IMPROVED BREAST CANCER

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IMPROVED BREAST CANCER DIAGNOSIS AND PROGNOSIS BY
COMUTATIONAL MODELING AND IMAGE ANALYSIS David
E. Axelrod J.-A. Chapman, W.A. Christens-Barry,
H.L. Lickley, N.A. Miller, J. Qian, L. Sontag,
B. Subramanian, Y. Yuan NCI, NJCCR, Busch

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BREAST CANCER
GOAL Clinical data ? Models ? Patient prognosis
OUTLINE Breast cancer stages in situ and
invasive Clinical data Models Prediction Image
analysis Prognosis
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NORMAL BREAST ANATOMY
Skarin, A.T. Breast Cancer I Slide Atlas of
Diagnostic Oncology, Bristol-Myers Squibb
Oncology
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BREAST CANCER
Skarin, A.T. Breast Cancer I Slide Atlas of
Diagnostic Oncology, Bristol-Myers Squibb
Oncology
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BREAST TUMOR PROGRESSION Conventional
View
Normal ? Ductal Carcinoma In Situ
? Invasive Ductal Carcinoma ? Metastasis
( DCIS)
(IDC)
(M)
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BREAST TUMOR PROGRESSION Conventional
View
Normal ? Ductal Carcinoma In Situ
? Invasive Ductal Carcinoma ? Metastasis

( DCIS) (IDC)
(M)
Normal? Atypical Hyperplasia? DCIS1? DCIS2?
DCIS3? IDC1? IDC2 ? IDC3 ? M
(AH)
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IMPORTANCE OF GRADING DUCTAL CARCINOMA IN SITU
220,000 Breast Cancers / year 20
DCIS 32 recurrence free DCIS
outcome 68 recur (DCIS or IDC) DCIS
heterogeneity 25 intermediate grade 50
mixed grades
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PROGNOSIS BY PATHOLOGIST Miller,
N.A. et al. The Breast Journal 7 292-302 (2001)
Nuclear grade No. Recurrence Recurrence Worst
DCIS Invasive Grade 1 1
0 0 Grade 2 35 4 6 Grade
3 52 13 5 p 0.18 p
0.73 Conclude Nuclear grade is not
prognostic.
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BREAST TUMOR PROGRESSION Conventional
View
Normal ? Ductal Carcinoma In Situ
? Invasive Ductal Carcinoma ? Metastasis

( DCIS) (IDC)
(M)
Normal? Atypical Hyperplasia? DCIS1? DCIS2?
DCIS3? IDC1? IDC2 ? IDC3 ? M
(AH)
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EXPECTATION
DCIS1? DCIS2? DCIS3? IDC1? IDC2 ? IDC3
CLINICAL OBSERVATIONS
Van Nuys Classification
Holland Classification IDC
DCIS IDC
DCIS 1 2 3 1 2 3 1 90.10 26.73 11.88 1 65.66
53.54 12.12 2 55.45 87.13 55.45 2 27.27 117.17
57.58 3 3.96 25.74 141.58 3 4.04 23.23 137.38

Sum of observations of Gupta, Cadman and Leong,
normalized to 498.
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BREAST TUMOR PROGRESSION Conventional
View
Normal ? Ductal Carcinoma In Situ
? Invasive Ductal Carcinoma ? Metastasis

( DCIS) (IDC)
(M)
Normal? Atypical Hyperplasia? DCIS1? DCIS2?
DCIS3? IDC1? IDC2 ? IDC3 ? M
(AH)
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Mommers et al. J. Pathol. 194 327-333 (2001)
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Buerger et al. J. Pathol. 187 396-402 (1999)
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" Unless you can express your knowledge with
numbers, your knowledge is meager and
unsatisfactory." William Thompson
Lord Kelvin 1824-1907
Smithsonian Institution of Washington, 1857
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B. Subramanian and D.E. Axelrod
Progression of Heterogeneous Breast
Tumors J. Theoret. Biol. 210
107-119 (2001) Purpose Pathways for tumor
progression (compartment models) Transition
rates between compartments Data Co-occurrence
frequencies of DCIS and IDC Method Genetic
algorithm (GA) search for transition
rates Result GA cant reproduce data with
models Conclusion GA and/or models not
adequate
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PROBLEMS

• Genetic algorithm
• limitations, stuck in local minimum
• Pathway models
• not describe the biological situation
• Polluted data
• combined data from five labs
• different criteria to classify grades

