Ductal Carcinoma In Situ Lesions Research Articles

Abstract PO3-24-01: Mapping inter- and intra-tumor heterogeneity in Ductal Carcinoma in situ and invasive breast cancer using integrative multi-omic profiling

Abstract Background: Molecular profiling of ductal carcinoma in situ (DCIS) has shown some prognostic utility in the clinic. However, there is still an incomplete understanding of the diversity of molecular mechanisms by which DCIS progresses to invasive breast cancer (IBC).Here, we utilize integrative multi-omic profiling of co-occurring DCIS and IBC in humans as a model for mapping the relationship between tumor mutations, global gene expression and morphological changes in DCIS and IBC. Methods: We performed targeted panel DNA sequencing (Tempus xT), whole transcriptome profiling and hyperplex immunofluorescence (Lunaphore COMET) on a cohort of 39 pairs of co-occurring DCIS and IBC lesions. We performed an integrative analysis of the above multi-modal data to uncover similar and dissimilar molecular trajectories in DCIS/IBC pairs. DAVID, KEGG and Reactome databases were utilized to analyze differential pathway activity between DCIS and IBC lesions. Results: IBC samples significantly overexpressed pathways associated with cycling cells and proliferation. For DCIS, many of the enriched pathways were related to CYP enzymes and xenobiotic metabolism. We also assessed enrichment of specific transcription factor binding sites (TFBS) with the associated differentially expressed genes. The top site enriched in IBC was a promoter regulatory element of unknown function (M120 motif KRCTCNNNNMANAGC) as well as sites regulated by heat shock transcription factor 4 (HSF4). Top TFBS enriched in DCIS included MEF2, HMEF2, AR and CEBPE. The top pathways associated with IBC using DAVID were related to extracellular matrix (ECM) organization and regulation. Interestingly, the top pathways associated with DCIS also included several pathways associated with ECM organization. On Reactome pathways diagrams for ECM formation distinct components of ECM formation and organization were enriched in IBC vs DCIS lesions, with invadopodia formation components and proteoglycans specifically enriched in IBC and integrin/laminin signaling enriched in DCIS. Among the 39 cases profiled, we observed distinct patterns of DCIS/IBC pairs with highly similar mutational profiles indicative of derivation from a shared progenitor as well as pairs with little-to-no molecular concordance that likely arose independently. Even within mutationally similar DCIS/IBC pairs there were different degrees of gene expression concordance. We subdivided mutationally similar pairs into two groups based on gene expression similarity (Euclidean Distance) and identified 115 genes that differed between these groups (q < 0.05), with the dissimilar DCIS lesions hallmarked by upregulation of a variety of pathways related to B-cell function, complement cascade and cell cycle progression. Specific mutations also were related to conserved transcriptional programs in these lesions, with MCL-1 amplified tumors showing a common gene expression signature of 357 altered genes (q < 0.05) with key differences in extracellular matrix organization and adaptive immune response pathways. Dissimilarly, tumors with CKS1B copy number alterations associated with 627 differentially expressed genes (q < 0.05) with the top targets related to endothelial function and angiogenesis. Conclusions: Integrative multi-modal analysis helps us better understand tumor progression at multiple levels of biomolecular dysregulation and shows the complex interplay among genome alterations, gene expression reprogramming and tissue morphology. Such approaches may yield future biomarker signatures that better encapsulate the diverse mechanisms by which DCIS lesions evolve. Citation Format: Henry Kaplan, Alexa Dowdell, Racheli Ben Shimoli, Angela Crabtree, Ann Berry, Fred Robinson, Christopher Carney, Carlo Bifulco, Brian Piening. Mapping inter- and intra-tumor heterogeneity in Ductal Carcinoma in situ and invasive breast cancer using integrative multi-omic profiling [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 PO3-24-01.

Abstract PO5-13-11: Quantitative Assessment of HER2 Expression in Intraductal Neoplasms of the Breast

Abstract HER2 (ERBB2) is an established prognostic and predictive marker for patients with invasive breast cancer and used in HER2-targeted therapy. The clinical and biological significance of expression of HER2 protein in patients with intraductal neoplasms of the breast is not well characterized. In this study, we used our HS-HER2 (High Sensitivity-HER2) which is a CAP/CLIA certified laboratory derived test (LDT) using quantitative immunofluorescence (QIF). We evaluated HER2 expression in DCIS (ductal carcinoma in situ), LCIS (lobular carcinoma in situ) and benign lesions to correlate with their clinicopathologic characteristics. Thirty- eight cases of DCIS, and fourteen cases of LCIS and thirty benign cases were selected from the Yale Pathology department archives and 252 ROIs (regions of interest) were annotated by a board-certified pathologist. DCIS is classified according to the three-tier nuclear grading system: low, intermediate, and high-nuclear grade. LCIS is classified as PLCIS (pleomorphic variant) and CLCIS (classic LCIS) according to the WHO classification of breast tumors. Serial sections of FFPE tumor specimens were used to accurately quantify the HER2 expression by the HS-HER2 assay and the acquisition by QuPath v.04 with Qymia extension. According to the LOD (limit of detection,3 amol/mm2), LOQ (limit of quantification, 9 amol/mm2) and LOL (limit of linearity, 23 amol/mm2) of the optimized HS-HER2 assay as performed in our CLIA lab shows a broad range of HER2 expression in both DCIS and LCIS lesions, ranging from 0.7 amol/mm2 to 111.4 amol/mm2 in DCIS and 3.6 amol/mm2 to 49.9 amol/mm2 in LCIS. High grade DCIS lesions express higher average HER2 levels (111.4 + 0.7 amol/mm2) than combined low and intermediate grade DCIS (77.9 +1.9 amol/mm2) with no significant difference between low/intermediate and high-grade DCIS. CLCIS lesions express higher average HER2 level (49.9 + 3.6 amol/mm2) than PLCIS (35.1 + 5.4amol/mm2) but again this is not statistically significant. HER protein expression is relatively low in benign lesions ranging from 0.8 to 8.4 amol/mm2. Using the HS-HER2 assay, our results show quantitative level HER2 levels in DCIS and LCIS breast lesions. These findings may be important as HER2 targeted therapies that work in gene-unamplified cancer (HER2 conjugated ADCs) gain broader usage in the clinic. Citation Format: Nay Nwe Nyein Chan, Haiying Zhan, Revekka Khaimova, Thazin Aung, Charles Robbins, Patricia Gaule, David Rimm. Quantitative Assessment of HER2 Expression in Intraductal Neoplasms of the Breast [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 PO5-13-11.

