Ductal Carcinoma In Situ Score Research Articles

Abstract GS03-01: Magnetic Resonance Imaging and a 12-Gene Expression Assay to Optimize Local Therapy for Ductal Carcinoma In Situ: 5-year clinical outcomes of E4112

Abstract BACKGROUND. Advanced diagnostics such as magnetic resonance imaging (MRI) and gene-expression profiles are potentially useful to guide treatment in patients with ductal carcinoma in situ (DCIS). To evaluate these tests, we performed a prospective single arm multicenter study. We have previously reported the impact of MRI on surgical management of DCIS patients, and the effect of a 12-gene DCIS Score (DS) on radiotherapy (RT) use after wide local excision (WLE). We now report a pre-planned analysis of ipsilateral breast events (IBE) at 5-years. METHODS. Adult women with a core needle biopsy diagnosis of DCIS and eligible for WLE based on conventional imaging were registered following consent. All registered patients underwent breast MRI. Those still eligible, and willing, to receive WLE after appropriate follow-up biopsies underwent resection to free margins. DCIS sections were submitted to Exact Sciences for DS. Those with a low DS (< 39) were advised to omit RT; those with intermediate/high (inter/hi) DS (≥39) were advised to receive RT. All participants were monitored at 6-month intervals for any breast cancer event, and for survival. An IBE was defined as the first DCIS or invasive recurrence in the ipsilateral breast following the final WLE. Participants without IBE were censored by date of last contact or date of death for those who died. Follow-up was truncated at 5 years from WLE. Using data available as of 07-06-2023, Kaplan-Meier (K-M) curves were constructed to estimate the time-to-event distributions for subjects who received RT and for those who did not. The 5-year IBE rates and 95% confidence intervals (CIs) were estimated from K-M curves for all subjects with a DS (analogue of Intention to Treat [ITT] analysis), and for the subset who were compliant with their DS-based RT recommendation (Per Protocol analysis). The analyses were repeated for subgroups based on age at DCIS diagnosis (< 50 vs. ≥ 50). RESULTS. Of 339 women evaluable for the previously reported primary analysis (PMID 30653209), 171 (50.4%) underwent WLE with free surgical margins and had DS available for RT recommendations (ITT population). Of these, 7/82 low DS patients underwent RT, and 5/89 inter/hi DS patients declined RT; thus, the adherence to DS-based RT recommendations was 93%. At a median of 5 years of follow-up from final WLE, the ITT population experienced a total of eight IBE events (4.8%, 95% CI 2.4, 9.4) with 5-year IBE rates that were similar for participants with a low DS and for those with a inter/hi DS: 5.1% (95% CI: 1.9, 12.9) and 4.5% (95% CI 1.7, 11.7), respectively. Stratification by age did not alter these results: among women aged < 50 years (n=33), the IBE rate was 6.7% (95% CI 1.0, 38.7) for low DS and 5.6% (95% CI 0.8, 33.4) for inter/hi DS. Among women aged ≥ 50 years (n=138), the IBE rate was 4.7% (95% CI 1.5, 13.8) for low DS and 4.3% (95% CI 1.4, 12.7) for inter/hi DS. In the per-protocol analysis (N=159 adherent to RT recommendations), IBE rates were also similar for participants who had a low DS and no RT [5.5% (95% CI 2.1, 14.1)] and for those with inter/hi DS who received RT [4.8% (95% CI: 1.8% to 12.3%)]. Again, there was no discernible influence by age as categorized above. CONCLUSION. We report the first prospective data on use of DCIS Score for RT decisions, and 5-year IBE rates. We find that DS-based recommendations are followed by >90% of patients. Although the sample size is limited, the data are reassuring in that the IBE rate is similar between the low DS group treated with WLE alone and the inter/hi DS group treated with WLE and radiation, whereas prior studies have shown a marked difference in IBE rates by DS with excision alone. Therefore, this prospective trial provides strong evidence to support the omission of RT after surgery in DCIS patients with low DS, and its use in patients with intermediate/high DS. Citation Format: Seema Khan, Justin Romanoff, Constantine Gatsonis, Habib Rahbar, Ruth Carlos, Sunil Badve, Jean Wright, Constance Lehman, Worta McCaskill-Stevens, Ralph Corsetti, Derrick Spell, Kenneth Blankstein, Linda Han, Jennifer Sabol, John Bumberry, Ilana Gareen, Bradley Snyder, Lynne Wagner, Kathy Miller, Joseph Sparano, Christopher Comstock. Magnetic Resonance Imaging and a 12-Gene Expression Assay to Optimize Local Therapy for Ductal Carcinoma In Situ: 5-year clinical outcomes of E4112 [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr GS03-01.

Abstract PO3-28-10: MRI Radiomic phenotypes derived from the ECOG-ACRIN E4112 Trial to assess high-risk ductal carcinoma in situ

Abstract INTRODUCTION Ductal carcinoma in situ (DCIS) is a non-lethal pre-invasive breast cancer that can co-exist with invasive disease. Dynamic contrast-enhanced (DCE) MRI is sensitive for the detection of high-grade DCIS and invasive cancer while Oncotype DCIS Score is a 12-gene assay that can assess recurrence risk. In practice, it is difficult to distinguish low- from high-risk DCIS, which leads to overtreatment for up to half of women diagnosed with DCIS. We hypothesize that radiomic phenotypes of DCIS derived from DCE-MRI data may serve as prognostic markers to improve risk stratification by capturing disease heterogeneity. Here we evaluate the ability of these phenotypes to predict DCIS Score and upstaging of DCIS to invasive disease on wide local excision in a multicenter trial. METHODS Data: DCE-MRI data from the ECOG-ACRIN E4112 trial were retrospectively analyzed. Primary analysis focused on participants with data on disease upstaging (N=295), with secondary analysis in a subset (N=174) of participants with DCIS Scores (dichotomized as >55 and 55) and pure DCIS. Clinical information included patient demographics, lesion morphology on MRI, background parenchymal enhancement, DCIS grade, central necrosis, and hormone receptor status. Data analysis: Radiologist-drawn lesion segmentations and publicly available software, CaPTk, were used to compute 64 radiomic features from first post-contrast images for each participant. Radiomic phenotypes were identified using hierarchical clustering on the extracted features. A Chi-square test was used to evaluate the association between radiomic phenotypes and each outcome. The likelihood ratio test was used to compare two logistic regression models: 1)clinical model using only clinical information as predictors and 2) clinical+phenotypes model using clinical information and phenotype assignment as predictors. Each model was used for the prediction of upstaging to invasive disease and DCIS score. Model performance was evaluated as the 10-fold cross-validated area under the receiver operator characteristic curve (AUC). A p< 0.05 was considered significant. RESULTS A total of 45 (15%) cases upstaged to invasive disease. Two radiomic phenotypes were identified: Phenotype 1 indicated greater lesion signal heterogeneity, while Phenotype 2 indicated lower heterogeneity. Radiomic phenotype was strongly associated with disease upstaging (p=0.0034) – with a higher rate of upstaging for Phenotype 1 – but not with DCIS score (p=0.1174, Table 1). For predicting disease upstaging, the clinical+phenotypes model yielded a higher AUC=0.72 and a significantly better fit to the data (p=0.0022) compared to the clinical model parameterized by clinical information alone (AUC=0.69). For predicting DCIS Score, the clinical+phenotypes model (AUC=0.77) showed similar performance compared to the clinical model (AUC=0.76) and no significant improvement in fit to the data (p=0.2920). CONCLUSION Radiomic phenotypes capturing disease heterogeneity show promise as prognostic predictors for predicting disease upstaging in DCIS compared to clinical information alone and may enable more efficient disease management. We observed that phenotypes did not have independent predictive outcome for DCIS score, suggesting that MRI and DCIS Score offer independent information and could be combined in future models to better predict disease recurrence or progression. Clinical applications of radiomic phenotypes may improve risk stratification and potentially result in decreased overtreatment of women diagnosed with DCIS. Table 1: Association between radiomic phenotypes and DCIS outcomes using a Chi square test. Citation Format: Kalina Slavkova, Ruya Kang, Vivian Belenky, Anum Kazerouni, Debosmita Biswas, Hannah Horng, Rhea Chitalia, Michael Hirano, Jennifer Xiao, Ralph Corsetti, Sarah Javid, Derrick Spell, Antonio Wolff, Joseph Sparano, Seema Khan, Christopher Comstock, Justin Romanoff, Jon Steingrimsson, Constantine Gatsonis, Constance Lehman, Savannah Partridge, Despina Kontos, Habib Rahbar. MRI Radiomic phenotypes derived from the ECOG-ACRIN E4112 Trial to assess high-risk ductal carcinoma in situ [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-28-10.

