Molecular studies carried out at different levels of the flow of genetic information, allow precise characterization of what is really happening in normal cells or pathologically changed. Knowledge and understanding of the mechanisms responsible for the induction and progression of malignant transformation becomes more and more likely, what in the future may result in a modification of diagnostic algorithms and personalization of molecularly targeted therapy. Integrated analysis is made possible by the large-scale research platforms adapted to evaluate the integrity of the genome (whole-genome microarrays), analysis of transcriptome changes (expression microarrays), the analysis of the mechanisms responsible for transcription regulation (epigenetic control), metabolomics (phenotypic microarrays), the analysis of proteome (protein microarray) or kinomics (the state of proteins’ phosphorylation).

The TGFβ superfamily includes a large group of structurally related regulatory proteins with over 60 members, including at least 29-42 representatives encoded by the human genome (1). Until recently, the family TGFβ was divided into two basic subfamilies: TGF/Activins and BMP/GDF (bone morphogenetic protein/growth and differentiation factor) (2). Currently it is divided into 4 main groups: 1) TGFβ, 2) activins and inhibins, 3) bone morphogenetic proteins (BMPs) including at least 11 growth and differentiation factors – GDFs, and 4) MIF (also known as anti-Müllerian hormone – AMH) or MIS (Müllerian inhibitory substance) (3). TGFβ group comprise of five molecular isoforms not related to TGFα and each of them is encoded by separate gene. Three isoforms have been identified in mammals: TGFβ1, TGFβ2, TGFβ3. They are pleiotropic cytokines involved in cell cycle regulation (4), differentiation (5), apoptosis (6), cel migration (7) and in the formation and degradation of extracellular matrix components (8) including type I collagen (9). These factors are suppressors of proliferation of vascular endothelial cells and hematopoietic cells (10), significantly affecting the regulation of the immune response (4). In advanced stages of cancer of TGFβ acts as a promoter of metastasis by: modulating the microenvironment of the tumor cells and extracellular matrix synthesis, induction of chemokines secretion, silencing immunological response and participation in epithelial-mesenchymal transition (EMT) (11). Signaling pathways in tumors induced by TGFβ ligands may lead to inhibition of carcinogenesis or progression of cancer, depending on cancer staging (12). In the early stages of malignant transformation TGFβ activates signaling cascades which stimulate the expression of genes involved in inhibition of proliferation, cell differentiation stimulation, apoptosis or autophagy activation, suppression of angiogenesis and inflammatory response (13). In the advanced stages of the disease TGFβ acts as a promoter of metastasis through participation in epithelial-mesenchymal transition, remodeling of extracellular matrix and the microenvironment of tumor cells, inducing the synthesis of chemokines and immune response silencing (14).

TGFβ acts through two types of transmembrane serine-threonine kinase receptors: TβRI (TGFβR1) and TβRII (TGFβR2). In mammalian cells are present five kinds of receptor type II, seven kinds of type I and three kinds of type III receptor, which are involved in signal transduction activated by transforming growth factor as accessory/auxiliary receptors. These proteins have no functional intracellular domain, and therefore are not direct signal transmitters. Their involvement in the regulation of signaling pathways activity triggered by TGFβ involves presenting of cytokines to TGFβR1 and TGFβR2 receptors or limiting of their interaction with receptors. This type of receptors is specific only for TGFβ receptors group and is particularly important for TGFβ2 isoform, which has very low affinity for TGFβR2 and requires the presence of an auxiliary receptor TGFβR3 to facilitate formation of complexes with TGFβR2 (15). TGFβ type I receptors, known as ALK (Activin-like kinase) consist of the extracellular binding domain, transmembrane domain and a 30 amino acid regulatory region, rich in repeating glycine and serine residues (GS region) located above the catalytic domain of serine-threonine kinase (16). Type II receptors (TGFβR2), like TGFβR1, consist of the N-terminal extracellular ligand binding domain with characteristic cysteine CXCX4C pattern, transmembrane region and a C-terminal domain with serine-threonine kinase activity (3). Five receptors of TGFβ type II have been described: BMP receptor (BMP RII), activin type II receptor (Act RII), activin receptor β – Act RIIβ and Müllerian inhibitory substance type II receptor (MIS RII) (17). After binding with a ligand type II receptors phosphorylate type I receptors, resulting in activation of SMAD family transcription factors – involved in the canonical TGFβ signaling pathway (16).

