Abstract
Purpose
The prognostic value of ER/PgR expression in ductal carcinoma in situ (DCIS) is unclear. We observed multi-clonality when evaluating ER/PgR expression in the UK/ANZ DCIS trial, therefore, we investigated the prognostic role of both uni-clonal and multi-clonal ER/PgR expression in DCIS.
Experimental Design
Formalin-fixed paraffin embedded (FFPE) tissues were collected from UK/ANZ DCIS trial participants (n=755) and ER/PgR expression was evaluated by immunohistochemistry in 181 cases (with recurrence) matched to 362 controls by treatment-arm and age. Assays were scored by the Allred method and by a newly devised clonal method - analyses categorising multi-clonal DCIS as ER/PgR-positive as per current practice (Standard) and as ER/PgR-negative (clonal) were performed.
Results
ER expression was multi-clonal in 11% (39/356) of ER-positive (70.6%, 356/504) patients. Ipsilateral breast event (IBE) risk was similarly higher in ER-multi-clonal and ER-negative DCIS as compared to DCIS with uni-clonal ER expression. ER-negative DCIS (clonal) had a higher risk of in situ IBE (DCIS-IBE) [Odds ratio (OR) 4.99; 95% Confidence Interval (CI) 2.66-9.36; p<0.0001] but the risk of invasive IBE was not significantly higher (OR 1.72; 95%CI, 0.84-3.53; p=0.14), pheterogeneity=0.03. ER was an independent predictor in multivariate analyses (OR 2.66; 95%CI, 1.53-4.61). PgR status did not add to the prognostic information provided by ER.
Conclusions
ER expression is a strong predictor of ipsilateral recurrence risk in DCIS. ER-positive DCIS with distinct ER-negative clones has a recurrence risk similar to ER-negative DCIS. ER should be routinely assessed in DCIS and ER scoring should take clonality of expression into account.
Keywords: ductal carcinoma in situ (DCIS), invasive breast cancer, ER, PgR, Recurrence, Prognostic factor
Introduction
Estrogen receptor (ER) expression is a well-established prognostic and predictive biomarker for invasive breast cancer. The prognostic and predictive role of ER expression in ductal carcinoma in situ (DCIS) is less clear and consequently it is not routinely evaluated in DCIS in many parts of the world (1,2).
Prognostic and predictive factors both play important role in treatment of cancers, with the former predicting the risk of recurrence and thereby guiding intensity of therapeutic approach including surgical treatment and the latter assisting in selection of adjuvant treatment/s. In DCIS patients where breast conservation is feasible, adjuvant treatment is currently mainly guided by grade and tumor size. However, wide variations in practice remain among different regions of the world, including variations in ER evaluation (1,2) and use of adjuvant endocrine therapy. For example, ESMO Guidelines (3) recommend adjuvant radiotherapy in low / intermediate grade DCIS larger than 10mm, whereas many centers do not routinely offer radiotherapy in any low / intermediate grade DCIS or in tumors smaller than 25mm, similar to patients in the cohort 1 of E5194 trial (4) in the USA. The 12-year ipsilateral breast event (IBE) rate without radiotherapy was 14.4% in this E5194 cohort (4), which is neither high nor low. A prognostic factor independent of grade and tumor size can further stratify such patients in low and high-risk groups to aid adjuvant radiotherapy decisions. Furthermore, a prognostic factor can also aid in surgical decisions. For example, a patient with a high-grade DCIS lesion requiring level II oncoplastic procedure with complex localisation and a high chance of margin involvement may opt for a mastectomy with immediate breast reconstruction and avoid radiotherapy altogether if an independent prognostic factor predicts even higher IBE risk. Common molecular prognostic and predictive factors in invasive breast cancer viz. ER, PgR and HER2 may fulfil such a role and merit further research to evaluate their role in DCIS.
Twenty-six studies (Supplementary references S1-S26) have investigated the prognostic role of ER in DCIS, however, only 5 of these (5-9) found a statistically significant lower risk IBE in ER-positive cases. Allred et al (10) assessed the role of ER in predicting benefit of adjuvant tamoxifen in the NSABP-B24 trial. They determined ER status in 732 (40.6%) participants by central (n=449; 24.9%) or local (n=283; 15.7%) assessment. Tamoxifen reduced recurrences by 42% in ER-positive DCIS [Hazard Ratio (HR) 0.58; 95% Confidence Interval (CI), 0.42-0.81] but not in ER-negative DCIS (HR=0.88; 95%CI, 0.49-1.59). These results suggesting predictive role of ER were based on combining central and local institutional assessments with only 74.5% agreement (positive versus negative) in a subset of patients (n=102) with both assessments.
Only two of 17 studies (Supplementary references S1-S7,S10,S12-S14,S16-S20,S22,S23,S26,S27) investigating the relationship between progesterone receptor (PgR) expression and recurrence in DCIS reported a statistically significant relationship (6,8). In the NSABP-B24 study (10), PgR expression was predictive of tamoxifen benefit, but was not more informative than ER.