Abstract PO4-13-02: Molecular Expression Assays Improve the Prediction of Local and Invasive Local Recurrence after Breast Conserving Surgery for DCIS

Abstract Introduction Ductal carcinoma in situ (DCIS) is routinely treated with adjuvant radiotherapy (RT) after breast conserving surgery (BCS) in order to reduce the risk of local recurrence (LR) and invasive LR. Nomograms based on clinicopathological features (CPF) and molecular expression assays have been developed in an effort to provide individualized risk estimates and personalize decision-making. However, molecular assays are costly and it remains unclear if they provide more accurate recurrence risk estimates compared to algorithms based on CPF alone. We examined the impact of the 12-Gene DCIS Score (DS) and the 21-Gene Recurrence Score (RS) molecular expression assays, in addition to CPF, on the accuracy of predicting 10-year LR and invasive LR risk compared to predicted estimates based on CPF alone. In addition, we examined if a model including the 21-Gene RS improves the 10-year predicted risks of invasive LR after BCS for DCIS compared to estimates based on the DS+CPF or CPF alone. Methods We used a population-based cohort diagnosed with pure DCIS treated with BCS +/- RT from 1994-2003. All cases had expert pathology review providing contemporary assessment of diagnosis, margin status, margin width, multifocality, presence and extent of comedo necrosis, subtype, nuclear grade, and tumor size. For each case, a representative tissue block or unstained slide was sent to measure the 12-Gene DS and 21-Gene RS. Predictive models were developed using multivariable Cox regression analyses with backward selection and included all CPF, treatment with RT, and interactions. The performance of each model was evaluated based on c-statistic, -2log likelihood estimate (-2LLE), and Akaike information criterion (AIC). Calibration was performed using bootstrap resamples, with replacement. We compared the performance of the best model derived from CPF alone, the 12-Gene DS with CPF, and the 21-Gene RS with CPF on their ability to predict the 10 year risks of LR and invasive LR measured against outcomes observed in the cohort. Results The population-based cohort includes 1226 women, 514 were treated with BCS alone and 712 were treated with BCS + RT. Median age was 56 years. Median follow-up was 10 years. Fifty-two percent of tumors were between 1 and 2.5 cm, 35% were ≤1cm, and 13% were >2.5 cm. Comedo necrosis was present in 68%, and nuclear grade was low, moderate, and high in 7%, 54%, and 39%, respectively. Margins were negative in 90.5% of cases (N=1109). The 12-Gene DS was low, intermediate, and high in 53.5%, 20.9%, and 25.6% and the 21-Gene RS was >25 in 30% of patients. 194 women (15.8%) experienced ipsilateral LR as a first event; 112 were invasive LR. Models including either the DS or RS expression assays performed better in predicting the 10-year risk of LR after BCS compared to the model based on CPFs alone, demonstrating higher c-statistics (0.705, 0.699, and 0.662, respectively), lower AIC and lower -2LLE. The two molecular-based predictive models also performed better in predicting the risk of invasive LR compared to CPF model, although with smaller differences in c-statistics (0.684, 0.683, and 0.667, respectively), AIC or -2LLE. The predictive model based on the 21-Gene RS with CPF did not perform better in the prediction of the 10 year risk of invasive LR compared the 12-Gene DS + CPF model. All models were well calibrated. Conclusion The predictive model based on the 12-Gene DS with CPF more accurately predicted the 10-year risk of LR and invasive LR after BCS compared to model based on CPF alone. Inclusion of the 21-Gene RS with CPF did not improve the prediction of the 10-year risk of LR or invasive LR. This suggests that nomograms that include the 12-Gene assay with CPF provide more accurate individualized estimates of recurrence risk after BCS and can help improve personalized decision-making in the management of DCIS. Citation Format: Ezra Hahn, Rinku Sutradhar, Lawrence Paszat, Lena Nguyen, Danielle Rodin, Sharon Nofech-Mozes, Sabina Trebinjac, Cindy Fong, Eileen Rakovitch. Molecular Expression Assays Improve the Prediction of Local and Invasive Local Recurrence after Breast Conserving Surgery for DCIS [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-13-02.

AI analytics can be used as imaging biomarkers for predicting invasive upgrade of ductal carcinoma in situ

ObjectivesTo evaluate whether the quantitative abnormality scores provided by artificial intelligence (AI)-based computer-aided detection/diagnosis (CAD) for mammography interpretation can be used to predict invasive upgrade in ductal carcinoma in situ (DCIS) diagnosed on percutaneous biopsy.MethodsFour hundred forty DCIS in 420 women (mean age, 52.8 years) diagnosed via percutaneous biopsy from January 2015 to December 2019 were included. Mammographic characteristics were assessed based on imaging features (mammographically occult, mass/asymmetry/distortion, calcifications only, and combined mass/asymmetry/distortion with calcifications) and BI-RADS assessments. Routine pre-biopsy 4-view digital mammograms were analyzed using AI-CAD to obtain abnormality scores (AI-CAD score, ranging 0–100%). Multivariable logistic regression was performed to identify independent predictive mammographic variables after adjusting for clinicopathological variables. A subgroup analysis was performed with mammographically detected DCIS.ResultsOf the 440 DCIS, 117 (26.6%) were upgraded to invasive cancer. Three hundred forty-one (77.5%) DCIS were detected on mammography. The multivariable analysis showed that combined features (odds ratio (OR): 2.225, p = 0.033), BI-RADS 4c or 5 assessments (OR: 2.473, p = 0.023 and OR: 5.190, p < 0.001, respectively), higher AI-CAD score (OR: 1.009, p = 0.007), AI-CAD score ≥ 50% (OR: 1.960, p = 0.017), and AI-CAD score ≥ 75% (OR: 2.306, p = 0.009) were independent predictors of invasive upgrade. In mammographically detected DCIS, combined features (OR: 2.194, p = 0.035), and higher AI-CAD score (OR: 1.008, p = 0.047) were significant predictors of invasive upgrade.ConclusionThe AI-CAD score was an independent predictor of invasive upgrade for DCIS. Higher AI-CAD scores, especially in the highest quartile of ≥ 75%, can be used as an objective imaging biomarker to predict invasive upgrade in DCIS diagnosed with percutaneous biopsy.Critical relevance statementNoninvasive imaging features including the quantitative results of AI-CAD for mammography interpretation were independent predictors of invasive upgrade in lesions initially diagnosed as ductal carcinoma in situ via percutaneous biopsy and therefore may help decide the direction of surgery before treatment.Key points• Predicting ductal carcinoma in situ upgrade is important, yet there is a lack of conclusive non-invasive biomarkers.• AI-CAD scores—raw numbers, ≥ 50%, and ≥ 75%—predicted ductal carcinoma in situ upgrade independently.• Quantitative AI-CAD results may help predict ductal carcinoma in situ upgrade and guide patient management.Graphical

Personalizing the Treatment of Women with Ductal Carcinoma In Situ (DCIS) Using the DCIS Score: A Qualitative Study on Score Use.

