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

Cancer: A global thread to health

Globally, there are currently about 12 million new

cancer cases and 7.6 million cancer death each year.

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

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

Tumor

Genetic alterations

Signalings

Transformation

Growth

Surgical

Chemo-

TherapyRadio-Ther

Late diagnosis

Limited therapies

Molecular

targetingstop

Key regulators

Biomarkers

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

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

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

Understanding mechanism

Genetic

Alteration

Alterations of

key events tumorigenesis

APC

P53

RB

PI3K

BRCA1

Ras

Myc

Cell cycle

Apoptosis

DNA repair

Transcription

Invasion

Metastasis

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

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

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

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

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

Early diagnosis is the key step of successful

cancer treatment

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

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

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

IRESSA（吉非替尼）：Target detection

Gefitinib, HR=0.19,

95% CI 0.13, 0.26, p

Personalized therapy

Over treatment

Insufficient treatment

Breast cancer

P53 mut Wnt mutBRCA1mut Ras mut EGFR mut

Animal model for breast tumorigenesis

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

Personalized cancer treatment

Molecular Data Treatment

Clinical issue-driven research

Biobank

Genomics

Proteomics

Mole-biology

Bioinformatics

Stem cell

Biomaterials

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

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

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

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

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

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

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

C:G>T:A transitions were the most common mutations, followed by

C:G>G:C transversions

Mutation spectrum of ESCC

Three main mutation spectrum clusters were yielded

Mutation spectrum of ESCC

Cluster 1 was significantly enriched in non-drinking, and marked

for better prognosis compared with patients of cluster 2

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

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).

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

FAM135B was mutated in 6.8% (6/88) cases and associated with poor

prognosis in ESCC

FAM135B mutation is relevant to clinical ESCC

FAM135B (mutation (6/88) + amplification (35/140) are associated with

poor prognosis in ESCC

FAM135B alterations is relevant to clinical ESCC

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

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

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

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

(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

(3) ESCC mainly exhibited distinct defects in G1/S transition control:

（4）The genetic variations of G2/M phase in cell cycle：

(5) EGFR downstream signaling cascade such as the RTK-Ras and AKT

pathways displayed genetic alterations in 78.6% cases:

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

• PI3K/MTOR and ERK pathways were identified as important potential

therapeutic targets in ESCC:

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

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