An Analysis of the Gene Expression Associated with Lymph Node Metastasis in Colorectal Cancer

Author:

Yang Hongjie12ORCID,Liu Jiafei1234ORCID,Jiang Peishi1234ORCID,Li Peng1234ORCID,Zhou Yuanda1234ORCID,Zhang Zhichun1234ORCID,Zeng Qingsheng1234ORCID,Wang Min5,Xiao Luciena Xiao6ORCID,Zhang Xipeng1234ORCID,Sun Yi1234ORCID,Zhu Siwei147ORCID

Affiliation:

1. Nankai University, Tianjin, China

2. Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, China

3. Tianjin Institute of Coloproctology, Tianjin, China

4. The Institute of Translational Medicine, Tianjin Union Medical Center of Nankai University, Tianjin, China

5. Key Laboratory of Molecular Microbiology and Technology, Ministry of Education, TEDA Institute of Biological Sciences and Biotechnology, Nankai University, Tianjin, China

6. Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland

7. Department of Oncology, Tianjin Union Medical Center, Tianjin, China

Abstract

Objective. This study aimed to explore the genes regulating lymph node metastasis in colorectal cancer (CRC) and to clarify their relationship with tumor immune cell infiltration and patient prognoses. Methods. The data sets of CRC patients were collected through the Cancer Gene Atlas database; the differentially expressed genes (DEGs) associated with CRC lymph node metastasis were screened; a protein–protein interaction (PPI) network was constructed; the top 20 hub genes were selected; the Gene Ontology functions and the Kyoto Encyclopedia of Genes and Genomes pathways were enriched and analyzed. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method was employed to further screen the characteristic genes associated with CRC lymph node metastasis in 20 hub genes, exploring the correlation between the characteristic genes and immune cell infiltration, conducting a univariate COX analysis on the characteristic genes, obtaining survival-related genes, constructing a risk score formula, conducting a Kaplan–Meier analysis based on the risk score formula, and performing a multivariate COX regression analysis on the clinical factors and risk scores. Results. A total of 62 DEGs associated with CRC lymph node metastasis were obtained. Among the 20 hub genes identified via PPI, only calcium-activated chloride channel regulator 1 (CLCA1) expression was down-regulated in lymph node metastasis, and the rest were up-regulated. A total of nine characteristic genes associated with CRC lymph node metastasis (KIF1A, TMEM59L, CLCA1, COL9A3, GDF5, TUBB2B, STMN2, FOXN1, and SCN5A) were screened using the LASSO regression method. The nine characteristic genes were significantly related to different kinds of immune cell infiltration, from which three survival-related genes (TMEM59L, CLCA1, and TUBB2B) were screened. A multi-factor COX regression showed that the risk scores obtained from TMEM59L, CLCA1, and TUBB2B were independent prognostic factors. Immunohistochemical validation was performed in tissue samples from patients with rectal and colon cancer. Conclusion. TMEM59L, CLCA1, and TUBB2B were independent prognostic factors associated with lymphatic metastasis of CRC.

Funder

Tianjin Key Medical Discipline (Specialty) Construction Project

Publisher

Hindawi Limited

Subject

Pharmaceutical Science,Genetics,Molecular Biology,Biochemistry

Reference51 articles.

1. GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;H. Sung;CA: a Cancer Journal for Clinicians,2021

2. Colon cancer;A. Recio-Boiles,2022

3. Origins of lymphatic and distant metastases in human colorectal cancer;K. Naxerova;Science,2017

4. Lymph node metastasis in colorectal cancer;M. Jin;Surgical Oncology Clinics of North America,2018

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3