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Race/Ethnicity-Specific Molecular
Cancer Biomarkers: What’s Next?
Partnerships to Advance Cancer Health Equity (PACHE) Investigators Workshop, July 28-29, 2014
Upender Manne, M.S., Ph.D.
Professor of Pathology Senior Scientist of Comprehensive Cancer Center,
University of Alabama at Birmingham Lead PI of the UAB Component of the MSM/TU/UAB CCC
Partnership-U54
MSM/TU/UAB-CCC Partnership Leadership
UAB Comprehensive Cancer Center
Lead PI: Upender Manne, MS, PhD
PI: Isabel Scarinci, PhD
PI: Edward Partridge, MD
Program Manager: Suzanne Byan-Parker, BS
Tuskegee University
Lead PI: Timothy Turner, PhD
PI: Roberta Troy, PhD
Prog. Manager: Chiquita Lee, MBA
Morehouse School of Medicine
Lead PI: James Lillard, PhD
Prog. Managers: Rene Jackson, MPH
Sonja Warner
Cancer Incidence and Mortality by Race/Sex
ACS-2014 Cancer Facts & Figures
Premise
Biological differences in demographic (racial/ethnic, age and sex) groups have implications on cancer incidence (new cases), presentation (stage at diagnosis) and outcomes (mortality/response to Rx).
Approaches to reduce cancer health disparities should also include understanding of their molecular basis.
NODULE
OF BPH
Products from Dying
Cells and Duct
Contents e.g., PSA
tumor
tissue
reaction
Venous and
lymphatic fluids
containing tumor
and tissue-reaction
products and their
metabolites
liver
Urine with tumor and tissue-
reaction products and metabolites
kidney
Molecular Cancer Biomarkers
Cancer biomarkers are present in malignant tissues or serum
They encompass a wide variety of molecules, including DNA, mRNA, miRNA, transcription factors, cell surface receptors, and secreted proteins.
These molecules are produced by tumors or by normal tissues in response to tumor.
Biomarkers will aid in evidence-based patient care and in predicting the clinical outcomes
Brennan DJ, et al. Cancer Genomics Proteomics. 2007;4(3):121-34.
Tumor Development and Progression: Cancer Biomomarkers
Early Detection (population/individual level)
Diagnosis (symptomatic/asymptomatic)
Prognosis (survival/recurrence/relapse)
Prediction (Therapy Efficacy)
Surrogates (Therapy Monitoring)
Surveillance (Risk
Assessment)
Biomarkers of Cancer: Usefulness Depends on Patient Race/Ethnicity
Prognostic Value of p53 Depends on Tumor Location and Patient Race/Ethnicity
Manne U, et al. Cancer 83:2456-2467, 1998
Afr
ica
n A
me
rica
ns (
n=
20
3)
Ca
uca
sia
ns (
n=
30
5)
Shanmugam C/Manne U et al. In Review
Validation of p53 Prognostic Value in an Independent Cohort of Colon Cancers
Ca
uca
sia
ns
Proximal tumors Distal tumors
Afr
ica
n A
me
rica
ns
Proximal tumors Distal tumors
p53 nuclear accumulation is a poor prognostic marker only for non-Hispanic Caucasians when CRCs are located in the proximal colon.
