Prognostic Factor In Osteosarcoma Research Articles

Tumor necrosis drives prognosis in osteosarcoma: No difference in chemotherapy response and survival between chondroblastic and osteoblastic osteosarcoma

IntroductionThe percentage of tumor necrosis is a crucial prognostic factor in osteosarcoma. Many studies adopt a 90 % cutoff based on osteoblastic osteosarcoma, but these findings are generalized to all conventional subtypes, including chondroblastic osteosarcoma. We sought to answer these questions: (1) Is tumor necrosis ≥90 % associated with better overall survival (OS) and disease-free survival (DFS) in osteoblastic and chondroblastic osteosarcoma? (2) Does the osteosarcoma subtype impact tumor necrosis? (3) Does the osteosarcoma subtype in “good” responders (tumor necrosis ≥90 %) affect OS and DFS?. Materials and methodsWe conducted a retrospective study of 156 patients with osteoblastic and chondroblastic osteosarcoma treated at our institution. All patients received a standardized chemotherapy protocol and underwent surgery with the goal of achieving negative margins (R0 resection). Propensity-score matching was performed to adjust for potential confounders. Kaplan-Meier survival analysis and Cox proportional hazards modeling were performed. ResultsPatients with osteoblastic osteosarcoma and tumor necrosis ≥90 % had higher 5- and 10-year OS and DFS compared to those with necrosis <90 %. In chondroblastic osteosarcoma, a trend towards higher OS and DFS was seen in patients with tumor necrosis ≥90 %; this, however, was not significant. Chondroblastic osteosarcoma was not a risk factor for either tumor necrosis <90 % (p = 0.89) or tumor necrosis <70 % (p = 0.57). Patients with osteoblastic or chondroblastic osteosarcoma that were deemed “good” responders (tumor necrosis ≥90 %) had similar OS and DFS at the 5- and 10-year marks. ConclusionConventional osteosarcoma subtype was not a risk factor for “poor” response. Survival outcomes (OS and DFS) were similar for osteoblastic and chondroblastic osteosarcoma with good response to chemotherapy.

Comprehensive analysis of the expression and prognosis for cyclin-dependent protein kinase family in osteosarcoma

Background and Objective Cyclin-dependent protein kinases (CDKs) have been suggested as prospective therapeutic targets because they control processes vital to the survival and growth of cancer cells. However, research on the varied CDK expression profiles and prognostic factors in osteosarcoma is still lacking. Methods The osteosarcoma microRNA (GSE65071) and gene expression profiles were retrieved from the Gene Expression Omnibus (GEO) database (GSE42352). A substantial variation in prognosis was discovered in CDKs using the TARGET database. Cytoscape was used to construct the miRNAs-CDKs network, and functional and pathway enrichment analyses were completed. It was looked at how immune checkpoint genes, m6A-related genes, and CDKs interact. Results In patients with osteosarcoma compared to normal samples, CDK1-5, CDK18, CDK16, and CDK17 gene expression levels were considerably greater, whereas CDK7-9, CDK11B, CDK16, and CDK20 gene expression levels were significantly lower. Patients with osteosarcoma who had low CDK3 and 18 gene levels or high CDK6, 9 gene levels were predicted to have a favorable prognosis and a long-life expectancy. Immune checkpoint genes, m6A-related gene expression, and CDKs expression all showed some connection. Finally, a network of crucial CDKs and miRNAs was constructed. Conclusion According to our research, CDK3, 6, 9, and 18 have been identified as possible therapeutic targets for osteosarcoma, and CDKs may have a role in controlling m6A mutations in tumor cells as well as immune checkpoint regulation.

