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中华细胞与干细胞杂志(电子版)

中华细胞与干细胞杂志(电子版) ›› 2024, Vol. 14 ›› Issue (04) : 204 -211. doi: 10.3877/cma.j.issn.2095-1221.2024.04.002

论著

AHNAK基因高表达与老年急性髓系白血病患者预后不良相关
杜鑫1, 刘霞霞2, 张恬波1, 张夏林3, 杨林花4, 张睿娟1,†()   
  1. 1. 030032　太原，山西医科大学第三医院　（山西白求恩医院　山西医学科学院　同济山西医院）血液内科
    2. 041000　临汾，山西省临汾市中心医院血液内科
    3. 030032　太原，山西白求恩医院　（山西医学科学院　同济山西医院），山西医科大学第三医院血液内科
    4. 030001　太原，山西医科大学第二医院血液内科
  • 收稿日期:2024-02-12 出版日期:2024-08-01
  • 通信作者: 张睿娟
  • 基金资助:
    山西白求恩人才引进基金(2021RC017)

The association between high AHNAK gene expression and poor prognosis in elderly AML patients

Xin Du1, XiaXia Liu2, Tianbo Zhang1, Xialin Zhang3, Linhua Yang4, Ruijuan Zhang1,†()   

  1. 1. Department of Hematology, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan 030032, China
    2. Department of Hematology, Linfen Central Hospital, Linfen 041000, China
    3. Department of Hematology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan 030032, China
    4. Department of Hematology, Second Hospital of Shanxi Medical University, Taiyuan 030001, China
  • Received:2024-02-12 Published:2024-08-01
  • Corresponding author: Ruijuan Zhang
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引用本文：

杜鑫, 刘霞霞, 张恬波, 张夏林, 杨林花, 张睿娟. AHNAK基因高表达与老年急性髓系白血病患者预后不良相关[J]. 中华细胞与干细胞杂志(电子版), 2024, 14(04): 204-211.

Xin Du, XiaXia Liu, Tianbo Zhang, Xialin Zhang, Linhua Yang, Ruijuan Zhang. The association between high AHNAK gene expression and poor prognosis in elderly AML patients[J]. Chinese Journal of Cell and Stem Cell(Electronic Edition), 2024, 14(04): 204-211.

目的

基于单细胞RNA测序（scRNA-seq）筛选老年急性髓系白血病（AML）造血干细胞（HSCs）中的关键基因，分析其对预后的影响。

方法

对3例初诊老年AML患者骨髓细胞进行scRNA-seq，采用统一流形逼近与投影（UMAP）算法聚类确定骨髓细胞类型。进一步根据拷贝数变异（CNV）分析、干性分析、拟时序分析、差异表达基因分析和富集分析揭示HSCs亚群的特点，筛选差异表达基因。通过癌症基因组图谱计划（TCGA）数据库/基因型-组织表达（GTEx）数据库以及实时荧光定量聚合酶链反应（RT-qPCR）对收集的老年AML患者、年轻AML患者和健康人骨髓样本检测，对筛选出的关键基因表达进行验证。采用单因素方差分析和Dunnett-t检验进行比较，生存分析用Log-rank检验。

结果

3例老年AML患者的骨髓细胞UMAP聚类分为11类细胞，其中HSCs比例差异较大；重新UMAP聚类HSCs，得到5个HSCs亚群。HSCs_2和4在细胞命运2 （Fate2）分支，CNV评分较高，且富集通路类似，因此归为一组，HSCs_1、3和5归为另一组；差异表达基因分析结果显示肺腺癌转移相关转录本1 （MALAT1）、AHNAK核蛋白（AHNAK）、Dmx like蛋白2 （DMXL2）和磷脂转运ATP酶8B4 （ATP8B4）基因差异显著。TCGA数据库/GTEx数据库分析结果显示，与健康人比较，MALAT1、AHNAK和ATP8B4基因在AML患者中高表达（P < 0.05），DMXL2基因表达在AML患者和健康人中比较差异无统计学意义。RT-qPCR结果显示AHNAK和ATP8B4 mRNA水平在老年AML患者中高于年轻AML患者和健康人（P < 0.05）[AHNAK mRNA：（0.74 ± 0.14）比（4.28 ± 1.06），（1.05 ± 0.11）比（4.28 ± 1.06），ATP8B4 mRNA：（0.03 ± 0.01）比（0.64 ± 0.14），（0.07 ± 0.02）比（0.64 ± 0.14）]。MALAT1 mRNA水平在老年AML患者中高于年轻AML患者[（0.45 ± 0.16）比（1.27 ±0.23）]（P < 0.05），但与健康人的差异无统计学意义。DMXL2 mRNA水平在老年AML患者中与年轻AML患者、健康人比较差异无统计学意义。生存分析显示AHNAK基因高表达与老年AML患者生存负相关。

结论

AHNAK基因在老年AML患者HSCs中高表达，且与预后不良相关。

关键词: 急性髓系白血病, 老年, 造血干细胞, 单细胞RNA测序, 预后
Objective

To screen the key genes in hematopoietic stem cells (HSCs) from elderly acute myeloid leukemia (AML) patients using single-cell RNA sequencing (scRNA-seq) and analyze their prognostic impact.

