the genome-analysis based cancer translational medicine · 2018. 5. 3. · tumor 1 tumor 2 tumor 3...
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The genome-analysis based cancer
translational medicine
Qimin Zhan
State Key Laboratory of Molecular Oncology
Cancer Institute and Cancer Hospital
Chinese Academy of Medical Sciences and Peking Union Medical College
Beijing, 2014-06-02
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Cancer: A global thread to health
Globally, there are currently about 12 million new
cancer cases and 7.6 million cancer death each year.
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Cancer : the most aggressive malignancy
in China
More than 2.8 million new cancer cases each year;
About 1.8 million cancer death annually;
Economical lost: more than 100 billion each year;
Big burdens for patients, family and society
The death caused by lung, gastric, liver and esophageal
cancers have ranked the first position in the world
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Thus: Cancer prevention and treatment are closely associated with saving human life
China/ World
Current
China/World
2020
Incidence
22.40% 22.30%
Death 23.68% 24.27%
2.8
1.8
3.8
2.5
0
1
2
3
4
5
Incidence Deaths
12.5
7.6
17
10.3
0
2
4
6
8
10
12
14
16
18
Incidence Deaths
Million
Million
Why should we act?
World 2012
World 2020
China 2012China 2020
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Tumor
Genetic alterations
Signalings
Transformation
Growth
Surgical
Chemo-
TherapyRadio-Ther
Late diagnosis
Limited therapies
Molecular
targetingstop
Key regulators
Biomarkers
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Cancer translational medicine
Genomics
Proteomics
Transcriptom
Metabolomics
Signaling
Cell cycle
Apoptosis
Bioinformatics
Drugs
Biomarkers
Early Diagnosis
Personalized therapy
Targeting therapy
Judgment of Prognosis
Basic
rese
arch
Clinicalquestions
Predictive PreventivePersonalized
Participatory
Clin
ical
ap
plica
tion
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Key issues in Cancer translational Res
Mechanism(s)
Early diagnosis
Targeting therapy
Population study
Molecular typing
Nature of cancer
Opportunity of therapy
Efficient treatment
Personalized therapy
Prevention and
intervention
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Platform and Technology
1、Bio-bank
2、Omics and biology
3、Disease models
4、Clinical research, clinical trials and field study
5、Biotechnology
6、Bioinformatics
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Understanding mechanism
Genetic
Alteration
Alterations of
key events tumorigenesis
APC
P53
RB
PI3K
BRCA1
Ras
Myc
Cell cycle
Apoptosis
DNA repair
Transcription
Invasion
Metastasis
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Prediction and prevention in large-scale
populations
Genome Environment
Genomic alterations (mutations, copy number)
SNP (genetic and environmental factors
Smoking : lung cancer
Drinking : esophageal cancer
HPV :cervical cancer
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Fine Mapping of 7 Novel Susceptibility Loci
4q23: Alcohol dehydrogenase superfamily
(5‘-ADH7-ADH1C-ADH1B-ADH1A-ADH6-
ADH4-ADH5-3')
16q12.1: TMEM188, HEATR3 and PAPD5
17q21: JUP encodes γ-catenin, while HAP1
produces huntingtin-associated protein-1
22q12: XBP1 and CHEK2, which encode X-
box binding protein 1 and a cell-cycle
checkpoint kinase, respectively.
3q27: ST6GAL1 encodes ST6 beta-
galactosamide alpha-2,6-sialyltranferase,
upregulated in many types of human cancer
17p13: SMG6
18p11: PTPN2 produces non-receptor type
2 protein tyrosine phosphatase, linked to a
number of diseases from autoimmune to
cancer
Wu et al, Nat Genet 2012
11
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Effects of Genetic Variations on Alcohol Metabolism
Alcohol drinking is an established risk factor for upper
aerodigestive tract cancers (WHO, World Cancer Report 2003)
Alcohol Aldehyde Acetate
NAD NADH
NADPH NADP
CYP2E1 ALDH2 variants
ADH
ALDH2CO2 + H2O
DNA damage Carcinogenesis
It is hypothesized that individuals with the fast alcohol metabolizer
genotype and slow aldehyde metabolizer genotype would be the most
susceptible to ESCC
12
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Five Loci Associated with Chinese NSCLC Survival
3p22.1
rs76293865p14.1
rs969088
7q31.31
rs419979p21.3
rs12000445
14q24.3
rs3850370
Hu et al. Clin Cancer Res. 2012;18:5507-14
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Identifications of biomarkers
Genetic
Pathology
Metabolism
Expression
Mutation
SNP
Methylation
Proteins
Enzymes
Metablites
Arrays and sequencing
Chips and Mass Spec, ……
The alterations of gene and protein are much earlier
than histological changes during tumorigenesis
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Early diagnosis is the key step of successful
cancer treatment
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Cancer biomarker
疾病预测:Cancer prediction via risk assessment
早期诊断:Early diagnosis:
Better response, low relapse and metastasis.
