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Cancer— Cancer— Molecular Network Molecular Network Disease Disease Cheng shujun, Gao yanning, Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Cancer Institute, Chinese Academy of Medical Sciences, Peking Union Medical Sciences, Peking Union Medical College Medical College

Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

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Page 1: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Cancer—Cancer—Molecular Network Molecular Network

DiseaseDisease

Cheng shujun, Gao yanning, Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Zhang kaitai, Xiao Tin

Cancer Institute, Chinese Academy of Medical Cancer Institute, Chinese Academy of Medical Sciences, Peking Union Medical CollegeSciences, Peking Union Medical College

Page 2: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Fortune Magazine, March 22,2004

Page 3: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Personalized Therapy

progress and challenge

Page 4: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

• Breast cancer patients with the same stage can have markedly different treatment responses. The clinical behaviour (such as lymph node status and histological grade) fail to classify accurately outcome. Chemotherapy or hormonal therapy reduces distant metastases by one-third, however 70-80% of these patients would not developed distant metastases without the adjuvant treatment, these patients may not benefit from the treatment, and may potentially suffer from the side effects.

(Nature, 2002,VOl.415, 530)

Page 5: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

• Breast cancer patients with the same stage can have markedly different treatment responses. The clinical behaviour (such as lymph node status and histological grade) fail to classify accurately outcome. Chemotherapy or hormonal therapy reduces distant metastases by one-third, however 70-80% of these patients would not developed distant metastases without the adjuvant treatment, these patients may not benefit from the treatment, and may potentially suffer from the side effects.

(Nature, 2002,VOl.415, 530)

Page 6: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

• FDA News• FOR IMMEDIATE RELEASE

P07-13February 6, 2007 Media Inquiries:

• .

• The MammaPrint test uses the latest in molecular technology to predict whether existing cancer will metastasize (spread to other parts of a patient's body).

• 70 genes activity confers information about the likelihood of tumor recurrence.

Page 7: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Imatinib(Glivec) Chronic myelogenous leukemia(CML) Bcr-abl tyrosine kinase inhibitor . CML patients have high-expression of Bcr-abl fusion protein.

Gefitinib (Iressa) (epidermal growth factor receptop tyrosine kinase inhibitor)

Lung adenocarcinoma patients with relatively high frequency of EGFR gene mutation

Herceptin Breast cancer Her2 monoclonal antibody

Ttumor regression 11-26% for unselected Ttumor regression 11-26% for unselected

breast cancer patients,breast cancer patients, 34% for HER2-34% for HER2-

positive breast cancer patients positive breast cancer patients

( Nature Review cancer, 2006, 6: 735-741)( Nature Review cancer, 2006, 6: 735-741)

Page 8: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Wood,LD,et.al(Science,2007,Nov.16,Vol.318:1108)

• isolated DNA from 11 breast and 11 colorectal tumors and determined the sequences based on exons representing 20,857 transcript from 18,191gene. Any gene that was mutated in the tumor but not in normal tissue from the same patients was analyzed in 24 additional tumors.

• Pathway rather than individual genes appear to govern the course of tumorigenesis. Disruption of a pathway by mutation in any one of its genetic components would presumably lead to similar changes in growth. The <15 driver mutation in an individual tumor likely reflect alterations in a similar number of pathways.

Page 9: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

A few gene ‘mountains’ are mutated in a large proportion of tumors; most genes are mutated in <5% of tumors represented as ‘hills’ 两个肿瘤突变基因重复的很少, (Science 2007,318:

1108)

Page 10: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

• Greenman,C et al(Nature, 2007,446:153-)reported 1,000 somatic mutations found in the coding exons of 518 protein kinase genes in 210 diverse human cancers. There was substantial variation in the number and pattern of mutations in individual cancer. Most somatic mutations are likely to be ‘passengers’ that do not contribute to oncogenesis. However, there was evidence for ‘driver’ mutation contributing to the development of the cancer studied in approximately 120 genes.

