miRNAs and biomarkers
Gabriella Sozzi
 diagnostic microRNAs in lung tumors
 stratifying lung cancer molecular subtypes ( Landi L. et al)
 prognostic microRNAS in tumors
 miRNA expression profiles to predict clinical outcomes of resectable
SCLC patients (Nan Bi et al)
 MicroRNAs associated with survival in malignant pleural mesothelioma
patients (Kirschner et al)
 diagnostic microRNAs in biological fluids
 sputum miRNA expression profiles for the detection of non-small cell
lung cancer (Razzak et al)
 plasma miRNA test for lung cancer screening (Sozzi et al)
 Biomarker-Driven Programs for Lung Cancer Screening
General considerations (Massion P.)
microRNA: a new
class of biomarkers
small noncoding RNAs that
regulate gene expression
by binding complementary
sequences of target
mRNAs and inducing their
degradation or translational
repression
Evolutionary conserved
One miRNA has multiple
targets
One miRNA
…
mRNA
mRNA
mRNA
mRNA
mRNA
Diagnostic/prognostic miRNAs in lung cancer
let-7a: target KRAS
Diagnostic miRNA signatures
Takamizawa et al., 2004
43 miRNAs (let-7a, miR-205, miR-126,
miR-21)
Yanaihara et al., 2006
miR-205  SCC; miR-21  ADC
Lebanony et al., 2009
34 miRNAs  ADC vs. SCC
Landi et al., 2010
Prognostic miRNAs
↓ Let-7a miR-155 in ADC
Takamizawa et al., 2004, Yanaihara et al., 2006
let-7a, miR-221, miR-137, miR-372 &
miR-182∗ Yu et al., 2008
↓ miR-34a: targets C-MET, BCL2
Gallardo et al., 2009
↓let-7a, -34a, 34c, 25, -91
Landi et al., 2010
Lung cancer meta-signature miRNAs
Urmo Võsa
Vo˜sa
Int. J. Cancer 2013
 20 published
miRNA studies
 598 tumor and 528
non-cancerous
samples
 15 miRNA
metasignature
 robust rank
aggregation method
microRNA : plasma/serum-based biomarkers for cancer
detection?
•Blood-based miRNA studies are
in their infancy
•miRNA remain rather intact and
stable in plasma/serum
•Simple universally applicable
assay for quantification (i.e. qRTPCR)
miRNAs have been found packaged in
exosomes derived from multivesicular bodies
(7) or be exported in the presence of RNAbinding proteins (i.e. Ago-2)(8) or might be
exported microvesicles shed during
membrane blebbing (9). Once in the
extracellular space, these miRNAs could be
taken up by other cells, degraded by RNases,
or excreted(10).
In lung cancer plasma/serum
levels of miRNAs might have
diagnostic (Silva, ERJ 2010;
Shen, Lab Invest 2010; Foss, J
TO 2011; Boeri PNAS 2011;
Bianchi EmboMolMed 2011;
Hennessey, PLoS One 2012) and
prognostic value (Hu, JCO, 2010).