The lack of significant association between ER/PgR expression and IBE risk in most studies is unsurprising given their limitations, such as small sample size and treatment-related confounding. ER expression is inversely associated with adverse histological features in DCIS (11) and this may result in treatment bias, for example, more frequent use of adjuvant radiotherapy or mastectomy in ER-negative DCIS, thus confounding the true association between ER and IBE risk. Therefore, the prognostic role of ER/PgR expression in DCIS is still unclear and a well-designed study that overcomes these limitations is needed. This is best achieved through a randomized trial with long-term follow-up. We evaluated prognostic value of ER/PgR expression in DCIS in a case-control study within in the UK/ANZ DCIS trial (12). During the course of this study, we observed multi-clonal ER/PgR expression in DCIS and assessed the prognostic relevance of multi-clonality. This led to a new method for assigning ER/PgR status – designated as the clonal method.
Methods
Study population
The study samples were derived from the UK/ANZ DCIS trial participants (12); a randomized 2X2 factorial design trial investigating roles of tamoxifen and/or radiotherapy as adjuvant treatment in DCIS. The trial enrolled a total of 1694 patients (Supplementary Figure S1) and median follow-up is 12.7 years (12). Pathology material collection and use in biomarker studies was approved by the National Research Ethics Service - Joint UCL/UCLH Committees on Ethics of Human Research.
Formalin-fixed paraffin embedded (FFPE) tissue blocks containing DCIS were collected from 36 hospitals in the UK. The subset, labelled as biomarker study subset 1 (BSS1) hereafter, comprised 755 (45%) patients, it was similar to the remaining trial population with regard to treatment allocation and clinico-pathological factors including age and completeness of excision but contained a significantly higher proportion of high grade tumors, and large tumors with necrosis (Supplementary Table S1).
Study design
A case-control study (below) was nested within the BSS1 to eliminate any residual treatment-related confounding. Study sample size was not formally estimated, and ER/PgR expression was evaluated in all case-control samples. This study is reported in accordance with the REMARK criteria (13).
Case-control matching
Controls (participants without recurrence) were individually matched (1:2 case-control ratio) to cases (participants with in situ or invasive recurrence) by - age + 7 years and treatment allocation; controls had to be followed up for at least the same length of time as the time-to-event in their matching case (supplementary material). The nested case-control study (NCC) comprised 181 cases and 362 controls (Table 1).
Table 1. Clinicopathological characteristics of patients included in the case-control study.
| Variable | Strata | Cases | Controls | χ2 | p |
|---|---|---|---|---|---|
| Patients | N | 181 | 362 | ||
| Age | Median (IQR) [y] | 56.9 (52.9-61.2) | 57.0 (53.5-61.5) | 0.10 | 0.75† |
| Tumor size | Median (IQR) [mm] | 16.0 (12-22) (n=166) | 14.0 (8.5-19) (n=319) | 13.07 | 0.0003† |
| Grade | Low | 5 (2.8%) | 22 (6.1%) | 7.50 | 0.023 |
| Intermediate | 17 (9.4%) | 53 (14.6%) | |||
| High | 142 (78.5%) | 240 (66.3%) | |||
| No information | 17 (9.4%) | 47 (13.0%) | |||
| Necrosis | Absent | 6 (3.3%) | 31 (8.6%) | 5.94 | 0.015 |
| Present | 160 (88.4%) | 284 (78.5%) | |||
| No information | 15 (8.3%) | 47 (13.0%) | |||
| Inflammation | Absent | 21 (11.6%) | 68 (18.8%) | 6.15 | 0.013 |
| Present | 144 (79.6%) | 240 (66.3%) | |||
| No information | 16 (8.8%) | 54 (14.9%) | |||
| Excision | Incomplete | 37 (20.4%) | 43 (11.9%) | 7.91 | 0.019 |
| Uncertain | 29 (16.0%) | 49 (13.5%) | |||
| Complete | 102 (56.4%) | 236 (65.2%) | |||
| No information | 13 (7.2%) | 34 (9.4%) | |||
| ER | Negative | 73 (40.3%) | 75 (20.7%) | 31.83 | <0.0001 |
| Multiclonal | 19 (10.5%) | 20 (5.5%) | |||
| Positive | 78 (43.1%) | 239 (66.0%) | |||
| No information | 11 (6.1%) | 28 (7.7%) | |||
| PgR | Negative | 77 (42.5%) | 86 (23.8%) | 26.12 | <0.0001 |
| Multiclonal | 33 (18.2%) | 51 (14.1%) | |||
| Positive | 59 (32.6%) | 192 (53.0%) | |||
| No information | 12 (6.6%) | 33 (9.1%) | |||
| RT | Not given | 140 (77.4%) | 280 (77.4%) | 0 | 1 |
| Given | 41 (22.7%) | 82 (22.7%) | |||
| Tamoxifen | Not given | 97 (53.6%) | 194 (53.6%) | 0 | 1 |
| Given | 84 (46.4%) | 168 (46.4%) | |||
IQR – Inter-Quartile Range; †: Wilcoxon rank-sum test; Missing values, although given in “No Information” row, are not treated as a separate category;
Immunohistochemistry assays and evaluation of ER and PgR
ER and PgR immunohistochemistry (IHC) assays were performed on whole sections using mouse monoclonal antibodies 1D5 (Dako) and PGR636 (Dako) respectively (14,15) and the EnVision™ FLEX+ detection system (Dako UK Ltd., Ely, UK) on a Dako Autostainer (Dako).
