The DNA Repair Network and Energy Balance
Guang Peng
Assistant Professor
Department of Clinical Cancer Prevention
MD Anderson Cancer Center
July 16, 2015
DNA double strand breaks and genomic instability
Intact DNA Damaged DNA
Endogenous factors
Metabolism (ROS)
Collapsed or stalled
replication forks
Normal genome
Double
Strand
Breaks
(DSBs)
Normal cells
Repair
Environmental factors
Genetic alterations
Radiation therapy
IR (Ionizing radiation )
Mutations
Amplifications
Deletions
Translocations
Anti-cancer drugs
Cisplatinum, Etoposide
Cancer cells
Genomic instability
DNA damage response and DNA repair
DNA damage
Sensors
BRCA1
MDC1
53BP1
Transducers
BRCT-domain
Containing proteins
Effectors
Transcriptional Cell cycle
control
arrest
DNA repair
Apoptosis
DSB repair pathways: HR and NHEJ
DSB
Homologous
HomologousRecombination
Recombination
(HR)
(HR)
5’ to 3’ resection
RPA
RAD51
BRCA1
BRCA1
BRCA2
BRCA2
Homology search
Strand invasion
Nonhomologous end joining
(NHEJ)
Ku70; Ku80
DNA-PKcs
Artemis
End processing
XRCC4 and
DNA ligase IV
DNA ligase
Error-free repair; S/G2 phase
Error-prone repair; G0/G1 phase
the DNA repair network and energy balance
Population studies ?
Mostoslavsky, R. Frontiers in Bioscience 2008
the DNA repair network and energy balance
Does energy balance affect
•
DNA repair capacity before and after intervention
•
DNA repair capacity in different populations/individuals
•
The choice and competition of different DNA repair pathways in
different populations/individuals or before/after intervention
DNA repair
Susceptibility to diseases (cancer)
aging
the DNA repair network and energy balance
Can we develop clinically applicable methods to analyze DNA repair
capacity for translational DNA repair research?
•
Classic molecular assays for detecting DNA repair capacity
•
Gene signature as a molecular tool for DNA repair capacity
•
Multi-pathway functional assays for detecting DNA repair capacity
Comet assay for analyzing DNA repair capacity
IR
Comet Assay
BRIT1
siRNA#1
-IR
+IR
15min
+IR
6h
100
90
80
70
60
50
40
30
20
10
0
After electrophoresis,
the damaged DNA
generates a comet “tail”
P<0.001
% of cells with intact DNA
Control
siRNA
Single cells embedded on
agarose-coated slide and
lysed
no IR
IR-15min
IR-6h
Control siRNA
BRIT1 siRNA#1
BRIT1 is required for DSB DNA repair
Peng, et al., 2009 Nature Cell Biology
HR repair assay for analyzing DNA repair capacity
DRGFP plasmid
SceGFP
iGFP
I-SceI plasmid transfection
HR
iGFP
GFP expression
Flow Cytometry Analysis
HR repair efficiency
Pierce, A.J., et al. 1999 Genes Dev.
Peng, et al., 2009 Nature Cell Biology
+
Fold change of GFP cells
I-SceI
P<0.05
P<0.01
1.2
1
0.8
0.6
0.4
0.2
0
(-)
siRNA (-)
- I-SceI
C
#1
#3
+ I-SceI
BRIT1 is required for HR repair
HR repair assay for analyzing DNA repair capacity
HR repair
Shen, et al., 2015 Cancer Discovery
Single strand annealing repair
Foci staining for analyzing DNA repair capacity
IRIF (ionizing radiation induced foci) assay
-IR
siRNA
Rad51
+IR
DAPI
Rad51
DAPI
IR
(-)
DNA damage
Responsive
proteins
RAD51
RAD51 RAD51
Control
BRIT1 #1
BRIT1 #2
Foci formation
HR repair
Peng, et al., 2009 Nature Cell Biology
BRIT1 is required for RAD51 foci formation
Foci staining for analyzing DNA repair capacity
IRIF (ionizing radiation induced foci) assay
IR
DNA damage
Responsive
proteins
-H2AX BRCA1
RPA
53BP1
Foci formation
HR repair
Shen, et al., 2015 Cancer Discovery
Foci staining for analyzing DNA repair capacity
IRIF (ionizing radiation induced foci) assay
IR
DNA damage
Responsive
proteins
-H2AX BRCA1
RPA
53BP1
Foci formation
HR repair
Shen, et al., 2015 Cancer Discovery
ChIP for analyzing DNA repair capacity
Chromatin immunoprecipitation assay
Shen, et al., 2015 Cancer Discovery
the DNA repair network and energy balance
Can we develop clinically applicable methods to analyze DNA repair
capacity for translational DNA repair research?
