studying ghanaian cancer genomes using cell-free dna
TRANSCRIPT
Studying Ghanaian cancer genomes using cell-free DNA
Purpose
MethodsConclusion
9th Annual Symposium on Global Cancer Research, ASGCR, 2021
• Breast cancer is among the leading cause of death among Ghanaian women, where there is more frequent early onset diagnosis and late presentation compared to European populations1.
• Analysis of cancer-related mutations in circulating tumor DNA (ctDNA) from cell-free DNA (cfDNA) that is shed into the bloodstream by tumor cells could be transformative to the African continent and provide new molecular insights as well as early detection strategies2.
• Here, we detected circulating tumor DNA (ctDNA) and copy number profiles from peripheral blood of newly diagnosed breast cancer pa-tients in Ghana, Africa.
Samuel Terkper Ahuno1,2, Anna-Lisa Doebley3,4, Thomas U. Ahearn5, Joel Yarney6, , Nicholas Titiloye7, Nancy Hamel8, Ernest Adjei7, Joe-Nat Clegg- Lamptey6, Lawrence Edusei6 , Baffour Awuah7, Xiaoyu Song8,9, Verne Vander-puye6, Mustapha Abubakar5, Maire Duggan11, Daniel Stover12,13, Kofi Nyarko14, John M S Bartlet15, Francis Aitpillah7, Daniel Ansong16, Kevin L Gardner17, Felix Andy Boateng7, Anne M. Bowcock2,10,18,19, Carlos Caldas20, Wil-
liam D. Foulkes8,21,22, Seth Wiafe23, Beatrice Wiafe-Addai24, Montserrat Garcia-Closas5, Alexander Kwarteng1,25, Gavin Ha4*^,Jonine D. Figueroa5,26*^, Paz Polak2,10,18*^, on behalf of the Ghana Breast Health Study Team
Results
Figure 3: ctDNA fractions and patho-clinical characteristics
Lorem ipsum
p = 1 p = 0.91
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ctDNA fractions by stage
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Tumor Fraction: 0.01815, Ploidy: 2.27
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2GBR05352_1000kb
Copy
Numb
er (lo
g2 ra
tio)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 18 20 22 X
Tumor Fraction: 0.2427, Ploidy: 2.99Subclone Fraction: 0.421, Frac. Genome Subclonal: 0.07, Frac. CNA Subclonal: 0.12
ctDNA fraction (WGS - 30x): 1.8% P15 ER+/PR-/HER2- GU
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0
1
2GBR05352_1000kb
Copy
Numb
er (lo
g2 ra
tio)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 18 20 22 X
Tumor Fraction: 0.2427, Ploidy: 2.99Subclone Fraction: 0.421, Frac. Genome Subclonal: 0.07, Frac. CNA Subclonal: 0.12
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−2
−1
0
1
2GBR05352_1000kb
Copy
Numb
er (lo
g2 ra
tio)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 18 20 22 X
Tumor Fraction: 0.2427, Ploidy: 2.99Subclone Fraction: 0.421, Frac. Genome Subclonal: 0.07, Frac. CNA Subclonal: 0.12
ctDNA fraction (WGS - 30x): 24.3% P01 ER-/PR-/HER2- G3 1.5
0
-1
1.5
0
-1
Copy neutral Deletion Gain Amplification
1 2 3 4 5 6 7 8 11 12 13 15 16 1718
1920
2122
X14109Chromosome
ZNF703 (CN=6)MYC (CN=5)
ZNF703 (CN=5)TERT (CN=4)
Cop
y nu
mbe
r (l
og2
ratio
)
R = 0.99p = 5.4e−09
0
10
20
30
0 10 20 30ctDNA fraction 0.1x ULPS / (%)
ctD
NA
fract
ion
30x
WG
S / (
%)
Scatter plots of Tumor fractions (TFx) 0.1x & 30x WGS (n=12) (Pearson)
0
5
10
15
20
25
Luminal A 2.28%[0.56% − 4.71%]
Luminal B 5.78%[5.78% − 5.78%]
HER2−enriched2.38% [1.19% −
3.57%]
TNBC/basal12.3% [9.38% −
13.2%]Molecular subtypes by Immunohistochemistry staining
ctD
NA
fra
ctio
ns
/ %
ctDNA fractions by subtypes sequenced at 0.1x WGS/ULPS
Acknowledgement