Neoadjuvant chemotherapy-induced hemoglobin decline as a prognostic factor in osteosarcoma around the knee joint: a single-center retrospective analysis of 242 patients

PurposeAnemia is relatively common in cancer patients, and is associated with poor survival in patients with various malignancies. However, how anemia would affect prognosis and response to neoadjuvant chemotherapy (NAC) in osteosarcoma (OS) is still without substantial evidence.MethodsWe retrospectively analysed 242 patients with stage II OS around the knee joint in our institute. Changed hemoglobin (Hb) levels (before and after NAC) were recorded to assess the prognostic value in DFS (disease-free survival) and tumor response to NAC. Univariate and multivariate analyses were conducted to identify prognostic factors related with outcome in OS patients.ResultsThe mean Hb level significantly decreased after NAC (134.5 ± 15.3 g/L vs. 117.4 ± 16.3 g/L). The percentage of mild (21%), moderate (4.2%) and severe (0%) anemia patients markedly increased after NAC: 41%, 24% and 4.1% respectively. There was higher percentage of ≥ 5% Hb decline in patients with tumor necrosis rate < 90% (141 out of 161), compared with those with tumor necrosis rate ≥ 90% (59 out of 81). Further univariate and survival analysis demonstrated that Hb decline had a significant role in prediction survival in OS patients. Patients with ≥ 5% Hb decline after NAC had an inferior DFS compared with those with < 5% Hb decline.ConclusionIn osteosarcoma, patients with greater Hb decrease during neoadjuvant treatment were shown to have worse DFS and a poorer response to NAC than those without. Attempts to correct anemia and their effects on outcomes for osteosarcoma patients should be explored in future studies.

Development of a novel six DNA damage response-related prognostic signature in osteosarcoma.

DNA damage response (DDR) plays a vital role in the development of cancer. Nevertheless, in osteosarcoma, the potential of DDR-related genes (DDRGs) remains unclear. Thus, the current research is intended to investigate the mechanisms of DDRGs in the development of osteosarcoma and to explore potential DDR-related biomarkers in forecasting the prognosis of osteosarcoma patients. The osteosarcoma genomic data from TCGA, GEO and cBioPortal databases were utilized for screening and identification of differentially expressed DDRGs (DEDDRGs). Consensus clustering analysis was performed to identify different subtypes of osteosarcoma based on the expressions of DDRGs. Key DEDRRGs were identified by overlapping DEDRRGs between different subtypes and DEDRRGs between tumor and control samples. Univariate, as well as LASSO regressions, were further applied to obtain robust prognostic signatures. GSVA and ssGSEA analysis were implemented to explore the underlying mechanisms of prognostic DDRG signature in regulating osteosarcoma. In addition, the drug sensitivity of patients in low- and high-risk groups was evaluated using pRRophetic algorithm. A total of 43 key DEDRRGs were identified. Followed by univariate Cox along with LASSO regression analyses, CDK6, CSF1R, EGFR, ERBB4, GATA3 and SOCS1 were identified as prognostic signatures in osteosarcoma. Cox regressions revealed that the risk score was an independent prognostic factor in osteosarcoma. DDR may affect osteosarcoma via regulating immune microenvironment along with influencing cell proliferation, migration, adhesion and apoptosis. The chemotherapeutic response between patients in low- and high-risk groups was much different. The role of DDRGs in osteosarcoma and identified six DDR-linked biomarkers for forecasting the prognosis of osteosarcoma patients. Our outcomes enhanced the understanding of DDR-related molecular mechanisms involved in osteosarcoma and provided potential therapeutic targets for osteosarcoma patients.

The correlation between clinical outcomes and genomic analysis with high risk factors for the progression of osteosarcoma.

Osteosarcoma (OS) is a rare but aggressive malignancy. Despite previous reports, molecular characterization of this disease is not well understood, and little is known regarding OS in Chinese patients. Herein, we analyzed the genomic signatures of 73 Chinese OS cases. TP53, NCOR1, LRP1B, ATRX, RB1, and TFE3 were the most frequently mutated gene in our OS cohort. In addition, the genomic analysis of Western OS patients was performed. Notably, there were remarkable disparities in mutational landscape, base substitution pattern, and tumor mutational burden between the Chinese and Western OS cohorts. Specific molecular mechanisms, including DNA damage repair (DDR) gene mutations, copy number variation (CNV) presence, aneuploidy, and intratumoral heterogeneity, were associated with disease progression. Additionally, 30.1% of OS patients carried clinically actionable alterations, which were mainly enriched in PI3K, MAPK, DDR, and RTK signaling pathways. A specific molecular subtype incorporating DDR alterations and CNVs was significantly correlated with distant metastasis-free survival and event-free survival, and this correlation was observed in all subgroups with different characteristics. These findings comprehensively elucidated the genomic profile and revealed novel prognostic factors in OS, which would contribute to understanding this disease and promoting precision medicine of this population.

