6N mice were inoculated with B16 (mouse melanoma) cells to establish the xenograft tumor model. After the mice had been administrated with dapagliflozin (30 mg/kg, IG) or insulin (0.75 U/kg, IP) for one hour, 9.25 MBq/10 g 18F-FDG was injected. Biodistributions were detected by gamma counting and microPET imaging. The results showed dapagliflozin did not significantly affect the 18F-FDG uptake in tumors but reduced uptake in reference tissues, resulting in a significant increase in the tumor-to-skeletal muscle ratio. Conversely, insulin increased 18F-FDG uptake in tumors without significant reduction in uptake in reference tissues; Although there was an observable improvement in tumor imaging, it did not reach significantly statistical differences. This study suggests that insulin and SGLT2 inhibitor yield comparable effects on the quality of 18F-FDG PET imaging in diabetic patients. Nevertheless, SGLT2 inhibitors would be more suitable when skeletal muscle is used as reference tissue.

Utility of 18F-FDG PET/CT uptake values in predicting response to neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer

INTRODUCTION

Reliable predictive markers are lacking for resectable non-small cell lung cancer (NSCLC) patients treated with neoadjuvant chemoimmunotherapy. The present study investigated the utility of SUV_max values acquired from PET/CT to predict the response to neoadjuvant chemoimmunotherapy for resectable NSCLC.

MATERAL AND METHODS

SUV_max, clinical and pathological outcomes, were collected from patients in 5 hospitals. Patients who received dynamic PET/CT surveillance were divided into cohorts A (chemoimmunotherapy) and B (chemotherapy), respectively, while cohort C (chemoimmunotherapy) comprised patients undergoing post-therapy PET/CT. Associations between SUV_max and major pathologic response (MPR) were evaluated through receiver operating characteristic (ROC) curves.

RESULTS

A total of 129 cases with an MPR rate of 46.5 % was identified. In neoadjuvant chemoimmunotherapy, ΔSUV_max% (AUC: 0.890, 95 % CI: 0.761-0.949) and post-therapy SUV_max (AUC: 0.933, 95 % CI: 0.802-0.959) could accurately predict MPR. On the contrary, the baseline SUV_max was not associated with MPR (p = 0.184). Furthermore, an independent cohort C proved that post-therapy SUV_max could serve as an independent predictor (AUC: 0.928, 95 % CI: 0.823-0.958). In addition, robust predictive performance could be observed when we use the optimal cut-off point of both ΔSUV_max% (54.4 %, AUC: 0.912, 95 % CI: 0.824-0.994) and post-therapy SUV_max (3.565, AUC: 0.912, 95 % CI: 0.824-0.994) in neoadjuvant chemoimmunotherapy. The RNA data revealed that the expression of PFKFB4, a key enzyme in glycolysis, was positively correlated with SUV_max value and tumor cell proliferation after neoadjuvant chemoimmunotherapy.

CONCLUSION

These findings highlighted that the ΔSUV_max% and remained SUV_max were accurate and non-invasive tests for the prediction of MPR after neoadjuvant chemoimmunotherapy.

Efficacy of a combined tool for stage I non‑small cell lung cancer against lymph node metastasis

In patients with clinical stage I non-small cell lung cancer (NSCLC), the prediction of occult lymph node metastasis (LNM) based on a combination of morphology using high-resolution computed tomography (HRCT) and metabolism using positron emission tomography (PET)-CT is unknown. The present study evaluated the use of predictive radiological tools, chest CT and PET-CT, for occult LNM in patients with clinical stage I NSCLC. The records of patients who underwent lobectomy between July 2014 and November 2021 were retrospectively reviewed. The differences in clinicopathological parameters, including CT and PET, between the LNM and non-LNM groups were assessed. Pure solid tumor was defined as a consolidation-to-tumor ratio of 1. The optimal cut-off value for predictive radiological tools for LNM was assessed according to the area under the receiver operating characteristic (ROC) curve. The present study included 288 patients, of whom 39 (13.5%) had LNM; of these 38 (97.4%) were pure solid type. Larger consolidation size (CS), higher maximal standardized uptake (SUVmax) value and histological type were statistically associated with LNM (all P<0.05). The optimal cutoff values of CS and SUVmax for predicting LNM were 19 mm and 5.5 respectively, as assessed using the area under the ROC curve. The combination of CS ≥19 mm and SUVmax ≥5.5 demonstrated a markedly higher odds ratio (9.184; 95% CI, 4.345-19.407) than each parameter individually. The minimum values of CS and SUVmax associated with LNM were 10 mm and 0.8 respectively. Pure solid formation and CS as morphology and SUVmax as metabolism were useful tools that complemented each other in predicting LNM. The combined method of evaluating SUVmax and CS may identify eligibility for LN dissection. However, considering the minimum values of CS and SUVmax in LNM, it cannot affirm the omission of LN dissection for cases that do not meet the combined criteria using HRCT and PET-CT.

