Comparison of postoperative lymphocytes and interleukins between laparoscopy-assisted and open radical gastrectomy for early gastric cancer

Objective This study aimed to study the effects of laparoscopic-assisted radical gastrectomy (LAG) and open radical gastrectomy (OG) on immune function and inflammatory factors in patients with early gastric cancer. Methods Seventy-five patients with pT1N0M0 gastric cancer in Ren Ji Hospital from August 2017 to January 2018 were studied. Lymphocytes subsets and interleukins were compared preoperatively and on the third postoperative day (POD3) and seventh postoperative day (POD7). Results There were no significant differences in age, sex, body mass index, duration of the operation, estimated blood loss, total gastrectomy rate, postoperative first fluid diet, and the levels of preoperative lymphocytes subsets and interleukins between the two groups. The number of CD4+ T cells and the CD4+/CD8+ ratio in the LAG group were significantly higher than those in the OG group on POD3. However, the number of CD8+ T cells, and interleukin-6 and interleukin-8 levels in the LAG group were significantly lower than those in the OG group on POD3. Conclusions Laparoscopy can effectively reduce the levels of inflammatory factors and has less effect on the immune system than OG.

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Prognostic analysis of patients with intra-abdominal infectious complications after laparoscopic-assisted and open radical gastrectomy for gastric cancer – A propensity score-matching analysis

Surgical Oncology ◽

10.1016/j.suronc.2021.101583 ◽

2021 ◽

pp. 101583

Author(s):

Jia-Bin Wang ◽

Si-Jin Que ◽

Qi-Yue Chen ◽

Qing Zhong ◽

Zhi-Yu Liu ◽

...

Keyword(s):

Gastric Cancer ◽

Propensity Score ◽

Propensity Score Matching ◽

Infectious Complications ◽

Radical Gastrectomy ◽

Propensity Score Matching Analysis ◽

Prognostic Analysis ◽

Laparoscopic Assisted

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Laparoscopic-assisted versus open radical gastrectomy for resectable gastric cancer: Systematic review, meta-analysis, and trial sequential analysis of randomized controlled trials

Journal of Surgical Oncology ◽

10.1002/jso.24243 ◽

2016 ◽

Vol 113 (7) ◽

pp. 756-767 ◽

Cited By ~ 23

Author(s):

Hui-Zi Li ◽

Jia-Xi Chen ◽

Yang Zheng ◽

Xiang-Nan Zhu

Keyword(s):

Gastric Cancer ◽

Systematic Review ◽

Sequential Analysis ◽

Meta Analysis ◽

Trial Sequential Analysis ◽

Controlled Trials ◽

Radical Gastrectomy ◽

Randomized Controlled ◽

Resectable Gastric Cancer ◽

Laparoscopic Assisted

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ILDR1 Is a Prognostic Biomarker and Associated With Immune Inﬁltration in Gastric Cancer

10.21203/rs.3.rs-944596/v1 ◽

2021 ◽

Author(s):

Yanling Ma ◽

WenBo Qi ◽

BaoHong Gu ◽

XueMei Li ◽

ZhenYu Yin ◽

...

Keyword(s):

Gastric Cancer ◽

T Cells ◽

Dendritic Cells ◽

Cancer Patients ◽

Cd8 T Cells ◽

Immune Cells ◽

Copy Number ◽

Sequencing Data ◽

Number Variation ◽

Gastric Cancer Patients

Abstract Objective: To investigate the association between ILDR1 and prognosis and immune infiltration in gastric cancer. Methods: We analyzed the RNA sequencing data of 9736 tumor tissues and 8587 normal tissues in the TCGA and GTEx databases through the GEPIA2 platform. The expression of ILDR1 in gastric cancer and normal gastric mucosa tissues with GEPIA and TIMER. Clinical subgroup analysis was made through Kaplan-Meier analysis. Analyzed the correlation between ILDR1 and VEGFA expression in gastric cancer, through the gene sequencing data of gastric cancer in TCGA. Explored the relationship between ILDR1 methylation and the prognosis of gastric cancer patients through the MethSurv database. The correlation between ILDR1 and immune cells and the correlation of copy number variation were explored through the TIMER database. Results: ILDR1-high GC patients had a lower PFS and OS. High ILDR1 expression was significantly correlated with tumor grade. There was a negative correlation between the ILDR1 expression and the abundances of CD8+ T, Macrophages and DC and etc. The methylation level of ILDR1 is associated with a good prognosis of gastric cancer. ILDR1 copy number variation was correlated with immune cells, IDLR1 arm-loss was associated with the infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells, and arm-duplication was associated with the infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells. Conclusion: The increased expression of ILDR1 is associated with poor prognosis in patients with gastric cancer. ILDR1 can be used as a novel predictive biomarker to provide a new therapeutic target for gastric cancer patients.

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Effect of Neoadjuvant Chemotherapy Laparoscopic-assisted Radical Gastrectomy on Advanced Gastric Cancer

10.47939/mh.v2i11.348 ◽

2021 ◽

Keyword(s):

Gastric Cancer ◽

Neoadjuvant Chemotherapy ◽

Advanced Gastric Cancer ◽

Radical Gastrectomy ◽

Laparoscopic Assisted

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A deep neural network improves endoscopic detection of early gastric cancer without blind spots

Endoscopy ◽

10.1055/a-0855-3532 ◽

2019 ◽

Vol 51 (06) ◽

pp. 522-531 ◽

Cited By ~ 33

Author(s):

Lianlian Wu ◽

Wei Zhou ◽

Xinyue Wan ◽

Jun Zhang ◽

Lei Shen ◽

...

Keyword(s):

Neural Network ◽

Gastric Cancer ◽

Early Gastric Cancer ◽

Predictive Value ◽

The Third ◽

Visual Tasks ◽

Deep Convolution Neural Network ◽

Different Parts ◽

Better Than ◽

Blind Spots

Abstract Background Gastric cancer is the third most lethal malignancy worldwide. A novel deep convolution neural network (DCNN) to perform visual tasks has been recently developed. The aim of this study was to build a system using the DCNN to detect early gastric cancer (EGC) without blind spots during esophagogastroduodenoscopy (EGD). Methods 3170 gastric cancer and 5981 benign images were collected to train the DCNN to detect EGC. A total of 24549 images from different parts of stomach were collected to train the DCNN to monitor blind spots. Class activation maps were developed to automatically cover suspicious cancerous regions. A grid model for the stomach was used to indicate the existence of blind spots in unprocessed EGD videos. Results The DCNN identified EGC from non-malignancy with an accuracy of 92.5 %, a sensitivity of 94.0 %, a specificity of 91.0 %, a positive predictive value of 91.3 %, and a negative predictive value of 93.8 %, outperforming all levels of endoscopists. In the task of classifying gastric locations into 10 or 26 parts, the DCNN achieved an accuracy of 90 % or 65.9 %, on a par with the performance of experts. In real-time unprocessed EGD videos, the DCNN achieved automated performance for detecting EGC and monitoring blind spots. Conclusions We developed a system based on a DCNN to accurately detect EGC and recognize gastric locations better than endoscopists, and proactively track suspicious cancerous lesions and monitor blind spots during EGD.

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