A twelve-gene molecular expression assay (DCIS score) may help guide radiation oncology treatment under specific circumstances. We undertook a study to examine radiation oncologist (RO), surgeon, and decision maker views on implementing the DCIS score in practice for women with low-risk DCIS. We conducted a qualitative study involving telephone interviews that were audio-recorded and transcribed. Two researchers conducted a thematic analysis of transcripts. Twenty-eight individuals (ROs, breast cancer surgeons, and cancer policy decision makers) were invited to participate; 22 out of the 28 people (79%) agreed. The final sample included 20 participants: 11 of 13 (85%) ROs, 5 of 7 (71%) surgeons, and 4 of 8 (50%) decision makers. Most ROs expressed concerns about overtreatment but could not predict with certainty which low-risk patients could safely avoid radiation. The DCIS score was viewed as contributing valuable personalized risk information as part of treatment decision making that included clinicopathological factors and women's preferences. Future implementation would require guidelines with input from the oncology team. ROs had concerns about the overtreatment of women with DCIS, but lacked the tools to reliably predict which women could safely avoid radiation. By providing oncologists and women with personalized tumor information, the DCIS score was an important component of treatment decision making.

Presurgical Oral Tamoxifen vs Transdermal 4-Hydroxytamoxifen in Women With Ductal Carcinoma In Situ

Oral tamoxifen citrate benefits women with ductal carcinoma in situ (DCIS), but concern about toxic effects has limited acceptance. Previous pilot studies have suggested transdermal 4-hydroxytamoxifen gel has equivalent antiproliferative efficacy to oral tamoxifen, with low systemic exposure. To demonstrate that 4-hydroxytamoxifen gel applied to the breast skin is noninferior to oral tamoxifen in its antiproliferative effect in DCIS lesions. This randomized, double-blind, phase 2 preoperative window trial was performed at multicenter breast surgery referral practices from May 31, 2017, to January 27, 2021. Among 408 women with estrogen receptor-positive DCIS who were approached, 120 consented and 100 initiated study treatment. The most common reasons for nonparticipation were surgical delay, disinterest in research, and concerns about toxic effects. Data were analyzed from January 26, 2021, to October 5, 2022. Random assignment to oral tamoxifen citrate, 20 mg/d, and gel placebo or 4-hydroxytamoxifen gel, 2 mg/d per breast, and oral placebo, for 4 to 10 weeks, followed by DCIS resection. The primary end point was absolute change in DCIS Ki-67 labeling index (Ki67-LI). Secondary end points included 12-gene DCIS Score, breast tissue tamoxifen metabolite concentrations, tamoxifen-responsive plasma protein levels, and patient-reported symptoms. Noninferiority of Ki67-LI reduction by 4-hydroxytamoxifen gel was tested using analysis of covariance; within- and between-arm comparisons were performed with paired t tests for mean values or the Wilcoxon rank sum test for medians. Of 90 participants completing treatment (mean [SD] age, 55 [11] years; 8 [8.9%] Asian, 16 [17.8%] Black, 8 [8.9%] Latina, and 53 [58.9%] White), 15 lacked residual DCIS in the surgical sample, leaving 75 evaluable for the primary end point analysis (40 in the oral tamoxifen group and 35 in the 4-hydroxytamoxifen gel group). Posttreatment Ki67-LI was 3.3% higher (80% CI, 2.1%-4.6%) in the 4-hydroxytamoxifen gel group compared with the oral tamoxifen group, exceeding the noninferiority margin (2.6%). The DCIS Score decreased more with oral tamoxifen treatment (-16 [95% CI, -22 to -9.4]) than with 4-hydroxytamoxifen gel (-1.8 [95% CI, -5.8 to 2.3]). The median 4-hydroxytamoxifen concentrations deep in the breast were nonsignificantly higher in the oral tamoxifen group (5.7 [IQR, 4.0-7.9] vs 3.8 [IQR, 1.3-7.9] ng/g), whereas endoxifen was abundant in the oral tamoxifen group and minimal in the 4-hydroxytamoxifen gel group (median, 13.0 [IQR, 8.9-20.6] vs 0.3 [IQR, 0-0.3] ng/g; P < .001). Oral tamoxifen caused expected adverse changes in plasma protein levels and vasomotor symptoms, with minimal changes in the transdermal group. In this randomized clinical trial, antiproliferative noninferiority of 4-hydroxytamoxifen gel to oral tamoxifen was not confirmed, potentially owing to endoxifen exposure differences. New transdermal approaches must deliver higher drug quantities and/or include the most potent metabolites. ClinicalTrials.gov Identifier: NCT02993159.

Can Molecular Biomarkers Help Reduce the Overtreatment of DCIS?

Ductal carcinoma in situ (DCIS), especially in the era of mammographic screening, is a commonly diagnosed breast tumor. Despite the low breast cancer mortality risk, management with breast conserving surgery (BCS) and radiotherapy (RT) is the prevailing treatment approach in order to reduce the risk of local recurrence (LR), including invasive LR, which carries a subsequent risk of breast cancer mortality. However, reliable and accurate individual risk prediction remains elusive and RT continues to be standardly recommended for most women with DCIS. Three molecular biomarkers have been studied to better estimate LR risk after BCS-Oncotype DX DCIS score, DCISionRT Decision Score and its associated Residual Risk subtypes, and Oncotype 21-gene Recurrence Score. All these molecular biomarkers represent important efforts towards improving predicted risk of LR after BCS. To prove clinical utility, these biomarkers require careful predictive modeling with calibration and external validation, and evidence of benefit to patients; on this front, further research is needed. Most trials do not incorporate molecular biomarkers in evaluating de-escalation of therapy for DCIS; however, one-the Prospective Evaluation of Breast-Conserving Surgery Alone in Low-Risk DCIS (ELISA) trial-incorporates the Oncotype DX DCIS score in defining a low-risk population and is an important next step in this line of research.

Association of quantitative MRI features of DCIS with surgical upstaging and recurrence after treatment.

e12540 Background: Ductal carcinoma in situ (DCIS) is a common preinvasive breast cancer typically identified on screening mammography. Pure DCIS is nonlethal, but 20-25% of DCIS cases identified on core biopsy upstage to invasive cancer at surgery and about half progress to invasive disease if not treated. As a result, most DCIS patients undergo excision and radiation therapy. DCIS score is a multigene assay that can aid in radiation treatment decision-making and serve as a surrogate marker of ipsilateral breast recurrence (IBR) risk. Breast MRI can accurately depict DCIS span and has potential to assess biology and IBR risk. We sought to assess the associations of advanced quantitative MRI features with upstaging and DCIS score. Methods: In this IRB-approved single institution prospective clinical trial, patients recommended for biopsy of calcifications or those who had residual calcifications after a biopsy yielding pure DCIS consented to receive a multiparametric breast MRI (dynamic contrast-enhanced and diffusion-weighted) prior to surgery. The following quantitative MRI features were obtained: functional tumor volume (FTV), volume transfer constant (Ktrans), extracellular extravascular volume fraction (ve), background parenchymal enhancement (BPE), and apparent diffusion coefficient (ADC). Patients with biopsy-proven DCIS were followed through completion of surgery to determine upstaging. DCIS score was performed in those with sufficient excision-proven pure DCIS. Associations of MRI features with invasive upstaging and DCIS score and were evaluated by Spearman’s correlation and the Wilcoxon rank-sum test. Results: Of the 120 patients enrolled in the study, 57 (48%) were diagnosed with pure DCIS on core biopsy. Fifty-five patients underwent surgery, 13 of whom (24%) upstaged to invasive disease. Thirty-eight pure DCIS lesions had sufficient tissue to generate a DCIS Score. Several MRI features were associated with upstaging and DCIS Score: Ktrans (p &lt; 0.01) was significantly higher in lesions that upstaged to invasive disease. Higher DCIS scores were associated with lower Ktrans (p = 0.04) and ve (p = 0.05) values. No statistically significant associations were observed between FTV, BPE, or ADC and invasive upstaging or DCIS Score. Conclusions: This trial suggests advanced quantitative MRI features may help identify DCIS lesions at risk for upstaging to invasive disease and IBR. Specifically, an imaging feature of vascular permeability (Ktrans) showed an expected positive association with upstaging. Imaging features of vascular permeability (Ktrans and ve) showed counterintuitive inverse associations with DCIS Scores. Future research in larger cohorts is needed to validate these findings, better determine the biological reasons for these associations, and determine whether MRI features can be used clinically to optimize DCIS treatment. Clinical trial information: NCT03495011 .

