PROGNOSTIC MARKERS IN BREAST CANCER

1
TRANSLATIONAL RESEARCHFOR H N CANCERS
F-F Liu MD Radiation Oncologist/Senior
Scientist Elia Chair in Head/Neck Cancer Research
University Health Network
2
Outline of Talk

• Clinical problem
• Research Question
• Resources to address hypotheses
• Mechanisms

3
Clinical Problem

• HNSCC
• Cigarette smoking EtOH consumption
• Median age 65 yrs
• New association with HPV

4
(No Transcript)
5
Clinical Problem

• Clinical Challenge
• locally-advanced HNC patients are treated with
  RT CT
• Overall survival rates remain modest (45 for
  HNSCC)
• Significant toxicity 35 - 56

6
Clinical Problem

• Problem
• NO TOOLS TO ALLOW FOR
• PATIENT SELECTION

7
Shiboski et al Cancer 1031843, 2005
8
HPV-Unrelated
HPV-Related
Chaturvedi et al JCO 26612, 2008
9
Outline of Talk

• Clinical problem
• Research Question
• Resources to address hypotheses
• Mechanisms

10
Hypothesis

• HPVve OPCs are associated with increased p16
  protein expression, and have an improved outcome,
  compared to HPV-ve OPC.

11
Outline of Talk

• Clinical problem
• Research Question
• Resources to address hypotheses
• Mechanisms

12
What are Current Challenges?

1. Vast majority are community-diagnosed
2. Very busy clinics
3. Limited OR times
4. Micro-array profiling impossible with FFPE
   tissues

13
What are Available Resources?

1. Volumes of HNC patients (500-600/annum)
2. Clinical anthology database (2700 patients)
3. Collect FFPE diagnostic blocks.

14
HPV

• dsDNA virus 7.9 kb
• 1974 1st postulated to be related to cervix
  cancer
• 1983 HPV16 18 were cloned

15
HPV

• gt300 types identified
• HPV16 18 account for gt98 HPV-positive HNSCC

16

• E6 inactivates p53
• E7 destabilizes Rb increase p16
• Net result failure to die uncontrolled
  proliferation

17
DSouza et al NEJM 3561944, 2007
18
OS
DFS
All Patients
OPC
Fakhry et al JNCI 100261, 2008
19
Methods Materials

• In July 2003, a prospective clinical database was
  established (Anthology of Outcomes)
• Real-time clinical data demographics, stage,
  treatment, and outcome
• 3200 patients currently registered

20
Methods Materials

• 2003 2006, 111 FFPE biopsies of OPC patients
  treated at PMH
• H E slides were reviewed by Dr. P-O
• Expression of p53, EGFR and p16 were determined
  by IHC

21
Methods Materials

• HPV16 status was determined using two different
  methods
• I. qRT-PCR
• qRT-PCR for simultaneous measurements of E6 and
  actin
• Positive control SiHa cells
• Negative control MCF10A, GM5757
• Ratio of E6actin Ct values of gt0.05 (positive)

22
Methods Materials

• II. HPV16 DNA ISH
• Specifically designed probe for HPV16 DNA (Dako)
• Positive control SiHa cells patient sample
• negative control MCF10A cells
• Scoring 0, 1, 2, 3

23
Demographics
Age Median 57 Range 27- 93 Gender
Frequency Percent Male 83
74 Female 29 26 Smoking/Drinking
History Non-smoker/Non-Drinker
Frequency Percent
27
24
24
TN Category
T-category Frequency Percent Tx
4 3 T1 13 12 T2
51 46 T3 23 20 T4
21 19 N-category Frequency Percent N0
21 19 N1 16 14 N2
70 63 N3 5 4
Stage category Frequency
Percent I
4 4
II 11
10
III 16
14 IV
81 72
25
Treatment Approach
Treatment Frequency
Percent CRT (70 Gy/35/7weeks)
44 39 RT
alone 67
61 70Gy/35/7weeks RT alone 13
(19) HARDWINS (64Gy/40/4weeks)
17 (25) 60 Gy/25/5weeks
25 (37) 66 Gy/30/6weeks
9 (13)
Other 3
(4) RT Technique Frequency Percent
IMRT 34 30 Non-IMRT 78 70
26
RESULTS
27
Patient Samples
28
Patient Samples
29
(No Transcript)
30
Scatter plot for HPV16 E6 mRNA vs. HPV16 ISH
HPV16 E6 mRNA relative Ratio (Ln)
(Ratiogt0.05)
Individual Patients
31
Correlation between HPV16 ISH and E6 mRNA
HPV 16 ISH
(1,2,3)
- ( 0 )
HPV 16 E6 mRNA (gt0.05)
59
11
70
(gt 0.05)
- (lt 0.05)
33
3
36
44
62
106
HPV16 ISH E6 Concordance is 86
(Plt0.00001)
32
Correlation between HPV16 ISH p16
HPV 16 ISH
- ( 0 )
(1,2,3)
61
8
69

p16
36
1
37
-
44
62
106
P16 HPV ISH Concordance is 92
(Plt0.00001)
33
Relation between HPV16/p16 Tumours and Age
34
Correlation of IHC with Smoking EtOH

