Can the pathologist predict the response of chemotherapy in GI

ESMO 16th World Congress on Gastrointestinal Cancer
25-28 June 2014 Barcelona
Clinical trials for GI oncologists – Trials
and endpoints in GI cancer
Can the pathologist predict
the response of
chemotherapy in GI
malignancies ?
L. Rubbia-Brandt, MD, PhD
Professor of Pathology
Geneva, Switzerland
No disclosure
Clinical trials in oncology
 Essential to improve cancer care
 Given rising costs of drug development, crucial
to design trials efficiently
 As for oncologic treatment, design of clinical
trials benefits from a multidisciplinary approach
Role of pathologist
By analyzing tissue or cells,
 Diagnose
 Estimate the prognosis
 Suggest appropriate treatment
(predictive marker)
 Gives preventive information
Pathology in clinical trials:
Inclusion criteria, stratification
 Tumor diagnosis: avoid overtreatment and falsepositive results with respect of tumor response
 Tumor staging
 Specific target detection (biomarkers): Specific
targeted drugs require precise selection of patient
population in order to successfully test its efficacy.
Pathology in clinical trials:
Quality control
 Quality and type of surgery (i.e. resection margins)
 Quality of pathology sample (representativity)
 Sensitivity and specificity of biomarker testing
Evaluation of adequate tumor content
Tumors are not homogeneous, both in terms of
 epithelial component
 relationship of tumor cells with stroma
Microdissection
Serous membrane
Fat
Mucosa
Tumor
Tumor
Stroma
Muscle
“Garbage in, garbage out (GIGO)”:
nonsensical, input data ("garbage
in") will produce undesired, often
nonsensical, output ("garbage out")
Pathology in clinical trials:
Endpoints/ response to therapy
 Pathological tumor response interpreted as an
indirect marker for recurrence or survival outcomes
Era of biomarkers
De Wit et al clinical biochemistry 2013, 46, 466
Predictive biomarkers
Where we are now…
Strong requirements for worthwhile tests
1. a drug that is active against a subgroup of tumors.
2. a test to distinguish between the two groups of
patients with high sensitivity and specificity.
Pathology: current techniques
Morphology,
Modern Pathology 2014 27, 156.
Predictive value
Gastric Carcinoma &
HER2 overexpression
 Anti-HER2 therapy
 Trastuzumab (monoclonal AC)
 Lapatinib (inhibitor of tyrosine kinase)
 Efficacy of HER2 therapy depends on
HER2 statut both in mammary than
gastric cancer.
 ToGA Study: Phase III international
multicentric, randomized, open study.
Trastuzumab and gastric cancer
Overall Survival according to HER2 statut
N
All
Median OS Hazard
(month)
ratio
IC 95%
584
11,1 vs 13,8
0,74 0,60, 0,91
61
70
159
256
15
7,2
10,2
10,8
12,3
17,7
0,92
1,24
0,75
0,58
0,83
131
446
8,7 vs 10,0
11,8 vs 16,0
Pre- planned analysis
IHC0/FISH+
IHC1+/FISH+
IHC2+/FISH+
IHC3+/FISH+
IHC3+/FISH-
vs
vs
vs
vs
vs
10,6
8,7
12,3
17,9
17,5
0,48, 1,76
0,70, 2,20
0,51, 1,11
0,41, 0,81
0,20, 3,38
Exploratory analysis
IHC0 ou 1+/FISH+
IHC2+/FISH+ ou
IHC3+
0,2
Favours
Trastuzumab
0,4 0,6
1
2
RR (Risk ratio)
3
4 5
Favors
chemotherapy
alone
1,07 0,70, 1,62
0,65 0,51, 0,83
Algorithm HER2 test in gastric cancer
Tumor sample
IHC
0
+1
+2
+3
FISH
-
+
Considered eligible for
Trastuzumab ttt
Who will benefit from treatment with
antibodies targeting EGFR in mCRCs ?
sequencing
Bardelli and Siena, J Clin Oncol 2010
Colorectal adenoma-carcinoma sequence
chromosomal instability pathway (85% tumors)
Activation:
CTNNB1
Inactivation:
APC
MMR genes (MSI)
Normal epithelium
Early adenoma/
dysplastic crypt
PIK3CA
KRAS
BRAF
TP53
PTEN
SMAD2/4
TGFBR2
Intermediate
adenoma
Late adenoma
Carcinoma
Other genetic alterations




Mutations of KRAS: 40%
Mutations in NRAS: 5%
Mutations in BRAF: 7%
Mutations pTEN: 6%
Metastasis
Mutations KRAS and mCRC
2006
2004
Anti-VEGF
Anti-EGFR
(EGFR IHC, HIS)
Mutation
KRAS
Exon 2
anti-EGFR (cetuximab,
panitumumab) in patients
without mutation KRAS (exon 2)
2013
Mutation exons 3 and 4
KRAS and NRAS, BRAF….
(PRIME ET FIRE3)
anti-EGFR in
super wild type RAS
Kras mutation major negative predicitor of efficacy
Where are we going…
What does NG sequencing and
‘-omics’ era brings in molecular
pathology and clinical trials
 Greater number of exons interrogated
 Greater sensitivity
 Genomic, transcriptomic and epigenetic studies
 Other –omics (proteomics, metabolomics,…)
Central dogma
Cascade
« omics »
DNA
Genome
>30’000
genes
mRNA
Transcriptome
>30’000
transcripts
Protein
Proteome
>100’000
proteins
Metabolites
Metabolome
>65’000
metabolites
Phenotype
Central dogma
Cascade
« omics »
DNA
Genome
What could occur
mRNA
Transcriptome
What seems to occur
Proteina
Proteome
What makes it append
Metabolites
Metabolome
What is occuring
Phenotype
Technologies evolutions
Avantages
« all » mutations (known and
unknown)
Covers large type of mutations
Disavantages
Sensitivity
(exception NGS)
Interpretation
end 2004, 15 years
Price : 3 Milliards $
Sequencing capacity
Dipness of lecture
Size of human genome
NGS : Next Generation Sequencing / HTS : High Throughput Sequencing
Technologies
• Pyrosequencing – Roche 454
• Reverse Dye Terminator (RDT) – Illumina
• Sequencing by ligation- 5500 series SOLiD sequencers(Life
Tech)
• Sequencing by ionic mesure – Ion Torrent (Life Tech)
NRAS mutations: predictive impact on PFS
Questions Regarding –omics
 How good are current clinical, morphological and
current molecular biomarkers ?
 Do –omics analysis add to current biomarkers ?
 Do –omics analysis replace current biomarkers ?
 Biological significances of the data ?
 Which best techniques ?
 Which platform and turn around time ?
Conclusions
 Pathologist: most likely will have an increasing role as an
active member of MDT and clinical trials
 Morphological and molecular tumor classification :
important tool for optimal treatment and parameter
in clinical trials
 Information provided depends on available technology
 For prediction, few definite markers but fast-moving field
 Tissue collected in trials: help to develop new generation
of biomarkers in order to propel personalized medicine into
reality.
Prediction is
difficult, especially
about the future
Nobel prize physicist Niels Bohr, 1885-1962