CTCs: Capturing, Cultivation and Molecular · PDF filePage 3 • PMWC, January 25th 2016 What is needed to deploy CTCs as predictive biomarker in Personalized Medicine? 1. Standardization

CTCs: Capturing, Cultivation and Molecular Analysis

Dr. Thomas Krahn

Head Global Biomarker Research

PMWC, January 25th 2016

Bayer Pharma AG is committed to develop a biomarker strategy for

every compound going into clinical studies and to fully leverage the

opportunities of personalized medicine for the benefit of our patients.

Personalised Medicine will be a major driver of innovation and the next

evolutionary step towards a more effective and efficient use of

therapeutic interventions. Today – with only few successful examples –

industry is still at an early stage. Bayer Pharma aims to become a leader

in providing personalized treatment solutions by 2020.

Page 2 • PMWC, January 25th 2016

Introduction


What is needed to deploy CTCs as predictive biomarker in Personalized Medicine?

1. Standardization of sample handling in the clinical setting / preanalytical

sample handling SOP / CTC definition(s)

3. Going beyond the pure numbers into molecular analysis of CTCs, we

need highly sensitive, validated technologies.

2. Approved CTC capturing technologies:

high yield in high percentage of patients incl. the non metastatic setting

As only CTCs offer the chance for isolation and subsequent functional testing,

whereas ctDNA and miRNA may be more likely to be detected and therefore

suitable especially in early disease stages of cancer or in minimal residual

disease.

Use of Circulating Tumor Cells as Predictive

Biomarker in Clinical Trials

Main problem

Low frequency

„Blood Based Biomarker /

Liquid Biopsy“

- Prognostic value (count)

- Prediction

- Pharmacodynamics

- „Companion Diagnostic“

e.g. as reviewed in Nature Biotechnology 2012

Circulating Tumor Cells as Blood Based BM

Beyond Counting in Personalized Medicine


> 3-5 CTCs in 7.5 mL of blood captured by EpCAM

Change or increase selection criteria

7.5 mL of blood, CTCs captured by 10 different ABs

Increase blood volume

Apheresis:

total blood volume 2-3 times

Capturing goal:

> 50 living CTCs in

> 50% of patients

1

10

7.5 > 5000 mL

2

YY Y Y YY YYY YY Y Y YY Y Y YY

YY Y Y YYY YYY Y

GILUPITa r g e t c e l l

FSMW


Enhancement of CTC Capturing Principles

Apheresis:

a medical technology in

which the blood of a donor or

patient is passed through an

apparatus that separates out

one particular constituent and

returns the remainder to the

circulation

(1) whole blood

enters the centrifuge

and separates into

plasma (2),

leukocytes (3), and

erythrocytes (4).

Selected

components are

then drawn off (5)

continuous flow centrifugation

Up to 150 mL/per patient of the leukocyte layer, the so called “buffy-coat” layer

Diagnostic leukapheresis enables reliable detection of circulating tumor cells of non-metastatic cancer

patients, Johannes C. Fischer et al.; PNAS, 2013 Oct. 8, vol. 110 no. 41, 16580–16585


Leukapheresis Approach


Yield

Spike-in experiments? / Clinical data?

Data in metastatic & non-metastatic setting available? Which indication?

Comparison data to CellSearch®?

Heterogeneity

Which CTC population is detected by the method? EpCAM-dependent?

Purity

Background of white blood cells?

Which downstream analysis are possible? Data?

Reproducibility

High potential to get standardized? (pre-analytic sample handling)

Sample logistics established?

Selection Criteria for Implementation of CTC

Technology in our Comparison Study

1. Group: antibody-based methods

→ capturing is based on the expression of surface marker e.g. EpCAM

2. Group: filter and electrophysical methods

→ capturing is based on the larger size or electrophysiology of the CTCs

ISET filter method by RareCells

filter method by Siemens

DEP technology by Apocell

standard methods CellSearchTM System by Veridex

enhanced antibody-based method by Fluxion

enrichment + FACS-Sorting @ University of Düsseldorf

in vivo isolation using an antibody-coated wire by GILUPI


Comparison of CTC Isolation Technologies

against CellSearch™

captured CTCs

The antibody-coated CellCollector is injected in the peripheral vein for 30 min.

Captured CTCs can be functionally profiled post capture.

