Gene signatures with predictive and prognostic survival values in human osteosarcoma

Abstract

Osteosarcoma is a common malignancy seen mainly in children and adolescents. The disease is characterized by poor overall prognosis and lower survival due to a lack of predictive markers. Many gene signatures with diagnostic, prognostic, and predictive values were evaluated to achieve better clinical outcomes. Two public data series, GSE21257 and UCSC Xena, were used to identify the minimum number of robust genes needed for a predictive signature to guide prognosis of patients with osteosarcoma. The lasso regression algorithm was used to analyze sequencing data from TCGA-TARGET, and methods such as Cox regression analysis, risk factor scoring, receiving operating curve, KMplot prognosis analysis, and nomogram were used to characterize the prognostic predictive power of the identified genes. Their utility was assessed using the GEO osteosarcoma dataset. Finally, the functional enrichment analysis of the identified genes was performed. A total of twenty-gene signatures were found to have a good prognostic value for predicting patient survival. Gene ontology analysis showed that the key genes related to osteosarcoma were categorized as peptide–antigen binding, clathrin-coated endocytic vesicle membrane, peptide binding, and MHC class II protein complex. The osteosarcoma related genes in these modules were significantly enriched in the processes of antigen processing and presentation, phagocytosis, cell adhesion molecules, Staphylococcus aureus infection. Twenty gene signatures were identified related to osteosarcoma, which would be helpful for predicting prognosis of patients with OS. Further, these signatures can be used to determine the subtypes of osteosarcoma.

Development and Verification of a Hypoxic Gene Signature for Predicting Prognosis, Immune Microenvironment, and Chemosensitivity for Osteosarcoma

“…Our in vitro experiments demonstrated that silencing MXI1 attenuated proliferation, migration, and invasion of osteosarcoma cells, confirming the important role of MXI1 in osteosarcoma progression. Thus, our study is novel and better suited than previously published prognostic protocols for osteosarcoma ( Wu Z.-l. et al, 2020 ; Qiu et al, 2021 ).…”

“…Our in vitro experiments demonstrated that silencing MXI1 attenuated proliferation, migration, and invasion of osteosarcoma cells, confirming the important role of MXI1 in osteosarcoma progression. Thus, our study is novel and better suited than previously published prognostic protocols for osteosarcoma (Wu Z.-l. et al, 2020;Qiu et al, 2021). Cancer progression is highly correlated with the physiological state of osteosarcoma immune microenvironment that consists of innate as well as adaptive immune cells (Roma-Rodrigues et al, 2019).…”

Bioinformatics integrated analysis to investigate candidate biomarkers and associated metabolites in osteosarcoma

“…A previous study shows that STC2 is an outstanding immune-related gene during the progression of OS [ 33 ]. A recent study indicates that 20 genes including STC2 signatures are identified related to OS, which can be helpful for predicting prognosis of patients with OS [ 34 ]. SPARC1 protein can affect osteoblast differentiation, tumorigenesis and tumor metastasis [ 35 ].…”

Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction

“…With this treatment, the five-year survival rate of osteosarcoma patients with localized disease is 65–70%. Unfortunately, the patient develops resistance to neoadjuvant chemotherapy, resulting in metastasis and a five-year survival rate of 15–30% [ 1 , 4 ]. Based on the clinical outcome of osteosarcoma patients without overt metastatic sites at diagnosis, 90% of patients developed lung metastasis 6–36 months later, but metastases can also develop in bone (8–10%) and rarely in lymph nodes.…”