Image_3_Genomic And Tumor Microenvironment Differences Between Cell Cycle Progression Pathway Altered/Non-Altered Patients With Lung Adenocarcinoma.tiff (4.2 MB)

Image_3_Genomic And Tumor Microenvironment Differences Between Cell Cycle Progression Pathway Altered/Non-Altered Patients With Lung Adenocarcinoma.tiff

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posted on 2022-02-28, 05:10 authored by Guangyao Shan, Guoshu Bi, Yunyi Bian, Besskaya Valeria, Dejun Zeng, Huan Zhang, Guangyu Yao, Yi Zhang, Hong Fan, Cheng Zhan

Background

Identified as a hallmark of cancer, the dysregulated cell cycle progression plays an important role in the promotion and progression of lung adenocarcinoma (LUAD). However, the genomic and microenvironment differences between cell cycle progression pathway altered/non-altered LUAD patients remain to be elucidated.

Materials and Methods

Data of this study were obtained from The Cancer Genome Atlas (TCGA), including simple nucleotide variation, copy number variation (CNV), RNA-seq gene expression, miRNA expression, survival, and clinical information. Besides, 34 LUAD samples from our institution were used as a validation cohort. Differentially expressed genes (DEGs), enrichment analysis, and immune cell infiltration were detected. At last, we built a LASSO-binary Logistic regression model to predict the cell-cycle-related gene mutation (CDKN2A, CCND1, CDK4, CCNE1, and RB1) in LUAD patients and further verified it in the samples from our institution.

Results

Based on the cell cycle progression pathway status, the LUAD patients were divided into the mutation (n=322) and wild (n=46) groups. Compared to the wild group, the mutation group had a higher mutational load and CNV. Among the 16684 protein-coding genes analyzed, 302 were upregulated, and 354 were downregulated in the mutation group. Enrichment analysis indicated that these DEGs were closely related to metabolism items. After performing immune cell infiltration analysis of 22 immune cells, we found the proportion of 5 immune cells such as monocytes (P<0.01) and dendritic cells (P<0.01) were higher in the wild group. Finally, a cell-cycle-related 15-signature model was built by LASSO-Logistic regression analysis, which could predict the cell cycle progression pathway-related gene mutation (CDKN2A, CCND1, CDK4, CCNE1, and RB1) in LUAD patients. The validation cohorts showed the sensitivity and specificity of this model were 0.667 and 0.929, respectively.

Conclusion

The genomic and microenvironment characteristics differed between the cell cycle progression pathway altered/non-altered patients with LUAD. Our findings may provide new insight into personalized treatment for LUAD patients.