沈洪兵南京医科大学公共卫生学院Tel. (Fax.): 86-25-86862756Email: hbshen@njmu.edu.cn

血浆 miRNA 表达谱与肺癌预后关系研究

(1) In the nucleus, pri-miRNAs processed by Drosha as pre-miRNAs;

(2) pre-miRNAs exported by Exportin-5 into cytoplasm;

(3) Processed by Dicer as mature miRNAs;

(4) Perfect complement with 3’UTR: mRNAs cleavage; in-perfect complement: translational repression.

Nat. Rev. Genet. 5(7):522-31,2004

MicroRNAs and Cancer

miRNA as Novel Important Tumor Suppresser Genes and Oncogenes

The discovery of microRNAs (miRNAs) has opened new avenues for cancer diagnosis and prediction of treatment response

Nature Reviews Cancer 6:259-269, 2006

Nature 435(7043):834-838,2005

miRNA expression profiles can classify human cancers

miRNA Profiling May Provide More Accurate Classification of Cancer

Subtypes than the Expression Profiles of Protein-coding Genes

In lung cancer, it has been shown that miRNA expression profiles and specific miRNAs in lung tissue are correlated with disease prognosis and clinical outcome

Cancer Cell. 2008;13:48-57. Cancer Cell. 2006;9:189-98.

Circulating microRNAs as stable blood-based markers for cancer detection

PNAS, 2008 Jul

miRNAs Exist in Serum?

Characterization of microRNAs in serum: a novel class of

biomarkers for diagnosis of cancer and other diseases

Cell Res. 2008 Oct

Why Serum Biomarkers are Important?

Easy to get (non-invasive)

Repeatable

In high risk population (cancer screening)

The discovery of stable serum miRNAs

Chen et al. 2007 Cell Res.

Solexa Whole Genome Sequencing

miRNAs (21-23nt) were most abundant sequences in serum RNAs

Serum miRNAs in Healthy People

Chen et al. 2007 Cell Res.

90 92

Exposure

Lung Cancer

Clinical Outcome

Serum miRNA expressions – prognosis?

Research Question:

Serum miRNA and Lung Cancer Survival

30 live cases34-68 months

30 dead cases2-22 months

120 patients 123 patients

Case-only study (303 cases)

DiscoverySolexa sequencing

Training setqRT-PCR

Validation setqRT-PCR

Randomly classified

Subjects and Assays

Study Population: Early stage (I-IIIa) adenocarcinoma and squamous cell lung cancer patients, treated with both operation and adjuvant chemotherapies

Discovery samples: “Long survival” patients: 30 live patients survival more than 30 months (34.6-61.8 months) (Stage I, 10; stage II, 10; stage III, 10 )“Short survival” group: 30 dead patients survival less than 25 months (2.0-22.5 months) (Stage I, 10; stage II, 10; stage III, 10 )

Training and testing sample sets:243 participants were classified as 120 for training and 123 for testing by computer-generated random numbers. qRT-PCR assay was conducted to quantify the serum levels of miRNAs.

Serum RNA Extraction Efficiency and the Reliability of qRT-PCR Assay

R2 = 0.9907

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-2 -1 0 1 2 3 4

log10 [the amount of ath-miR156a (unit: fmol)]

CT

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0.1-1000 fmol synthesized ath-miR156a miRNA put into 250ul serum ： R=0.99

R2 = 0.9798

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Technical replicate 1

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32 miRNAs detected in 2 repeat samples ： R=0.98

Copies of Solexa Sequencing and qRT-PCR Expression of the 11 miRNAs (30 LS vs 30 SS)

miRNA

Long survival group Short survival groupRatio P **

NCopies

*Mean±s.d. median N

Copies*

Mean±s.d. median

miR-486 30 163 0.658±0.361 0.669 30 3205 1.129±0.542 1.065 0.05 0.0002

miR-22 30 18 0.722±1.225 0.375 30 209 1.103±2.401 0.254 0.09 0.443

miR-30d 30 28 0.455±0.371 0.341 30 165 1.353±0.738 1.122 0.17 4.3×10-7

miR-21 30 230 1.490±0.544 1.480 30 44 1.239±0.501 1.239 5.23 0.069

miR-26b 30 56 1.423±1.337 0.943 30 10 1.240±0.973 0.793 5.60 0.545

let-7i 30 153 2.249±1.805 1.789 30 26 1.845±1.139 1.563 5.88 0.304

miR-378 30 212 2.946±5.963 0.740 30 34 4.407±11.335 1.042 6.24 0.535

miR-1 30 2918 2.918±3.818 1.182 30 407 0.408±0.608 0.180 7.17 0.001

miR-206 30 1979 1.471±0.898 1.450 30 196 1.500±1.023 1.37910.1

00.907

miR-146b 30 81 1.309±1.012 1.114 30 6 1.299±0.823 1.31513.5

00.966

miR-499 30 112 1.096±0.465 1.039 30 6 0.683±0.269 0.71218.6

70.0001* By Solexa sequencing on pooled samples

** Student t test between the two groups

The 4 miRNAs Expression and NSCLC Patients’ Survival of Discovery Data Set

miRNAs PatientsN=60

DeathsN=30

MST (Months)

Adjusted HR(95% CI)

TrendP

miR-486

Q1(<=0.470) 16 3 Not reached 1.00

Q2(0.470-0.830) 14 5 Not reached 3.34(0.75-14.94)

Q3(0.830-1.190) 15 10 9.97 7.46(1.95-28.58)

Q4(>1.190) 15 12 13.77 7.26(1.94-27.23) 0.0009miR-30d

Q1(<=0.325) 15 1 Not reached 1.00

Q2(0.325-0.760) 15 5 Not reached 6.51(0.75-56.83)