Methods

Bone marrow cells from three newly diagnosed elderly AML patients were subjected to scRNA-seq. Cell types were classified by uniform manifold approximation and projection (UMAP) clustering algorithm. Copy number variation (CNV) analysis, stemness analysis, pseudotime analysis, differential gene expression analysis, and enrichment analysis was used to identify characteristic genes of HSCs subgroups. The expression of selected key genes was validated using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, as well as real-time quantitative polymerase chain reaction (RT-qPCR) on collected bone marrow samples from elderly AML patients, young AML patients, and healthy individuals.Univariate ANOVA and Dunnett-t test were used for comparison the differences among groups. Survival analysis was analysed by Log-rank test.

Results

Eleven cell types were identified in three elderly AML patients, with significant differences in the proportion of HSCs. Five subsets of HSCs were identified after reclustering. HSCs_2 and HSCs_4 showed higher CNV scores and similar enrichment pathways, which were in the branch of cell fate 2 (Fate2), thus being grouped into a separate category from subsets HSCs_1, HSCs_3, and HSCs_5. Differential expression gene analysis highlighted that metastasis associated in lung denocarcinoma transcript 1 (MALAT1), AHNAK nucleoprotein (AHNAK), Dmx like 2 (DMXL2) and ATPase phospholipid transporting 8B4 (ATP8B4) genes were significantly differentially expressed. Analysis of TCGA and GTEx databases confirmed high expression levels of MALAT1, AHNAK, and ATP8B4 genes in AML patients, which significantly different from healthy individuals (P < 0.05), but without significant difference in the expression of DMXL2. RT-qPCR results showed that AHNAK and ATP8B4 mRNA expressions were significantly higher in elderly AML patients compared to young AML patients and healthy individuals [AHNAK mRNA: (0.74 ± 0.14) vs (4.28 ± 1.06), (1.05 ± 0.1) vs (4.28 ± 1.06), ATP8B4 mRNA: (0.03 ± 0.01) vs (0.64 ±0.14), (0.07 ± 0.02) vs (0.64 ± 0.14) ] (P < 0.05), while MALAT1 mRNA levels in elderly AML patients were significantly higher compared to young AML patients [ (0.45 ± 0.16) vs (1.27 ±0.23) ] (P < 0.05), but no significant difference compared to healthy individuals. No significant difference was observed in the expression of DMXL2 mRNA. Survival analysis showed that elderly AML patients with high AHNAK expression had poor prognosis.

Conclusions

AHNAK was highly expressed in HSCs of elderly AML patients and was associated with poor prognosis.

