Wang Yaping, Ma Xiaopeng, Li Huimin, Zhao Ji'ou, Kang Meiyun, Rong Liucheng, Xue Yao, Wang Jiali, Tang Junwei, Fang Yongjun
Department of Hematology and Oncology, Children's Hospital of Nanjing Medical University, Nanjing Medical University, 72# Guangzhou Road, Nanjing, Jiangsu Province, China.
Department of General Surgery, Colorectal Institute of Nanjing Medical University, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, 210029, China.
Heliyon. 2024 Dec 10;10(24):e41102. doi: 10.1016/j.heliyon.2024.e41102. eCollection 2024 Dec 30.
Pediatric Acute Lymphoblastic Leukemia (ALL) is the most common malignant tumor of the hematological system in children, and its relapse after treatment has consistently been a significant factor hindering prognosis. This study aimed to develop a blood-based non-invasive method for predicting relapse in children with ALL. Two cohorts of pediatric ALL patients were analyzed. Through high-throughput profiling, three miRNAs and three circRNAs were identified as potential biological markers, exhibiting a gradient increase in expression from healthy controls to the relapsed group. Logistic regression analysis revealed the superior predictive ability of the combined non-coding RNA panel compared to individual groups. A nomogram incorporating the non-coding RNA panel and other clinical risk features was developed. Combining the non-coding RNA panel with relevant risk features could enhance predictive accuracy. The non-coding RNA panel remained an independent predictor of relapse in the validation cohort, and its combination with clinical features formed a superior risk stratification model. In conclusion, this blood-based non-invasive method holds promise for predicting relapse in pediatric ALL patients at the time of initial diagnosis. The non-coding RNA panel, along with clinical risk features, may significantly impact patient care and outcomes.
小儿急性淋巴细胞白血病(ALL)是儿童最常见的血液系统恶性肿瘤,其治疗后的复发一直是阻碍预后的重要因素。本研究旨在开发一种基于血液的非侵入性方法来预测ALL患儿的复发情况。对两组小儿ALL患者进行了分析。通过高通量分析,鉴定出三种miRNA和三种circRNA作为潜在的生物标志物,其表达从健康对照到复发组呈梯度增加。逻辑回归分析显示,与单个组相比,联合非编码RNA面板具有更好的预测能力。开发了一个包含非编码RNA面板和其他临床风险特征的列线图。将非编码RNA面板与相关风险特征相结合可以提高预测准确性。在验证队列中,非编码RNA面板仍然是复发的独立预测因子,并且其与临床特征的组合形成了一个更好的风险分层模型。总之,这种基于血液的非侵入性方法有望在小儿ALL患者初诊时预测复发情况。非编码RNA面板以及临床风险特征可能会对患者护理和预后产生重大影响。