Comparison of conventional clinical models and a multigene assay to assess DCIS risk in a prospective single center study.

e12578 Background: Ductal carcinoma in situ (DCIS) is a preinvasive breast cancer typically excised and treated with adjuvant therapy. While there is consensus that this results in overtreatment, there is little agreement on who may avoid radiation or endocrine therapy. Two freely available prediction models, Van Nuys Prognostic Index (VNPI) and Memorial Sloan Kettering Nomogram (MSK-N), are commonly used to identify low-risk DCIS based on standard clinicopathological features. Oncotype DCIS is a newer commercially available tissue-based multigene assay also used to assess risk, but its use is limited due to cost and unclear value over VNPI and MSK-N. We sought to compare these tests’ agreement in determining DCIS ipsilateral breast recurrence (IBR) risk and potential to de-escalate therapy. Methods: In this subanalysis from a prospective single center clinical trial, we analyzed 38 patients with newly diagnosed pure DCIS confirmed at excision. Each risk assessment tool presents risk in a different manner. Oncotype DCIS provides multiple assessments: a raw score (0-100), a DCIS Score Category (low, intermediate, high), and a Refined Score incorporating clinical features (10-year IBR risk). The VNPI calculates a raw score (4-12) and assigns a risk category (low, intermediate, high). MSK-N calculates a 10-year IBR risk. The tests were dichotomized as low vs. not-low risk categories using these thresholds: DCIS Score Category = low, DCIS Refined Score ≤ 10% IBR risk, VNPI risk category = low, MSK-N ≤ 10% IBR risk. Agreement of the 4 models (DCIS Score Category, DCIS Refined Score, VNPI, MSK-N) were compared using Spearman’s rank correlation for continuous data; percent agreement and Cohen’s kappa (k) were used to compare categorized data. Results: There was poor agreement of continuous risk assessments across the 4 models, with only VNPI and DCIS Refined Score showing significant but moderate correlation (r = 0.53, p = 0.001; others ranged r = 0-0.27, p &gt; 0.1). The number of cases identified as low-risk for each assay was DCIS Score Category = 14 (37%), DCIS Refined Score = 3 (8%), VNPI = 1 (3%), and MSK-N = 0. Percent agreement of low vs. not-low risk categorizations between DCIS Refined Score, VNPI, and MSK-N was 92-97%, but each assay classified 3 or fewer cases as low-risk and kappa was not significant (k = 0-0.48, p &gt; .1). DCIS Score Category demonstrated 63-71% agreement with the other 3 assays (k = 0-0.26). Only 1 case was classified as low-risk DCIS on multiple tests. Conclusions: DCIS risk models have poor agreement for determining IBR risk. DCIS Score Category initially identified many low-risk lesions; however, inclusion of clinical features to create a Refined Score decreased this substantially, providing very few additional low-risk cases for de-escalation over VNPI or MSK-N. Additional studies are needed to determine precise IBR rates when these models are used for adjuvant therapy decision-making. Clinical trial information: NCT03495011 .