Assays were scored by the Allred method (16), and H-scores (17) were also recorded. Multi-clonal nature of ER/PgR expression (Supplementary Figure S2) was observed and a new scoring method - designated the “clonal method”, was devised. ER or PgR-positive DCIS was labelled as ER-multi-clonal or PgR-multi-clonal if it showed presence of at least 1 carcinoma in situ (CIS) duct with a complete lack of ER or PgR expression (independent of different DCIS components such as morphological patterns and grades). Under the hypothesis that clonal subpopulations of cancer cells completely lacking ER or PgR expression are the dominant clones with a greater impact on outcome, such multi-clonal DCIS was assigned ER/PgR-negative status by the clonal method. In short, current methods (e.g. Allred, Quick score) classify ER-multi-clonal DCIS as ER-positive, whereas the clonal method classifies it as ER-negative.
Clinico-pathological variables
Data on clinico-pathological variables were derived from the trial database and a pathology review (18). Age, completeness of excision, treatment allocation, tumor size (in mm), cytonuclear grade (UK National Pathology Group) (19), necrosis and periductal inflammation were analyzed.
Statistical analysis
Trial procedures, follow-up (12) and a histopathology review (18) have been reported previously. For these analyses, only the first recurrence event was considered. Missing data were not imputed. Associations between a continuous and an ordinal variable were assessed by the Kruskal-Wallis test and those between 2 ordinal variables by Goodman-Kruskal’s gamma. Analyses of the risk of recurrence by groups were performed using conditional logistic regression model to estimate matched Odds Ratios (mORs) with 95%CI. These univariate [ER or PgR or Hormone Receptor (HR)] and multivariate analyses (additional covariates tumor size, grade, completeness of excision, presence of necrosis, and presence of inflammation) used any ipsilateral breast event (IBE) as the primary case definition. Analyses with in situ IBE (DCIS-IBE) and invasive IBE (I-IBE) as case definitions were also performed.
Analyses using the Allred method are labelled as ER (standard)/PgR (standard) and those using the clonal method are labelled as ER (clonal)/PgR (clonal). Sensitivity analyses separating ER or PgR status into 3 categories viz. pure positive, multi-clonal, and negative were also performed.
All P values are two-sided and values <0·05 were deemed significant. Comparisons of different models were based on differences in χ2 values of respective likelihood ratio (LR) tests. Statistical analyses were performed using STATA 13.0 (StataCorp LP, College Station, TX, USA). Kaplan-Meier survival plots weighted for control sampling in the BSS1 were generated using NestedCohort (20,21) package (version 1.1-3) in R (version 3.3.2; R Foundation for Statistical Computing, Vienna, Austria).
Results
ER expression in DCIS
One-hundred and forty-eight (29.4%) of 504 evaluable tumors were ER-negative and 356 (70.6%) were ER-positive (Table 1) with 39 (11%) of these displaying multi-clonal ER expression (Supplementary Figure S2, Supplementary Table S2), median Allred score in ER-multi-clonal cases was 7 [interquartile range (IQR) 5-8] and 15 (38.5%) cases had Allred score of 8. Thirty-nine samples were not evaluable (see supplementary material).
ER positivity was associated with decreasing age (p=0.011), tumor size (p=0.0009), cytonuclear grade (19) (p<0.0001), necrosis (p<0.0001), and periductal inflammation (p<0.0001) (Supplementary Table S3). ER correlated strongly with PgR (χ2=6249; p<0.0001); 31 (79.5%) ER-multi-clonal cases had multi-clonal PgR expression, 5 (12.8%) were PgR-negative and 3 (7.7%) were PgR-positive.
ER status and the risk of recurrence
ER-negative (standard) DCIS had an almost 3-fold higher risk of ipsilateral recurrence (mOR=2.81; 95%CI, 1.76-4.48) in univariate analyses, mainly driven by a higher DCIS-IBE risk (Table 2). The risk of I-IBE was non-significantly increased. However, the increase in I-IBE risk was not significantly different than that in DCIS-IBE risk (pheterogeneity=0.06). Prognostic discrimination was higher when ER status was determined by the clonal method [Δχ2 8.64 (IBE), 9.47 (DCIS-IBE), 1.03 (I-IBE)] and the increase in DCIS-IBE risk (mOR=4.99; 95%CI, 2.66-9.36) was significantly higher (pheterogeneity=0.03) than the increase in I-IBE risk (mOR=1.72; 95%CI, 0.84-3.53). ER-negative (clonal) DCIS had a 5-fold higher risk of DCIS-IBE. With ER-negative DCIS as reference, the OR for multi-clonal DCIS was very close to unity (Table 3). Thus, while ER-multi-clonal DCIS cases are classified as ER-positive by current methods, these lesions behave much more like ER-negative DCIS in terms of high recurrence risk. Survival curves for ER-negative and ER-multi-clonal DCIS were very similar in Kaplan-Meier survival plots (Figure 1). Allred score (continuous variable) was a predictor of IBE risk (mOR=0.88; 95%CI, 0.83-0.93), however, addition of ER (clonal) significantly improved the model [Δχ2 (1d.f.) 9.33; p=0.0023]. ER-positive (clonal) status (mOR=0.27; 95%CI, 0.11-0.63) and not the Allred score (mOR=1.02; 95%CI, 0.91-1.15) was an independent predictor in this model confirming that the association between IBE risk and multi-clonal ER expression is independent of Allred score.