•
Classic molecular assays for detecting DNA repair capacity
•
Gene signature as a molecular tool for DNA repair capacity
•
Multi-pathway functional assays for detecting DNA repair capacity
Can we use systems biology approaches to define DNA repair
network?
DNA repair pathway
Single gene approach
DNA repair network
A Systems Biology
Approach
Gene signature approach
Genome-wide microarray
HR repair–defective (HRD) gene signature
Strategy of developing HR-defective gene signature
Homologous
recombination
BRIT1
Normal Breast Epithelial Cells
(MCF10A)
Stable knockdown cell lines
BRCA1
shRNA lentiviral particles
Functional HR defects
RAD51
Control
Homology search
Strand invasion
BRIT1
BRCA1
RAd51
Illumina microarray
Generate signature
HR-defective gene signature and applications
Predictive marker for
drug response
Drug discovery tool
Prognostic marker
Venn diagram and heat map of HRD
signature
Peng, et al., 2014 Nature Communications
United States, PCT/US2014/020376, 3/4/2014, Filed
Drs. Shiaw-Yih Lin, Samir Hanash, and Gordon Mills
PARP inhibitors targeting HR repair deficiency
Normal Cells
DNA Damage
DSB
SSB
HR
PARP
mediated-repair mediated repair
x PARPi
HR-deficient Cancer Cells
DNA Damage
DSB
SSB
HR
PARP
mediated-repair mediated repair
x
x PARPi
BRCA1
PARP
BRCA1
BRCA1
PARP
BRCA2 Others
Others
factors
BRCA2 Others
factors
Others
factors
x
x
factors
Survival
x
Death
Can we can use the HR defective gene signature as a guide
for HR-deficiency in cancer cells?
Can we use HR-defective gene signature as a guide for
HR deficiency in cancer cells?
NCI60 cell lines
HR signature
Intact
Breast cancer
MCF-10A
MDA-MB-436
HCC1937
Defective
MCF7
T47D
MDA-MB-231
Ovarian cancer OVCAR-8
OVCAR-3
Prostate cancer DU-145
PC-3
Lung cancer
H522
H266
Renal cancer
786-0
ACHN
Functional assays for HR
repair efficiency
The HRD gene signature predicts HRD in human cancer cells
HR repair Assay
Cell lines with HR defective (HRD) gene signature showed reduced
HR repair activity.
The HRD gene signature predicts sensitivity to PARP
inhibitor in human cancer cells
Cell Survival Assay
Cell lines with HR defective (HRD) gene signature showed increased
insensitivity to PARP inhibitors.
Drs. Milind Javle and David Fogelman (GI Medical Oncology)
Pancreatic cancer PARPi clinical trial
HR-defective gene signature and applications
Predictive marker for
drug response
Drug discovery tool
Prognostic marker
Venn diagram and heat map of HRD
signature
Peng, et al., 2014 Nature Communications
United States, PCT/US2014/020376, 3/4/2014, Filed
Drs. Shiaw-Yih Lin, Samir Hanash, and Gordon Mills
The HRD gene signature identifies PARP-inhibitorsynergizing agents
PI3K inhibitor LY294002
FDA-proved
drugs
mTOR inhibitor
Rapamycin
Connectivity Map
gene-expression
signature Database
Output
HDAC inhibitor
Vorinostat
Hsp90 inhibitor
AUY922
Query
HR-defective
gene signature
Genomic approach: the Connectivity Map as a drug discovery platform
The HRD gene signature identifies PARP-inhibitorsynergizing agents
PI3K inhibitor and mTOR inhibitor sensitized cancer cells to PARP inhibitors
Clinical trials
HR-defective gene signature and applications
Predictive marker for
drug response
Drug discovery tool
Prognostic marker
Venn diagram and heat map of HRD
signature
Peng, et al., 2014 Nature Communications
United States, PCT/US2014/020376, 3/4/2014, Filed