Abstract F1-2: Clonal evolution of DCIS to invasion

Abstract Clonal evolution of DCIS to invasion Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive breast cancer (IBC). If not treated, at least 3 out of 4 women with DCIS will not develop IBC1-3. This implies many women with non-progressive, low-risk DCIS are likely to carry the burden of overtreatment. To solve this DCIS dilemma, two fundamental questions need to be answered. The first question is, how the subsequent IBC is related to the initial DCIS lesion. The second question is how to distinguish high- from low-risk DCIS at the time of diagnosis. This is essential to take well-informed DCIS management decisions, i.e., surgery, followed by radiotherapy in case of breast conserving treatment with or without subsequent endocrine treatment, or test whether active surveillance for low-risk DCIS is safe. How is the subsequent IBC related to the initial DCIS? The high genomic concordance in DNA aberrations between DCIS and IBC suggest that most driver mutations and CNA events are acquired at the earliest stages of DCIS initiation. It has therefore been assumed that most solid tumours arise from a single cell and that the probability of two independent tumours arising from the same tissue is low4-6. However, lineage tracing and genomic studies strongly suggest both direct and independent clonal lineages during the initiation of DCIS and evolution to IBC. In these processes, mammary stem cells have been implicated in DCIS initiation. Role of mammary stem cells in DCIS initiation Lineage tracing mouse model experiments have shown the fate of individual cells and lineages that acquire mutations before a tumour is established7-9. This is also relevant for DCIS initiation10,11, as different pools of MaSCs drive the growth and development of the ductal network and are considered the cell of origin for breast cancers9,10. The ductal trees remain quiescent until puberty, during which extension, branching and termination of terminal end buds (TEBs) leads to its expansion throughout the fat pad7,12,13. Any oncogenic mutation that occurs in a fetal MaSC will spread throughout the ductal network to a large part of the ductal tree, leading to sick lobes9. By contrast, oncogenic mutations acquired by a single MaSC during puberty spread to a smaller number of offspring located in small clusters in a part of the ductal network8,14. Direct lineage models for DCIS progression Direct lineage models postulate that DCIS has a single cell of origin that acquires mutations and progresses to IBC15-18. This is also supported by the high genomic concordance of CNAs and mutations in synchronous DCIS–IBC regions6,15,17,19-21 and the results of a recent large longitudinal study that profiled pure DCIS and recurrent IBC using multiple sequencing techniques, which estimated direct clonal lineages in approximately ~80% of patients18. Two distinct direct lineage models have been proposed: the evolutionary bottleneck model and the multiclonal invasion model. In the evolutionary bottleneckmodel, a single clone (or a limited number of clones) with an invasive genotype is selected and breaks through the basement membrane to migrate into surrounding tissues15,16,22, while other clones are unable to escape the ducts21-28. The multiclonal invasion model posits that most or all subclones can escape the basement membrane, establishing invasive disease6,16,17,20. The multiclonal model has not been studied widely in pure DCIS and recurrent IBC samples. Independent lineage model for DCIS progression DCIS lesions and IBCs can arise from different initiating cells in the same breast independently5,20,29-32. An analysis of sequential DCIS–IBC pairs in a unique, large-scale, in-depth study of 95 matched pure DCIS and recurrent IBC showed that ~20% of the IBC recurrences were indeed clonally unrelated to the primary DCIS18, as is also supported by some mathematical model studies33. The potential role of a field effect IBC can develop in the same breast as an initial DCIS even after treatment, which could be explained by the presence of a field effect34-37. Alternatively, the sick lobe hypothesis proposes that a single lobe harbours first-hit mutations, acquired in utero or during early mammary development37-42. This could also explain the restriction of IBC to the ipsilateral side of the breast39,43,44. Germline mutations may also explain the emergence of independent lineages in DCIS and IBC patients, lowering the threshold for cancer development32,43-46. Convergent evolution model of DCIS progression A third model for the emergence of IBC from DCIS is convergent evolution, in which the same mutations and CNA are selected and expanded during tumour growth such that environmental factors fuel competition between distinct clones and push them towards a similar genotype. Ultimately, two independent clonal lineages from different ancestral cells then happen to share multiple genomic aberrations or driver mutations across regions47-49. Although independent lineages are considered uncommon (~20%) in ipsilateral recurrences, they occur at much higher frequencies in contralateral recurrences (&amp;gt;80%), in which single-nucleotide polymorphism and comparative genomic hybridization microarrays show few (or no) genomic alterations shared in tumours from the contralateral breast cancer18,50,51. How to distinguish high- from low-risk DCIS at the time of diagnosis? The genomic and transcriptomic profile present at the time of DCIS diagnosis may contain crucial information on the risk of progression of DCIS to IBC. Thus far, it has been unclear whether prognostic gene expression markers can be used to separate indolent DCIS from potentially progressive DCIS. To this end, microarrays and RNA-seq have been applied for the comparison of bulk RNA from microdissected DCIS and IBC tissue. In synchronous DCIS–IBC, a limited number of transcriptional differences have been found and the few events discovered often varied extensively across different tumours52-56. Although these differences were strong, the added value of these studies is uncertain as they are often confounded by small sample size, lack of matched receptor status data, and low sample purity. Despite these limitations, these studies have implicated the epithelial-mesenchymal transition (EMT) and extracellular matrix (ECM) remodelling pathways as potentially relevant for the progression of DCIS to IBC55-62. We studied two large DCIS cohorts: the Sloane cohort, a prospective breast screening cohort from the UK (median follow-up of 12.5 years), and a Dutch population-based cohort (NKI, median follow-up of 13 years). FFPE tissue specimens from patients with pure primary DCIS after breast-conserving surgery (BCS) +/- RT that did develop a subsequent ipsilateral event (DCIS or invasive) were considered as cases, whereas patients that did not develop any form of recurrence up to the last follow-up or death were considered as controls. We performed copy number analysis (CNA) and RNAseq analysis on 229 cases (149 IBC recurrences and 80 DCIS recurrences) and 344 controls. We classified DCIS into the PAM50 subtypes using RNAseq data which revealed an enrichment of luminal A phenotype in DCIS that did not recur (P = 0.01, Fisher Exact test). No single copy number aberration was more common in cases compared to controls. RNAseq data did not reveal any genes significantly over/under expressed in cases versus controls after false discovery rate (FDR) correction. However, by limiting the analysis to samples that had not had RT and excluding pure DCIS recurrences we developed a penalized Cox model from RNAseq data. The model was trained on weighted samples (to correct for the biased sampling of the case control dataset) from the NKI series with double loop cross validation. Using this predicted hazard ratio, the samples were split into high, medium and low risk quantiles, with a recurrence risk of 20%, 9% and 2.5%, respectively at 5 years (p&amp;lt;0.001, Wald test). The NKI-trained predictor was independently validated in the Sloane No RT cohort (p = 0.02, Wald test). GSEA analysis revealed proliferation hallmarks enriched in the recurrence predictor (FDR = 0.058). The NKI-RNAseq predictor was more predictive of invasive recurrence than PAM50, clinical features (Grade, Her2 and ER) and the 12-gene Oncotype DCIS score (p &amp;lt; 0.001, permutation test using the Wald statistic) in both the NKI and Sloane series. In the methylation analysis, 50 controls were compared with 35 cases. We could identify Variably Methylation Regions (VMRs) and Differentially Methylated Regions (DMRs) between cases and controls. Interestingly, VMRs were enriched in cell adhesion pathways Conclusion The recently acquired knowledge described above on how often the subsequent IBC is directly related to the initial DCIS and on molecular markers predicting the risk of DCIS progression is essential for accurate DCIS risk assessment. This is essential to aid accurate clinical decision making to personalize DCIS management in the near future.

Abstract F1-3: Defining recurrence risk for DCIS: How do we tailor therapy

Abstract In tailoring treatment for DCIS, the goal is to avoid overtreatment while minimizing risk of recurrence. This necessitates estimation of recurrence risk and assessment of efficacy of each intervention in reducing risk. There are several clinicopathologic and treatment factors that have been proven in prospective trials to affect risk. These have been combined into a multivariable nomogram that estimates 10-year risk of recurrence (DCIS Nomogram). It is available online and free-of-charge, and has been validated in at least 5 independent populations with assessments of calibration and discrimination to assess its utility. There have also been attempts to develop genomic predictors of risk. The Oncotype DCIS score originally was based on a purely genomic analysis, but was “refined” to include clinicopathologic factors. DCISionRT was initially created with the inclusion of clinicopathologic factors. Neither has been prospectively validated and neither has published any assessments of calibration and discrimination. It is unclear what proportion of either risk estimate is due to the inclusion of clinicopathologic factors vs the actual genomic analysis. Both cost thousands of dollars. Furthermore, neither the refined Oncotype DCIS score nor the DCISionRT score incorporates the use of endocrine therapy. Tamoxifen and aromatase inhibitors have been proven to reduce the risk of recurrence by about 30-50%, and their use should be expected to decrease risk of recurrence. Yet, neither score accounts for this fact, and therefore the risk predictions are too high for those that take endocrine therapy, and too low for those that do not. In a sample of 59 women age ≥50 years old, with DCIS ≤2.5cm in size and clear margins, 10-year recurrence risk estimates from the DCIS Nomogram and refined Oncotype DCIS score (RDS) were compared. Overall, RDS risk estimates were in agreement (within 1-2% of the nomogram risk estimate range, calculated with and without the use of endocrine therapy) in 92% of cases. Among the 5 patients for which the Nomogram and RDS estimates disagreed, all had close margins (≤2mm). Close margins are associated with a statistically significant doubling of risk of recurrence. Nevertheless, the Oncotype DCIS score 10-year recurrence estimate was only 5-8% for these patients with close margins, while the Nomogram estimates were 11-14% (assuming use of endocrine therapy) or 21-27% (without endocrine therapy). From all published data, it seems clear that the refined Oncotype DCIS score markedly underestimates risk for those with close margins. And for those with clear margins, there was excellent (100%) agreement between the Nomogram and the refined Oncotype DCIS score. Given the need for cost-based value in health care, and given the cost-free availability of a validated predictive online DCIS nomogram, rigorous evaluation of predictive accuracy and proof of significant added clinical benefit should be performed and made available before any new expensive commercially available test is adopted for clinical use. Citation Format: Kimberly Van Zee. Defining recurrence risk for DCIS: How do we tailor therapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr F1-3.