Table 2. Univariate analysis of ER status (standard and clonal) as a predictor of recurrence.
| Case-definition | Events | Standard method | Clonal method | ||||
|---|---|---|---|---|---|---|---|
| mOR (95%CI) | p | mOR (95%CI) | p | ||||
| ER-negative n = 148 | ER-positive n = 346 | ER-negative n = 187 | ER-positive n = 307 | ||||
| IBE 138 | 2.81 (1.76-4.48) | 0.36 (0.22-0.57) | <0.0001 | 3.33 (2.09-5.30) | 0.30 (0.19-0.48) | <0.0001 | |
| I-IBE 51 | 1.53 (0.71-3.26) | 0.66 (0.31-1.40) | 0.28 | 1.72 (0.84-3.53) | 0.58 (0.28-1.20) | 0.14 | |
| DCIS-IBE 85 | 3.85 (2.09-7.08) | 0.26 (0.14-0.48) | <0.0001 | 4.99 (2.66-9.36) | 0.20 (0.11-0.38) | <0.0001 | |
Matched odds ratio (mOR) for ER-negative DCIS versus ER-positive DCIS; recurrence type not known in 2 cases.
Note: The mORs presented in this table are in both directions, i.e. with ER-positive as reference in the first column and ER-negative as reference in the second column to permit easier comparisons with the published literature.
Table 3. ER status as a predictor of recurrence when multi-clonal DCIS is categorised separately.
| Case-definition | events | Subgroup | mOR (95%CI) | p | mOR (95%CI) | p |
|---|---|---|---|---|---|---|
| IBE | 138 | ER-positive* | 1 (reference) | - | 0.30 (0.18-0.49) | <0.0001 |
| ER-multi-clonal | 3.23 (1.48-7.04) | 0.0033 | 0.96 (0.44-2.13) | 0.93 | ||
| ER-negative | 3.36 (2.04-5.51) | <0.0001 | 1 (reference) | - | ||
| I-IBE | 51 | ER-positive* | 1 (reference) | - | 0.61 (0.28-1.34) | 0.22 |
| ER-multi-clonal | 2.14 (0.54-8.49) | 0.28 | 1.31 (0.30-5.69) | 0.72 | ||
| ER-negative | 1.63 (0.75-3.55) | 0.22 | 1 (reference) | - | ||
| DCIS-IBE | 85 | ER-positive* | 1 (reference) | - | 0.20 (0.10-0.38) | <0.0001 |
| ER-multi-clonal | 4.66 (1.73-12.54) | 0.002 | 0.92 (0.34-2.44) | 0.86 | ||
| ER-negative | 5.09 (2.61-9.89) | <0.0001 | 1 (reference) | - |
Matched odds ratio (mOR); * Uni-clonal ER-positive - DCIS not exhibiting multi-clonal expression; recurrence type not known in 2 cases.
Note: The mORs presented in this table are in both directions, i.e. with ER-positive (uni-clonal) as reference in the first column and ER-negative as reference in the second column.
Figure 1. Kaplan-Meier survival plots* for IBE by ER expression in DCIS, ER multi-clonal cases plotted as a separate category.
* Plots weighted for control sampling in the BSS1 using NestedCohort (20,21) package.
The role of ER expression in Multivariate analyses
Inclusion of ER (standard) in a multivariate model including clinico-pathological variables (tumor size, grade, completeness of excision, presence of necrosis, and presence of inflammation – null-model) significantly improved the model [Δχ2 (1d.f.) 10.55; p=0.0012] and ER-negative (standard) status was an independent predictor of recurrence (mOR=2.42; 95%CI, 1.40-4.19; p=0.0016). The improvement in model was greater [Δχ2 (1d.f.) 13.28; p=0.0003] with ER (clonal) (Table 4). Analyses with multi-clonal DCIS as a separate category show similar results (Supplementary Table S4).
Table 4. Multivariate analysis of ER (clonal), other tumor characteristics and completeness of excision as a prognostic factor for IBE.