MO 16.01: Different Micro-RNA Expression In Lung
Adenocarcinoma With Molecular Driver Events
Lorenza Landi1
Pierluigi Gasparini2, Stefania Carasi 2, Carmelo Tibaldi1 , Luciano Cascione2,
Greta Alì3, Armida D’Incecco1, Jessica Salvini1, Gabriele Minuti1 , Antonio Chella3 ,
Gabriella Fontanini3, Federico Cappuzzo1 and Carlo M.Croce2
1
2
Istituto Toscano Tumori, Dipartimento di Oncologia, Livorno Italy
The Ohio State University, Comprehensive Cancer Center, Department of Molecular Virology,
Immunology and Medical Genetics, Columbus, OH, USA
3 Azienda Ospedaliera Universitaria Pisana, Pisa, Italy
Trial Background:
•
Oncogenic driving mutations identify lung adenocarcinoma with different prognosis and
sensitivity to targeted therapy
•
Recent studies have suggested that miRNAs could be useful for stratifying lung cancer
subtypes, however miRNAs deregulation in NSCLC with ALK translocation, EGFR or KRAS
mutations is largely unknown
Aim:
• Identify miRNA signature differences according to the presence of specific oncogenic driver
Methods:
•
Retrospective analysis of a cohort of 67 NSCLCs matched with 17 normal lung tissues
•
RNA was isolated from FFPE using the Recover ALL kit (Ambion) and miRNA levels were
analyzed using the NanoString miRNA V2 panel
•
Data were processed according to manufacture guidelines. We used Limma to test for
differential expression analysis data
•
The miRNAs expression between tissues for all RT-qPCR was analyzed using the parametric
t-test (unpaired,2-tailed for validation)
MO 16.01: Different Micro-RNA Expression In Lung Adenocarcinoma With Molecular Driver Events - Landi L
Patient Characteristics
* other histology included patients with clear cell carcinoma; § EGFR wild type (wt) included patients EGFR wt and KRAS wt and ALK negative; ^
Codon 12 exclusively; ° defined by break-apart FISH assay.
MO 16.01: Different Micro-RNA Expression In Lung Adenocarcinoma With Molecular Driver Events - Landi L
Results
ALK +ve
Normal
EGFR WT
KRAS mut.
EGFR mut
Upregulated
Downregulated
hsa-miR-515 family expression in normal versus tumor and according to molecular events
hsa-miR-515 family
Normal
ALK pos *
EGFR WT*
EGFR mut*
KRAS mut*
miR-520d-5p+hsa-miR-518a-5p+hsa-miR-527
5.3
5.2
2.7
2.0
1.4
miR-520h
4.9
5.3
2.8
3.0
2.0
miR-548d-3p
5.7
5.0
2.6
2.5
1.3
miR-548q
5.5
3.7
2.0
1.8
1.3
7.1
5.7
2.5
1.8
1.5
miR-549
*p < 0.001
MO 16.01: Different Micro-RNA Expression In Lung Adenocarcinoma With Molecular Driver Events - Landi L
Conclusions
• miRNAs profile significantly differs in lung cancer
patients with ALK translocation, EGFR mutations and
KRAS mutations
• Prognostic and predictive role of several miRNAs are
currently under investigation
• miRNAs expression could represent an useful tool to
refine diagnosis of oncogene addicted NSCLC
• Targeting miRNAs could represent a potential strategy
to modulate sensitivity to biological agents
MO 16.01: Different Micro-RNA Expression In Lung Adenocarcinoma With Molecular Driver Events - Landi L
MicroRNA Signature Predicts Survival
in Resectable Small Cell Lung Cancer
Nan Bi, Jianzhong Cao, Yongmei Song, Jie Shen, Wenyang Liu, Jing Fan, Guogui
Sun, Tong Tong, Jie He, Yuankai Shi, Xun Zhang, Ning Lu, Qimin Zhan, and Luhua
Wang
Cancer Hospital and Cancer Institute, Chinese Academy of Medical Sciences &
Peking Union Medical College, Beijing 100021, China
Study Design
R
Patients
Training set
(n=42)
RNA
isolation
Testing set
(n=40)
Tissue
Normal Lung (n=3)
Microarray
Good prognosis
Identifying miRNA
signature associated
with overall
surivival
42 patients
Internal
validation
qRTPCR
Bad prognosis
40 patients
miRNA
analysis
Results (3)-Training Set (N=42)
The expression levels of miR-886-3p and miR-150 are lower in
SCLC tumors than those in normal lung tissues.
