scholarly journals Glucose Transporter-1 (GLUT-1) Expression is Associated with Tumor Size and Poor Prognosis in Locally Advanced Gastric Cancer

2020 ◽  
Vol 26 ◽  
Author(s):  
Chenqing Yin ◽  
Bin Gao ◽  
Ju Yang ◽  
Jingbo Wu
2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e15647-e15647
Author(s):  
S. R. Park ◽  
J. S. Lee ◽  
Y. W. Kim ◽  
I. J. Choi ◽  
K. W. Ryu ◽  
...  

e15647 Background: In metastatic gastric cancer, the response to chemotherapy is assessed by RECIST or WHO criteria according to the change of tumor size. There are no data, however, on the usefulness of those criteria in evaluating tumor response in the setting of neoadjuvant chemotherapy. The aim of this study was to evaluate the relationship between tumor response to neoadjuvant chemotherapy-as assessed by RECIST and WHO criteria-and clinical outcome in locally advanced gastric cancer (LAGC) patients. Methods: This study recruited LAGC patients who, from January 2003 through November 2005, entered the neoadjuvant arm of prospective randomized phase II trials comparing neoadjuvant chemotherapy to adjuvant chemotherapy. LAGC was defined as stage III or IV (M0) disease based on computed tomography (CT) according to the Japanese Classification of Gastric Carcinoma. Patients with measurable lesions received 3 cycles of neoadjuvant chemotherapy consisting of docetaxel (36 mg/m2) and cisplatin (40 mg/m2) on days 1 and 8 every 3 weeks, followed by surgery. Results: After chemotherapy, 40 (95%) patients underwent surgery and the remaining 2 patients showed new distant metastasis on CT scan. Thirty-five (83%) patients had curative R0 resection. Twenty-eight (67%) patients had a clinical response to neoadjuvant chemotherapy according to RECIST/WHO criteria. Although R0 resection rate (93% vs 64%, P = 0.03), median relapse-free survival (RFS) (43.2 vs 7.5 months, P = 0.14), and overall survival (OS) (not reached vs 27.0 months, P = 0.10) were better in responders than non-responders, they did not differ significantly in the subgroup that subsequently underwent surgery. When we redefined the decrease in tumor size judged as a response by RECIST (≥60% rather than ≥30%) and WHO (≥75% rather than ≥50%) criteria, response correlated significantly with both RFS (P = 0.03) and OS (P = 0.02). Conclusions: In the neoadjuvant setting, which frequently involves smaller measurable lesions than the metastatic setting, larger changes in tumor size than those specified by RECIST and WHO criteria are needed to predict postoperative outcome. No significant financial relationships to disclose.


2001 ◽  
Vol 120 (5) ◽  
pp. A129-A129
Author(s):  
E NEWMAN ◽  
S MARCUS ◽  
M POTMESIL ◽  
H HOCHSTER ◽  
H YEE ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jaeseung Shin ◽  
Joon Seok Lim ◽  
Yong-Min Huh ◽  
Jie-Hyun Kim ◽  
Woo Jin Hyung ◽  
...  

AbstractThis study aims to evaluate the performance of a radiomic signature-based model for predicting recurrence-free survival (RFS) of locally advanced gastric cancer (LAGC) using preoperative contrast-enhanced CT. This retrospective study included a training cohort (349 patients) and an external validation cohort (61 patients) who underwent curative resection for LAGC in 2010 without neoadjuvant therapies. Available preoperative clinical factors, including conventional CT staging and endoscopic data, and 438 radiomic features from the preoperative CT were obtained. To predict RFS, a radiomic model was developed using penalized Cox regression with the least absolute shrinkage and selection operator with ten-fold cross-validation. Internal and external validations were performed using a bootstrapping method. With the final 410 patients (58.2 ± 13.0 years-old; 268 female), the radiomic model consisted of seven selected features. In both of the internal and the external validation, the integrated area under the receiver operating characteristic curve values of both the radiomic model (0.714, P < 0.001 [internal validation]; 0.652, P = 0.010 [external validation]) and the merged model (0.719, P < 0.001; 0.651, P = 0.014) were significantly higher than those of the clinical model (0.616; 0.594). The radiomics-based model on preoperative CT images may improve RFS prediction and high-risk stratification in the preoperative setting of LAGC.


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