Dataset Information

Transcriptomic analysis identifies CYP27A1 as a diagnostic marker for the prognosis and immunity in lung adenocarcinoma.

ABSTRACT:

Background

The association between lipid metabolism disorder and carcinogenesis is well-established, but there is limited research on the connection between lipid metabolism-related genes (LRGs) and lung adenocarcinoma (LUAD). The objective of our research was to identify LRGs as the potential biomarkers for prognosis and assess their impact on immune cell infiltration in LUAD.

Methods

We identified novel prognostic LRGs for LUAD patients via the bioinformatics analysis. CYP27A1 expression level was systematically evaluated via various databases, such as TCGA, UALCAN, and TIMER. Subsequently, LinkedOmics was utilized to perform the CYP27A1 co-expression network and GSEA. ssGSEA was conducted to assess the association between infiltration of immune cells and CYP27A1 expression. CYP27A1's expression level was validated by qRT-PCR analysis.

Results

CYP27A1 expression was decreased in LUAD. Reduced CYP27A1 expression was linked to unfavorable prognosis in LUAD. Univariate and multivariate analyses indicated that CYP27A1 was an independent prognostic biomarker for LUAD patients. GSEA results revealed a positive correlation between CYP27A1 expression and immune-related pathways. Furthermore, CYP27A1 expression was positively correlated with the infiltration levels of most immune cells.

Conclusion

CYP27A1 is a potential biomarker for LUAD patients, and our findings provided a novel perspective to develop the prognostic marker for LUAD patients.

SUBMITTER: Yin Y

PROVIDER: S-EPMC10565965 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Publications

Transcriptomic analysis identifies CYP27A1 as a diagnostic marker for the prognosis and immunity in lung adenocarcinoma.

Yin Yi Y He Muqun M Huang Yunjian Y Xie Xianhe X

BMC immunology 20231010 1

<h4>Background</h4>The association between lipid metabolism disorder and carcinogenesis is well-established, but there is limited research on the connection between lipid metabolism-related genes (LRGs) and lung adenocarcinoma (LUAD). The objective of our research was to identify LRGs as the potential biomarkers for prognosis and assess their impact on immune cell infiltration in LUAD.<h4>Methods</h4>We identified novel prognostic LRGs for LUAD patients via the bioinformatics analysis. CYP27A1 e ...[more]

PMID: 37817081

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Project description:BackgroundLung cancer is the most common cause of cancer-related death worldwide. The most prevalent histological subtype of lung cancer is lung adenocarcinoma (LUAD), with incidence rising each year. Treating LUAD remains a significant issue due to a lack of early diagnosis and poor therapy outcomes. YKT6 is a member of the SNARE protein family, whose clinical value and biological function in LUAD has yet to be established.MethodsTCGA, HPA and UALCAN were used to analyze YKT6 mRNA and protein levels, the correlation between YKT6 expression and clinicopathological features and prognosis. YKT6 mRNA and protein expression were verified by qRT-PCR, immunohistochemistry (IHC) and tissue microarrays (TMA). Additionally, lung cancer cell lines were chosen for YKT6 silencing to explore the effects on cell proliferation and migration. The cBioPortal was used to select YKT6-related genes. Protein-protein interaction (PPI) network was created based on STRING database and hub genes were screened, with their expression levels and prognosis values in LUAD analyzed accordingly. YKT6-related genes were enriched by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses.ResultsIn LUAD, YKT6 was distinctly highly expressed with relation to clinical features of staging, smoking, lymph node metastasis, and TP53 mutation. Elevated YKT6 expression was linked to adverse prognosis, serving as an independent unfavorable prognostic factor. Moreover, YKT6 presented high diagnostic value in LUAD patients (AUC = 0.856). Experimental validation indicated that freshly collected LUAD tissues showed significantly high mRNA expression of YKT6. IHC and TMA verified increased YKT6 protein level in LUAD. Knockdown of YKT6 inhibited cell proliferation and promoted apoptosis, with mitigated capability of migration and invasion. The top ten hub genes screened by PPI network were highly expressed in LUAD, and significantly associated with poor prognosis. GO and KEGG analyses showed that YKT6-related genes were mainly involved in cell cycle.ConclusionElevated YKT6 expression is related to poor prognosis of LUAD patients. YKT6 can serve as a novel biomarker for LUAD diagnosis and prognosis. Cell proliferation, migration and invasion was impaired with increased apoptosis upon YKT6 silencing in lung cancer cells. In summary, this study comprehensively uncovered that YKT6 could be identified as a potential prognostic and diagnostic biomarker in LUAD.

Project description:BackgroundLung cancer continues to be a problem faced by all of humanity. It is the cancer with the highest morbidity and mortality in the world, and the most common histological type of lung cancer is lung adenocarcinoma (LUAD), accounting for about 40% of lung malignant tumors. This study was conducted to discuss and explore the immune-related biomarkers and pathways during the development and progression of LUAD and their relationship with immunocyte infiltration.MethodsThe cohorts of data used in this study were downloaded from the Gene Expression Complex (GEO) database and the Cancer Genome Atlas Program (TCGA) database. Through the analysis of differential expression analysis, weighted gene co-expression network analysis (WGCNA), and least absolute shrinkage and selection operator(LASSO), selecting the module with the highest correlation with LUAD progression, and then the HUB gene was further determined. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were then used to study the function of these genes. Single-sample GSEA (ssGSEA) analysis was used to investigate the penetration of 28 immunocytes and their relationship with HUB genes. Finally, the receiver operating characteristic curve (ROC) was used to evaluate these HUB genes accurately to diagnose LUAD. In addition, additional cohorts were used for external validation. Based on the TCGA database, the effect of the HUB genes on the prognosis of LUAD patients was assessed using the Kaplan-Meier curve. The mRNA levels of some HUB genes in cancer cells and normal cells were analyzed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR).ResultsThe turquoise module with the highest correlation with LUAD was identified among the seven modules obtained with WGCNA. Three hundred fifty-four differential genes were chosen. After LASSO analysis, 12 HUB genes were chosen as candidate biomarkers for LUAD expression. According to the immune infiltration results, CD4 + T cells, B cells, and NK cells were high in LUAD sample tissue. The ROC curve showed that all 12 HUB genes had a high diagnostic value. Finally, the functional enrichment analysis suggested that the HUB gene is mainly related to inflammatory and immune responses. According to the RT-qPCR study, we found that the expression of DPYSL2, OCIAD2, and FABP4 in A549 was higher than BEAS-2B. The expression content of DPYSL2 was lower in H1299 than in BEAS-2B. However, the expression difference of FABP4 and OCIAD2 genes in H1299 lung cancer cells was insignificant, but both showed a trend of increase.ConclusionsThe mechanism of LUAD pathogenesis and progression is closely linked to T cells, B cells, and monocytes. 12 HUB genes(ADAMTS8, CD36, DPYSL2, FABP4, FGFR4, HBA2, OCIAD2, PARP1, PLEKHH2, STX11, TCF21, TNNC1) may participate in the progression of LUAD via immune-related signaling pathways.

Dataset Information

Transcriptomic analysis identifies CYP27A1 as a diagnostic marker for the prognosis and immunity in lung adenocarcinoma.

Background

Methods

Results

Conclusion

Publications

Transcriptomic analysis identifies CYP27A1 as a diagnostic marker for the prognosis and immunity in lung adenocarcinoma.

Similar Datasets

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