MicroRNA Expression Profiling by Bead Array Technology in Human Tumor Cell Lines Treated with Interferon-Alpha-2a

互联网2013-09-06

1878

364

−32.1undefined*~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~013~E112~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0358~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0−35.6undefined*~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~012~E201~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0315~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0−37.7undefined*~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~012~E355~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0355~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0−33.8undefined*~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0Hybdridization_controls~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0array~Shyb~Scon4~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~06~E404~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~07~E110~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~00.11~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~07~E724~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~06~E684~K~Hp~M~2~1~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0−0.16

7,031

6,739

−0.04

6,964

6,746

−0.03

array_hyb_con3

6,923

7,681

0.11

7,833

7,368

−0.06

7,422

7,054

−0.05

6,906

7,365

0.07

array_hyb_con1

10,779

11,868

0.10

11,812

11,728

−0.0.01

11,436

11,382

0.00

11,059

11,522

0.04

array_hyb_con2

10,258

11,145

0.09

11,382

10,829

−0.05

11,075

10,650

−0.04

9,997

10,283

0.03

List of calculated relative fluorescent levels (without background correction) and calculated differences (CHF) between hepatoma (HuH7) and melanoma (ME-15) cells. A linear model with ME-15 and HuH7 as separate factors was used to estimate cell line differences in microRNA expression. The genes with the highest significance (and log factor change >0.5) are listed in the upper section and the bottom shows data for the hybridization controls as reference. Change factors show the cell line differences of the retransformed mean to the linear scale. p values (limma t test) were adjusted by false discovery rate correction. Significance codes are defined by the intervals: ‘**’ < 0.001 ≤ ‘*’ < 0.01 ≤ ‘’ < 0.05

Table 2 Modulation of microRNA expression by IFNα―4 and 24 h after stimulation

Control

Interferon-alpha treated

4 h

24 h

4 h

24 h

ME-15

HuH7

CHF

ME-15

HuH7

CHF

ME-15

HuH7

CHF

ME-15

HuH7

CHF

Validated microRNAs

hsa-miR-19a

13,617

6,726

−1.02

18,318

17,178

−0.07

19,226

17,409

−0.10

14,425

14,079

−0.02

hsa-miR-19b

13,365

9,406

−0.42

25,463

22,438

−0.13

21,532

20,625

−0.04

18,039

17,440

−0.03

hsa-miR-30e-5p

9,497

6,838

−0.39

13,045

11,321

−0.15

12,643

10,887

−0.16

13,230

11,809

−0.12

hsa-let-7a

15,244

4,335

−2.52.

28,304

6,181

−3.58 ***

22,226

6,386

−2.4undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~030~E449~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E612~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−4.4undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~Flet~F7b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~08~E236~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0539~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−14.2undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E563~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0475~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−25.4undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E150~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0500~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−23.30 ***

12,309

452

−26.2undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F203~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0907~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0325~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−1.7undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E155~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0348~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02.3undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E302~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0359~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−2.6undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E186~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E757~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−1.0undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F130b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E700~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~08~E316~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.46

13,023

13,880

0.07

9,994

14,055

0.41

12,053

12,432

0.03

hsa-miR-455

2,677

2,604

−0.03

3,944

5,285

0.3undefined

3,437

5,927

0.7undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E262~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E342~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.6undefined

ME-15

HuH7

4 h

24 h

4 h

24 h

−IFNa

+IFNa

CHF

−IFNa

+IFNa

CHF

−IFNa

+IFNa

CHF

−IFNa

+IFNa

CHF

Interferon-regulated microRNAs

hsa-miR-33b

1,226

3,484

1.8undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E888~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E318~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.25

476

1,113

1.3undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E306~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E851~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.4undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F33~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E631~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~07~E352~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01.79~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~09~E774~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E764~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.7undefined

1,887

6,645

2.52.

8,893

2,726

−2.26

hsa-miR-12undefined

2,221

5,409

1.4undefined

5,578

6,111

0.10

4,749

6,410

0.35.

5,687

5,803

0.0undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F10b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E695~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E564~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01.1undefined

2,929

4,297

0.4undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0378~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0411~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.09~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0371~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0382~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.03~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F551b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E085~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~04~E169~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01.0undefined

4,423

3,419

−0.29

1,804

4,979

1.7undefined

5,221

4,865

−0.07

hsa-miR-137

1,037

1,966

0.90

2,523

2,872

0.14

1,613

3,155

0.9undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E429~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E598~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.05~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F138~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E158~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~04~E074~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.8undefined

4,709

3,701

−0.27

725

828

0.14

903

859

−0.05

hsa-miR-130b

5,700

9,994

0.75

13,023

12,053

−0.08

8,316

14,055

0.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~013~E880~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E432~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.12

hsa-miR-101

6,701

11,387

0.70

13,088

11,688

−0.12

3,569

10,871

2.0undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~010~E445~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~010~E796~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.03~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F140~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~07~E339~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E236~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.67~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~015~E512~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~015~E931~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.03~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E058~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E976~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.9undefined

6,135

7,221

0.18

HS_92

829

1,356

0.64.

