1. Sesion de Controversias nº 5 Conclusiones Carlos Camps
Tratamiento de la Enfermedad Avanzada en NSCLC Perfil Genómico vs Perfil Clínico
Sesion de Controversias nº 5
Conclusiones
Carlos Camps

2. Individualized Medicine
“In the very near future, primary care physicians will routinely perform genetic tests before writing a prescription because they will want to identify the poor responders”
Dr. Francis Collins, HGRI Director AAFP Annual Meeting, 1998

3. Everybody is Different
The Right Drug
To The Right Patient
For The Right Disease
At The Right Time
And The Right Physician
The basis of pharmacogenomics and of molecular oncology is the realization that each body is different. The behavior of a specific tumor in a specific individual is unique; the response to specific drugs or even the need to be treated is unique. The challenge is to be able to administer
The Right Drug
To The Right Patient
For The Right Disease
At The Right Time

4. Targeting the correct patients
We already define patients on the basis of histological cell type and tumour location, age, gender, PS, etc.
How do we identify the patients who may benefit most from molecular targeted therapy?
Individualized manegement patient
Who needs therapy and how intense?
What agents are the most effective?
When to stop treatment?

5. Who Can Be Spared Therapy? Which Therapy Will Work Best?
Therapy Decision-Making for
Lung Cancer
Who Can Be Spared Therapy?
Which Therapy Will Work Best?
The therapy decision making for early breast cancer involves two major decision points:
1.     Who does not need systemic treatment?
2.     Which treatment is the most effective and least toxic for those who need treatment?
Prognostic factors needed
Predictive factors needed

6. Current scientific interest in biomarkers
Definition of a biomarker
‘A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to therapeutic intervention’1
1Biomarker Definitions Working Group. Clin Pharm Ther 2001

7. Prognostic versus predictive markers
Indicate likelihood of outcome (tumour recurrence, patient survival, adverse event), regardless of which treatment is used
Predictive
Indicate likelihood of an outcome to a specific therapy
Biomarkers could be both predictive and prognostic value
Source:

8. Individualized management patients
Prognostic Factors
Clinical and molecular ( indicators of tumor virulence)
Predictive factors
Clinical and molecular ( indicators of efficacy of specific therapies)

9. What defines a useful biomarker?
1. Reproducible: measured reproducibly by means of a reliable and simple assay
2. Applicable: information about the disease that is clinically relevant
3. Validated: confirmation of the above two from independent data set
Source:

10. Clinical selection parameters Biologic markers
Treatment Factors in Advanced NSCLC
Clinical selection parameters
Biologic markers
 ERCC-1
 RRM-1
 Beta-tubulin
 EGFR
 k Ras mutation
BRCA1
 Sex
Age
Comorbidities
Stage
Histology PS
Smoking story

11. Useful prognostic and predictive clinical characteristics
Age No
Gender
no ¿yes?
No /yes? (TKI’s)
Histology PS
Yes
Yes(Chemo)
Stage
Smoking history
Yes (Tarceva)
Ethnicity

12. State of Art Therapeutic modality determined by stage
Decision not to treat based on PS / Comorbidities
Minimal treatment selection based on predictive factors ( clinical)
First accurate assessment of efficacy performed not earlier than 6 weeks after starting therapy (CT scan)

13. Useful of clinical characteristics to select therapy
Not useful to select the most effective chemoregimens
Useful to exclude agents to avoid certain toxicities
Potentially useful to select erlotinib for front line therapy

14. Useful Clinical characteristics predictive of Toxicity
Age No
Gender No
Histology Yes ( Avastin)
PS Yes ( Chemo)
Stage No
Smoking story No/Yes
Ethnicity No/Yes

15. Molecular prognostic and predictive markers
Unifactorial
Single molecular determinants
Multifactorial
Genomic signatures
Proteomic profiles

16. Molecular studies in Lung Cancer.
Low RRM1
Longer survival
No differences in response
Rosell et al
Oncogene
Better than
ERCC1
CC: 0.410
P < 0.001
CCR
Low ERCC1
NSCLC
Better response
ASCO
Low ERCC1
NSCLC
Longer survival
No differences in response
Lord et al
CCR
Potti
Chen
Zheng
Olaussen
Rosell
Soria
Simon
Low ERCC1
Colorectal cancer
Longer survival
No differences in response
Shirota JCO
BRCA1
Differential
modulator
Quinn et al
Cancer Res
Low BRCA1
Better than
RRM1
CC:0.815
P < 0.001
Taron et al
Hum Mol Genet

17. Progression-Free Survival
Ras Gene Mutations in TRIBUTE
Progression-Free Survival
Overall Survival
0.2
0.4
0.6
0.8
1.0
0.2
0.4
0.6
0.8
1.0 5 10 15 20
Months 5 10 15 20
Months
Chemotherapy, wild type (n=103)
Erlotinib + chemotherapy, wild type (n=104)
Chemotherapy, mutant (n=30)
Erlotinib + chemotherapy, mutant (n=25)
Eberhard D, et al. J Clin Oncol 2005;25:5900–9.