Drs. Shiaw-Yih Lin, Samir Hanash, and Gordon Mills
The HRD gene signature correlates with clinical outcome in
multiple human cancers
A five-gene signature predicts clinical outcome of
breast cancer
Cox
proportional
hazard model
13 genes
ADM
EXO1
LRP8
PRC1
TRIP13
Recursive
results
Cox proportional hazard model:
13 genes selected
Statistical analysis tools are applied to select the most significant genes associated
with patient survival time
40
230 genes
Value
80
0
40
60
Heat Map of NKI
RAD54L
DKFZp762E1312
TY
MS
BLM
PRC1
EXO1
CCNA2
MCM7
MCM2
TRIP13
TK1
PKMY T1
RRM2
OIP5
FEN1
CCNB1
PCNA
RFC4
CHEK1
ANLN
DONSON
POLA2
MCM5
TACC3
LRP8
SUV39H1
CHRNA5
POLD1
MCM3
CHAF1B
CHAF1A
LMNB2
DNMT1
SFRS2
SLC25A10
RECQL4
DNA2L
TTK
RAD54B
RFC3
RFC5
TIMELESS
POLQ
POLE2
BRCA1
DHFR
CSE1L
VRK1
TERF1
MSH6
MSH2
CCNE1
IL1R2
E2F2
INSIG1
FDPS
SRPK2
SLC25A13
SFPQ
STAT2
KIAA0513
CBLB
NFIL3
ADM
MT1G
BTG1
KRT6B
PPL
HLA.E
CTSC
DAPK1
CD68
TNFRSF14
TINF2
NFE2L1
HSD11B2
CRIP2
POLR3K
FXY
D3
PLEK2
CKB
FLRT3
PLCD1
KCNB1
DDIT3
ATP10B
TUBB4Q
ARSD
VAMP5
HSPE1
DUT
DCN
DPY SL3
MSX1
PHLDA3
CPE
XPC
BTG2
LOH11CR2A
CDKN1C
CRY AB
MME
PROS1
FBLN1
LAMB2
GJB2
13 genes
Value
80
5
25
Count
10
Count
Heat Map of NKI Data
Color Key
and Histogram
0
40
190
270
177
75
142
79
115
164
232
113
9
284
10
132
42
155
295
91
214
181
2
41
72
258
255
254
93
192
283
106
186
280
141
5
173
3
203
130
87
40
294
103
126
108
131
85
253
43
179
53
176
198
257
212
276
39
151
245
288
200
152
278
219
250
25
264
290
159
58
244
226
13
221
243
14
112
259
30
11
188
97
111
12
268
26
45
183
180
182
234
263
149
38
15
116
216
162
49
266
197
246
160
102
248
140
109
98
252
267
134
218
223
287
57
211
256
262
281
202
100
282
208
66
154
50
229
80
61
237
153
189
37
69
95
67
275
274
62
88
174
146
240
1
17
96
261
163
64
65
191
277
184
107
84
213
46
235
205
185
157
225
247
86
269
175
158
52
105
44
60
73
74
241
78
166
54
144
16
6
292
114
122
138
272
59
230
193
207
47
242
251
48
89
195
168
118
120
227
228
204
18
119
238
220
285
8
201
77
23
171
136
81
36
209
170
279
68
71
21
210
260
27
51
125
34
167
143
286
222
194
32
273
215
20
187
70
169
121
199
165
161
110
139
265
94
147
178
293
128
83
217
104
123
156
29
31
271
33
289
4
56
236
117
92
124
82
28
239
101
148
19
55
133
172
90
150
127
35
63
145
231
249
135
99
22
76
7
291
224
137
24
196
233
129
206
Color Key
and Histogram
261
107
213
286
143
81
27
189
95
210
231
273
217
24
239
35
291
218
56
136
194
34
238
8
36
220
228
209
171
170
69
154
282
229
153
37
157
23
275
274
185
205
235
77
260
86
225
161
125
63
61
80
144
124
249
289
233
82
148
147
178
128
206
92
83
101
196
129
28
135
33
51
4
167
90
150
55
133
172
127
137
145
22
7
224
19
76
99
14
11
112
30
259
243
13
221
188
111
97
226
41
234
180
72
258
254
12
268
91
232
42
284
164
9
93
255
214
181
295
270
53
179
113
294
3
87
130
192
132
283
45
183
176
106
149
162
17
240
64
204
1
163
15
216
146
253
173
43
142
155
10
75
67
177
105
60
190
79
264
159
263
2
25
115
203
26
98
109
160
116
40
250
186
102
5
182
57
141
280
197
131
108
126
85
281
267
140
38
151
212
262
256
202
198
257
58
134
219
290
244
287
223
241
288
208
66
174
54
70
278
276
100
292
16
215
94
20
32
265
199
110
139
227
29
71
222
117
236
237
50
68
245
39
104
6
187
165
169
121
123
152
293
31
271
156
193
279
47
114
272
201
285
184
84
158
175
44
65
166
211
48
74
49
195
73
78
103
246
277
62
88
242
120
21
269
247
46
207
230
138
59
119
18
118
89
168
96
52
191
251
200
122