Abstract PS03-07: Morphometric signature identifies ductal carcinoma in situ of the breast with low risk of progression to invasive breast cancer

Abstract Background. Ductal carcinoma in situ (DCIS) is a frequently found precursor of invasive breast cancer (IBC). However, the majority of DCIS will never progress to IBC. As we cannot distinguish yet which DCIS will remain indolent (‘harmless’) from those that might progress in the future to IBC, almost all women with DCIS are intensively treated by surgery, often followed by radiotherapy. This brings an urgent clinical need to learn distinguishing harmless from potentially progressive DCIS to save many women with indolent DCIS the burden of unnecessary overtreatment. Aim. We aimed to investigate if the geometry and spatial configuration of DCIS ducts in Hematoxylin-Eosin (H&E) stained tissue sections are related to the risk of progression of DCIS to ipsilateral IBC (iIBC). Methods. We obtained data from a population-based cohort of women diagnosed with primary DCIS between 1989 and 2004 in the Netherlands, treated with breast conserving surgery (BCS) only and a median follow-up time of 12 years. A nested case-control study (n=689) was designed in which patients diagnosed with iIBC recurrences during follow-up were considered as “cases” (n= 226) and those with no subsequent iIBC as “controls” (n=463). The DCIS and stroma regions were digitally annotated on H&E-stained whole slide images (WSIs) by a pathologist as ground truth for the deep learning neural network of HALO AI module (IndicaLabs). We developed a computational pipeline to automatically detect and measure stroma areas, DCIS ducts, and the nucleus of their cells. We validated the accuracy of DCIS detection in H&Es WSIs from an external study, in which DCIS regions were digitally annotated by an independent pathologist (Translational Breast Cancer Research Consortium, TBCRC). We classified cases and controls according to morphological measurements using logistic ridge regression with double-loop cross-validation, followed by hierarchical clustering. The risk of subsequent iIBC after primary DCIS diagnosis was evaluated by multivariate Cox proportional hazards models. Results. The accuracy of DCIS detection performed by the computational pipeline was compared with pathologist annotations in 20 slides from the TBCRC study. Results showed a satisfactory DCIS overlap area agreement of 0.76 (0.68 – 0.83). We applied the DCIS computational pipeline on the case-control series. We obtained 15 morphological measurements for each DCIS duct, such as duct area, cell density, distance between ducts, average nucleus area, etc. We calculated 8 distribution parameters from each measurement in each WSI, including median and range. After leaving out redundant variables, 55 unique morphometric variables were obtained, representing the heterogeneity of DCIS ducts per WSI. The c lassifier revealed a median area-under the curve (AUC) of 0.66 (0.55-0.77) to predict 5-years free of iIBC, 0.59 (0.50-0.67) to predict 10-years and 0.60 (0.52-0.68) to predict 15-years. The 30 variables with the highest association with outcome were used to build four morphometric signatures. Signature number 1, which is characterized by lesions with small-sized ducts, a lower number of cells and a lower DCIS/stroma area ratio, showed a significant lower risk of developing iIBC compared to the other three signatures in a multivariate Cox regression model including grade, ER, COX-2 and HER2 expression: HR = 0.56 (0.28-0.78 95%CI). Conclusion. We developed a computational pipeline able to detect and measure DCIS ducts in H&E WSIs with high accuracy and reproducibility. DCIS lesions presenting the morphometric signature of small-sized DCIS ducts have a very low chance to progress to invasive breast cancer. After successful validation, our morphometric method will serve as a robust and easy to implement biomarker for de-escalation strategies in DCIS, and as such, could limit unnecessary overtreatment in the near future. Citation Format: Marcelo Sobral-Leite, Simon Castillo, Shiva Vonk, Xenia Melillo, Noomie Lam, Brandi de Bruijn, Yeman Hagos, Joyce Sanders, Mathilde Almekinders, Lindy Visser, Emilie Groen, Carolien Van der Borden, Petra Kristel, Ercan Caner, Leyla Azarang, Yinyin Yuan, Renee Menezes, Esther Lips, Jelle Wesseling, Grand Challenge PRECISION Consortium. Morphometric signature identifies ductal carcinoma in situ of the breast with low risk of progression to invasive breast cancer [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 PS03-07.

Ultrasound deep learning radiomics and clinical machine learning models to predict low nuclear grade, ER, PR, and HER2 receptor status in pure ductal carcinoma in situ.

