To better understand the expression pattern of programmed death-ligand 1 (PD-L1) expression in different breast cancer types, we characterized PD-L1 expression in tumor and tumor-infiltrating immune ...cells, in relation to mutation rate, BRCA1-like status and survival. We analyzed 410 primary treatment-naive breast tumors comprising 162 estrogen receptor-positive (ER+) and HER2−, 101 HER2+ and 147 triple-negative (TN) cancers. Pathologists quantified tumor-infiltrating lymphocytes (TILs) and PD-L1 expression in tumor cells and TILs using whole slides and tissue microarray. Mutation rate was assessed by DNA sequencing, BRCA1-like status using multiplex ligation-dependent probe amplification, and immune landscape by multiplex image analyses of CD4, CD68, CD8, FOXP3, cytokeratin, and PD-L1. Half of PD-L1 scores evaluated by tissue microarray were false negatives compared to whole slide evaluations. We observed at least 1% of PD-L1-positive (PD-L1+) cells in 53.1% of ER+HER2−, 73.3% of HER2+, and 84.4% of TN tumors. PD-L1 expression was higher in ductal compared to lobular carcinomas, also within ER+HER2− tumors (p = 0.04). High PD-L1+ TILs score (> 50%) was independently associated with better outcome in TN tumors (HR = 0.27; 95%CI = 0.10-0.69). Within TN tumors, PD-L1 and TIL scores showed a modest but significant positive association with the number of silent mutations, but no association with BRCA1-like status. Multiplex image analyses indicated that PD-L1 is expressed on multiple immune cells (CD68+ macrophages, CD4+, FOXP3+, and CD8+ T cells) in the breast tumor microenvironment, independent of the PD-L1 status of the tumor cells. We found no evidence that levels of PD-L1+ TILs in TN breast cancer are driven by high mutation rate or BRCA1-like status.
To assess cause-specific mortality in women treated for ductal carcinoma in situ (DCIS).
From screening and treatment perspective, it is relevant to weigh the low breast cancer mortality after DCIS ...against mortality from other causes and expected mortality in the general population.
We conducted a population-based cohort study comprising 9799 Dutch women treated for primary DCIS between 1989 and 2004 and estimated standardized mortality ratios (SMRs).
After a median follow up of 9.8 years, 1429 patients had died of whom 284 caused by breast cancer (2.9% of total cohort). DCIS patients <50 years experienced higher mortality compared with women in the general population (SMR 1.7; 95% confidence interval, CI: 1.4-2.0), whereas patients >50 had significantly lower mortality (SMR 0.9; 95% CI: 0.8-0.9). Overall, the risk of dying from general diseases and cancer other than breast cancer was lower than in the general population, whereas breast cancer mortality was increased. The SMR for breast cancer decreased from 7.5 (95% CI: 5.9-9.3) to 2.8 (95% CI: 2.4-3.2) for women aged <50 and >50 years, respectively. The cumulative breast cancer mortality 10 years after DCIS was 2.3% for women <50 years and 1.4% for women >50 years treated for DCIS between 1999 and 2004.
DCIS patients >50 years had lower risk of dying from all causes combined compared with the general female population, which may reflect differences in health behavior. Women with DCIS had higher risk of dying from breast cancer than the general population, but absolute 10-year risks were low.
To determine prospectively overall and age-specific estimates of contralateral breast cancer (CBC) risk for young patients with breast cancer with or without BRCA1/2 mutations.
A cohort of 6,294 ...patients with invasive breast cancer diagnosed under 50 years of age and treated between 1970 and 2003 in 10 Dutch centers was tested for the most prevalent BRCA1/2 mutations. We report absolute risks and hazard ratios within the cohort from competing risk analyses.
After a median follow-up of 12.5 years, 578 CBCs were observed in our study population. CBC risk for BRCA1 and BRCA2 mutation carriers was two to three times higher than for noncarriers (hazard ratios, 3.31 95% CI, 2.41 to 4.55; P < .001 and 2.17 95% CI,1.22 to 3.85; P = .01, respectively). Ten-year cumulative CBC risks were 21.1% (95% CI, 15.4 to 27.4) for BRCA1, 10.8% (95% CI, 4.7 to 19.6) for BRCA2 mutation carriers and 5.1% (95% CI, 4.5 to 5.7) for noncarriers. Age at diagnosis of the first breast cancer was a significant predictor of CBC risk in BRCA1/2 mutation carriers only; those diagnosed before age 41 years had a 10-year cumulative CBC risk of 23.9% (BRCA1: 25.5%; BRCA2: 17.2%) compared with 12.6% (BRCA1: 15.6%; BRCA2: 7.2%) for those 41 to 49 years of age (P = .02); our review of published studies showed ranges of 24% to 31% before age 40 years (BRCA1: 24% to 32%; BRCA2:17% to 29%) and 8% to 21% after 40 years (BRCA1: 11% to 52%; BRCA2: 7% to 18%), respectively.
Age at first breast cancer is a strong risk factor for cumulative CBC risk in BRCA1/2 mutation carriers. Considering the available evidence, age-specific risk estimates should be included in counseling.