Significance of expression of CD109 in osteosarcoma and its involvement in tumor progression via BMP signaling.

Osteosarcoma, the most common primary malignant bone tumor, is defined by the formation of neoplastic osteoid and/or bone. This sarcoma is a highly heterogeneous disease with a wide range of patient outcomes. CD109 is a glycosylphosphatidylinositol-anchored glycoprotein that is highly expressed in various types of malignant tumors. We previously reported that CD109 is expressed in osteoblasts and osteoclasts in normal human tissues and plays a role in bone metabolism in vivo. While CD109 has been shown to promote various carcinomas through the downregulation of TGF-β signaling, the role and mechanism of CD109 in sarcomas remain largely unknown. In this study, we investigated the molecular function of CD109 in sarcomas using osteosarcoma cell lines and tissue. Semi-quantitative immunohistochemical analysis using human osteosarcoma tissue revealed a significantly worse prognosis in the CD109-high group compared with the CD109-low group. We found no association between CD109 expression and TGF-β signaling in osteosarcoma cells. However, enhancement of SMAD1/5/9 phosphorylation was observed in CD109 knockdown cells under bone morphogenetic protein-2 (BMP-2) stimulation. We also performed immunohistochemical analysis for phospho-SMAD1/5/9 using human osteosarcoma tissue and found a negative correlation between CD109 expression and SMAD1/5/9 phosphorylation. In vitro wound healing assay showed that osteosarcoma cell migration was significantly attenuated in CD109-knockdown cells compared with control cells in the presence of BMP. These results suggest that CD109 is a poor prognostic factor in osteosarcoma and affects tumor cell migration via BMP signaling.

Identification of an EMT-related gene-based prognostic signature in osteosarcoma.

The correlation between epithelial-mesenchymal transition (EMT) and osteosarcoma (OS) has been widely reported. Integration of the EMT-related genes to predict the prognosis is significant for investigating the mechanism of EMT in OS. Here, we aimed to construct a prognostic EMT-related gene signature for OS. Transcriptomic and survival data of OS patients were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO). We performed univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and stepwise multivariate Cox regression analysis to construct EMT-related gene signatures. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) were applied to evaluate its predictive performance. GSVA, ssGSEA, ESTIMATE, and scRNA-seq were performed to investigate the tumor microenvironment, and the correlation between IC50 of drugs and ERG score was investigated. Furthermore, Edu and transwell experiments were conducted to assess the malignancy of OS cells. We constructed a novel EMT-related gene signature (including CDK3, MYC, UHRF2, STC2, COL5A2, MMD, and EHMT2) for outcome prediction of OS. According to the signature, patients stratified into high- and low-ERG-score groups exhibited significantly different prognoses. ROC curves and Kaplan-Meier analysis revealed a promising performance of the signature with external validation. GSVA, ssGSEA, ESTIMATE algorithm, and scRNA-seq excavated EMT-related pathways and suggested the correlation between ERG score and immune activation. Notably, the pivotal gene CDK3 was upregulated in OS tissue and positively related to OS cell proliferation and migration. Our EMT-related gene signature might reference OS risk stratification and guide clinical strategies as an independent prognostic factor in OS.

