Dataset Information

Decoding the Impact of Tumor Microenvironment in Osteosarcoma Progression and Metastasis.

ABSTRACT: Osteosarcoma (OS) is a heterogeneous, highly metastatic bone malignancy in children and adolescents. Despite advancements in multimodal treatment strategies, the prognosis for patients with metastatic or recurrent disease has not improved significantly in the last four decades. OS is a highly heterogeneous tumor; its genetic background and the mechanism of oncogenesis are not well defined. Unfortunately, no effective molecular targeted therapy is currently available for this disease. Understanding osteosarcoma's tumor microenvironment (TME) has recently gained much interest among scientists hoping to provide valuable insights into tumor heterogeneity, progression, metastasis, and the identification of novel therapeutic avenues. Here, we review the current understanding of the TME of OS, including different cellular and noncellular components, their crosstalk with OS tumor cells, and their involvement in tumor progression and metastasis. We also highlight past/current clinical trials targeting the TME of OS for effective therapies and potential future therapeutic strategies with negligible adverse effects.

SUBMITTER: Nirala BK

PROVIDER: S-EPMC10605493 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Decoding the Impact of Tumor Microenvironment in Osteosarcoma Progression and Metastasis.

Nirala Bikesh K BK Yamamichi Taku T Petrescu D Isabel DI Shafin Tasnuva N TN Yustein Jason T JT

Cancers 20231023 20

Osteosarcoma (OS) is a heterogeneous, highly metastatic bone malignancy in children and adolescents. Despite advancements in multimodal treatment strategies, the prognosis for patients with metastatic or recurrent disease has not improved significantly in the last four decades. OS is a highly heterogeneous tumor; its genetic background and the mechanism of oncogenesis are not well defined. Unfortunately, no effective molecular targeted therapy is currently available for this disease. Understandi ...[more]

PMID: 37894474

Similar Datasets

Project description: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.

Project description:BackgroundThe tumor microenvironment (TME) is not only a key factor in the malignant progression of cancer but also plays an indispensable role in tumor immunotherapy. As an important regulatory factor in the TME, long non-coding RNAs (incRNA) are important for the development of bladder cancer. The purpose of this study was to explore the molecular mechanism of malignant progression of bladder cancer (BCa) from the perspective of immunology, establish a reliable signature, and evaluate its effect on prognosis, metastasis, and the effectiveness of immunotherapy.MethodsThe TME was assessed by single-sample gene set enrichment analysis (ssGSEA) in 373 patients with muscle invasive bladder cancer (MIBC) in The Cancer Genome Atlas (TCGA). Combining RNA sequence data from 49 BCa patients in our center, we established TME-related prognostic signatures (TMERPS) based on TME-related immune prognosis genes using weighted gene correlation network analysis, selection operator Cox analysis, minimum absolute shrinkage, and survival analysis. Real-Time Quantitative PCR was used for expression level analysis of related genes. Functional enrichment analysis and nomograms were used to explore the potential impact of TMERPS on the immune system, prognosis, and metastasis.ResultsThe ssGSEA proved to be an accurate assessment of immune levels in BCa samples. TMERPS was established based on six TME-associated prognostic lncRNAs and was shown to be closely associated with prognosis, metastasis, and immune levels, and to have a significant stratifying effect on the therapeutic efficacy of immune checkpoint inhibitors. Finally, three TMERPS-based nomograms were shown to be effective in predicting prognosis, lymph node metastasis, and distant metastasis in BCa patients.ConclusionsTMERPS can stratify BCa patients into different risk groups with different prognoses, immunotherapy sensitivity, and risk of metastasis. TMERPS-based nomograms can effectively predict prognosis and metastasis in BCa patients.

Dataset Information

Decoding the Impact of Tumor Microenvironment in Osteosarcoma Progression and Metastasis.

Publications

Decoding the Impact of Tumor Microenvironment in Osteosarcoma Progression and Metastasis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets