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

Taira, Naohiro; Atsumi, Eriko; Nakachi, Saori; Takamatsu, Reika; Yohena, Tomofumi; Kawasaki, Hidenori; Kawabata, Tsutomu; Yoshimi, Naoki

doi:10.1016/j.lungcan.2018.06.004

Cited by 17 publications

(11 citation statements)

References 21 publications

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“…In this study, PET was also significantly better than MR in the diagnosis of lymph nodes. But we found a large number of PET false-negative cases, which accords with the findings of endometrial cancer and non-small cell lung cancer studies [36,37]. Identifying PET false-negative cases has always been a clinical challenge.…”

Section: Discussionsupporting

confidence: 88%

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

Shi

et al. 2020

Cancer Imaging

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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.

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Section: Discussionsupporting

confidence: 88%

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

Shi

et al. 2020

Cancer Imaging

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“…Moreover, a small amount of tumors might express less GLUT proteins and are, therefore, negative on PET studies, which is a very important reason for false negativity of FDG-PET. For example, this was shown in lymph node staging in lung cancer patients [82, 83]. Other reasons for PET negativity are small tumor sizes and some good differentiated tumor types [84].…”

Section: Discussionmentioning

confidence: 99%

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

2019

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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.

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“…An association between the overexpression of a subtype of SLC2A proteins and poor clinical outcomes has been reported in colorectal cancer [9,10]. In patients with non-small-cell lung cancer, SLC2A1 expression is related to poor prognosis [11,12]. Kuang et al revealed comprehensive metabolic reprogramming in tumors resistant to antiangiogenic therapy emanating from increased SLC2A3 expression [13].…”

Section: Introductionmentioning

confidence: 99%

SLC2A3 promotes macrophage infiltration by glycolysis reprogramming in gastric cancer

Yao

Qin

et al. 2020

Cancer Cell Int

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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.

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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

Cited by 17 publications

References 21 publications

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

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

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

SLC2A3 promotes macrophage infiltration by glycolysis reprogramming in gastric cancer

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