Low nuclear grade ductal carcinoma in situ (DCIS) patients can adopt proactive management strategies to avoid unnecessary surgical resection. Different personalized treatment modalities may be selected based on the expression status of molecular markers, which is also predictive of different outcomes and risks of recurrence. DCIS ultrasound findings are mostly non mass lesions, making it difficult to determine boundaries. Currently, studies have shown that models based on deep learning radiomics (DLR) have advantages in automatic recognition of tumor contours. Machine learning models based on clinical imaging features can explain the importance of imaging features. The available ultrasound data of 349 patients with pure DCIS confirmed by surgical pathology [54 low nuclear grade, 175 positive estrogen receptor (ER+), 163 positive progesterone receptor (PR+), and 81 positive human epidermal growth factor receptor 2 (HER2+)] were collected. Radiologists extracted ultrasonographic features of DCIS lesions based on the 5th Edition of Breast Imaging Reporting and Data System (BI-RADS). Patient age and BI-RADS characteristics were used to construct clinical machine learning (CML) models. The RadImageNet pretrained network was used for extracting radiomics features and as an input for DLR modeling. For training and validation datasets, 80% and 20% of the data, respectively, were used. Logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms were performed and compared for the final classification modeling. Each task used the area under the receiver operating characteristic curve (AUC) to evaluate the effectiveness of DLR and CML models. In the training dataset, low nuclear grade, ER+, PR+, and HER2+ DCIS lesions accounted for 19.20%, 65.12%, 61.21%, and 30.19%, respectively; the validation set, they consisted of 19.30%, 62.50%, 57.14%, and 30.91%, respectively. In the DLR models we developed, the best AUC values for identifying features were 0.633 for identifying low nuclear grade, completed by the XGBoost Classifier of ResNet50; 0.618 for identifying ER, completed by the RF Classifier of InceptionV3; 0.755 for identifying PR, completed by the XGBoost Classifier of InceptionV3; and 0.713 for identifying HER2, completed by the LR Classifier of ResNet50. The CML models had better performance than DLR in predicting low nuclear grade, ER+, PR+, and HER2+ DCIS lesions. The best AUC values by classification were as follows: for low nuclear grade by RF classification, AUC: 0.719; for ER+ by XGBoost classification, AUC: 0.761; for PR+ by XGBoost classification, AUC: 0.780; and for HER2+ by RF classification, AUC: 0.723. Based on small-scale datasets, our study showed that the DLR models developed using RadImageNet pretrained network and CML models may help predict low nuclear grade, ER+, PR+, and HER2+ DCIS lesions so that patients benefit from hierarchical and personalized treatment.

Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer.

The progression of ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) in humans is highly variable. To better understand the relationship between them, we performed a multi-omic characterization of co-occurring DCIS and IBC lesions in a cohort of individuals. Formalin-fixed paraffin-embedded tissue samples from 50 patients with co-occurring DCIS and IBC lesions were subjected to DNA-seq and whole transcriptome RNA-seq. Paired DCIS and IBC multi-omics profiles were then interrogated for DNA mutations, gene expression profiles and pathway analysis. Most small variants and copy number variations were shared between co-occurring DCIS and IBC lesions, with IBC exhibiting on average a higher degree of additional mutations. However, 36% of co-occurring lesions shared no common mutations and 49% shared no common copy number variations. The most frequent genomic variants in both DCIS and IBC were PIK3CA, TP53, KMT2C, MAP3K1, GATA3 and SF3B1, with KMT2C being more frequent in DCIS and TP53 and MAP3K1 more frequent in IBC, though the numbers are too small for definitive conclusions. The most frequent copy number variations were seen in MCL1, CKSB1 and ERBB2. ERBB2 changes were not seen in IBC unless present in the corresponding DCIS. Transcriptional profiles were highly distinct between DCIS and IBC, with DCIS exhibiting upregulation of immune-related signatures, while IBC showed significant overexpression in genes and pathways associated with cell division and proliferation. Interestingly, DCIS and IBC exhibited significant differential expression of different components of extracellular matrix (ECM) formation and regulation, with DCIS showing overexpression of ECM-membrane interaction components while IBC showed upregulation of genes associated with fibronectin and invadopodia. While most co-occurring DCIS and IBC were mutationally similar and suggestive of a common clonal progenitor, transcriptionally the lesions are highly distinct, with IBC expressing key pathways that facilitate invasion and proliferation. These results are suggestive of additional levels of regulation, epigenetic or other, that facilitate the acquisition of invasive properties during tumor evolution.

Development of a Multi-Parametric ultrasonography nomogram for prediction of invasiveness in ductal carcinoma in situ

