Systematic Multiomic Analysis of PKHD1L1 Gene Expression and Its Role as a Predicting Biomarker for Immune Cell Infiltration in Skin Cutaneous Melanoma and Lung Adenocarcinoma.
Int J Mol Sci
; 25(1)2023 Dec 26.
Article
em En
| MEDLINE
| ID: mdl-38203530
ABSTRACT
The identification of genetic factors that regulate the cancer immune microenvironment is important for understanding the mechanism of tumor progression and establishing an effective treatment strategy. Polycystic kidney and hepatic disease 1-like protein 1 (PKHD1L1) is a large transmembrane protein that is highly expressed in immune cells; however, its association with tumor progression remains unclear. Here, we systematically analyzed the clinical relevance of PKHD1L1 in the tumor microenvironment in multiple cancer types using various bioinformatic tools. We found that the PKHD1L1 mRNA expression levels were significantly lower in skin cutaneous melanoma (SKCM) and lung adenocarcinoma (LUAD) than in normal tissues. The decreased expression of PKHD1L1 was significantly associated with unfavorable overall survival (OS) in SKCM and LUAD. Additionally, PKHD1L1 expression was positively correlated with the levels of infiltrating B cells, cluster of differentiation (CD)-8+ T cells, and natural killer (NK) cells, suggesting that the infiltration of immune cells could be associated with a good prognosis due to increased PKHD1L1 expression. Gene ontology (GO) analysis also revealed the relationship between PKHD1L1-co-altered genes and the activation of lymphocytes, including B and T cells. Collectively, this study shows that PKHD1L1 expression is positively correlated with a good prognosis via the induction of immune infiltration, suggesting that PKHD1L1 has potential prognostic value in SKCM and LUAD.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Cutâneas
/
Adenocarcinoma de Pulmão
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Neoplasias Pulmonares
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Melanoma
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Int J Mol Sci
Ano de publicação:
2023
Tipo de documento:
Article