European polygenic risk score for prediction of breast cancer shows similar performance in Asian women

Ho, Weang Kee; Tan, Min; Mavaddat, Nasim; Tai, Mei Chee; Mariapun, Shivaani; Li, Jingmei; Ho, Peh Joo; Dennis, Joe; Tyrer, Jonathan P.; Bolla, Manjeet K.; Michailidou, Kyriaki; Wang, Qin; Kang, Daehee; Choi, Ji Yeob; Jamaris, Suniza; Shu, Xiao Ou; Yoon, Sook Yee; Park, Sung Sup; Kim, Sung Won; Shen, Chen; Yu, Jyh Cherng; Tan, Ern Yu; Chan, Peter; Muir, Kenneth; Lophatananon, Artitaya; Wu, Anna H.; Stram, Daniel O.; Matsuo, Keitaro; Ito, Hidemi; Chan, Ching Wan; Ngeow, Joanne; Yong, Wei Sean; Lim, Swee Ho; Lim, Geok Hoon; Kwong, Ava; Chan, Tsun Leung; Tan, Su Ming; Seah, Jaime Chin Mui; John, Esther M.; Kurian, Allison W.; Koh, Woon Puay; Khor, Chiea Chuen; Iwasaki, Motoki; Yamaji, Taiki; Tan, Kiak Mien Veronique; Tan, Karsoon; Spinelli, John J.; Aronson, Kristan J.; Hasan, Siti Norhidayu; Rahmat, Kartini; Vijayananthan, Anushya; Sim, Xueling; Pharoah, Paul D.P.; Wang, Zheng; Dunning, Alison M.; Simard, Jacques; Dam, Rob M van; Yip, Cheng Har; Taib, Nur Aishah Mohd; Hartman, Mikael; Easton, Douglas F.; Teo, Soo‐Hwang; Antoniou, Antonis C.

doi:10.1038/s41467-020-17680-w

Cited by 97 publications

(117 citation statements)

References 34 publications

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“…Compared with patients in The Cancer Genome Atlas (TCGA) 10 , our patients were younger, presented at later stages and had higher proportions of ductal carcinoma and Her2 positivity (28.9% MyBrCa versus 19.3% TCGA when NAs are excluded; Supplementary Table 1 ). The MyBrCa tumour cohort includes Malaysians from a number of different ethnicities, primarily Chinese (89%), Malay (4.6%) and Indian (3.4%) (Supplementary Table 1 ), and is as a whole genetically similar to other East/Southeast Asian populations according to genotyping analysis 21 . A principal component analysis of our RNA-seq data did not reveal any significant differences across different ethnicities (Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

The molecular landscape of Asian breast cancers reveals clinically relevant population-specific differences

Pan

Zabidi

et al. 2020

Nat Commun

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Molecular profiling of breast cancer has enabled the development of more robust molecular prognostic signatures and therapeutic options for breast cancer patients. However, non-Caucasian populations remain understudied. Here, we present the mutational, transcriptional, and copy number profiles of 560 Malaysian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to breast tumours in Caucasian women, we show an increased prevalence of HER2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. We also observe elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst HER2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

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Section: Resultsmentioning

confidence: 99%

The molecular landscape of Asian breast cancers reveals clinically relevant population-specific differences

Pan

Zabidi

et al. 2020

Nat Commun

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“…A recent study used a genetic risk score based on 287 SNPs in a European population and found an AUC of about 0.63. They also found that this same genetic risk score is applicable to a Chinese population, where it had an AUC of about 0.61[29]. One genetic risk score to predict breast cancer risk is commercially available and has been validated in several large cohorts with over 100,000 women.…”

