Faculty and Student Publications

Document Type

Article

Publication Date

10-30-2021

Abstract

Background: The major histocompatibility complex class I polypeptide-related sequence A (MICA) is one of the ligands of the natural killer group 2D (NKG2D) activating receptor. MICA stimulates NKG2D, which further triggers activation of natural killer cells and leads to killing of infected target cells. To subvert the biological function of NKG2D, tumor cells utilize an escape strategy by shedding overexpressed MICA. In this study, we determined the levels of MICA in colorectal cancers (CRCs). Additionally, we established correlations between MICA expression and clinical characteristics. Publicly available data and bioinformatics tools were used for validation purposes. Methods: We determined the MICA RNA expression levels and assessed their correlation with clinicopathological parameters in CRC using the UALCAN web-portal. We performed immunohistochemical analysis on tissue microarrays having 192 samples, acquired from 96 CRC patients, to validate the expression of MICA in CRC and adjacent uninvolved tissue and investigated its prognostic significance by Kaplan-Meier and proportional hazards methods. Results: Bioinformatics and immunohistochemical analyses showed that MICA expression was significantly upregulated in CRCs as compared to uninvolved tissue, and the overexpression of MICA was independent of pathologic stage, histotype, nodal metastasis status, p53-status, as well as patient's race, age and gender. Moreover, PROGgeneV2 survival analysis of two cohorts showed a poor prognosis for CRC patients exhibiting high MICA expression. Conclusions: Overall, our findings for CRC patients demonstrate generally high expression of MICA, and suggest that a poor prognosis relates to high MICA expression. These results can be further explored due to their potential to provide clues to the contribution of the tumor microenvironment to the progression of CRC.

Relational Format

journal article

DOI

10.52586/4986

Accessibility Status

Searchable text

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.