UAB-Caucasians (n=346) and non-UAB-African Americans (n=241)
0
10
20
30
40
50
60
70
Fre
qu
ency
%
Wild type Missense Point-
Mutations
Polymorphic Point-
Mutations
p53 gene status
African Americans (N=63)
Caucasians (N=121)
p53 Mutational Profile of Proximal Colonic Adenocarcinomas
from African-Americans and Caucasians
Survival Analysis of Caucasian Colon Cancer Patients Based
on the Type of p53 Mutations (L 3 Domain Vs. Wild-Type)
0 20 40 60 80 100 120 140 160 180 200
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Wild type p53
Mutations in L 3 Domain
Post-surgical Survival in Months
Su
rviv
al P
rop
ort
ion
Log-rank, Over all P = 0.0291
Log-rank, 10-yr P = 0.0291
Log-rank, 5-yr P = 0.0377
(N = 17)
(N = 61)
0 20 40 60 80 100 120 140 160 180 200
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Wild type p53
0 20 40 60 80 100 120 140 160 180 200
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Wild type p53
Mutations in L 3 Domain
Post-surgical Survival in Months
Su
rviv
al P
rop
ort
ion
Log-rank, Over all P = 0.0291
Log-rank, 10-yr P = 0.0291
Log-rank, 5-yr P = 0.0377
(N = 17)
(N = 61)L 3 Domain =
Codons 236 – 251
Exon 7 = Codons
225 - 261
Manne U, Future Med (Reviews in oncology), 3(3);235-241-2007
Distribution of p53 Mutations in CRCs
Based Patient Race/Ethnicity
3 (5 %)10 (8 %)Other codons
11 (18 %)5 (4 %)Polymorphisms
(Codon 72)
4 (6 %)13 (11 %)LSH-Domain
(Codons 273-286)
2 (3 %)17 (14 %)L 3-Domain
(Codons 236-251)
4 (6 %)15 (12 %)L 2-Domain
(Codons 163-195)
0.0180
39 (62 %)61 (51 %)Wild Type p53
χ2
P - Value
African-
Americans
N = 63 (34%)
Caucasians
N = 121 (66%)p53 Status
3 (5 %)10 (8 %)Other codons
11 (18 %)5 (4 %)Polymorphisms
(Codon 72)
4 (6 %)13 (11 %)LSH-Domain
(Codons 273-286)
2 (3 %)17 (14 %)L 3-Domain
(Codons 236-251)
4 (6 %)15 (12 %)L 2-Domain
(Codons 163-195)
0.0180
39 (62 %)61 (51 %)Wild Type p53
χ2
P - Value
African-
Americans
N = 63 (34%)
Caucasians
N = 121 (66%)p53 Status
Clinical Implications of p53 Codon 72 Polymorphisms in African
American and Caucasian CRCs
Katkoori VR/Manne U, Clin Can Res, 15: 2406-2416, 2009
miR-181b in CRCs
Combined miR-181b (N=344)
0 60 120 180 240 300 3600.0
0.2
0.4
0.6
0.8
1.0
Low (N=234)
High (N=110)
p=0.004
Survival (months)
Su
rviv
al
Pro
po
rtio
n
Blacks miR-181b (N=106)
0 60 120 180 240 300 3600.0
0.2
0.4
0.6
0.8
1.0
Low (N=72)
High (N=34)
p=0.003
Survival (months)
Su
rviv
al
Pro
po
rtio
n
Whites miR-181b (N=238)
0 60 120 180 240 300 3600.0
0.2
0.4
0.6
0.8
1.0
Low (N=162)
High (N=76)
p=0.120
Survival (months)
Su
rviv
al
Pro
po
rtio
n
Whites miR-181b: Stage III (N=70)
0 60 120 180 240 300 3600.0
0.2
0.4
0.6
0.8
1.0
Low (N=42)
High (N=28)
p=0.502
Survival (months)
Su
rviv
al
Pro
po
rtio
n
Blacks miR-181b: Stage III (N=35)
0 60 120 180 240 300 3600.0
0.2
0.4
0.6
0.8
1.0
Low (N=24)
High (N=11)
p=0.001
Survival (months)
Su
rviv
al
Pro
po
rtio
n
__High (N=27)
……Low (N=43)
(N=70)
Bovell L. et al/Manne U. Clin Can Res; 19(14); 1–11, 2013
Jones J et al /Yates C, The A Journal Pathol, 181; 5, 2012 ***Patent pending
Kaiso is Biomarker for African American Prostate Cancer Patients
Kaiso is Biomarker for African American Breast Cancer Patients
Jones et al/Yates C Clin Exp Metastasis. 2014 Feb 26. ***Patent pending
Biomarkers of Cancer: Useful to both African American and
Caucasian Patients
Bcl-2 Expression: Prognostic Markers of Stage II CRC
(Manne/Grizzle, et al. Int. J. Cancer, 74:346-358, 1997)
Prognostic Value of Bcl-2/p53: Multivariate Analysis
0 40 80 120 160 200 240 2800.0
0.2
0.4
0.6
0.8
1.0
Bcl-2 High
Bcl-2 Low
log-rank, Over all P = 0.0003log-rank, 10 year P = 0.0006log-rank, 5 year P = 0.0015
Time to Recurrence(months after surgery)
Re
cu
rre
nc
e f
ree
pro
po
rtio
n
Patients with Stage II CRCs (n=210)
0 40 80 120 160 200 240 280
0.0
0.2
0.4
0.6
0.8
1.0
Bcl-2 High
Bcl-2 Low
log-rank, Over all P = 0.6063log-rank, 10 year P = 0.6063log-rank, 5 year P = 0.6058
(months after surgery)
Recu
rren
ce f
ree
pro
po
rtio
n
Patients with Stage III CRCs (n=306)
Chatla /Manne . et al. Cancer Biomarkers, 1 ; 17-27, 2006
Kennedy R D/Manne U et al. JCO 2011;29:4620-4626
(A) Receiver operating characteristic curve of 10 cross-validation repeats from the 215-sample training set.