| Variable | Subgroup | n | Univariate≠ | Multivariate | ||
|---|---|---|---|---|---|---|
| mOR (95%CI) | p | mOR (95%CI) | P | |||
| ER (clonal) | Positive | 188 | 1 (reference) | - | 1 (reference) | - |
| Negative | 125 | 2.93 (1.76-4.87) | <0.0001 | 2.66 (1.53-4.61) | 0.0005 | |
| Excision | Complete | 198 | 1 (reference) | 1 (reference) | ||
| Uncertain | 60 | 1.30 (0.69-2.44) | 0.42 | 1.28 (0.65-2.50) | 0.48 | |
| Incomplete | 55 | 1.48 (0.80-2.72) | 0.21 | 1.41 (0.71-2.77) | 0.32 | |
| Trend test | 0.17 | 0.25 | ||||
| Size (mm) | 313 | 1.03 (1.00-1.06) | 0.026 | 1.02 (1.00-1.05) | 0.10 | |
| Grade | Low | 17 | 1 (reference) | 1 (reference) | ||
| Intermediate | 42 | 1.35 (0.38-4.80) | 0.64 | 0.96 (0.23-3.93) | 0.95 | |
| High | 254 | 1.88 (0.61-5.83) | 0.27 | 0.90 (0.23-3.54) | 0.88 | |
| Trend test | 0.17 | 0.84 | ||||
| Necrosis | No | 22 | 1 (reference) | 1 (reference) | ||
| Yes | 291 | 1.54 (0.58-4.10) | 0.39 | 1.12 (0.37-3.42) | 0.84 | |
| Inflammation | No | 54 | 1 (reference) | 1 (reference) | ||
| Yes | 259 | 1.84 (0.94-3.60) | 0.075 | 1.19 (0.51-2.80) | 0.69 | |
Matched odds ratio (mOR); n = 313; events = 117; ≠ univariate analyses restricted to the same sample size as available for multivariate analyses. Case definition – IBE. Age was a matching variable in the case-control study, and therefore its prognostic impact cannot be assessed.
PgR expression in DCIS
One-hundred and sixty-three (32.7%) of 498 evaluable tumors were PgR-negative and 335 (67.3%) were PgR-positive with 84 (25%) of these displaying multi-clonal PgR expression (median Allred score 6; IQR 5-7).
The risk of in situ (mOR=3.34; 95%CI, 1.86-6.00; p<0.0001) and any ipsilateral recurrence (mOR=2.45; 95%CI, 1.55-3.88; p=0.0001) was higher in PgR-negative than PgR-positive DCIS (Supplementary Table S5) but the increase in the risk was not as high as for ER-negative DCIS. Unlike ER, prognostic discrimination was also only marginally higher when PgR status was determined by clonal method (Δχ2 1.19 for IBE). PgR was not an independent predictor in multivariate models of clinico-pathological variables with ER. Inclusion of PgR did not significantly improve these models (Supplementary Table S6).
Hormone receptor (HR) status
HR status (HR-negative only if both receptors negative) was a predictor of risk of recurrence (Supplementary Table S7), the risk of in situ (mOR=4.07; 95%CI, 2.17-7.63; p<0.0001) and any ipsilateral recurrence (mOR=2.88; 95%CI, 1.79-4.63; p<0.0001) was higher in HR-negative DCIS but the models of HR status were not more informative than models using ER status alone (Supplementary Table S8).
Discussion
We assessed the prognostic value of ER/PgR expression in DCIS using a case-control study within the UK/ANZ DCIS trial (12). By the virtue of random treatment allocation and control matching by treatment allocation, we were able to eliminate any treatment allocation bias or treatment-related confounding and robustly assess the true prognostic value of ER/PgR expression in DCIS.
ER-negative DCIS carried a significantly higher risk of in situ and overall ipsilateral recurrences. The risk of invasive ipsilateral recurrences was also non-significantly higher in ER-negative DCIS. Our findings of a 64% lower IBE risk in ER-positive DCIS (mOR=0.36) are similar to meta-analysis by Wang et al (22) who reported a significantly lower IBE risk in ER-positive DCIS (RR=0.39). Zhang et al (23) reported a non-significant 26% lower I-IBE risk in ER-positive DCIS (RR=0.74) in their meta-analysis, which was similar to our non-significantly lower I-IBE risk (mOR=0.66).
Of note was the importance of multi-clonal expression in 39 (11%) ER-positive DCIS; 30 (77%) of these with an Allred score of >5, and 15 (38.5%) with score 8. The prognostic value of multi-clonal ER expression was independent of Allred score. The importance of branched evolutionary tumor growth and resulting intratumor heterogeneity is now increasingly recognised in a variety of cancers (24,25). However, to the best of our knowledge, multi-clonality in ER/PgR expression in DCIS has not been reported before. This novel observation not only has bearing on prognosis and treatment of DCIS, but also highlights the potential of in situ disease models for research into cancer development, progression and therapeutic resistance. Clonal populations with distinct temporal and/or spatial evolution coalesce and become admixed together due to stromal invasion in invasive cancers, but these remain geographically compartmentalised within individual ducts in DCIS. Therefore, DCIS offers an opportunity to easily identify, separate and investigate different clonal populations, including their impact on outcomes and progression.
Clonal populations with differential molecular target expression are likely to respond differently to targeted therapies. Such differential therapeutic selection pressure resulting in elimination of treatment-responsive clones may make treatment-resistant clones (e.g. without target expression) dominant, and thus adversely impact outcome despite using an effective therapy (26). Our novel observation therefore suggests that an in situ disease model would be valuable in investigating therapeutic effectiveness/resistance. The number of multi-clonal cases in our study are too small to draw any treatment-effect inferences (Supplementary Table S9). However, a randomized trial of adjuvant endocrine therapy versus not in ER-multi-clonal DCIS would help investigate such a question but may not be feasible.
