serum and via radiology. PD was tested using Axin2 mRNA levels in hair follicles (HFs). Immune markers were analysed in pre-and post-dose biopsies. Dose escalation and DLT incidence assessment were assisted by a Bayesian approach, with a DLT period of 28d. Results: As of April 2018, 5 pts were treated at 16 mg and 3 at 24 mg. 50% were female, median age (range) 55.5 yr (47-71). There was one DLT (grade 2 dysgeusia). Adverse events (>20%) were: dysgeusia (62%), fatigue (37%), weight loss (37%), back pain (37%), headache (37%), vomiting (25%), nausea (25%) and abdominal pain (25%). At the dose of 16 mg ETC-159 showed inter-patient PK variability, with a mean t 1 =2 of 15h (d1) and 37h (d15). Serum b-CTX reduction from pre-dose was seen in 6/8 pts. In 1 pt serum b-CTX increased to > 1000 pg/mL (with reduction of bone mineral density) and reduced after ETC-159 discontinuation; in 1 pt b-CTX was not assessed due to early discontinuation. 4 pts withdrew for progressive disease,1 pt for DLT, 1pt for consent withdrawal and 2 pts are ongoing. Decreased Axin2 mRNA was seen in HFs and a 2-fold increase of the ratio of tumour infiltrating CD8 þ /FOXP3 þ T-cells was seen in the tumour. Conclusions: ETC-159 with prophylactic denosumab is safe; there are no compression fractures and b-CTX decreases in most pts. ETC-159 has PD activity and increases immune infiltration. ETC-159 dosing is ongoing at 24 mg. Clinical trial identification: NCT02521844.

Background: Osteosarcoma (OS) is the most common primary solid malignant bone tumor, and its metastasis is a prominent cause of high mortality in patients.Methods: A risk signature was constructed based on re-annotating the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) data matrix, of the lncRNAs related to OS prognosis and immunity. From the OS transcription data, which is downloaded from the TARGET, the 1126 lncRNAs those harbour co-expressions with immunity genes were selected by Pearson correlation test and later divided into the training set (n=44) and validation set (n=41) with the caret package of R. With the training set we build the model related to Osteosarcoma prognosis by the univariate and multivariate Cox, and the Lasso regression analysis, and in combination with the clinical factors we conducted the multivariate Cox regression analysis to build the 1-year, 3-year and 5-year survival rate nomograms. Afterwards, we validated the ROC and the calibration curve of the subjects with the validation set and the whole dataset. Lastly, we performed functional enrichment analysis with the GSEA, GO and KEGG to figure out the biological functions of the prognosis genes.Results: The training set was performed in univariate and multivariate Cox regression analysis, identifying 25 lncRNAs correlated with prognosis. Eleven lncRNAs were selected by the least absolute shrinkage and selection operator (LASSO) regression for multivariate cox analysis and Kaplan-Meier (KM) survival analysis. Finally, lncRNAs (RP11-69E11.4, SNHG6, MIR210HG, RP11-750H9.5 and CTD-2341M24.1) risk signature was constructed, and the validation set and the whole dataset were used to evaluate the prediction stability and accuracy of the signature. The survival times of high- and low-risk groups were significantly different in the training set, validation set and the whole dataset. Further, function enrichment and gene set enrichment analysis revealed that the lncRNAs in the signature may affect the proliferation, migration, chemotaxis and combination of Osteosarcoma-related immune cells, and involve in every pathways of OS metabolism. Conclusion: The five lncRNAs survival risk signature could potentially predict the prognosis of OS patients, additionally, may provide novel insights for future clinical diagnosis and treatment of OS.