The predictive value of MISP for the postoperative outcomes of gastric cancer

Gastric cancer (GC) is defined as the primary epithelial malignancy derived from the stomach. This study aims to investigate the predictive and prognostic values of mitotic spindle positioning (MISP) expression in patients with GC, providing new strategies for GC diagnosis and prognosis. MISP expression in GC tissues and adjacent tissues from 120 GC patients was detected. The correlation between pathological characteristics and MISP expression was analyzed. Pathological conditions of patients after 5 years of postoperative treatment were recorded. The correlation between MISP expression and postoperative outcomes of GC patients was analyzed using the Kaplan-Meier method. Cox proportional hazards model was used to analyze independent risk factors affecting the 5-year survival rate of GC patients. MISP expression in GC tissues was higher than in adjacent tissues. MISP expression was correlated with differentiation degree, invasion, lymph node metastasis, and Lauren classification. Patients in the high MISP expression group tended to have poorer postoperative outcomes. High MISP expression was an independent risk factor for the 5-year survival rate of GC patients. In conclusion, high expression of MISP in GC patients indicates a higher possibility of adverse prognosis and is an independent risk factor affecting the post-operative survival rate of GC patients.

Authors

Institutions

Publication Details

Journal
Biomedical Research
Published
2025-05-22
DOI
https://doi.org/10.2220/biomedres.46.93
Citations
1
Primary Topic
Gastric Cancer Management and Outcomes
Type
article
Field-Weighted Citation Impact
1.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The predictive value of MISP for the postoperative outcomes of gastric cancer

Yuan‐Feng Lin, Hao Wang, Xiao Jin, Lei Xin et al.
1 citations
Biomedical Research
Gastric Cancer Management and Outcomes
1.52
article

The predictive value of MISP for the postoperative outcomes of gastric cancer

Yuan‐Feng Lin, Hao Wang, Xiao Jin, Lei Xin, Yan Zhou
article en
1 citations

Abstract

Gastric cancer (GC) is defined as the primary epithelial malignancy derived from the stomach. This study aims to investigate the predictive and prognostic values of mitotic spindle positioning (MISP) expression in patients with GC, providing new strategies for GC diagnosis and prognosis. MISP expression in GC tissues and adjacent tissues from 120 GC patients was detected. The correlation between pathological characteristics and MISP expression was analyzed. Pathological conditions of patients after 5 years of postoperative treatment were recorded. The correlation between MISP expression and postoperative outcomes of GC patients was analyzed using the Kaplan-Meier method. Cox proportional hazards model was used to analyze independent risk factors affecting the 5-year survival rate of GC patients. MISP expression in GC tissues was higher than in adjacent tissues. MISP expression was correlated with differentiation degree, invasion, lymph node metastasis, and Lauren classification. Patients in the high MISP expression group tended to have poorer postoperative outcomes. High MISP expression was an independent risk factor for the 5-year survival rate of GC patients. In conclusion, high expression of MISP in GC patients indicates a higher possibility of adverse prognosis and is an independent risk factor affecting the post-operative survival rate of GC patients.

Biomedical ResearchVol. 46(3)
Yantaishan Hospital (CN)
Zero hunger
Openalex Percentile: Top 18%
Gastric Cancer Management and Outcomes
1.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.