A tumor microenvironment-based prognostic index for osteosarcoma

BackgroundThe tumor microenvironment (TME) has a central role in the oncogenesis of osteosarcomas. The composition of the TME is essential for the interaction between tumor and immune cells. The aim of this study was to establish a prognostic index (TMEindex) for osteosarcoma based on the TME, from which estimates about patient survival and individual response to immune checkpoint inhibitor (ICI) therapy can be deduced.MethodsBased on osteosarcoma samples from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, the ESTIMATE algorithm was used to estimate ImmuneScore and StromalScore. Combined differentially expressed gene analysis, weighted gene co-expression network analyses, the Least Absolute Shrinkage and Selection Operator regression and stepwise regression to construct the TMEindex. The prognostic role of TMEindex was validated in three independent datasets. The molecular and immune characteristics of TMEindex and the impact on immunotherapy were then comprehensively investigated. The expression of TMEindex genes in different cell types and its effects on osteosarcoma cells were explored by scRNA-Seq analysis and molecular biology experiments.ResultsFundamental is the expression of MYC, P4HA1, RAMP1 and TAC4. Patients with high TMEindex had worse overall survival, recurrence-free survival, and metastasis-free survival. TMEindex is an independent prognostic factor in osteosarcoma. TMEindex genes were mainly expressed in malignant cells. The knockdown of MYC and P4HA1 significantly inhibited the proliferation, invasion and migration of osteosarcoma cells. A high TME index is related to the MYC, mTOR, and DNA replication-related pathways. In contrast, a low TME index is related to immune-related signaling pathways such as the inflammatory response. The TMEindex was negatively correlated with ImmuneScore, StromalScore, immune cell infiltration, and various immune-related signature scores. Patients with a higher TMEindex had an immune-cold TME and higher invasiveness. Patients with a low TME index were more likely to respond to ICI therapy and achieve clinical benefit. In addition, the TME index correlated with response to 29 oncologic drugs.ConclusionsThe TMEindex is a promising biomarker to predict the prognosis of patients with osteosarcoma and their response to ICI therapy, and to distinguish the molecular and immune characteristics.

FKBP11 improves the malignant property of osteosarcoma cells and acts as a prognostic factor of osteosarcoma.

Osteosarcoma has become the most common bone malignancy in adolescents. Although the clinical treatment of osteosarcoma has advanced considerably in recent years, the 5-year survival rate has not improved significantly. Recently, many studies have shown that mRNA has unique advantages as a target for drug therapy. Therefore, this study aimed to identify a new prognostic factor and provide a new target for the treatment of osteosarcoma to improve the prognosis of patients. We selected prognostic genes that are closely associated with osteosarcoma clinical features by obtaining osteosarcoma patient information from the GTEx and TARGET databases, and then we developed a risk model. We detected the expression of FKBP11 in osteosarcoma by qRT-PCR, western blotting, and immunohistochemistry and performed CCK-8, Transwell, colony formation, and flow cytometry assays to reveal the regulatory role of FKBP11. We found that FKBP11 was highly expressed in osteosarcoma; silencing FKBP11 expression suppressed the invasion and migration of osteosarcoma cells, slowed cell proliferation, and promoted apoptosis. We also found that silencing the expression of FKBP11 led to inhibition of MEK/ERK phosphorylation. In conclusion, we validated that the prognostic factor FKBP11 is closely associated with osteosarcoma. Additionally, we identified a novel mechanism by which FKBP11 ameliorates the malignant properties of osteosarcoma cells through the MAPK pathway and serves as a prognostic factor in osteosarcoma. This study provides a new method for the treatment of osteosarcoma.

The bioinformatic approach identifies PARM1 as a new potential prognostic factor in osteosarcoma.