Abstract PR002: Genomic predictor can discriminate between high- and low-risk DCIS

Abstract Introduction: Ductal carcinoma in situ (DCIS) is considered a non-obligate precursor of invasive ductal carcinoma. With the aim of preventing a subsequent invasive cancer, all DCIS lesions are currently treated with surgical excision often supplemented with radiotherapy (RT). To prevent DCIS over- or undertreatment, a reliable marker of DCIS invasiveness risk is urgently needed. Methods: We studied two large DCIS cohorts: the Sloane cohort, a prospective breast screening cohort from the UK (median follow-up of 11 years), and a Dutch population-based cohort (NKI, median follow-up of 13 years). FFPE tissue specimens from patients with pure primary DCIS after breast-conserving surgery (BCS) +/- RT that did develop a subsequent ipsilateral event (DCIS or invasive) were considered as cases, whereas patients that did not develop any form of recurrence up to the last follow-up or death were considered as controls. We performed copy number analysis (CNA) and RNAseq analysis on 229 cases (80 DCIS only recurrences) and 344 controls. Results: DCIS was classified into the PAM50 subtypes using RNAseq data which revealed an enrichment of luminal A phenotype in DCIS that did not recur (P = 0.01, Fisher Exact test). No single copy number aberration was more common in cases compared to controls. RNAseq data did not reveal any genes significantly over/under-expressed in cases versus controls after FDR correction. However, by limiting the analysis to samples that had not had RT and excluding pure DCIS recurrences, we could develop a penalized Cox model from RNAseq data. The model was trained on weighted samples (to correct for the biased sampling of the case-control dataset) from the NKI series with double loop cross-validation. The genes were selected using the Elastic net framework of penalization. Using this predicted hazard ratio, the samples were split into high, medium, and low-risk quantiles, with a recurrence risk of 23%, 7% and 2%, respectively at 5 years (p = 10-10, Wald test). The NKI-trained predictor was independently validated in the Sloane No RT no DCIS recurrence cohort (p = 0.02, Wald test). GSEA analysis revealed proliferation hallmarks enriched in the recurrence predictor (FDR = 0.058). The RNAseq predictor was more predictive of recurrence than PAM50, clinical features (Grade, Her2 and ER) and the 12-gene Oncotype DCIS score (p &amp;lt; 0.001, permutation test using the Wald statistic) in both the NKI and Sloane series. Conclusion: Genomic profiling of two independent series of DCIS with outcome data did not reveal any clear associations with recurrence until analysis was limited to a set of samples who had not had radiotherapy and DCIS recurrences were excluded. We then identified an RNAseq-based classifier that could differentiate primary DCIS in low-, medium-, and high-risk groups, and validated it in an independent cohort. This classifier, if validated in other datasets, will allow us to identify women who do not need intensive treatment for their DCIS. Citation Format: Maria Roman Escorza, Michael Sheinman, Tycho Bismeijer, Ahmed A. Ahmed, Vandna Shah, Jeffrey R. Marks, Lorraine M. King, Anargyros Megalios, Lindy L. Visser, Marlous Hoogstrat, Helen R. Davies, Tapsi Kumar, Deborah Collyar, Hilary Stobart, Sarah Pinder, Nicholas N. Navin, Andrew Futreal, Serena Nik-Zainal, E. Shelley Hwang, Esther H. Lips, Alastair Thompson, Lodewyk F.A. Wessels, Jelle Wesseling, Elinor J. Sawyer. Genomic predictor can discriminate between high- and low-risk DCIS [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr PR002.

A prospective decision impact study to evaluate the utility of the Oncotype DX Breast DCIS score assay in selecting patients with ductal carcinoma in situ (DCIS) following breast conservation surgery (BCS) for radiotherapy.

e12571 Background: There is increasing reliance on data provided by genomic risk assessment assays to guide therapeutic decisions. The objective of this prospective study was to assess the impact of the Oncotype DX Breast DCIS Score assay on radiation treatment recommendations in patients with DCIS undergoing BCS. Methods: This decision impact study is a prospectively enrolled observational study of newly diagnosed patients (n = 135) following BCS for removal of DCIS of all grades 30mm or less with clear margins (i.e. 2 mm or normal re-excised margins). Only patients who were candidates to receive radiation therapy were considered. Fifteen patients withdrew from the study or had insufficient volume of DCIS for assay analysis. Radiation Oncologists were blinded to the Oncotype DX Breast DCIS Score assay prior to recording their recommendation for radiotherapy or not. IRB approval was granted following review of study protocol and informed consent was obtained from all patients. Results: Among 120 patients tested, the Oncotype DX Breast DCIS Score assay determined that 58/120 (48.3%) of patients had a low score (LS) (0-38), 30/120 (25%) had an intermediate score (IS) (39-54) and 32/120 (26.7%) had a high score (HS) (&gt;55). The Oncotype DX Breast DCIS Score assay concurred with the Radiation Oncologists recommendation to proceed with radiation treatment in 96.7% of patients (i.e. 60/62 patients with an IS or HS). The Oncotype DX Breast DCIS Score assay altered treatment decisions in 12.5% (4/32) of patients with a HS and in 7.1% (2/28) patient with an IS. In patients where the Oncotype DX Breast DCIS Score assay altered treatment recommendation all had a low volume (i.e. less than 10mm) of high/intermediate grade DCIS with an IS or HS. Conclusions: This study demonstrates that Oncotype DX Breast DCIS Score assay accurately supports the selection of patients with DCIS for radiation treatment and equally can be helpful in selecting a subgroup of patients with small volumes of intermediate/high grade DCIS who can potentially avoid radiotherapy.

MiRNA expression deregulation correlates with the Oncotype DX® DCIS score

BackgroundCurrent clinical criteria do not discriminate well between women who will or those who will not develop ipsilateral invasive breast cancer (IBC), or a DCIS recurrence after a ductal carcinoma in situ (DCIS) diagnosis. The 12-gene Oncotype DX® DCIS assay (RT qPCR gene-based scoring system) was established and shown to predict the risk of subsequent ipsilateral IBC or DCIS recurrence. Recent studies have shown that microRNA (miRNA) expression deregulation can contribute to the development of IBC, but very few have evaluated miRNA deregulation in DCIS lesions. In this study, we sought to determine whether specific miRNA expression changes may correlate with Oncotype DX® DCIS scores.MethodsFor this study, we used archived formalin-fixed, paraffin-embedded (FFPE) specimens from 41 women diagnosed with DCIS between 2012 and 2018. The DCIS lesions were stratified into low (n = 26), intermediate (n = 10), and high (n = 5) risk score groups using the Oncotype DX® DCIS assay. Total RNA was extracted from DCIS lesions by macro-dissection of unstained FFPE sections, and next-generation small-RNA sequencing was performed. We evaluated the correlation between miRNA expression data and Oncotype score, as well as patient age. RT-qPCR validations were performed to validate the topmost differentially expressed miRNAs identified between the different risk score groups.ResultsMiRNA sequencing of 32 FFPE DCIS specimens from the three different risk group scores identified a correlation between expression deregulation of 17 miRNAs and Oncotype scores. Our analyses also revealed a correlation between the expression deregulation of 9 miRNAs and the patient’s age. Based on these results, a total of 15 miRNAs were selected for RT-qPCR validation. Of these, miR-190b (p = 0.043), miR-135a (p = 0.05), miR-205 (p = 0.00056), miR-30c (p = 0.011), and miR-744 (p = 0.038) showed a decreased expression in the intermediate/high Oncotype group when compared to the low-risk score group. A composite risk score was established using these 5 miRNAs and indicated a significant association between miRNA expression deregulation and the Oncotype DX® DCIS Score (p < 0.0021), between high/intermediate and low risk groups.ConclusionsOur analyses identified a subset of 5 miRNAs able to discriminate between Oncotype DX® DCIS score subgroups. Together, our data suggest that miRNA expression analysis may add value to the predictive and prognostic evaluation of DCIS lesions.

Association of the 12-Gene Breast DCIS Score® Assay With Local Recurrence in Patients With Ductal Carcinoma In Situ Treated on Accelerated Partial Breast Radiotherapy Protocols.