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.

Diagnostic utility of metabolic parameters on FDG PET/CT for lymph node metastasis in patients with cN2 non-small cell lung cancer

Background

The aim of this study was to assess the diagnostic utility of metabolic parameters on fluorine-18-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/computed tomography (CT) for predicting lymph node (LN) metastasis in patients with cN2 non-small cell lung cancer (NSCLC).

Methods

We retrospectively reviewed patients who underwent surgery for cN2 NSCLC between 2007 and 2020. Those who had clinically diagnosed positive hilar and mediastinal LNs by routine CT and PET/CT imaging were investigated. To measure the metabolic parameters of LNs, the data according to maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and LN-to-primary tumor ratio of SUVmax (LPR) were examined. The diagnosis of each retrieved LN was confirmed based on histopathological examination of surgical tissue specimens. Receiver operating characteristics (ROC) curves with area under the curve (AUC) calculations and multivariate analysis by logistic regression were performed.

Results

Forty-five patients with 84 clinically diagnosed positive hilar or mediastinal LNs were enrolled in the present study. Of the 84 LNs, 63 LNs were pathologically proven as positive (75%). The SUVmax, MTV, TLG, and LPR of LN metastasis were significantly higher than those of benign nodes. In the ROC analysis, the AUC value of LPR [AUC, 0.776; 95% confidence interval (CI), 0.640–0.913] was higher than that of LN SUVmax (AUC, 0.753; 95% CI, 0.626–0.880) or LN TLG3.5 (AUC, 0.746; 95% CI, 0.607–0.885). Using the optimal LPR cutoff value of 0.47, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.1, 66.7, 88.3, 58.3, and 79.8%, respectively. Multivariate analysis by logistic regression showed that LPR was an independent predictor for LN metastasis (odds ratio, 6.45; 95% CI, 1.785–23.301; P = 0.004). In the subgroup analysis of adenocarcinoma patients (n = 18; 32 LNs), TLG3.5 was a better predictor (AUC, 0.816; 95% CI, 0.639–0.985) than LPR (AUC, 0.792; 95% CI, 0.599–0.986) or LN SUVmax (AUC, 0.792; 95% CI, 0.625–0.959).

Conclusions

Our findings suggest that LPR on FDG-PET is a useful predictor for LN metastasis in patients with cN2 NSCLC. TLG can be a good predictor for LN metastasis in patients with adenocarcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08688-6.

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.

Optimization of a modeling platform to predict oncogenes from genome-scale metabolic networks of non-small-cell lung cancers

Cancer cell dysregulations result in the abnormal regulation of cellular metabolic pathways. By simulating this metabolic reprogramming using constraint-based modeling approaches, oncogenes can be predicted, and this knowledge can be used in prognosis and treatment. We introduced a trilevel optimization problem describing metabolic reprogramming for inferring oncogenes. First, this study used RNA-Seq expression data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) samples and their healthy counterparts to reconstruct tissue-specific genome-scale metabolic models and subsequently build the flux distribution pattern that provided a measure for the oncogene inference optimization problem for determining tumorigenesis. The platform detected 45 genes for LUAD and 84 genes for LUSC that lead to tumorigenesis. A high level of differentially expressed genes was not an essential factor for determining tumorigenesis. The platform indicated that pyruvate kinase (PKM), a well-known oncogene with a low level of differential gene expression in LUAD and LUSC, had the highest fitness among the predicted oncogenes based on computation. By contrast, pyruvate kinase L/R (PKLR), an isozyme of PKM, had a high level of differential gene expression in both cancers. Phosphatidylserine synthase 1 (PTDSS1), an oncogene in LUAD, was inferred to have a low level of differential gene expression, and overexpression could significantly reduce survival probability. According to the factor analysis, PTDSS1 characteristics were close to those of the template, but they were unobvious in LUSC. Angiotensin-converting enzyme 2 (ACE2) has recently garnered widespread interest as the SARS-CoV-2 virus receptor. Moreover, we determined that ACE2 is an oncogene of LUSC but not of LUAD. The platform developed in this study can identify oncogenes with low levels of differential expression and be used to identify potential therapeutic targets for cancer treatment.