To explore the key factors affecting the prognosis of osteosarcoma patients. Based on the GEO dataset and differential expression analysis of normal and osteosarcoma tissues, the gene modules related to the prognosis of osteosarcoma patients were screened by WGCNA, and intersecting genes were taken with differential genes, and the risk prognosis model of osteosarcoma patients was constructed by LASSO regression analysis of intersecting genes, and the prognosis-related factors of osteosarcoma patients were obtained by survival analysis, followed by target for validation, and finally, the expression of prognostic factors and their effects on osteosarcoma cell migration were verified by cellular assays and lentiviral transfection experiments. The prognosis-related gene module of osteosarcoma patients were intersected with differential genes to obtain a total of 9 common genes. PARM1 was found to be a prognostic factor in osteosarcoma patients by LASSO regression analysis, followed by cellular assays to verify that PARM1 was lowly expressed in osteosarcoma cells and that overexpression of PARM1 in osteosarcoma cells inhibited cell migration. Pan-cancer analysis showed that PARM1 was lowly expressed in most cancers and that low expression of PARM1 predicted poor prognosis for patients. The data from this study suggest that PARM1 is closely associated with the prognosis of osteosarcoma patients, and PARM1 may serve as a novel potential prognostic target for osteosarcoma, providing a heartfelt direction for the prevention and treatment of osteosarcoma.

Clinical Targeted Next-Generation Panel Sequencing Reveals MYC Amplification Is a Poor Prognostic Factor in Osteosarcoma.

Osteosarcoma risk stratification, on the basis of the presence of metastatic disease at diagnosis and histologic response to chemotherapy, has remained unchanged for four decades, does not include genomic features, and has not facilitated treatment advances. We report on the genomic features of advanced osteosarcoma and provide evidence that genomic alterations can be used for risk stratification. In a primary analytic patient cohort, 113 tumor and 69 normal samples from 92 patients with high-grade osteosarcoma were sequenced with OncoPanel, a targeted next-generation sequencing assay. In this primary cohort, we assessed the genomic landscape of advanced disease and evaluated the correlation between recurrent genomic events and outcome. We assessed whether prognostic associations identified in the primary cohort were maintained in a validation cohort of 86 patients with localized osteosarcoma tested with MSK-IMPACT. In the primary cohort, 3-year overall survival (OS) was 65%. Metastatic disease, present in 33% of patients at diagnosis, was associated with poor OS (P = .04). The most frequently altered genes in the primary cohort were TP53, RB1, MYC, CCNE1, CCND3, CDKN2A/B, and ATRX. Mutational signature 3 was present in 28% of samples. MYC amplification was associated with a worse 3-year OS in both the primary cohort (P = .015) and the validation cohort (P = .012). The most frequently occurring genomic events in advanced osteosarcoma were similar to those described in prior reports. MYC amplification, detected with clinical targeted next-generation sequencing panel tests, is associated with poorer outcomes in two independent cohorts.

Construction and validation of a prognostic model for osteosarcoma patients based on autophagy-related genes

BackgroundOsteosarcoma is the most frequent primary bone malignancy with a poor prognosis because of pulmonary metastasis. Autophagy is strongly associated with tumor metastasis, and it is valuable to construct an autophagy-related gene risk model for predicting the prognosis of osteosarcoma.MethodsWe obtained ARGs from the Human Autophagy Database and RNA-sequencing data of osteosarcoma patients from the Gene Expression Omnibus (GEO) database. Subsequently, univariate and multivariate cox regression analyses were performed to construct a three-gene prognostic model and its accuracy was further confirmed in the Therapeutic Applications Research to Generate Effective Treatments (TARGET) database. Afterward, we detected the expression levels and effects on osteosarcoma cells metastasis of MYC and MBTPS2, which were involved in the model.ResultsIn both training and verification cohorts, patients with lower risk scores had longer OS, and the model was identified as an independent prognostic factor in osteosarcoma. Besides, the ROC curve demonstrated the reliability of the model. Furthermore, RT-qPCR, Western Blotting and IHC results indicated that MYC and MBTPS2 were differently expressed in osteosarcoma tissues and cell lines. MYC knockdown or MBTPS2 overexpression prevented the capacity of migration and invasion in osteosarcoma cell lines through inhibiting cellular autophagy.ConclusionThe risk model based on three ARGs had a strong ability to predict the prognosis of osteosarcoma patients. Our findings also suggested that MYC and MBTPS2 were two major factors regulating autophagy in osteosarcoma, and could serve as potential therapeutic targets for osteosarcoma.

