Implementing Polygenic Risk Scores for Breast Cancer Prevention: a Feasibility Study

Official title

Implementing Polygenic Risk Scores for Breast Cancer Prevention: Protocol for a Feasibility Study in a Real-world Clinical Setting

Overview

This single-arm interventional feasibility study will evaluate whether integrating polygenic risk scores (PRS) into the CanRisk model can improve breast cancer risk prediction and personalized prevention in women at risk of breast cancer. The study will assess the organizational feasibility, patient acceptance, emotional impact and satisfaction of an integrated pathway combining PRS testing with standard genetic counseling and other risk factors at Fondazione Policlinico Universitario Agostino Gemelli IRCCS.

Detailed description

This study will test the feasibility of integrating polygenic risk scores (PRS) into the CanRisk breast cancer risk model in a real-world clinical setting at Fondazione Policlinico Universitario Agostino Gemelli IRCCS. By embedding PRS testing into routine genetic counseling and patient care, the study aims to examine organizational, logistical, and patient-centered aspects of incorporating genomic data into breast cancer risk assessment.

Eligible participants include women with a family history of breast cancer, carriers of pathogenic variants included in CanRisk (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1), and women with unilateral breast cancer for controlateral risk assessment. Carriers of pathogenic variants not included in CanRisk (e.g., PTEN, TP53, CDH1) as well as women with bilateral breast cancer or ductal carcinoma in situ (DCIS), will be excluded, as CanRisk does not estimate risk for this condition.

All participants will provide a blood sample (9 mL in three K2EDTA tubes) for DNA extraction and SNP genotyping. PRS will be calculated using a 313-SNP array with ThermoFisher GeneTitan and the Axiom Precision Medicine Diversity Array, followed by standard quality control and genotype imputation. Results will be integrated into the CanRisk model previously calculated without PRS, to provide individualized risk estimates, in combination with clinical, anthropometric, and family history variables systematically collected for every participant.

Participants who request their CanRisk with PRS results will receive an email report approximately within one month of sample collection, summarizing their CanRisk estimates with and without PRS, and will be invited to complete a questionnaire on comprehension, perception, and emotional impact of the result. If the PRS leads to a change in risk classification, the case will be reviewed in a multidisciplinary discussion and the prevention plan may be modified accordingly. Participants who accept to be enrolled in the study but decline to receive their PRS results will be asked their reason, which will be documented verbatim.

Primary outcome:

Feasibility of CanRisk+PRS pathway assessment, measured by a 27-item Care Process Self-Evaluation Tool (CPSET) validated questionnaire, completed by both participants and healthcare staff at the end of the study.

Secondary outcomes:

1. Uptake of CanRisk+PRS pathway 2. Risk understanding and emotional impact, assessed using a validated questionnaire (Woof et al.) 3. Risk reclassification rate, after PRS integration in the CanRisk model assessment 4. Changes in breast cancer preventive pathway, recommended following multidisciplinary evaluation after CanRisk+PRS-based risk reclassification 5. Impact on overall distribution across risk categories after PRS integration

This study will generate evidence on the clinical, technical, and organizational feasibility of integrating PRS into breast cancer risk assessment, informing the future implementation of personalized prevention programs.

Interventions

• Genetic Clinical pathway for breast cancer prevention based on PRS-integrated CanRisk assessment
  Standard genetic counseling followed by a blood draw (0.5 mL) for DNA extraction. The sample is processed using a high-throughput SNP genotyping platform, and the PRS, based on 313 SNPs, is calculated and integrated into the CanRisk model for refined breast cancer risk stratification. In conjunction with result disclosure, participants complete structured questionnaires to assess psychological impact and risk comprehension (questionnaire by Woof et al.). At the end of the study, both participant

Primary outcome measures

• Feasibility of implementing an integrated clinical pathway including PRS [Time frame: At 12 months from enrollment]

Secondary outcome measures (6)

• Uptake of CanRisk+PRS integrated pathway [Time frame: At the time of enrollment, when eligible participants are offered PRS testing]
• Proportion of women requesting their individual CanRisk+PRS result [Time frame: At month 12.]
• Percentage of women reclassified into different risk categories after PRS integration [Time frame: At month 12]
• Proportion of women with modified prevention pathways after PRS-informed reclassification [Time frame: At month 12.]
• Perception of risk and psychological impact [Time frame: At month 12]
• Global redistribution of risk categories after PRS integration [Time frame: At month 12.]

