Circulating biomarkers for prediction of treatment ...€¦ · Circulating tumor DNA to monitor...

Circulating biomarkers for

prediction of

treatment response

Maria Grazia [email protected]

Department of Experimental Oncology

& Molecular Medicine

Milan, Italy

Cremona, October 5-7, 2013

Towards the rapid assessment of therapy efficacy

Big challenges in the development of biomarkers for

personalized medicine

Intratumor heterogeneity and

branched evolution: ……one or two

accessible metastases may not be

representative of biologically and

clinically relevant tumor features….

Gerlinger et al., NEJM2012

Impact of the microenvironment on tumor progression

Primary tumor

or metastasis, and their

microenvironment

Liquid biopsy as a window for therapeutic

intervention between initial dissemination

and eventual metastatic dissemination

Blood as a real-time liquid biopsy ?(for CTCs, ct-DNA, ct-miRNA)

The liquid biopsy concept� Peripheral blood contains CTCs, nucleic

acids, proteins, microvescicle and

exosomes, etc., derived from primary

and metastatic lesions

� Easy accessibility, with minimally

invasive approaches

� Dynamic and real-time monitoring

feasible and reliable for:

� therapeutic targets

� drug-resistance conferring

mutations

� new actionable mutations

� early detection of disease

progression


Ex

pe

rim

en

tal

On

co

log

y D

ep

t.

BLOOD PROCESSING

Circulating Tumor Cells (CTC)� enumeration� molecular characterization

Me

dic

al

On

co

log

y

De

pt.

baseline 1st cycle of treatment

2nd cycle of treatment

Pre-surgery

treatment

BLOOD WITHDRAWAL

Post-surgery

Workflow for primary systemic trials


Circulating microRNA Mutations in cell-free DNA

C. Alix-Panabieres, K. Pantel, Clin Chem, 2013


CTCs as a real-time

liquid biopsy

CTCs: not only enumeration

CIRCULATING TUMOR CELLS: NOT ALL DETECTED CELLS ARE BAD AND NOT ALL BAD CELLS ARE DETECTED, HAYES DF, WICHA M, JCO 2011


METHOD ADVANTAGES DISADVANTAGES

PROTEIN

EXPRESSION

(immuno-

fluorescence)

� CTC count obtainable in the

same assay

� Assessment of inter-cell

heterogeneity

� Cut-off defined at the cell-level

by comparison with cell lines

� Assessment of protein-protein

interactions

� No cut-off at the sample level due

to CTC heterogeneity within one

sample

� Limitations for multi-plexing

mRNA

EXPRESSION

(qRT-PCR )

� Multi-plexing possible up to a

large number of genes

� Small reaction volume required

� No information on CTC count in a

sample

� No information on heterogeneity

� Hampered by leukocyte

contamination

CHROMOSOMAL

ABNORMALITIES

(FISH)

� CTC count obtainable in the

same assay

� Assessment of inter-cell

heterogeneity

� Lower sensitivity for small genes

due to large size of FISH probes

� Knowledge needed of possibly

altered genes for probe design

� Limitations for multi-plexing

Summary of currently used CTC characterization methods


8

Author Method for CTC

characterization

# Patients Setting Treatment Clinical relevance

Xenidis

(2007)

qRT-PCR for

CK-19 mRNA

119 Early,

ER+/PR+

Tamoxifen Presence of CK-19 mRNA+ cells

during treatment associated with

lower DFS and OS, also in

multivariate

Xenidis

(2009)

qRT-PCR for

CK-19 mRNA

437 Early Epirubicin +

Docetaxel

(ET)

Presence of CK-19 mRNA+ cells after

adjuvant treatment associated with

lower DFS and OS, also in

multivariate

Saloustros

(2011)

qRT-PCR for

CK-19 mRNA

312 Early ET Presence of CK-19 mRNA+ cells after

treatment associated with risk of

relapse

Georgoulias

(2012)

qRT-PCR for

CK-19 mRNA

75 Early,

HER2-

Trastuzumab Presence of CK-19 mRNA+ cells after

treatment associated with lower

DFS and risk of recurrence

Xenidis

(2013)

qRT-PCR for

CK-19 mRNA

545 Early FEC or EC vs

ETC or ET

Absence of CK-19 mRNA+ cells after

treatment associated with

treatment response and favourable

clinical outcome

Muller (2012) CellSearch vs

ADNA Test

(EPCAM, ERBB2,

MUC1)