ObjectiveTo investigate the independent risk variables associated with the potential invasiveness of ductal carcinoma in situ (DCIS) on multi-parametric ultrasonography, and further construct a nomogram for risk assessment. MethodsConsecutive patients from January 2017 to December 2022 who were suspected of having ductal carcinoma in situ (DCIS) based on magnetic resonance imaging or mammography were prospectively enrolled. Histopathological findings after surgical resection served as the gold standard. Grayscale ultrasound, Doppler ultrasound, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS) examinations were preoperative performed. Binary logistic regression was used for multifactorial analysis to identify independent risk factors from multi-parametric ultrasonography. The correlation between independent risk factors and pathological prognostic markers was analyzed. The predictive efficacy of DCIS associated with invasiveness was assessed by logistic analysis, and a nomogram was established. ResultsA total of 250 DCIS lesions were enrolled from 249 patients, comprising 85 pure DCIS and 165 DCIS with invasion (DCIS-IDC), of which 41 exhibited micro-invasion. The multivariate analysis identified independent risk factors for DCIS with invasion on multi-parametric ultrasonography, including image size (>2cm), Doppler ultrasound RI (≥0.72), SWE's Emax (≥66.4 kPa), hyper-enhancement, centripetal enhancement, increased surrounding vessel, and no contrast agent retention on CEUS. These factors correlated with histological grade, Ki-67, and human epidermal growth factor receptor 2 (HER2) (P < 0.1). The multi-parametric ultrasound approach demonstrated good predictive performance (sensitivity 89.7 %, specificity 73.8 %, AUC 0.903), surpassing single US modality or combinations with SWE or CEUS modalities. Utilizing these factors, a predictive nomogram achieved a respectable performance (AUC of 0.889) for predicting DCIS with invasion. Additionally, a separate nomogram for predicting DCIS with micro-invasion, incorporating independent risk factors such as RI (≥0.72), SWE's Emax (≥65.2 kPa), and centripetal enhancement, demonstrated an AUC of 0.867. ConclusionMulti-parametric ultrasonography demonstrates good discriminatory ability in predicting both DCIS with invasion and micro-invasion through the analysis of lesion morphology, stiffness, neovascular architecture, and perfusion. The use of a nomogram based on ultrasonographic images offers an intuitive and effective method for assessing the risk of invasion in DCIS. Although the nomogram is not currently considered a clinically applicable diagnostic tool due to its AUC being below the threshold of 0.9, further research and development are anticipated to yield positive outcomes and enhance its viability for clinical utilization.

Abstract PR05: Spatial transcriptomics of ductal carcinoma in situ reveal subtype specific differences in tumoral and stromal cell compartments

Abstract Up to 50% of patients diagnosed with ductal carcinoma in situ (DCIS) never experience progression to invasive disease, even if left untreated. Current knowledge of what makes DCIS become invasive is limited and we lack diagnostic tools to predict which patients can be spared treatment. Escape of tumor cells from the breast ducts is influenced by characteristics of the tumor cells, the microenvironment surrounding the ducts, and the interplay between the two. Intraductal tumor cells in DCIS are not physically in contact with extraductal stromal cells. Until now, analyses of DCIS tissue have mainly been performed on bulk tissue, however, this approach does not take into consideration the unique morphology of DCIS. We used the Nanostring GeoMX® digital spatial profiling platform to determine the transcriptome of DCIS tumor cells and the surrounding stromal cells separately. From a large cohort of &amp;gt;500 DCIS cases from Akershus and Oslo University Hospitals, we selected 23 pure DCIS cases, grade 3, of different molecular subtypes: triple negative (TN), Luminal A (LumA) and HER2-enriched. At least four tumor-stroma pairs were selected from each case. Bioinformatic analyses were used to explore both tumor and stroma expression data and the interplay between the two cellular compartments. There were distinct gene expression differences between DCIS of different subtypes. Intertumoral heterogeneity was larger than intratumoral heterogeneity in all subtypes. This was also apparent in stromal cell compartments, although less pronounced. Gene ontology analyses of DCIS tumor cells from each of the three subtypes showed several overlapping biological processes, suggesting common mechanisms for regulating tumor cell growth in DCIS. We also found subtype specific differences: Tumor cells of the TN subtype showed upregulation of protein synthesis. Processes associated with RNA splicing were upregulated in tumor cells of the LumA subtype, whereas the HER2-enriched subtype showed increased DNA repair activity. The immune microenvironment differed between the subtypes: LumA DCIS were characterized by lower immune cell infiltration than TN and HER2-enriched, however, there was variation between and within the cases. Using in silico cell deconvolution, we found that B-cells were more abundant in HER2-enriched tumors, while T-cells were more common in TN and LumA. T-regulatory cells were found in all subtypes. The GeoMX® digital spatial profiling platform is well suited for exploring the transcriptome of DCIS samples. We found biologically relevant differences between tumor cells of the different molecular subtypes already at the DCIS stage in breast cancer progression. The immune cell composition surrounding DCIS lesions also differed between the subtypes. Further studies of the tumor-stroma interplay are required to understand the processes involved in progression of DCIS to invasive disease. Citation Format: Helga Bergholtz, Jens Henrik Norum, Tonje G Lien, Hossein Schandiz, Torill Sauer, Jürgen Geisler, Therese Sørlie. Spatial transcriptomics of ductal carcinoma in situ reveal subtype specific differences in tumoral and stromal cell compartments [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr PR05.

Predictive Performance of Radiomic Features Extracted from Breast MR Imaging in Postoperative Upgrading of Ductal Carcinoma in Situ to Invasive Carcinoma.

To investigate the predictive performance of radiomic features extracted from breast MRI for upgrade of ductal carcinoma in situ (DCIS) to invasive carcinoma. This retrospective study included 71 women with DCIS lesions diagnosed preoperatively by biopsy. All women underwent breast dynamic contrast-enhanced (DCE) MRI of the breast, which included pre-contrast and five post-contrast phases continuously with a time resolution of 60s. Lesion segmentation was performed manually, and 144 radiomic features of the lesions were extracted from T2-weighted images (T2WI), pre-contrast T1-weighted images (T1WI), and post-contrast 1st, 2nd, and 5th phase subtraction images on DCE-MRI. Qualitative features of mammography, ultrasound, and MRI were also assessed. Clinicopathological features were evaluated using medical records. The least absolute shrinkage and selection operator (LASSO) algorithm was applied for features selection and model building. The predictive performance of postoperative upgrade to invasive carcinoma was assessed using the area under the receiver operating characteristic curve. Surgical specimens revealed 13 lesions (18.3%) that were upgraded to invasive carcinoma. Among clinicopathological and qualitative features, age was the only significant predictive variable. No significant radiomic features were observed on T2WI and post-contrast 2nd phase subtraction images on DCE-MRI. The area under the curves (AUCs) of the LASSO radiomics model integrated with age were 0.915 for pre-contrast T1WI, 0.862 for post-contrast 1st phase subtraction images, and 0.833 for post-contrast 5th phase subtraction images. The AUCs of the 200-times bootstrap internal validations were 0.885, 0.832, and 0.775. A radiomics approach using breast MRI may be a promising method for predicting the postoperative upgrade of DCIS. The present study showed that the radiomic features extracted from pre-contrast T1WI and post-contrast subtraction images in the very early phase of DCE-MRI were more predictable.