Outcomes in ER-multi-clonal DCIS would depend on whether the ER-expressing or the ER-lacking population is the dominant outcome-determining clonal population; and accordingly, the current standard method or the new clonal method would respectively be more appropriate for scoring of ER. Our observation that outcomes in ER-multi-clonal DCIS are similar to ER-negative DCIS indicates that the ER-lacking clonal population is the dominant outcome-determining population and therefore the new clonal method would be more appropriate for scoring of ER since it more accurately estimates the true prognostic value of ER by avoiding misclassification.
Clinico-pathological variables such as age, tumor size, grade, necrosis, and completeness of excision (margin status) are currently the most commonly used prognostic factors. Multivariate analyses showed that inclusion of ER resulted in a significant improvement of the multivariate model of clinico-pathological variables, with a greater improvement using ER (clonal) than ER (standard) and ER was an independent prognostic factor in this model.
The Kaplan-Meier plots (Figure 1) adjusted for control sampling in the entire FFPE subset (36% received radiotherapy) show 10-year ipsilateral recurrence rate of approximately 35% in ER-negative DCIS. Despite all participants receiving radiotherapy, the 10-year IBE rate (21%) in ER-negative DCIS in the NSABP-B24 trial (10) also exceeds the often-recommended threshold of 20% (27) to warrant discussion regarding mastectomy as a surgical option and therefore routine evaluation of ER is merited for its prognostic value alone.
PgR status was a predictor of IBE and DCIS-IBE but (Table 2) not an independent predictor in multivariate analyses (Supplementary Table S5). In their meta-analyses, Wang et al (22) reported a non-significant 44% lower risk of IBE (RR 0.56) in PgR-positive DCIS whereas we observed a significantly lower risk of IBE (mOR 0.41). Zhang et al (23) reported a lower risk of I-IBE in PgR-positive DCIS (RR 0.89) in their meta-analysis, but similar to our results (mOR 0.84), their results were not statistically significant. Our results show that although PgR is a prognostic factor in DCIS, it does not add further to the information already provided by ER. Hormone receptor status was also not more informative than ER. Assessment of PgR status by clonal method did not substantially improve the prognostic value of PgR. Among PgR-multi-clonal cases, recurrence rate was lower in ER-positive (16/46, 34.8%) than ER-multi-clonal (15/31, 48.4%) cases. This may suggest that the outcome is mainly driven by ER expression upstream, a likely explanation for the lack of further contribution by PgR to the prognostic information already provided by ER.
Strengths and Limitations
A large sample size, random treatment allocation, and good long-term follow-up are major strengths of our study. A careful case-control design further allowed us to eliminate any residual treatment-related confounding. Selection bias however remains one of the limitations of our study. The BSS1 and the case-control study respectively comprised of 45% and 32% of patients enrolled in the trial. Several characteristics of participants in this subset were similar to those in remaining trial participants, however, tumors in the subset were marginally larger and a higher proportion of these were high grade. Furthermore, the proportion of high grade tumors (68%) in our study is higher compared with other large datasets (18,28) although not substantially higher than contemporary UK reports (57%) (29). Recruitment in the UK/ANZ DCIS trial started in 1989, almost immediately after initiation of the breast screening programme in the UK. This resulted in more enrolment of advanced lesions being found in the prevalence screening round. Additionally, even though the trial entry criteria (supplementary material) clearly required patients with only completely excised DCIS to be enrolled, a proportion of cases (Supplementary Table S1) were found to have incomplete or uncertain excision on central pathology review. However, this deviation did not affect our estimation of prognostic value of ER since sensitivity analyses excluding cases with incomplete or uncertain excision showed only minor and non-significant changes in effect sizes (supplementary material). The novel observation of multi-clonal expression is based on 16 events in 39 cases and merits cautious interpretation. The clonal method will be easily transferrable but may slightly increase reporting time. The principal objective of our study was to evaluate prognostic role of ER/PgR, therefore matching of cases and controls by treatment allocation was necessary. As a result, the role of these receptors in predicting tamoxifen treatment benefit could not be assessed in this case-control study; this will be analyzed in further ongoing study.
Conclusions
ER status is not routinely assessed in DCIS (1,2). Our results show that ER is a strong prognostic factor in DCIS with the risk of ipsilateral recurrence being more than 3-fold higher in ER-negative DCIS. Allred et al (10) suggested the role of ER in predicting tamoxifen benefit. Our results and those from the NSABP-B24 trial (10), together make a strong case for routine evaluation of ER expression in DCIS. Furthermore, a high 10-year IBE risk in ER-negative DCIS in both these studies also warrants that the treatment discussions with patients should also include mastectomy as a surgical option. ER expression was multi-clonal in 11% of ER-positive DCIS in this study and while these cases have recurrence risk similar to that in ER-negative DCIS, they currently get misclassified as ER-positive. Therefore, the clonal method reported here should be considered when determining ER status in clinical settings and in future research studies. Our novel observation of multi-clonality in DCIS suggests DCIS as an excellent model to investigate cancer progression, therapeutic effectiveness and resistance, particularly in relation to the use of targeted therapies.
Supplementary Material
Statement of translational relevance.
The prognostic role of ER/PgR in ductal carcinoma in situ (DCIS) remains unclear and ER/PgR are not routinely evaluated in DCIS in many parts of the world. Our Study design eliminated treatment allocation bias and treatment-related confounding to robustly assess the true prognostic value of ER/PgR in DCIS. We observed multi-clonality in ER expression in 11% of ER-positive DCIS i.e. ER-positive DCIS with distinct ER-negative clones and investigated the prognostic role of such multi-clonality in ER expression.