1,246

1,179

−0.06

407

587

0.44

492

478

−0.03

hsa-miR-362

1,382

2,234

0.6undefined

2,144

2,276

0.06

1,907

2,737

0.4undefined

2,456

2,519

0.03

hsa-miR-19b

13,365

21,532

0.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~025~E463~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~018~E039~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.41

9,406

20,625

1.1undefined

22,438

17,440

−0.29

hsa-miR-130a

13,031

20,878

0.60.

27,571

23,048

−0.20

17,884

31,012

0.7undefined

33,801

28,875

−0.17

hsa-miR-579

552

816

0.48.

992

1,053

0.06

729

1,362

0.8undefined

1,250

1,308

0.05

hsa-miR-29b

23,138

34,148

0.48.

32,691

29,710

−0.10

8,737

17,989

1.0undefined

20,599

17,405

−0.18.

hsa-miR-19a

13,617

19,226

0.4undefined

18,318

14,425

−0.27

6,726

17,409

1.59.

17,178

14,079

−0.22.

hsa-miR-338

1,298

1,813

0.40.

1,870

1,603

−0.17

2,363

4,603

0.95.

5,109

4,088

-0.25

hsa-miR-590

1,403

1,949

0.39.

1,545

1,367

−0.13

669

1,068

0.60.

884

847

−0.04

hsa-miR-545

1,455

1,973

0.36.

2,149

1,720

−0.2undefined

829

1,371

0.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E573~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E393~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.13

hsa-miR-30e-5p

9,497

12,643

0.33

13,045

132,030

0.01

6,838

10,887

0.5undefined

11,321

11,809

0.04

hsa-miR-570

1,989

2,576

0.30.

2,397

2,610

0.09

2,213

3,739

0.6undefined

4,312

3,708

−0.16

hsa-miR-301

13,621

17,531

0.2undefined

16,321

15,142

−0.08

5,646

10,460

0.8undefined

10,925

10,295

−0.06.

hsa-miR-561

517

621

0.20

568

464

−0.2undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0683~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E157~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E149~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0941~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.22

HS_250

4,284

1,813

−1.36.

740

983

0.33

3,688

2,337

−0.58

1,195

1,303

0.09

ME-15

HuH7

4 h

24 h

4 h

24 h

−IFNa

+IFNa

CHF

−IFNa

+IFNa

CHF

−IFNa

+IFNa

CHF

−IFNa

+IFNa

CHF

Validated microRNAs

hsa-miR-19a

13,617

19,226

0.4undefined

18,318

14,425

−0.27

6,726

17,409

1.59.

17,178

14,079

−0.22

hsa-miR-19b

13,365

21,532

9,406

20,625

1.1undefined

22,438

17,440

−0.29.

hsa-miR-30e-5p

9,497

12,643

0.33

13,045

13,230

0.01

6,838

10,887

0.5undefined

11,321

11,809

0.04

hsa-let-7a

15,244

22,226

0.46

28,304

30,449

0.08

4,335

6,386

0.47.

6,181

5,612

−0.10

hsa-let-7b

8,236

12,150

0.4undefined

12,563

2,309

−0.02

539

500

−0.08

475

452

−0.05

hsa-miR-203

907

1,302

0.4undefined

1,155

1,186

0.03

325

359

0.10

348

575

0.66undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~K~Htbody~M~2~1~0~0~0~0~0~K~Htable~M~2~1~0~0~0~0~0~Kdiv~M~2~1~0~0~0~0~0~0~Kdiv~M~2~1~0~0~0~0~0~0~0~Kdiv~M~2~1~0~0~0~0~0~0~0~0Microarray_data_for_RT~FPCR_validated_microRNAs~E see description of Table 1. Average relative fluorescent levels and their change factors (CHFs) are shown for hepatoma (HuH7) and melanoma (ME-15) cells at two time points. Genes were selected by significance calculated in a linear model with interaction assuming that the change may not occur in both cell lines (e.g. miR-10b has no detectable levels in HuH7). p value significance codes: 0 ‘**’ 0.001 ‘*’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ‘ 1. Section c shows the microarray expression levels of microRNAs assayed by RT-PCR (treatment analysis)

Quantitative PCR and Data Processing

microRNA levels were measured using TaqMan® microRNA assays (Applied Biosystems) using the TaqMan® MicroRNA reverse transcription (RT) kit with TaqMan® 2× universal PCR master mix (No AmpErase® UNG) as recommended by the supplier. Ten nanograms of total RNA was used as input for amplification using the samples used for microarray analysis. Reversed transcriptase products were diluted 1:15 and measured on an ABI 7900HT fast real-time PCR system. Technical replicates were run on three different plates (one with 40 cycles and two with 50 cycles) and threshold for cycling time (CT) calculation was set for all probes to 0.2. For estimation of endogenous small RNA content, the nucleolar RNA RNU48 was used as control and reference.