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.

Combinative evaluation of primary tumor and lymph nodes to predict pelvic lymphatic metastasis in cervical cancer: an integrated PET-IVIM MRI study

Background

The aim of this study was to evaluate the value of combining pelvic lymph node and tumor characteristics on positron emission tomography-intravoxel incoherent motion magnetic resonance (PET-IVIM MR) imaging for predicting lymph node metastasis in patients with cervical cancer, especially in those with negative lymph nodes on PET.

Methods

The medical records of 95 patients with cervical cancer who underwent surgical resection with pelvic lymph node dissection were evaluated. The patients were divided into negative and positive groups according to postoperative pathologic lymph node diagnosis, and comparisons of the PET and IVIM-derived parameters between the two groups were performed. Univariate and multivariate analyses were performed to construct a predictive model of lymph node metastasis.

Results

For all patients, tumor SUV_max, TLG, D_min, PET and MRI for lymph node diagnosis showed significant differences between patients with and without confirmed lymph node metastasis. Univariate and multivariate logistic analysis showed that the combination of tumor TLG, D_min and PET for lymph node diagnosis had the strongest predictive value (AUC 0.913, p < 0.001). For patients with PET-negative lymph nodes, SUV_max, SUV_mean, MTV, TLG, and D_min showed significant between-group differences, and univariate and multivariate logistic analysis showed that TLG had the strongest predictive value.

Conclusions

The combination of tumorTLG, D_min and PET for lymph node diagnosis is a powerful prognostic factor for all patients. TLG has the best predictive performance in patients with PET negative lymph nodes.

[18F]fluorodeoxyglucose-positron emission tomography and glucose-transporter type 1 expression in untreated primary small bowel adenocarcinoma

BACKGROUND

Literature reporting [18F]fluorodexoyglucose positron emission tomography (FDG-PET) of small bowel adenocarcinoma, a rare tumor, is sparse. To assess FDG uptake in small bowel adenocarcinoma, we retrospectively analyzed a large, single-center database and determined the expression of glucose-transporter type 1 (GLUT-1).

METHODS

Screening of PET datasets in the database (N.=28,961 scans) for untreated histologically-confirmed primary small bowel adenocarcinoma revealed evaluable PET datasets for eight patients. Maximum and peak standardized uptake values (SUV<inf>max</inf> and SUV<inf>peak</inf>, respectively) were calculated via volume-of-interest (VOI) analysis. Additionally, GLUT-1 expression on tumor specimens was prospectively immunohistochemically assessed.

RESULTS

All primary tumors showed high FDG uptake: mean SUVmax was 9.5±2.6 (range: 5.0-13.0) and SUVpeak, 8.1±2.3 (range: 3.9-10.7). Corresponding biopsy specimens (N.=7) demonstrated high GLUT-1 expression.

CONCLUSIONS

Primary small bowel adenocarcinomas have a high GLUT-1 expression. Tumor lesions consistently demonstrated high FDG uptake pre-treatment, suggesting FDG-PET utility in staging and follow-up of these tumors.

Associations between GLUT expression and SUV values derived from FDG-PET in different tumors-A systematic review and meta analysis

Purpose

Fluorodeoxyglucose-Positron-emission tomography (FDG-PET), quantified by standardized uptake values (SUV), is one of the most used functional imaging modality in clinical routine. It is widely acknowledged to be strongly associated with Glucose-transporter family (GLUT)-expression in tumors, which mediates the glucose uptake into cells. The present systematic review sought to elucidate the association between GLUT 1 and 3 expression with SUV values in various tumors.

Methods

MEDLINE library was screened for associations between FDG-PET parameters and GLUT correlation cancer up to October 2018.

Results

There were 53 studies comprising 2291 patients involving GLUT 1 expression and 11 studies comprising 405 patients of GLUT 3 expression. The pooled correlation coefficient for GLUT 1 was r = 0.46 (95% CI 0.40–0.52), for GLUT 3 was r = 0.35 (95%CI 0.24–0.46). Thereafter, subgroup analyses were performed. The highest correlation coefficient for GLUT 1 was found in pancreatic cancer r = 0.60 (95%CI 0.46–0.75), the lowest was identified in colorectal cancer with r = 0.21 (95% CI -0.57–0.09).

Conclusion

An overall only moderate association was found between GLUT 1 expression and SUV values derived from FDG-PET. The correlation coefficient with GLUT 3 was weaker. Presumably, the underlying mechanisms of glucose hypermetabolism in tumors are more complex and not solely depended on the GLUT expression.