Clinical significance and immune landscape of a novel ferroptosis-related prognosis signature in osteosarcoma

• Published in: BMC cancer 2023-03, Vol.23 (1), p.229-229, Article 229
• Main Authors: Yang, Liyu, Liu, Jiamei, Liu, Shengye
• Format: Article
• Language: English
• Subjects: Adolescent; Apoptosis; Bioinformatics; Biotechnology; BNIP3 protein; Bone cancer; Bone Neoplasms; Cancer therapies; Cell death; Cell migration; Cell proliferation; Chemotherapy; Clinical Relevance; Clinical significance; Datasets; Development and progression; Drug therapy; Ferroptosis; Gene expression; Genes; Health aspects; Humans; Immune; Immune system; Immunotherapy; Infiltration; Inflammation; Interleukin 17; Iron in the body; Lymphocytes T; Medical prognosis; Melanoma; Metastases; Metastasis; Mucins; Osteosarcoma; Osteosarcoma cells; Physiological aspects; Prognosis; Proteins; Risk groups; Sarcoma; Scientific equipment and supplies industry; Signature; Survival analysis; T cells; Transcriptomes; Tumors
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-023-10688-7

Osteosarcoma is a malignant tumor that usually occurs in adolescents aged 10-20 years and is associated with poor prognosis. Ferroptosis is an iron-dependent cell death mechanism that plays a vital role in cancer. Osteosarcoma transcriptome data were downloaded from the public database TARGET and from previous studies. A prognostic risk score signature was constructed using bioinformatics analysis, and its efficacy was determined by analyzing typical clinical features. The prognostic signature was then validated with external data. Differences in immune cell infiltration between high- and low-risk groups were analyzed. The potential of the prognostic risk signature as a predictor of immunotherapy response was evaluated using the GSE35640 (melanoma) dataset. Five key genes expression were measured by real-time PCR and western blot in human normal osteoblasts and osteosarcoma cells. Moreover, malignant biological behaviors of osteosarcoma cells were tested by modulating gene expression level. We obtained 268 ferroptosis-related genes from the online database FerrDb and published articles. Transcriptome data and clinical information of 88 samples in the TARGET database were used to classify genes into two categories using clustering analysis, and significant differences in survival status were identified. Differential ferroptosis-related genes were screened, and functional enrichment showed that they were associated with HIF-1, T cells, IL17, and other inflammatory signaling pathways. Prognostic factors were identified by univariate Cox regression and LASSO analysis, and a 5-factor prognostic risk score signature was constructed, which was also applicable for external data validation. Experimental validation indicated that the mRNA and protein expression level of MAP3K5, LURAP1L, HMOX1 and BNIP3 decreased significantly, though meanwhile MUC1 increased in MG-63 and SAOS-2 cells compared with hFOB1.19 cells. Cell proliferation and migration ability of SAOS-2 were affected based on alterations of signature genes. Significant differences in immune cell infiltration between high- and low-risk groups indicated that the five ferroptosis-related prognostic signature was constructed and could be used to predict the response to immunotherapy in osteosarcoma.