Dataset Information

Prognostic Value of ER and PgR Expression and the Impact of Multi-clonal Expression for Recurrence in Ductal Carcinoma in situ: Results from the UK/ANZ DCIS Trial.

ABSTRACT:

Purpose

The prognostic value of estrogen receptor (ER)/progesterone receptor (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 tissues were collected from UK/ANZ DCIS trial participants (n = 755), and ER/PgR expression was evaluated by IHC 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 categorizing 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 with DCIS with uni-clonal ER expression. ER-negative DCIS (clonal) had a higher risk of in situ IBE [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), P _{heterogeneity} = 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.

SUBMITTER: Thorat MA

PROVIDER: S-EPMC7611296 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundInitial results of the UK/ANZ DCIS (UK, Australia, and New Zealand ductal carcinoma in situ) trial suggested that radiotherapy reduced new breast events of ipsilateral invasive and ductal carcinoma in situ (DCIS) compared with no radiotherapy, but no significant effects were noted with tamoxifen. Here, we report long-term results of this trial.MethodsWomen with completely locally excised DCIS were recruited into a randomised 2×2 factorial trial of radiotherapy, tamoxifen, or both. Randomisation was independently done for each of the two treatments (radiotherapy and tamoxifen), stratified by screening assessment centre, and blocked in groups of four. The recommended dose for radiation was 50 Gy in 25 fractions over 5 weeks (2 Gy per day on weekdays), and tamoxifen was prescribed at a dose of 20 mg daily for 5 years. Elective decision to withhold or provide one of the treatments was permitted. The endpoints of primary interest were invasive ipsilateral new breast events for the radiotherapy comparison and any new breast event, including contralateral disease and DCIS, for tamoxifen. Analysis of each of the two treatment comparisons was restricted to patients who were randomly assigned to that treatment. Analyses were by intention to treat. All trial drugs have been completed and this study is in long-term follow-up. This study is registered, number ISRCTN99513870.FindingsBetween May, 1990, and August, 1998, 1701 women were randomly assigned to radiotherapy and tamoxifen, radiotherapy alone, tamoxifen alone, or to no adjuvant treatment. Seven patients had protocol violations and thus 1694 patients were available for analysis. After a median follow-up of 12·7 years (IQR 10·9-14·7), 376 (163 invasive [122 ipsilateral vs 39 contralateral], 197 DCIS [174 ipsilateral vs 17 contralateral], and 16 of unknown invasiveness or laterality) breast cancers were diagnosed. Radiotherapy reduced the incidence of all new breast events (hazard ratio [HR] 0·41, 95% CI 0·30-0·56; p<0·0001), reducing the incidence of ipsilateral invasive disease (0·32, 0·19-0·56; p<0·0001) as well as ipsilateral DCIS (0·38, 0·22-0·63; p<0·0001), but having no effect on contralateral breast cancer (0·84, 0·45-1·58; p=0·6). Tamoxifen reduced the incidence of all new breast events (HR 0·71, 95% CI 0·58-0·88; p=0·002), reducing recurrent ipsilateral DCIS (0·70, 0·51-0·86; p=0·03) and contralateral tumours (0·44, 0·25-0·77; p=0·005), but having no effect on ipsilateral invasive disease (0·95, 0·66-1·38; p=0·8). No data on adverse events except cause of death were collected for this trial.InterpretationThis updated analysis confirms the long-term beneficial effect of radiotherapy and reports a benefit for tamoxifen in reducing local and contralateral new breast events for women with DCIS treated by complete local excision.FundingCancer Research UK and the Australian National Health and Medical Research Council.

Project description:BackgroundBreast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mastectomy or adjuvant radiation can reduce recurrence risk, there are significant concerns regarding patient over-/under-treatment. Current clinicopathological markers are insufficient to accurately assess the recurrence risk. To address this issue, we developed a novel machine learning (ML) pipeline to predict risk of ipsilateral recurrence using digitized whole slide images (WSI) and clinicopathologic long-term outcome data from a retrospectively collected cohort of DCIS patients (n?=?344) treated with lumpectomy at Nottingham University Hospital, UK.MethodsThe cohort was split case-wise into training (n?=?159, 31 with 10-year recurrence) and validation (n?=?185, 26 with 10-year recurrence) sets. The sections from primary tumors were stained with H&E, then digitized and analyzed by the pipeline. In the first step, a classifier trained manually by pathologists was applied to digital slides to annotate the areas of stroma, normal/benign ducts, cancer ducts, dense lymphocyte region, and blood vessels. In the second step, a recurrence risk classifier was trained on eight select architectural and spatial organization tissue features from the annotated areas to predict recurrence risk.ResultsThe recurrence classifier significantly predicted the 10-year recurrence risk in the training [hazard ratio (HR)?=?11.6; 95% confidence interval (CI) 5.3-25.3, accuracy (Acc)?=?0.87, sensitivity (Sn)?=?0.71, and specificity (Sp)?=?0.91] and independent validation [HR?=?6.39 (95% CI 3.0-13.8), p?<?0.0001;Acc?=?0.85, Sn?=?0.5, Sp?=?0.91] cohorts. Despite the limitations of our cohorts, and in some cases inferior sensitivity performance, our tool showed superior accuracy, specificity, positive predictive value, concordance, and hazard ratios relative to tested clinicopathological variables in predicting recurrences (p?<?0.0001). Furthermore, it significantly identified patients that might benefit from additional therapy (validation cohort p?=?0.0006).ConclusionsOur machine learning-based model fills an unmet clinical need for accurately predicting the recurrence risk for lumpectomy-treated DCIS patients.