We report that ER is a strong prognostic factor with greater than 3-fold risk of ipsilateral recurrence in ER-negative DCIS. Therefore, ER should be routinely assessed in DCIS and the clonal method reported here should be considered. Furthermore, multi-clonality in DCIS suggests DCIS as an excellent model to investigate cancer progression and tumor evolution as well as therapeutic effectiveness and resistance, particularly in relation to the use of targeted therapies
Acknowledgements
Dr. Amar Ahmad for help with analyses using NestedCohort package (version 1.1-3) in R.
Funding source
This work was funded by Cancer Research UK grants: C569/A12061 (MA Thorat) and C569/A16891 (J Cuzick, MA Thorat).
The Breast Cancer Research Foundation, New York, USA provided support for biospecimen collection and management activities (J Cuzick, MA Thorat).
Role of the funding source
Funders had no role in study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. MAT had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Footnotes
Author contributions:
MAT and JC led the study design.
ISF and NJB contributed to patient recruitment and data collection in the trial.
SEP led the central pathology review.
MAT, PML and LJJ contributed to biomarker assays, scoring and data collection.
MAT and JC analyzed data, which were interpreted by all co-authors.
MAT drafted the manuscript, the final version of which was approved by all co-authors.
Declaration of interests: The authors declare no potential conflicts of interest.
Prior presentations:
Some findings presented as a poster at the San Antonio Breast Cancer Symposium 2015.
References
- 1.Thomas J, Hanby A, Pinder S, Ellis I, Macartney J, Clements K, et al. Implications of Inconsistent Measurement of ER Status in Non-Invasive Breast Cancer: A Study of 1,684 Cases from the Sloane Project. The Breast Journal. 2008;14:33–8. doi: 10.1111/j.1524-4741.2007.00523.x. [DOI] [PubMed] [Google Scholar]
- 2.Jarosek S, Tuttle TM, Durham S, Virnig BA. Data Points Publication Series. Rockville (MD): 2011. Prognostic factor testing among older women with ductal carcinoma in situ and early invasive breast cancer: Data Points # 15. [PubMed] [Google Scholar]
- 3.Cardoso F, Kyriakides S, Ohno S, Penault-Llorca F, Poortmans P, Rubio IT, et al. Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-updagger. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO. 2019;30(8):1194–220. doi: 10.1093/annonc/mdz173. [DOI] [PubMed] [Google Scholar]
- 4.Solin LJ, Gray R, Hughes LL, Wood WC, Lowen MA, Badve SS, et al. Surgical Excision Without Radiation for Ductal Carcinoma in Situ of the Breast: 12-Year Results From the ECOG-ACRIN E5194 Study. J Clin Oncol. 2015 doi: 10.1200/JCO.2015.60.8588. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Roka S, Rudas M, Taucher S, Dubsky P, Bachleitner-Hofmann T, Kandioler D, et al. High nuclear grade and negative estrogen receptor are significant risk factors for recurrence in DCIS. Eur J Surg Oncol. 2004;30(3):243–7. doi: 10.1016/j.ejso.2003.11.004. [DOI] [PubMed] [Google Scholar]
- 6.Ringberg A, Anagnostaki L, Anderson H, Idvall I, Ferno M, South SwedenBreast Cancer G Cell biological factors in ductal carcinoma in situ (DCIS) of the breast-relationship to ipsilateral local recurrence and histopathological characteristics. Eur J Cancer. 2001;37(12):1514–22. doi: 10.1016/s0959-8049(01)00165-4. [DOI] [PubMed] [Google Scholar]
- 7.Kerlikowske K, Molinaro AM, Gauthier ML, Berman HK, Waldman F, Bennington J, et al. Biomarker expression and risk of subsequent tumors after initial ductal carcinoma in situ diagnosis. J Natl Cancer Inst. 2010;102(9):627–37. doi: 10.1093/jnci/djq101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Provenzano E, Hopper JL, Giles GG, Marr G, Venter DJ, Armes JE. Biological markers that predict clinical recurrence in ductal carcinoma in situ of the breast. Eur J Cancer. 2003;39(5):622–30.:S0959804902006664 [pii] doi: 10.1016/s0959-8049(02)00666-4. [DOI] [PubMed] [Google Scholar]
- 9.Kuerer HM, Lari SA, Arun BK, Hu CY, Brewster A, Mittendorf EA, et al. Biologic features and prognosis of ductal carcinoma in situ are not adversely impacted by initial large body mass. Breast Cancer Research and Treatment. 2012;133(3):1131–41. doi: 10.1007/s10549-012-1999-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Allred DC, Anderson SJ, Paik S, Wickerham DL, Nagtegaal ID, Swain SM, et al. Adjuvant tamoxifen reduces subsequent breast cancer in women with estrogen receptor-positive ductal carcinoma in situ: a study based on NSABP protocol B-24. J Clin Oncol. 2012;30(12):1268–73. doi: 10.1200/JCO.2010.34.0141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Claus EB, Chu P, Howe CL, Davison TL, Stern DF, Carter D, et al. Pathobiologic findings in DCIS of the breast: morphologic features, angiogenesis, HER-2/neu and hormone receptors. Exp Mol Pathol. 2001;70(3):303–16. doi: 10.1006/exmp.2001.2366. [DOI] [PubMed] [Google Scholar]
