Ductal Carcinoma In Situ Samples Research Articles

FKBP10-inhibited β-catenin ubiquitination in the malignant transformation of breast epithelial cells.

e12580 Background: Current model of breast cancer (BCa) progression suggests a linear and three-stage process from normal epithelial tissue to ductal carcinoma in situ (DCIS), and then invasive ductal carcinoma (IDC). Since the detailed mechanisms for BCa oncogenesis remain largely unclear and there is still a lack of root-cause level interventions, exploring the underlying molecular alterations during three-stage process of BCa carcinogenesis is urgently needed. Methods: Three-stage specimens from the very same patients were collected. High-throughput sequencing was applied to obtain the differentially expressed genes among normal, DCIS, and IDC samples. Expression level and prognostic value of the selected gene were evaluated by PCR, western blot, tissue chip, and bioinformatics analysis. MCF10DCIS and MCF10Ca cell lines were respectively used to establish DCIS and IDC tumor models in breast epithelial cell-specific gene knockout mice. Patient-matched DCIS and IDC organoids were also constructed. Signaling pathways associated with malignant transformation of breast epithelial cells were detected by using high-throughput sequencing in mouse models and organoids. Protein binding was evaluated by protein mass spectrometry and co-immunoprecipitation. Results: By using high-throughput sequencing, we found that FKBP10 levels were gradually increased in three-stage specimens from the very same patients and were associated with poor prognosis. By establishing DCIS and IDC models in FKBP10flox/floxCre+/- and FKBP10flox/floxCre-/- control mice, we confirmed that FKBP10 deficiency could suppress BCa formation. Besides, FKBP10 knockdown could reduce oncogenic potentials in patient-matched DCIS and IDC organoids. Wnt/β-catenin signaling pathway was related to malignant transformation of breast epithelial cells, when MCF10DCIS+FKBP10flox/floxCre+/- model, MCF10Ca+FKBP10flox/floxCre+/- model, FKBP10-knockdown DCIS and IDC organoids, and their corresponding controls were comprehensively compared. Moreover, FKBP10 was found to inhibit β-catenin ubiquitination with the help of deubiquitinase Trim13, thus activating Wnt/β-catenin signaling pathway and accelerating malignant transformation of breast epithelial cells. Increased level of β-catenin was able to promote FKBP10 expression in a feedback loop. We also confirmed that exosome-loaded FKBP10-targeting peptide could suppress tumor growth both in vitro and in vivo. Conclusions: FKBP10-inhibited β-catenin ubiquitination was responsible in the malignant transformation from normal tissue to DCIS, and then IDC. Our study would uncover novel regulatory mechanisms of FKBP10 in three-stage process of BCa carcinogenesis and provide a new therapeutic approach for clinical treatment.

Multi-omics portrait of ductal carcinoma in situ in young women.

Young patients with breast ductal carcinoma in situ (DCIS) often face a poorer prognosis. The genomic intricacies in young-onset DCIS, however, remain underexplored. To address this gap, we undertook a comprehensive study encompassing exome, transcriptome, and vmethylome analyses. Our investigation included 20 DCIS samples (including 15 young-onset DCIS) and paired samples of normal breast tissue and blood. Through RNA sequencing, we identified two distinct DCIS subgroups: "immune hot" and "immune cold". The "immune hot" subgroup was characterized by increased infiltration of lymphocytes and macrophages, elevated expression of PDCD1 and CTLA4, and reduced GATA3 expression. This group also exhibited active immunerelated transcriptional regulators. Mutational analysis revealed alterations in TP53 (38%), GATA3 (25%), and TTN (19%), with two cases showing mutations in APC, ERBB2, and SMARCC1. Common genomic alterations, irrespective of immune status, included gains in copy numbers at 1q, 8q, 17q, and 20q, and losses at 11q, 17p, and 22q. Signature analysis highlighted the predominance of signatures 2 and 1, with "immune cold" samples showing a significant presence of signature 8. Our methylome study on 13 DCIS samples identified 328 hyperdifferentially methylated regions (DMRs) and 521 hypo-DMRs, with "immune cold" cases generally showing lower levels of methylation. In summary, the molecular characteristics of young-onset DCIS share similarities with invasive breast cancer (IBC), potentially indicating a poor prognosis. Understanding these characteristics, especially the immune microenvironment of DCIS, could be pivotal in identifying new therapeutic targets and preventive strategies for breast cancer.