• p53-positive
  EGFR-positive p16-positive
• Smoking
• - 16/27 (59) 19/27
  (70) 22/27 (81)
• 38/85 (45) 62/85
  (73) 42/85 (49) plt0.05
• Drinking
• - 27/55 (49) 40/55
  (73) 43/55 (78)
• 25/50 (50) 41/50
  (82) 18/50 (36) plt0.001

35
3-year OS, DFS Probability of Relapse
Overall survival 3 year 80
Disease-free survival 3 year 65
Probability of relapse 3 year 26
36
P16 with Survival
OS
DFS
p16 (3-yr 82)
p16 (3-yr 92)
p16- (3-yr 42)
p16- (3-yr 61)
Plt0.0002
Plt0.0001
37
HPV16 E6 mRNA Survival
OS
DFS
P0.0014
P0.00059
38
HPV16 ISH Survival
OS
DFS
P0.088
P0.00056
39
Multivariable Analysis for OS DFS
Variables Hazard ratio
p value
Overall survival p16
0.44
0.092
HPV E6 mRNA
0.32 0.016 ISH (0
vs. 1-3) 0.66
0.38 Disease-free survival
p16
0.31 0.00066
HPV E6 mRNA
0.30 0.0004
ISH (0 vs. 1-3)
0.33 0.0019
adjusting for Age Treatment
adjusting for Stage Treatment
40
Conclusions

1. From 2003-2006, 58-65 of OPCs treated at PMH
   are HPV16-positive, as well as p16
   over-expressing.
2. Excellent concordance between HPV16 assays (ISH
   or mRNA), and p16 IHC.
3. Such tumours are associated with younger age, and
   non-smokers/non-drinkers.

41
Conclusions

• 4. P16 over-expression, and HPV-positive OPCs are
  independent predictors for improved DFS.
• 5. Either p16 IHC or HPV ISH should become
  routine evaluations for HNSCC patients with OPC.

42
Outstanding Questions

• Why do HPV-positive OPC fare better than
  HPV-negative disease?
• Genetic instability
• DNA repair defects b/o HPV genes
• Immunologic response
• Micro-RNA profiling
• What host genetic factors lead to HPV-positive
  OPC?
• a) SNP profiles

43
Outstanding Questions

• 3. Should HPV-positive OPC be treated
  differently?
• RT only
• Both RT and CT
• 4. Is there a role for HPV vaccines for young
  male teenagers?

44
Outline of Talk

• Clinical problem
• Research Question
• Resources to address hypotheses
• Mechanisms

45
Outstanding Questions

• Why do HPV-positive OPC fare better than
  HPV-negative disease?
• Genetic instability
• DNA repair defects b/o HPV genes
• Immunologic response
• Micro-RNA profiling
• What host genetic factors lead to HPV-positive
  OPC?
• a) SNP profiles

46
Technological Innovations

• use new tools to address important
  hypotheses
• genetics (micro-RNA profiling)

47
miRs in Human Cancers

• 50 human miR genes located in fragile sites or
  genomic regions involved in cancers
• Dysregulated miR expression associated with many
  human cancers

48
Lowery et al CCR 14360, 2008
49
miRNAs in Human Cancers

• Predictive miRNA signatures reported for
• Chronic Lymphocytic Leukemia (CML)
• Acute myeloid leukemia (AML)
• Hepatocellular carcinoma
• Esophageal squamous cell carcinoma
• Lung cancer (2 sets)
• Colon cancer

50
Experimental Design
Quantitative Real-time PCR
Macrodissection
RNA extraction
Human miRs 365 Endogenous miRs 3
51
Aberrant miR Expression in OPC

• 168 miRs were expressed in normal oropharynx
• miR-21, miR-106b, miR-146b, and miR-9 were
  over-expressed in gt90 of cases
• miR-211 was under-expressed in gt90 of cases

52
None of these miRs are more powerful than HPV or
p16 status
53
Micro-RNA Profiling in OPC
54
miR 193b Knockdown
Fold Change Compared to Normal Fold Change Compared to Normal Fold Change Compared to Normal Fold Change Compared to Normal
Fadu UTSCC 42a UTSCC 8a 54 Primary HNSCC Samples
3.2 19.0 29.0 1.1
55
miR 193b Knockdown
56
miR 193b K/D Clonogenic Survival
57
miR 193b K/D Apoptosis
58
Future Work

• Finalize miR data analysis
• Functionally characterize important miRs, e.g.
  miR-193b
• Complete other in vitro transfection studies
• Biochemistry cellular analyses
• Identify down-stream mRNA targets
• In vivo evaluations

59
Conclusions

• 1. HPV positivity and p16 over-expression are
  amongst the most significant predictors of
  outcome for human OPC.
• 2. An evolving entity, with challenging biology,
  clinical management, and health policy
  implications.

60
Final Conclusions

• Clinical problem
• Identify resources available to address
  hypotheses

61
FINAL CONCLUSIONS

• 3. Research is a continuously dynamic process
• Seeking new knowledge
• Finding a better way to do science
• Constant evaluation challenge.
• 4. Ultimate goal is to improve outcome for our
  patients with cancer.

62
PMH HNC Clinicians Sophie Huang B
Perez-Ordonez Melania Pintilie Maura Gillison
Dr. Mariano Elia Chair in Head Neck Cancer
Research
63
(No Transcript)