Epidemiology of Chronic Myeloid Leukemia

Tom Radivoyevitch, PhDAssistant Professor

Epidemiology and BiostatisticsCase Western Reserve University

Two CML-ogens: Radiation and Age

𝑦=𝐴𝑒𝑘∗𝑎𝑔𝑒

Not exponential => use additive risk model

Sv = gamma ray dose (Gy) + 10 neutron dose (Gy)

0 20 40 60 80Age

1

10

102

Cas

es p

er 1

06 Per

son-

Yea

rs

U.S. CML Incidence 1973-2009

Males k = 0.047Females k = 0.046

11

1

10 20 30 40 50 60 70Age

2

2

2 2

3

33

3

10

102

103

Cas

es p

er 1

06 Per

son-

Yea

rs

Japanese A-Bomb Survivors

D < 0.02 Sv0.02 < D < 1 SvD > 1 Sv

Radiation-induced CML is Multi-scale

Figure by R.K. Sachs.

For a 500 keV incoming photon

J = 6.2e18eVGy = J/kg= 6.2e6eV/pL

Stochastic versus Deterministic

Figure by R.K. Sachs.

Why Study Radiation as the Input?

• Best carcinogen exposure assessment: A-bomb survivors remember exactly where they were, so doses can be reconstructed

• Compared to chemical carcinogen, cannot simply not use it: background, diagnostic, and therapeutic exposures are here to stay

• Physics is understood, so results across x- & γ-rays, neutrons & protons, and α- and β particles at different energies can be unified

Other CML-ogen, aging, also cannot be avoided+exposure is known

Why Study CML as the Output?

• CML is homogeneous: all have BCR-ABL• CML is prevalent: introns large => per-cell

target size for creating bcr-abl is large• leukemias have rapid onset kinetics: white

blood cells go in and out of tissues naturally so they don’t need to learn to metastasize

Chr9 = 136.3 Mb

~140 kb 139.6 Kb DNA Repair 10 (2011) 1131– 1137

~5 kb = introns between e12-e15

Chr 2249.2 Mb

From 1KG browser

PML-RARA intron sizes

~20kbSeer APL/CML 1234/10103= 12%=1/8

40/700=1/18

40%,55% Mediterr J Hematol Infect Dis. 2011;3(1)

~2kb

Dose Response

itkc

iikac

i PetDem iti )( 21 2

)(22 221 ])([ niknikikitni DDD

itkc

iniiikac

i ePetDDDem

ittkcii ettwTbaPN 22)()|(

N is the number of CML target cells in an individual P(ba|T) is the probability of BCR-ABL given a translocation

w(t)=probability density that CML arrives at t given bcr-abl at t=0

2)(

23 tkt

tetktw

30

22

22

t

ctkc

kedtetR t

Linear R = 0.0075/Gy. LQE posterior R = 0.0022/Gy

CML Target Cell Numbers

• A comparison of age responses for CML and total translocations suggests a CML target cell number of 4x108

• 1012 nucleated marrow cells per adult and one LTC-IC per 105 marrow cells suggests 107 CML target cells

• P(ba|T) = 2TablTbcr/2 may not hold

Kozubek et al. (1999) Chromosoma 108: 426-435

BCR-to-ABL 2D distances

23

Hi-C Datahttp://hic.umassmed.edu/heatmap/heatmap.php

133

chr9

chr22

K562 = bcr-abl+ CML cells

Lieberman-Aiden, et al. Science 9 October 2009: 289-293.

23

133

GM06690 = EBV-transformed lymphoblasts

Off by 2 Mb?