Standard error (Δx ) was calculated by the average standard error of treated and untreated MNE for biological replicates.

Results and Discussion

The following technical aspects have to be considered for result interpretation. The dataset of the microRNA bead array assay is not directly comparable to gene expression arrays where in vitro translated transcripts are directly hybridized to the probes. Moreover Illumina’s bead array technology tends to have higher background fluorescence levels and lower change factor values than Genechips from Affymetrix. Background (average of negative control signals) and noise (standard deviation of negative probes from each sample) were 528 ± 60 and 229 ± 67, respectively. The density of all samples shows a bimodal distribution peaking around the background fluorescent levels and the robust levels (approximately 12,000). The curve is skewed to the right and peak density height is found in the ratio 4:1 considering all probes (data not shown). The distribution of probes detected in all samples (detection p value threshold at 0.01) has a plateau ranging from about 2,000 close to the detectors maximum capacity of 2^16 relative fluorescent units (12 ). As expected, the correlation of data coming from biological replicates r ² = 0.952 ± 0.028 (not normalized) and r ² = 0.956 ± 0.022 (after loess normalization and log-transformation) was lower than for technical replicates r ² > 0.97 (12 ). We preferred loess normalization to quantile normalization because the later was too aggressive for the given small probe numbers.

As a first step we wished to address the robustness of the microRNA array in probe detection by selecting microRNA genes that are detected under all experimental conditions with high statistical significance in all biological triplicates (detection p value < 0.01). In each set of triplicate samples (control, 4 h or 24 h, IFNα stimulation) we detect approximately 270 genes that fulfill the above criteria. This corresponds to roughly a third of microRNAs available for detection in the assay system. Furthermore, this result suggests indirectly that IFNα treatment does not induce global changes in microRNA gene expression, but it modulates rather the expression of individual genes.

Today it is well established that microRNA expression patterns are cell and tissue type specific, which is consistent with a role in cell differentiation and biological function (8 ). Thus we expected to detect genes with preferential expression in either hepatoma or melanoma cells as these cell lines are derived from different tumors. Indeed, when all experimental conditions and data points are included in the data analysis about 150 microRNAs genes show preferential expression in either HuH7 or ME-15 cells (Fig. 1). Table 1 shows the expression data for the most significant genes including change factors and significance score as reference. Among these differentially expressed genes there are three members of the let-7 family, which has properties of tumor suppressor genes (for review see (18 )). Therefore it is not surprising that the members of this well-known microRNA gene family are deregulated in the analyzed cancer cells too. Furthermore, the different developmental stage of our cancer cell lines is expected to have left a genomic fingerprint where some microRNA genes are expressed in one but not the other cell line (19 ). Consistent with this, expression of some microRNAs is strictly cell type specific and barely detectable in the other cell type (Fig. 2a), for example the liver-specific miR-122a and miR-192 (20 ).

Fig. 2 Cell line specific microRNA expression Volcano plot (a ) display demonstrates the multi-variant biological diversity of microRNA expression in ME-15 or HuH7 cells. The estimated fold-change value (change factor) is plotted on the X -axis against the p value (limma t statistics) in logarithmic scale on the Y -axis. A linear model, using the expression values of untreated ME-15 cells at 4 h as base together with three parameters to estimate differences in time, treatment, or cell line. The top ranked and qPCR measured microRNAs are annotated. b Quantitative PCR validation of microarray data using eight selected microRNAs. Input total RNA came from independent cell cultures. Data are shown as relative cycling times (ΔCT) calculated with endogenous control RNU18 for ME-15 (color-filled bars ) and HuH7 (gray ). Error bars represent ΔCT ± Δx (standard deviation of biological replicates). ΔΔCT are noted above the bars together with the significance codes for t statistics (0 ‘**’, 0.001 ‘*’, 0.01 ‘’, 0.05 ‘.’, and 0.1 ‘‘ 1).

Bead-array-based microRNA detection technology, including the bio-statistic analysis, is currently not well established or widely used and we have applied a commercial PCR-based assay to confirm the array data for some microRNAs that cover different expression levels and change factors. In contrast to mRNA profiling, where RT-PCR-based assays are considered as gold standard for data validation, new generation deep sequencing is considered as the method of choice for microRNA quantification but is not available in our research institute. For the microRNAs let-7 a/b, miR-19 a/b, and miR-203, the PCR-based quantification method (Fig. 2b) confirmed the direction of change found with microarray technology (Table 2a). Expression of miR-130b and miR-455 was at similar levels in both assays. The correlation calculated for the eight tested microRNAs was acceptable: multiple r ² from f test of mean relative cycling times (ΔCT) to mean log2 microarray expression values was 0.9279. Differences of absolute levels between the microRNA targets probably results from different hybridization properties of the microarray probes and variation in the performance of Taqman primers for the specific microRNA on the other side.