Section: Discussionmentioning

confidence: 99%

A Genetic Risk Score for Glioblastoma Multiforme Based on Copy Number Variations

Brody

2021

Preprint

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Glioblastoma multiforme is the most common form of brain cancer. Several lines of evidence suggest that glioblastoma multiforme has a genetic basis. A genetic test that could identify people who are at high risk of developing glioblastoma multiforme could improve our understanding of this form of brain cancer.Using the Cancer Genome Atlas (TCGA) dataset, we found common germ line DNA copy number variations in the TCGA population. We tested whether different sets of these germ line DNA copy number variations could effectively distinguish patients with glioblastoma multiforme from others in the TCGA dataset. We used a gradient boosting machine, a machine learning classification algorithm, to classify TCGA patients solely based on a set of germline DNA copy number variations.We found that this machine learning algorithm could classify TCGA glioblastoma multiforme patients from the other TCGA patients with an area under the curve (AUC) of the receiver operating characteristic curve (AUC=0.875). Grouped into quintiles, the highest ranked quintile by the machine learning algorithm had an odds ratio of 3.78 (95% CI 3.25-4.40) higher than the average odds ratio and about 40 (95% CI 20-70) times higher than the lowest quintile.The identification of an effective germ line genetic test to stratify risk of developing glioblastoma multiforme should lead to a better understanding of how this cancer forms. This result might ultimately lead to better treatments of glioblastoma multiforme.

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“…The PRSs are strati ed by setting cut offs at below 60th percentile for the low risk group, 60th to 95th percentile for intermediate risk group and above 95th percentile for the high risk group. In the Asian population, these cutoffs correspond to expected proportions of 51%, 41% and 8% for low, intermediate and high risk groups respectively [18]. The starting age for this strategy was chosen based on ndings that women with a high genetic risk for developing breast cancer may reach the equivalent 10-year risk to an average 50-year old woman at 35 years of age [18].…”

Section: Methodsmentioning

confidence: 99%

“…In the Asian population, these cutoffs correspond to expected proportions of 51%, 41% and 8% for low, intermediate and high risk groups respectively [18]. The starting age for this strategy was chosen based on ndings that women with a high genetic risk for developing breast cancer may reach the equivalent 10-year risk to an average 50-year old woman at 35 years of age [18]. There is no clear guideline on the ending age for mammogram.…”

Section: Methodsmentioning

confidence: 99%

Cost Effectiveness Analysis of a Polygenic Risk Tailored Breast Cancer Screening Programme in Singapore

Wong

Chai

Yeoh

et al. 2021

Preprint

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BackgroundThis study aimed to evaluate the cost effectiveness of a breast cancer screening programme that incorporates genetic testing using breast cancer associated single nucleotide polymorphisms (SNPs) in Singapore, against the current biennial mammogram only screening programme.MethodsA Markov model was used to compare the costs and health outcomes of the current screening programme, against a polygenic risk tailored screening programme that advises long term screening depending polygenic risk. The model took the perspective of the healthcare system, with a time horizon of 40 years, following women from the age of 35 to 74. Epidemiological and cost data was taken from Asian studies. An annual discount rate of 3% was used. The model outcome was the incremental cost-effectiveness ratio (ICER), calculated from the difference in costs per quality adjusted life year (QALY). Scenarios with varying risk thresholds for each polygenic risk group were examined. One-way and probabilistic sensitivity analyses were performed to assess parameter uncertainty.ResultsThe ICER for a polygenic risk tailored breast cancer screening programme, compared to the current biennial mammogram only screening programme, was -3,713.80, with incremental costs <0 and incremental effects >0. Scenario analysis of different polygenic risk cutoffs showed that the ICERs remain negative, with all ICERs falling within the south east quadrant of the cost effectiveness plane, indicating that tailored screening dominates mammogram only screening with lower costs and higher QALYs. This suggests that a polygenic risk tailored breast cancer screening programme is cost effective, being cheaper than the current mammogram only programme while bringing no additional harm to women.ConclusionResults from this cost effectiveness analysis show that polygenic risk tailored screening is cost effective with an ICER of –3,713.80 SGD/QALY. Tailored screening remains cost effective even when varying percentile cutoffs for each risk group. While the results look promising for incorporating polygenic risk into the current breast cancer screening programme, further studies should be conducted due to various limitations.

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European polygenic risk score for prediction of breast cancer shows similar performance in Asian women

Cited by 97 publications

References 34 publications

The molecular landscape of Asian breast cancers reveals clinically relevant population-specific differences

The molecular landscape of Asian breast cancers reveals clinically relevant population-specific differences

A Genetic Risk Score for Glioblastoma Multiforme Based on Copy Number Variations

Cost Effectiveness Analysis of a Polygenic Risk Tailored Breast Cancer Screening Programme in Singapore

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