CASE DESCRIPTION: A 25-year-old man had been diagnosed with severe oncogenic osteomalacia that gradually crippled him over 6 years. 68Ga-DOTA-TATE positron emission tomography/computed tomography scan localized the culprit tumor to his left sole, which on resection revealed a deep fibrous histiocytoma displaying a proliferation of spindle cells with storiform pattern associated with multinucleated giant cells resembling osteoclasts. Circulating FGF-23, which was elevated more than 2-fold, declined to undetectable levels 24 h after surgery. Microarray analysis revealed increased tumor gene expression of the phosphatonins FGF-23, matrix extracellular phosphoglycoprotein (MEPE) and secreted frizzled-related protein subtype 4, with elevated levels of all 3 proteins confirmed through immunoblot analysis. Differential expression of genes involved in bone formation and bone mineralization were further identified. The patient made an astonishing recovery from being wheelchair bound to fully self-ambulant 2 months postoperatively.
CONCLUSION: This report describes oncogenic osteomalacia due to a deep fibrous histiocytoma, which coincidentally has been found to induce profound muscle weakness via the overexpression of 3 phosphatonins, which resolved fully upon radical resection of the tumor. Additionally, genes involved in bone formation and bone remodeling contribute to the molecular signature of oncogenic osteomalacia.
METHODS:: A literature search was done for articles published between 2002 and 2017 on Medline electronic databases. Of 249 titles identified, 38 fulfilled the inclusion criteria, with 14 articles related to quantifiable imaging parameters (heterogeneity, vascularity, diffusion, cell density, infiltrations, perfusion, and metabolite changes) and 24 articles relevant to molecular biomarkers linked to imaging.
RESULTS:: Genes found to correlate with various imaging phenotypes were EGFR, MGMT, IDH1, VEGF, PDGF, TP53, and Ki-67. EGFR is the most studied gene related to imaging characteristics in the studies reviewed (41.7%), followed by MGMT (20.8%) and IDH1 (16.7%). A summary of the relationship amongst glioma morphology, gene expressions, imaging characteristics, prognosis and therapeutic response are presented.
CONCLUSION:: The use of radiogenomics can provide insights to understanding tumour biology and the underlying molecular pathways. Certain MRI characteristics that show strong correlations with EGFR, MGMT and IDH1 could be used as imaging biomarkers. Knowing the pathways involved in tumour progression and their associated imaging patterns may assist in diagnosis, prognosis and treatment management, while facilitating personalised medicine.
ADVANCES IN KNOWLEDGE:: Radiogenomics can offer clinicians better insight into diagnosis, prognosis, and prediction of therapeutic responses of glioma.
MATERIALS AND METHODS: A total of 20 genes were selected from the list of up-regulated genes for the validation assay. The qPCR confirmed that 19 out of the 20 genes were up-regulated in endometrial cancer compared with normal endometrium. RNA interference (RNAi) was used to knockdown the expression of the upregulated genes in ECC-1 and HEC-1A endometrial cancer cell lines and its effect on proliferation, migration and invasion were examined.
RESULTS: Knockdown of MIF, SOD2, HIF1A and SLC7A5 by RNAi significantly decreased the proliferation of ECC-1 cells (p < 0.05). Our results also showed that the knockdown of MIF, SOD2 and SLC7A5 by RNAi significantly decreased the proliferation and migration abilities of HEC-1A cells (p < 0.05). Moreover, the knockdown of SLC38A1 and HIF1A by RNAi resulted in a significant decrease in the proliferation of HEC1A cells (p < 0.05).
CONCLUSION: We have identified the biological roles of SLC38A1, MIF, SOD2, HIF1A and SLC7A5 in endometrial cancer, which opens up the possibility of using the RNAi silencing approach to design therapeutic strategies for treatment of endometrial cancer.
METHODS: mRNA was extracted from 44 fibroadenomas and 36 giant fibroadenomas, and transcriptomic profiling was performed to identify up- and down-regulated genes in the giant fibroadenomas as compared to the fibroadenomas.
RESULTS: A total of 40 genes were significantly up-regulated and 18 genes were significantly down-regulated in the giant fibroadenomas as compared to the fibroadenomas of the breast. The top 5 up-regulated genes were FN1, IL3, CDC6, FGF8 and BMP8A. The top 5 down-regulated genes were TNR, CDKN2A, COL5A1, THBS4 and BMPR1B. The differentially expressed genes (DEGs) were found to be associated with 5 major canonical pathways involved in cell growth (PI3K-AKT, cell cycle regulation, WNT, and RAS signalling) and immune response (JAK-STAT signalling). Further analyses using 3 supervised learning algorithms identified an 8-gene signature (FN1, CDC6, IL23A, CCNA1, MCM4, FLT1, FGF22 and COL5A1) that could distinguish giant fibroadenomas from fibroadenomas with high predictive accuracy.
CONCLUSION: Our findings demonstrated that the giant fibroadenomas are biologically distinct to fibroadenomas of the breast with overexpression of genes involved in the regulation of cell growth and immune response.