254 Metastatic Various The clinical relevance depends on

the test methods

Clinical relevance of CTC characterization in breast cancer:

treatment response


EPCAM is mainly represented in CTCs from metastatic breast cancers compared to CTCs from early-stage disease

0

10

20

30

40

50

60

EPCAM MUC1 ERBB2 PIK3CA AKT2 TWIST1 ALDH1

posi

tivity

per

cent

age

markers

neoadjuvant

metastatic


Patients: women with metastatic breast cancer

CTC counts: Cell Search on 7.5 ml blood

CTC capture : AdnaGEN

Lysis : Agencourt lysis buffer

RNA extraction : Agencourt RNA Advance cell v2 kit

Gene expression profiling: DASL Illumina (29,000

genes)

Bioinformatics analysis: Experimental Oncology

Department at INT

CTCs: Not only enumeration

Gene Expression Profiling – collaboration between INT and Cremona Hospital Breast Unit


Samples clustered by PAM50 genesSamples clustered by PAM50 genes Clustering with 24 selected leukocyte genesClustering with 24 selected leukocyte genes

Samples with 10-100 CTCs:

technical failure or CTC

negativity?

Gene Expression Profiling of CTCs


Sample with 300 CTCs:

excellent GEP

True CTC -ve

samples

Technical failure

� Experiments with spiked cells have demonstrated the

technical and biological reliability of GEPs obtained from

at least 25 tumor cells

� A pilot study with the Cremona Breast Unit demonstrated

(in the metastatic setting) the feasibility of a multicentric

CTC gene profiling study

� Studies in the advanced breast cancer setting are crucial

for validating the hypothesis that CTCs may represent the

cell population that drives disease progression and that

their features (rather than the primary tumor) guide

prognosis and treatment response

� If succesfull such a paradigm can be exploited also for

NGS studies at DNA level to identify possible druggable

targets directly on CTCs as surrogate of the metastatic

cell population

Gene expression profiling of CTCs – INT experience


13

Hurdles and solutions in CTC research (Plaks, Koopman & Werb, Science 2013)


Biophysical factors thatmay diminish CTC

detection

Biological factors likelycomplicating isolation &

detection of clinicallyrelevant CTC populations

Future research

miRNA signature test

miRNA

miRNA extraction from plasma/serum

�miRNAs were found to be stable and

detectable in many biological fluids

�miRNAs can disseminate from tumor cells to

periferal circulation due to a passive or active

release

� miRNAs have been found packaged in

exosomes derived from multivesicular bodies, or

to be exported in the presence of RNA-binding

proteins (i.e., Ago-2) or into microvesicles shed

during membrane blebbing

�Recent studies demonstrated that circulating

miRNAs have diagnostic and prognostic

significance in cancer and many other diseases (Shen et al. Cancer letter 2013 and Weiland et al. RNA

Biol 2013)Diagnosis,

prognosis,

etc.

14

Blood as a real-time liquid biopsy: circulating microRNA


Potentially novel non-invasive biomarkers for cancer

MicroRNAs for cancer:

therapeutic applications

(modified from William C.S.

Cho, BBA, 2010)

association with drug sensitivity

association with endocrine sensitivity

association with anti-HER2 treatments

Different studies, different results

�Poor overlap/reproducibility of results

�Several studies using different approaches

Author Body fluid Method Normalization # Pts (#HDs) Candidate miR, #(DE)

Zhao (2010) PlasmaArrays

(Illumina)Quantile 20 (20) 1145 (miR-589, miR-425, let7c)

Schrauder (2011) Whole bloodArrays,

qRT-PCRVSN 72 (81)

1100 (16 up- and 46 down-

regulated miRs)

Cuk (2012) PlasmaTaqMan LD-arrays,

qRT-PCRQuantile 127 (80)

667(miR-148b, miR-376c, miR-

409-3p, miR-801)

VanSchoone-veld (2012) Serum qRT-PCR miR-16 75 (20)4 (miR-215, miR-299-5p, miR-

411, miR-452)

Schwarzen-bach(2010) Serum qRT-PCR miR-16 168 (53)4 (miR-19a, miR-20a, miR-21,

miR-214)

Heneghan (2010) Whole blood qRT-PCR miR-16 83 (44) 7 (miR-195, let7a)

Cookson (2012) Plasma qRT-PCR miR-16, mean miR level 10 367(miR-18b, let-7b, let-7c)

Roth (2010) Serum qRT-PCR miR-16 89 (29)4 (miR-10b, miR-34a,

miR-155)