Study of the Immunohistochemical Expression of p63 in Benign Lesions and Carcinoma of the Breast at a Tertiary Hospital in South India.

Invasive breast carcinoma is among the most common female cancers worldwide, causing high morbidity and mortality. Considerable disagreement in the interpretation of diagnostically challenging breast lesions based on histology alone has been documented. One of the essential histopathological findings that help distinguish benign from malignant lesions is the presence of the myoepithelial cell layer. Myoepithelial markers such as tumor protein 63 (p63) help distinguish invasive carcinoma from benign proliferations. p63 antibody is superior to other myoepithelial markers as it selectively stains the nuclei and is negative in stromal cells. To study the expression of p63 in various histological subtypes and grades of breast carcinomas. After routine hematoxylin and eosin stain, 65 cases of breast lesions were subjected to immunohistochemistry for p63 antigen using Novacastra ready-to-use monoclonal antibody p6. All cases were analyzed for p63 expression, and its staining arrangement was interpreted. In all benign lesions, immunoreactivity was noted in the myoepithelial cells, forming a continuous layer surrounding the luminal epithelial cells. The benign papillary lesions showed p63 staining in the fibrovascular core of the papillary fronds and at the periphery. A few single myoepithelial cells stained by p63 were also seen scattered discontinuously in ductal carcinoma in situ (DCIS). All invasive carcinomas and encapsulated papillary carcinomas were completely devoid of peripheral p63 staining of myoepithelial cells. p63 is a specific nuclear marker of myoepithelial cells in the breast and can, therefore, aid in distinguishing invasive ductal carcinoma from DCIS or rare questionable hyperplastic lesions. They also play a significant role in distinguishing various papillary lesions of the breast and, hence, can be incorporated into routine reporting for definitive diagnosis and accurate treatment.

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.

Role of contrast-enhanced mammography in the preoperative detection of ductal carcinoma in situ of the breasts: a comparison with low-energy image and magnetic resonance imaging.

To compare contrast-enhanced mammography (CEM) with low-energy image (LEI) alone and with magnetic resonance imaging (MRI) in the preoperative diagnosis of ductal carcinoma in situ (DCIS). In this single-center retrospective study, we reviewed 98 pure DCIS lesions in 96 patients who underwent CEM and MRI within 2weeks preoperatively. The diagnostic performances of each imaging modality, lesion morphology, and extent were evaluated. The sensitivity of CEM to DCIS was similar to that of MRI (92.9% vs. 93.9%, p = 0.77) and was significantly higher than that of LEI alone (76.5%, p = 0.002). The sensitivity of CEM to calcified DCIS (92.4%) was not significantly different from LEI alone (92.4%) and from MRI (93.9%, p = 1.00). However, CEM contributed to the simultaneous comparison of calcifications with enhancements. CEM had considerably higher sensitivity compared with LEI alone (93.8% vs. 43.8%, p < 0.001) and performed similarly to MRI (93.8%, p = 1.00) for noncalcified DCIS. All DCIS lesions were enhanced in MRI, whereas 94.9% (93/98) were enhanced in CEM. Non-mass enhancement was the most common presentation (CEM 63.4% and MRI 66.3%). The difference between the lesion size on each imaging modality and the histopathological size was smallest in MRI, followed by CEM, and largest in LEI. CEM was more sensitive than LEI alone and comparable to MRI in DCIS diagnosis. The enhanced morphology of DCIS in CEM was consistent with that in MRI. CEM was superior to LEI alone in size measurement of DCIS. This study investigated the value of CEM in the diagnosis and evaluation of DCIS, aiming to offer a reference for the selection of examination methods for DCIS and contribute to the early diagnosis and precise treatment of DCIS. • DCIS is an important indication for breast surgery. Early and accurate diagnosis is crucial for DCIS treatment and prognosis. • CEM overcomes the deficiency of mammography in noncalcified DCIS diagnosis, exhibiting similar sensitivity to MRI; and CEM contributes to the comparison of calcification and enhancement of calcified DCIS, thereby outperforming MRI. • CEM is superior to LEI alone and slightly inferior to MRI in the size evaluation of DCIS.

Prediction of coexisting invasive carcinoma on ductal carcinoma in situ (DCIS) lesions by mass spectrometry imaging.

