Universität zu Köln

Zhong, Haihui, Wang, Jie, Zhu, Yaru and Shen, Yefeng (2021). Comprehensive Analysis of a Nine-Gene Signature Related to Tumor Microenvironment in Lung Adenocarcinoma. Front. Cell. Dev. Biol., 9. LAUSANNE: FRONTIERS MEDIA SA. ISSN 2296-634X

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Abstract

Lung adenocarcinoma (LUAD) is the most common malignancy, leading to more than 1 million related deaths each year. Due to low long-term survival rates, the exploration of molecular mechanisms underlying LUAD progression and novel prognostic predictors is urgently needed to improve LUAD treatment. In our study, cancer-specific differentially expressed genes (DEGs) were identified using the robust rank aggregation (RRA) method between tumor and normal tissues from six Gene Expression Omnibus databases (GSE43458, GSE62949, GSE68465, GSE115002, GSE116959, and GSE118370), followed by a selection of prognostic modules using weighted gene co-expression network analysis. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were applied to identify nine hub genes (CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6) that constructed a prognostic risk model. The RNA expressions of nine hub genes were validated in tumor and normal tissues by RNA-sequencing and single-cell RNA-sequencing, while immunohistochemistry staining from the Human Protein Atlas database showed consistent results in the protein levels. The risk model revealed that high-risk patients were associated with poor prognoses, including advanced stages and low survival rates. Furthermore, a multivariate Cox regression analysis suggested that the prognostic risk model could be an independent prognostic factor for LUAD patients. A nomogram that incorporated the signature and clinical features was additionally built for prognostic prediction. Moreover, the levels of hub genes were related to immune cell infiltration in LUAD microenvironments. A CMap analysis identified 13 small molecule drugs as potential agents based on the risk model for LUAD treatment. Thus, we identified a prognostic risk model including CBFA2T3, CR2, SEL1L3, TM6SF1, TSPAN32, ITGA6, MAPK11, RASA3, and TLR6 as novel biomarkers and validated their prognostic and predicted values for LUAD.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Zhong, Haihui UNSPECIFIED UNSPECIFIED UNSPECIFIED Wang, Jie UNSPECIFIED UNSPECIFIED UNSPECIFIED Zhu, Yaru UNSPECIFIED UNSPECIFIED UNSPECIFIED Shen, Yefeng UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-578083
DOI:	10.3389/fcell.2021.700607
Journal or Publication Title:	Front. Cell. Dev. Biol.
Volume:	9
Date:	2021
Publisher:	FRONTIERS MEDIA SA
Place of Publication:	LAUSANNE
ISSN:	2296-634X
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language GLOBAL CANCER STATISTICS; BREAST-CANCER; CELL; GENE; EXPRESSION; PROTEIN; VALIDATION; VORINOSTAT; PROGNOSIS; GENOMICS Multiple languages Cell Biology; Developmental Biology Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/57808