Assuming that any IFNα relevant microRNA will have the same kinetics as the mRNA for PRGs, we looked at the regulation of microRNA genes in our experiment. These IRmiRs should respond to IFNα stimulation preferentially in both cell lines, because this would be a good indication of a general mechanism in the IFNα response. Within the 25 most significantly regulated genes (Table 2b), only one gene (HS_250) is downregulated. A general upregulation of transcripts is consistent with classic IFNα signaling seen for mRNAs. However, the maximal observed change factor with high significance was 1.84 (miR-33b in Table 2b) which is clearly lower than the values seen for protein coding mRNAs (2 ). We also included an expression analysis 24 h after IFNα stimulation in order to detect microRNA genes that show either delayed induction or remain activated at comparable levels to the 4 h stimulus. Based on our data set, the majority of the microRNA response genes show no further induction, but rather moderate downregulation 24 h after induction. This finding is not surprising as we expected immediate early impact of IFNα-mediated primary signaling.

We also measured the IFNα response in the same experiment and for the same microRNAs (Table 2c). When we analyze the IFNα effect at the early time point in both cell lines we find all the validated microRNAs to be upregulated (Fig. 3a). The magnitude of upregulation and the basal expression levels of the microRNA-19a and 19b are similar in both cell lines (Fig. 3b, top). This and the finding that miR-19 regulates SOCS1 (4 ) may be relevant for the regulation of cytokine signaling. let-7a and let-7b had higher levels in the melanoma-cell-line-derived samples compared HuH7, but the induction by IFNα in ME-15 could not be reproduced by RT-PCR (Fig. 3b, bottom). In both assays accurate fold changes are difficult to calculate, if the baseline expression level is close to background noise or the detection limit. An example of a gene at the detection limit is miR-203, which is not detectable without IFNα treatment in HuH7 cells (Table 2c). Upon IFNα stimulation (24 h in HuH7) the microRNA is detectable above background suggesting minimal induction. Consequently a solid change factor cannot be calculated, which is consistent with the high variance obtained by qPCR (ME-15). This result is in fact not surprising, because both technologies rely on logarithmic PCR amplification of microRNA templates. At low expression levels, both technologies show relatively high variation in biological replicates, which should be considered for data interpretation. Interestingly, miR-203 has a putative binding site for ISGF3 in the promoter region, which would enable IFNα-dependent upregulation. miR-30 has been reported to be IFNβ inducible, although the subclass measured was not specified by the authors (9 ). We decided to analyze the most promising candidate (miR-30e-5p) present in our microarray dataset (Fig. 3a in gray). Detection of miR-30e failed in ME-15 cells due to technical problems, but induction in HuH7 was similar to miR-19a/b.

Fig. 3 IFNα-dependent modulation of microRNA expression. a Volcano plot display of IFNα induced microRNA upregulation 4 h after induction. The change factor values (2^log factor change −1) are plotted on the X -axis against the p value in logarithmic scale on the Y -axis. Top-rated microRNAs are annotated together with the let-7 family members. b Confirmation of IFNα effect for selected microarray data by qPCR. The CT-values are the average of three technical and three biological replicates and changes were calculated with 2^ΔMNE (mean normalized expression values). Error bars show 2^ΔMNE ± Δx (average standard error of treated and untreated MNE) from biological triplicates. miR-30e failed to amplify in ME-15 and miR-203 was below the detection limit in HuH7. Expression values were normalized against endogenous snoRNA RNU48 levels.

Some technology-related questions remain open. The microRNA assay measures essentially the number of amplicons generated by RT-PCR for each transcript. Thus the signal is an indirect measurement of transcript abundance as compared to classical mRNA microarray platforms, where the target mRNA is directly labeled during linear amplification by in vitro transcription. As a consequence, change factor calculations for amplicon-based assays are ambiguous.

In summary, Illumina’s bead array technology is well suited for multi-parallel profiling of microRNAs expressed in different cell types or tissues. We were also able to detect IFNα-inducible microRNA genes although the changes observed were moderate and biological significance remains to be proven. Like most microarray-based detection technologies the technical variability among identical samples is low compared to biological variations of individual cell cultures. At this point it is important to note that variation among biological samples occurs and is independent of the parameters that are measured. Consistent with IFNα-dependent induction of mRNAs we find that virtually all modulated microRNA genes are upregulated. However, the IFNα-induced changes detected in our study are relatively small compared to the changes induced by IFNβ in HuH7 cells (9 ). Finally, it is noteworthy that IRmiRs have similar kinetic properties to their mRNA counterparts. miR-10b for instance is induced early in ME-15 and remains upregulated, while miR-19 abundance ceases after 24 h. In general, the majority of IRmiR genes were reset to basal levels after 24 h and further studies are needed for kinetic classification. Thus, our study adds another level of complexity to the dynamic regulation IFNα signaling and other mechanisms like epigenetic promoter methylation are currently under intense investigation in our laboratories.