Due to limited biopsy samples, ~20% of DCIS lesions confirmed by biopsy are upgraded to invasive ductal carcinoma (IDC) upon surgical resection. Avoiding underestimation of IDC when diagnosing DCIS has become an urgent challenge in an era discouraging overtreatment of DCIS. In this study, the metabolic profiles of 284 fresh frozen breast samples, including tumor tissues and adjacent benign tissues (ABTs) and distant surrounding tissues (DSTs), were analyzed using desorption electrospray ionization-mass spectrometry (DESI-MS) imaging. Metabolomics analysis using DESI-MS data revealed significant differences in metabolite levels, including small-molecule antioxidants, long-chain polyunsaturated fatty acids (PUFAs) and phospholipids between pure DCIS and IDC. However, the metabolic profile in DCIS with invasive carcinoma components clearly shifts to be closer to adjacent IDC components. For instance, DCIS with invasive carcinoma components showed lower levels of antioxidants and higher levels of free fatty acids compared to pure DCIS. Furthermore, the accumulation of long-chain PUFAs and the phosphatidylinositols (PIs) containing PUFA residues may also be associated with the progression of DCIS. These distinctive metabolic characteristics may offer valuable indications for investigating the malignant potential of DCIS. By combining DESI-MS data with machine learning (ML) methods, various breast lesions were discriminated. Importantly, the pure DCIS components were successfully distinguished from the DCIS components in samples with invasion in postoperative specimens by a Lasso prediction model, achieving an AUC value of 0.851. In addition, pixel-level prediction based on DESI-MS data enabled automatic visualization of tissue properties across whole tissue sections. Summarily, DESI-MS imaging on histopathological sections can provide abundant metabolic information about breast lesions. By analyzing the spatial metabolic characteristics in tissue sections, this technology has the potential to facilitate accurate diagnosis and individualized treatment of DCIS by inferring the presence of IDC components surrounding DCIS lesions. © 2023 The Pathological Society of Great Britain and Ireland.

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 .

Predicting Upgrade of Ductal Carcinoma In Situ to Invasive Breast Cancer at Surgery With Ultrafast Imaging.

BACKGROUND. Biopsy-proven ductal carcinoma in situ (DCIS) lesions are often upgraded to invasive cancer at surgery. Therefore, accurate prediction of the likelihood of invasion is helpful for surgical planning, including the need for sentinel lymph node biopsy (SLNB). OBJECTIVE. The purpose of the present study was to investigate whether kinetic features of clinically available ultrafast MRI (UF-MRI) can predict upgrade of biopsy-proven DCIS to invasive cancer at surgical excision. METHODS. Consecutive patients with biopsy-proven pure DCIS lesions who underwent UF-MRI with conventional dynamic contrast-enhanced MRI (DCE-MRI) and subsequently underwent surgery between August 2019 and January 2021 were identified. Patient and lesion characteristics, biopsy method and pathology, and lesion features on mammography, ultrasound, DCE-MRI, and UF-MRI were assessed to determine predictors of upgrade to invasive cancer. The Fisher exact test and Kruskal-Wallis test were used for association analysis. RESULTS. In 68 patients (median age, 52.0 years; range, 31-79 years) with 68 biopsy-proven pure DCIS lesions, 26 lesions (38%) were upgraded from in situ to invasive cancer. An upgrade of DCIS to invasive cancer was significantly associated with a shorter time to enhancement (TTE) on preoperative UF-MRI (p = .03), with a threshold of 11 seconds providing maximum specificity (50%) and sensitivity (76%) for upgrade. Larger lesion size on DCE-MRI (p = .001) and mammography (p = .04) was also significantly associated with upgrade; an optimal predictive threshold of 4.4 cm on DCE-MRI yielded sensitivity of 88% and specificity of 56%. No other specific variables were significantly associated with upgrade after surgery. Logistic regression of selected features combined with TTE produced a higher AUC (0.85) in predicting upgrade to invasive disease than did each factor alone, but this result was not statistically significant. CONCLUSION. Preoperative UF-MRI TTE and lesion size on DCE-MRI and mammography show potential in predicting upgrade of DCIS to invasive cancer at surgery. CLINICAL IMPACT. UF-MRI provides useful information that can be used in surgical planning, including determination of the need to perform SLNB.

Abstract 2875: Evidence of immunosuppression in patients with breast ductal carcinoma in situ

Abstract Introduction: Ductal carcinoma in situ (DCIS) is a noninvasive precursor to invasive breast cancer. Although not all DCISlesions progress to cancer, most DCIS are treated as early breast cancer, given the uncertainty of which lesions will progress. The current increase in the incidence of DCIS has sparked interest in the immune contexture of the DCIS lesions as well as the immune status of DCIS patients, as a means to predict which DCIS lesions will progress to cancer. Studies done so far in invasive breast cancer showed that the immune system can mediate both tumor-promoting influence (via T regulatory (Treg) cells, M2 macrophages, myeloid-derived suppressor cells (MDSCs)), as well as tumor-suppressing influences (via CD8+ and CD4+ effector T cells, natural killer cells (NK), M1 macrophages, tissue-resident memory T (Trm) cells, B cell and dendritic (DCs) cells). Similar studies are still lacking in DCIS. Our aim was to start closing the gap in our understanding of the DCIS immune microenvironment, which will pave the way for novel preventative and therapeutic strategy. Methods: We analyzed by flow cytometry peripheral blood mononuclear cells (PBMCs) from newly diagnosed DCIS patients for the presence of various immune cell types expressing specific phenotypic markers of immune effectors or immune suppressors and compared them with PBMC from age-matched healthy individuals. Results: We found a statistically significant increase in the frequency of FoxP3+ regulatory T cells in DCIS PBMC compared with healthy controls. There was also a significant increase in Tim-3+CD8+ T effector memory cells (P= 0.035) and Tim-3+ CD8+ NKT cells (P = 0.033) in the PBMCs of patients with DCIS compared with healthy controls. T cells expressing other exhaustion markers, such as PD-1+ and LAG-3+ were present at very low levels in both groups. Conclusion: Our results suggest that some of the many immunosuppressive mechanisms seen in patients with invasive breast cancer, such as regulatory T cells, are already present in pre-cancer DCIS. Evidence of the beginning of immune suppression is also reflected in the increased frequency of CD4+ and CD8+ T cells expressing the exhaustion marker Tim-3. Citation Format: Sedigheh Taghinezhad-S, Amir Hossein Mohseni, Pamela L. Beatty, Leisha A. Emens, Olivera J. Finn. Evidence of immunosuppression in patients with breast ductal carcinoma in situ [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2875.

