Identification of novel prognostic biomarkers for osteosarcoma: a bioinformatics analysis of differentially expressed genes in the mesenchymal stem cells from single-cell sequencing data set

Jiang, Haoli; Du, Haoyuan; Liu, Yingnan; Tian, Xiao; Xia, Jinquan

doi:10.21037/tcr-22-2370

Cited by 5 publications

(7 citation statements)

References 43 publications

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“…Therefore, the high expression of IFITM5 was associated with the shorter overall survival subtype which is in line with the previous study (Additional file 1: Fig. S1A) [24].…”

Section: Transcriptomic Heterogeneity Of Oncocytes In Ossupporting

confidence: 91%

Abnormal signal pathways and tumor heterogeneity in osteosarcoma

et al. 2023

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Background Osteosarcoma (OS) is the most frequent and aggressive primary malignant sarcoma among adolescents and chemotherapy has not substantially progressed for decades. New insights into OS development and therapeutic strategies are urgently needed. Methods We analyzed integrated single-cell transcriptomes, bulk RNA-seq, and microarray data from Gene Expression Omnibus (GEO) datasets. We also used Weighted Gene Co-expression Network Analysis (WGCNA), Gene set enrichment analysis (GSEA), and Gene set variation analysis (GSVA), along with Simple ClinVar and Enrichr web servers. Results The findings of integrated single-cell analysis showed that OS arises from imperfect osteogenesis during development. Novel abnormalities comprised deficient TGFβ and P53 signal pathways, and cell cycle pathway activation, and a potentially new driver mutation in the interferon induced transmembrane protein 5 (IFITM5) that might function as a pathogenic factor in OS. Osteosarcoma is characterized by oncocyte heterogeneity, especially in immunogenic and adipocyte-like subtypes that respectively promote and hamper OS treatment. Etoposide is a promising chemotherapeutic that provides palliation by affecting the subtype of OS and correcting the abnormal pathways. Conclusion Various abnormal signal pathways play indispensable roles in OS development. We explored the heterogeneity and underlying mechanisms of OS and generated findings that will assist with OS assessment and selecting optimal therapies.

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“…Therefore, the high expression of IFITM5 was associated with the shorter overall survival subtype which is in line with the previous study (Additional file 1: Fig. S1A) [24].…”

Section: Transcriptomic Heterogeneity Of Oncocytes In Ossupporting

confidence: 91%

Abnormal signal pathways and tumor heterogeneity in osteosarcoma

et al. 2023

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“…Its main role is to promote osteoclast bone resorption activity and to inhibit osteoclast apoptosis ( 32 ). Upregulation of FDPS expression is also significantly associated with patients’ poor prognosis ( 33 ). MMD, one of the proteins associated with monocyte-to-macrophage differentiation, can enhance ERK1/2 and Akt phosphorylation in macrophages after LPS stimulation.…”

Section: Discussionmentioning

confidence: 99%

A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes

et al. 2023

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BackgroundTumor infiltrating lymphocytes (TILs), the main component in the tumor microenvironment, play a critical role in the antitumor immune response. Few studies have developed a prognostic model based on TILs in osteosarcoma.MethodsScRNA-seq data was obtained from our previous research and bulk RNA transcriptome data was from TARGET database. WGCNA was used to obtain the immune-related gene modules. Subsequently, we applied LASSO regression analysis and SVM algorithm to construct a prognostic model based on TILs marker genes. What’s more, the prognostic model was verified by external datasets and experiment in vitro. ResultsEleven cell clusters and 2044 TILs marker genes were identified. WGCNA results showed that 545 TILs marker genes were the most strongly related with immune. Subsequently, a risk model including 5 genes was developed. We found that the survival rate was higher in the low-risk group and the risk model could be used as an independent prognostic factor. Meanwhile, high-risk patients had a lower abundance of immune cell infiltration and many immune checkpoint genes were highly expressed in the low-risk group. The prognostic model was also demonstrated to be a good predictive capacity in external datasets. The result of RT-qPCR indicated that these 5 genes have differential expression which accorded with the predicting outcomes.ConclusionsThis study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response.

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“…For example, Jiang et al discovered seven hub genes, including ANXA1, FKBP11, SP7, and TPM1, which were more upregulated in MSCs than in highgrade OS cells and FDPS, IFITM5, and SQLE, which were more downregulated. 101 Xu et al revealed that the cellular communication among MSCs, proliferative osteoblastic OS cells, and osteoblastic OS cells mainly revolves around three pathways: SPP1, FGF, and Notch. 41 The SPP1-CD44 axis, for example, is involved in the communication between myeloid cells, pericytes, OCs, MSCs, and proliferative osteoblasts in OS.…”

Section: Mesencymal Stem Cellsmentioning

confidence: 99%

The heterogeneity and drug resistance of malignant cells and intercellular communication of microenvironment in osteosarcoma: Based on single‐cell analysis

Ma,

Wang,

Zhao

et al. 2023

Clinical and Translational Dis

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Background: Osteosarcoma (OS) is a prevalent bone cancer characterized by its aggressive nature, which often metastasizes to the lungs and contributes to a poor prognosis. Treatment progress has been hindered by drug resistance, distant metastases, and significant patient heterogeneity. However, recent advancements in technologies such as sequencing and multi-omics have enabled more in-depth investigations at the micro level.Aim: By undertaking a critical analysis of related studies, the present work intends to provide an overview of the microenvironmental features of osteosarcoma discovered through single-cell RNA sequencing (scRNA-seq) analysis. The articles included in this review were from several medical and health databases. Results and discussion: We also discuss drug resistance traits, taking into account the heterogeneity of OS cells within the tumor microenvironment (TME). This includes inherent and acquired resistance in both pre-and postchemotherapy osteosarcoma, as well as the close association between cancer stem cells (CSCs) and drug resistance. Additionally, we examine the intercellular communication between OS cells and other cell types, as revealed by both traditional and single-cell studies, and suggest several promising therapeutic targets. Conclusion:Single-cell RNA sequencing (scRNA-seq) provides a detailed view of the tumor microenvironment, revealing intercellular communication between osteosarcoma cells and other cells, and aiding in the identification of potential therapeutic targets.

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Identification of novel prognostic biomarkers for osteosarcoma: a bioinformatics analysis of differentially expressed genes in the mesenchymal stem cells from single-cell sequencing data set

Cited by 5 publications

References 43 publications

Abnormal signal pathways and tumor heterogeneity in osteosarcoma

Abnormal signal pathways and tumor heterogeneity in osteosarcoma

A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes

The heterogeneity and drug resistance of malignant cells and intercellular communication of microenvironment in osteosarcoma: Based on single‐cell analysis

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