18. Inverse Relationship between RRM-1 Expression & Outcomes after Cis/Gem
Phase II trial in patients with locally advanced NSCLC treated with cisplatin/gemcitabine (n=35)
0,0
0,2
0,4
0,6
0,8
1,0
Influence of ß-Tubulin Levels on Survival In Advanced NSCLC
P=0.039
100 80 60 40 20
Percent Disease Free
200
400
600
800
1000
1200
TubIII <50% n=22
TubIII >50% n=25
P =
Paclitaxel
Cumulative survival
< 7.5
> 7.5 10 20 30 40 50 60 70
Time (months)
Bepler et al. JCO 2006;24:
Seve et al. Mol Cancer Ther 2005;4:

19. docetaxel/gemcitabine
ERCC1 and BRCA1 Profiling: Pharmacogenomics
Control arm
docetaxel/cisplatin
Experimental arm
ERCC1 levels
GENOTYPE B1
(low ERCC1 mRNA)
GENOTYPE B2
docetaxel/gemcitabine
(high ERCC1 mRNA)
1:2
Cobo et al. J Clin Oncol 2007;25:
BRCA1 in NSCLC GILT II
Induces resistance to cisplatin-mediated apoptosis
Increased levels associated with poorer OS in completely resected, chemotherapy-naïve NSCLC
 BRCA1 > 5 vs ≤ 5: HR 1.98, p=0.02

20. Biomarkers for chemotherapy in NSCLC
Biomarker for cytotoxic therapy
RRM1 (low-level expression is associated with resistance to gemcitabine)
ERCC1 (high-level expression is associated with resistance to cisplatin)
others: BRCA1, XRCC,tubulin III, etc.
Biomarker for EGFR inhibition
protein expression by IHC
gene copy expression by FISH
EGFR mutation by sequencing
Ueno H, et al. Br J Cancer 2007

21. Molecular subclasses of NSCLC

22. Tumor-Cell Behavior Is Determined By The Activity Of Many Genes
The activity of one or a few genes cannot predict tumor-cell behavior in a reliable way.
We need tools to measure the activity of many genes in a single experiment
Thus, tumor-cell behavior is determined by the activity of many genes. The activity of one or a few genes cannot predict tumor-cell behavior in a reliable way. We need tools to measure the activity of many genes in a single experiment.

23. Few genes, Little Information
We can look at the molecular profile of a tumor as pieces of a big puzzle. If we look at only one piece, let’s say the presence of an estrogen receptor, these two tumors look identical. But if we look at a multitude of pieces, that is, the expression of many genes, we see that these two tumors are nothing alike.

24. Assessment of Multigenic basis for individualized patient management
Multiple genes involved in hots cases
Protein function more important than gene expression
Methods must be accurate and reproducible

25. Lung Cancer – A Paradigm for Tailored Medicine
Current practice
Histological profile of the tumor
Treatment decisions according to population prognostic factors
Drug choice according to population predictive factors of efficacy and safety
Emerging practice
Molecular profile of the tumor
Treatment decisions according to individual prognostic factors
Drug choice according to individual predictive factors of efficacy and safety
Since my main clinical and research interests are in the field of breast cancer, I will try and illustrate the application of molecular oncology and phrmacogenomics in the treatment decision process of this disease
 Breast cancer can serve as a paradigm for tailored medicine.
Our current practice involves the use of a histological profile of the tumor, treatment decisions, and drug choices that are based on population prognostic and predictive factors.
The emerging practice involves the molecular profile of the tumor, with treatment and drug choice based on individual prognostic and predictive factors that are derived from the unique molecular profile of the tumor and the unique genetic make-up of the patient.

26. Information Based Medicine will require unprecedented access to diverse, integrated information
Challenges
Volume and complexity of data
Integrating massive volumes of disparate data
Need for sophisticated analytics
Growing collaboration across ecosystem

27. an Important Step Toward Personalized Medicine – But Barriers remain
Lack of technology standards (genomics, informatics, emerging technologies)
Lack of common technology platforms to enable the sharing of information and transfer to clinical application
Inability to manage and interpret large quantities of data
Lack of a coordinated, integrated system
Lack of common vocabularies
Need for new funding mechanisms to facilitate data sharing and collaboration
Need for new clinical trials design models
Existence of cultural barriers

28. The Problem of Fresh Tissue
The major problem with this assay is the need for fresh or frozen tumor tissue. Logistically, this is quite difficult.

29. Conclusion and future prospects
Clinical characteristics have proved so far its use as prognostic factor and treatment selection in the case of erlotinib
Age and PS/Comorbidities should be considered separately when evaluating a patient for chemotherapy
Uni / Multigenetic and Proteomic assessment of prognostic and predictive factors has shown promising results in the case of erlotinib and several cytotoxic agents
Molecular markers undoubtedly will play a larger role in the selection of patients for chemotherapy as well as molecularly targeted agents in the futurerelated
Clinical and Biological factors are RELATED
The treatment selection tools developed need to be validated in prospective clinical studies
Clinical Data
Molecular Data

30. Convergence: Molecular Biology, Advanced Technologies, Bioinformatics/Clinic knowledges
Unprecedented Potential for Exponential Progress Toward Personalized Medicine (Molecular Oncology)
Image courtesy of Nature, Feb. 15, 2001