Development of a Multiple-Gene Expression Prognostic Signature Stage II CRCs
(A) Receiver operating characteristic (ROC) curve of the 144-sample independent validation set.
The 634 –probe set signature identified high-risk patients with a hazard ratio (HR) of 2.62 (P=0.001) in the training set.
In an independent validation set of 144 samples, this signature identified high-risk patients with an HR of 2.53 (P=0.001) for recurrence and an HR of 2.21 (P .0084) for cancer-related death.
The signature was shown to perform independently from known prognostic factors (HR=2.55; P=0.001).
Stage I
0 60 120 180 2400
20
40
60
80
100
P = 0.500
(n=15)
(n=27)
Post-Surgery Survival in Months
Su
rviv
al
Pro
bab
ilit
y
0 60 120 180 2400
20
40
60
80
100
P = 0.159
Stage II
(n=50)
(n=19)
Post-Surgical Survival in Months
Su
rviv
al
Pro
bab
ilit
y
Stage III
0 60 120 180 2400
20
40
60
80
100
P = 0.014
(n=37)
(n=16)
Post-Surgery Survival in Months
Su
rviv
al
Pro
bab
ilit
y
Stage IV
0 10 20 30 40 500
20
40
60
80
100
(n=11)
(n=31)P = 0.553
Post-Surgery Survival in Months
Su
rviv
al
Pro
bab
ilit
y
Figure 1
A B
C D
Prognostic Significance of p27kip-1 Based on Tumor Stage
______ p27kip-1 high expressors
------- p27kip-1 low expressors
p27kip-1 Expression Biomarker of Stage III CRCs
Manne et al. Clin Cancer Res. 10, 1743-1752, 2004
Bax Expression Predicts Efficacy 5-FU-Based Therapy in CRCs
0 30 60 90 120 150 180 210 2400.0
0.2
0.4
0.6
0.8
1.0
Bax - High
Bax - Low
A
Log-rank, Over all P = 0.0006Log-rank, 10-yr P = 0.0006Log-rank, 5-yr P = 0.0055
Post-surgical Survival in Months
Su
rviv
al
Pro
po
rtio
n
Surgical resection only
0 30 60 90 120 150 180 210 2400.0
0.2
0.4
0.6
0.8
1.0
Bax - High
Bax - Low
Post-surgical Survival in MonthsS
urv
iva
l P
rop
ort
ion
Log-rank, Over all P = 0.0343Log-rank, 10-yr P = 0.0343Log-rank, 5-yr P = 0.0343
B
Surgical resection plus
5-FU based therapy
Age, race, gender, tumor location and stage matched 5-FU treated (Rx) (N=56) and untreated (only surgical resection) (N=56) CRC patients.
( Shanmugam CKet al /Manne U J. GI Oncol, 1(2):76-89, 2010)
Serum CXCL13 & PSA Correlates of Prostatic Disease
CXCL13/CXCR5 as Biomarkers of Prostate Cancer
( Singh S et al /Lillard J. Int J Cancer 15;125(10):2288-95, 2009)
overweight and obese TNBC patients have higher levels of leptin and develop chemo-resistance.
ObR and Leptin levels higher in African Americans than Whites.
Leptin secreted by adipose and breast cancer tissue activates the Notch pathway, increasing tumor growth, angiogenesis and breast cancer stem cell numbers.
