{"title":"自噬相关基因和免疫失调的整合揭示了多发性骨髓瘤的预后前景。","authors":"Yibo Xia, Dong Zheng, Xinyi Zhang, Shuxia Zhu, Enqing Lan, Hansen Ying, Zixing Chen, Bingxin Zhang, Shujuan Zhou, Yu Zhang, Xuanru Lin, Qiang Zhuang, Honglan Qian, Xudong Hu, Yan Zhuang, Qianying Zhang, Xiangjing Zhou, Zuoting Xie, Songfu Jiang, Yongyong Ma, Zhouxiang Jin, Sisi Zheng","doi":"10.3389/fonc.2025.1635596","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Autophagy is a self-renewal mechanism in which cells degrade damaged organelles or abnormal proteins through lysosomes. This process eliminates harmful components within the cell and maintains energy homeostasis. Multiple myeloma (MM) is a hematological malignancy characterized by uncontrolled plasma cell proliferation. Autophagy plays a dual role in tumorigenesis, yet its prognostic implications in MM remain underexplored.</p><p><strong>Methods: </strong>Transcriptomic and clinical data from 1,386 MM patients (training cohort: GSE136337, n = 415; validation cohorts: GSE24080, n = 558; GSE4581, n = 413) were analyzed. A seven-gene signature (ATIC, CDKN1A, DNAJB9, EDEM1, GABARAPL1, RAB1A, VAMP7) was identified using LASSO-Cox regression. Predictive performance of the autophagy-related model was assessed via Kaplan-Meier analysis, ROC curves, and nomograms. Immune infiltration, drug sensitivity, and functional pathways of the autophagy-related model were evaluated using CIBERSORT, ESTIMATE, and GSEA. The gene expression in the autophagy prognostic model was verified by qRT-PCR in the U266 and RPMI8226 cell lines and blood samples of multiple myeloma patients from the First Affiliated Hospital of Wenzhou Medical University.</p><p><strong>Results: </strong>The autophagy-related risk score stratified patients into high-risk and low-risk groups with distinct survival outcomes (high-risk HR = 0.391, 95%CI:0.284-0.540, p < 0.001). The model demonstrated robust predictive accuracy (5-year AUC = 0.729) and was independently validated. High-risk patients exhibited elevated immune checkpoint expression (CD48, CD70, BTLA), stromal infiltration, and drug resistance. Functional enrichment linked high-risk profiles to MYC activation and oxidative phosphorylation. Through qRT-PCR, the accuracy of the autophagy-related model has been verified in the U266 and RPMI8226 cell lines, as well as in the blood samples of multiple myeloma patients from the First Affiliated Hospital of Wenzhou Medical University.</p><p><strong>Conclusion: </strong>This autophagy-related gene signature provides a reliable prognostic tool for MM, highlighting immune dysregulation and therapeutic resistance mechanisms. Its integration with clinical parameters enhances risk stratification and treatment planning.</p>","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":"15 ","pages":"1635596"},"PeriodicalIF":3.5000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483933/pdf/","citationCount":"0","resultStr":"{\"title\":\"Integration of autophagy-related genes and immune dysregulation reveals a prognostic landscape in multiple myeloma.\",\"authors\":\"Yibo Xia, Dong Zheng, Xinyi Zhang, Shuxia Zhu, Enqing Lan, Hansen Ying, Zixing Chen, Bingxin Zhang, Shujuan Zhou, Yu Zhang, Xuanru Lin, Qiang Zhuang, Honglan Qian, Xudong Hu, Yan Zhuang, Qianying Zhang, Xiangjing Zhou, Zuoting Xie, Songfu Jiang, Yongyong Ma, Zhouxiang Jin, Sisi Zheng\",\"doi\":\"10.3389/fonc.2025.1635596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Autophagy is a self-renewal mechanism in which cells degrade damaged organelles or abnormal proteins through lysosomes. This process eliminates harmful components within the cell and maintains energy homeostasis. Multiple myeloma (MM) is a hematological malignancy characterized by uncontrolled plasma cell proliferation. Autophagy plays a dual role in tumorigenesis, yet its prognostic implications in MM remain underexplored.</p><p><strong>Methods: </strong>Transcriptomic and clinical data from 1,386 MM patients (training cohort: GSE136337, n = 415; validation cohorts: GSE24080, n = 558; GSE4581, n = 413) were analyzed. A seven-gene signature (ATIC, CDKN1A, DNAJB9, EDEM1, GABARAPL1, RAB1A, VAMP7) was identified using LASSO-Cox regression. Predictive performance of the autophagy-related model was assessed via Kaplan-Meier analysis, ROC curves, and nomograms. Immune infiltration, drug sensitivity, and functional pathways of the autophagy-related model were evaluated using CIBERSORT, ESTIMATE, and GSEA. The gene expression in the autophagy prognostic model was verified by qRT-PCR in the U266 and RPMI8226 cell lines and blood samples of multiple myeloma patients from the First Affiliated Hospital of Wenzhou Medical University.