ArticleFrontiers in genetics2022
Identification of a Solute Carrier Family-Based Signature for Predicting Overall Survival in Osteosarcoma.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 17 citations in OpenAlex.
- SLC45A4 encodes a peroxisomal putrescine transporter that promotes GABA de novo synthesis.Nature communications · 2025Article
- The homeobox family gene signature predicts the prognosis of osteosarcoma and correlates with immune invasion.Scientific reports · 2025Article
- Article
- Comprehensive analyses of solute carrier family members identify SLC12A2 as a novel therapy target for colorectal cancer.Scientific reports · 2024Article
- Identification of key pyroptosis-related genes and microimmune environment among peripheral arterial beds in atherosclerotic arteries.Scientific reports · 2024Article
- A ferroptosis-related LncRNAs signature for predicting prognoses and screening potential therapeutic drugs in patients with lung adenocarcinoma: A retrospective study.Cancer reports (Hoboken, N.J.) · 2024Article
- Construction of a prognostic risk score model based on the ARHGAP family to predict the survival of osteosarcoma.BMC cancer · 2023Article
- Transcriptional profiling of canine osteosarcoma identifies prognostic gene expression signatures with translational value for humans.Communications biology · 2023Article
- Rethinking our approach to cancer metabolism to deliver patient benefit.British journal of cancer · 2023Review
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Given the important role of SLC family in essential physiological processes including nutrient uptake, ion transport, and waste removal, and that their dysregulation was found in distinct forms of cancer, here we identified a novel gene signature of SLC family for patient risk stratification in osteosarcoma. Gene expression data and relevant clinical materials of osteosarcoma samples were retrieved from The Cancer Genome Atlas (TCGA) database. Prognosis-related SLC genes were identified by performing univariate Cox regression analysis and were utilized to construct a four-SLC gene signature in osteosarcoma. It allowed patients to be classified into high- and low-risk groups, and Kaplan-Meier survival analysis in the training, testing, entire, and external GSE21257 cohorts suggested that the overall survival of patients in high-risk group was consistently worse than that in low-risk group, suggesting the promising accuracy and generalizability of the SLC-based signature in predicting the prognosis of patients with osteosarcoma. Moreover, univariate and multivariate Cox regression analyses indicated that the derived risk score was the only independent prognostic factor for osteosarcoma patients in TCGA and GSE21257 cohorts. Besides, a prognostic nomogram comprising the derived risk score and clinical features including gender and age was developed for clinical decision-making. Functional enrichment analyses of the differentially expressed genes between high- and low-risk group revealed that immune-related biological processes and pathways were significantly enriched. Estimation of tumor immune microenvironment using ESTIMATE algorithm revealed that patients with lower risk score had higher stromal, immune, and ESTIMATE score, and lower tumor purity. ssGSEA analyses indicated that the scores of various immune subpopulations including CD8+ T cells, DCs, and TIL were lower in high-risk group than these in low-risk group in both cohorts. As for the related immune functions, the scores of APC co-inhibition, CCR, check-point, T cell co-stimulation, and Type II IFN response were lower in high-risk group than these in low-risk group in both cohorts. In all, we identified a novel prognostic signature based on four SLC family genes that accurately predicted overall survival in osteosarcoma patients. Furthermore, the signature is linked to differences in immunological status and immune cell infiltrations in the tumor microenvironment.
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