Analysis of Clinical Manifestations and Prognostic Factors Affecting Osteosarcoma.

Objective This study is aimed at exploring the clinical manifestations and prognostic factors of osteosarcoma. Methods The clinical data of patients with osteosarcoma who were treated in our hospital from January 2018 to March 2020 were selected for retrospective analysis. The general information of the patients, including age, gender, tumor diameter, tumor location, tumor type, surgical method, and Enneking stage, distant disease metastasis, KPS score, and the number of postoperative adjuvant chemotherapy, were grouped by prognosis for statistical analysis. The clinical characteristics, morbidity and mortality, and prognostic factors of patients were statistically analyzed. Results Among the 83 patients in this group, there were 52 males and 31 females, 59 tumors > 10 cm in diameter and 24 tumors < 10 cm in diameter, 16 tumors in the upper limbs and 67 tumors in the lower limbs, 25 tumors in osteoblastoma, 16 tumors in chondroblastoma, 42 tumors in fibroblastoma, 62 tumors in stage II, and 21 tumors in stage III of Enneking stage, 10 tumors in distant metastasis, and 10 tumors in distant metastasis. The death rate of this group was 19.28% (16/83). Multifactor regression analysis confirmed that the Enneking stage III, distant metastasis, KPS score < 70, and the number of postoperative adjuvant chemotherapy < 6 were important factors influencing the death of osteosarcoma (P < 0.05). Conclusion Enneking stage III, distant metastasis, KPS score < 70, and the number of postoperative adjuvant chemotherapy < 6 are important influencing factors of osteosarcoma death. Clinical practice can take corresponding preventive and control measures according to the existence of these factors to ensure a good prognosis.

RNA adenosine modifications related to prognosis and immune infiltration in osteosarcoma

BackgroundRNA adenosine modifications, which are primarily mediated by “writer” enzymes (RMWs), play a key role in epigenetic regulation in various biological processes, including tumorigenesis. However, the expression and prognostic role of these genes in osteosarcoma (OS) remain unclear.MethodsUnivariate and multivariate Cox analyses were used to construct the RMW signature for OS using Target datasets. RMW expression in OS tissue was detected by qPCR analysis. Xcell and GSVA were used to determine the relationship between RMWs and immune infiltration. The DGIdb and CMap databases were used for drug prediction. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS.ResultsA 3-RMW (CSTF2, ADAR and WTAP) prognostic signature in OS was constructed using the Target dataset and verified using GEO datasets and 63 independent OS tissues via qPCR analysis. High-risk OS patients had poor overall survival, and the prognostic signature was an independent prognostic factor for OS. Functional studies showed that tumour-, metabolism-, cell cycle- and immune-related pathways were related to high risk. Next, we found that RMW-derived high-risk patients exhibited increased infiltration of M2 macrophages and cDCs. Furthermore, we predicted the potential drugs for OS using the DGIdb and CMap databases. In vivo and in vitro experiments showed that strophanthidin elicited antitumor activity against OS by repressing cell growth and inducing cell cycle arrest at the G1 phase.ConclusionThe 3-RWM-based prognostic signature established in this study is a novel gene signature associated with immune infiltration, and strophanthidin was identified as a candidate therapy for OS by repressing OS cell growth and the cell cycle.

