1. Biomarkers for personalized therapy in myeloma
Mike Chapman
University of Cambridge Department of Haematology

2. Novel agents have improved survival

3. What is a biomarker? For the purposes of today…
“A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention”
For the purposes of today…
“A measurable characteristic that is predictive of the response to a therapeutic intervention”

4. Why is this important? For the patient Maximizing efficacy
Minimizing risk
of side effects
Avoiding development
of resistant clones

5. Why is this important? Health economics
Exponential increases in drugs spending probably not sustainable
US/Canada per capita medication expenditure

6. Why is this important? Health economics
Exponential increases in drugs spending probably not sustainable
US/Canada per capita medication expenditure
Already capped in the UK?
NHS per capita medication expenditure (red)

7. Why is this important?
For the pharmaceutical industry

8. Why is this important? For the pharmaceutical industry
Iressa (gefitinib)
Tarceva (erlotinib)

9. Why is this important? For the pharmaceutical industry
Iressa (gefitinib)
Tarceva (erlotinib)
Tarceva: Genentech USA, Roche elsewhere
Iressa: AstraZeneca

10. Properties of an ideal biomarker
Cost effective
Easy to sample
Safe to sample
Easy to perform
Reproducible in different diagnostic labs
Rapid processing
Guides choice of treatment

11. Properties of an ideal biomarker
Cost effective
Easy to sample
Safe to sample
Easy to perform
Reproducible in different diagnostic labs
Rapid processing
Guides choice of treatment

12. International Staging System (ISS) in myeloma
Out of date
Does not reflect response to individual treatments

13. Improving ISS: ISS-FISH
ISS I/II & negative FISH
ISS III & negative FISH or
ISS I & positive FISH
ISS II/III & positive FISH

14. Improving ISS: Revised-ISS
ISS I AND
FISH negative AND
LDH normal
ISS III AND
FISH positive OR LDH high

15. Biomarkers in Multiple Myeloma?
Gene expression profiling (GEP)
Myeloma profiled by John Shaughnessy’s group
Some prognostic significance
But…
Expensive
User/batch dependent
Largely reflects cytogenetics
Difficult to class individual samples
Clustering not robust

16. Biomarkers in Multiple Myeloma?
Gene expression profiling
70 gene signature defined poor prognosis
Derived 17 gene signature made available as RT-PCR kit
Does not alter treatment decisions

17. Additive effects of predictive microarray signatures
Incorporation of different signatures is additive for prognosis
Signatures do not predict effective treatment

18. Actionable mutations: BRAF

19. Actionable mutations: BRAF

20. Vemurafenib active in myeloma

21. How to identify new biomarkers?
Incorporation of genomics into clinical trials
IRF4 predictive of lenalidomide responsiveness (Myeloma XI)
RNAseq signature specifically predictive of bortezomib responsiveness (PADIMAC)
Sequential whole exome sequencing at diagnosis and relapse (CARDAMON)
Cell surface proteomics…

22. Challenges for identifying novel monoclonal antibody targets
Poor correlation between mRNA expression and protein expression
Variable quality of antibodies
Difficulty quantifying proteins
Difficulty enriching for plasma membrane proteins

23. Plasma membrane profiling (PMP)
Oxidation of sugar groups by periodate creates aldehydes. These react with hydroxylamines to form stable oxime bonds. Use aminooxy-biotin to label oxidized glycoproteins.

24. PMP in myeloma: high inter-run consistency
JIM3
KMS12BM

25. PMP in myeloma: close correlation with flow cytometry

26. Prioritizing targets
CD38

27. Conclusions
Need to focus on biomarkers that inform treatment decisions
Incorporation of “-omics” technologies in clinical trials essential
Monoclonal antibody therapy is ideal for personalized medicine