Circulatory miRNA biomarkers as “liquid biopsy” in diseases – Hope or Hype?

Evidence-based approach: circulatory miRNA biomarkers

Circulating microRNAs in cancer: Hope or hype?

Lessons learnt

HP Too

Clinical spaces/domains: Cancer, Cardiovascular, Diabetes, Immunology, Neurosciences, Viral Biology etc

> 430 (Sept 2017) clinical trials on miRNA globally: biomarkers & therapeutics

An emerging field in Diagnostics & Therapeutics

What are microRNA?

~ 2000 mature human miRNA

Average mRNA length ~ 1.4 kb mRNA

miRNA

Relative length

5’-gcuacuucacaacaccagggcc-3’ hsa-miR-138-1-3p

18th Feb 2016 Medicare

20th Aug 2015 Blue cross Blue shield

miRNA tests are now reimbursable – solid tumor

Rosetta Genomics

What has changed…. “small but Masterful”

“Central Dogma” in Molecular Biology

“Servant”

RNA merely plays an accessory role

DNA mRNA PROTEIN

Genetic information

Information carrier: “messenger”

‘Workhorse’

http://www.mirbase.org/

Front Mol Neurosci. 2015; 8: 4

Paradigm Shift

“Master”

Non-coding RNA (eg. miRNA) as regulators of gene expression

DNA mRNA PROTEIN

miRNA 5’-gcuacuucacaacaccagggcc-3’

All cells make & use miRNA

Growing interest: miRNA as Novel Liquid Biopsy

Cells-based

Circulatory tumor cells (CTC)

Cell-free

Extracellular vesicles Proteins/ Metabollites

Nucleic acids

cfDNA (100-200 bp)

Coding RNA (>1000 bp)

Noncoding RNA (miRNA ..)

ALL biofluids contain miRNA

Present in all biofluids examined

Low abundance

Nat. Rev. Clin. Oncol. 11, 145–156 (2014) Nat Rev Neurol. 11:556-66 (2015)

miRNA

Diagnostic Biomarkers

Prognostic Biomarkers

Predictive Biomarkers

Companion diagnostic biomarkers

“liquid biopsy”

What makes miRNA a good circulatory biomarker

Excellent choice as biomarkers

Highly accessible

Extremely stable in biofluids

Extremely stable with storage

Serum & Extracellular vesicular miRNA can be stored on paper-based matrix

Ease for distribution

FTA storage 250C > 6 months

Unmet needs

I. “Invasive tools (endoscopy, biopsy) available, no good biomarkers”: Gastric cancer

II. “Existing tool (mammography) but not so good” : Breast cancer

III. Other examples: colorectal, lung & non-oncology based

Examples of clinical studies using serum/plasma

Compliance

Discovery: qPCR

Final test: qPCR

Experimental approach Biobanks

Clinical Team

Prof Yeoh Khay Guan

Prof Jimmy So

Dr Zhu Feng

Prof Yong Wei Peng

Prof Koji Kono

Dr Rha Sun Young

Technology & Dx Team

Dr Thomas Li (DXD hub)

Dr Zhou Lihan

Dr Zou Ruiyang

Health Economics Specialists

Prof Teo Yik Ying

Dr Yoong Su-Yin

Prof Chia Kee Seng

Dr Lotte Steuten

I. Gastic cancer circulatory miRNA biomarker program

Assemble clinicians, technologists/scientists, Healthcare economists

Define clinical unmet needs & intended use

SGCC- National initiative in cohort studies since 2007

Addressing unmet needs

Clinical Unmet Needs

Late manifestation, high mortality

No accurate blood test (helicobacter/pepsinogen < 0.7 AUC)

Gastroendoscopy/biopsy: highly invasive/costly/ low compliance/ specialists

Determine the need for endoscopy/ biopsy

Improve early diagnosis and reduce health-care cost

High Risk Subjects [Age > 45; Symptomatic]

Clinic Endoscopy

Gastric cancer (~0.1-0.6%)

Cancer free (>99%)