Transcription factor c-Myb: novel prognostic factor in osteosarcoma

The transcription factor c-Myb is an oncoprotein promoting cell proliferation and survival when aberrantly activated/expressed, thus contributing to malignant transformation. Overexpression of c-Myb has been found in leukemias, breast, colon and adenoid cystic carcinoma. Recent studies revealed its expression also in osteosarcoma cell lines and suggested its functional importance during bone development. However, the relevance of c-Myb in control of osteosarcoma progression remains unknown. A retrospective clinical study was carried out to assess a relationship between c-Myb expression in archival osteosarcoma tissues and prognosis in a cohort of high-grade osteosarcoma patients. In addition, MYB was depleted in metastatic osteosarcoma cell lines SAOS-2 LM5 and 143B and their growth, chemosensitivity, migration and metastatic activity were determined. Immunohistochemical analysis revealed that high c-Myb expression was significantly associated with poor overall survival in the cohort and metastatic progression in young patients. Increased level of c-Myb was detected in metastatic osteosarcoma cell lines and its depletion suppressed their growth, colony-forming capacity, migration and chemoresistance in vitro in a cell line-dependent manner. MYB knock-out resulted in reduced metastatic activity of both SAOS-2 LM5 and 143B cell lines in immunodeficient mice. Transcriptomic analysis revealed the c-Myb-driven functional programs enriched for genes involved in the regulation of cell growth, stress response, cell adhesion and cell differentiation/morphogenesis. Wnt signaling pathway was identified as c-Myb target in osteosarcoma cells. Taken together, we identified c-Myb as a negative prognostic factor in osteosarcoma and showed its involvement in the regulation of osteosarcoma cell growth, chemosensitivity, migration and metastatic activity.

Overexpression of KIAA1199, a novel strong hyaluronidase, is a poor prognostic factor in patients with osteosarcoma

BackgroundHyaluronan (HA) has been shown to play important roles in the growth, invasion, and metastasis of malignant tumors. KIAA1199, which has potent HA-degrading activity, has been reported to be expressed in various malignancies and associated with patient prognosis. However, there are no reports on the expression of KIAA1199 in osteosarcoma. The aim of this study was to investigate the impact of KIAA1199 and HA expression in osteosarcoma tissues on the prognosis and other clinical characteristics of osteosarcoma patients.MethodsFrom 2003 to 2013, we included 49 patients with osteosarcoma at our institution, whose FFPE (formalin fixed paraffin embedded) tissue was available at the time of biopsy. The expressions of KIAA1199 and HA in each sample were assessed by immunohistochemistry using the primary antibody for KIAA1199 and HA-binding protein (HABP), respectively. For evaluation of the positivity of KIAA1199 staining, we divided the samples into two groups: High group with more than 75% positive staining and Low group with less than 75% positive staining. In the HABP staining, those with more than and less than 60% were assigned to a High group, and Low group respectively. Various clinical features were correlated with staining positivity. Prognostic factors including positivity of the staining were analyzed. Levels of mRNA expression for enzymes related to HA metabolism were assessed in two osteosarcoma cell lines using real-time RT-PCR.ResultsIn KIAA1199 staining, high positivity was significantly correlated with occurrence of distant metastases (P = 0.002). The necrosis rate after preoperative chemotherapy was significantly lower in the High positivity group (59%), compared to that in the Low group (84.8%) (P = 0.003). HABP positivity was not correlated with any demographic variables, although the Low positivity group had a significantly better overall survival than the High group with KIAA1199 and HABP staining (P = 0.026 and P = 0.029, respectively). In multivariable analysis, KIAA1199 (P = 0.036) and HABP staining (P = 0.002), location (P = 0.001), and distant metastasis at initial diagnosis (P < 0.001) were identified as significant prognostic factors. KIAA1199 and hyaluronan synthase mRNA were expressed at different levels in the two osteosarcoma cell lines.ConclusionsOur results showed that high expression of KIAA1199 and HA are both poor prognostic factors in osteosarcoma. KIAA1199 may be a useful marker for distant metastasis and chemoresistance.

Trophinin Is an Important Biomarker and Prognostic Factor in Osteosarcoma: Data Mining from Oncomine and the Cancer Genome Atlas Databases.