Abstract PO4-26-02: Evaluation of Tumor Infiltrating Lymphocytes as a predictive biomarker of recurrence in patients with Ductal Carcinoma In Situ of the breast

Abstract Introduction: Ductal carcinoma in situ (DCIS) represents around 20% of early breast cancer diagnoses globally. Some studies evaluated risk factors associated with DCIS recurrence. Among these, age, surgical margins, comedonecrosis (CN), high nuclear grade, negative hormone receptors and HER2 expression stand out. Recent approaches have been evaluating the role of the immune microenvironment and its association with recurrence and progression of DCIS. Objective: To evaluate the association between Tumor Infiltrating Lymphocytes (TILs) in DCIS samples and disease recurrence. To characterize the immunological microenvironment of DCIS, analyzing the presence of TILs, “touching TILs” and desmoplastic reaction and their association with recurrence. Epidemiological, clinical, histological and immunohistochemical (IHC) characteristics were also evaluated. Methods: This is a retrospective cohort study with patients diagnosed with DCIS and treated at Sao Paulo State Cancer Institute and Hospital das Clinicas of University of Sao Paulo. We included women over 18 years old with a diagnosis of DCIS who underwent treatment from Jan/2007 to Dec/2020. Male patients, patients with a diagnosis of invasive or microinvasive disease in the anatomopathological examination of the surgical specimen or patients with history of any neoplasm were excluded. The main outcome was survival analysis according to the quantification of TILs, adjusted for potential confounders. For that, we collected data on age, presence of palpable mass, imaging findings, histological and IHC characteristics, such as expression of estrogen receptor (ER), progesterone receptor (PR) and hyperexpression of HER2, type of surgical approach, type of radiation therapy, use of endocrine therapy, length of follow-up, recurrence, and its type. Two pathologists evaluated TILS in the sample with the highest tumor representation and numerically quantified it as percentage. They also evaluated the presence of “touching tils” (lymphocytes in contact with the basement membrane) and desmoplastic reaction in the tumor stroma. Kaplan-Meier curves, log-rank tests and Cox regression models were used to evaluate survival. Chi-square tests were used to evaluate the association between categorical variables. Results: 283 patients met the eligibility criteria. Mean age of patients was 55 years. 15% had a palpable nodule at physical examination. Clustered amorphous microcalcifications were the most prevalent mammographic presentation, found in 41% of the patients. The most frequent histological and IHC features were cribriform presentation (73%) and ER positivity (86%), respectively. Desmoplastic reaction was absent in 10.5%, discreet in 51.9%, moderate in 24% and intense in 13.6% of the patients. Breast conserving surgery was performed in 189 patients, and 100 of them received adjuvant radiation therapy. Mean follow-up was 77.2 months, with a recurrence rate of 9.2%. We observed that tumors with focal necrosis (HR 6.4 [1.39-34.71] p 0.018) or CN (HR 4.53 [1.34 – 15.28] p 0.015) had higher risks of recurrence. Patients with a percentage value of TILs greater than or equal to 17% also had a higher risks of recurrence (HR 2.97 (1.17-7.51) p 0.02). These patients were mostly under 65 years of age (OR 0.45 [0.21 - 0.97] p 0.049). In a multivariate model, CN and TILs>17% remained significantly associated with recurrence (p=0.034 and p=0.035 respectively). There was a trend for invasive recurrence in 76.9% of the patients that relapsed when TILS were greater than or equal to 17% (p 0.062). “Touching TILs” were present in 12.9% of the patients but were not associated with recurrence (p=0.575). Conclusion: In our cohort, high value of TILs (>= 17%) and presence of CN were independently associated with DCIS recurrence. Our findings suggest that TILS are a prognostic immunological biomarker in DCIS and warrant further investigation in prospective trials to determine the most adequate cut-point. Citation Format: Camila Pasetto, Fernando Aguiar, Marcella Peixoto, Maira Doria, Bruna Mota, Jonathan Maesaka, Jose Roberto Filassi, Edmund Baracat, Rodrigo Gonçalves. Evaluation of Tumor Infiltrating Lymphocytes as a predictive biomarker of recurrence in patients with Ductal Carcinoma In Situ 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 PO4-26-02.