Current clinical practice

Serum

miRNA test

High

Medium

Low

Score

Follow up

Intended use

Discovery to validation

100-200 l serum Discovery Phase

Validation Phase

Productization Phase

Test <50 l serum

Blinded Clinical Validation

n=3 n=4 n=5 n=6 n=7 n=8 n=9 n=100.65

0.7

0.75

0.8

0.85

0.9

0.95

1

0.800

0.741

0.847

0.801

0.877

0.838

0.904

0.855

0.918

0.876

0.928

0.881

0.935

0.888

0.940

0.889

Discovery

Validation

AU

C

***

***

***

**

Number of miRNAs in the biomarker panel

Biomarker cross-validation

Performance of multi-

variant biomarker panels

Development Roadmap & Clinical Cohorts

Biomarker Discovery Development

Phases Biomarker Validation Clinical Validation Productization

SGCC 1 Schedules

N=236

SGCC 2

N=236

SGCC 3 (Blinded)

N=89

Korean (cross-

population)

N=186

BnB Cohort

Other Cohorts

N=7000 N>1000

Regulatory compliance

miRNA Candidates

600 320

75

320

Panels of <24 miR Test Kit IVDMIA algorithm

In Vitro Diagnostic Multivariate Index Assay (IVDMIA) - FDA

Developmental Roadmap

2015 2016 2017 2018 2019 2012-14

Biomarker Discovery

Productization

Analytical Validation

SG Clinical Validation

(N=7,000)

China Clinical Validation

(N=10,000)

Korea Clinical Validation

(N=3,000)

HSA Registration

cFDA Reg-istration

kFDA Reg-istration

Expanding utility miRNA liquid biopsy for monitoring treatment response

Progression-free survival (PFS)

Overall Survival (OS)

3 12 1

miRNA - treatment monitoring

Intended use Blood-based breast cancer screening test to determine the need for follow up imaging and biopsy in women above 45.

II. miRNA for Breast Cancer High-risk Screening

Prof M Hartman Prof Ann Lee

Technology Team

Dr Zhou Lihan

Dr Zou Ruiyang

Issues with Imaging Accuracy

Mammogram sensitivity significantly reduced in dense breast

Asians have higher breast density than Caucasians

Overdiagnosis results in Unnecessary biopsies

Quality of life

Healthy Stage 1 BC

Distinct Early Stage Cancer Signature

[DCIS (Ductal Carcinoma In-

Situ)/Stage 0]

Consistent Performance in European, Asian and US Cohorts

Cross-population Validation of Serum miRNA Biomarker in Stage I & 2 Breast Cancer

Are circulating miRNA Biomarkers Cancer Specific?

Ovarian Cancer Gastric Cancer

Breast Cancer

2

1

6 16

14 12

27

Ovarian Cancer Gastric Cancer

Breast Cancer

0

0

0 13

7 11

25

Up-regulated miRNA Down-regulated miRNA

III. Other Indications

Examples of other cancers & non-cancers

Lung (NSLC) cancer Colorectal cancer

Cardiovascular

(* many others not discussed)

III. Others: Biomarker Panel for lung cancer

Multisite collaboration

MNC

China Case-Ctrl 1 (N=431)

China Case-Ctrl 2 (N=448)

China Clinical validation 1 (Screening) N>3000

Biomarker Discovery

Development Phases

Biomarker Verification

Analytical and Clinical Validation

Kit Prototyping and Pre-clinical validation

2015 2016-2017 2018 Jan - Jun 2018 Jun – 2019 Dec

Development Roadmap

Serum miRNA Candidates

500 320

145 39

China Clinical validation 2 (Aid-to-diagnosis) N>2000

Singapore Prospective N>1500

12

China Case-Ctrl 3 (n=252)

China Case-Ctrl 4 (n=467)

Singapore Case-Ctrl 1 (n=65)

High Risk (Smoker)

Average Risk Population

Average Risk Population (Chinese/Indian/Malay)

High Risk (Smoker)

Independent site Control/Lung disease/Cancer

Cohorts

Early Stage Cancer

Differentiate high-risk subjects/control (aged >50 yr) from early stage (0+1+2) CRC cases

