Reconstruction and Exploratory Analysis of mTORC1 Signaling Pathway and Its Applications to Various Diseases Using Network-Based Approach

Abstract

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

Keywords: differentially expressed genes; gene and pathway enrichment; mTORC1 network; survival analysis.

Fig. 1

Signaling and function of complexes formed by mTOR Ser/Thr kinase: mTORC1 and mTORC2 and their respective subunits.

Fig. 2

Flowchart depicting the overall methodology followed for the study.

Fig. 3. Electronic representation of mTORC1: The network consists of 206 nodes and 470 edges.

The overall network is represented in the form of an electronic circuit depicting the nodes (genes/proteins) and the edges (activation/inhibition/interaction).

Fig. 4. A network condensation through ExprEssence for A) Pancreatic Ductal Adenocarcinoma B) Hepatic Cirrhosis C) Cervical Cancer D) Glioblastoma E) Anaplastic Thyroid Cancer.

Upregulated proteins/genes are denoted by red color edges and downregulated proteins/genes by green color edges. Arrows denote activation, T-bars denote inhibition, and straight lines denote interaction. The top 10% start-ups (red) and the top 10% shutdowns (green) are highlighted.

Fig. 5. MCODE analysis for A) Pancreatic Ductal Adenocarcinoma B) Hepatic Cirrhosis C) Cervical Cancer D) Glioblastoma E) Anaplastic Thyroid Cancer.

Cluster members are shown in red. MCODE parameters- degree cutoff- 2, node score cut-off-0.2, k-core cut-off-2 and max depth-100. One cluster was obtained for Pancreatic ductal adenocarcinoma and Cervical cancer where as two clusters each were obtained for Hepatic cirrhosis, Glioblastoma, and Anaplastic thyroid cancer.

Fig. 6. Kaplan-Meier plots for hub-genes: A) MYC B) IDH1 C) MGMT D) CCND1.

The blue color indicates low expression while pink color shows high expression.