Q3(0.760-1.280) 15 10 13.77 22.70(2.69-191.85)

Q4(>1.280) 15 14 8.7 41.02(5.22-322.53) <0.0001miR-1

Q4(>1.465) 15 2 Not reached 1.00

Q3(0.525-1.465) 15 6 Not reached 6.03(0.70-52.29)

Q2(0.180-0.525) 15 11 12.27 12.70(1.54-104.98)

Q1(<=0.180) 15 11 9.8 45.17(5.73-355.82) <0.0001miR-499

Q4(>1.115) 15 1 Not reached 1.00

Q3(0.815-1.115) 15 5 Not reached 3.32(0.66-16.61)

Q2(0.605-0.815) 13 8 15.17 9.27(1.98-43.41)

Q1(<=0.605) 17 16 7.2 8.73(1.88-40.58) 0.0006

The 4 miRNAs Expression and NSCLC Patients’ Survival of Training/Testing Sets

miRNAsPatientsTraining /Testing

DeathsMST

(Months)

Adjusted HR1(95% CI) 1

Training

Adjusted HR2(95% CI) 1

Testing

miR-486

Low(<=0.795) 60/62 16/20 ----/39.93 1.00 1.00High (>0.795) 60/61 24/23 31.33/31.33 1.78(0.91-3.49) 1.70(0.91-3.18)

miR-30d

Low(<=0.680) 60/58 13/17 ----/42.6 1.00 1.00High(>0.680) 60/65 27/26 22.97/31.6 4.57(2.24-9.34) 3.27(1.63-6.55)

miR-1

High(>0.675) 60/62 11/16 ----/42.6 1.00 1.00Low(<=0.675) 60/61 29/27 22.97/31.8 3.04(1.49-6.22) 2.81(1.43-5.50)

miR-499

High(>0.750) 58/74 13/21 ----/43.17 1.00 1.00Low(<=0.750) 62/49 27/22 22.97/31.6 2.76(1.39-5.50) 2.14(1.10-4.14)

Number of high-risk miRNAs0-1 37/41 4/10 ----/43.17 1.00 1.002 43/48 8/12 41.67/36.77 2.62(0.76-9.08) 1.82(0.73-4.52)3 34/30 23/17 17.83/18.73 17.38(5.55-54.45) 11.59(4.40-30.53)4 6/4 5/4 17.03/17.08 24.39(5.96-99.75) 16.25(4.46-59.19)

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Training Set (120 patients) Testing Set (123 patients)

Number of High-Risk miRNAs and NSCLC Patients’ Survival of Training/Testing Sets

P < 0.0001

MonthsMonths

Survival rate

43

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The 4 miRNAs

Expression and

NSCLC Patients’

Survival of all Sample

Sets

Number of high-risk miRNAsPatientsN=303

DeathsN=113

MST (Months)Adjusted HR

(95% CI)

0-1 100 14 Not reached 1.002 107 28 Not reached 3.03(1.58-5.78)3 75 51 17.83 16.83(8.79-32.23)4 21 20 12.27 36.06(17.17-75.77)

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Risk Score Analysis of 303 NSCLC Patients

Low risk miRNA signatures

miR-486miR-30dmiR-499 miR-1

High risk miRNA signatures

Risk Score=0.415

020

4060

Alive Death

Each patient was assigned a risk score according to a linear combination of the expression level of the miRNA, weighted by the regression coefficients from the training samples

Risk Score and NSCLC Survival

Risk score Patients Deaths MST (Months)Log-rank

PAdjusted HR

(95% CI)

Training set N=120 N=40

Low(<=0.415) 60 7 Not reached 1.00

High(>0.415) 60 33 20.3 <0.0001 10.74(4.28-26.96)

Testing set N=123 N=43

Low(<=0.415) 75 16 43.17 1.00

High(>0.415) 48 27 23.97 <0.0001 6.35(3.07-13.15)

All data sets N=303 N=113

Low(<=0.415) 167 26 Not reached 1.00

High(>0.415) 136 87 18.43 <0.0001 9.31(5.78-14.98)

Stepwise Cox Proportional Hazards Analyses on NSCLC Survival

Final variables β SE HR 95% CI P

Stage 0.51 0.12 1.67 1.32-2.12 <0.0001

miR-486 (high verse low) 0.90 0.22 2.47 1.61-3.79 <0.0001

miR-30d (high verse low) 1.41 0.23 4.10 2.62-6.42 <0.0001

miR-1 (low verse high) 1.17 0.23 3.22 2.04-5.08 <0.0001

miR-499 (low verse high) 1.02 0.22 2.78 1.81-4.27 <0.0001

Final variables β SE HR 95% CI P

Stage 0.48 0.12 1.62 1.29-2.03 <0.0001

The four-miRNA signature (>0.415 vs <0.415)

2.23 0.24 9.31 5.79-14.97 <0.0001

Conclusions

Serum miRNA signature can be also used to predict the subgroup of NSCLC patients with poor prognosis (short survival).

Journal of Clinical Oncology 2010 (IF=17.2)

Key Grant of National Natural Science Foundation of China (30730080);

National Outstanding Youth Science Foundation of China (30425001);

The China National Key Basic Research Program Grants (2002CB512902)

Dr. Dongxin Lin Cancer Institute/Hospital, Chinese Academy of Medical Sciences, Beijing, China

Dr. Chenyu Zhang Naning University, Nanjing, China

Dr. Lin Xu Jiangsu Cancer Hospital, Nanjing, China

Dr. Yijiang Chen First Affiliated Hospital of Nanjing Medical University, Nanjing, China

Acknowledgements

Thanks!