Authors information1Department of Biochemistry and Biotechnology, Kwame Nkrumah University of Science and Technology, Kumasi; 2Departments of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York; 3Molecular and Cellular Biology Program, University of Washington, Seattle, Washington, United States of Ameri-ca; 4Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD; 6Korle Bu Teaching Hospital, Accra, Ghana; 7Komfo Anokye Teaching Hospital, Kumasi, Ghana; 8Research Institute of the McGill University Health Centre, Montréal, QC, Canada; 9Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; 10Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; 11Department of Pathology and Laboratory Medicine, University of Cal-gary, Calgary, AB, Canada;12Stefanie Spielman Comprehensive Breast Cancer, The Ohio State University, Columbus, OH, USA; 13Division of Medical Oncology, Com-prehensive Cancer Center, The Ohio State University Medical Center, Columbus, OH, USA; 14University of Ghana, Accra, Ghana; 15Ontario Institute for Cancer Re-search, Toronto, Ontario, Canada; 16Department of Child Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana; 17Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10027, USA; 18Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York; 19Department of Dermatology, Icahn School of Medicine at Mount Sinai, New York City, New York;20Cancer Research UK Cam-bridge Centre, Cambridge, UK; 21Lady Davis Institute and Segal Cancer Centre, Jewish General Hospital, Montréal, QC, Canada; 22Program in Cancer Genetics, De-partments of Oncology and Human Genetics, McGill University, Montréal, QC, Canada; 23Loma Linda University, School of Public Health, Loma Linda, CA;24Peace and Love Hospital, Kumasi, Ghana; 25Kumasi Center for Collaborative Research in Tropical Medicine (KCCR), Kumasi, Ghana; 26Usher Institute and CRUK Edinburgh Centre, University of Edinburgh, Edinburgh, United Kingdom; *equal contribution; ^corresponding authors: [email protected], [email protected]. [email protected]
Our data provide evidence that ctDNA-based genomic studies are possible using standardised prospective collections of blood and tumour tissues from low and middle-income countries (LMIC).
Our analysis provides a framework for future molecular oncology studies in LMICs including Africa, for cancer etiology, surveillance, early detection and precision medicine clinical trials
Cancer Genome Analysis On The Cloud
Ghanaian women (n =15) with suspicion of breast
cancer from Ghana Breast Health Study (GBHS)
Figure 2: Genome-Wide copy number profiles
0.1x Whole Genome Sequencing (WGS)30x Whole Genome Sequencing (WGS)
cfDNA extraction
Bioinformatics Analysis;Data processing (GATK)
ctDNA fractions & Copy Number (IchorCNA)
p = 0.65
0
10
20
30
50 years andabove (5.90%
[3.53%−10.9%])
< 50 years(5.51%
[2.80%−6.18%])Age at dignosis (years)
ctD
NA
fra
ctio
ns
/ %
ctDNA fractions by age sequenced at 0.1x WGS/ULPS
p = 1
0
10
20
30
50 years andabove (3.96%
[2.54%−10.2%])
< 50 years (5.6%[2.45%−7.34%])
Age at dignosis (years)
ctD
NA
frac
tions
/ %
ctDNA fractions by age sequenced at 30x WGS
0
5
10
15
20
25
Luminal A 2.22%[2.03% − 4.77%]
Luminal B 7.07%[7.07% − 7.07%]
HER2−enriched3.02% [2.55% −
3.49%]
TNBC/basal 11.7%[8.66% − 14.5%]
Tumor subtypes by Immunohistochemistry staining
ctD
NA
fra
ctio
ns
/ %
ctDNA fractions by subtypes sequenced at 30x WGS
Genome-Wide copy number profiles
Figure 4: High correla-tion between 0.1x WGS
and 30x WGS ctDNA fractions
Figure 1: cfDNA study design
Figure 5: TNBCs have higher ctDNA fractions
Figure 6: ctDNA fractions by tumor stage
Figure 7: ctDNA fractions by age at diagnosis
Email: [email protected]