Page 11: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Thomas,RK et al.(Nature genetics,2007,39:347-)determined 238 known oncogen mutation across 1,000 human tumor samples of 17 cancer

types. Of 17 oncogens analyzed, they found 14 to be mutated at least once, and 298(30%) samples carried at least one mutation

Page 12: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Sian jones, et al, Scienceexpress, 2008, Sep. 4, 1-10

检查了 24 例胰腺癌的 20661 蛋白编码基因Pancreatic cancer contain an average of 63 genetic alterations, the majority of which

are point mutations. These alterations defined a core set of 12 cellular signaling pathways

Page 13: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

1). Wood,LD,et.al determined the 乳腺癌和结直肠癌 DNA sequences based on exons of 20,857 transcript from 18,191gene. (Science,2007,Nov.16,Vol.318:1108)

2). Thomas RK,et al 分析 17 类肿瘤 238 个 oncogenes 的突变 (Nature genetics, 2007: 39; 153-) 3). Greenman,C;et al. 分析 210 个不同人的肿瘤的 518 protein kinase gene exons 的突变 ( Nature, 2007, 446:: 153-)

The mutated genes in two colorectal tumors overlap to only a small extent

• Pathway rather than individual genes appear to govern the course of tumorigenesis.

• Disruption of a pathway by mutation in any one of its genetic components would presumably lead to similar changes in growth.

• The differences are likely to be the basis for the wide variation in tumor behavior and responsiveness to therapy

• the acquisition of numerous somatic mutations, each with a small fitness advantage, may also drive tumourigenesis

Page 14: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Molecular lesions that occur in early stage of cancer or in precursor lesions are more likely to have a direct influence on cancer occurrence and progression than those that accumulate at the later stage of cancer development. Among the latter, many alterations may be considered as ’passengers’ .

Page 15: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Next-generation sequencing

Cancer—Whole Genome Sequencing

Page 16: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Recurring mutations found by sequencing an acute myeloid leukemia genome. N Engl J Med. 2009 Sep 10;361(11):1058-66

38-year-old man of European ancestry

DNA samples from the patient’s bone marrow sample and a normal skin- biopsy specimen obtained

The AML genome that we sequenced contains approximately 750 point mutations,

We identified 12 acquired (somatic) mutations within the coding sequences of genes and 52 somatic point mutations in conserved or regulatory portions in

the tumor sample. Four of the 64 mutations occurred in at least 1 additional AML sample in 188 samples that were tested

Page 17: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

A comprehensive catalogue of somatic mutations from a human cancer genome

Published online 16 December 2009.Nature 08658

we have sequenced the genomes of a malignant melanoma and a lymphoblastoid cell line from the same person

We identified 33,345 somatic base substitutions.

A total of 32,325 were single-base and 510 were double-base substitutions

Page 18: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

A small-cell lung cancer genome with complex signatures of tobacco exposure

/nature Published online 16 December 2009

.

Using massively parallel sequencing technology, we sequenced a small-cell lung cancer cell line, NCI-H209, NCI-BL209 (an Epstein–Barr-virus-transformed lymphoblastoid line has been generated from the patient. ) to explore the mutational burden associated with tobacco smoking.

A total of 22,910 somatic substitutions were identified, including 134 in coding exons.

One mutation for every 15 cigarettes smoked.

Page 19: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Cancer –Molecular network disease caused by cellular abnormal growth and differentiation related to developmental genome

Page 20: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

PNAS, 2007,104:8685-

Page 21: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Gene Expression Profiles in Different Phases of

Human Lung Embryonic Development and Tumorigenesis

Page 22: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Development landscape

Embud

Early FL

Mid FL

Adult L

(41k probes)

Page 23: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union
Page 24: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

DNA ReplicationDNA Replication Pre-InitiationDNA strand elongationE2F mediated regulation of DNA replicationE2F transcriptional targets at G1/SFOXM1 transcription factor networkFoxO family signalingG1/S TransitionG2/M CheckpointsG2/M DNA damage checkpointG2/M Transition

M PhaseM/G1 TransitionMitotic Metaphase/Anaphase TransitionMitotic PrometaphaseMitotic ProphaseMitotic Spindle CheckpointMitotic Telophase /Cytokinesis

The dynamic gene expressing patterns in human developmental process

Page 25: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Clinical Significance

• The expression level of these genes was correlated with survival cancer patients.Type of cancers