Asaga (2011) Serum qRT-PCR miR-16 102 (20) 1 (miR-21)

Madhavan (2012) PlasmaTaqMan LD-arrays,

qRT-PCRQuantile, cel-miR-39 192 (76)

667(miR-141, miR-200a,b,c,

miR-210, miR-375, miR-203,

miR-801)

Outcome of studies on cell-free miRNAs in breast cancer: diagnosis & prognosis

16


17

Author Body

fluid

source

Method Normali-

zation

# Pts

(#HDs)

Stage Candidate

miR, #(DE)

Relation with:

Zhao (2011) Plasma qRT-PCR miR-16 93 II, III miR-221 Overall response

to NAC, ER-

Wang (2012) Serum qRT-PCR miR-16 56 II, III 4(miR-125b) FEC response,

high PCNA, low AI

Wu (2012) Serum Deep

sequencing

(Illumina),

qRT-PCR

edgeR

algorithm58 II, III >800(miR-122,

miR-375, miR-

184, miR-1299,

miR-196a, miR-

381,miR-41, miR-

1246)

pCR to AC +/-

Tx+trastuzumab,

distant metastasis

Jung (2012) Plasma qRT-PCR U6-RNA 29 (28)

43

I-III

I-III

4(miR-126, miR-

21, miR-210,

miR-29a)

↓ post-treatment,

response to

Trastuzumab

Sun (2012) Serum qRT-PCR miR-16 29 III miR-155 ↓ post-treatment,

response to

chemotherapy

Outcome of studies on cell-free miRNAs in breast cancer: treatment response


Technical/biological aspects challenging circulating miRNA studies

Feature Challenge Outcome

Hemolysis in

plasma/serum samples

affects miRNA profile

Identification of

hemolyzed samples

Developed a hemolysis score able to identify low level of hemolysis

independently from lipema.

Heparin could be used

as anticoagulant

Heparin inhibits

amplification reaction

(RT-PCR)

If adequately treated, heparinized plasma samples could be

suitable for miRNA expression analysis, without affecting miRNA

detection performance.

P Tiberio, et al. The Journal of Molecular Diagnostics, 2013;15:138-9.

Plasma or serum

samples

Is miRNA profile

equivalent?Ongoing

miRNA are short, have

variable GC content and

high homology between

family members, are

present in low

concentration in

circulation

Are conventional

available techniques

(such as RT-PCR,

miRNA microarray)

suitable for circulating

miRNA profiling?

Agilent microarray is suitable for measuring miRNA expression in

human tissues and in archival (>20 years old) plasma samples.

M Callari, et al. Analytical Biochemistry 2013;437:123-5.

Callari M, et al. PLoS One. 2013 May 14;8(5).

Established reference

miRNAs are missing

Identification of

appropriate

normalization methods

Ongoing (three normalization methods adopted: raw data,

normalization approaches ratio-based or using housekeeping

miRNAs )


19

microRNAs as indicators of

sensitivity/resistance to

specific treatments

In vitro studies on cell

coltures

In vitro studies on cell

colturesIn vivo correlative studies

within PST/NAC trials

In vivo correlative studies

within PST/NAC trials

Pre-clinical in vitro/in vivo

functional validation

Pre-clinical in vitro/in vivo

functional validation

Prospective clinical

validation

Prospective clinical

validation

End point:

identification of

novel

biomarkers/

pathways

End point:

identification of

novel

biomarkers/

pathways

Identification of:

1. miRNA associated to

drug sensitivity/

resistance

2. treatment-induced

miRNA changes

Identification of:

1. miRNA associated to

drug sensitivity/

resistance

2. treatment-induced

miRNA changes

Identification of:

1. miRNA associated with

clinical outcome

2. miRNAs as monitoring

tools:

Identification of:

1. miRNA associated with

clinical outcome

2. miRNAs as monitoring

tools:

PST/NAC trials integrating clinico-pathologic & molecular findings

Blood as a real-time liquid biopsy: mutations in circulating DNA


Primary tumor

or metastasis

DNA from cancer cells ( ) my be released

into the bloodstream, enabling the

detection of mutations, methylation, DNA

integrity and microsatellite alterations.

Identification of cancer mutations in

plasma may be useful for:

� early detection

� prognosis

� monitoring tumor dynamics over time

� detection of minimal disease

� monitoring recurrence

M Murtaza et al. 2013

Identification of treatment-associated mutational changes from

exome sequencing of serial plasma samples


NGS of tumor sample

Tracking of mutations in serial plasma samples

Selection of DNA alterations (tumor “barcodes”)

Monitoring Circulating Tumor DNAEarly detection of relapse and/or of disease progression


Breast cancer at surgery (relapse detection)Early

detectionof relapse?