Abstract 6255: Personalized medicine for DCIS

Abstract Background: In 2023, 55,720 women will be diagnosed with non-invasive ductal carcinoma in situ (DCIS) in the United States. We evaluated RNA sequencing (RNA-Seq), clinical and social factors that drive subsequent breast events in a DCIS study population enriched for Black women (30%). Methods: RNA was extracted from macrosections of archival formalin-fixed paraffin-embedded (FFPE) DCIS tissue from Resource Archival Human Breast Tissue (RAHBT) from the St. Louis Breast Tissue Registry at Washington University School of Medicine and the Dana Farber Cancer Institute patient cohorts. Tissues were prepared by microsection of 5 uM whole section from unstained slides (Fisher). RNA was extracted using Qiagen RNeasy FFPE Kits from macrosectioned DCIS specimens. Purified total RNA was evaluated for quality and quantity using the Agilent Fragment Analyzer RNA assay. Bulk RNA sequencing was piloted in DCIS case-control samples using the SMART-seq and Hybrid Capture platforms at the DFCI Molecular Biology Core Facilities. Raw reads were aligned to the GRCh38/hg38 reference genome using STAR. Preliminary quality control analysis of a curated gene list showed higher quality data using the Hybrid Capture technology. Libraries for Hybrid Capture were pooled in 8plex reactions and hybridized to Twist Exome 2.0 probes for target enrichment. The final library pools were sequenced on an Illumina NovaSeq. Cases were defined as women diagnosed with DCIS in 1999 or later with subsequent invasive breast cancer, local DCIS recurrence, or lobular CIS recurrence. Controls were defined as women diagnosed with DCIS in 1999 or later without subsequent breast events during a similar follow-up time. The R package DESeq2 was used for data analysis. Results: The mean age at DCIS diagnosis was 56.3 (Std Dev 10.23). The mean follow-up time was 147.8 months. Hybrid Capture RNA-Seq files are stored and analyzed from the Harvard Medical School O2 Cluster using R programming (version 4.2.2, DEGreport). Quality control analyses demonstrated that the majority of the samples sequenced by Hybrid Capture had over 20 million total reads. Principal Component Analyses (PCA) and hierarchical clustering analyses of 19,821 protein-coding genes were conducted on the 143 DCIS samples sequenced using Hybrid Capture. PC1 was race (9%). A significant association was observed for follow-up time (PC3, 4.03%). First, we explored the association of the candidate gene ERBB2. The mean transcript abundance for ERBB2 was 11784.37 (case-control p-value=0.08). Preliminary analysis of selected genes of interest did not show statistically significant differences between cases and controls after FDR p-value adjustment. Differential gene expression analyses are ongoing. Conclusion: This study demonstrates the feasibility of generating high-quality RNA-seq data from diverse, archival DCIS samples. Citation Format: Aditi Hazra. Personalized medicine for DCIS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6255.

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 >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.

Interaction of de novo cholesterol biosynthesis and Hippo signaling pathway in ductal carcinoma in situ (DCIS)-comparison with the corresponding normal breast epithelium.

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer. However, if left untreated, about 50% of DCIS progress. Preventing such a progression is of paramount importance. Cumulative evidence indicated that the mevalonate cascade, the core of cholesterol biosynthesis, contributes to the regulation of the Hippo signaling pathway providing the isoprenoids required for GTPase activation, the nuclear accumulation of the Yes-associated protein (YAP)/transcriptional coactivator with PDZ-binding motif (TAZ) coactivator, and the subsequent gene transcription and that the disruption of this cooperation associated with tumor progression. In this in silico study, we investigated whether such a disruption occurred already during the transformation of the normal mammary epithelium into DCIS. To this aim, we interrogated a publicly available dataset, and we explored the interrelationship of the genes involved in the de novo cholesterol biosynthesis and the association with those coding for the core components of the Hippo signaling pathway in a set of patient-matched samples of DCIS and corresponding histologically normal (HN) epithelium. Most genes involved in cholesterol biosynthesis were more expressed in DCIS than in the corresponding HN epithelium. This differential expression was associated with a substantial change in their correlation profile. In particular, 3-hydroxy-3-methylglutaryl coenzyme-A reductase (HMGCR) and INSIG1 lost the positive association shown in the HN epithelium, and their negative association with LSS switched to a positive one. Also, GGPS1, which plays a crucial role in isoprenoids production, significantly changed its correlation profile. The positive association between GGPS1 and HMGCR or INSIG1 disappeared, whereas the positive association with SQLE, which drives the irreversible commitment to cholesterol, switched to a negative one in DCIS. Present findings corroborated the hypothesis that a dysfunctional mevalonate pathway possibly concurs with DCIS development by leading to abnormal production of isoprenoids, which in turn activate GTPases and promote YAP/TAZ nuclear translocation, and suggested the safe and low-cost treatment with statins as the possible winning strategy to contrast this metabolic dysfunction.

