Genetic Prediction of Individual Breast Cancer Risk Peter Devilee - PowerPoint PPT Presentation

Genetic Prediction of Individual Breast Cancer Risk Peter Devilee Leiden University Medical Center

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10-Year risk to develop breast cancer in the Netherlands 4,00% 3,50% Absolute 3,00% risk 2,50% 2,00% 1,50% 1,00% 0,50% 0,00% 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age Data: Netherlands Cancer Registry, 1999-2003

Lifetime breast cancer risk in NL 16 14 12 10 % Risk 8 Incidence* 6 Death 4 2 0 1990 2000 2010 Year * Invasive + CIS; Bron: IKNL

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Risk stratification Communicating risk: • Relative risk • Absolute risk • Lifetime risk • Cumulative risk • 10-year risk 0% 100%

Br63 Br45 “Am I at risk?” Br46 44

Breast cancer prevention Options Disadvantages  Chemoprevention  Side-effects  Prophylactic surgery  Over-diagnosis  Screening  Increased cost Target those most likely to benefit Identify women at greatest disease risk

Br63 Br45 “Am I at risk?” Br46 44 Genetic Test

Genetic testing in NL 1991 1994 1995 2014 2018 Linkage BRCA1 CHEK2 PALB2 analysis BRCA2 Gene panels (Research) Specific Cancer Syndromes: TP53, PTEN, CDH1, NF1, . . . .

Genetic architecture of breast cancer TP53 1. BRCA1, BRCA2 CDH1 BRCA1 BRCA2 2. Non-B1/2 genes 10 STK11 3. Risk SNPs Relative Risk PALB2 PTEN CHEK2 ATM Risk SNPs 1 0,000001 0,00001 0,0001 0,001 0,01 0,1 1 Allele frequency

Risk management in NL Low (RR <2) Moderate (RR: 2-3) High (RR >3) Life time risk <20% 20-30% >30% Start screening 50 yr 40 yr 35 yr Physical - - + examination Mammography population <50 yr: annually <60 yr: annually screening >50 yr: population >60 yr: population screening screening MRI - - - BRCA1/2 mutation carriers:

Uncertainties in risk level PALB2 High 4x lifetime risk Moderate 2x lifetime risk Low CHEK2 Genetic risk Population risk 95% CI Easton et al. 2015

Br63 Br45 “Am I at risk?” Br46 44 BRCA1/2 Test = Negative

Breast cancer risk prediction tools  Absolute Risk Prediction Models  Gene Carrier Status Risk Prediction Models  Risk Prediction Models of Women at High Risk

Risk factors for breast cancer  Biology  Age  Hormonal factors  Breast density on mammogram  Lifestyle  Reproductive factors  Alcohol / smoking / physical exercise / obesity  Use of HRT, radiation exposure  Family history  Familial relative risk (FRR)

FRR for breast cancer is ~2-fold Number of Relative Risk Affected (99% CI) First Degree Relatives 1.00 0 (0.97 – 1.03) 1.80 ~12% of all patients 1 (1.70 – 1.91) and 7% of controls 2.93 2 (2.37 – 3.63) 3.90 ≥3 (2.03 – 7.49) Collaborative Group on Hormonal Factors in Breast Cancer (2001)

FRR explained by “genetics” (25 years of genetic research) Unexplained: 41%* Estimated on chip (18%) BRCA1 BRCA2 ~65 new SNPs Oncoarray (4%) CHEK2 ~80 new SNPs TP53 ATM 27 pre-iCOGS on iCOGS (5%) PTEN PALB2 SNPs (9%) LKB1 * For overall breast cancer in Europeans (Lower for ER-negative disease, early onset disease, and breast cancer in non-Europeans)

The multifactorial model Avg Risk Number of individuals Risk level Fletcher & Houlston (2010)

All breast cancer SNPs (N = 33,381) (N = 33,673) 77 SNPs – max 154 risk alleles Mavaddat et al (2015), JNCI 107: djv036

Two-way SNP interactions Mavaddat et al (2015), JNCI 107: djv036

A polygenic risk score (PRS) Under a polygenic multiplicative model For women in the highest 1% of the PRS, the estimated 5% of OR compared with women in the middle quintile was women 3.36 (95%CI: 2.95-3.83, p= 7.5x10 -74 ) 5% of women Mavaddat et al (2015), JNCI 107: djv036

Risk of developing breast cancer All Breast Cancers All Breast Cancers – Absolute lifetime risk 0.35 >99% 95-99% 0.30 90-95% 80-90% 0.25 60-80% Absolute risk 40-60% 0.20 20-40% 10-20% 0.15 80% of 5-10% women 1-5% 0.10 <1% 0.05 0.00 20 25 30 35 40 45 50 55 60 65 70 75 Age (years) Mavaddat et al (2015), JNCI 107: djv036

PRS and family history Mavaddat et al (2015), JNCI 107: djv036

Br63 Br45 “Am I at risk?” Br46 44 SNPs BRCA1/2 Test PRS = Negative Gene Panel ATM Testing

Panel testing: which genes are relevant? Gene Breast Ovary > 2x risk? BRCA1 Yes BRCA2 Probably TP53 Unlikely PTEN No CDH1 STK11 Unknown PALB2 ATM CHEK2 NF1 BRIP1 RAD51C RAD51D Douglas Easton, unpublished

Don’t just do panel testing! <0.1% Approx. Centile 1% 10% BRCA1 PALB2 CHEK2 ATM BRCA2 0.1 1 10 Relative Risk

Br63 Br45 “Am I at risk?” Br46 44 SNPs + Other risk factors: BRCA1/2 Test PRS = Negative • Family history Gene Panel ATM Testing • Breast density etc.