Ductal carcinoma in situ (DCIS) is widely accepted as a precursor of invasive ductal carcinoma (IDC). Lobular carcinoma in situ (LCIS) is considered a risk factor for invasive lobular carcinoma ...(ILC), and it is unclear whether LCIS is also a precursor. Therefore, it would be expected that similar risk factors predispose to both DCIS and IDC, but not necessarily LCIS and ILC. This study examined associations with risk factors using data from 3075 DCIS cases, 338 LCIS cases, and 1584 controls aged 35–60, recruited from the UK-based GLACIER and ICICLE case-control studies between 2007 and 2012. Analysis showed that breastfeeding in parous women was protective against DCIS and LCIS, which is consistent with research on invasive breast cancer (IBC). Additionally, long-term use of HRT in post-menopausal women increased the risk of DCIS and LCIS, with a stronger association in LCIS, similar to the association with ILC. Contrary to findings with IBC, parity and the number of births were not protective against DCIS or LCIS, while oral contraceptives showed an unexpected protective effect. These findings suggest both similarities and differences in risk factors for DCIS and LCIS compared to IBC and that there may be justification for increased breast surveillance in post-menopausal women taking long-term HRT.
Ductal carcinoma
(DCIS) is treated to prevent progression to invasive breast cancer. Yet, most lesions will never progress, implying that overtreatment exists. Therefore, we aimed to identify factors ...distinguishing harmless from potentially hazardous DCIS using a nested case-control study.
We conducted a case-control study nested in a population-based cohort of patients with DCIS treated with breast-conserving surgery (BCS) alone (
= 2,658) between 1989 and 2005. We compared clinical, pathologic, and IHC DCIS characteristics of 200 women who subsequently developed ipsilateral invasive breast cancer (iIBC; cases) and 474 women who did not (controls), in a matched setting. Median follow-up time was 12.0 years (interquartile range, 9.0-15.3). Conditional logistic regression models were used to assess associations of various factors with subsequent iIBC risk after primary DCIS.
High COX-2 protein expression showed the strongest association with subsequent iIBC OR = 2.97; 95% confidence interval (95% CI), 1.72-5.10. In addition, HER2 overexpression (OR = 1.56; 95% CI, 1.05-2.31) and presence of periductal fibrosis (OR = 1.44; 95% CI, 1.01-2.06) were associated with subsequent iIBC risk. Patients with HER2
/COX-2
DCIS had a 4-fold higher risk of subsequent iIBC (vs. HER2
/COX-2
DCIS), and an estimated 22.8% cumulative risk of developing subsequent iIBC at 15 years.
With this unbiased study design and representative group of patients with DCIS treated by BCS alone, COX-2, HER2, and periductal fibrosis were revealed as promising markers predicting progression of DCIS into iIBC. Validation will be done in independent datasets. Ultimately, this will aid individual risk stratification of women with primary DCIS.
.
The multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all ...established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort.
We validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45-63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes:
,
,
,
,
,
,
and
. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC).
Among the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%).
The multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.
Abstract
Background
Conventional epidemiologic studies have evaluated associations between circulating lipid levels and breast cancer risk, but results have been inconsistent. As Mendelian ...randomization analyses may provide evidence for causal inference, we sought to evaluate potentially unbiased associations between breast cancer risk and four genetically predicted lipid traits.
Methods
Previous genome-wide association studies (GWAS) have identified 164 discrete variants associated with high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), triglycerides and total cholesterol. We used 162 of these unique variants to construct weighted genetic scores (wGSs) for a total of 101 424 breast cancer cases and 80 253 controls of European ancestry from the Breast Cancer Association Consortium (BCAC). Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between per standard deviation increase in genetically predicted lipid traits and breast cancer risk. Additional Mendelian randomization analysis approaches and sensitivity analyses were conducted to assess pleiotropy and instrument validity.
Results
Corresponding to approximately 15 mg/dL, one standard deviation increase in genetically predicted HDL-C was associated with a 12% increased breast cancer risk (OR: 1.12, 95% CI: 1.08–1.16). Findings were consistent after adjustment for breast cancer risk factors and were robust in several sensitivity analyses. Associations with genetically predicted triglycerides and total cholesterol were inconsistent, and no association for genetically predicted LDL-C was observed.
Conclusions
This study provides strong evidence that circulating HDL-C may be associated with an increased risk of breast cancer, whereas LDL-C may not be related to breast cancer risk.
To determine the changes in surveillance category by adding a polygenic risk score based on 311 breast cancer (BC)-associated variants (PRS311), questionnaire-based risk factors and breast density on ...personalized BC risk in unaffected women from Dutch CHEK2 c.1100delC families.
In total, 117 unaffected women (58 heterozygotes and 59 non-carriers) from CHEK2 families were included. Blood-derived DNA samples were genotyped with the GSAMDv3-array to determine PRS311. Lifetime BC risk was calculated in CanRisk, which uses data from the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). Women, were categorized into three surveillance groups.
The surveillance advice was reclassified in 37.9 % of heterozygotes and 32.2 % of non-carriers after adding PRS311. Including questionnaire-based risk factors resulted in an additional change in 20.0 % of heterozygotes and 13.2 % of non-carriers; and a subanalysis showed that adding breast density on top shifted another 17.9 % of heterozygotes and 33.3 % of non-carriers. Overall, the majority of heterozygotes were reclassified to a less intensive surveillance, while non-carriers would require intensified surveillance.
The addition of PRS311, questionnaire-based risk factors and breast density to family history resulted in a more personalized BC surveillance advice in CHEK2-families, which may lead to more efficient use of surveillance.
•Lifetime breast cancer risk in unaffected CHEK2 heterozygotes and familial non-carriers was calculated using CanRisk.•Risks ranged from 22.1‑51.7% in heterozygotes and 10.7‑31.0% in non-carriers based on family history alone.•Adding PRS311 caused the largest shift in risk prediction, followed by breast density and questionnaire-based risk factors.•Risk stratifications were similar among distant relatives, not supporting modified cascade screening in CHEK2 families.
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