Osteosarcoma has been a common primary bone malignant tumor in children and adolescents, although the incidence is relatively low comparing to other human tumors, the degree of malignancy is threateningly high[38]. To make it worse, no notable improvement has been received for patients survival over the past 30 years, attributing partly to the clinical fact that neither of the emerging gene-targeting therapy nor immunotherapy which have been showing inspiring clinical effects in many other tumors receives encouraging response in osteosarcoma[39]. It is of clinical realistic value to keep exploring the genetic information of osteosarcoma thus screening potential responsible genes during cancer development and identifying promising gene indicators.
The emerging molecular pathological technologies in current modern precise medicine era have been bringing in oceans of high throughput disease sequencing data[40–42], and a considerable part of these data are openly accessed to the public, making it more convenient for worldwide researchers to analyze the genetic events in cancer development and explore potential disease-causing gene alterations. In the study, multiple public online datasets and bioinformatic analyzing tools as well as local hospital biobank patients samples were combine used to explore promising genetic events in osteosarcoma development.
Firstly, four GEO transcriptome profiles of osteosarcoma namely GSE12865, GSE42352, GSE16088 and GSE28424 were picked to analyze the abnormally expressed genes in cancer comparing to control samples, which result revealed a total of 24430 genes in 4 profiles including 13456 genes whose expression discrepancy was < 2 fold, 7984 genes with expression discrepancy 2 ~ 4 fold, 2175 genes with expression discrepancy 4 ~ 8 fold, and 815 genes whose expression discrepancy was > 8 fold in osteosarcoma versus control samples.
Next step GO/KEGG interpretation of the 4 groups of genes revealed a specific phenomenon that the more the genes’ expression discrepancy are, the more they tend to locate far away from cellular nuclear. To be more specific, the < 2 fold genes were shown to focus mainly in nuclear, and 2 ~ 4 fold as well as 4 ~ 8 fold genes were mostly located in cell cytoplasm, meanwhile the > 8 fold genes were prefer to locate on the cellular membrane or out in extracellular region. Similar phenomenon has been discovered in other cancers[43, 44] which makes reasonable sense considering the classic biology “central dogma” that most human functional proteins were synthesized in nuclear following DNA-RNA-protein direction, slight change in nuclear proteins which might play roles as transcription regulatory factors shall result in massive extracellular locating proteins’ expression difference[45, 46].
Considering the feasibility of further clinical validation using IHC experiment which has been one of the most commonly used pathology test, we paid high attention on the > 8 fold genes for next step analysis. A total of 815 > 8 fold genes were identified in 4 profiles, and 67 of these 815 genes were shared in at least two profiles indicating they are more credible to be high level differently expressed in osteosarcoma comparing to normal control samples. To further understand the genes’ relationship with each other, the PPI network of 67 high level AEGS was constructed followed by function module analysis. As a result, three top gene clusters involving multiple signaling pathways were identified based on the network, and of the three modules a 22 genes-containing cluster which were interpreted by GO/KEGG to be mostly extracellular matrix structural constituent regulation related genes drew our attention based on the commonsense that a characteristic feature of osteosarcoma is the formation of specialized osteoid matrix.
To further scale down the candidate genes and identify credible key genes during osteosarcoma development, survival analysis was then performed to evaluate the association between each of the 22 genes and osteosarcoma patients survival, and the result revealed three genes: STC2, FGF2 and PRKCSH, they were all supported to be associated with both patients overall and recurrence free survival. Given the GeneCards online interpretation of the three genes, we finally picked STC2 for further analysis for its reported function in the regulation of cellular calcium metabolism and bone microenvironment development.
STC2, which is short for stanniocalcin2, locates in 5q35.2 and encodes a hydrophilic protein composed of 302 amino acids including 35 positively charged amino acid residues (Arg + Lys) and 36 negatively charged amino acid residues (ASP + Glu), weighting 33.2KD and being predicted to be stable in human cells with estimated half-time as 30 hours in all mammals. Meanwhile, cNLS-mapper and TMHMM online database analyzed that there’s no nuclear localization region nor transmembrane domain existing in STC2 protein structure, which is consistent with Human Protein Atlas and GeneCards prediction result that STC2 mainly locates in cellular endoplasmic reticulum and extracellular regions.
STC2 gene was selected base on previous GEO data exploration combined with further survival analysis which results supported that STC2 was one of the genes that were high level differently expressed in osteosarcoma comparing to normal control samples and related with patients survival. To uniquely validate the gene’s expression change and to preliminary explore the gene’s regulation on osteosarcoma development, online databases analysis (Oncomine data) and IHC experiment conducted on 43 local hospital patients samples were performed.
The IHC experiment not only validated the gain of expression of STC2 in osteosarcoma (95.3%) comparing to adjacent control samples (< 5%), but also shown an interesting fact that a big portion of samples were nuclear staining (92.7%) which is a different stain pattern than the previous location prediction result. After ruling out the possibility of IHC technical elements based on the same experiment which showed that STC2 stains as expected in perinuclear endoplasmic reticulum in breast cancer samples, the changed cellular location in osteosarcoma indicated that STC2 participate in osteosarcoma development via specific mechanisms for example interacting with nuclear locating transcription factors or regulators which is certainly an inspiring direction for further research. Besides the IHC experiment, Oncomine online analysis also supported that although STC2 expression was broad spectrum up regulated in multiple sarcomas, the expression was higher in osteosarcoma than other tumors.
Inspired by above especially IHC experiment results, to preliminary explore the potential mechanism of STC2 regulation on osteosarcoma development, the PPI network of STC2 centered genes was constructed to analyze the probable signaling pathways these genes enriched in. And the result preliminary revealed that the biological processes STC2 gene participated in were mainly focused on cellular response to hypoxia, cellular calcium and phosphate metabolism regulation, response to hormone related biological processes. Meanwhile, the signaling pathways STC2 gene involved includes HIF-1 signaling pathway, growth hormone synthesis, secretion and action related signaling pathway, as well as cell cycle modulation related pathways.
Although previous study also reported the potential regulation of STC2 on osteosarcoma survival[47, 48], comprehensive and deeper analysis are still needed to confirm the regulatory role of STC2 in osteosarcoma development and the current result is not yet enough to classify the gene as an useful clinical drug target. We sincerely hope above results shall provide inspiring insight into better understanding of the disease and provoke worldwide researchers’ interest to further and deeper explore the bone malignancy and benefit the clinical treatment in near future.