Osteosarcoma (OS) is a type of bone malignancy with a high rate of treatment failure. To date, few evident biomarkers for the prognostic significance of OS have been established. Oncomine was used to integrate RNA and DNA-seq data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and the published literature. The correlation of the gene Trophinin (TRO) and different types of cancers was generated using the Cancer Cell Line Encyclopedia (CCLE) online tool. Prognostic values of featured Melanoma Antigen Gene (MAGE) members were further assessed by establishing the overall survival using the Kaplan-Meier plotter. Moreover, the online tool, Database for Annotation, Visualization and Integrated Discovery version (DAVID), was used to understand the biological meaning list of the genes. MAGEB10, MAGED2, TRO, MAGEH1, MAGEB18, MAGEB6, MAGEB4, MAGEB1, MAGED4B, MAGED1, MAGEB2, and MAGEB3 were significantly overexpressed in sarcoma. TRO was further demonstrated to be distinctively upregulated in osteosarcoma cell lines and associated with shorter overall survival. TRO may play an important role in the development of OS and may be a promising potential biomarker and prognostic factor.

Correlation between vascular endothelial growth factor (VEGF) expression with histopathological findings in osteosarcoma

Vascular endothelial growth factor (VEGF) expression is associated with malignancy progression, metastasis, and poor prognosis in many malignancies, including osteosarcoma. However, studies concerning correlations between VEGF expression and histopathological prognostic factors ofosteosarcoma are limited. This study aimed to evaluate the correlations between VEGF expression and histopathological findings in osteosarcoma’spatients.This was a cross-sectional study using formalin-fixed paraffin embedded (FFPE) samples of 32 osteosarcoma’s patients from Dr. Sardjito General Hospital, Yogyakarta. Histopathological findings of specimens were re-evaluated by two independent observers, recorded for the subtypes, invasiveness, grading, mitotic counts, and tumor infiltrating lymphocytes (TIL). Expression of VEGF was determined based on immunostaining and evaluated using immunoreactivity score (IRS).Chi-square and Spearman correlation test were used to analyze the association between variables. Range of VEGF expression score was 0 to 11, with mean 5.09. Significant negative correlation between the VEGF expression and TIL was observed (p=0.046). However, there was no significant correlations between the VEGF expression and osteosarcomas subtypes, invasion, grading or mitotic counts (p&gt; 0.05). In conclusion, the VEGF expression is associated with TIL. Further study is needed to evaluate the roles of VEGF and lymphocytes in osteosarcoma development dan progression in order to better understand of the role of VEGF in immunotherapy of osteosarcoma.

Identification of Prognostic RBPs in Osteosarcoma.

Osteosarcoma often occurs in children and adolescents and causes poor prognosis. The role of RNA-binding proteins (RBPs) in malignant tumors has been elucidated in recent years. Our study aims to identify key RBPs in osteosarcoma that could be prognostic factors and treatment targets. GSE33382 dataset was downloaded from Gene Expression Omnibus (GEO) database. RBPs extraction and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological function of differential expression RBPs. Moreover, we constructed Protein-protein interaction (PPI) network and obtained key modules. Key RBPs were identified by univariate Cox regression analysis and multiple stepwise Cox regression analysis combined with the clinical information from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Risk score model was generated and validated by GSE16091 dataset. A total of 38 differential expression RBPs was identified. Go and KEGG results indicated these RBPs were significantly involved in ribosome biogenesis and mRNA surveillance pathway. COX regression analysis showed DDX24, DDX21, WARS and IGF2BP2 could be prognostic factors in osteosarcoma. Spearman’s correlation analysis suggested that WARS might be important in osteosarcoma immune infiltration. In conclusion, DDX24, DDX21, WARS and IGF2BP2 might play key role in osteosarcoma, which could be therapuetic targets for osteosarcoma treatment.

1647P Evaluation of baseline neutrophil to lymphocyte (NLR), platelet to lymphocyte (PLR) and lymphocyte to monocyte ratios (LMR) as prognostic factors in osteosarcoma – The Toronto Sarcoma Program Experience

1647P Evaluation of baseline neutrophil to lymphocyte (NLR), platelet to lymphocyte (PLR) and lymphocyte to monocyte ratios (LMR) as prognostic factors in osteosarcoma – The Toronto Sarcoma Program Experience