• Adenocarcinoma of the lung ( 242 samples)– 117, 125 samples

• Brain Cancer ( 268 samples )

• Breast Cancer ( 1077samples )– 249, 159, 179, 286 samples

Page 26: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Survival analysis

0 1 2 3 4 5 6 7

100

90

80

70

60

50

40

30

20

Time (years)

Surv

ival

pro

babi

lity

(%)

Number at riskGroup: H

25 22 15 8 3 0 0 0Group: L

24 23 19 14 6 3 2 1

SMC4_groupHL

Survival analysis

0 1 2 3 4 5 6 7

100

90

80

70

60

50

40

30

20

Time (years)

Surv

ival

pro

babi

lity

(%)

Number at riskGroup: H

25 22 15 8 3 0 0 0Group: L

24 23 19 14 6 3 2 1

SMC4_groupHL

P = 0.0407

Survival analysis of 49 ADC patients

P = 0.041

Overall survival analysis of 49 lung ADC patients

Page 27: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Survival analysis of stage I lung

ADC patients :

the relationship between the development related genes

and the prognosis of stage I lung

ADC patients.

Page 28: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

events

0 2 4 6 8 10

100

80

60

40

20

0

Time

Su

rviv

al p

rob

ab

ilit

y (

%)

Number at riskGroup: H

100 17 6 0 0 0Group: L

91 25 13 7 2 1

Group_SHA_86HL

Survival analysis of 191 Glioma patients

P = 0.0299

EVENTS

0 1 2 3 4 5 6 7

100

90

80

70

60

50

40

30

20

10

Time

Su

rviv

al p

rob

ab

ilit

y (

%)

Number at riskGroup: H

40 13 6 4 3 2 1 0Group: L

40 28 18 9 6 4 1 1

SHA_86HL

P = 0.0009

Survival analysis of 80Glioma patients

Survival analysis of glioma patients :

The relationship between the development related genes and the overall survival of patients with glioma.

Page 29: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

The expression level of development related genes was associated with the relapse-free survival of the breast cancer patients, which was confirmed in 7 independent datasets, involving 1300 samples.

Page 30: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

The expression level of development related genes was associated with the overall survival of the breast cancer patients, which was confirmed in 3 independent datasets.

Page 31: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

The expression level of development related genes was associated with both the overall survival and the relapse-free survival of the breast cancer patients without lymph note metastasis (N0).

Page 32: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

For the patients treated with Tamoxifen, the expression level of the development related genes was associated with their prognoses.

Page 33: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

The expression level of the development related genes was also associated with the prognoses of the patients not treated with Tamoxifen.

Page 34: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

The expression level of development related genes was associated with the Elston Histologic Grade of breast cancer.

Most patients with Grade 1 breast cancer (good prognosis) had a lower expression level of the development related genes. And most patients with Grade 3 (bad prognosis) had a higher expression level. However, the patients with Grade 2, whose prognosis was unpredictable according to Elston Histologic Grade, could still be divided into two groups with different expression level of development related genes.

Page 35: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

And the prognosis of the two groups of Elston Grade 2 patients was significantly different.

Page 36: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Cancer prevention and treatment (present and future)

High-risk individual--Precancerous lesions--invasive cancer

Future present

prevention (life style) Surgery

Network drugs radiotherapy

Vaccine chemotherapy

new-therapy

Page 37: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union
Page 38: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

• Key Steps for cancer research in the Future

• To intensify clinical investigation on human cancer and set up tumor tissue banks( translational study).

• To establish high-throughput platforms for fast analysis of genes, proteins, cell structures and functions through a synthetic approach.

• Systematic analysis of both clinical and basic research data with bioinformatics.

Page 39: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

AcknowledgementsDr. Fung Lin Dr. Liu YuDR. Cao bangrong Dr. Sun WenyueDr. Xiao Tin Dr. Liu Yan Ms. Guo supin Ms. Hun NaijunMr. Di Xuebing Dr. Se XiaoyuBeijing Haidian Women- Children Hospital

Page 40: Cancer— Molecular Network Disease Cheng shujun, Gao yanning, Zhang kaitai, Xiao Tin Cancer Institute, Chinese Academy of Medical Sciences, Peking Union

Thank youThank you