A risk score model for the prediction of osteosarcoma metastasis

Dong, Siqi; Huo, Hongjun; Mao, Yu; Li, Xin; Liu, Dong

doi:10.1002/2211-5463.12592

Cited by 38 publications

(35 citation statements)

References 33 publications

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“…ALOX5AP is one of the essential genes in the production of leukotrienes from arachidonic acid via encoding the ALOX5AP.Consistent with our results, Wu et al (2018) found that high expression of ALOX5AP is associated with poor survival outcome in esophageal carcinoma. Additionally, ALOX5AP also involved in a risk model to serve as a prediction of osteosarcoma metastasis (Dong et al, 2019). It is known that the nuclear autoantigen SP100 participates in various biological processes, such as cellular gene expression, differentiation, and cell growth (Everett et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

Prognostic Value of a Stemness Index-Associated Signature in Primary Lower-Grade Glioma

et al. 2020

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Objective: As a prevalent and infiltrative cancer type of the central nervous system, the prognosis of lower-grade glioma (LGG) in adults is highly heterogeneous. Recent evidence has demonstrated the prognostic value of the mRNA expression-based stemness index (mRNAsi) in LGG. Our aim was to develop a stemness index-based signature (SI-signature) for risk stratification and survival prediction. Methods: Differentially expressed genes (DEGs) between LGG in the Cancer Genome Atlas (TCGA) and normal brain tissue samples from the Genotype-Tissue Expression (GTEx) project were screened out, and the weighted gene correlation network analysis (WGCNA) was employed to identify the mRNAsi-related gene sets. Meanwhile, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed for the functional annotation of the key genes. ESTIMATE was used to calculate tumor purity for acquiring the correct mRNAsi. Differences in overall survival (OS) between the high and low mRNAsi (corrected mRNAsi) groups were compared using the Kaplan Meier analysis. By combining the Lasso regression with univariate and multivariate Cox regression, the SI-signature was constructed and validated using the Chinese Glioma Genome Atlas (CGGA). Results: There was a significant difference in OS between the high and low mRNAsi groups, which was also observed in the two corrected mRNAsi groups. Based on threshold limits, 86 DEGs were most significantly associated with mRNAsi via WGCNA. Seven genes (ADAP2, ALOX5AP, APOBEC3C, FCGRT, GNG5, LRRC25, and SP100) were selected to establish a risk signature for primary LGG. The ROC curves showed a fair performance in survival prediction in both the TCGA and the CGGA validation cohorts. Univariate and multivariate Cox regression revealed that the risk group was an independent prognostic factor in primary LGG. The nomogram was developed based on clinical parameters integrated with the risk signature, and its accuracy for

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Section: Discussionmentioning

confidence: 99%

Prognostic Value of a Stemness Index-Associated Signature in Primary Lower-Grade Glioma

et al. 2020

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“…Downregulation of IgG binding protein in prostate cancer was found by Mozammel H et al [7]. FCGBP were identi ed as being associated with osteosarcoma metastasis and might facilitate the individual management of patients after osteosarcoma treatment [8]. Yasui Y et al reported that compared to the normal tissues, FCGBP was down-regulated in cancer tissues.…”

Section: Introductionmentioning

confidence: 96%

IgG Fc Binding Protein (FCGBP) Is Down-Regulated in Metastatic Lesions and Predicts Survival in Metastatic Colorectal Cancer Patients