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PROBLEMS SOLUTIONS

• Genetic algorithm 1. Directed search
• limitations, stuck in local minimum
  seed Nelder-Mead simplex
• Pathway models 2. New pathway
• not describe the biological situation
  relax assumption DCIS -gt IDC
• Polluted data 3. Combine similar data
• combined data from five labs
  combine data from three labs
• different criteria to classify grades
  same criteria to classify grades

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CLINICAL OBSERVATIONS
Van Nuys Classification
Holland Classification IDC
DCIS IDC
DCIS 1 2 3 1 2 3 1 90.10 26.73 11.88 1 65.66
53.54 12.12 2 55.45 87.13 55.45 2 27.27 117.17
57.58 3 3.96 25.74 141.58 3 4.04 23.23 137.38

Sum of observations of Gupta, Cadman and Leong,
normalized to 498.
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PATHWAYS
Linear
Nonlinear
Branched
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DIFFERENTIAL EQUATIONS
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BRANCHED PATHWAY
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PATHWAY SIMULATIONS
Linear IDC
DCIS 1 2 3 1 94.62 49.80 0 2 0 114.54 74.70 3 0 0
164.34
Non-linear IDC
DCIS 1 2 3 1 60.00 0 0 2 84.00 120.00 78.00 3 0 0
156.00
Branched IDC
DCIS 1 2 3 1 103.48 0 0 2 64.68 103.48 71.14 3 0
0 155.22
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PATHWAY SIMULATIONS
Linear IDC
DCIS 1 2 3 1 94.62 49.80 0 2 0 114.54 74.70 3 0 0
164.34
Non-linear IDC
DCIS 1 2 3 1 60.00 0 0 2 84.00 120.00 78.00 3 0 0
156.00
Observed - Van Nuys Classification IDC DCIS 1 2
3 1 90.10 26.73 11.88 2 55.45 87.13 55.45 3 3.96 2
5.74 141.58
Branched IDC
DCIS 1 2 3 1 103.48 0 0 2 64.68 103.48 71.14 3 0
0 155.22
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PATHWAYS
Linear
Nonlinear
Branched
Parallel
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PARALLEL PATHWAY
Common Progenitor
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PARALLEL PATHWAY
p (0.642)
11 12 13 21 22 23 31 32
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PARALLEL PATHWAY
p (0.642)
p (0.326)
11 12 13 21 22 23 31 32
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11 12 13 21 22 23 31 32
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PARALLEL PATHWAY
p (0.032)
p (0.642)
p (0.326)
11 12 13 21 22 23 31 32
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11 12 13 21 22 23 31 32
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11 12 13 21 22 23 31 32
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PATHWAY SIMULATIONS
Linear IDC
DCIS 1 2 3 1 94.62 49.80 0 2 0 114.54 74.70 3 0 0
164.34
Non-linear IDC
DCIS 1 2 3 1 60.00 0 0 2 84.00 120.00 78.00 3 0 0
156.00
Branched IDC
DCIS 1 2 3 1 103.48 0 0 2 0 103.48 71.14 3 0 0 15
5.22
Parallel IDC
DCIS 1 2 3 1 106.57 40.59 7.97 2 40.59 106.57 40.
59 3 7.97 40.59 106.57
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COMPARISON OF RESULTS
Clinical Observation Model
Simulation Van Nuys Classification
Parallel Model
IDC DCIS IDC
DCIS 1 2 3 1 2 3 1 90.10 26.73 11.88 1 106.5
7 40.59 7.97 2 55.45 87.13 55.45 2 40.59 106.57
40.59 3 3.96 25.74 141.58 3 7.97 40.59 106.57

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BREAST TUMOR PROGRESSION
Conventional View - Linear Progression
Normal
Ductal Carcinoma In Situ
Invasive Ductal Carcinoma
Metastasis
New View - Parallel Progression
Ductal Carcinoma In Situ
Common Progenitor
Metastasis
Normal
Invasive Ductal Carcinoma
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PARALLEL PATHWAY
Common Progenitor
L. Sontag and D. E. Axelrod Evaluation of
pathways for progression of heterogeneous breast
tumors J. Theoret. Biol. 232 179-189 (2005)
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Slides 34-45 are excluded. They include data on
diagnosis and prognosis of breast ductal
carcinoma in situ by image analysis which has
been submitted for publication.
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CONCLUSION
GOAL Clinical data ? Models ? Patient
prognosis
OUTCOME Clinical data ? Models ? Improved
Patient prognosis
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