ArticleBMC genomics2024
Integrated analysis of single-cell and bulk RNA sequencing data reveals prognostic characteristics of lysosome-dependent cell death-related genes in osteosarcoma.
Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Development of a Novel 11-Gene Signature Related to Immune Subtypes for FibromyalgiaEndocrine, metabolic & immune disorders drug targets · 2026Article
- Integrative analysis of lysosome-dependent cell death related molecular subtypes and prognosis prediction in papillary thyroid carcinoma.Journal of Cancer · 2026Article
- Utilises Machine Learning Techniques to Deeply Analyse the Role of Lysosome-Dependent Cell Death in Endometrial Cancer and Its Interactions With the Tumour Microenvironment.Journal of cellular and molecular medicine · 2025Article
- Single-cell RNA sequencing in osteosarcoma: applications in diagnosis, prognosis, and treatment.Medical oncology (Northwood, London, England) · 2025Review
- Identification of key programmed cell death genes for predicting prognosis and treatment sensitivity in colorectal cancer.Frontiers in oncology · 2024Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundTumor cells exhibit a heightened susceptibility to lysosomal-dependent cell death (LCD) compared to normal cells. However, the role of LCD-related genes (LCD-RGs) in Osteosarcoma (OS) remains unelucidated. This study aimed to elucidate the role of LCD-RGs and their mechanisms in OS using several existing OS related datasets, including TCGA-OS, GSE16088, GSE14359, GSE21257 and GSE162454.
resultsAnalysis identified a total of 8,629 DEGs1, 2,777 DEGs2 and 21 intersection genes. Importantly, two biomarkers (ATP6V0D1 and HDAC6) linked to OS prognosis were identified to establish the prognostic model. Significant differences in risk scores for OS survival were observed between high and low-risk cohorts. Additionally, scores of dendritic cells (DC), immature DCs and γδT cells differed significantly between the two risk cohorts. Cell annotations from GSE162454 encompassed eight types (myeloid cells, osteoblastic OS cells and plasma cells). ATP6V0D1 was found to be significantly over-expressed in myeloid cells and osteoclasts, while HDAC6 was under-expressed across all cell types. Moreover, single-cell trajectory mapping revealed that myeloid cells and osteoclasts differentiated first, underscoring their pivotal role in patients with OS. Furthermore, ATP6V0D1 expression progressively decreased with time.
conclusionsA new prognostic model for OS, associated with LCD-RGs, was developed and validated, offering a fresh perspective for exploring the association between LCD and OS.
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