AUTHOR=Zhang Bingxin , Wang Quanqiang , Zhang Tianyu , Zheng Ziwei , Lin Zhili , Zhou Shujuan , Zheng Dong , Chen Zixing , Zheng Sisi , Zhang Yu , Lin Xuanru , Dong Rujiao , Chen Jingjing , Qian Honglan , Hu Xudong , Zhuang Yan , Zhang Qianying , Jin Zhouxiang , Jiang Songfu , Ma Yongyong
TITLE=Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma
JOURNAL=Frontiers in Cell and Developmental Biology
VOLUME=11
YEAR=2023
URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2023.1159355
DOI=10.3389/fcell.2023.1159355
ISSN=2296-634X
ABSTRACT=Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.
Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).
Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.
Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.