Acknowledgements We thank Dr. Guido Steiner and Andreas Buness (F. Hoffmann-La Roche Ltd.) for their support in bioinformatics and statistics, Dr. Martin Ebeling (F. Hoffmann-La Roche Ltd.) for the comparative genomic evaluation of microRNA-targeted transcripts and Prof. Dr. Giulio Spagnoli (University Hospital Basel) for the gift of the ME-15 melanoma cell line. Finally, we are grateful to Heather Hinton (F. Hoffmann-La Roche Ltd.) for critical reading of the manuscript and to Dr. Laura Suter-Dick (F. Hoffmann-La Roche Ltd.) for sharing lab space and introduction into GCP sampling.

364

7,031

6,739

−0.04

6,964

6,746

−0.03

array_hyb_con3

6,923

7,681

0.11

7,833

7,368

−0.06

7,422

7,054

−0.05

6,906

7,365

0.07

array_hyb_con1

10,779

11,868

0.10

11,812

11,728

−0.0.01

11,436

11,382

0.00

11,059

11,522

0.04

array_hyb_con2

10,258

11,145

0.09

11,382

10,829

−0.05

11,075

10,650

−0.04

9,997

10,283

0.03

Table 2 Modulation of microRNA expression by IFNα―4 and 24 h after stimulation

	Control	Interferon-alpha treated
4 h	24 h	4 h					24 h
a	ME-15	HuH7	CHF	ME-15	HuH7	CHF	ME-15	HuH7	CHF	ME-15	HuH7	CHF
Validated microRNAs
hsa-miR-19a	13,617	6,726	−1.02	18,318	17,178	−0.07	19,226	17,409	−0.10	14,425	14,079	−0.02
hsa-miR-19b	13,365	9,406	−0.42	25,463	22,438	−0.13	21,532	20,625	−0.04	18,039	17,440	−0.03
hsa-miR-30e-5p	9,497	6,838	−0.39	13,045	11,321	−0.15	12,643	10,887	−0.16	13,230	11,809	−0.12
hsa-let-7a	15,244	4,335	−2.52.	28,304	6,181	−3.58 ***	22,226	6,386	−2.4undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~030~E449~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E612~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−4.4undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~Flet~F7b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~08~E236~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0539~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−14.2undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E563~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0475~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−25.4undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E150~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0500~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−23.30 ***	12,309	452	−26.2undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F203~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0907~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0325~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−1.7undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E155~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0348~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02.3undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E302~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0359~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−2.6undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E186~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E757~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−1.0undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F130b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E700~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~08~E316~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.46	13,023	13,880	0.07	9,994	14,055	0.41	12,053	12,432	0.03
hsa-miR-455	2,677	2,604	−0.03	3,944	5,285	0.3undefined	3,437	5,927	0.7undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E262~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E342~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.6undefined
b	ME-15	HuH7
4 h	24 h	4 h					24 h
−IFNa	+IFNa	CHF	−IFNa	+IFNa	CHF	−IFNa	+IFNa	CHF	−IFNa	+IFNa	CHF
Interferon-regulated microRNAs
hsa-miR-33b	1,226	3,484	1.8undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E888~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E318~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.25	476	1,113	1.3undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E306~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E851~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.4undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F33~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E631~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~07~E352~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01.79~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~09~E774~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E764~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.7undefined	1,887	6,645	2.52.	8,893	2,726	−2.26
hsa-miR-12undefined	2,221	5,409	1.4undefined	5,578	6,111	0.10	4,749	6,410	0.35.	5,687	5,803	0.0undefined*~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F10b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E695~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E564~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01.1undefined	2,929	4,297	0.4undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0378~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0411~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.09~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0371~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0382~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.03~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F551b~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E085~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~04~E169~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01.0undefined	4,423	3,419	−0.29	1,804	4,979	1.7undefined	5,221	4,865	−0.07
hsa-miR-137	1,037	1,966	0.90	2,523	2,872	0.14	1,613	3,155	0.9undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E429~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E598~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.05~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F138~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~02~E158~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~04~E074~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.8undefined	4,709	3,701	−0.27	725	828	0.14	903	859	−0.05
