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. 2019 Jan;17(1):492-501.
doi: 10.3892/ol.2018.9598. Epub 2018 Oct 18.

Identification of potential genes and pathways for response prediction of neoadjuvant chemoradiotherapy in patients with rectal cancer by systemic biological analysis

Qiliang Peng  1   2   3 , Kaisu Lin  4 , Yi Shen  5 , Ping Zhou  1   2   3 , Shaonan Fan  1   2   3 , Yuntian Shen  1   2   3 , Yaqun Zhu  1   2   3
Affiliations

Identification of potential genes and pathways for response prediction of neoadjuvant chemoradiotherapy in patients with rectal cancer by systemic biological analysis

Qiliang Peng et al. Oncol Lett. 2019 Jan.

Abstract

Currently, neoadjuvant chemoradiotherapy (CRT) followed by radical surgery is the standard of care for locally advanced rectal cancer. However, to the best of our knowledge, there are no effective biomarkers for predicting patients who may benefit from neoadjuvant treatment. The aim of the current study was to screen potential crucial genes and pathways associated with the response to CRT in rectal cancer, and provide valid biological information to assist further investigation of CRT optimization. In the current study, differentially expressed (DE) genes were identified from the tumor samples of responders and non-responders to neoadjuvant CRT in the GSE35452 gene expression profile. Seven hub genes and one significant module were identified from the protein-protein interaction (PPI) network. Functional enrichment analysis of all the DE genes and the hub genes, retrieved from PPI network analysis, revealed their associations with CRT response. Genes were identified that may be used to discriminate patients who would or would not clinically benefit from neoadjuvant CRT. Several important pathways enriched by the DE genes, hub genes and selected module were identified, and revealed to be closely associated with radiation response, including excision repair, homologous recombination, Ras signaling pathway, the forkhead box O signaling pathway, focal adhesion and the Wnt signaling pathway. In conclusion, the current study demonstrated that the identified gene signatures and pathways may be used as molecular biomarkers for predicting CRT response. Furthermore, combinations of these biomarkers may be helpful for optimizing CRT treatment and promoting understanding of the molecular basis of response differences; this needs to be confirmed by further experiments.

Keywords: differentially expressed genes; enrichment analysis; pathways; rectal cancer.

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Figures

Figure 1.
Figure 1.
Heat map of the 100 most significantly differentially expressed genes (50 upregulated genes and 50 downregulated genes). Each row represents a single gene; each column represents a tissue sample. Green represents upregulated genes; red represents downregulated genes.
Figure 2.
Figure 2.
GO analysis of the DE genes. (A) Top five GO items for DE genes upregulated in CRT responders. (B) Top five GO items for DE genes downregulated in CRT responders. GO, Gene Ontology; BP, biological process; CC, cell component; MF, molecular function; DE, differentially expressed.
Figure 3.
Figure 3.
Degree distributions of network nodes.
Figure 4.
Figure 4.
Analysis of the selected hub nodes and modules. (A) The sub-network reconstructed with the selected hub nodes and their first neighbor genes. (B) KEGG pathways enriched by all hub nodes. (C) Biological process ontology terms enriched by all hub nodes. (D) The most significant modules identified from the protein-protein interaction network. (E) KEGG pathways enriched by all nodes associated with the identified module with the highest significance. KEGG, Kyoto Encyclopedia of Genes and Genomes; MAPK, mitogen-activated protein kinase; TRP, transient receptor potential; FoxO, forkhead box O; ERK, extracellular signal-regulated kinase.
Figure 4.
Figure 4.
Analysis of the selected hub nodes and modules. (A) The sub-network reconstructed with the selected hub nodes and their first neighbor genes. (B) KEGG pathways enriched by all hub nodes. (C) Biological process ontology terms enriched by all hub nodes. (D) The most significant modules identified from the protein-protein interaction network. (E) KEGG pathways enriched by all nodes associated with the identified module with the highest significance. KEGG, Kyoto Encyclopedia of Genes and Genomes; MAPK, mitogen-activated protein kinase; TRP, transient receptor potential; FoxO, forkhead box O; ERK, extracellular signal-regulated kinase.
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