Yuan

Zhao

et al. 2020

Preprint

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Background: Liver is the most frequent metastatic spread sites for CRC patients and these patients have much poorer prognosis compared to those without metastasis. Previous studies have shown that IgG Fc binding protein (FCGBP) plays important roles in tumorigenesis, progression and prognosis. In this study, we are aimed to explore the significance of FCGBP in liver metastatic CRC (LMCRC) patients. Methods: The expression data of FCGBP was obtained from GEO and TCGA database, FCGBP RNA expression was evaluated between primary lesions (PC) and liver metastatic lesion (LM). 135 paired specimens including normal mucosa, primary tumor and liver metastasis tissues were all collected from CRC patients and adopted in Tissue microarrays (TMAs). Immunohistochemical staining was performed on the TMAs slides with FCGBP and the immunohistochemistry score (SI) was calculated by the staining intensity multiplied by the positive rate of stained cells. Survival curves were calculated by Kaplan–Meier method and the log-rank test was used to compare the overall survival (OS) and disease-free survival (DFS). Univariate and multivariate analysis for prognosis were using Cox proportional hazards regression model.Results: FCGBP RNA was down-regulated in PC and LM, and especially lower in LM in database. We also found FCGBP protein was down-regulated in primary lesion and metastatic lesion, especially in metastatic lesion in 135 paired tumor tissues. According to immunohistochemistry score (SI), each cohort (primary lesion and metastatic lesion) was divided into FCGBP-positive (SI=4-12) and FCGBP-negative (SI=0-3) group. In both groups, the level of CEA (PC group, 3.880 vs 77.049, p<0.001; LM group, 3.890 vs 14.239, p=0.008) and CA19-9 (PC group, 8.610 vs 111.700, p<0.001; LM group, 7.660 vs 19.380, p=0.037) was lower than those in FCGBP-negative group. FCGBP-positive in LM cohort was an independent risk factor both in OS (HR 1.573, 95% Cl [1.017-2.433], p=0.042) and DFS (HR 1.869, 95% Cl [1.256-2.781], p=0.002). Conclusions: This study has found the relationship between FCGBP and clinical information of LMCRC patients. FCGBP expression was much lower in liver metastasis tumor tissues compared with primary tumor tissues in liver metastatic CRC patients and associated with the OS and PFS. Our works illustrate that FCGBP can be a promising prognostic factor for LMCRC.

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“…Previous studies found that some genes, such as p16 and nm23 could also inhibit the metastatic process in OS. Further, Dong et al constructed a risk score model consisting of eight genes (RAB1, CLEC3B, FCGBP, RNASE3, MDL1, ALOX5AP, VMO1, and ALPK3) to predict OS metastasis. However, it is unclear which genes were survival‐associated.…”

Section: Introductionmentioning

confidence: 99%

A risk signature‐based on metastasis‐associated genes to predict survival of patients with osteosarcoma

Shi

Zhuang

et al. 2020

J of Cellular Biochemistry

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Osteosarcoma (OS) is the most common primary solid malignant bone tumor, and its metastasis is a prominent cause of high mortality in patients. In this study, a prognosis risk signature was constructed based on metastasis-associated genes. Four microarrays datasets with clinical information were downloaded from Gene Expression Omnibus, and 256 metastasis-associated genes were identified by limma package. Further, a protein-protein interaction network was constructed, and survival analysis was performed using data from the Therapeutically Applicable Research to Generate Effective Treatments data matrix, identifying 19 genes correlated with prognosis. Six genes were selected by the least absolute shrinkage and selection operator regression for multivariate cox analysis. Finally, a three-gene (MYC, CPE, and LY86) risk signature was constructed, and datasets GSE21257 and GSE16091 were used to validate the prediction efficiency of the signature. The survival times of low-and highrisk groups were significantly different in the training set and validation set.Additionally, gene set enrichment analysis revealed that the genes in the signature may affect the cell cycle, gap junctions, and interleukin-6 production. Therefore, the three-gene survival risk signature could potentially predict the prognosis of patients with OS. Further, proteins encoded by CPE and LY86 may provide novel insights into the prediction of OS prognosis and therapeutic targets.differentially expressed genes, metastasis, osteosarcoma, risk signature, survival analysis 1 | INTRODUCTION Osteosarcoma (OS), characterized by malignant mesenchymal cells producing an osteoid matrix and fibrillary stroma, is the most common osseous aggressive cancer in children and juveniles and commonly arises at the terminus of the long bones, including distal femurs, proximal tibias, and proximal humor. 1 According to the National Cancer Institute Surveillance, Epidemiology, and End Results program, the frequency of OS has increased by 0.3% per year over the last decade. 2 With the intensification of chemotherapeutic regimens, the 5-year survival rate of OS patients without metastasis has been improved to 60%-70%. 3 By contrast, the survival rate is only 0%-30% in patients with OS with metastasis, 4 indicating that OS metastasis is associated poor longterm prognosis. However, metastasis-associated molecules Yi Shi and Ronghan He contributed equally to this work.

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A risk score model for the prediction of osteosarcoma metastasis

Cited by 38 publications

References 33 publications

Prognostic Value of a Stemness Index-Associated Signature in Primary Lower-Grade Glioma

Prognostic Value of a Stemness Index-Associated Signature in Primary Lower-Grade Glioma

IgG Fc Binding Protein (FCGBP) Is Down-Regulated in Metastatic Lesions and Predicts Survival in Metastatic Colorectal Cancer Patients

A risk signature‐based on metastasis‐associated genes to predict survival of patients with osteosarcoma

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