248
266
252
0
262
265
89
293
260
295
162
149
134
68
294
292
112
30
151
219
188
212
64
281
114
199
140
163
270
204
142
17
26
3
214
202
198
38
11
53
180
268
93
111
102
182
116
85
241
10
44
141
58
57
186
203
130
155
97
108
109
277
67
240
65
276
16
174
278
40
250
252
25
132
43
243
254
87
176
146
41
290
2
192
12
181
106
183
264
91
253
216
259
221
258
13
14
15
20
159
256
255
257
232
226
234
190
280
179
283
113
75
60
45
42
173
131
126
9
284
164
72
32
94
139
24
287
279
271
35
119
66
242
70
62
54
156
88
269
96
158
6
187
227
184
118
168
21
154
200
104
267
1
289
231
213
193
261
71
48
47
215
191
211
56
189
18
5
46
175
152
77
208
237
205
125
161
248
138
128
272
169
59
223
39
263
266
288
244
49
120
195
78
98
73
79
197
160
115
103
74
84
136
220
52
29
275
157
165
185
177
166
100
207
251
235
105
245
246
122
201
34
37
36
80
194
210
107
81
129
225
143
147
86
247
282
274
238
196
69
229
239
27
23
8
218
217
286
285
50
95
249
291
28
222
51
230
178
7
124
31
236
117
110
228
153
144
76
148
83
92
101
273
61
121
123
233
90
150
82
19
137
224
63
171
209
99
22
170
172
33
133
127
4
206
167
145
55
135
Count
100
A five-gene signature predicts clinical outcome of
breast cancer
Color Key
and Histogram
Heat Map of NKI
Value
80
PRC1
DKFZp762E1312
EXO1
CCNB1
EXO1
FEN1
PRC1
TRIP13
TK1
RAD54L
TRIP13
TYMS
MCM7
LRP8
POLA2
LRP8
ADM
ADM
5 genes
HR-defective gene signature stratifies breast cancer patients
A five-gene signature predicts clinical outcome of
breast cancer
230 genes
13 genes
5 genes
HR-defective gene signature predicts patient clinical outcome
Biomarker of high risk DCIS
50,000 DCIS, 2/3 of DCIS are destined never to progress to
invasive breast cancer, over-treatment of surgical resection
Dr. Abenaa Brewster
the DNA repair network and energy balance
Can we develop clinically applicable methods to analyze DNA repair
capacity for translational DNA repair research?
•
Classic molecular assays for detecting DNA repair capacity
•
Gene signature as a molecular tool for DNA repair capacity
•
Multi-pathway functional assays for detecting DNA repair capacity
Multiple-pathway functional assays for translational
DNA repair research
High-throughput, fluorescence-based multiplex (FM) host cell
reactivation (HCR) assay (FN-HCR) for measuring DNA repair capacity in
living cells
Simultaneous measurements of DNA repair capacity in three
pathways
In vitro DNA damage blocks transcription and repair pathway permits
expression of fluorescent reporters
Simultaneous measurements of DNA repair capacity in four
pathways
Applications of FM-HCR to assesse DNA repair capacity
Workflow of analyzing reporter expression
Acknowledgements
Peng Lab
Jianfeng Shen, Ph.D.
Claire Hsieh, M.D.
Lulu Wang, Ph.D.
Yang Peng, Ph.D.
Xiangdong Peng, Ph.D.
Lihong Zhang, M.D., Ph.D.
Systems Biology
Gordon Mills, M.D., Ph.D.
Shiaw-Yih Lin, Ph.D.
Clinical Cancer Prevention
Ivan Uray, M.D., Ph.D.
Powel Brown, M.D, Ph.D.
Abenaa Brewster, M.D.
Samir Hanash, M.D., Ph.D.
Peter Davies, M.D., Ph. D.
Xiangwei Wu, Ph. D.
Xiaochun Xu, Ph. D.
Qian Shen, M.D., Ph.D.
Florencia McAllister, M. D.
Georgia Southern University
Hua Wang, Ph.D.
Shujiao Huang, M.S.
NIH/NCI K99/R00
Landon Foundation-AACR INNOVATOR Award for Cancer Prevention Research
Ovarian SPORE Career Development Award, MDACC, NIH/NCI
Susan G. Komen for the Cure Foundation Career Catalyst Research Award
Duncan Family Institute
CPRIT