Otherwise: high relapse and mortality
肿瘤定位:Detection and localization of tumors
制定方案:Guide the therapeutic approaches
检测病程:Surveillance of disease progression
监测疗效:Surveillance of therapeutic sensitivity
判断预后:Judgment of prognosis
复发监测:Screening for disease recurrence
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Targeting cancer therapy
Gleevec:CML
Herceptin:Her2/ErbB2 inhibitor, Breast cancer
Iressa:EGFR mutant inhibitor, lung cancer
Vemurafenib: BRAF inhibitor, melanoma
Erbitux: Ras signaling inhibitor, colorectal cancer
……..
but nothing for ESCC
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Mutations of EGFR
①第18外显子核苷酸2155G >A突变②第19外显子如核苷酸2235-2249Del、核苷酸2254-2277Del、核苷酸2236-2250Del、核苷酸2240-2257Del等共19个突变③第20外显子核苷酸2369C>T ④第21外显子核苷酸2576T>G⑤ 第20外显子的插入突变(D770_N771)、T790M可能会导致原发性
耐药
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IRESSA(吉非替尼):Target detection
Gefitinib, HR=0.19,
95% CI 0.13, 0.26, p
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Personalized therapy
Over treatment
Insufficient treatment
Breast cancer
P53 mut Wnt mutBRCA1mut Ras mut EGFR mut
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Animal model for breast tumorigenesis
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Effect
Scientific evidence for personalized medicine-genomic difference
Gene
Environment
SNP, mutations,
Amplifications…
Smoking, diet, drug dose,
Gender , weight
Drugs
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Low response to cancer drugs
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Personalized cancer treatment
Molecular Data Treatment
Clinical issue-driven research
Biobank
Genomics
Proteomics
Mole-biology
Bioinformatics
Stem cell
Biomaterials
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Tumor 1 Tumor 2 Tumor 3
Standard (Generic) Therapy
In this case, only less than 50% of patients
benefited from such drug treatment
More effective
Less toxic
Less costly
Same Histopathologic Type
The Vision of Personalized Medicine
Approach 1
Tumor 1 Tumor 2 Tumor 3
Molecular diagnosis
Same Histopathologic Type
Approach 2 Approach 3
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GENE EXPRESSION PROFILING PREDICTS
CLINICAL OUTCOME OF B.C. (Nature 2002)
78 untreated N- primary tumors
44 w/o relapse
at 8 y follow-up
34 with a relapse
within 5 y
5000 genes
231 genes
70 genes
= Poor prognosis signature
9791
70
27
Prognosis signature
St Gallen criteria
Groupwith
relapse
Grouprelapse
-free
%
who
"need"
adjuvant
therapy
23
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Gene expression profile predicts
therapeutic sensitivity
The patients received
new adjuvant therapy
showed different
response
Gene expression
profile is able to give
a suggestion for
clinician
Responder Non-responder
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Metastasis
Primary
Invasion
Normal
Genomic
instability
Genomic
alterations
Genomic
disaster
Cancer is fundamentally
a disease of genomic alteration
http://www.bartleby.com/107/illus970.htmlhttp://www.bartleby.com/107/illus970.html
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1、癌症基因组Human Cancer Genome Project
(HCGP)
2、全基因组关联分析Genome-Wide Association Study
Genomic alterations and tumor
From genetic analysis to personalized therapy
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1、Human cancer genome project:(1)、amplifications
(2)、Deletions
(3)、Mutations
(4)、Gene rearrangement
(5)、Methylations
(6)、Expression
2、GWAS in human cancersIdentifications of SNP and tumorigenesis or
therapeutic sensitivity
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XinjiangHebei, Henan and
Shanxi
Chaoshan
district of
Guangdong
province
Esophageal cancer is one of the most aggressive cancers and is the sixth
leading cause of cancer death worldwide;
Approximately 70% of global
esophageal cancer cases occur in China;
more than 90 % histopathological form
of esophageal cancer are ESCC in China;
ESCC exhibits obvious regional
distribution feature in China;
Five-year overall survival rate for
patients with ESCC is about 10-15%;
Esophageal Squamous Cell Carcinoma (ESCC)
To conquer ESCC is the historical
duty of Chinese scientists
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158 tumor and matched blood DNA samples were collected in
Guangdong Province during 2007-2011;
Among158 patients: 35 females and 123 males; the average age was
59 years old; the average follow-up was 805.1;
WGS (>30×) in 17 ESCC cases and WES (>100×) in 71 cases, of which 53 cases, plus an additional 70 ESCC were subjected to CGH
analysis
Genomic analysis in ESCC
CGH WES
70 18
53
WGS
17
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C:G>T:A transitions were the most common mutations, followed by
C:G>G:C transversions
Mutation spectrum of ESCC
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Three main mutation spectrum clusters were yielded
Mutation spectrum of ESCC
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Cluster 1 was significantly enriched in non-drinking, and marked
for better prognosis compared with patients of cluster 2
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Identification of 8 significantly mutated genes in ESCC
PTCH1; CREBBP; RB1;TTN; NOTCH1; EP300; MUC5B; FAM135B; ADAM29;
CDKN2A; PIK3CA; UTRN; GRM5; TP53; NFE2L2
All genes in SNVs and indels data
MutsigCV (q
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In addition to 6.8% (6/88) mutation, FAM135B amplifications were
detected in 25.0% (35/140) cases;
In an independent cohort by Dr. Cui, FAM135B mutation was about
7.6% (8/104);
In this cohort, FAM135B amplification was about 42.3% (44/104).