High-Grade Ductal Carcinoma In Situ of the Breast With Regressive Changes: Radiological and Clinicopathological Findings.

Tumour regression is defined as continuity of changes leading to the elimination of a neoplastic population and is reflected as periductal fibrosis and intraductal tumour attenuation. The aim of this study was to describe the radiological and clinicopathological characteristics of high-grade breast ductal carcinoma in situ (DCIS) with regressive changes (RC). Thirty-two cases of high-grade DCIS with RC on biopsy specimens followed by excision were included. The mammographic, ultrasonographic (US), and magnetic resonance imaging (MRI) findings of cases were retrospectively reviewed according to the breast imaging reporting and data system (BI-RADS) lexicon. Clinical and histopathological findings [comedonecrosis, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) status and Ki-67 proliferation index] were recorded. The rate of upgrade to invasive cancer after surgical excision and lymph node involvement were evaluated. The most common mammographic finding was microcalcifications alone (68.8%). The most frequently seen findings on US were microcalcifications only (21.9%), followed by microcalcifications and hypoechoic area (18.7%). On MRI, most lesions presented as clumped non-mass enhancement with segmental distribution. ER/PR negativity (53.1%, 65.6%), HER2 positivity (56.3%) and high Ki-67 (62.5%), which are known to be associated with more aggressive behavior, were found to be proportionally higher. The rate of upgrade to invasive cancer was 21.8%. DCIS with RC lesions present most often as microcalcifications alone on both mammography and US. MRI features are not distinguishable from those of other DCIS lesions. DCIS with RC lesions show biomarker status reflecting more aggressive behavior and high upgrade rate to invasive cancer.

Abstract P6-05-11: Active surveillance versus conventional treatment in low-risk DCIS; women’s preferences in the LORD trial

Abstract Background: Ductal carcinoma in situ (DCIS) is a potential precursor to breast cancer. Its incidence has increased multifold with the introduction of breast cancer screening and makes for 20% of all malignant breast lesions in women. DCIS has the potential to progress into invasive breast cancer. However, the majority of DCIS lesions are indolent and will never progress during the patient’s lifetime. Consequently, there is a growing concern of overdiagnosis and overtreatment for women with DCIS. The LORD trial is a non-randomized, patient preference trial comparing active surveillance to conventional treatment (i.e., breast conserving surgery with or without radiotherapy or mastectomy). The primary outcome of this trial is the percentage of women without an occurrence of ipsilateral invasive breast cancer after 10 years of follow up. Within the patient preference design, women are free to opt for either treatment arm. In addition to active surveillance of the DCIS, quality of life (QOL) of women included in the LORD trial is also actively monitored. The aims of this study were to: a) describe the distribution of participants within the treatment arms, b) identify women’s motives to opt for their preferred treatment arm, and c) assess factors associated with a preference for either treatment arm. Methods: Data from the baseline patient QOL questionnaire was collected. This questionnaire was completed after the women’s diagnosis and first consultation with their physician. Descriptive statistics were used to assess the distribution in both treatment arms. Thematic analyses were used to describe self-reported reasons for treatment selection derived from the open-ended question about treatment preference. Multivariable logistic regression analyses were used to assess associations between the patient characteristics and their preferred treatment arm. Results: In total 384 women completed the baseline questionnaire, of which 376 entered their final treatment decision. Of these women, 287 (76%) opted for active surveillance and 89 (24%) for conventional treatment. Most frequently cited reason for opting for active surveillance was that treatment was not yet necessary (55%). Also, patients’ reasons for preferring active surveillance alluded to a high level of trust in the active surveillance plan (24%) and that disease progression could be picked up and treated in a timely manner (14%). Furthermore, 11% of patients cited the advice of their healthcare professional as a reason for opting for active surveillance and 8% cited reasons relating to altruism. Most reported reasons for opting for the conventional treatment arm were avoiding unnecessary risks (26%), avoiding cancer worry (18%), the notion that what doesn’t belong, should be removed from the body (18%) and a need for closure (13%). In multivariable logistic regression analyses, high level of education (OR 2.17; 95%CI 1.09-4.38) and higher knowledge score (OR 1.8; 95%CI 1.07-3.02) were associated with a preference for conventional treatment. Furthermore, women opting for active surveillance more often reported the decision to be a shared decision between them and their healthcare professional (OR 2.30; 95%CI 1.18-4.47) compared to women who chose conventional treatment, who more often reported decision-making to be patient-driven. Age and tolerance of uncertainty were not significantly associated with treatment preference. Conclusion: The LORD trial is the first to actively offer women with low-risk DCIS a choice between conventional treatment and active surveillance. Within this trial, most women opt for active surveillance, even though clinical guidelines still recommend treatment for all women with DCIS. Women with low-risk DCIS report high levels of trust in their physicians and the safety of active surveillance. Their preferences also highlight the necessity to proof that de-escalating treatment of low-risk DCIS is safe. Citation Format: Renée S. Schmitz, Ellen G. Engelhardt, Miranda A. Gerritsma, Carine M. Sondermeijer, Sena Alaeikhanehshir, Ellen Verschuur, Marja van Oirsouw, Julia Houtzager, Rosalie Griffioen, Nina Bijker, Ritse M. Mann, Frederieke van Duijnhoven, Jelle Wesseling, Eveline Bleiker. Active surveillance versus conventional treatment in low-risk DCIS; women’s preferences in the LORD trial [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 P6-05-11.