Theory of Dual Radiation Action

P(ba|D) = probability of a BCR-ABL translocation per G0/G1 cell given a dose D

tD(r)dr = expected energy at r given an ionization event at the origin

= intra-track component + inter-track component

Sba(r) = the BCR-to-ABL distance probability density

g(r) = probability that two DSBs misrejoin if they are created r units apart

Y = 0.004 DSBs per Mb per Gy; = mass density

TBCR = 5.8 kbp; TABL = 140 kbp

2

02

2 )()(4

)(2)|( DDdrrgrSrrtDYTTDbaP bababa

DABLBCR

DrrtrtD24)()(

Total Translocations → g(r) estimate

)/(0

0)( rreprg

6

5

4

3

3

2

0 )16/3()4/9(3)(Rr

Rr

RrrS

0

)/(2

02

0 0

4)()(

25.6)(

41 dre

rrSrt

Gp rrd

0

)/(2

02

0 0

4)()(

25.6)(

41 dre

rrSrt

Gp rrxdx

0

)/(0

20

0)()(41 drerSGp rr

d

G=25 DSB/Gy

6.25 kev/m3 = 1 Gy

R = 3.7 m r0 = 0.24 m, p0 = 0.12

d in [.01, .025], dx in [.04, .05], d in [.05, .06]

Risk and Target Cell Numbers

Dependence of R and N on the choice of fixed LQE parameters ba/ba and ban/ba

BA/BA BAn/BA R (Gy-1) N

.055/.0107 .8/.0107 .0022 (.0012, .0039)a 6.1x108 (3.3x108, 1.1x109) .055/.022 .8/.022 .0039 (.0020, .0073) 5.2x108 (2.7x108, 9.8x108) .45/3.64 .8/.022 .0094 (.0051, .0176) 7.6x106 (4.1x106, 1.4x107)

aIn parentheses are the 95% CI.

bat

ctkc N

kedtetR t

30

22

22

ba

RN

Higher risk estimate is more biologically plausible

Linear-to-quadratic transition dose changed from [0.011-0.022]/0.055= [0.2-0.4] Gy to3.64/.45= 8.09 Gy

Linear R = 0.0075/Gy for D < 4Sv is higher here at 0.0094/Gy due to cell killing term

Bcr-Abl to CML Waiting Times

2)(

23 tkt

tetktw

ijkkjiijk PYFDAE

1950 1970 1990

IR-to-CML Latency

Year

Cas

es p

er 1

04 Per

son-

Yea

r-S

v

0

2

4

6 MalesFemales

M/F=1.42tf-tm=6.3y

M/F=1.6tf-tm=10 yrs

0 20 40 60 80Age

1

10

102

Cas

es p

er 1

06 Per

son-

Yea

rs

U.S. CML Incidence 1973-2009

Males k = 0.047Females k = 0.046

Age at Exposure Dependence

10 20 30 40 50Age at exposure

Cas

es p

er 1

05 Per

son-

Yea

rs0.

11

10

Males

mostly radiogenic

High DoseMedium DoseLow Dose

10 20 30 40 50Age at exposure

Cas

es p

er 1

05 Per

son-

Yea

rs0.

11

10

Females

mostly radiogenic

High DoseMedium DoseLow Dose

Nagasaki HSC Reserve Loss?

6 Nagasaki CML vs 53 in Hiroshima Hiroshima PY=1558995 Nagasaki PY= 690084 (i.e. 2.26 lower),

53/2.26 = ~23 cases expected in Nagasaki HSC reserve permanently depleted to 25%?

Human T-cell leukemia virus (HTLV): 22 adult T-cell leukemias (ATLs) in Nagasaki compared to 1 in Hiroshima (2.26 more PY => expect ~50)

11

1

10 20 30 40 50 60 70Age

2

2

2 2

3

33

3

10

102

103

Cas

es p

er 1

06 Per

son-

Yea

rs

Japanese A-Bomb Survivors

D < 0.02 Sv0.02 < D < 1 SvD > 1 Sv

Dead-Band Control of HSC levels

• Transplant doses of 10, 100, and 1000 CRU => CRU levels 1-20% or 15-60% normal Blood (1996) 88: 2852-2858

