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

血浆 miRNA 表达谱与肺癌预后关系研究. 沈洪兵 南京医科大学公共卫生学院 Tel. (Fax.): 86-25-86862756 Email: hbshen@njmu.edu.cn. MicroRNAs and Cancer. (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 ;

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

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  1. 血浆miRNA表达谱与肺癌预后关系研究 沈洪兵 南京医科大学公共卫生学院 Tel. (Fax.): 86-25-86862756 Email: hbshen@njmu.edu.cn

  2. MicroRNAs and Cancer (1) In the nucleus, pri-miRNAsprocessed by Drosha as pre-miRNAs; (2)pre-miRNAsexported by Exportin-5into cytoplasm; (3) Processed by Dicerasmature miRNAs; (4) Perfect complement with 3’UTR: mRNAs cleavage; in-perfect complement: translational repression. Nat. Rev. Genet.5(7):522-31,2004

  3. miRNAas 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

  4. miRNA Profiling May Provide More Accurate Classification of Cancer Subtypes than the Expression Profiles of Protein-coding Genes miRNA expression profiles can classify human cancers Nature 435(7043):834-838,2005

  5. 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.

  6. miRNAs Exist in Serum? Circulating microRNAs as stable blood-based markers for cancer detection PNAS, 2008 Jul Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases Cell Res. 2008 Oct

  7. Why Serum Biomarkers are Important? • Easy to get (non-invasive) • Repeatable • In high risk population (cancer screening)

  8. The discovery of stable serum miRNAs Chen et al. 2007 Cell Res.

  9. Solexa Whole Genome Sequencing miRNAs (21-23nt) were most abundant sequences in serum RNAs

  10. Serum miRNAs in Healthy People 92 90 Chen et al. 2007 Cell Res.

  11. Serum miRNA expressions – prognosis? Exposure Lung Cancer Clinical Outcome Research Question:

  12. Serum miRNA and Lung Cancer Survival Case-only study (303 cases) 30 live cases 34-68 months 30 dead cases 2-22 months 120 patients 123 patients Randomly classified Discovery Solexa sequencing Validation set qRT-PCR Training set qRT-PCR

  13. Subjects and Assays Study Population: Early stage (I-IIIa) adenocarcinomaand squamous celllung 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.

  14. Serum RNAExtraction Efficiency and the Reliability of qRT-PCRAssay 32miRNAs detected in 2 repeat samples：R=0.98 0.1-1000 fmol synthesized ath-miR156amiRNA put into 250ulserum：R=0.99

  15. Copies of Solexa Sequencing and qRT-PCR Expression of the 11 miRNAs (30 LS vs 30 SS) * By Solexa sequencing on pooled samples ** Student t test between the two groups

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

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

  18. Number of High-Risk miRNAs and NSCLC Patients’ Survival of Training/Testing Sets Training Set (120 patients) Testing Set (123 patients) Survival rate 1 2 1 3 4 2 3 P < 0.0001 4 P < 0.0001 Months Months

  19. 1 2 3 4 P < 0.0001 The 4 miRNAs Expression and NSCLC Patients’ Survival of all Sample Sets

  20. 60 Risk Score=0.415 miR-486 miR-30d miR-499 miR-1 40 Low risk miRNA signatures High risk miRNA signatures Alive Death 20 0 Risk Score Analysis of 303 NSCLC Patients 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

  21. Risk Score and NSCLC Survival

  22. Stepwise Cox Proportional Hazards Analyses on NSCLC Survival

  23. 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)

  24. Acknowledgements Dr. Dongxin LinCancer 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 ChenFirst Affiliated Hospital of Nanjing Medical University, Nanjing, China • 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)

  25. Thanks!

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