基于 WGCNA 鉴定费城阴性急性淋巴细胞白血病中与 anoikis 相关的亚型、预后意义和免疫微环境特征

Na Li, Yang Hong, Ling Zhang, Aining Sun
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摘要

费城染色体阴性 B 细胞急性淋巴细胞白血病(ph-neg B-ALL)的临床结果和发病率在不同年龄段有很大差异,从而影响了预后。尽管近年来诊断和治疗技术不断进步,但不同年龄段ph阴性B细胞急性淋巴细胞白血病的详细预后仍有待阐明。在这项研究中,我们获得了在本中心确诊的80名ph阴性B-ALL患者的临床数据。利用他们最初的骨髓抽吸样本进行了核糖核酸测序。通过对 408 个嗜酸相关基因(ARGs)进行加权基因共表达网络分析(WGCNA),确定了四个不同的模块,并随后通过生物信息学进行了分析。WGCNA 发现了 ARGs 之间不同的共表达模块。具体来说,绿松石模块中的ARGs可能会评估与新诊断的ph-neg B-ALL相关的风险。此外,该研究还揭示了免疫微环境和基因组变异的显著异质性,凸显了该疾病内部的显著异质性。从80名ph-neg B-ALL患者的RNA测序数据中筛选出408个ARGs,并通过WGCNA算法构建了4个不同的共表达模块;其中绿松石模块中的ARGs最多,可用于将新发ph-neg B-ALL患者划分为不同的风险组(高危组和低危组);ph-neg B-ALL患者可分为PS-1和PS-2,PS-1和PS-2之间存在基因组异质性;PS-1和PS-2之间存在免疫浸润差异。总之,我们的研究对于探索噬菌体阴性 B-ALL 中与厌氧相关的分子通路和机制,以及促进该疾病的治疗和预后工具的开发具有重要价值。
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WGCNA-based identification of anoikis-related subtypes, prognostic significance, and characterisation of the immune microenvironment in Philadelphia-negative acute lymphoblastic leukaemia
The clinical outcomes and incidence of Philadelphia chromosome-negative B cell acute lymphoblastic leukaemia (ph-neg B-ALL) vary significantly across different age groups, influencing the prognosis. Despite recent advancements in diagnostic and therapeutic techniques, the detailed prognosis for ph-negative B-ALL across age demographics remains to be elucidated. In this study, clinical data were obtained from 80 patients with ph-neg B-ALL who were diagnosed at our centre. Ribonucleic acid sequencing was performed using their initial bone marrow aspirate samples. By employing weighted gene co-expression network analysis (WGCNA) on 408 anoikis-related genes (ARGs), four different modules were identified and subsequently analysed through bioinformatics. The WGCNA revealed distinct co-expression modules among ARGs. Specifically, the ARGs in the turquoise module might assess the risk associated with newly diagnosed ph-neg B-ALL. Additionally, the study revealed significant heterogeneity in the immune microenvironment and genome variance, highlighting the notable heterogeneity within the disease. 408 ARGs were screened out and four different co-expression modules were constructed by WGCNA algorithms from the RNA-sequencing data of 80 ph-neg B-ALL patients; The ARGs in the turquoise module were the most, and it can be used to divide the de novo ph-neg B-ALL patients to different risk groups(high-risk and low-risk); The ph-neg B-ALL patients can be divided into PS-1 and PS-2, there is heterogeneity of genomes between PS-1 and PS-2; Immune infiltration difference exists in between PS-1 and PS-2. In conclusion, our study holds significant value in exploring the molecular pathways and mechanisms associated with anoikis implicated in ph-neg B-ALL, and in facilitating the development of treatments and prognostic tools for this disease
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