Background: This study identifies the overall survival status of lung cancer patients with bone metastasis and metastasis patterns. Poor prognostic factors were identified to develop a scoring system for estimating survival period after bone metastasis. Methods: A retrospective cohort analysis was performed at Chiang Mai University for the period January 1, 2006 and December 31, 2013. Time-to-event analysis was performed to estimate survival rate. The primary end point was death related to lung cancer. Univariate and multivariate analysis of the prognostic variables was done using the Cox's regression model. The score was derived from the corresponding estimated regression coefficients of significantly poor prognostic factors. Results: A total of 505 lung cancer with bone metastasis patients were analyzed. Four hundred two cases (79.6%) were concurrent diagnosis and 103 (20.4%) were subsequent diagnosis. The median survival time of lung cancer after bone metastasis 148 days. Male gender and ECOG 3-4 were significant poor prognostic factors for lung cancer after bone metastasis, with hazard ratios of 1.42 (95% CI 1.17-1.73), and 1.30 (95% CI 1.06-1.60), respectively. Prognosis score was determined using the binary term present/not-present for those factors. The curve from prognostic score summations of 2, 1 and 0 presented a good discrimination of survival expectancy, showing an expected median survival time of approximately 109, 146, and 225 days, respectively. Conclusions: Prognostic score is a clinically simple and easy method for estimating life expectancy and for guiding interventions in bone metastasis of lung cancer.

Purpose: Cell-free DNA (cfDNA) analysis is a powerful tool for noninvasively predicting patient outcomes. We analyzed the size distribution of cfDNA and assessed its prognostic and diagnostic values in an osteosarcoma cohort. Experimental Design: The fragment size distribution and level of cfDNA were analyzed in 15 healthy donors and 50 patients with osteosarcoma using automated capillary electrophoresis. The prognostic performance of cfDNA size analysis was assessed using univariate and multivariable analyses. By performing whole-genome sequencing of matched cfDNA and osteosarcoma tissue samples, we investigated the correlation between the size and mutation profiles of cfDNA and the mutation concordance between cfDNA and paired tissue tumors. Results: The size of cfDNA fragments in patients with osteosarcoma was significantly shorter than in healthy donors, with the integrative analysis of size distribution and level of cfDNA achieving a high specificity and sensitivity of 100%. The short cfDNA fragment (150-bp cut-off) was an independent prognostic predictor in this osteosarcoma cohort [HR, 9.03; 95% confidence interval (CI), 1.13–72.20; P = 0.038]. Shortened cfDNA fragments were found to be a major source of mutations. Enrichment of cfDNA fragments with less than or equal to 150 bp by in silico size selection remarkedly improved the detection of copy-number variation signals up to 2.3-fold when compared with total cfDNA, with a higher concordance rate with matched osteosarcoma tissue. Conclusions: This finding demonstrated the potential of cfDNA size profiling in the stratification of poor prognostic patients with osteosarcoma. The short fragments of cfDNA are a promising source for boosting the detection of significant mutations in osteosarcoma. See related commentary by Weiser et al., p. 2017

A liquid biopsy is currently an interesting tool for measuring tumor material with the advantage of being non-invasive. The overexpression of vimentin and ezrin genes was associated with epithelial-mesenchymal transition (EMT), a key process in metastasis and progression in osteosarcoma (OS). In this study, we identified other OS-specific genes by calculating differential gene expression using the Gene Expression Omnibus (GEO) database, confirmed by using quantitative reverse transcription-PCR (qRT-PCR) to detect OS-specific genes, including VIM and ezrin in the buffy coat, which were obtained from the whole blood of OS patients and healthy donors. Furthermore, the diagnostic model for OS detection was generated by utilizing binary logistic regression with a multivariable fractional polynomial (MFP) algorithm. The model incorporating VIM, ezrin, and COL5A2 genes exhibited outstanding discriminative ability, as determined by the receiver operating characteristic curve (AUC = 0.9805, 95% CI 0.9603, 1.000). At the probability cut-off value of 0.3366, the sensitivity and the specificity of the model for detecting OS were 98.63% (95% CI 90.5, 99.7) and 94.94% (95% CI 87.5, 98.6), respectively. Bioinformatic analysis and qRT-PCR, in our study, identified three candidate genes that are potential diagnostic and prognostic genes for OS.

This study aimed to assess survival outcomes, prognostic factors, and adverse events following chemotherapy treatment for osteosarcoma and Ewing’s sarcoma. This retrospective observational study was conducted to collect the data of the patients with osteosarcoma or Ewing’s sarcoma who received chemotherapy treatment between 2008 and 2019. The flexible parametric survival model was performed to explore the adjusted survival probability and the prognostic factors. A total of 102 patients (79 with osteosarcoma and 23 with Ewing’s sarcoma) were included. The estimated 5-year disease-free survival (DFS) and 5-year overall survival (OS) probabilities in patients with resectable disease were 60.9% and 63.3% for osteosarcoma, and 54.4% and 88.3% for Ewing’s sarcoma, respectively, whereas the 5-year DFS and 5-year OS for those with unresectable/metastatic disease remained below 25%. Two prognostic factors for osteosarcoma included a response to neoadjuvant chemotherapy and female gender. Ewing’s sarcoma patients aged 25 years and older were significantly associated with poorer survival outcomes. Of 181 chemotherapy treatment cycles, common self-reported adverse symptoms included tumor pain (n = 32, 17.7%), fever (n = 21, 11.6%), and fatigue (n = 16, 8.8%), while common grade III adverse events included febrile neutropenia (n = 13, 7.3%) and neutropenia (n = 9, 5.1%). There was no chemotherapy-related mortality (grade V) or anaphylaxis events.

Diverse aberrancy in genetic background, protein profiling, and biological pathways have emerged as important factors hindering discovery of effective treatment of osteosarcoma. In a previous study, we used a proteomic approach to identify some osteosarcoma-related proteins by analysis of protein profiling in individual patients through primary cell culture. Endoplasmic reticulum protein 29 (ERp29) emerged as a protein of interest for further study since accumulating evidence suggests it has broad functions in tumorigenesis of different types of cancer. Importantly, until now no report on examination of the expression patterns of ERp29 in osteosarcoma has been published. In this study, an expression of ERp29 was examined in patient-derived osteosarcoma cells (7 cases) and normal bone graft-derived osteoblasts (7 cases) using western blotting. Expression profile of ERp29 in 94 osteosarcoma cases was investigated using immunohistochemically stained on formalin-fixed paraffin-embedded biopsied tissue. An association with clinicopathologic parameters and the patient survival was evaluated. The doubling time of five osteosarcoma cells lines expressing different levels of ERp29 was determined by a cell number along the exponential phase of the growth curve. The results substantiate the outcome from the proteomic study in which ERp29 expression was significantly higher in primary osteosarcoma cells compared to osteoblastic cells. Immunohistochemical analysis found that expression of ERp29 was low in 79% of the cases (immunoreactive score (IRS) <6). A significant correlation was observed between expression of ERp29 and patient survival. Lower expression of ERp29 (IRS<6) was statistically significantly associated with shorter overall survival of the patients (P = 0.041). In addition, we found that osteosarcoma cells with low ERp29 expression had a higher growth rate compared with high-ERp29-expressing cells. These findings suggest a tumor suppressive role of ERp29 in osteosarcoma. In addition, ERp29 might potentially be applied as a prognostic indicator in patients with osteosarcoma.