Most frequently mutated breast cancer genes

(according to Baird & Caldas, BMC Medicine 2013)

Gene

mutation Function

Approximate mutation frequency (%)

Overall Luminal

A

Luminal

B

HER2-

enriched

Basal-

like

PIK3CA

Catalytic subunit of PI3K, key

signal transduction enzyme

involved in cell growth &

survival, and insulin signaling

25-36 40-45 29 39 9

TP53Tumor suppressor, key

regulator of cell cycle, DNA

repair and apoptosis27-37 12 29 72 80

GATA3

Transcription factor regulating

luminal epithelial cell

differentiation in the

mammary glad

4-11 14 15 2 2

MAP3K1Kinase activating ERK and JNK

pathways 3-8 13 5 4 0

MLL3Histone-lysine N-methyl-

transferase involved in

transcriptional co-activation7 8 6 7 5

CDH1

Cell-cell adhesion

glycoprotein: LoF mutations in

E-cadherin as a feature of

lobular breast cancer

7 9-10 5 5 0

CT scan

Whole-genome seq of tumor material used to identifi y tumor mutations

Selection of 10 mutations(tumor “barcode”)

Tracking of mutations in serial plasma samples

paclitaxel

Epirubicine

Common pattern of sharp decline in AF upon chemother apyand increase upon disease progression

Dynamics of tumor-specific mutationsin plasma of a metastatic BC patientundergoing two phases of chemotherapy


Circulating tumor DNA to monitor metastatic breast c ancer:Study Overview and Outcome

• This study evaluated the sensitivity of assaying tumor DNA circulating

in the plasma.

• This assay is compared with three other approaches: radiographic

imaging, assay of cancer antigen 15-3 (CA 15-3) levels, and CTC

assay.

• Circulating tumor DNA successfully detected in 97% (29/30) of women

in whom genomic alterations were identified (CA15.3 and CTCs

detected in 78% (21/27) and 87% (26/30) of the cases, respectively)

• Circulating tumor DNA levels showed greated dynamic range, greater

correlation with changes in tumor burden, earliest measure of

treatment response (in 53% of women, 10/19)

• This proof-of-concept analysis showed that circulating tumor DNA is

an informative, inherently specific, and highly sensitive biomarker of

metastatic breast cancer.

• Now, VALIDATION!!!


Current points of strengthCTC molecular

profilemiRNAs

Mutations in

cell-free

DNA

Feasible on small sample amount (<1.5 ml) NO YES YES

Independence from tissue heterogeneity YES YES YES

Direct information on tumor biology,

distinct subpopulations & heterogeneityYES NO

YES (only through

WGS)

Accounting for microenvironment

interactionsNO YES NO

Dynamic time-related monitoring

(feasibility for longitudinal studies)YES YES YES

Identification of clonal resistance YES NO YES

Suitable to investigate druggable targets YES NO YES

Suitable for retrospective studies NO YES YES

Taylored for personalized monitoring NO NO YES


Circulating biomarkers to monitor progression/treatment response

Current points of

weaknessCTC molecular

profilemiRNAs

Mutations in cell-

free DNA

Low feasibilityDependent on

capture efficiencyNO NO

Contamination by other

cells/other cell productsYES

YES (hemolysis issue)

YES(possible dilution)

Possible missing of clinically

relevant populationsYES NYI* NYI*

Technical-related hurdles YES YES YES

Data analysis-related issues NO YES YES

Timing of blood withdrawal NO YES YES

Few studies with clinical

correlationsYES YES YES

Discordance among published

resultsNO

(single group studies)YES

NO(single group

studies)

Tayloring for individual

patientsNO NO YES


Circulating biomarkers to monitor progression/treatment response

* NYI: Not Yet Investigated

The best preparation for tomorrow is to do today’s work

superbly well

Sir William OslerCanadian Physician (1849-1919)


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Thanks to Colleagues of the:

Department of Medical OncologyIstituto Nazionale Tumori @ Milan

Breast UnitIstituti Ospedialieri @ Cremona

Biomarkers UnitDept. of Experimental OncologyIstituto Nazionale Tumori @ Milan

Circulating biomarkers for prediction of treatment ...€¦ · Circulating tumor DNA to monitor...

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