Fig$13.$PEG+LPrA2$reduces$BC$growth$in$lean$and$obese$mice.$
m4T1$cells$
BC+4T1$
%BC$free$obese$DIO+$mice$
PEG+LPrA2$
DMBA$
months$
control$
PEG+LPrA2$
%$of$mE0771+Tumors$
2
(A)LPrA2reduced4T1-BCgrowthinBalb/csyngeneicmice[4];(B)humanBCxenogra s[5];DMBA(a
carcinogenic)-inducedBCinC57Bl/6Jobesemice(diet-induced-obesity,DIO[6],and(C)E0771-BC
hostedbyDIO-syngeneicmice[7].
Leptin peptide receptor antagonist (LPrA2):
LPrA2 is a small peptide (~3,000 Da) derived from Helix 3 of leptin that shows high binding affinity for OB-R (Ki ≈ 0.6x10-10 M).
LPrA2 significantly decreases leptin-mediated growth of breast cancer and pancreatic cancer cells.
LPrA2 inhibits leptin-induced Notch and cancer stem cells markers, and improves chemotherapeutic effects.
LPrA2 abrogates growth of breast cancer and Notch expression in mice.
Leptin-VEGFR2/Notch Axis in Breast Cancer Progression and Chemoresistance
Gonzalez-Perez RR et al Cell Signal. 2010;22(9):1350-62. Gonzalez-Perez RR et al. Cancers 2013; 6;5(3):1140-62.
Manne U et al. Drug Discovery Targets (review),10 (14); 2005
Phases of Discovery and Validation of Cancer Biomarkers(Developed by the NCI-EDRN)
Academic/Research
Institutions
Potential
Biomarkers
Pre-ClinicalExploratory Studies
Phase I
Phase IVProspective
Validation Studies forDisease Detection
ClinicalAssay/Technique
Validation StudiesPhase II
RetrospectiveValidation Studies for
Disease Detection
Prospective ClinicalUtility Assessment
Studies
Approval byRegulatoryAgencies
Development ofClinical Testing Kits
Clinical Usage forDisease Detection
Phase III
Phase V
Distinguishes differentcancers or/and
normal vs cancers
Estimates false referralrates & disease
detection
Assesses assay ortechnique reproducibility
& portability
Evaluatessensitivity & specificity of
disease detection
Evaluates overallbenefits & risks of the
test
Industry
Discovery
Preclinical Validation
Clinical Validation
Convenient Sample Set
Reference
Sample Set
Steps to Move Biomarkers to the Next-Level
To translate race/ethnicity-specific discoveries into clinical practice:
Initiate larger national-level prospective studies
Conduct academic-community partnership studies by involving community oncologists to better serve the local communities
Needs funding mechanisms specifically to conduct race/ethnicity-specific trials.
Benefits of Academic-Community Partnership
The academic-community based efforts -
will aid in rapid incorporation of molecular test (profiling) into community practice
will facilitate in integrating molecular biomarker profiles with epidemiological, nutritional, and behavioral data
will improve interactions with community oncologists and aid in updating the latest advancements in molecular and medical oncology
will aid in integrating the use of molecular analyses to make treatment decisions both in community and academic practices, and in reducing the cancer burden.
Thanks!!
Bcl-2 (IHC) - increase expression is a good prognostic markers only for Stage II CRC (Int. J. Cancer, 74:346-358, 1997 & Cancer Biomarkers, 1; 17-27, 2006)
p27kip-1 (IHC) – increased nuclear accumulation is a good prognosticator only in Stage III CRCs (Clin Cancer Res. 10, 1743-1752, 2004).
MUC1 (IHC) – increased expression is a poor prognostic indicator (Clin Cancer Res. 6,4017, 2000).
MUC4 (IHC) – increased expression is a poor prognosticator only in early stage (Stages I & II) CRCs (Cancer, 116,15:3577-86,2010).
Bax or Bax/Bcl-2 (IHC) - high Bax is good prognosticator and low Bax/Bcl-2 expressors are candidates for adjuvant chemotherapy (J. GI Oncol, 1(2):76-89, 2010).
Microsatellite Instability (MSI) – MSI-L in Caucasians is a poor prognosticator, behave like MSS, but in African-Americans it is a good prognosticator like MSI-H (in review).
Distinct Prognostic Value of Molecular Marker in CRCs: Tumor Stage, Location, Race/Ethnicity (UAB-Studies)
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