BackgroundThe following analysis explores clinicopathologic factors and the 12-gene Breast DCIS Score test result in order to better define an appropriate DCIS (ductal carcinoma in situ) population eligible for APBI (accelerated partial breast radiotherapy).MethodsThis exploratory analysis aimed to retrospectively measure the association between the 12-gene Oncotype DX Breast DCIS Score® assay (Redwood City, CA) and relevant clinicopathologic factors with locoregional recurrence in a pooled cohort of women treated with local excision and APBI on prospective phase II (NCT01185145) and phase III (NCT01185132) clinical trials. Univariable Cox proportional hazards regression was used to determine whether there was an association between local recurrence and DCIS Score result risk group (≥ 39 vs < 39) and clinicopathologic factors.ResultsThis analysis included 104 evaluable patients (n = 18 from NCT01185145 and n = 86 from NCT01185132). The median age was 60 years (range: 40-79). Seventy-nine percent of patients were postmenopausal. The median span of DCIS was 10 mm (range 2-45 mm). Two-thirds of the cohort presented with necrosis (71%). The distribution of DCIS Score® results ranged from 0 to 82, with 69% of patients having a DCIS Score result < 39. The median follow-up time was 8.2 years in NCT01185145 versus 3.0 years in NCT01185132. There were 6 local ipsilateral breast recurrences. DCIS Score result was significantly associated with local recurrence in univariable modeling, hazard ratio = 10.3 (95% CI 1.7, 198.4); p = 0.010. None of the clinicopathologic characteristics resulted in any significant association with locoregional recurrence.ConclusionThe Breast DCIS Score assay demonstrated risk stratification in this cohort of patients treated with local excision and APBI pooled from two clinical trials. These results are consistent with those recently published utilizing whole breast radiotherapy. Due to the small number of local recurrence events and limited follow-up time, further investigations are needed to confirm findings.

DUCHESS: an evaluation of the ductal carcinoma in situ score for decisions on radiotherapy in patients with low/intermediate-risk DCIS

Identification of women with DCIS who have a very low risk of local recurrence risk (LRR) after breast-conserving surgery (BCS) is needed to de-escalate therapy. We evaluated the impact of 10-year LRR estimates after BCS, calculated by the integration of a 12-gene molecular expression assay (Oncotype Breast DCIS Score®) and clinicopathological features (CPFs), on its ability to change radiation oncologists' recommendations for RT after BCS for DCIS. Prospective cohort study of women with DCIS treated with BCS. Eligibility criteria were as follows: age > 45years, tumor ≤ 2.5cm, and margins ≥ 1mm. Radiation oncologists provided 10-year LRR estimates without RT and recommendation for RT pre- and post-assay. Primary outcome was change in RT recommendation. 217 patients were evaluable, with mean age = 63years, mean tumor size = 1.1cm, and mean DCIS Score = 32; 140 (64%) were in the low-risk (<39), 32 (15%) were in the intermediate-risk (39-54), and 45 (21%) were in the high-risk groups (≥55). The assay led to a change in treatment recommendation in 76 (35.2%) (95%CI 29.1-41.8%) patients. RT recommendations decreased from 79% pre-assay to 50% post-assay (difference = 29%; 95%CI 22-35%) due to a significant increase in the proportion of patients with a predicted low LRR (< 10%) post-assay and recommendations to omit RT for those with a low predicted risk. The assay was associated with improved patient satisfaction and reduced decisional conflict. The DCIS Score assay combined with CPFs identified more women with an estimated low (<10%) 10-yr LR risk after BCS, leading to a significant decrease in recommendations for RT compared to estimates based on CPFs alone.

Abstract PS1-03: Active surveillance for DCIS: Clinical outcomes at 5.6 years mean follow-up

Abstract Introduction: Standard treatment for ductal carcinoma in situ (DCIS) involves surgical excision with radiation and often endocrine therapy. However, not all DCIS progresses to invasive ductal carcinoma (IDC); thus, surgical intervention may constitute overtreatment for DCIS that has low risk for progressing to IDC. A period of active surveillance (AS) with magnetic resonance imaging (MRI) monitoring may offer the opportunity to stratify lesions with high and low risk for invasion and to avoid overtreatment of DCIS. The purpose of this study was to characterize the outcomes of a cohort of women who elected to go on AS to avoid surgical intervention and to identify whether clinical and imaging features would identify patients who should convert to operative management. Methods: The clinicopathologic variables and outcomes of patients with DCIS who prospectively enrolled in MRI monitoring studies between 2002 and 2019 were retrospectively analyzed with IRB approval. We included 64 cases among 63 women who declined standard operative management for DCIS and had at least two breast MRIs. Clinicopathologic data and physician recommendations regarding continuing surveillance versus converting to operative management were recorded from the medical record. Those who had surgical excision showing IDC were considered to have progressed; those with only DCIS at excision or no operative intervention were considered to have stable disease. Results: Women in the cohort were an average of 53.6 years (29.8 - 78.9) old, and nearly all cases of DCIS with estrogen receptor (ER) status were ER+ (98.3%). Of the 64 cases in the cohort, 57 received endocrine therapy (89.1%). Average length of time on AS was 2.7 years (.2 – 11.9) with a median of 3 (2 – 18) MRIs performed and mean follow-up time 5.6 years (0.9 – 15.3). A total of 31 cases (48.4%) eventually had surgical excision while 33 (51.6%) remained on AS. There were 17 cases with IDC at surgery (26.6%). The IDC was an average of 1.5 cm (0.1 – 9.0) and most commonly ER + (88.2%), HER2 + (53.3%), grade 2 (58.9%), and node negative (82.4%). Only 7 women did not take endocrine therapy, but 3 of those women had IDC (42.9%). In 15 of the 17 cases with IDC (88.2%), the physician noted concern for progression in their clinic note and recommended surgical excision. This occurred a mean of 1.9 years (0.2 – 6.5) from the start of AS, with 47%, 67%, and 87% of cases identified within 1, 2 and 3 years from the start of AS. Suspicion of progression was based on an increase in lesion size or prominence on MRI and/or increase in calcifications on mammography. Of those that were identified as good candidates to continue AS with no concern for progression (n = 49), 16 chose to undergo surgical excision (32.7%) and 2 had IDC (4.1%). Conclusion: After over a decade of following women who seek alternatives to surgery for DCIS, we have identified clinicopathologic and imaging features that discriminate good candidates for AS and endocrine risk reducing therapy from those best treated with surgical excision. In our cohort of mostly ER+ patients receiving endocrine therapy on AS, over half of the cohort (51.6%) avoided surgical intervention. Her2 status, Oncotype DCIS, and Mammaprint scores of IDC is in process and will be presented. Our data support the study of AS as a method to stratify the risk of IDC and avoid overtreatment. We will present a personalized AS algorithm (based on biology and imaging) that we intend to prospectively test in the ATHENA network and NCI funded MCL consortium. Table 1: Cohort CharacteristicsFull Cohort (n=64)No evidence of IDC (n=47)IDC at surgery (n=17)Age at Diagnosis (years)53.6 (29.8 - 78.9)52.9 (29.8 - 74.5)55.5 (41.9 - 78.9)Time on AS (years)2.7 (.2 - 11.9)2.8 (.2 - 11.9)2.2 (.3 -5.9)Follow-Up (years)5.6 (0.9 - 15.3)Menopausal StatusPremenopausal26 (40.6%)22 (46.8%)4 (23.5%)Postmenopausal35 (54.7%)24 (51.1%)11 (64.7%)Unknown3 (4.7%)1 (2.1%)2 (11.8%)Breast CompositionFatty4 (6.3%)3 (6.4%)1 (5.9%)Scattered14 (21.9%)9 (19.1%)5 (29.4%)Heterogeneous27 (42.2%)19 (40.4%)8 (47.1%)Extreme17 (26.5%)14 (29.8%)3 (17.6%)Unknown2 (3.1%)2 (4.3%)0 (0.0%)ER StatusPositive57 (89.1%)41 (87.2%)16 (94.1%)Negative1 (1.6%)0 (0.0%)1 (5.9%)Unknown6 (9.3%)6 (12.8%)0 (0.0%)PR StatusPositive50 (78.1%)36 (76.6%)14 (82.3%)Negative5 (7.8%)3 (6.4%)2 (11.8%)Unknown9 (14.1%)8 (17.0%)1 (5.9%)GradeHigh20 (31.3%)15 (31.8%)5 (29.4%)Intermediate32 (50.0%)21 (44.6%)11 (64.7%)Low10 (15.6%)9 (19.1%)1 (5.9%)Unknown2 (3.1%)2 (28.5%)0 (0.0%Hormone TherapyYes57 (89.1%)43 (91.5%)14 (82.4%)No7 (10.9%)4 (8.5%)3 (17.6%) Citation Format: Case Brabham, Rita Mukhtar, April Liang, Paul Kim, Gillian Hirst, Amrita Basu, Heather Greenwood, Rita Freimanis, Alexander Borowsky, Shelley Hwang, Rick Baehner, Gregor Krings, Nola Hylton, Laura Esserman. Active surveillance for DCIS: Clinical outcomes at 5.6 years mean follow-up [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS1-03.