hsa-miR-130b	5,700	9,994	0.75	13,023	12,053	−0.08	8,316	14,055	0.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~013~E880~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E432~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.12
hsa-miR-101	6,701	11,387	0.70	13,088	11,688	−0.12	3,569	10,871	2.0undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~010~E445~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~010~E796~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.03~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~0~Ktr~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0hsa~FmiR~F140~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~07~E339~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~012~E236~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.67~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~015~E512~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~015~E931~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.03~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~03~E058~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~05~E976~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.9undefined	6,135	7,221	0.18
HS_92	829	1,356	0.64.	1,246	1,179	−0.06	407	587	0.44	492	478	−0.03
hsa-miR-362	1,382	2,234	0.6undefined	2,144	2,276	0.06	1,907	2,737	0.4undefined	2,456	2,519	0.03
hsa-miR-19b	13,365	21,532	0.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~025~E463~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~018~E039~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.41	9,406	20,625	1.1undefined	22,438	17,440	−0.29
hsa-miR-130a	13,031	20,878	0.60.	27,571	23,048	−0.20	17,884	31,012	0.7undefined	33,801	28,875	−0.17
hsa-miR-579	552	816	0.48.	992	1,053	0.06	729	1,362	0.8undefined	1,250	1,308	0.05
hsa-miR-29b	23,138	34,148	0.48.	32,691	29,710	−0.10	8,737	17,989	1.0undefined	20,599	17,405	−0.18.
hsa-miR-19a	13,617	19,226	0.4undefined	18,318	14,425	−0.27	6,726	17,409	1.59.	17,178	14,079	−0.22.
hsa-miR-338	1,298	1,813	0.40.	1,870	1,603	−0.17	2,363	4,603	0.95.	5,109	4,088	-0.25
hsa-miR-590	1,403	1,949	0.39.	1,545	1,367	−0.13	669	1,068	0.60.	884	847	−0.04
hsa-miR-545	1,455	1,973	0.36.	2,149	1,720	−0.2undefined	829	1,371	0.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E573~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E393~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.13
hsa-miR-30e-5p	9,497	12,643	0.33	13,045	132,030	0.01	6,838	10,887	0.5undefined	11,321	11,809	0.04
hsa-miR-570	1,989	2,576	0.30.	2,397	2,610	0.09	2,213	3,739	0.6undefined	4,312	3,708	−0.16
hsa-miR-301	13,621	17,531	0.2undefined	16,321	15,142	−0.08	5,646	10,460	0.8undefined	10,925	10,295	−0.06.
hsa-miR-561	517	621	0.20	568	464	−0.2undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0683~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E157~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~00.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~01~E149~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0941~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.22
HS_250	4,284	1,813	−1.36.	740	983	0.33	3,688	2,337	−0.58	1,195	1,303	0.09
c	ME-15	HuH7
4 h	24 h	4 h					24 h
−IFNa	+IFNa	CHF	−IFNa	+IFNa	CHF	−IFNa	+IFNa	CHF	−IFNa	+IFNa	CHF
Validated microRNAs
hsa-miR-19a	13,617	19,226	0.4undefined	18,318	14,425	−0.27	6,726	17,409	1.59.	17,178	14,079	−0.22
hsa-miR-19b	13,365	21,532	0.6undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~025~E463~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~018~E039~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~0~Ktd~M~2~1~0~0~0~0~0~0~0~0~0~Kp~M~2~1~0~0~0~0~0~0~0~0~0~0−0.41	9,406	20,625	1.1undefined	22,438	17,440	−0.29.
hsa-miR-30e-5p	9,497	12,643	0.33	13,045	13,230	0.01	6,838	10,887	0.5undefined	11,321	11,809	0.04
hsa-let-7a	15,244	22,226	0.46	28,304	30,449	0.08	4,335	6,386	0.47.	6,181	5,612	−0.10
hsa-let-7b	8,236	12,150	0.4undefined	12,563	2,309	−0.02	539	500	−0.08	475	452	−0.05
hsa-miR-203	907	1,302	0.4undefined	1,155	1,186	0.03	325	359	0.10	348	575	0.66undefined~K~Hp~M~2~1~0~0~0~0~0~0~0~0~K~Htd~M~2~1~0~0~0~0~0~0~0~K~Htr~M~2~1~0~0~0~0~0~0~K~Htbody~M~2~1~0~0~0~0~0~K~Htable~M~2~1~0~0~0~0~0~Kdiv~M~2~1~0~0~0~0~0~0~Kdiv~M~2~1~0~0~0~0~0~0~0~Kdiv~M~2~1~0~0~0~0~0~0~0~0Microarray_data_for_RT~FPCR_validated_microRNAs~E see description of Table 1. Average relative fluorescent levels and their change factors (CHFs) are shown for hepatoma (HuH7) and melanoma (ME-15) cells at two time points. Genes were selected by significance calculated in a linear model with interaction assuming that the change may not occur in both cell lines (e.g. miR-10b has no detectable levels in HuH7). p value significance codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ‘ 1. Section c shows the microarray expression levels of microRNAs assayed by RT-PCR (treatment analysis) Quantitative PCR and Data Processing microRNA levels were measured using TaqMan® microRNA assays (Applied Biosystems) using the TaqMan® MicroRNA reverse transcription (RT) kit with TaqMan® 2× universal PCR master mix (No AmpErase® UNG) as recommended by the supplier. Ten nanograms of total RNA was used as input for amplification using the samples used for microarray analysis. Reversed transcriptase products were diluted 1:15 and measured on an ABI 7900HT fast real-time PCR system. Technical replicates were run on three different plates (one with 40 cycles and two with 50 cycles) and threshold for cycling time (CT) calculation was set for all probes to 0.2. For estimation of endogenous small RNA content, the nucleolar RNA RNU48 was used as control and reference. Standard error (Δx ) was calculated by the average standard error of treated and untreated MNE for biological replicates. Results and Discussion The following technical aspects have to be considered