Eligibility criteria

Inclusion criteria

• Ability to provide informed consent
• Voluntary consent to participate
• Estimated risk of carrying an inherited pathogenic variant (in BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1) > 5%, (calculated on www.canrisk.org)
• Healthy women with:

• Known family history of breast cancer, or
• Known familiarity with carriers of pathogenic variants for genes included in the CanRisk model (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1), or
• Known carriers of pathogenic variants for genes included in the CanRisk model (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1)
• Affected women with:

• Diagnosis of unilateral breast cancer
• Personal history of ovarian cancer

Exclusion criteria

• Diagnosis or history of bilateral breast cancer
• Diagnosis of ductal carcinoma in situ
• Previous bilateral mastectomy
• Life expectancy < 12 months due to other medical conditions
• Participation in interventional clinical trials for breast cancer prevention in the last 12 months
• Carriers or relatives of carriers of pathogenic variants in genes not included in the CanRisk model (genes other than BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1)
• Inability to provide informed consent

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation

N/A

Model

Single group

Masking

Open label

Primary purpose

Prevention

Study locations

Italy · 1 center

• Policlinico Universitario Fondazione Agostino Gemelli — Roma

Publications

• Vanhaecht K, De Witte K, Depreitere R, Van Zelm R, De Bleser L, Proost K, Sermeus W. Development and validation of a care process self-evaluation tool. Health Serv Manage Res. 2007 Aug;20(3):189-202. doi: 10.1258/095148407781395964. PMID 17683658
• Du Z, Gao G, Adedokun B, Ahearn T, Lunetta KL, Zirpoli G, Troester MA, Ruiz-Narvaez EA, Haddad SA, PalChoudhury P, Figueroa J, John EM, Bernstein L, Zheng W, Hu JJ, Ziegler RG, Nyante S, Bandera EV, Ingles SA, Mancuso N, Press MF, Deming SL, Rodriguez-Gil JL, Yao S, Ogundiran TO, Ojengbe O, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Sandler DP, Taylor JA, Wang Q, Weinbe PMID 33769540
• Lakeman IMM, Rodriguez-Girondo M, Lee A, Ruiter R, Stricker BH, Wijnant SRA, Kavousi M, Antoniou AC, Schmidt MK, Uitterlinden AG, van Rooij J, Devilee P. Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort. Genet Med. 2020 Nov;22(11):1803-1811. doi: 10.1038/s41436-020-0884-4. Epub 2020 Jul 6. PMID 32624571
• Archer S, Donoso FS, Carver T, Yue A, Cunningham AP, Ficorella L, Tischkowitz M, Easton DF, Antoniou AC, Emery J, Usher-Smith J, Walter FM. Exploring the barriers to and facilitators of implementing CanRisk in primary care: a qualitative thematic framework analysis. Br J Gen Pract. 2023 Jul 27;73(733):e586-e596. doi: 10.3399/BJGP.2022.0643. Print 2023 Aug. PMID 37308304
• Vassy JL, Brunette CA, Lebo MS, MacIsaac K, Yi T, Danowski ME, Alexander NVJ, Cardellino MP, Christensen KD, Gala M, Green RC, Harris E, Jones NE, Kerman BJ, Kraft P, Kulkarni P, Lewis ACF, Lubitz SA, Natarajan P, Antwi AA. The GenoVA study: Equitable implementation of a pragmatic randomized trial of polygenic-risk scoring in primary care. Am J Hum Genet. 2023 Nov 2;110(11):1841-1852. doi: 10.1016 PMID 37922883
• Tsoulaki O, Tischkowitz M, Antoniou AC, Musgrave H, Rea G, Gandhi A, Cox K, Irvine T, Holcombe S, Eccles D, Turnbull C, Cutress R; Meeting Attendees; Archer S, Hanson H. Joint ABS-UKCGG-CanGene-CanVar consensus regarding the use of CanRisk in clinical practice. Br J Cancer. 2024 Jun;130(12):2027-2036. doi: 10.1038/s41416-024-02733-4. Epub 2024 Jun 4. PMID 38834743
• Mbuya-Bienge C, Pashayan N, Kazemali CD, Lapointe J, Simard J, Nabi H. A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population. Cancers (Basel). 2023 Nov 12;15(22):5380. doi: 10.3390/cancers15225380. PMID 38001640
• Hovhannisyan M, Zemankova P, Nehasil P, Matejkova K, Borecka M, Cerna M, Dolezalova T, Dvorakova L, Foretova L, Horackova K, Jelinkova S, Just P, Kalousova M, Kral J, Machackova E, Nemcova B, Safarikova M, Springer D, Stastna B, Tavandzis S, Vocka M, Zima T, Soukupova J, Kleiblova P, Ernst C, Kleibl Z, Janatova M. Population-specific validation and comparison of the performance of 77- and 313-vari PMID 38718029

Identifiers

NCT: NCT06922708 · 7310 · No. D.D. 931

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