Key words: Acute myeloid leukemia, Elderly, Hematopoietic stem cells, Single-cell RNA sequencing, Prognosis
表1 3例老年AML患者临床特点
患者 年龄（岁） 性别 骨髓原始细胞比例（%） 患者状况 染色体核型 基因突变
1 67 男 33 初诊 46, XY, del （20） （q4） [3] / 46, XY[7] FLT3-ITDlow/NPM1
2 62 男 50 初诊 46, XY[20] CEBPAdm/GATA2
3 61 女 22.5 初诊 45, X, -X[1] IDH2 /NPM1
表2 基因MALAT1、AHNAK、DMXL2和ATP8B4的引物序列
基因名称 引物序列（5'→3'） 预期扩增长度（bp）
MALAT1 上游AAAGCAAGGTCTCCCCACAAG 71
  下游GGTCTGTGCTAGATCAAAAGGCA  
AHNAK 上游TGCCTGAGATTGCTACTGGTG 136
  下游CCTTTCAGTTTAGGAGACCCAAG  
DMXL2 上游TGGAGGAGTATCAGAATTGGCT 109
  下游GCAGTATGTGCCTAGACAGTAAC  
ATP8B4 上游ATAATCGGCAGTCTGAAGTGC 140
  下游TGGCTCACTACTTGATAGGAGAA  
β-actin 上游CATGTACGTTGCTATCCAGGC 250
  下游CTCCTTAATGTCACGCACGAT  
图1 3例老年AML患者骨髓细胞scRNA-seq分析注：a图为3例老年AML患者骨髓细胞UMAP聚类分布情况，不同颜色代表不同的细胞类型；b图为热图展示各类型细胞的特异性高表达基因；c图为3例老年AML患者骨髓中不同细胞占比
图2 老年AML患者骨髓HSCs scRNA-seq分析注：a图为3例老年AML患者骨髓HSCs UMAP聚类分布情况，不同颜色代表不同HSCs亚群；b图为HSCs亚群CNV分析；c图为HSCs亚群干性分析；d、e图为HSCs拟时序分析，颜色越深代表衍化轨迹起点；HSCs各亚群拟时序分析，不同颜色代表不同的亚群细胞分化轨迹；f图为HSCs亚群RNA速率，不同颜色代表不同的HSCs亚群，箭头代表细胞分化方向；g图为HSCs亚群GSVA富集分析
图3 HSCs亚群差异基因表达分析注：a图为火山图展示HSCs _2、4和HSCs_1、3、5的差异基因表达，红点代表上调基因，蓝点代表下调基因；b图为差异表达基因KEGG富集通路
图4 差异表达基因MALAT1、AHNAK、DMXL2和ATP8B4的临床验证注：a~d为TCGA/GTEx数据库分析MALAT1、AHNAK、ATP8B4和DMXL2基因在AML患者和健康人中的表达，*为P<0.05，ns为P>0.05
图5 AHNAK基因在老年AML患者中的生存分析
表3 MALAT1、AHNAK、DMXL2和ATP8B4基因表达量（ ± s）
基因 例数 MALAT1 AHNAK DMXL2 ATP8B4
老年AML组 20 1.27 ± 0.23 4.28 ± 1.06 0.58 ± 0.07 0.64 ± 0.14
年轻AML组 20 0.45 ± 0.16a 0.74 ± 0.14a 1.37 ± 0.52 0.03 ± 0.01a
健康对照组 20 1.04 ± 0.10 1.05 ± 0.11a 1.05 ± 0.12 0.07 ± 0.02a
F值   3.310 5.500 0.933 7.007
P值   0.060 0.020 0.415 0.010
1
Dinardo CD, Erba HP, Freeman SD, et al. Acute myeloid leukaemia[J]. Lancet, 2023, 401(10393):2073-2086.
2
Hokland P, Fernández, Ii, Freeman SD, et al. AML in the elderly-A global view[J]. Br J Haematol, 2023, 203(5):760-773.
3
Wang BH, Guan W, Lv N, et al. Genetic features and efficacy of decitabine-based chemotherapy in elderly patients with acute myeloid leukemia[J]. Hematology, 2021, 26(1):371-379.
4
Stetson LC, Balasubramanian D, Ribeiro SP, et al. Single cell RNA sequencing of AML initiating cells reveals RNA-based evolution during disease progression[J]. Leukemia, 2021, 35(10):2799-2812.
5
Chen DW, Fan JM, Schrey JM, et al. Inflammatory recruitment of healthy hematopoietic stem and progenitor cells in the acute myeloid leukemia niche[J]. Leukemia, 2024, 38(4):741-750.
6
Zhang ZY, Deng C, Zhu P, et al. Single-cell RNA-seq reveals a microenvironment and an exhaustion state of T/NK cells in acute myeloid leukemia[J]. Cancer Sci, 2023, 114(10):3873-3883.
7
Arber D, Orazi A, Hasserjian R, et al. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia[J]. Blood, 2016, 127(20):2391-2405.
8
Isobe T, Kucinski I, Barile M, et al. Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes[J]. Cell Genom, 2023, 3(12):100426. doi: 10.1016/j.xgen.2023.100426.
9
Moore JA, Mistry JJ, Hellmich C, et al. LC3-associated phagocytosis in bone marrow macrophages suppresses acute myeloid leukemia progression through STING activation[J]. J Clin Invest, 2022, 132(5):e153157. doi: 10.1172/JCI153157.
10
Chan CP, Kok KH, Jin DY. Human T-Cell leukemia virus type 1 infection and adult T-cell leukemia[J]. Adv Exp Med Biol, 2017, 1018:147-166.
11
Barbier V, Erbani J, Fiveash C, et al. Endothelial E-selectin inhibition improves acute myeloid leukaemia therapy by disrupting vascular niche-mediated chemoresistance[J]. Nat Commun, 2020, 11(1):2042. doi: 10.1038/s41467-020-15817-5.
12
