Abstract
A universal cancer biomarker candidate for diagnosis is supposed to distinguish, within a broad range of tumors, between healthy and diseased patients. Recently published studies have explored the universal usefulness of some biomarkers in human tumors. In this study, we present an integrative approach to search for potential common cancer biomarkers. Using the TFactS web-tool with a catalogue of experimentally established gene regulations, we could predict transcription factors (TFs) regulated in 305 different human cancer cell lines covering a large panel of tumor types. We also identified chromosomal regions having significant copy number variation (CNV) in these cell lines. Within the scope of TFactS catalogue, 88 TFs whose activity status were explained by their gene expressions and CNVs were identified. Their minimal connected network (MCN) of protein-protein interactions forms a significant module within the human curated TF proteome. Functional analysis of the proteins included in this MCN revealed enrichment in cancer pathways as well as inflammation. The ten most central proteins in MCN are TFs that trans-regulate 157 known genes encoding secreted and transmembrane proteins. In publicly available collections of gene expression data from 8,525 patient tissues, 86 genes were differentially regulated in cancer compared to inflammatory diseases and controls. From TCGA cancer gene expression data sets, 50 genes were significantly associated to patient survival in at least one tumor type. Enrichment analysis shows that these genes mechanistically interact in common cancer pathways. Among these cancer biomarker candidates, TFRC, MET and VEGFA are commonly amplified genes in tumors and their encoded proteins stained positive in more than 80% of malignancies from public databases. They are linked to angiogenesis and hypoxia, which are common in cancer. They could be interesting for further investigations in cancer diagnostic strategies.
Highlights
Identification of transcription factors (TFs) Regulated in Cancer Cell Lines Gene expression and SNP data were available for 305 cell lines, from which results were further analyzed
We assumed that important TFs would be those for which gene expression and copy number variation (CNV) could explain their activity status [31,32]
We hypothesized that cancer-associated TFs could interact together in a modular manner, such that cancer-triggering events end up perturbing the function of this module
Summary
On the basis of literature reviewing or by using high-throughput techniques some authors identified potential biomarkers common to several cancers and tried to develop strategies to identify them from patient biofluids either directly or indirectly. Among these markers, telomerase has been reported as being highly expressed in neoplasms [2]. Some authors have pointed to cancer-specific DNA methylation patterns as a marker for malignant diseases [8] They can be detected on cell-free circulating DNA in the blood [9]. Auto-antibodies against leukocyte antigen F (HLA-F) were detected in patients with various cancer types compared to healthy individuals [10]
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