miR-886-3p
miR-150
4000
5000
P=0.05
3000
P=0.09
4000
3000
2000
2000
1000
1000
0
0
NL
SCLC
NL
N=3
N=42
N=3
SCLC
N=42
Results (3)-Training Set (N=42)
miRNA signature:
0.545microRNA150 + 0.617microRNA886-3p
P=0.02
100
OS(%)
80
Low risk (N=21) MST
not reached
60
40
High risk (N=21) MST =
20 12.6 months
0
0
12
24
36
48 D 60
Months
72
84
96
Results (5)-Test Set (N=40)
P=0.005
100
OS(%)
80
60
Low risk (N=20) MST
not reached
40
20 High risk (N=20) MST =
18.9 months
0
0
12 24 36 48 60 72 84 96 108 120
Months
Results (6)- MiRNA Signature Predicts PFS in both
Training and Test Groups
B
100
80
80
Low risk
PFS(%)
PFS(%)
A
60
40
High risk
20
100
Low risk
60
40
High risk
20
P=0.017
P=0.045
0
0
0
12
24
36
48
60
72
84
Months
Training group (N=42)
96
0
12 24 36 48 60 72 84 96 108 120
Months
Test group (N=40)
Results (7)- Multivariate Regression Analysis of MiRNA
Signature and Survivals in Test Set (N=40)
Variable
Hazard Ratio
95%CI
P value
miRNA signature (low risk vs high risk)
0.26
0.10-0.69
0.007
Age (≥60 vs <60)
1.96
0.77-5.02
0.16
Gender (female vs male)
1.12
0.11-11.71
0.92
Smoking status (no smoking vs smoking)
0.57
0.07-4.49
0.60
0.36
0.15-0.86
0.02
Age (≥60 vs <60)
1.45
0.60-3.52
0.41
Gender (female vs male)
1.15
0.11-11.73
0.91
0.45
0.06-3.46
0.44
Overall survival
Progression-free survival
miRNA signature (low risk vs high risk)
Smoking status (no smoking vs smoking)
Conclusion

A miR-150/miR-886-3p signature was correlated with the
survivals in 42 resectable SCLCs and validated independently
with another 40 SCLC cases.

The expression levels of both miR-150 and miR-886-3p were
lower in tumors than in normal lung tissues, indicating both of
them could serve as tumor suppressor genes in SCLC.

MicroRNAs may serve as promising prognostic markers as well
as noval therapeutic targets for SCLC.

Larger sample size and function studies are warranted to
validate our findings.
MicroRNAs miR-17-5p, miR-21 and
miR-210 are associated with survival in
malignant pleural mesothelioma patients
undergoing extrapleural pneumonectomy
Michaela B Kirschner1,
Yuen Yee Cheng1, Steven C Kao1,2,
Brian C McCaughan3,4, Nico van Zandwijk1, Glen Reid1
1Asbestos
Diseases Research Institute, University of Sydney
of Medical Oncology, Sydney Cancer Centre
3Cardiothoracic Surgical Unit, Royal Prince Alfred Hospital Sydney
4The Baird Institute and Sydney Medical School, University of Sydney
2Department
Patient characteristics
• Patients undergoing EPP in Sydney between 1994 and 2009:
– Series previously used to assess NLR and Calretinin (Kao et al, JTO, 2011)
– Complete Cohort = 85
– Patients with RNA = 64
Training Set (microarray+RT-qPCR)
Test Set (RT-qPCR)
Variables
Long survivors
(N=8)
Short survivors
(N=8)
Median Age
(range)
51.5 (37 – 64)
62 (47 – 70)
6
2
6
2
Gender
Male
Female
37
11
8
0
8
0
Histological
Subtype
Epithelioid
Biphasic
31
17
0
1
7
0
0
0
8
0
Gender
Male
Female
Histological
Subtype
Epithelioid
Biphasic
Variables
All patients
(N=48)
Median Age
(range)
58 (22 - 74)
Stage
Stage
I
II
III
IV
Induction
Chemotherapy
Yes
No
Median survival
(mo)
0
8
0
8
57.2 ( 45.83 – 90.48)
6.4 (1.94 – 8.28)
I
II
III
IV
2
8
32
6
Induction
Chemotherapy
Yes
No
13
35
Median survival
(mo)
15.28 (0.07 – 81.18)
