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Table 2 Association of age with molecular genetic alterations

From: Next-generation sequencing-based genetic landscape and its clinical implications for Chinese acute myeloid leukemia patients

 

Total (n = 179)

Younger patients (n = 111)

Older patients (n = 68)

p value

Mutation number (mean)

2.08

1.83

2.50

0.003

CEBPA

32 (17.9)

22 (19.8)

10 (14.7)

0.428

TET2

30 (16.8)

15 (13.5)

15 (22.1)

0.153

ASXL1

25 (14.0)

10 (9.0)

15 (22.1)

0.025

NRAS

21 (11.7)

17 (15.3)

4 (5.9)

0.092

NPM1

20 (11.2)

12 (10.8)

8 (11.8)

1

IDH2

18 (10.1)

10 (9.0)

8 (11.8)

0.768

FLT3ITD

18 (10.1)

12 (10.8)

6 (8.8)

0.800

DNMT3A

16 (8.9)

6 (5.4)

10 (14.7)

0.056

KIT

14 (7.8)

12 (10.8)

2 (2.9)

0.083

TP53

13 (7.3)

4 (3.6)

9 (13.2)

0.034

RUNX1

13 (7.3)

5 (4.5)

8 (11.8)

0.081

IDH1

12 (6.7)

5 (4.5)

7 (10.3)

0.216

WT1

9 (5.0)

7 (6.3)

2 (2.9)

0.486

GATA2

5 (2.8)

2 (1.8)

3 (4.4)

0.370

FLT3TKD

5 (2.8)

3 (2.7)

2 (2.9)

1

KRAS

4 (2.2)

3 (2.7)

1 (1.5)

1

DNA methylation

63 (35.2)

30 (27.0)

33 (48.5)

0.004

RNA splicing

37 (20.7)

16 (14.4)

21 (30.9)

0.013

Chromatin architecture

32 (17.9)

12 (10.8)

20 (29.4)

0.002

Transcriptional deregulation

50 (27.9)

31 (27.9)

19 (27.9)

1

Activated signaling

55 (30.7)

42 (37.8)

13 (19.1)

0.012