Development of a prognostic gene signature based on an immunogenomic infiltration analysis of osteosarcoma

Abstract

Osteosarcoma is the most common primary malignant bone tumour predominantly occurring in children and adolescents with a high tendency of local invasion and early metastases. Currently, the systemic chemotherapy plus wide surgical resection are generally recognized as the most effective therapy for this malignancy. However, the main protocol has not been improved since 1980s. And neither does the cure rate. The investigations of prognostic factors and biomarkers of cancer and sarcoma are in progress for these years, with the help of the next-generation sequencing (NGS), single-cell sequencing (SCS) and analysis techniques. Several studies on osteosarcoma reported that tumour size, metastatic disease at the time of diagnosis, histological grade, histologic response to neoadjuvant chemotherapy and adequate surgical margins have consistently shown a strong correlation with prognosis and outcome. 1,2 Additionally, many biomarkers have been identified to be correlated with the

Immune classification of osteosarcoma

“…In this study, we find that infiltration of CD8 T cells, NK cells and M1 Macrophages have a positive association with prognosis, while infiltration of γδ T cells, Mast cells, M0 Macrophages and Dendritic cells have a negative association with prognosis. Yu et al [ 24 ] also illustrates that high level of CD8 T cells is a good prognosis in their survival analysis, and results from [ 26 ] and [ 28 ] indirectly suggest the positive prognostic value of CD8 T cells. Tang et al [ 26 ] reports that CD8 T cells infiltration has a positive correlation with CXCR3 expression which is related to good prognosis.…”

“…Another set of studies find genes with prognostic values by applying Cox model on survival data or performing differentially expressed genes analysis between two groups of interest, and then investigate the relationship between these genes and estimated immune infiltrates [ 26 – 30 ]. Others study the association of immune abundance with clinical information directly [ 24 , 31 – 34 ]. Our work falls somewhat into the third category.…”

“…Among the studies that directly investigate the relationship between immune infiltrations and clinical information, three of them use TARGET data set [ 24 , 31 , 33 ], one uses data from GSE21257 [ 32 ], and one uses data from GSE39058 [ 34 ]. Most of these studies use CIBERSORT [ 24 , 32 – 34 ], while the other uses ssGSEA and ImmuCellAI along with expression of immune marker genes to get estimated abundance of immune cells [ 31 ]. Our study, on the other hand, utilizes the latest and best performing version of deconvolution methods called CIBERSORTx B-mode, and conducts our analyses on both TARGET data set and GSE21257 data set.…”

Identification of a Novel Prognostic Gene Signature From the Immune Cell Infiltration Landscape of Osteosarcoma

“…In addition, more and more studies are involved. For example, in the nine studies (Cao et al, 2020;Chen Z. et al, 2020;Song et al, 2020;Wen et al, 2020;Xiao et al, 2020;Yu et al, 2020;Zhu et al, 2020;Fu et al, 2021;Yang et al, 2021) we included in the study based on the inclusion criteria, they all looked for potential survival-related OS gene signatures from public datasets.However, after we validated them in the training and validation cohorts, we found that the nine-gene signature we generated was superior to others in predicting OS prognosis. Among the nine studies, the one by Yang et al (2021)revealed a gene signature that closely resembled ours.…”

Whole exome sequencing and gene expression analysis of canine osteosarcomas identify mutant TP53 and enriched immune pathways associated with longer survival

“…Although, there is relatively little success of immunotherapy in OSA patients to date, based on the tumor microenvironment profile it is suggested that OSA might be receptive to immune-therapies [13]. Recent articles on the immuno-genomic landscape in human OSA have sought to identify prognostic markers and genomic targets for immune therapy [14,15]. It has been shown that expression of PD-L1 in human OSA was significantly associated with number of immune infiltrates such as T cells, dendritic cells, and natural killer cells [16].…”