Kaplan-Meier and Multivariate Analysis
• Classic prognostic factors (N=48):
– Female gender (49.8 mo vs 14.6 mo in males, p=0.019)
– Epithelioid histology (18.17 mo vs 12.16 mo in biphasic, p=0.048)
28.2 mo
19.7 mo
24.2 mo
9.4 mo
13.3 mo
13.3 mo
(p=0.001)
(p=0.005)
(p=0.031)
• Cox-Regression for each microRNA combined with classic prognostic factors (Histology, age,
gender, stage)
Hazard
Ratio
miR-17-5p
Low
High
2.26
95 % CI
p-value
Factor
1.04 – 4.93
1 (ref)
0.041
miR-21
Low
High
Hazard
Ratio
4.12
95 % CI
p-value
Factor
1.86 – 9.14
1 (ref)
<0.001
miR-210
Low
High
Hazard
Ratio
95 % CI
p-value
1.46
0.73 – 2.89
1 (ref)
0.283
Conclusions and Future Directions
• Lower expression levels of three microRNAs in tumour tissue are associated with
longer survival of patients undergoing EPP
• miR-17-5p and miR-21 remain significant in a multivariate model including classic
prognostic factors
Those microRNAs have the potential to assist in better selection of patients
considered for EPP
• Validation in independent samples sets is required
• Combination of several microRNAs as potential prognostic signature
miRNAs in biological fluids
• P2.20-011 | A prospective clinical study
evaluating stage dependent sputum micro-RNA
expression profiles for the detection of nonsmall cell lung cancer
• Authors: Rene Razzak1, Eric L.R. Bédard1, Julian
O. Kim2, Sayf Gazala1, Linghong Guo2, Sunita
Ghosh2, Anil A. Joy2, Tirath Nijjar2, Eric Wong1,
Wilson H. Roa2
1University of Alberta, Edmonton, AB/CANADA,
2Cross Cancer Institute, Edmonton, AB/CANADA
Our objective was to utilize an efficient, cost-effective panel consisting of 3
miRNAs (miR-21, miR-210 and miR-372) for prospective validation as a potential
means of accurately detecting NSCLC. This panel was selected based on
retrospective analysis of 11 miRNAs our group had previously undertaken using
separate NSCLC and control cohorts.
• 21 early NSCLC (≤ Stage II) patients, 22 advanced NSCLC (≥
Stage III) patients and 10 control subjects were
prospectively accrued. A single sputum sample was
obtained through spontaneous expectoration from each
study participant.
• miR-21, miR-210 and miR-372 expression was conducted
on each sputum sample and normalized to an
endongenous control (U6) relative to a MRC-5 reference
sample, using RNA reverse transcription and Quantitative
real-time Polymerase Chain Reaction (RT-qPCR).
• Statistical evaluation consisted of unsupervised
hierarchical cluster analysis of the experimentalnormalized miRNA expression profiles using within-group
linkage.
Comparing early NSCLC to controls, the
use of miR-21, miR-210 and miR372
expression yielded a diagnostic
sensitivity of 66.7% and a specificity of
90.0%. Advanced NSCLC patients had an
improved sensitivity of 81.8% with the
same specificity of 90.0%.
The utilization of miR-21, miR-210 and
miR372 sputum expression might
provide a sensitive and specific means
of detecting NSCLC. The potential
linkage between their expression and
NSCLC stage may account for the higher
sensitivity observed in the advanced
NSCLC group. Future use of this
promising panel on a larger population
will be required to establish its potential
application as a screening tool.
Plasma miRNA test for lung
cancer screening
Gabriella Sozzi
2005 - 2011
4,000
Smokers ≥
50 years
Smoking cessation
Lung function assessment
blood sampling
R
> 100,000 biological samples
+ LDCT
R
LDCT
every year
LDCT
every 2
years
Pastorino U. et al., Eur J Cancer Prev. 2012
1000 controls
(no disease)
Study
Design &
Aims
130 samples
(13%):
haemolyzed
870 controls
suitable for
analyses: 594
LDCT arm; 276
observational arm
 Diagnostic performance of miRNA test (3 levels,
H-I-L risk MSC classifier) for lung cancer detection
across LDCT and observational arms
85 lung
cancer
patients
9 patients
(11%) :
samples not
available
7 patients
(9%):
haemolyzed
samples
69 Lung Cancer
patients:
26 pre-diagnosis
only; 28 at & prediagnosis; 15 at
diagnosis only
 Combination of LDCT and plasma miRNA test
 Prognostic value of the miRNA assay
Sozzi G. et al., in press
Diagnostic and prognostic performance of MSC
Total
MSC (risk of lung cancer)
Intermediate
High (H)
(I)
Low (L)
All subjects
939
63 (6.7)
159 (16.9)
717 (76.4)
No lung cancer
870
32 (3.7)
130 (14.9)
708 (81.4)
Lung cancer
69
31 (44.9)
29 (42.0)
9 (13.0)
performance*
SE=87%, SP=81%, PPV=27%, NPV=99%
Lung cancer deaths+
19
12 (63.2)
6 (31.6)
1 (5.3)º
Lung cancer, stage Iǂ
Lung cancer, stage IIIIIǂ
37
14 (37.8)
19 (51.4)
4 (10.8)
12
5 (41.7)
4 (33.3)
3 (25.0)
Lung cancer, stage IVǂ
19
11 (57.9)
6 (31.6)
2 (10.5)
*SE,
SP, PPV and NPV were calculated combining pre-specified MSC High and Intermediate versus Low risk.
+P=0.0366, based on the Cochran-Armitage test for trend in the proportion of deaths across strata of MSC risk
groups among subjects with lung cancer.
º plasma sample obtained 30 months before disease detection.
ǂ tumor stage information was not available in one patient.p=0.49 for association of MSC with tumor stage
Sozzi G. et al., in press
Time dependency analysis of diagnostic performance of MSC, at 6, 12, 18
and 24 months intervals between blood sampling and lung cancer diagnosis
( according to Heagerty PJ )
Months from blood
sampling to lung
cancer detection
SE
SP
PPV
NPV
6
83%
80%
18%
99%
12
86%
81%
22%
99%
18
86%
81%
23%
99%
24
87%
81%
25%
99%
Sozzi G. et al., in press
Modulation of the miRNA signatures in plasma samples collected pre-disease,
at time of disease and after surgery (disease-free) from 20 pts
H
miRNAs returning miRNAs remaining
at the normal
deregulated after
levels after surgery
surgery
660
451
106a
197
17
142-3p
92a
320
486-5p
28-3p
I
L
Pre
H
Pre
-
Median time 20
months (5-28)
At
surgery
At
Median time 18
months (4-46)
Post
Patient developing a
second primary lung
cancer
At II
H
At
surgery
I
I
Patient developing
surrenal metastases
LDCT +
L
L
-30
Post
Post II
Post
-20
-10
0
10
20
30
Months from first surgery
40
50
0
2
4
6
Months from CT detection
8
Biomarker-Driven Programs for
Lung Cancer Screening
Pierre P. Massion, MD
Thoracic Program
Vanderbilt University
Nashville, TN
WCLC
Oct 30th, 2013
Diagnosis
Biomarkers in the natural history of lung cancer
BM of risk
Diagnostic
BM
BM of
Response
Early Lung cancer diagnostic biomarkers
Sullivan-Pepe, JNCI 2001- EDRN
Candidates
Phase 1
Phase 2
Phase 3
Phase 4
Phase 5
Discovery, Prediction
Assay validation
Retro-longitudinal
Prospective screening
Cancer Control
MALDI TOF MS profiling
x
x
x
Autoantibodies
x
x
x
Specific antigens /proteins
x
x
x
miRNA
x
x
x
DNA methylation Blood
x
x
Circulating Tumor cells
x
TUMOR/airway epith
Preinvasive histo/cytology
x
x
x
DNA methylation
x
x
x
RNA airway signature
x
x
x
MALDI MS profiling
x
x
Chromosome aberrations
x
x
DNA Methylation Sputum
x
x
DNA CN -FISH
x
x
VOCs
x
x
SERUM/PLASMA
SPUTUM/EBC
x
x
Low probability
Indeterminate Pulmonary Nodules
(6-15 mm)
High
Prob
Risk model
Low probability
Risk model + Biomarkers
Low probability
IPN
PET or Biopsy
Low
Prob
Risk increase
Risk reduction
Low
Prob
Low
Prob
High
Prob
IPN
PET or Biopsy
High
Prob
Decrease rate of invasive bx, futile thoracotomy
Decrease in cost, radiation and anxiety
37
How good should the biomarker be?
• Better than standard of care.
• What are the metrics?
-
Performance of the test: PPV & NPV
ROC curves (TPR vs FPR). C index comparison
Net reclassification Improvement (NRI) index
Change in decision making.
• De-emphasize Sensitivity and Specificity
–
–
–
–
–
–
Pecot, CEBP 2012
Irrelevant (except in early phase of marker evaluation)
Not stable across populations
Require dichotomization of marker values (loss of information)
No information on added value
Not actionable metric; PPV or NPV are.
Independent of the prevalence of the cancer.
Plasma C4d levels (a stable complement split product) in early
C4d in plasma samples
from
early lung cancer
stage lung
cancer
Phase 2
N=50
N=50
Ajona et al, JNCI 2013
C4d levels in screening detected lung cancer
N=158
N=32
Ajona et al, JNCI 2013
A Blood-Based Proteomic Classifier for the Molecular
Characterization of Pulmonary Nodules
Phase 3
• Shotgun Proteomic analysis of tumors.
• Selected candidate proteins for testing in the blood
• Developed 13 multiple reaction monitoring MRM
assays. LRP1, BGH3, COIA1, TETN, TSP1, ALDOA,
GRP78, ISLR, FRIL, LG3BP, PRDX1, FIBA, GSLG1
• Training and testing algorithm.
Li et al. Sci Transl Med. 2013 Oct
13 MRM predictor of lung cancer
among 247 lung nodules 4-30 mm (prev 15%)
A negative test implies a >2
fold decrease risk for cancer.
High NPV of the test would
obviate 1/4 patients with
benign nodules from a biopsy
Discovery
Validation
Validation 2
N=
143
104
37
Sens Spec
82
66
71
44
79
56
NPV
95
90
94
PPV
30
18
24
Li et al. Sci Transl Med. 2013 Oct
7 Autoantibody signature
Phase 4
CAGE, GBU 4–5, HER2, p53, c-myc, NY-ES0-1 and MUC1
Boyle, Annals of Oncology 2010
Lam, Cancer Prev Res 2011
Chapman Tum. Biol. 2012
Jett, Lung Cancer 2013 in press
7 Autoantibody signature
EarlyCDT- Lung Oncimmune
189 nodules tested with the 7 AAB test
Profile +
Profile -
Cases
19
24
43
Controls
17
129
146
36
153
Sensitivity
Specificity
PPV
NPV
Prevalence
RR
44.2
88.4
52.8
84.3
0.23
3.36
In nodules 8-20 mm, the RR is 4.6
P2.20-006 | Autoantibodies to a panel of lung cancer-associated antigens can provide
significant discrimination between malignant and non-malignant lung nodules
P. Massion
44
Personalizing the management of
indeterminate pulmonary nodules
45
Clinical utility of a diagnostic biomarker:
study design
Positive
test
Negative
Randomize
IPNs
No test
SOC
(Guidelines)
Biopsy
3 mo CT F/U
Biopsy
Outcomes:
Early stage
Futile Thorac.
Survival
Decrease cost
3 mo CT F/U
Randomization of nodules based on the use of a biomarker test.
Proves that biomarker “+” affects patients outcome
Proves that biomarker test affects patients outcome when compared
with unselected use of same Standard Of Care.
Conclusions
• Many early detection candidate biomarkers exist
• Few are validated or tested in preclinical setting. Priority
to validate existing candidates.
• We need to de-emphasize Sensitivity and Specificity and
emphasize NPV or PPV with change in decision making.
• BM should provide knowledge about added value and
therefore should be integrated to clinical, laboratory and
imaging routine data.
• To demonstrate clinical utility requires significant
investment in effort and resources towards biomarkers
driven clinical trial.