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Cancer Biology

High expression of LUM independently predicts poor prognosis in gastric cancer: a bioinformatics study combining TCGA and GEO datasets

ORCID Icon, & ORCID Icon
Pages 1063-1072 | Received 08 Aug 2021, Accepted 27 Oct 2021, Published online: 17 Nov 2021
 

Abstract

LUM, a less-explored member of small leucine-rich proteoglycan family, has gained growing concern with controversial roles in tumor prognosis in recent years. The function of LUM in gastric cancer remains rarely reported and largely unclear. In this study, we investigated the expression of LUM in gastric cancer as well as its association with clinical parameters. Data from the GEO and Human Protein Atlas (HPA) databases are used for further validation. GC tissue shows significantly high expression of LUM compared with normal tissue (P < 0.001). High expression of LUM is correlated with poor differentiation, advanced tumor stage, deeper local invasion and worse overall survival. Patients with high expression of LUM have significantly worse prognosis than those with low expression. Multivariate analysis shows that high expression of LUM is an independent risk factor for overall survival. Several biomolecular pathways, including extracellular matrix receptor interaction, melanoma, cancer, chemokine signaling, Toll-like receptor signaling and Wnt signaling, are screened out as significantly enriched in GCs with high LUM expression using GSEA. Our study reveals that LUM, as an independent predictor, is highly expressed and associated with clinicopathologic factors in gastric cancer, demonstrating potential applications in prognosis of patient with gastric cancer.

Acknowledgements

The authors extend deepest appreciation to Dr Huang Yingshi for editing the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data accessibility

The datasets or profiles used in the current study are from TCGA and GEO databases, which are available at the following websites:

https://portal.gdc.cancer.gov/repository

https://www.ncbi.nlm.nih.gov/geo/

https://www.proteinatlas.org/