• Broad variation in human HSC levels Stem Cells (1995) 13: 512-516

• Low levels of HSCs in BMT patients Blood (1998) 91: 1959-1965

0 20 40 60 80Age

0.1

1

10

102

Cas

es p

er 1

06 PY

Males

1973-1984 k = 0.0581985-1996 k = 0.0481997-2009 k = 0.038

0 20 40 60 80Age

Females

0.1

1

10

102

Cas

es p

er 1

06 PY

1973-1984 k = 0.0531985-1996 k = 0.0491997-2009 k = 0.038

HSC Reserve Loss Trend?Ave last 7 ratios0.700.49

1995 data yielded k= 0.041 [Radiat Environ Biophys (1999) 38:201–206]. 0.031 in 2006 is consistent with tlcns leading CML by 10 yrs

0.800.54

All Cancer Incidence Conclusion: Cancer therapy is not the cause of the HSC reserve depletion

Other Guesses? Does obesity increase bone marrow fat and thus squeeze out HSC? 1. Mississippi (34.4%) 51. Colorado (19.8%) 0.1*x+1(1-x)=0.5 => .5=.9x => x=.555Prevalence of cause must be greater than 55%Cancer Epidemiol Biomarkers Prev 2009;18:1501-1506 => obesity causes CML

Easier travel=> greater loads on immune system?

0 20 40 60 80

Cumulative Incidence of Cancer

age

prob

abili

ty o

f can

cer

10 3

10 2

0.1

0.5

malesfemales

0 20 40 60 80Age

0.1

1

10

102

Cas

es p

er 1

06 PY

Males

1973-1984 k = 0.0581985-1996 k = 0.0481997-2009 k = 0.038

0 20 40 60 80Age

Females

0.1

1

10

102

Cas

es p

er 1

06 PY

1973-1984 k = 0.0531985-1996 k = 0.0491997-2009 k = 0.038

Or is it CMML Misclassification?

CML = ICDO-2 9863 does not include CMML. Maybe all were called CML <1985, 50% in 1985-1995, and 0 after

0 20 40 60 80Age

0.1

1

10

102

Cas

es p

er 1

06 PY

Males

1973-1984 k = 0.0581985-1996 k = 0.0481997-2009 k = 0.038

0 20 40 60 80Age

Females

0.1

1

10

102

Cas

es p

er 1

06 PY

1973-1984 k = 0.0531985-1996 k = 0.0491997-2009 k = 0.038

CML=ICD9 205.1 includes 20% CMML

0 20 40 60 80Age

0.1

1

10

102

Cas

es p

er 1

06 PY

Males

1973-1984 k = 0.0581985-1996 k = 0.0551997-2009 k = 0.053

0 20 40 60 80Age

Females

0.1

1

10

102

Cas

es p

er 1

06 PY

1973-1984 k = 0.0531985-1996 k = 0.0541997-2009 k = 0.05

CMML rises at older ages

ICDO-2 9945 = CMML

0 20 40 60 80Age

0.1

1

10

102

Cas

es p

er 1

06 PY

Males

1985-19961997-2009

0 20 40 60 80Age

Females

0.1

1

10

102

Cas

es p

er 1

06 PY

1985-19961997-2009

Counts of CMML per year. None before 19851984 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 1 40 41 43 50 53 70 61 68 66 65 79 93 65 85 78 82 87 2003 2004 2005 2006 2007 2008 2009 93 127 84 91 104 80 123

AML

More APL or better diagnostics?

0 20 40 60 80Age

10

102

Cas

es p

er 1

06 PY

AML Males

1973-19841985-19961997-2009

0 20 40 60 80Age

AML Females

10

102

Cas

es p

er 1

06 PY

0 20 40 60 80Age

1

Cas

es p

er 1

06 PY

APL Males

1973-19841985-19961997-2009

0 20 40 60 80Age

APL Females

0.1

1

Cas

es p

er 1

06 PY

Retinoic Acid and Imatinib

Cures found for cancers that are molecularly homogeneous:simpler cancers are being solved first

0 20 40 60 80 100 1200.

00.

20.

40.

60.

81.