</p><p><strong>Results: </strong>The autophagy-related risk score stratified patients into high-risk and low-risk groups with distinct survival outcomes (high-risk HR = 0.391, 95%CI:0.284-0.540, p < 0.001). The model demonstrated robust predictive accuracy (5-year AUC = 0.729) and was independently validated. High-risk patients exhibited elevated immune checkpoint expression (CD48, CD70, BTLA), stromal infiltration, and drug resistance. Functional enrichment linked high-risk profiles to MYC activation and oxidative phosphorylation. Through qRT-PCR, the accuracy of the autophagy-related model has been verified in the U266 and RPMI8226 cell lines, as well as in the blood samples of multiple myeloma patients from the First Affiliated Hospital of Wenzhou Medical University.</p><p><strong>Conclusion: </strong>This autophagy-related gene signature provides a reliable prognostic tool for MM, highlighting immune dysregulation and therapeutic resistance mechanisms. 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引用次数: 0
摘要
背景：自噬是细胞通过溶酶体降解受损细胞器或异常蛋白的一种自我更新机制。这个过程消除了细胞内的有害成分，维持了能量稳态。多发性骨髓瘤（MM）是一种血液学恶性肿瘤，其特征是浆细胞增殖失控。自噬在肿瘤发生中起双重作用，但其在MM中的预后意义仍未得到充分探讨。方法：对1386例MM患者（训练队列：GSE136337， n = 415；验证队列：GSE24080， n = 558; GSE4581, n = 413）的转录组学和临床数据进行分析。采用LASSO-Cox回归方法鉴定出7个基因特征（ATIC、CDKN1A、DNAJB9、EDEM1、GABARAPL1、RAB1A、VAMP7）。通过Kaplan-Meier分析、ROC曲线和模态图评估自噬相关模型的预测性能。使用CIBERSORT、ESTIMATE和GSEA评估自噬相关模型的免疫浸润、药物敏感性和功能途径。在温州医科大学第一附属医院多发性骨髓瘤患者的U266和RPMI8226细胞系及血液样本中，采用qRT-PCR方法验证基因在自噬预后模型中的表达。结果：自噬相关风险评分将患者分为高危组和低危组，生存结局不同（高危HR = 0.391, 95%CI:0.284 ~ 0.540, p < 0.001）。该模型具有稳健的预测准确性（5年AUC = 0.729），并得到了独立验证。高危患者表现出免疫检查点表达（CD48、CD70、BTLA）升高、间质浸润和耐药。功能富集将高风险基因与MYC激活和氧化磷酸化联系起来。通过qRT-PCR，在U266和RPMI8226细胞系以及温州医科大学第一附属医院多发性骨髓瘤患者的血液样本中验证了自噬相关模型的准确性。结论：这种自噬相关基因标记为MM提供了可靠的预后工具，突出了免疫失调和治疗耐药机制。它与临床参数的结合增强了风险分层和治疗计划。
Integration of autophagy-related genes and immune dysregulation reveals a prognostic landscape in multiple myeloma.
Background: Autophagy is a self-renewal mechanism in which cells degrade damaged organelles or abnormal proteins through lysosomes. This process eliminates harmful components within the cell and maintains energy homeostasis. Multiple myeloma (MM) is a hematological malignancy characterized by uncontrolled plasma cell proliferation. Autophagy plays a dual role in tumorigenesis, yet its prognostic implications in MM remain underexplored.
Methods: Transcriptomic and clinical data from 1,386 MM patients (training cohort: GSE136337, n = 415; validation cohorts: GSE24080, n = 558; GSE4581, n = 413) were analyzed. A seven-gene signature (ATIC, CDKN1A, DNAJB9, EDEM1, GABARAPL1, RAB1A, VAMP7) was identified using LASSO-Cox regression. Predictive performance of the autophagy-related model was assessed via Kaplan-Meier analysis, ROC curves, and nomograms. Immune infiltration, drug sensitivity, and functional pathways of the autophagy-related model were evaluated using CIBERSORT, ESTIMATE, and GSEA. The gene expression in the autophagy prognostic model was verified by qRT-PCR in the U266 and RPMI8226 cell lines and blood samples of multiple myeloma patients from the First Affiliated Hospital of Wenzhou Medical University.
Results: The autophagy-related risk score stratified patients into high-risk and low-risk groups with distinct survival outcomes (high-risk HR = 0.391, 95%CI:0.284-0.540, p < 0.001). The model demonstrated robust predictive accuracy (5-year AUC = 0.729) and was independently validated. High-risk patients exhibited elevated immune checkpoint expression (CD48, CD70, BTLA), stromal infiltration, and drug resistance. Functional enrichment linked high-risk profiles to MYC activation and oxidative phosphorylation. Through qRT-PCR, the accuracy of the autophagy-related model has been verified in the U266 and RPMI8226 cell lines, as well as in the blood samples of multiple myeloma patients from the First Affiliated Hospital of Wenzhou Medical University.
Conclusion: This autophagy-related gene signature provides a reliable prognostic tool for MM, highlighting immune dysregulation and therapeutic resistance mechanisms. Its integration with clinical parameters enhances risk stratification and treatment planning.
期刊介绍：
Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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