Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in multiple myeloma.
Xu. Li L; Zhang. Hui H; Wang. Kai K; Gao. Xuejie X; Bu. Wenxuan W; Yu. Dandan D; Hu. Ke K; Zhang. Qikai Q; Wang. Guanli G; Wu. Xiaosong X; Jia. Xinyan X; Peng. Yu Y; Song. Dongliang D; Yi. Hongfei H; Cai. Haiyan H; Shi. Jumei J; Feng. Qilin Q
Key Findings
- Six copper‑death genes show different expression in myeloma patients and link to survival.
- Two molecular subtypes of myeloma were defined, each with distinct immune profiles.
- A five‑gene risk model (CKS2, HGF, HSP90B1, PRIM1, VCAM1) predicts prognosis.
Practical Outcomes
- There are no actionable protocols, dosages, or lifestyle recommendations for the biohacker community. The findings are specific to cancer research and clinical treatment planning, not to general health optimization.
Summary
The study looks at how a copper‑related cell‑death pathway (cuproptosis) affects multiple myeloma, a blood cancer, and identifies gene patterns that predict patient outcomes. It does not involve palmitoyl‑dipeptide‑6 or any interventions that everyday health‑optimizers could use.
Abstract
Multiple myeloma (MM) is a challenging hematologic malignancy with increasing incidence. Cuproptosis, a copper-dependent form of cell death associated with mitochondrial metabolism and protein lipoylation, remains unexplored in MM. This study aims to investigate this connection using transcriptome profiling and clinical data from the Gene Expression Omnibus database. Analysis of copper death-related genes (CRGs) revealed significant expression differences in 6 out of 12 CRGs, with GLS, ATP7B, PDHA1, MTF1, CDKN2A and DLAT showing notable correlations with survival of MM patients. Unsupervised clustering identified two cuproptosis molecular subtypes in MM patients, which exhibited significant associations with clinical features, prognosis, and immune cell infiltration. These subtypes identified 186 potential MM target genes, enriched in protein binding and intracellular/extracellular structure regulations. Five key biomarkers (CKS2, HGF, HSP90B1, PRIM1, and VCAM1) effectively stratified patients into high- and low-risk groups, strongly correlated with age, ISS stage, serum LDH content, and survival. Functional enrichment analysis revealed differential genes were involved in regulating cell membrane structure, protein binding, and metabolic pathways. High- and low-risk groups displayed distinct immune cell infiltration patterns and immune checkpoint expressions. In vitro experiments, the combination of elesclomol (a copper ion carrier) and bortezomib (Bortezomib) demonstrated a synergistic anti-myeloma effect through excessive intracellular reactive oxygen species generation. This study provides valuable insights into the role of CRGs in MM, potentially aiding in prognosis prediction and the development of effective, personalized therapeutic strategies.
Study Information
pubmed
2025
2025-11-14T00:00:00.000Z
10.1016/j.tranon.2025.102601
49