Manuel Salto-Tellez, MD (LMS), FRCPath, FRCPI
Professor and Chair of Molecular Pathology
Clinical Director, Molecular Diagnostics
Deputy Director, Centre for Cancer Research and Cell Biology
WORKFLOWS IN TISSUE AND CELLULAR PATHOLOGY
SAMPLE
C L I N I C A L D I A G N O S I S
SAMPLE PREPARATION AUTOMATED H+E IMAGING SCANNING
AUTOMATED IHCAUTOM. FISH
AUT NA EXTR
HIGH THROUGHPUT TESTINGLOW THROUGHPUT TESTING
MORPHOLOGICAL OR DIGITAL EVALUATION
MANUAL OR DIGITAL SCORING
MANUAL OR DIGITAL ANNOTATION
INTEGRATED PATHOLOGY WORKFLOWS:MORPHOMOLECULAR
Building a 'Repository of Science': the importance of integrating Biobanks within molecular Pathology programmes. EJC 2016, ACCEPTED
Northern Ireland Molecular Pathology Laboratory (NI-MPL)End to End Diagnostic and Research Service
Cutting Across Technologies and Infrastructures
Molecular biomarkers used in clinical standard-of-care decision making in colorectal cancer
Biomarker Purpose
DiagnosticAPC mutation detection
MMR protein expression (MSH2, MLH1, MSH6,
PMS2)
MSI (microsatellite instability) analysis
MMR mutation detection (MSH2, MLH1, MSH6,
PMS2)
BRAF mutation detection
MYH mutation detection
LKB1, SMAD4, BMPR1A, PTEN mutation detection
Diagnosis of FAP
Diagnosis of HNPCC
Diagnosis of MYH-associated polyposis
Diagnosis of harmartomatous polyp syndromes
Prognostic/PredictiveKRAS mutation analysis
BRAF mutation analysis
Thymidylate synthase protein expression
MSI
Gene expression signature
Molecular stratification for treatment with epidermal
growth factor receptor (EGFR) inhibitors
Identification of response to 5-FU
Identification of response to 5-FU
Prognostication
Van Schaeybroeck S, et al (Salto-Tellez M). Abeloff's Clinical Oncology. 5th edition; in press.
Molecular testing in breast cancer
American Society of Clinical Oncology/College
of American Pathologists Guideline
Recommendations for Human Epidermal Growth
Factor Receptor 2 Testing in Breast
Cancer - Antonio C. Wolff AC et al.
JCO Jan 1 2007: 118-145.
Boyle DP, et al. (Salto-Tellez M). Biochim Biophys Acta 2013;1835:230–42.
AKT1 mut in 2% of patients AKT1 inhibitor AZD5363
Activating ERBB2 mut in 3% of patients plasmaMATCH
BRCA1 and BRCA2 mutPARP inhibitors.
ESR1 mutOral SERDs.
Molecular classification of lung adenocarcinoma
Pao W & Hutchinson KE.Nat Med 2012;18:349–51.
Lindeman NI et al. J Mol Diagn. 2013 Jul;15(4):415-53.
Molecular testing in sarcomas &lymphomas
Molecular testing in malignant melanomas
GLIOMA TESTING
DNA QPCR
1P
19Q
PTEN
EGFR Amplification
DNA Sanger Sequencing
IDH 1 & 2
DNA Methylation
RNA QPCR
BRAF Translocations
EGFR v.3
NI-MPL Validation Strategy
Selected target therapeutics in clinical oncology practice
Salto-Tellez M. In: Tan & Lynch’s Principles of Molecular Diagnostics and Personalized Cancer Therapy, Lippincott Williams & Wilkins, 2012.
16
Revolution in OncologyNew Drugs for Targeted Therapy
Discovery Medicine 2014
32
M O L E C U L A R D I A G N O S T I C C Y T O P A T H O L O G Y
(i) that almost any molecular test that could be applied to FFPEmaterial could also be applied to any cytology sample, providedthat due diligence in the pre-analytical aspects of the test wasexercised and that the test was specifically optimised for cytologysamples as well; and
(ii) that the adoption of a genotypic dimension to phenotypicdiagnostic routine would change the way that many of us operated, becoming both a challenge, but also an opportunity for all practising pathologists.
Salto-Tellez M, Koay ES.Cytopathology. 2004 Oct;15(5):252-5
M O L E C U L A R D I A G N O S T I C C Y T O P A T H O L O G Y
Salto-Tellez M, Koay ES.Cytopathology. 2004 Oct;15(5):252-5
2004
Salto-Tellez M.Cytopathology. 2015 Oct; in press
2015
DIGITAL PATHOLOGY IN INTEGRATEDMOLECULAR PATHOLOGY WORKFLOWS
PRIMARY DIGITAL MORPHO-EVALUATION
Healthcare EconomicsIs the digital approach cost-effective?
Can a digital image substitute the microscope for routine
morphology-based diagnostics?