Examples * * * 1.24 1.62 1.02 1.50 1.68 1.55 1.62 * CHEK2* 1100delC PRS-160 Odds Ratio Hilbers et al., manuscript in preparation

Combining PRS with family history Lakeman et al., unpublished

Counseling familial breast cancer Current practice Future practice  Aimed at identifying or  A more holistic approach, excluding high risk aimed at establishing individual risk  Test affected individual  Anyone can be tested  In “positive” families:  A wide range of risk  Carriers are given gene- specific risks levels can be found  Those testing negative are  Some risk factors are given population risk modifiable  In “negative” families, family history determines risk

Outstanding issues  Which genes confer risk?  Allelic diversity and risk*  Imprecise risk estimates  How do risk factors combine?* * Journal Club

Filling in the gaps… Penetrance Linkage studies: exhausted Sequencing studies: Terra incognita GWA studies: Stretching limits 0.001 0.01 0.1 Allele frequency

Need to do REALLY BIG studies

BRIDGES Gene Panel Sequencing Studies Cases Controls Population-based 23 18,513 15,503 “Other” (clinic- 12 12,891 8,615 based, selected for FH or bilaterality) TOTAL 35 31,404 24,118

Truncating variants – known genes Pop-based Familial/other Gene Cases Controls OR OR (95%CI) P 6.7x10 -25 BRCA1 278 35 11.96 (7.01-20.41) 2.53 (1.37-4.67) 110 1.1x10 -24 BRCA2 394 3.51 (2.68-4.61) 2.85 (1.74-4.67) 29 17.48 (7.53-40.59) 4.9x10 -20 PALB2 224 4.39 (2.75-7.02) 83 3.3x10 -9 ATM 230 1.92 (1.33-2.76) 2.61 (1.67-4.10) 3.6x10 -41 CHEK2 706 166 2.48 (1.96-3.13) 5.16 (3.80-7.02) 2.6x10 -36 - 1100delC 591 130 2.67 (2.04-3.49) 5.05 (3.66-6.98) 3.0x10 -6 - other 117 36 1.94 (1.21-3.20) 4.07 (1.75-9.48) BRIDGES consortium, preliminary data

DNA variation and breast cancer miRNA binding sites Splicing signals 5’ 3’ UTR UTR Long-range Transcription Aminoacid Polyadenylation enhancers factor binding substitutions signals sites • Real breast cancer genes • Candidate breast cancer genes • Common SNPs

Complementation and HR efficiency 1,4 1,2 Relative HR to WT HBRCA2 hBRCA2 WT 1,0 0,8 0,6 0,4 0,2 0,0 Mesman et al., submitted

Translating functional results into cancer risk Continuous Model 1,2 1 Relative HR efficiency OR 1 0,8 OR 1.5 0,6 OR 2.0 0,4 OR 2.5 0,2 OR OR > 3 3.0 0 OR 8.0

Towards better risk prediction Genetics Family history Risk Calculator Lifestyle Hormonal factors Breast density Personal risk estimate

10-Year risk to develop breast cancer in the Netherlands 4,00% 3,50% Absolute 3,00% risk Start mammographic 2,50% screening 2,00% 1,50% 1,00% 0,50% 0,00% 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Age Data: Netherlands Cancer Registry, 1999-2003

Risk stratification 10-year risk all breast cancers, by SNP profile All Breast Cancers 0.12 >99% 95-99% 0.10 90-95% 80-90% 0.08 60-80% 20% of women 10 year risk reach threshold 40-60% OR = 1.00 before age 40 20-40% 0.06 10-20% 5-10% 0.04 1-5% Screening threshold <1% 0.02 20-40% of women never reach threshold 0.00 20 25 30 35 40 45 50 55 60 65 Age (years) Mavaddat et al (2015), JNCI 107: djv036

Identifying surveillance group Clinical Guideline: Enhanced surveillance when lifetime risk > 17% 17% of cases 8% of women Pop. Avg. Risk

Acknowlegdements LUMC (Inter)national  Romy Mesman, Inge  Douglas Easton Lakeman, Rick Boonen,  Jacques Simard Harry Vrieling, Haico van  Fergus Couch Attikum, Maaike  Matti Rookus (for Hebon) Vreeswijk, Mar Rodriguez  Clinical Genetics: Christi van Asperen, Setareh Moghadasi, Juul Wijnen

Thank you for your attention…