Predictors of Lymph Node Metastasis and Differences Between Pure and Mixed Histologic Types of Early Gastric Signet-ring Cell Carcinomas

Chu, Yuning; Mao, Tao; Li, Xiaoyü; Xue, Jie; Ren, Ming-Han; Huang, Zhen; Zhou, Xiaobin; Chen, Yunqing; Tian, Zibin

doi:10.1097/pas.0000000000001460

Cited by 13 publications

(9 citation statements)

References 30 publications

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“…Molecular mechanisms underlying the unfavorable behavior are still unclear. Anyway, it has been postulated that more aggressive clinicopathological as well as morphological findings of mixed-type cancers (10,31) could be attributed to the angiogenetic process and cell proliferation, to cytosinephosphate-guanine (CpG) island hypermethylation (32), or to the unregulated expression of proteins such as Ki-67, E-cadherin, and VEGF proteins, which were involved in proliferation (10), adhesion, and angiogenesis activities (10,28). Interestingly, some researchers argued that mixed type would undergo transitional events leading to phenotype transformation along with cancer progression (33).…”

Section: Discussionmentioning

confidence: 99%

The Percentage of Signet Ring Cells Is Inversely Related to Aggressive Behavior and Poor Prognosis in Mixed-Type Gastric Cancer

et al. 2022

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Background and ObjectivesOnly recently the percentage of signet ring cells (SRCs) in gastric cancer (GC) has been proposed as an independent predictor of survival. High amounts of SRCs have been related to lower recurrence and mortality rates, better prognosis, and favorable clinicopathological features in a poorly cohesive histotype. It is not known what the effect of SRC percentage in mixed-type GC is. We investigate the role of SRCs as a prognostic marker in mixed-histotype GC.MethodsA retrospective analysis was performed through a prospectively maintained database of patients with diagnosed “mixed-type” gastric carcinoma, defined according to 2019 WHO classification. These patients underwent surgery between 1995 and 2016, and their tissue samples were stored in a tissue bank. All slides were analyzed, and patients were divided into three groups according to the percentage of SRCs: “Group 1” (displaying ≤10% of SRCs), “Group 2” (displaying <90% but >10% of SRCs), and “Group 3” (displaying ≥90% of SRCs). We compared clinical and pathological features as well as prognostic factors between the different groups.ResultsAmong 164 enrolled patients, 68.9% were male and 31.1% were female (p = 0.612). The mean (±SD) age at diagnosis was 71.4 ± 9.6 years. Ninety-eight (59.7%) patients were classified as “Group 1”, 66 (40.3%) as “Group 2”, and none as “Group 3”. Five-year overall survival was remarkably higher in Group 2 (73.8%) in comparison to Group 1 (35.4%), p < 0.001. Mortality risk was three times higher in patients with ≤10% SRC pattern compared to those with >10% [HR 2.70 (95% CI 1.72–4.24)]. After adjusting according to potential confounding factors, SRC percentage was still an independent predictor of survival.ConclusionsThe proportion of SRCs is inversely related to aggressive behavior and poor prognosis in mixed-type GCs, highlighting the role of SRC amount as an independent predictor of survival.

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Section: Discussionmentioning

confidence: 99%

The Percentage of Signet Ring Cells Is Inversely Related to Aggressive Behavior and Poor Prognosis in Mixed-Type Gastric Cancer

et al. 2022

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“…The previous studies confirmed that several risks such as tumor size, invasion depth, ulceration, histological types, and lymph vascular invasion were related with LNM in EGC (13)(14)(15)(16). Even a few of research based on these factors constructed traditional scoring to evaluate the probability of LNM in EGC after the endoscopic resection (17,18).…”

Section: Introductionmentioning

confidence: 79%

A retrospective analysis based on multiple machine learning models to predict lymph node metastasis in early gastric cancer

et al. 2022

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BackgroundEndoscopic submucosal dissection has become the primary option of treatment for early gastric cancer. However, lymph node metastasis may lead to poor prognosis. We analyzed factors related to lymph node metastasis in EGC patients, and we developed a construction prediction model with machine learning using data from a retrospective series.MethodsTwo independent cohorts’ series were evaluated including 305 patients with EGC from China as cohort I and 35 patients from Spain as cohort II. Five classifiers obtained from machine learning were selected to establish a robust prediction model for lymph node metastasis in EGC.ResultsThe clinical variables such as invasion depth, histologic type, ulceration, tumor location, tumor size, Lauren classification, and age were selected to establish the five prediction models: linear support vector classifier (Linear SVC), logistic regression model, extreme gradient boosting model (XGBoost), light gradient boosting machine model (LightGBM), and Gaussian process classification model. Interestingly, all prediction models of cohort I showed accuracy between 70 and 81%. Furthermore, the prediction models of the cohort II exhibited accuracy between 48 and 82%. The areas under curve (AUC) of the five models between cohort I and cohort II were between 0.736 and 0.830.ConclusionsOur results support that the machine learning method could be used to predict lymph node metastasis in early gastric cancer and perhaps provide another evaluation method to choose the suited treatment for patients.

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“…Within the undifferentiated type, SRC has a lower lymph node metastasis frequency, which is reported to be at a level similar to that of the differentiated type [ 41 42 43 ]. In addition, some reports indicate that the lymph node metastasis frequency is lower in pure SRC cases than in SRC cases mixed with other component types [ 44 45 46 47 ]. However, only the histologic type is applied for determining whether an endoscopic resection is curative, and because differences in histologic components are not applied, they are reflected as conditional elements rather than a standard element.…”

Section: Application Of Standard Pathology Reportmentioning

confidence: 99%

A Standardized Pathology Report for Gastric Cancer: 2nd Edition

et al. 2023

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The first edition of ‘A Standardized Pathology Report for Gastric Cancer’ was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.

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Predictors of Lymph Node Metastasis and Differences Between Pure and Mixed Histologic Types of Early Gastric Signet-ring Cell Carcinomas

Cited by 13 publications

References 30 publications

The Percentage of Signet Ring Cells Is Inversely Related to Aggressive Behavior and Poor Prognosis in Mixed-Type Gastric Cancer

The Percentage of Signet Ring Cells Is Inversely Related to Aggressive Behavior and Poor Prognosis in Mixed-Type Gastric Cancer

A retrospective analysis based on multiple machine learning models to predict lymph node metastasis in early gastric cancer

A Standardized Pathology Report for Gastric Cancer: 2nd Edition

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