Routine H&E
5 years219,000 biopsies/year
$12.4M savings in productivity/consolidation
1 year40,000 biopsies/year
£286,380 savings in productivity/consolidation
DIGITAL IHC / ISH SCORING
Molecular Diagnostics
Tissue Hybridization-basedTesting
Extracted Nucleic Acid-basedTesting
Digital pathology is not FDA approved for primary diagnosis.However, several manufacturers have received 510(k) clearances or specific uses.
https://digitalpathologyassociation.org/healthcare-faqs
WHY IS DIGITAL PATHOLOGY NOT GENERALLY ADOPTED AS THE TOOL OF CHOICE FOR
TISSUE-BASED PERSONALISED MEDICINE TESTING?
1.DOES DIGITAL PATHOLOGY NEED TO BE AS GOOD
AS THE HUMAN EYE?OR DOES IT NEED TO BE BETTER?
2.IS IHC THE BEST WAY OF QUANTITATING EXPRESSION IN
TISSUE HYBRIDIZATION STUDIES?
WHY IS DIGITAL PATHOLOGY NOT GENERALLY ADOPTED AS THE TOOL OF CHOICE FOR
TISSUE-BASED PERSONALISED MEDICINE TESTING?
1.DOES DIGITAL PATHOLOGY NEED TO BE AS GOOD
AS THE HUMAN EYE?OR DOES IT NEED TO BE BETTER?
2.IS IHC THE BEST WAY OF QUANTITATING EXPRESSION IN
TISSUE HYBRIDIZATION STUDIES?
Ong CW, (Salto-Tellez M). Histopathology. 2010 Mar;56(4):523-9.
?
Ong CW, (Salto-Tellez M). Histopathology. 2010 Mar;56(4):523-9.
Ong CW, (Salto-Tellez M). Histopathology. 2010 Mar;56(4):523-9.
https://qupath.github.ioBankhead P et al (Salto-Tellez & Hamilton), 2016
Bankhead P et al (Salto-Tellez & Hamilton), 2016 Submitted
WHY IS DIGITAL PATHOLOGY NOT GENERALLY ADOPTED AS THE TOOL OF CHOICE FOR
TISSUE-BASED PERSONALISED MEDICINE TESTING?
1.DOES DIGITAL PATHOLOGY NEED TO BE AS GOOD
AS THE HUMAN EYE?OR DOES IT NEED TO BE BETTER?
2.IS IHC THE BEST WAY OF QUANTITATING EXPRESSION IN
TISSUE HYBRIDIZATION STUDIES?
Maxwell P, Salto-Tellez M. Cancer Cytopathol. 2016 Aug;124(8):540-5
Bingham V, (Salto-Tellez M) McQuaid S. Human Pathology. 2015, In Press
Bingham V, (Salto-Tellez M) McQuaid S. Human Pathology. 2015, In Press
Bingham V, (Salto-Tellez M) McQuaid S. Human Pathology. 2015, In Press
Gland-to-gland &Intragland heterogeneity
QUANTITATION - ABSOLUTE AND RELATIVE(HOUSE-KEEPING GENE)
DIGITAL ANNOTATION FOR MACRODISSECTION
Transforming how we practice pathology….
Molecular Diagnostics
Tissue Hybridization-basedTesting
Extracted Nucleic Acid-basedTesting
EGFRKRASBRAFNRASCMETMMR
Oncotype DxMammaprint
Foundation OneClinical Sequencing
Molecular testing, FFPE and H&E Review
Sample
FFPE
Tumour Markup
TumourSufficiency
Macrodissection
DNA Extraction
DNA Quantification
Platform
Molecular Assay Output
Sanger
QPCR
NGS
Pre-Analytical
Analytical
Op
era
tor
Var
iab
ility
NGS Failure Rates
Quantity of DNAQuality of DNA
SMP2
ALL CANCERSWGS
FAILURE RATE = 60%
LUNG CANCERSNGS TARGETED PANELFAILURE RATE = 30%
Ion Torrent Illumina iScan Affymetrix Illumina MiSeq Illumina NextSeq
MOLECULAR PATHOLOGY PROGRAMME – GENOMICS
Hamilton P (Salto-Tellez M). Oncotarget 2015 (advanced publication)
% Tumour cells is criticalTotal number of cells is critical
Tumour cells ? Tumour cells ?