- 12.Cuzick J, Sestak I, Pinder SE, Ellis IO, Forsyth S, Bundred NJ, et al. Effect of tamoxifen and radiotherapy in women with locally excised ductal carcinoma in situ: long-term results from the UK/ANZ DCIS trial. Lancet Oncol. 2011;12(1):21–9. doi: 10.1016/S1470-2045(10)70266-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM, et al. REporting recommendations for tumour MARKer prognostic studies (REMARK) Br J Cancer. 2005;93(4):387–91. doi: 10.1038/sj.bjc.6602678. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Hammond ME, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, et al. American Society of Clinical Oncology/College Of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol. 2010;28(16):2784–95. doi: 10.1200/JCO.2009.25.6529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Press M, Spaulding B, Groshen S, Kaminsky D, Hagerty M, Sherman L, et al. Comparison of different antibodies for detection of progesterone receptor in breast cancer. Steroids. 2002;67(9):799–813. doi: 10.1016/s0039-128x(02)00039-9. [DOI] [PubMed] [Google Scholar]
- 16.Allred DC, Harvey JM, Berardo M, Clark GM. Prognostic and predictive factors in breast cancer by immunohistochemical analysis. Mod Pathol. 1998;11(2):155–68. [PubMed] [Google Scholar]
- 17.Detre S, Saclani Jotti G, Dowsett M. A “quickscore” method for immunohistochemical semiquantitation: validation for oestrogen receptor in breast carcinomas. J Clin Pathol. 1995;48(9):876–8. doi: 10.1136/jcp.48.9.876. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Pinder SE, Duggan C, Ellis IO, Cuzick J, Forbes JF, Bishop H, et al. A new pathological system for grading DCIS with improved prediction of local recurrence: results from the UKCCCR/ANZ DCIS trial. Br J Cancer. 2010;103(1):94–100. doi: 10.1038/sj.bjc.6605718. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.National Pathology Co-ordinating Group. Pathology Reporting of Breast Disease. Vol. 58. NHSBSP Publication, NHS Cancer Screening Programmes and The Royal College of Pathologists; Sheffield: 2005. pp. 50–9. [Google Scholar]
- 20.Mark SD, Katki HA. Specifying and Implementing Nonparametric and Semiparametric Survival Estimators in Two-Stage (Nested) Cohort Studies With Missing Case Data. Journal of the American Statistical Association. 2006;101(474):460–71. doi: 10.1198/016214505000000952. [DOI] [Google Scholar]
- 21.Katki HA, Mark SD. Survival Analysis for Cohorts with Missing Covariate Information. The R Journal. 2008;8(1):14–9. [Google Scholar]
- 22.Wang SY, Shamliyan T, Virnig BA, Kane R. Tumor characteristics as predictors of local recurrence after treatment of ductal carcinoma in situ: a meta-analysis. Breast Cancer Res Treat. 2011;127(1):1–14. doi: 10.1007/s10549-011-1387-4. [DOI] [PubMed] [Google Scholar]
- 23.Zhang X, Dai H, Liu B, Song F, Chen K. Predictors for local invasive recurrence of ductal carcinoma in situ of the breast: a meta-analysis. Eur J Cancer Prev. 2015 doi: 10.1097/CEJ.0000000000000131. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012;366(10):883–92. doi: 10.1056/NEJMoa1113205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.de Bruin EC, McGranahan N, Mitter R, Salm M, Wedge DC, Yates L, et al. Spatial and temporal diversity in genomic instability processes defines lung cancer evolution. Science. 2014;346(6206):251–6. doi: 10.1126/science.1253462. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Gatenby RA, Silva AS, Gillies RJ, Frieden BR. Adaptive therapy. Cancer Res. 2009;69(11):4894–903. doi: 10.1158/0008-5472.CAN-08-3658. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Silverstein MJ, Lagios MD. Treatment selection for patients with ductal carcinoma in situ (DCIS) of the breast using the University of Southern California/Van Nuys (USC/VNPI) prognostic index. Breast J. 2015;21(2):127–32. doi: 10.1111/tbj.12368. [DOI] [PubMed] [Google Scholar]
- 28.Curigliano G, Disalvatore D, Esposito A, Pruneri G, Lazzeroni M, Guerrieri-Gonzaga A, et al. Risk of subsequent in situ and invasive breast cancer in human epidermal growth factor receptor 2-positive ductal carcinoma in situ. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO. 2015;26(4):682–7. doi: 10.1093/annonc/mdv013. [DOI] [PubMed] [Google Scholar]
- 29.Thompson AM, Clements K, Cheung S, Pinder SE, Lawrence G, Sawyer E, et al. Management and 5-year outcomes in 9938 women with screen-detected ductal carcinoma in situ: the UK Sloane Project. Eur J Cancer. 2018;101:210–9. doi: 10.1016/j.ejca.2018.06.027. [DOI] [PubMed] [Google Scholar]
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