Investigating the expression of cytokeratin 5/6 in benign and malignant breast lesions

Introduction: Breast cancer (BC) is the most common cancer in women, which is the second most common malignancy in terms of mortality and prevalence after lung cancer. BC is a group of very diverse diseases that can be detected at a molecular, histopathological and clinical level. Objectives: The aim of the present study was to evaluate the expression of CK5/6 and its relationship to some of the factors affecting prognosis, such as tumor grade, lymph node involvement. Patients and Methods: In this cross-sectional study with descriptive and analytical aspects, 40 malignant and 20 benign tumors were collected in 2020 from the archives of the pathology department of two educational hospitals in the city of Ahvaz. The demographic and clinical characteristics of each specimen, including age, patient, lymphovascular and perineural invasion, lymph node involvement, tumor grade and tumor type were extracted from the patients’ record. Then the expression of CK5/6 intensity staining was examined by immunohistochemistry. Results: All benign breast lesions had positive expression for CK5/6 and staining intensity between six and nine. In the malignant group, 33 samples showed negative expression of CK5/6 and only seven samples (17.5%) showed positive expression with a low-staining index. A positive expression with a low-staining index. All seven positive specimens were invasive ductal carcinoma (IDC) lesions with staining index 2, 4, and 6. Additionally, none of the ductal carcinoma in situ (DCIS) specimens which immunostained were positive for CK5/6. In the present study, all IDCs with weak expression of CK5/6 were grade III. No statistically significant relationship was observed between perineural and lymphovascular invasion and lymph node involvement with the intensity of CK5/6 expression. Conclusion: Our study showed that cytokeratin immunohistochemical intensity is able to distinguish benign lesions from malignant IDC and DCIS lesions and accordingly in determining of tumor grade after weak staining in high-grade IDC, which may be due to squamous metaplasia in these tumors; however, more extensive research with a larger sample size are required to assess its effect in lymphovascular and perineural invasion and also lymph node involvement.

Inflammatory cytokine-enriched microenvironment plays key roles in the development of breast cancers.

As the incidence of breast cancer continues to increase, it is critical to develop prevention strategies for this disease. Inflammation underlies the onset of the disease, and NF-κB is a master transcription factor for inflammation. Nuclear factor-κB (NF-κB) is activated in a variety of cell types, including normal epithelial cells, cancer cells, cancer-associated fibroblasts (CAFs), and immune cells. Ductal carcinoma in situ (DCIS) is the earliest stage of breast cancer, and not all DCIS lesions develop into invasive breast cancers (IBC). Currently, most patients with DCIS undergo surgery with postoperative therapy, although there is a risk of overtreatment. In BRCA mutants, receptor activator of NF-κB (RANK)-positive progenitors serve as the cell of origin, and treatment using the RANK monoclonal antibody reduces the risk of IBC. There is still an unmet need to diagnose malignant DCIS, which has the potential to progress to IBC, and to establish appropriate prevention strategies. We recently demonstrated novel molecular mechanisms for NF-κB activation in premalignant mammary tissues, which include DCIS, and the resultant cytokine-enriched microenvironment is essential for breast cancer development. On the early endosomes in a few epithelial cells, the adaptor protein FRS2β, forming a complex with ErbB2, carries the IκB kinase (IKK) complex and leads to the activation of NF-κB, thereby inducing a variety of cytokines. Therefore, the FRS2β-NFκB axis in the inflammatory premalignant environment could be targetable to prevent IBC. Further analysis of the molecular mechanisms of inflammation in the premalignant microenvironment is necessary to prevent the risk of IBC.

Establishment of a 3D co-culture model to investigate the role of primary fibroblasts in ductal carcinoma in situ of the breast.

Ductal carcinoma in situ (DCIS) is a precursor form of breast cancer. 13%-50% of these lesions will progress to invasive breast cancer, but the individual progression risk cannot be estimated. Therefore, all patients receive the same therapy, resulting in potential overtreatment of a large proportion of patients. The role of the tumor microenvironment (TME) and especially of fibroblasts appears to be critical in DCIS development and a better understanding of their role may aid individualized treatment. Primary fibroblasts isolated from benign or malignant punch biopsies of the breast and MCF10DCIS.com cells were seeded in a 3D cell culture system. The fibroblasts were cultured in a type I collagen layer beneath a Matrigel layer with MCF10DCIS.com cells. Dye-quenched (DQ) fluorescent collagen I and IV were used in collagen and Matrigel layer respectively to demonstrate proteolysis. Confocal microscopy was performed on day 2, 7, and 14 to reveal morphological changes, which could indicate the transition to an invasive phenotype. MCF10DCIS.com cells form smooth, round spheroids in co-culture with non-cancer associated fibroblasts (NAFs). Spheroids in co-culture with tumor-associated fibroblasts (TAFs) appear irregularly shaped and with an uneven surface; similar to spheroids formed from invasive cells. Therefore, these morphological changes represent the progression of an in situ to an invasive phenotype. In addition, TAFs show a higher proteolytic activity compared to NAFs. The distance between DCIS cells and fibroblasts decreases over time. The TAFs seem to play an important role in the progression of DCIS to invasive breast cancer. The better characterization of the TME could lead to the identification of DCIS lesions with high or low risk of progression. This could enable personalized oncological therapy, prevention of overtreatment and individualized hormone replacement therapy after DCIS.