Pre-analytical Pipeline - Cellularity
0 %
20 %
40 %
60 %
80 %
100 %
Very low <100 Very low-low 100-700
Low ~1,000 Low-intermediate1,500-4,000
Intermediate4,000-10,000
High >10,000 Very high >50,000
QC fail result at varying sample cellularity
QC Pass
QC Fail
n=9 n=37 n=98 n=73 n=59 n=115 n=26
Sample size: 417
0 %
20 %
40 %
60 %
80 %
100 %
Very low <100 Very low-low 100-700
Low ~1,000 Low-intermediate1,500-4,000
Intermediate4,000-10,000
High >10,000 Very high >50,000
Number of genes failed at varying sample cellularity (samples run on NGS)
All genes passed
1-7 genes failed
8-14 genes failed
15-21 genes failed
22-all genes failed
n=2 n=16 n=50 n=48 n=46 n=100 n=15
Sample size: 287
32
Graph 21
Graph 22
From: Prof. David Gonzalez de Castro
25 High resolution images breast cancer
Circulate to 3 pathologists
% tumour estimates
Variation in breast % tumour cell estimates amongst pathologists
PathXL – QUB – BHSCT internal assessment, 2015
Breast Cancer % Tumour Estimates
PathXL – QUB – BHSCT internal assessment, 2015PathXL – QUB – BHSCT internal assessment, 2015
Variation in % Tumor Cell
Evaluation in Lung Cancer
Smits AJJ et al. Modern Pathology 27, 168-174 (February 2014)
Variation in % Tumor Cell
Evaluation in Colorectal Cancer
Viray, et al. Arch Pathol Lab Med. 2013;137:1545–154
Oncotarget 2015, minor revisionsOncotarget 2015, advanced publication
Figure 5. Scatterplot of tumor percentage for 136 lung cancer cases derived from two experienced pathologists, showing gross variation between estimates.
Oncotarget 2015, minor revisionsOncotarget 2015, advanced publication
Oncotarget 2015, minor revisionsOncotarget 2015, advanced publication
FIG 11. (A) COMPARISON OF AUTOMATED TUMOUR NUCLEI COUNTS AND PERCENTAGE
TUMOUR VALUES (Y-AXIS), AGAINST BENCHMARK DATA ON TUMOR % SHOWING STRONG
CORRELATION, MAPPING CLOSELY TO ACTUAL TUMOR CELL PERCENTAGE VALUES. (B) THE
SAME SCATTERPLOT AS (A) BUT SUPERIMPOSING THE RANGE OF PATHOLOGY ESTIMATES (RED
CIRCLES) AGAINST THE BENCHMARK DATA.
Oncotarget 2015, minor revisionsOncotarget 2015, advanced publication
Oncotarget 2015, minor revisionsOncotarget 2015, advanced publication
Transformational Digital Pathology
Hamilton P (Salto-Tellez M) Oncotarget 2015, advanced publication
DIGITAL PATHOLOGY: THE FUTURE
Digital Pathology: The Tipping Point
Digital Pathology: The Tipping Point
Digital Pathology: The Tipping Point
Information Integration
Cancer Immunology & Immunotherapy
PATHOLOGICAL INFORMATION
MOLECULAR DIAGNOSTIC INFORMATION(SINGLE BIOMARKERS)
MOLECULAR DIAGNOSTIC INFORMATION(MULTIPLE BIOMARKERS)
RESEARCH INFORMATION(SINGLE BIOMARKERS)
RESEARCH INFORMATION(MULTIPLE BIOMARKERS)
CLINICAL INFORMATION
DIGITAL PATHOLOGY THE FUTURE - INFORMATION MANAGEMENT
McArt, Salto-Tellez & Hamilton. Mol Oncology, 2015;9(6):1234-40
McArt, Salto-Tellez & Hamilton. Mol Oncology, 2015;9(6):1234-40
Cancer immunology is a branch of immunology that studies
interactions between the immune system and cancer cells.
It is a growing field of research (and increasingly diagnostics) that aims to discover innovative cancer immunotherapiesand immune companion diagnostics to treat and retard
progression of the disease.
DIGITAL PATHOLOGY: THE FUTURECANCER IMMUNOLOGY
$3.9M to develop Digital Pathology in the UK
Fridman (Galon). Nat Rev Cancer 2012 Galon. J Pathol 2014; 232: 199–209
http://qupath.github.io
$3.9M to develop Digital Pathology in the UK
Time
Pe
rce
nt
Surv
ival
CHEMOTHERAPY
GENOMIC TARGETED THERAPY
IMMUNE CHECKPOINT THERAPY
COMBINATION OF IMMUNE CHECKPOINT THERAPYAND GENOMIC TARGETED THERAPY
Sharma & Allison. Cell 161, April 9, 2015
Progression-free Survival in the Intention-to-Treat Population.
Reck M et al. N Engl J Med 2016. DOI: 10.1056/NEJMoa1606774
KEYNOTE – 024 Phase 3 trial305 patients
untreated advanced NSCLC with PD-L1 expression on at least 50% of tumor cells
EGFR wt & no ALK translocation
http://www.captodayonline.com/pd-l1-targeted-therapies-await-standardized-ihc/
Single IHC analysis may not be able to encapsulate all thepredictive value necessary: not ideal predictive value
C O N C L U S I O N
An Integrated Morpho-molecular Pathology workflow make the most of our talent, capacities and technical know-how
Digital Pathology can improve the workflow by: a) digital routine H&E analysis;
b) automated scoring of tissue hybridization-type tests; andc) annotation of H&E ahead of molecular testing
The paradigms that may facilitate this approach in the broader sense are the analysis of cancer adaptive immunity and immune checkpoints
Tom Simms Memorial Fund