In vivo CTC technology


CT

Cs

CellCollector CELLSEARCH0

10

20

30

40

100200300

p<0.0001

Wilcoxon Matched-Pairs Signed Rank Test

77.4% 17.8% >0 CTCs Unpublished data

Detection of CTCs in NSCLC patients

In vivo isolation using the CellCollector by

GILUPI

Enrichment & staining by

automated liquid handling

CK 8,18,19

CTC detection by scanning

fluorescence microscopy

Integrated filter slide with

micro pore membrane

Her2/neu

DAPI

High-throughput walk-away workflow with 8 samples processed in parallel

Efficient use of reagents and easy adaption to sample type and volume

Broad menu of direct labeled antibodies, e.g. CK, EpCAM, CD 45, HER2neu,

PR, ER, VEGF-165, KRAS, EGFR, WAF, BAX-1, PDGF, P53, CAIX, MIB1, MDM

Automated image analysis software for identification of rare cells

Downstream analysis either on slide (e.g. FISH) or with single cells after laser

micro dissection (e.g. qPCR, sequencing)


Filter Technology by Siemens

Maximum information from cells can be extracted through a

combination of

advanced CTC enrichment technology

with an integrated detection method

FP7-610472-CanDo


This work is carried out within the FP7-ICT-610472-CanDo project, funded by the European Commission.

A CANcer Development mOnitor

FP7-CanDo Platform Structure


Mean spectra of WBCs, HPAF-II, and Panc1 cells show significant differences

between WBCs and pancreatic tumor cells

Mean spectrum of ca. 500 WBCs

Mean spectrum of ca. 1000 Panc1

Mean spectrum of ca. 1000 HPAF-II

Schie IW, Huser T.; Methods and applications of Raman microspectroscopy to single-cell analysis

Appl Spectrosc. 2013 Aug;67(8):813-28. doi: 10.1366/12-06971

HPAF-II

Raman Spectra of Tumor Cells compared to

White Blood Cells

wave number cm-1


HPAF-II Panc1 WBC

WBC Panc1 HPAF-II

WBC 363 0 0

Panc1 0 773 4

HPAF-II 0 0 854

Original Class

Pre

dic

ted

Cla

ss

C. Krafft, I. W. Schie, T. Meyer, M. Schmitt and J. Popp; Developments in spontaneous and coherent Raman scattering

microscopic imaging for biomedical applications, Chem. Soc. Rev., 2016,

PCA-SVM based classification models can effectively differentiate between WBCs

and pancreatic tumor cell lines

Differentiation WBCs / Pancreatic Tumor Cells

Xcell technology has been developed for whole blood.

It works also for leukapheresis lysate and there even with frozen

specimen.


Avatar Platform for

CTC culture

Technology: enrichment and propagation of viable CTC clusters

requires ‘tuning’ of the ex vivo microenvironment

Xcell Biosciences Technology:

Maintain, Propagate and Characterize CTCs


6 patient samples that yielded CTC colonies

have been profiled

Pancreatic CTC colonies have more

snps/indels in PDAC associated genes than

in controls

Simple and Easy Workflow for CTC Enrichment:

Culture + Sequencing


Tumor cells from ascites fluid of an ovarial CA can be captured and profiled

Ex vivo/ in vitro drug response profile can be performed

PI3Ki

MEKi

PI3Ki+

MEKi

DMSO

HER1

HER2

CMET

CK

Phospho GF+ GF-

Total

Superior pathway inhibition when PI3K & MEK inhibitor are combined

Based on this analysis:

Single agent treatment is predicted not to be effective

This patient would benefit from PI3K/MEK inhibitor combination therapy

Tumor Cells Isolated from Ascites

Biomarker Predicting Treatment Outcome

CEER technology

to compare already existing technologies or new technologies with

close to market maturity

to evaluate their clinical utility

to generate data sets in the clinical setting that support regulatory

approval of the selected technologies as companion diagnostics

to show prognostic/predictive value of CTC/ctDNA/miRNA blood-

based biomarkers

to validate blood-based biomarkers for patient stratification and

monitoring of treatment response


Defining Standards for the Use of Blood-Based Biomarkers

Cancer-ID is a project funded by the Innovative Medicines Initiative Joint Undertaking (IMI JU).

Innovative Medicine Initiative:

Biofluid Based Biomarker Assays


37

All rights of sample donors are respected, e.g. via Cancer ID's Ethical AdBoard.

CANCER-ID Partners


Cancer-ID is a project funded by the Innovative Medicines Initiative Joint Undertaking (IMI JU).

CANCER-ID Set-up

We continuously explore technologies to overcome the need for tissues

biopsies and search for less invasive procedures

High sensitivity molecular pathway analysis protein level is possible and

can be used for patient stratification.

Apheresis enables the capturing of high amounts of CTCs, novel

approaches for CTC capturing show an improvement in yield of viable

CTCs.

Cultivation of CTCs will enable further molecular analysis for the benefit

of patients and the concept of personalised medicine.


Summary

Thank you for your attention!

Documents

CTCs: Capturing, Cultivation and Molecular · PDF filePage 3 • PMWC, January 25th 2016 What is needed to deploy CTCs as predictive biomarker in Personalized Medicine? 1. Standardization