Chen X, Zhu H, Qiao C, et al. Next-generation sequencing reveals gene mutations landscape and clonal evolution in patients with acute myeloid leukemia[J]. Hematology, 2021, 26(1):111-122.
13
Song MZ, Zhang T, Yang DD, et al. Chromosomal aberrations and prognostic analysis of secondary acute myeloid leukemia-a retrospective study[J]. PeerJ, 2023, 11:e15333. doi: 10.7717/peerj.15333.
14
Pastore F, Pastore A, Rothenberg-Thurley M, et al. Molecular profiling of patients with cytogenetically normal acute myeloid leukemia and hyperleukocytosis[J]. Cancer, 2022, 128(24):4213-4222.
15
Cheng PL, Hsiao TH, Chen CH, et al. Chemoresistance in acute myeloid leukemia:an alternative single-cell RNA sequencing approach[J]. Hematol Oncol, 2023, 41(3):499-509.
16
Zeng AGX, Bansal S, Jin LQ, et al. A cellular hierarchy framework for understanding heterogeneity and predicting drug response in acute myeloid leukemia[J]. Nat Med, 2022, 28(6):1212-1223.
17
Kolodziejczyk AA, Kim JK, Svensson V, et al. The technology and biology of single-cell RNA sequencing[J]. Mol Cell, 2015, 58(4):610-620.
18
Su YJ, Zhang XQ, Liang YC, et al. Integrated analysis of single-cell RNA-seq and bulk RNA-seq to unravel the molecular mechanisms underlying the immune microenvironment in the development of intestinal-type gastric cancer[J]. Biochim Biophys Acta Mol Basis Dis, 2024, 1870(1):166849. doi: 10.1016/j.bbadis.2023.166849.
19
Goyal B, Yadav SRM, Awasthee N, et al. Diagnostic, prognostic, and therapeutic significance of long non-coding RNA MALAT1 in cancer[J]. Biochim Biophys Acta Rev Cancer, 2021, 1875(2):188502. doi: 10.1016/j.bbcan.2021.188502.
20
Sheng XF, Hong LL, Li H, et al. Long non-coding RNA MALAT1 modulate cell migration, proliferation and apoptosis by sponging microRNA-146a to regulate CXCR4 expression in acute myeloid leukemia[J]. Hematology, 2021, 26(1):43-52.
21
Ni IB, Ching NC, Meng CK, et al. Translocation t(11;14) (q13;q32) and genomic imbalances in multi-ethnic multiple myeloma patients: a Malaysian study[J]. Hematol Rep, 2012, 4(3):e19. doi: 10.4081/hr.2012.e19.
22
Zhang SS, Cai ZG, Li H. AHNAKs roles in physiology and malignant tumors[J]. Front Oncol, 2023, 13:1258951. doi: 10.3389/fonc.2023.1258951.
23
Xu M, Wen JL, Xu QD, et al. AHNAK2 promotes the progression of differentiated thyroid cancer through PI3K/AKT signaling pathway[J]. Curr Cancer Drug Targets, 2024, 24(2):220-229.
24
Lee IH, Sohn M, Lim HJ, et al. Ahnak functions as a tumor suppressor via modulation of TGFβ/Smad signaling pathway[J]. Oncogene, 2014, 33(38):4675-4684.
25
Sohn M, Shin S, Yoo JY, et al. Ahnak promotes tumor metastasis through transforming growth factor-β-mediated epithelial-mesenchymal transition[J]. Sci Rep, 2018, 8(1):14379. doi: 10.1038/s41598-018-32796-2.
26
Dumitru CA, Bankfalvi A, Gu X, et al. AHNAK and inflammatory markers predict poor survival in laryngeal carcinoma[J]. PLoS One, 2013, 8(2):e56420. doi: 10.1371/journal.pone.0056420.
27
Xie ZY, Lun Y, Li X, et al. Bioinformatics analysis of the clinical value and potential mechanisms of AHNAK2 in papillary thyroid carcinoma[J]. Aging, 2020, 12(18):18163-18180.
28
Leong S, Nunez AC, Lin MZ, et al. iTRAQ-based proteomic profiling of breast cancer cell response to doxorubicin and TRAIL[J]. J Proteome Res, 2012, 11(7):3561-3572.
29
Guo RQ, Lü MD, Cao FJ, et al. Single-cell map of diverse immune phenotypes in the acute myeloid leukemia microenvironment[J]. Biomark Res, 2021, 9(1):15. doi: 10.1186/s40364-021-00265-0.
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