TGFβ and its antagonists have enormous potential in the treatment of diseases that are now resistant to conventional therapy. Analysis of gene expression associated with TGFβ activity and the design of additional analogs and antagonists of TGFβ is an object of many studies aimed at developing new molecularly targeted treatment strategies (18).

The aim of this study is to compare the concentration profile of 1050 mRNA associated with Transforming Growth Factor beta (TGFβ) signaling pathways in cancer biopsy specimens of basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and keratoacanthoma (KA) in comparison to normal skin and selecting mRNA significantly differentiating analyzed transcriptomes.

The study included a group of 39 patients diagnosed and treated in the Dermatology Clinics and Department of Medical University of Silesia in Katowice. The tumours located on the skin of the face and head were pathomorphologically and clinically examined. Based on these results 19 samples were enrolled to transcriptome analysis: 6 cases of kerathoacanthoma (KA), 3 cases of squamous cell carcinoma (SCC), 7 of basal cell carcinoma (BCC) and 4 margins of healthy tissues. After surgical excision, tissue samples were immediately preserved in the RNA stabilisation reagent RNAlater (Qiagen GmbH, Hilden, Germany). All of the patients were informed about the research and signed an informed consent form. The study was approved by the Bioethical Commission of the Medical University of Silesia.

Total cellular RNA was isolated from tissue samples with the use of TRIZOL® reagent (Invitrogen Life Technologies, Kalifornia, USA), according to the manufacturer’s protocol. Extracts of total RNA were purified with the use of RNeasy Mini Kit (Qiagen Gmbh, Hilden, Germany) and treated with DNAase I (Fermentas International Inc., Ontario, Kanada) according to the manufacturer’s protocol. The RNA concentration was determined with the use of Gene Quant II spectrophotometer (Pharmacia LKB Biochrom Ltd., Cambridge, UK). The quality of RNA was estimated electrophoretically (1% agarose gel stained with ethidium bromide).

10 μg of purified RNA was reverse transcribed with the use of SuperScript Choice System (Invitrogen Life Technologies, California, USA). dsDNA was purified using Phase Lock Gel Light (Eppendorf, Germany). Synthesis of biotynylated cRNA was performed with the use of BioArray HighYield RNA Transcript Labeling Kit (Enzo Life Science, New York, USA). Biotynylated cRNA was purified using RNeasy Mini Kit (Qiagen Gmbh, Hilden, Germany). Fragmentation of 16 μg cRNA was performed with the use of Sample Cleanup Module (Qiagen Gmbh, Hilden, Germany). Hybridization with the oligonucleotide microarray HG U133A (Affymetrix, California, USA) was performed according to Affymetrix Gene Expression Analysis Technical Manual (Affymetrix, California, USA). Fluorescence intensity was measured with the use of Agilent GeneArray Scanner G2500A (Agilent Technologies, California, USA).

For finding significant genes between KA, SCC, BCC and control samples comparative analysis was performed with the use of GeneSpring 12.6.1 platform (Agilent Technologies, Inc., Santa Clara, CA, USA) and PL-Grid Infrastructure. The differences were analysed using the Oneway ANOVA test with Benjamini-Hochberg Multiple Testing Correction and TukeyHSD Post Hoc test. Genes were considered as potentially differentiating when FC ≥ 1.1 (fold change) and the significance level was set at p < 0.05.

mRNA concentration profiles of genes involved in TGFβ signalling pathways in KA, SCC, BCC and healthy skin margins were appointed with the use of oligonucleotide microarrays HG-U133A (Affymetrix). Comparative analysis of 10 ID mRNA for TGFβ and its receptors with the use of Oneway ANOVA test with Benjamini-Hochberg Multiple Testing Correction showed statistically significant differences of TGFB1 (TGFβ1) and TGFBR3 mRNA level (p < 0.05). TGFB1 was upregulated in SCC, comparing to controls. TGFBR3 mRNA level was down-regulated both in SCC and KA in comparison to healthy skin margins.