Abstract PD5-05: Including a 21-gene assay recurrence score in multivariable predictive model generation improves prediction of local recurrence after breast conserving surgery for ductal carcinoma-in-situ

Abstract Introduction Accurate prediction of local recurrence (LR) after breast conserving surgery (BCS) for ductal carcinoma-in-situ (DCIS) is crucial to personalize recommendations for adjuvant radiotherapy (RT). The 21-gene recurrence score (RS) predicts for distant metastases for woman with invasive breast cancer. We hypothesised that the RS could improve prediction of LR after BCS for DCIS. Methods We performed a population-based analysis of 1226 woman aged ≤74 treated with BCS ± RT for pure DCIS. Expert pathology review was obtained for all cases, as was the RS. Treatment and outcomes were obtained by deterministic linkage to administrative databases and chart review. Clinico-pathologic features obtained included: age, tumor size, nuclear grade, presence of comedonecrosis, multifocality, margins, and adjuvant radiation. The outcome assessed was local recurrence by 10 years from diagnosis of DCIS. The LR prediction model was developed using multivariable Cox regression, where a non-parametric approach was implemented to estimate the baseline hazard function. The proportional hazards assumption was assessed and time-interaction terms were included with each covariate in the model. Models were ranked based on c-statistic, log-likelihood estimate, and Akaike information criterion (AIC). Backward selection was used to obtain the final reduced model with time-interaction terms. Calibration for the best model was examined by grouping predicted 10-year risk of LR into deciles and plotting against observed 10-year risk of LR based on mean Kaplan-Meier estimates. Internal validation was performed by bootstrapping. Results Of the 1226 woman included, 514 were treated with BCS alone and 712 received adjuvant RT. Median follow up from time of treatment was 16 years (interquartile range (IQR): 14-18). The median age was 56 years (IQR: 49-64). Margins were negative in 90.5% of cases. Tumor size was ≤1cm in 430 (35.1%), 1-2.5cm in 633 (51.6%), and &amp;gt;2.5cm in 163 (13.3%). The median RS was 15 (IQR: 8-30) and the mean RS was 21.37 (SD 18.93). The best predictive model included the RS and had a c-statistic of 0.68 as well as the lowest AIC. This model included the following variables: RS, age, tumor size, nuclear grade, margin status, comedonecrosis (≤30% vs higher), multifocality, and treatment (BCS vs BCS+RT); it also included the following interaction terms: treatment and time, RS and time, comedonecrosis and time, and treatment and tumor size. Due to the non-linear relationship between certain characteristics and the risk of LR, quadratic terms for RS and age were also included. This model was well calibrated overall, especially in the lower risk range around the 10% risk threshold. It was also well calibrated in this risk range in the subset of woman who were treated with BCS alone. Conclusion The best performing model generated to predict LR after BCS for DCIS includes the RS. Work is ongoing to compare RS and the 12-gene DCIS score in terms of prediction of LR, as well as prediction of invasive LR specifically. This work can help guide future clinical de-escalation trials by better identifying woman with truly low risk of LR after BCS for DCIS. Citation Format: Ezra Hahn, Rinku Sutradhar, Sumei Gu, Lawrence Paszat, Danielle Rodin, Sharon Nofech-Mozes, Cindy Fong, Eileen Rakovitch. Including a 21-gene assay recurrence score in multivariable predictive model generation improves prediction of local recurrence after breast conserving surgery for ductal carcinoma-in-situ [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD5-05.

Use of the Twelve-Gene Recurrence Score for Ductal Carcinoma in Situ and Its Influence on Receipt of Adjuvant Radiation and Hormonal Therapy.

Tumor genomic prognostic assays estimate 10-year local recurrence risk in ductal carcinoma in situ (DCIS) and can guide treatment decisions. This study aimed to evaluate which DCIS patients treated with breast-conserving surgery (BCS) underwent DCIS score genomic testing and the influence of the results on adjuvant treatment recommendations. The study identified patients from the National Cancer Database (NCDB) who had DCIS treated with BCS from 2010 to 2016. Of 141,047 patients, 4255 (3%) had a DCIS score assessed, 0.3% in 2010 increasing to 5.8% in 2016 (p < 0.001). The patients most likely to undergo DCIS score assessment had more favorable tumor features in the multivariable analysis. The DCIS score result was documented for 91.4% of the tested patients (n = 3888): 70.5% of the low-risk, 14.9% of the intermediate-risk, and 14.6% of the high-risk patients. The patients with low-risk scores were less likely to have radiation than those with intermediate- or high-risk scores among the patients with either ER + (35.0% vs 71.0% or 81.1%) or ER- disease (48.1% vs 77.0% or 85.5%) (each p ≤ 0.001). The patients who had ER + disease with high- and intermediate-risk scores were most commonly treated with both radiation and hormone therapy (HT) (57.1% and 52.2%), whereas the most common treatment for those with a low-risk DCIS score was HT alone without radiation (37.1%). Comparison of genomic testing with clinicopathologic features showed an independent influence of genomic testing on treatment. Use of the DCIS score increased over time, predominantly for favorable DCIS. Patients with a low-risk score were significantly less likely to receive radiation, supporting an impact of the DCIS score on treatment de-escalation.

Tumour-infiltrating lymphocytes in ductal carcinoma in situ (DCIS)-assessment with three different methodologies and correlation with Oncotype DX DCIS Score.

Tumour-infiltrating lymphocytes (TILs) are prognostic in invasive breast cancer; however, their prognostic significance in ductal carcinoma in situ (DCIS) has not been established. The Oncotype DX (ODX) Breast DCIS Score test is a genomic assay used to predict the local recurrence risk. The aims of this study were to quantify TILs in DCIS by the use of three methodologies, and correlate them with the ODX DCIS Score. We studied 97 DCIS cases, all with an ODX DCIS Score. Cases with a low ODX DCIS Score were considered as one group, and those with an intermediate/high ODX Score were considered together. TILs were quantified on haematoxylin and eosin-stained slides. The methodologies used to quantify TILS included assessment of stromal TILs, assessment of touching TILs, and assessment of circumferential TILS. In cases with >5% stromal TILS, the percentage of stromal TILS was considered to be high. In cases with a mean number of more than five touching TILs per DCIS duct, TILs were considered to be present. The ODX DCIS Score was intermediate/high in 27 (28%) cases and low in 70 (72%) cases. There were >5% stromal TILs in 33 (34%) cases, and more than five touching TILs per DCIS duct in 15 (15%) cases; circumferential TILs were present in nine (9%) cases. In univariate analysis, a low ODX DCIS Score showed significant associations with absent touching TILS (P=0.027), stromal TILs<5% (P=0.031), and absent circumferential TILs (P=0.002). In logistic regression analysis adjusted for necrosis and nuclear grade, touching TILs and circumferential TILs showed significant associations with the ODX DCIS Score, whereas stromal TILs did not. Our results suggest that both the presence of TILs and the spatial arrangement of TILs or close proximity of TILs to DCIS, and TILs touching or encircling DCIS, may be predictive of recurrence.