Serum – 150 samples/ 360 miRNA

4-miRNA panel identifies early stage cancer from control with AUC 0.952

Serum miRNA biomarkers for colorectal cancer

Current Gold Standard: Plasma BNP or NT-pro-BNP

Unmet Needs

NT-proBNP is Sensitive but NOT specific in diagnosing heart failure

Stratification of two heart failure subgroups is NOT accurate

Chronic heart failure

MiRNA Provides Complementary Information to NT-proBNP

6-miR panel classifies NT-proBNP false positive and negative with >90% accuracy

Clinical Gold Standard (NT-proBNP) generates false positives & false negatives

Study design 265 Heart Failure patient o Standard treatment practice followed-up

for 3 years

3 or more miR biomarker panel can stratify risk groups

Developmental Plan

Biomarker Discovery

Analytical Validation

Clinical Validation

Signature Verification Stages

Heart Failure

Singapore Cohort 1

Caucasian Cohort

Singapore Cohort 2

Other Cohorts

Test Prototyping

Prospective Clinical Test

N =130

Control (age matched) HF-REF HF-PEF

N =434 N =131 N > 1000

A 6-miRNA-classifier separates HF from normal control o Outperforms BNP (AUC 0.8 to 0.9)

o IVDMIA of miRNA panel and BNP should achieve better diagnostic power

Where do these microRNA comes from and what forms are they in?

Does the circulatory miRNA comes from the tumor in vivo?

PDX tissue/ serum of different cancers are matched

Patient Derived Xenograft (PDX) Models

hsa-miR-1299 hsa-miR-550a-5p hsa-miR-589-5p hsa-miR-629-5p hsa-miR-629-3p

Specific human miRNA are found in serum of gastric cancer PDX model

Are extracellular miRNA functional?

miR-200–containing extracellular vesicles promote breast cancer cell metastasis (J Clin Invest. 2014;124(12):5109–5128)

MiR-122 overexpression reduces primary tumour growth while enhancing metastasis

Breast cancer-secreted miR-122 reprograms glucose metabolism in pre-metastatic niche to promote metastasis (Nat Cell Biol. 2015; 17(2): 183–194)

Melanoma miRNA trafficking controls tumour primary niche formation (Nat Cell Biol. 2016;18(9):1006-17)

Reprogramming cancer associated fibroblast

Adipose-Derived Circulating miRNAs Regulate Gene Expression in Other Tissues (Nature. 2017; 542(7642): 450–455)

Tissues / Tumor + niche

System responses

Clin Chem. 61:1138-55; 2015 Nat Rev Clin Oncol. 11:145-56, 2014 Nat Rev Gastroenterol Hepatol. 11:350-61, 2014 Nat Rev Endocrinol. 9:513-21, 2014

Protein complexes (Ago2, nucleoplasmins)

Apoptotic bodies Extracellular Vesicles (Exosomes,Microvesicles, Melanosomes, Oncosome)

HDL Passive release

What do we know today -forms of circulatory miRNA

Effects of miRNA

Biofluid

Lessons learnt

What we have learnt so far….

Circulating microRNAs in cancer: Hope or hype? Cancer Letters 381 (2016) 113–121

Emerging appreciation that this is NOT as simple as was envisaged initially

Technical & Non-technical challenges

Issues confounding the use of miRNA as liquid biopsy

Discovery & Validation Roadmap

Pre-analytics

Analytics

Clinical validity

Clinical Utility

Henry & Hayes. MOLONCOL 6:140-2012 Hayes et al. J Natl Cancer Inst. 88:1456-66 – 1996

* Pepe et al, J Natl Cancer Inst. 2001 Jul 18;93(14):1054-61

Study design

Pre-analytics Standard operating procedure for sample procurement/

handling/ storage Sample preparation & quality (hemolysis/isolation)

Analytics Sensitive/specific Reproducibility (intra- interassay variation) Assay efficiency (copy number determination) Internal/ external controls Normalization of data