for result interpretation. The dataset of the microRNA bead array assay is not directly comparable to gene expression arrays where in vitro translated transcripts are directly hybridized to the probes. Moreover Illumina’s bead array technology tends to have higher background fluorescence levels and lower change factor values than Genechips from Affymetrix. Background (average of negative control signals) and noise (standard deviation of negative probes from each sample) were 528 ± 60 and 229 ± 67, respectively. The density of all samples shows a bimodal distribution peaking around the background fluorescent levels and the robust levels (approximately 12,000). The curve is skewed to the right and peak density height is found in the ratio 4:1 considering all probes (data not shown). The distribution of probes detected in all samples (detection p value threshold at 0.01) has a plateau ranging from about 2,000 close to the detectors maximum capacity of 2^16 relative fluorescent units (12 ). As expected, the correlation of data coming from biological replicates r ² = 0.952 ± 0.028 (not normalized) and r ² = 0.956 ± 0.022 (after loess normalization and log-transformation) was lower than for technical replicates r ² > 0.97 (12 ). We preferred loess normalization to quantile normalization because the later was too aggressive for the given small probe numbers. As a first step we wished to address the robustness of the microRNA array in probe detection by selecting microRNA genes that are detected under all experimental conditions with high statistical significance in all biological triplicates (detection p value < 0.01). In each set of triplicate samples (control, 4 h or 24 h, IFNα stimulation) we detect approximately 270 genes that fulfill the above criteria. This corresponds to roughly a third of microRNAs available for detection in the assay system. Furthermore, this result suggests indirectly that IFNα treatment does not induce global changes in microRNA gene expression, but it modulates rather the expression of individual genes. Today it is well established that microRNA expression patterns are cell and tissue type specific, which is consistent with a role in cell differentiation and biological function (8 ). Thus we expected to detect genes with preferential expression in either hepatoma or melanoma cells as these cell lines are derived from different tumors. Indeed, when all experimental conditions and data points are included in the data analysis about 150 microRNAs genes show preferential expression in either HuH7 or ME-15 cells (Fig. 1). Table 1 shows the expression data for the most significant genes including change factors and significance score as reference. Among these differentially expressed genes there are three members of the let-7 family, which has properties of tumor suppressor genes (for review see (18 )). Therefore it is not surprising that the members of this well-known microRNA gene family are deregulated in the analyzed cancer cells too. Furthermore, the different developmental stage of our cancer cell lines is expected to have left a genomic fingerprint where some microRNA genes are expressed in one but not the other cell line (19 ). Consistent with this, expression of some microRNAs is strictly cell type specific and barely detectable in the other cell type (Fig. 2a), for example the liver-specific miR-122a and miR-192 (20 ). Fig. 2 Cell line specific microRNA expression Volcano plot (a ) display demonstrates the multi-variant biological diversity of microRNA expression in ME-15 or HuH7 cells. The estimated fold-change value (change factor) is plotted on the X -axis against the p value (limma t statistics) in logarithmic scale on the Y -axis. A linear model, using the expression values of untreated ME-15 cells at 4 h as base together with three parameters to estimate differences in time, treatment, or cell line. The top ranked and qPCR measured microRNAs are annotated. b Quantitative PCR validation of microarray data using eight selected microRNAs. Input total RNA came from independent cell cultures. Data are shown as relative cycling times (ΔCT) calculated with endogenous control RNU18 for ME-15 (color-filled bars ) and HuH7 (gray ). Error bars represent ΔCT ± Δx (standard deviation of biological replicates). ΔΔCT are noted above the bars together with the significance codes for t statistics (0 ‘*’, 0.001 ‘’, 0.01 ‘’, 0.05 ‘.’, and 0.1 ‘‘ 1). Bead-array-based microRNA detection technology, including the bio-statistic analysis, is currently not well established or widely used and we have applied a commercial PCR-based assay to confirm the array data for some microRNAs that cover different expression levels and change factors. In contrast to mRNA profiling, where RT-PCR-based assays are considered as gold standard for data validation, new generation deep sequencing is considered as the method of choice for microRNA quantification but is not available in our research institute. For the microRNAs let-7 a/b, miR-19 a/b, and miR-203, the PCR-based quantification method (Fig. 2b) confirmed the direction of change found with microarray technology (Table 2a). Expression of miR-130b and miR-455 was at similar levels in both assays. The correlation calculated for the eight tested microRNAs was acceptable: multiple r ² from f test of mean relative cycling times (ΔCT) to mean log2 microarray expression values was 0.9279. Differences of absolute levels between the microRNA targets probably results from different hybridization properties of the microarray probes and variation in the performance of Taqman primers for the specific microRNA on the other side. Assuming that any IFNα relevant microRNA will have the same kinetics as the mRNA for PRGs, we looked at the regulation of microRNA genes in our experiment. These IRmiRs should respond to IFNα stimulation preferentially in both cell lines, because this would be a good indication of a general mechanism in the