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Transcription Factors Contribute to Differential Expression in Cellular Pathways in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

  • Shiyi Liu
  • Xujun Wang
  • Wenyi Qin
  • Georgi Z. Genchev
  • Hui Lu
Original Research Article

Abstract

Lung cancers are broadly classified into small cell lung cancers and non-small cell lung cancers (NSCLC). Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are two common subtypes of NSCLC, and despite the fact that both occur in lung tissues, these two subtypes show a number of different pathological characteristics. To investigate the differences and seek potential therapy targets, we used bioinformatics methods to analyze RNA-Seq data from different aspects. The previous studies and comparative pathway enrichment analysis on publicly available data showed that expressed or inhibited genes are different in two cancer subtypes through important pathways. Some of these genes could not only affect cell function through expression, but also could regulate other genes’ expression by binding to a specific DNA sequence. This kind of genes is called transcription factor (TF) or sequence-specific DNA-binding factor. Transcription factors play important roles in controlling gene expression in carcinoma pathways. Our results revealed transcription factors that may cause differential expression of genes in cellular pathways of LUAD and LUSC, which provide new clues for study and treatment. Once such TF is NFE2l2 which may regulate genes in the Wnt signaling pathway, and the MAPK signaling pathway, thus leading to an increase the cell growth, cell division, and gene transcription. Another TF-XBP1 has high correlation with genes related to cell adhesion molecules and cytokine–cytokine receptor interaction pathways that may further affect the immune system. Moreover, the two TF and high correlated genes also show similar patterns in an independent GEO data set.

Keywords

LUAD LUSC Transcription factor Gene expression features Enrichment analysis RNA-Seq 

Abbreviations

LUAD

Lung adenocarcinoma

LUSC

Lung squamous cell carcinoma

NSCLC

Non-small cell lung carcinoma

GSEA

Gene set enrichment analysis

FDR

False discovery rate

Notes

Acknowledgements

This result here is based upon the data generated by TCGA Research Network: http://cancergenome.nih.gov/. We gratefully acknowledge contributions from the TCGA Research Network and the specimen donors. Furthermore, we thank Lung Cancer Group of Spanish National Cancer Center for providing validation microarray data set.

Funding

This work is supported in part by the National Natural Science Foundation of China (Nos. 31071167 and 31370751), Shanghai Municipal. Commission of Health and Family Planning (Grant No. 20144Y0179), Neil Shen's Medical Research Fund to SJTU-Yale Joint Center for Biostatistics, and Shanghai Engineering Research Center Project (17DZ2251200).

Compliance with Ethical Standards

Conflict of interest

The authors declare no conflicts of interest.

Supplementary material

12539_2018_300_MOESM1_ESM.tiff (2.4 mb)
Supplementary Figure 1: Venn diagram of expressed and inhibited genes with FDR < 0.05 in LUAD and LUSC. The figure shows that inhibited gene set share larger overlap area than expressed gene set. (TIFF 2502 KB)
12539_2018_300_MOESM2_ESM.tiff (1.7 mb)
Supplementary Figure 2: Pathway enrichment on differential expression in LUAD and LUSC. A. Cell cycle and DNA replication pathway are overexpressed in LUSC. B. CAMS and immune system-related pathway are overinhibited in LUSC. C. Protein export and cell adhesion are overexpressed in LUAD. D. Wnt signaling pathway and MAPK signaling pathway and tight junction are overinhibited in LUAD. (TIFF 1781 KB)
12539_2018_300_MOESM3_ESM.tif (4.3 mb)
Supplementary Figure 3: Correlation between enriched transcription factors and target genes provided using GSEA. (TIF 4405 KB)
12539_2018_300_MOESM4_ESM.tif (12.9 mb)
Supplementary Figure 4: Correlation between XBP1, NFE2L2, and their potential target genes through different stages in TCGA data set. (TIF 13223 KB)
12539_2018_300_MOESM5_ESM.tif (2.6 mb)
Supplementary Figure 5: Pathway enrichment analysis in GEO data set. (TIF 2611 KB)
12539_2018_300_MOESM6_ESM.tiff (2.1 mb)
Supplementary Figure 6: Boxplot of counts from XBP1 and CD4 RNA-Seq data in LUAD and LUSC tumor samples. (TIFF 2172 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Shiyi Liu
    • 1
  • Xujun Wang
    • 1
    • 2
  • Wenyi Qin
    • 2
    • 3
  • Georgi Z. Genchev
    • 2
  • Hui Lu
    • 1
    • 2
    • 3
  1. 1.Department of Bioinformatics and BiostatisticsShanghai Jiaotong UniversityShanghaiChina
  2. 2.SJTU-Yale Joint Center for BiostatisticsShanghai Jiaotong UniversityShanghaiChina
  3. 3.Department of BioengineeringUniversity of Illinois at ChicagoChicagoUSA

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