0

APL males

Months

Sur

viva

l

0 20 40 60 80 100 120

0.0

0.2

0.4

0.6

0.8

1.0

APL females

Months

Sur

viva

l

0 50 100 150 200 250 300

0.0

0.2

0.4

0.6

0.8

1.0

CML males

Months

Sur

viva

l

0 50 100 150 200 250 3000.

00.

20.

40.

60.

81.

0

CML females

Months

Sur

viva

l

1973-19811982-19911991-19992000-2009

AML and CLL

More typically progress is slower

0 50 100 150 200 250 300

0.0

0.2

0.4

0.6

0.8

1.0

AML males

Months

Sur

viva

l

0 50 100 150 200 250 300

0.0

0.2

0.4

0.6

0.8

1.0

AML females

Months

Sur

viva

l

0 50 100 150 200 250 300

0.0

0.2

0.4

0.6

0.8

1.0

CLL males

Months

Sur

viva

l

0 50 100 150 200 250 300

0.0

0.2

0.4

0.6

0.8

1.0

CLL females

Months

Sur

viva

l

1973-19811982-19911991-19992000-2009

Acknowledgements

• Department of Epidemiology & Biostatistics • Rainer Sachs (UC Berkeley) • Yogen Saunthararajah (Cleveland Clinic)• Thank you for listening!

SEER Underreporting Possibility

Most conservative claims-based algorithm vs. SEER. B. M. Craig et al. Cancer Epidemiol Biomarkers Prev; 21(3) March 2012

Radiation Doses Rising

AML

Assuming all CML-ogens are also AML-ogens, this implies CML decreases are NOT due to decreases in exposures to bcr-abl forming agents.

No AML trend is consistent with target cells being lineage committed and thus more tightly regulated than HSCs.

0 20 40 60 80Age

10

102

Cas

es p

er 1

06 PY

AML Males

1973-19841985-19961997-2009

0 20 40 60 80Age

AML Females

10

102

Cas

es p

er 1

06 PY

Others

0 20 40 60 80Age

0.1

1

10

102

Cas

es p

er 1

06 PY

MML Males

1973-19841985-19961997-2008

0 20 40 60 80Age

MML Females

0.1

1

10

102

Cas

es p

er 1

06 PY

0 20 40 60 80Age

0.1

1

10

102

Cas

es p

er 1

06 PY

CLL Males

1973-19841985-19961997-2008

0 20 40 60 80Age

CLL Females

1

10

102

Cas

es p

er 1

06 PY

All Cancer Incidence

0 20 40 60 80

Age

Cas

es p

er P

erso

n-Y

ear

10 4

10 3

10 2

Males

1973-19841985-19961997-2008

0 20 40 60 80

Age

Cas

es p

er P

erso

n-Y

ear

Females

10 4

10 3

10 2

Incidence of All Cancers

All Cancer Incidence

0 20 40 60 80

Incidence of All Cancers

age

Cas

es p

er P

erso

n-Y

ear

10 4

10 3

10 2

femalesmales

2026202 Males 2157740 Females 438616821 MalePY 454528905 FemPY

Nagasaki HSC Reserve Loss?

Hiroshima

Nagasaki10 20 30 40 50

Age at exposure

Cas

es p

er 1

05 Per

son-

Yea

rs0.

11

10

mostly radiogenic

High DoseMedium DoseLow Dose

10 20 30 40 50Age at exposure

Cas

es p

er 1

05 Per

son-

Yea

rs0.

11

10

High DoseMedium DoseLow Dose

6 Nagasaki CML vs 53 in Hiroshima Hiroshima PY=1558995 Nagasaki PY= 690084 (i.e. 2.26 lower),

53/2.26 = ~23 cases expected in Nagasaki HSC reserve permanently depleted to 25%? Human T-cell leukemia virus (HTLV): 22 adult T-cell leukemias (ATLs) in Nagasaki compared to 1 in Hiroshima (2.26 more PY => expect ~40)

iii

i mmO )log(