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Depletion of FAM135B attenuated cell growth and migration
Wild-type FAM135B significantly enhanced cell growth and migration
Mutant FAM135B (p.S165P) showed stronger capability of promoting cell
growth and migration
Identification of FAM135B
as a novel cancer-implicated oncogene
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FAM135B was mutated in 6.8% (6/88) cases and associated with poor
prognosis in ESCC
FAM135B mutation is relevant to clinical ESCC
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FAM135B (mutation (6/88) + amplification (35/140) are associated with
poor prognosis in ESCC
FAM135B alterations is relevant to clinical ESCC
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48 histone modification-related genes were mutated in 53.4% cases ;
The most frequent alterations were observed in histone H3–modifying
lysine methyltransferases (21.6% cases)
Mutations in histone modification-related genes
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large-scale chromosome amplifications at 3q, 5p, 8q, 11q, 12p, 20p,
20q and deletions at 3p, 4q, 9p, 13q, 18q, 19p, 21q ;
CNAs landscape in ESCC
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Totally, 1,325 genes in 43 significant amplified regions and 229 genes in 15
significant deleted regions were characterized;
6 significantly amplified regions were associated with regional lymph nodes
involvement, including 11q13.3-13.4, 8q24.3 and 14q32.2-32.33
Relationships between CNAs and clinical features
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MIR548K positively regulates cell growth, colony formation in ESCC cell lines
MIR548K positively regulates cell migration and invasion in ESCC cell lines;
MIR548K , a miRNA encoded in the amplified 11q13.3-13.4 region , is
characterized as a novel oncogene
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(1) Wnt pathway were detected in 86.4% cases:
(2) Notch pathway was recurrently mutated in 35.2% cases
Genetic alterations of multiple pathways in ESCC
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(3) ESCC mainly exhibited distinct defects in G1/S transition control:
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(4)The genetic variations of G2/M phase in cell cycle:
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(5) EGFR downstream signaling cascade such as the RTK-Ras and AKT
pathways displayed genetic alterations in 78.6% cases:
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Mutations of validated and candidate therapeutic targeted genes were
discovered in 42% samples;
The most frequently mutated target was PI3K (class I);
Intriguingly, EGFR displayed one nonsense mutation (p.E665X),
whereas its amplifications were detected in 24.3% samples;
In amplification data, 136 genes harboring potentially drugable
alterations in 117 cases, including some novel therapeutic targets such as
PSMD2, RARRES1, SRC, GSK3β and SGK3.
Potential therapeutic target analysis
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• PI3K/MTOR and ERK pathways were identified as important potential
therapeutic targets in ESCC:
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Cancer genomic analysis:
To well understand the underlying mechanism(s) of
tumorigenesis and malignant development;
To define the biomarkers for early diagnosis and prognosis;
To identify cancer susceptible genes and related signaling;
To establish molecular classifications for individualized
diagnosis and therapy;
To identify the molecular targets for drug screening and
discovery.
Summary
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Zhan’s group
Acknowledgement
BGI:
Yongmei Song
Yunwei Ou
Weimin Zhang
Xiaojuan Ma
Huanming Yang
Jun Wang
Lin Li
Zhibo Gao
Xiangchun Li
Thank you!
Enmin Li,
Liyan Xu
Shantou University