Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12957-016-1033-z
Title: The expression of metastasis-associated in colon cancer-1 and KAI1 in gastric adenocarcinoma and their clinical significance
Authors: Lu, G
Zhou, L 
Zhang, X
Zhu, B
Wu, S
Song, W
Gong, X
Wang, D
Tao, Y
Keywords: Kangai 1
metastasis associated in colon cancer 1 protein
tumor protein
unclassified drug
CD82 antigen
CD82 protein, human
MACC1 protein, human
transcription factor
tumor marker
adult
Article
cancer grading
cancer patient
cancer prognosis
cancer staging
cancer survival
colon cancer
controlled study
female
histopathology
human
human tissue
immunohistochemistry
lymph node metastasis
major clinical study
male
overall survival
protein expression
protein function
stomach adenocarcinoma
survival time
tumor biopsy
tumor volume
adenocarcinoma
aged
case control study
enzyme immunoassay
follow up
gene expression regulation
lymph node metastasis
metabolism
middle aged
pathology
prognosis
secondary
stomach tumor
survival rate
tumor invasion
Adenocarcinoma
Adult
Aged
Antigens, CD82
Biomarkers, Tumor
Case-Control Studies
Female
Follow-Up Studies
Gene Expression Regulation, Neoplastic
Humans
Immunoenzyme Techniques
Lymphatic Metastasis
Male
Middle Aged
Neoplasm Grading
Neoplasm Invasiveness
Neoplasm Staging
Prognosis
Stomach Neoplasms
Survival Rate
Transcription Factors
Issue Date: 2016
Citation: Lu, G, Zhou, L, Zhang, X, Zhu, B, Wu, S, Song, W, Gong, X, Wang, D, Tao, Y (2016). The expression of metastasis-associated in colon cancer-1 and KAI1 in gastric adenocarcinoma and their clinical significance. World Journal of Surgical Oncology 14 (1) : 276. ScholarBank@NUS Repository. https://doi.org/10.1186/s12957-016-1033-z
Rights: Attribution 4.0 International
Abstract: Background: The most common reason for malignant tumor treatment failure is recurrence and metastasis. Metastasis-associated in colon cancer-1 (MACC1) was originally identified as a metastatic and prognostic biomarker for colon cancer and later other solid tumors. Kangai 1 (KAI1), a marker of suppressor of metastasis, is also associated with metastasis and poor prognosis in many tumors. However, the prognostic value of either MACC1 or KAI1 in gastric adenocarcinoma (GAC) is unclear. In this study, we explored the relationship between MACC1 and KAI1 expression, as well as their respective correlation with clinicopathological features, to determine if either could be helpful for improvement of survival prognosis in GAC patients. Methods: The expression levels of both MACC1 and KAI1 in 325 whole-tissue sections of GAC were examined by immunohistochemistry. Clinical data was also collected. Results: MACC1 was significantly overexpressed in GAC tissues when compared to levels in normal gastric tissues; KAI1 was significantly down-expressed in GAC tissues when compared to levels in normal gastric tissues. Investigation of association between MACC1 and KAI1 protein levels with clinicopathological parameters of GAC indicated association between the expression of each with tumor grade, lymph node metastasis, invasive depth, and TNM stages. The overall survival time of patients with MACC1- or KAI1-positive GAC tumors was significantly shorter or longer than that of those who were negative. Importantly, multivariate analysis suggested that positive expression of either MACC1 or KAI1, as well as TNM stage, could be independent prognostic factors for overall survival in patients with GAC. Conclusions: MACC1 and KAI1 may represent promising metastatic and prognostic biomarkers, as well as potential therapeutic targets, for GAC. © 2016 The Author(s).
Source Title: World Journal of Surgical Oncology
URI: https://scholarbank.nus.edu.sg/handle/10635/181330
ISSN: 14777819
DOI: 10.1186/s12957-016-1033-z
Rights: Attribution 4.0 International
Appears in Collections:Elements
Staff Publications

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1186_s12957-016-1033-z.pdf753.57 kBAdobe PDF

OPEN

NoneView/Download

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons