MiRNAs as novel biomarkers for dysplsia in IBD associated cancer

MicroRNAs as novel biomarkers for neoplastic progression in
Inflammatory Bowel Disease
Dr. Gerhard Jung, MD, PhD
Results from a retrospective study with a prosepective validation cohort
Gerhard Jung (jung@clinic.cat)*, Isabel Quintanilla*, Mireya Jimeno, Juan José Lozano, Jordi Camps, Sabela Carballal, Luis Bujanda, Maria Isabel
Vera, Enrique Quintero, Marta Carrillo, Montserrat Andreu, Miriam Cuatrecasas, Antoni Castells, Julià Panés, Elena Ricart, Francesc Balaguer,
Maria Pellisé (mpellise@clinic.cat)
* Both Authors contributed equeally.

Conflicts of interest
Possible conflicts of interest:
• FB: I have endoscopic equipment on loan of Fujifilm, I receive an honorarium for
consultancy from Sysmex, and speaker’s fee from Norgine.
• MP: I received research grant from Fujifilm, received consultancy fee from Norgine
and speaker’s fee from Olympus, Norgine, Casen Recordati and Janssen.
The speaker of this talk and the rest of the authors do not have any conflicts of
interets to declare.

Backgroud Aims Design & Methods Results Discussion Conclusion
Inflammatory Bowel Disease (IBD) is associated with a higher risk of Colorectal
Cancer (CRC): OR 3.09 (CI 1.50-5.75) for extensive colitis compared to general population1,2.
The pathophysiologic model postulates that repeated cycles of inflammation cause
oxidative stress which ends up damaging the DNA and this induces finally a
carcinogenic transformation of the mucosa through its premalignant lesions: low
grade and high grade dysplasia3.
Negative
for
dysplasia
Indefinite
dysplasia
Low grade
dysplasia
High grade
dysplasia
Adenocarcinoma
Sustained
Chronic
Inflammation
1 Stewenius, J. et al. Int J Color. Dis 10, 117–122 (1995)
2 Manninen, P. et al. J Crohns Colitis 7, e551-7 (2013)
3 Saraggi, D. et al. Dig Liver Dis 49, 326–330 (2017)

Inflamation Dysplasia Colitis associated Cancer
Detect and treat this... ...to prevent this!
The aim of actual surveillance strategies is to detect the premalignant lesion: the
dysplasia by repeated colonoscopies, generally every year, beginning from 8-10
years of disease onset1,2.
1 Magro, F. et al. J. Crohns. Colitis 11, 649–670 (2017)
2 Rutegard, Met al. Scand J Surg 106, 133–138 (2017)

Dysplasia as a biomarker for colitis associated CRC risk has important shortcomings:
Inflammation
Regenerative lesion
Low grade dysplasia High grade dysplasia Cancer
Indefinite dysplasia
1 Van Assche G et al. J Crohn’s&Colitis 2012
2 Melville, et al. Hum Pathol 1989
3 Sanduleanu, S et al. Gastrointest. Endosc.
Clin. N. Am. 2014
4 Levi, Am J Surg Path 2006
Histologically tricky to differentiate between regenerative lesions and dysplasia.L1
High inter-observar variability in differentiating low grade and high grade dysplasia2.L2
High risk for interval cancers compared to sporadic cases due to not detected lesions3.L3
Some CRCs develop without previos dysplasia or pass directly from LGD to HGD4.L4
Difficult to differentiate inflammation associated dysplasia from that which occurs in sporadic polyps.L5
Tubular adenoma with LGD Sporadic CRC
https://es.slideshare.net/lhumbertocc/plipos-en-colon https://en.wikipedia.org/wiki/Colorectal_cancer

New biomarker are needed to identify IBD associated dysplasia.
An ideal biomarker should be
Minimally or non-invasive, preferrably testable in blood or stool, in
order to avoid unnecessary colonoscopies.
Very sensitive:
Detect all patients at risc, independently if they have visible
premalignant lesions or not.
Very accurate and specific:
Differentiate between inflammation associated dysplasia from the
sporadic pathway, in order to avoid unnecessary colectomies.
The management depends
on a correct diagnosis of
the dysplasia and can
change radically depending
on the histological and
clinical findings.
Endoscopic suerveillance
Segment resection
Proctocolectomy
Endoscopic resection: en bloc, EMR, ESD

Micro-RNAs (miRNAs)
•Small molecules(20-22 nucleotides).
•Do not code for proteins.
•Regulate gene expression (around
60% of all human genes) on a post-
transcriptional level by binding to
their corresponding mRNA =>
degradation or block of the
translational machinery.
Image from: Moein S, J Cell Physiol. 2019 Apr;234(4):3277-3293.
Ideal candidate as new biomarkers, because:
They are small and stable in diferent biological specimens.
Detectable in blood (circulating miRNAs).
Can regulate hundreds of mRNAs.
Limited total number compared to mRNAs (around 2,000 are known).
Have been associated to different pathways that are important for inflammation and carcinogenesis.
Have proven their potential as new biomarkers for sporadic CRC.
BUT: their role in IBD associated CRC is unclear.
Hutchison, J et al. Cancer Genet 206, 309–316 (2013)
Chapman, C. G. & Pekow, J. Therap. Adv. Gastroenterol. 8, 4–22 (2015)
Kanaan, Z. et al. Hum Mutat 33, 551–560 (2012)

Identify miRNAs associated with dysplasia in
Inflammatory Bowel Disease.
Identify those miRNAs that:
Are deregulated across the sequence normal mucosa – dysplasia – colitis associated CRC
Identify the dysplasia with a high diagnostic accuracy
Are specific for colitis associated CRC (and different to sporadic cancer)
Validate the results in an independent cohort
AimsBackground Design & Methods Results Discussion Conclusion

Multicentric case cohort:
•Hospital Clínic de Barcelona
•Hospital Universitario de Donostia
•Hospital Universitario Puerta de Hierro
•Hospital Universitario de las Islas Canarias
•Hospital Universitario del Mar, Barcelona
Observational.
Inclusion criteria:
>18 years
Long standing ulcerative colitis (>8 years)
Confirmed endoscopically and
pathologically
Lesions in areas of colitis
Exclusion criteria:
Crohn’s Disease
Indeterminate colitis
Sepcimens older than 5 years
Control cohort (sporadic CRC)
From the biobank of the Hospital Clínic
of Barcelona
Inclusion criteria:
Specimens collected prospectively from
the CRC screening cohort trying to be
similar in age, sex and stage to that of
the case cohort.
Exclusion criteria:
Specimens older than 5 years
Design & MethodsBackground Aims Results Discussion Conclusion

Validated MiRNAs
Discovery
by Custom TaqMan™ Array Cards de 96 miRs
50 Cases
18 normal mucosa
20 dysplasias
12 colitis associated CRC
50 Controls
11 normal mucosa
20 dysplasias
19 sporadic CRCs
Differentially expressed miRNAs across the sequence
normal mucosa → dysplasia → cancer
Select most adequate
Imatges modificats de: www.thermofisher.com; i www.nature.com (amunt); Madhu P
Menon, Journal Of Cancer Genetics And Biomarkers - 1(1):21-28 (avall)
RecoverAll™
Thermo Fisher
Scientific
RNA
extraction
TaqMan™
PreAmp
Master Mix
Thermo Fisher
Scientific
Pre-amplification
TaqMan™
Microarray
Thermo Fisher
Scientific
Microarray
96 miRs
Validation
by individual qRT-PCR
50 Cases
13 normal mucosa
25 dysplasias
12 colitis associated CRC
46 Controls
7 normal mucosa
19 dysplasias
20 sporadic CRCs
qRT-PCR Data analysis
Tissue
Extraction
Ambion
punch
To extract only
from relevant
tissue
Design & MethodsBackground Aims Results Discussion Conclusion

Distribution by sex (all)
P=0.102
68%
♂
52%
♂
32%
♀
48%
♀
0%
20%
40%
60%
80%
100%
All cases All controls
Basic characteristics.
P=0.006
50%
IS/I/II
79%
IS/I/II
42%
III/IV
21%
III/IV
8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Cases CAC Control CRC
Stages
75%
♂ 53%
♂
25%
♀ 47%
♀
0%
20%
40%
60%
80%
100%
Cases CAC Controls
CRC
P=0.213
Distribution by sex (cancer)
0
10
20
30
40
50
60
70
80
Cases CAC Controls CRC
P=0.527
Age cancer
0
20
40
60
80
100
Cases CAC Controls
CCR
P=0.442
Age cancer
68%
♂
52%
♂
32%
♀
48%
♀
0%
20%
40%
60%
80%
100%
All cases All controls
Distribution by sex (all)
P=0.331
75%
♂
53%
♂
25%
♀
47%
♀
0%
20%
40%
60%
80%
100%
Cases CAC Controls
CRC
Distribution by sex (càncer)
P=0.854
75%
IS/I/II 55%
IS/I/II
25%
III/IV
35%
III/IV
10%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Cases CAC Controls CRC
Staging
P=0.235
Discovery phase. Validation phase.
ResultsAims Design & MethodsBackground Discussion Conclusion

48 of 96 preselected miRNAs were differentially expressed across the sequence normal
mucosa → dysplasia → cancer (P<0.05)
miR-125-5p, -126, -155, -17, -182, -183, -188-5p, -192, -192*, -193b, -194, -215, -31*, -375, -422a, -490, -491, -552, -127, -1290, -146a, -
17*, -200b, -200c, -224, -23a, -320, -34a, -502, -let-7e, -let-7f, -143, 148a, -16, -19a, -203, -21, -342-3p, -429, -9, -20b, -31, -135b, 106a, -
24, -29a, -let-7f, -195
Discovery
Only in dysplasia
miR-200b
miR-200c
miR-16
P-value
.0
.0016
.003
Only in cancer
miR-126
miR-490
P-value
.001
.0
Progressively across
the sequence
miR-20b
miR-31
P-value
.0
.0
Only in cancer
miR-192
miR-192*
Mir-23a
P-value
.0
.0
.0004
Equally in dysplasia
and cancer
Let-7f
P-value
.012
 OVER-EXPRESSED  UNDER-EXPRESSED

8 miRNAs: miR-20b, -24, -29a, -31, -106a, -135b, -195,
let-7f
4 miRNAs positively validated:
miR-20b, -31, -135b, 106a
48 miRNAs associated with the sequence NM →
dysplasia → CRC
Normal mucosa vs dysplasia p<0.05 and AUROC > 0.70
Consistent deregulation across the sequence
Normal mucosa vs. dysplasia vs. CAC, P<0.05
CAC vs. sporadic CRC, P<0.05 40 miRs excluded: miR-125-5p, -126, -155, -17, -182, -
183, -188-5p, -192, -192*, -193b, -194, -215, -31*, -
375, -422a, -490, -491, -552, -127, -1290, -146a, -17*, -
200b, -200c, -224, -23a, -320, -34a, -502, -let-7e, -let-
7f, -143, 148a, -16, -19a, -203, -21, -342-3p, -429, -9
Validation
4 miRNAs not confirmed:
miR-24, -29a, -let-7f, -195

MiRNA Discovery Validation
Normal
mucosa vs.
displasia,
P
Normal
mucosa vs.
dysplasia
CAC
sequence,
P
CAC vs.
Sporadic
CRC,
P
Normal
mucosa vs.
displasia,
P
Normal
mucosa vs.
dysplasia
CAC
sequence,
P
CAC vs.
Sporadic
CRC,
PAUROC AUROC
let-7f 0.0026 0.72 0.0121 0.00052 0.7455 0.55 0.044* 0.29
miR-106a 0 0.90 0 0.0011 0.002* 0.78 0.003* 0.0004*
miR-135b 0 0.97 0 0.01 0* 0.92 0* 0.0030*
miR-195 0.00084 0.80 0 n.s. 0.0002* 0.83 0.693 1.46E-06*
miR-20b 0.00029 0.83 0 0.0045 0.017* 0.73 0* 0.019*
miR-31 0.013 0.76 0 0.020 0.00026* 0.77 0* 0.0084*
miR-24 0 0.90 0 0.045 0.1997 0.62 0.024* 0.0032*
miR-29a 0 0.92 0 n.s. 0.6627 0.52 0.021* 0.0040*

miR-135bmiR-20b

miR-31 miR-106a

Nice results! But, what next…?

Tumor Type Direction Pathway Role Ref.
Colon Cancer
Up
(Down)
Up-regulated → ↓PTEN
Downregulation in 5FU resistant cells/tissues →
↑ ADAM9 and EGFR → ↓apoptosis
oncomiR
ts-miR?
Zhu, 2014
Fu, 2017
Breast Cancer (Down)
Down-regulated in taxol resistant cancers →
↑NCOA3 → ↓apoptosis
ts-miR? Ao, 2016
Thyroid Cancer Down
Downregulation → ↑MAPK/ERK →
initiation/progression/metastasis
ts-miR Hong, 2016
Esophageal
Cancer
Up Up-regulated → ↓PTEN oncomiR
Wang,
2016
Osteosarcoma Down
Down-regulated → ↑HIF-1α → ↑neo-
angiogenesis
ts-miR
Lin, 2016
Khuun,
2016
Bladder Cancer Down
Down-regulated → activation of Sp-1 binding
motif (important TF in the promoter of MMP-2)
→ ↑MMP-2 → ↑Stromal invasion
Down-regulated → ↑Cyclin D1, CDK2/6 →
↓G1 cell cycle arrest
ts-miR Park, 2015
What do we know about miR-20b?
Seems to be up-regulated in GI cancers (as in our case) and PTEN is an important
target.
DiscussionAims Design & MethodsBackground Discussion Conclusion

Mir-20b and PTEN
Picture modified from: Wise HM et al., Clin Sci (Lond), 2017
miR-20b

What do we knoe about mir-20b in IBD?
Coskun M et al., World J. Gastroenterol, 2013
Well, not much…

What do we know about miR-31?
• Described for many cancers: lung, gastric, breast, bladder, prostate, Barrett.
• In CRC, up-regulation associated with advanced stage, recurrence risk (HR: 4,03)
1 and predictive for response to anti-EGFR in CC and neoadjuvant CRT in RC2,3.
• Related to BRAF mutation and CIMP (serrated pathway)4,5.
• Potential targets: Wdr5, RASA1*2 and FIH-1#6.
Wdr5§
(interacts
with myc)
Signal
trans-
duction
Apoptosis
Cell cycle
progression
Gene
regulation
1Wang C et al., Dis Markers, 2010
2Sun D et al., J Biol Chem, 2013
3Drebber U et al., Int. J. Oncol, 2011
4Ito M et al., Int J Cancer, 2014
5Aoki H et al., World J Gastroenterol, 2014
6Olaru A, Inflamm Bowel Dis, 2011
*RAS p21 protein activator 1
#Factor inhibiting HIF-1
§WD repeat domain 5

What do we know about miR-31 in IBD?
• MiR-31 increases in a stepwise fashion during
progression from normal to chronic IBD to dysplasia.1
• Accurately discriminated dysplasia from normal or
chronically inflamed tissues.
1Olaru A et al., Inflamm Bowel Dis, 2011
2Liu et al., Biochem Biophys Res Commun, 2017
MiR-31 knockout promotes colitis
associated cancer2
Also not much, but interesting…

Mir-31 and HIF-1α in IBD
Olaru A et al., Inflamm Bowel Dis, 2011
Picture modified from: Wong HA et al., Mol Ther. 2015
• Factor inhibiting hypoxia inducible factor 1 (FIH-1) is a direct target of
miR-31 (in silico analysis).
• Transfection of HCT-116 cells with miR-31 mimic confirms down-
regulation of FIH-1 (western blotting).
Inhibition of FIH leads to
increased levels of HIF-1α
and promotes
neoangiogenesis and
metabolic changes.

A complete miR Study Workflow – miR-31 as an example
Identify dysregulated miRs
Array Cards, q-rt-PCR
Step 1
Sun D et al. J Biol Chem, 2013

A complete miR Workflow – miR-31 as an example
Step 1
Identify candidate targets for miR-31
By bioinformatics
Step 2
Correlate expression in vivo
Between miR and its putative target
(miR-31 and RASA1)
Step 3
Confirm expression in vitro
Pre-miR-31 → ↓RASA1
Anti-miR-31 → ↑RASA1
Step 4
Step 4a
Step 4b
Confirm specific binding location
Of miR-31 within the 3’UTR of RASA1 transcript
by luciferase reporter assay
Step 5
Expression of miR-31
RASA1 protein expression
RASA1 mRNA expression RASA1 Luciferase activity

Correlate expression in vivo
Between miR and its putative target
(miR-31 and RASA1)
Step 3
Confirm expression in vitro
Pre-miR-31 → ↓RASA1
Anti-miR-31 → ↑RASA1
Step 4
Step 4a
Step 4b
Confirm specific binding location
Of miR-31 within the 3’UTR of RASA1 transcript
by luciferase reporter assay
Step 5
A complete miR Workflow – miR-31 as an example
Step 1
Identify candidate targets for miR-31
By bioinformatics
Step 2
Examine the biological consequences
(in HT-29 cells)
Cell proliferation assay in vitro
Xenograft model in vivo
Step 6a
Step 6b
Step 6

Conclusion: miR-31 in the post-transcriptional regulation of RAS-MAPK pathway

What do we know about miR-106?
• Also described for many tumor entities.
• Role in suppressing tumor cell death by targeting ATG71.
• Distinguishes between Crohn’s Disease and Ulcerative Colitis2.
• Can classify indeterminate Colitis2.
1Hao H et al., Med Mol Morphol, 2017
2Lin J et al., Mod Pathol, 2013

• Described in many tumor types.
• Regulates many different pathways.
miR-135
TGFBR23
PTEN4
PI3K/AKT2
Wnt/β-
catenin1
1Valeri N et al., Cancer Cell, 2014
2Liu B et al., Mol Carcinog, 2017
3Li J et al., PLoS One, 2015
4Xiang S et al., Oncol Rep, 2015

1Aslam M et al., Color. Dis, 2015
2Koga Y et al., Cancer Prev. Res. (Phila), 2010
3Wu C et al., Clin Cancer Res, 2014
4Wu W et al., Mol Cell Biochem, 2014
• May predict development of metastasis in Dukes B CRC1.
• Potential non-invasive biomarker in stool for sporadic
CRC and advanced adenoma2,3.
• Targets Metastasis Suppressor-1 (MTSS-1), which was
associated with lymph node metastasis and distant
metastasis4.
• Anti-135b transfected HCT-116 CRC cells decreased cell
migration and invasiveness, which was reversed by
MTSS-1-siRNA4.

One of the largest cohorts so far to detect miRNAs in CAC.
The results have been validated positively in an independent cohort.
qRT-PCR technology allowed to know the relative amount of miRNAs.
For comparison of different lesions, changes in these relative amounts were taken into account.
After literature research, the miRNAs seem to be highly relevant for carcinogenesis.
•4 miRs could not be confirmed in the validation phase, probably due to the limited number of cases
and slightly different cancer stages.
•The retrospective design does not allow to establish causality.
•The results have not been correlated to clinical data (grade of inflammation, staging, survival).
•„Only“ the 96 most relevant miRs had been selected. (Around 2,000 are known and 200 for cancer).
Despite their potential as biomarkers and to reduce the burden of screening colonoscopies, the CS
is still essential to know the extension of the lesions and to treat them.
Sometimes inconsistent results are reported in the literature regarding the direction of the
alteration. Hence, interpretation is challanging.
The miRs are part of a very sophisticated system of epigenetic regulation which has different levels
of complexity. (miRs expression → protein translation → pathways).
Functional studies could confirm the relevance of these miRs for carcinogenesis.
Clinical trials with larger cohorts (multicentric) could confirm their utility as biomarkers.
A panel of miRs could diagnose more accurately compared to single miRs.
The miRs are potentially detectable also in blood and stool (as shown for sporadic cancer).
Evaluate miRs in biopsies of normal appearing rectal mucosa (less invasive) „field defect“.
In cancer, they are potential predictors for prognosis and response to treatment.

Ideal future: screening with miR (-panels) in blood, stool or rectal
biopsies (minimally invasive). If positive => colonoscopy with directed
biopsies.
MiRNAs are new potential biomarkers to detect dysplasia associated
to CRC.
MiRNAs change their expression and show a specific patern during
carcinogenesis (normal mucosa → dysplasia → cancer).
Colitis associated CRC and sporadic CRC have distinct miRNA
expression patterns.
Functional Studies could elucidate the pathophysiological role of the
miRNAs detected in this preliminary study.
ConclusionAims Design & MethodsBackground Discussion Discussion

For those interested in (clinical) epigenetics…
“Epigenetics of Colorectal Cancer: Biomarker and Therapeutic Potential”
Gerhard Jung1, Eva Hernández-Illán1, Leticia Moreira1, Francesc Balaguer1 and Ajay Goel2
Coming very soon…

Acknowledgemt
To:
Isabel Quintanilla, Mireya Jimeno, Juan José Lozano, Jordi Camps,
Sabela Carballal, Luis Bujanda, Maria Isabel Vera, Enrique Quintero,
Marta Carrillo, Montserrat Andreu, Miriam Cuatrecasas, Antoni
Castells, Julià Panés, Elena Ricart, Francesc Balaguer, Maria Pellisé
Eduard Klein
To the audience

MiRNAs as novel biomarkers for dysplsia in IBD associated cancer

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