Study design Sample selection (control/age/gender/co-morbidity) Powering of study (number of sample analysed) Well defined clinical indications & data

Need a robust, highly sensitive and consistent assay

Analytics Challenges : robust sensitive assays

Technology benchmarking study: Nat Methods. 2014 qPCR technologies outperform microarray and sequencing in terms of detection sensitivity and specificity, especially in Biofluid (serum)

Nature Methods (2014);

Inconsistency & poor performance of miRNA assays. [Clinical Chemistry (2011); PLoS ONE (2013); Nature Methods (2014); J Clin Med. 2015 Oct 23;4(10):1890-1907]

>500

>500

Integrated workflow & technology = robust miRNA signatures

Assay Design proprietary Algorithms

Reagent

Experimental Design (normalization)

Bionformatics

Technology Technical know-how

Data

Integrated Platform

MIQE compliant & validated

RNA (2010) 16(7):1436-45 US61/354,683, 2010

Designing miRNA assay is demanding: 5’-gcuacuucacaacaccagggcc-3’ hsa-miR-138-1-3p

Highest sensitivity & specificity (> 7 logs in serum) and robustness.

Low abundant miRNA in serum has high value

5L blood to dilute samples

Many miRNAs (100-10000 copies/ml) have excellent diagnostic power - importance of assay sensitivity.

Method 1

Method 2

Method 3

Our assays

Technical Reproducibility

Samples: 30 Normal and Gastric Cancer Patient Serum miRNA targets: 214 Expression range: 102 – 109 copies

Measu

rem

ent

1

Measurement 2

Measurement 1: Dec 2012, TriZol RNA Isolation / qPCR on BioRad CFX 384

Measurement 2: Sep 2013 QiaCube RNA Isolation / qPCR on LifeTech ViiA7

2 different teams

Instrument number

384 sample run I II III

Max Ct 21.164 21.164 21.025

Min Ct 20.678 20.589 20.555

Max-Min Ct difference 0.486 0.575 0.470

Mean Ct 20.960 20.921 20.847

SD 0.079 0.101 0.082

Median Ct 20.972 20.924 20.854

Max-Median Ct difference 0.191 0.240 0.171

Min-Median Ct difference -0.295 -0.335 -0.299

Well-Controlled High throughput assay is critical for Biomarker Discovery – not trivial to set up

Controls, controls & more controls

Copy number of miRNA/ml biofluid

Independent validation by 2 Multinational companies

Central to success of study Biobanking of samples – A big challenge

Quality samples

Technology

“Rubbish in rubbish out”

Results

Biobank

Clinical collaborations Clinical centres

Ecosystem

Pre-analytics Standard operating procedure for sample procurement/ handling/ storage

Hemolysis A cautionary tale of using circulatory miRNA

RBC miRNA

Many clinical samples are not good. Differences: processing tubes, time, temperature, handling etc

Harmonization of discovery/validation cohort preanalytics Biobanking

RBC miRNAs

Non RBC miRNAs

Hemolysis score

RBC – Non RBC

0 1 2 3 4 5 6 7 8 950

100

150

200

250

300

0 2 4 6 8 10400

450

500

550

600

650

0 2 4 6 8 10300

350

400

450

500

550

0 2 4 6 8 10400

450

500

550

600

650

0 2 4 6 8 10300

350

400

450

500

550

De

cre

ase

Co

rre

lati

on

wit

h R

BC

Pre-analytics Sample preparation & quality (hemolysis/isolation)

What’s next…. from discovery to utility

Established regulatory compliant manufacturing center, trial, R&D facilities

Manufacturing @ JTC Medtech One, Singapore (2016)

Singapore Hangzhou SciTechPark (2016)

ncRNA center miRNA liquid biopsy

International Research Center

Dedicated miRNA profiling facility with highest throughput globally 35 units of Applied Biosystems QS5-384 Throughput of 200,000 qPCR reactions per day

Continue with discovery of circulatory miRNA signatures addressing clinical unmet needs

miRNA as liquid biopsy no longer a hype but reality & opportunity

Thank you