Analysis and Prediction of Pathways in HeLa Cells by Integrating Biological Levels of Organization with Systems-Biology Approaches

Abstract

It has recently begun to be considered that cancer is a systemic disease and that it must be studied at every level of complexity using many of the currently available approaches, including high-throughput technologies and bioinformatics. To achieve such understanding in cervical cancer, we collected information on gene, protein and phosphoprotein expression of the HeLa cell line and performed a comprehensive analysis of the different signaling pathways, transcription networks and metabolic events in which they participate. A total expression analysis by RNA-Seq of the HeLa cell line showed that 19,974 genes were transcribed. Of these, 3,360 were over-expressed, and 2,129 under-expressed when compared to the NHEK cell line. A protein-protein interaction network was derived from the over-expressed genes and used to identify central elements and, together with the analysis of over-represented transcription factor motifs, to predict active signaling and regulatory pathways. This was further validated by Metal-Oxide Affinity Chromatography (MOAC) and Tandem Mass Spectrometry (MS/MS) assays which retrieved phosphorylated proteins. The 14-3-3 family members emerge as important regulators in carcinogenesis and as possible clinical targets. We observed that the different over- and under-regulated pathways in cervical cancer could be interrelated through elements that participate in crosstalks, therefore belong to what we term “meta-pathways”. Additionally, we highlighted the relations of each one of the differentially represented pathways to one or more of the ten hallmarks of cancer. These features could be maintained in many other types of cancer, regardless of mutations or genomic rearrangements, and favor their robustness, adaptations and the evasion of tissue control. Probably, this could explain why cancer cells are not eliminated by selective pressure and why therapy trials directed against molecular targets are not as effective as expected.

Systems-level effects of ectopic galectin-7 reconstitution in cervical cancer and its microenvironment

“…Despite the gene composition, there is a powerful convergence in the functional modules towards the hallmarks of cancer, as suggested by our previous work [48]. A factor to be discussed is if these functional modules are a response to the imminent cell destruction, a desperate response to survive, or a combination of both.…”

Norepinephrine triggers an immediate-early regulatory network response in primary human white adipocytes

“…We could identify genes with several functions: those codifying for signaling transduction proteins (MAPK14, SOS1, ABL1), structural proteins (ACTB), cell cycle (CDK1, BCL2), metabolic signaling proteins (PIK3CA, AKT, mTOR), post-translational modifiers (UBE2D1, YWAHZ), and specific TFs (NCOR2, RELA, SMAD3, FOXO1, JUN, FOS, YAP1). Nodes with high betweenness have been demonstrated to play a central role in biological networks [ 75 – 77 ], and are frequently recognized as pleiotropic or essential genes, and their differential expression can predict information flow [ 78 ].…”

IPA Analysis of Cervicovaginal Fluid from Precancerous Women Points to the Presence of Biomarkers for the Precancerous State of Cervical Carcinoma

“…For this, we used the key word combination “XXX_HUMAN” (XXX = name of the protein, according to UniProt nomenclature) and “cervical cancer” as to find out whether relations between these proteins and cervical cancer have been described in literature. In addition, several high-throughput differential proteomics studies on cervical cancer [ 26 , 27 , 28 , 29 , 30 , 31 ] were screened for differential abundance of these proteins. Results showed that a markedly higher number of unique CVF proteins from precancerous women were described to be involved in cervical cancer: 19 (precancerous) versus 8 (healthy).…”

“…Recently, Higareda-Almarez et al . [ 26 , 27 ] compared the intracellular proteomes of six cervical cancer cell lines with the non-tumorigenic cell line HaCat and identified a consensus set of 66 unique or overexpressed cervical cancer proteins, which they called the “central core of cervical cancer”. As expected, many of these proteins had functions related to cancer hallmark processes such as cell migration/metastasis, evasion of apoptosis and central metabolism.…”