IFNα response. Within the 25 most significantly regulated genes (Table 2b), only one gene (HS_250) is downregulated. A general upregulation of transcripts is consistent with classic IFNα signaling seen for mRNAs. However, the maximal observed change factor with high significance was 1.84 (miR-33b in Table 2b) which is clearly lower than the values seen for protein coding mRNAs (2 ). We also included an expression analysis 24 h after IFNα stimulation in order to detect microRNA genes that show either delayed induction or remain activated at comparable levels to the 4 h stimulus. Based on our data set, the majority of the microRNA response genes show no further induction, but rather moderate downregulation 24 h after induction. This finding is not surprising as we expected immediate early impact of IFNα-mediated primary signaling. We also measured the IFNα response in the same experiment and for the same microRNAs (Table 2c). When we analyze the IFNα effect at the early time point in both cell lines we find all the validated microRNAs to be upregulated (Fig. 3a). The magnitude of upregulation and the basal expression levels of the microRNA-19a and 19b are similar in both cell lines (Fig. 3b, top). This and the finding that miR-19 regulates SOCS1 (4 ) may be relevant for the regulation of cytokine signaling. let-7a and let-7b had higher levels in the melanoma-cell-line-derived samples compared HuH7, but the induction by IFNα in ME-15 could not be reproduced by RT-PCR (Fig. 3b, bottom). In both assays accurate fold changes are difficult to calculate, if the baseline expression level is close to background noise or the detection limit. An example of a gene at the detection limit is miR-203, which is not detectable without IFNα treatment in HuH7 cells (Table 2c). Upon IFNα stimulation (24 h in HuH7) the microRNA is detectable above background suggesting minimal induction. Consequently a solid change factor cannot be calculated, which is consistent with the high variance obtained by qPCR (ME-15). This result is in fact not surprising, because both technologies rely on logarithmic PCR amplification of microRNA templates. At low expression levels, both technologies show relatively high variation in biological replicates, which should be considered for data interpretation. Interestingly, miR-203 has a putative binding site for ISGF3 in the promoter region, which would enable IFNα-dependent upregulation. miR-30 has been reported to be IFNβ inducible, although the subclass measured was not specified by the authors (9 ). We decided to analyze the most promising candidate (miR-30e-5p) present in our microarray dataset (Fig. 3a in gray). Detection of miR-30e failed in ME-15 cells due to technical problems, but induction in HuH7 was similar to miR-19a/b. Fig. 3 IFNα-dependent modulation of microRNA expression. a Volcano plot display of IFNα induced microRNA upregulation 4 h after induction. The change factor values (2^log factor change −1) are plotted on the X -axis against the p value in logarithmic scale on the Y -axis. Top-rated microRNAs are annotated together with the let-7 family members. b Confirmation of IFNα effect for selected microarray data by qPCR. The CT-values are the average of three technical and three biological replicates and changes were calculated with 2^ΔMNE (mean normalized expression values). Error bars show 2^ΔMNE ± Δx (average standard error of treated and untreated MNE) from biological triplicates. miR-30e failed to amplify in ME-15 and miR-203 was below the detection limit in HuH7. Expression values were normalized against endogenous snoRNA RNU48 levels. Some technology-related questions remain open. The microRNA assay measures essentially the number of amplicons generated by RT-PCR for each transcript. Thus the signal is an indirect measurement of transcript abundance as compared to classical mRNA microarray platforms, where the target mRNA is directly labeled during linear amplification by in vitro transcription. As a consequence, change factor calculations for amplicon-based assays are ambiguous. In summary, Illumina’s bead array technology is well suited for multi-parallel profiling of microRNAs expressed in different cell types or tissues. We were also able to detect IFNα-inducible microRNA genes although the changes observed were moderate and biological significance remains to be proven. Like most microarray-based detection technologies the technical variability among identical samples is low compared to biological variations of individual cell cultures. At this point it is important to note that variation among biological samples occurs and is independent of the parameters that are measured. Consistent with IFNα-dependent induction of mRNAs we find that virtually all modulated microRNA genes are upregulated. However, the IFNα-induced changes detected in our study are relatively small compared to the changes induced by IFNβ in HuH7 cells (9 ). Finally, it is noteworthy that IRmiRs have similar kinetic properties to their mRNA counterparts. miR-10b for instance is induced early in ME-15 and remains upregulated, while miR-19 abundance ceases after 24 h. In general, the majority of IRmiR genes were reset to basal levels after 24 h and further studies are needed for kinetic classification. Thus, our study adds another level of complexity to the dynamic regulation IFNα signaling and other mechanisms like epigenetic promoter methylation are currently under intense investigation in our laboratories. Acknowledgements We thank Dr. Guido Steiner and Andreas Buness (F. Hoffmann-La Roche Ltd.) for their support in bioinformatics and statistics, Dr. Martin Ebeling (F. Hoffmann-La Roche Ltd.) for the comparative genomic evaluation of microRNA-targeted transcripts and Prof. Dr. Giulio Spagnoli (University Hospital Basel) for the gift of the ME-15 melanoma cell line. Finally, we are grateful to Heather Hinton (F. 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