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Tumor-Associated Neutrophils Can Predict Lymph Node Metastasis in Early Gastric Cancer.

ABSTRACT: The consensus of endoscopic therapy for early gastric cancer (EGC) mainly depends on its clinicopathological features. However, the roles of tumor-associated neutrophils (TANs) in EGC remain uncertain. Here, we explored its predictive role for lymph node metastasis (LNM) in EGC. Three hundred twenty-two patients who underwent radical gastrectomy for EGC were enrolled. Preoperative peripheral blood was used to analyze the neutrophil-to-lymphocyte ratio (NLR), and the different status of TANs was determined by hematoxylin-and-eosin staining (H&E) and immunohistochemistry (IHC). TANs, rather than NLR, were positively associated with tumor size, Lauren classification, lymphovascular invasion (LVI), and LNM. Univariate analysis revealed that TANs were associated with LNM as well as tumor size, depth of invasion, Lauren classification, histological classification, LVI, and perineural invasion. In addition to histological classification and LVI, TANs were found to be an independent risk factor for LNM in EGC (P = 0.013). Stratification analysis by depth of invasion showed LVI in SM1 tumor, and both LVI and TANs (P = 0.042) in SM2 tumor were independent risk factors for LNM. In conclusion, TANs in EGC can predict LNM, and TANs may help to estimate LNM precisely in addition to the current criteria.

SUBMITTER: Wang Y

PROVIDER: S-EPMC7537418 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Tumor-Associated Neutrophils Can Predict Lymph Node Metastasis in Early Gastric Cancer.

Wang Yaohui Y Zhai Jing J Zhang Tiancheng T Han Shutang S Zhang Yifen Y Yao Xuequan X Shen Lizong L

Frontiers in oncology 20200921

The consensus of endoscopic therapy for early gastric cancer (EGC) mainly depends on its clinicopathological features. However, the roles of tumor-associated neutrophils (TANs) in EGC remain uncertain. Here, we explored its predictive role for lymph node metastasis (LNM) in EGC. Three hundred twenty-two patients who underwent radical gastrectomy for EGC were enrolled. Preoperative peripheral blood was used to analyze the neutrophil-to-lymphocyte ratio (NLR), and the different status of TANs was ...[more]

PMID: 33072602

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Project description:Importance:Lymph node status is the primary determinant in treatment decision making in early gastric cancer (EGC). Current evaluation methods are not adequate for estimating lymph node metastasis (LNM) in EGC. Objective:To develop and validate a prediction model based on a fully quantitative collagen signature in the tumor microenvironment to estimate the individual risk of LNM in EGC. Design, Setting, and Participants:This retrospective study was conducted from August 1, 2016, to May 10, 2018, at 2 medical centers in China (Nanfang Hospital and Fujian Provincial Hospital). Participants included a primary cohort (n = 232) of consecutive patients with histologically confirmed gastric cancer who underwent radical gastrectomy and received a T1 gastric cancer diagnosis from January 1, 2008, to December 31, 2012. Patients with neoadjuvant radiotherapy, chemotherapy, or chemoradiotherapy were excluded. An additional consecutive cohort (n = 143) who received the same diagnosis from January 1, 2011, to December 31, 2013, was enrolled to provide validation. Baseline clinicopathologic data of each patient were collected. Collagen features were extracted in specimens using multiphoton imaging, and the collagen signature was constructed. An LNM prediction model based on the collagen signature was developed and was internally and externally validated. Main Outcomes and Measures:The area under the receiver operating characteristic curve (AUROC) of the prediction model and decision curve were analyzed for estimating LNM. Results:In total, 375 patients were included. The primary cohort comprised 232 consecutive patients, in whom the LNM rate was 16.4% (n = 38; 25 men [65.8%] with a mean [SD] age of 57.82 [10.17] years). The validation cohort consisted of 143 consecutive patients, in whom the LNM rate was 20.9% (n = 30; 20 men [66.7%] with a mean [SD] age of 54.10 [13.19] years). The collagen signature was statistically significantly associated with LNM (odds ratio, 5.470; 95% CI, 3.315-9.026; P < .001). Multivariate analysis revealed that the depth of tumor invasion, tumor differentiation, and the collagen signature were independent predictors of LNM. These 3 predictors were incorporated into the new prediction model, and a nomogram was established. The model showed good discrimination in the primary cohort (AUROC, 0.955; 95% CI, 0.919-0.991) and validation cohort (AUROC, 0.938; 95% CI, 0.897-0.981). An optimal cutoff value was selected in the primary cohort, which had a sensitivity of 86.8%, a specificity of 93.3%, an accuracy of 92.2%, a positive predictive value of 71.7%, and a negative predictive value of 97.3%. The validation cohort had a sensitivity of 90.0%, a specificity of 90.3%, an accuracy of 90.2%, a positive predictive value of 71.1%, and a negative predictive value of 97.1%. Among the 375 patients, a sensitivity of 87.3%, a specificity of 92.1%, an accuracy of 91.2%, a positive predictive value of 72.1%, and a negative predictive value of 96.9% were found. Conclusions and Relevance:This study's findings suggest that the collagen signature in the tumor microenvironment is an independent indicator of LNM in EGC, and the prediction model based on this collagen signature may be useful in treatment decision making for patients with EGC.

Dataset Information

Tumor-Associated Neutrophils Can Predict Lymph Node Metastasis in Early Gastric Cancer.

Publications

Tumor-Associated Neutrophils Can Predict Lymph Node Metastasis in Early Gastric Cancer.

Similar Datasets

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