Computer Vision Identifies Recurrent and Nonrecurrent Ductal Carcinoma in Situ Lesions with Special Emphasis on African-American Women

Although nonrecurrent and recurrent forms of ductal carcinoma in situ (DCIS) of the breast are observed, no evidence-based test can make this distinction. The current retrospective case-control study used archival DCIS samples stained with anti-phospho-Ser226-glucose transporter type 1 and anti-phosphofructokinase type L antibodies. Immunofluorescence micrographs were used to create machine learning models of recurrent and nonrecurrent biomarker patterns, which were evaluated in cross-validation studies. Clinical performance was assessed by holdout studies using patients whose data were not used in training. Micrographs were stratified according to the recurrence probability of each image. Recurrent patients were defined by at least one image with a probability of recurrence ≥98%, whereas nonrecurrent patients had none. These studies found no false-negatives, identified true-positives, and uniquely identified true-negatives. Roughly 20% of the microscope fields of recurrent lesions were computationally recurrent. Strong prognostic results were obtained for both white and African-American women. This machine tool provides the first means to accurately predict recurrent and nonrecurrent patient outcomes. Data indicate that at least some false-positive findings were true-positive findings that benefited from surgical intervention. The intracellular locations of phospho-Ser226-glucose transporter type 1 and phosphofructokinase type L likely participate in cancer recurrences by accelerating glucose flux, a key feature of the Warburg effect.

Abstract 3126: Multimodal genome-wide survey of progressing and non-progressing DCIS

Abstract Introduction: Our current understanding of the molecular changes predisposing Ductal carcinoma in situ (DCIS) to progress to invasive breast cancer (IBC) is limited. The aim of this study is to characterize the molecular changes of DCIS to improve DCIS risk assessment. Methods: We obtained paraffin-embedded tissue of 210 DCIS samples with no concurrent or antecedent IBC from 5 cancer institutions, and extracted DNA and RNA. Transcriptome analysis: Illumina’s TruSeq RNA Exome kit was used for library construction, followed by sequencing. Methylome analysis: Bisulfite treated genomic DNA was restored and arrayed using the Illumina 450K methylation chips. DNA Copy number (CNV) analysis: CNV was estimated from the methylation data set using the EpiCopy R package. Results: Samples passing Q/C metrics: Transcriptome: 59 cases, 63 controls. Methylome & CNV: 93 cases, 98 controls. We classified samples into their intrinsic PAM50 subsets. Cases showed an increase in the Her2 subtype, and the controls were enriched in LuminalA (LumA) samples, while Basal and LuminalB (LumB) subtypes were evenly distributed. Compared to the TCGA IBC dataset, proportions of Her2 and LumB subtypes in DCIS were increased while the LumA cohort was decreased. Unsupervised clustering of the transcriptome data resulted in 3 clusters with key differences between PAM50 subtypes: one cluster predominated in Basal and Her2 subtypes, and a second was enriched in hormone-positive samples (LumA and LumB). For the methylome data, the optimal number of clusters was 6. Again, several clusters showed correlation with PAM50 subtype, e.g., one was enriched for hormone-negative subtypes (Basal and Her2), while another was enriched for hormone-positive subtypes (LumA and LumB). For the CNV data, the optimal number of clusters was 4. Here, one CNV cluster appeared predominantly in the Basal subtype, and there were multiple regions showing significant subtype-specific differences with the TCGA IBC data set. While the well-known heterogeneity of DCIS prevents the above broad molecular categories from strongly stratifying DCIS by outcome, we are continuing to analyze our data sets for predictive molecular signatures. Since the long-term outcome of all DCIS in this cohort is known, we are in the unique position to pursue additional questions such as PAM50 subtype differences in times-to-events or lineage fidelity (i.e., whether the subtype of the subsequent IBC matches the preceding DCIS), and it appears that the time to IBC diagnosis is shortest in Basal DCIS, while at the same time, lineage fidelity is lowest in Basal DCIS, as has been previously reported. Conclusions: Our subtype-stratified analyses identified multiple molecular differences both between intrinsic subtypes as well as between DCIS and IBC that suggest subtype-specific characteristics that may be exploitable for risk stratification of DCIS. Citation Format: Marija Debeljak, Soonweng Cho, Bradley Downs, Michael Considine, Brittany Avin-McKelvey, Yongchun Wang, William Grizzle, Katherine Hoadley, Charles Lynch, Brenda Hernandez, Paul van Diest, Wendy Cozen, Ann Hamilton, Debra Hawes, Edward Gabrielson, Ashley Cimino-Mathews, Liliana Florea, Leslie Cope, Christopher B. Umbricht. Multimodal genome-wide survey of progressing and non-progressing DCIS [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 3126.

Abstract PD2-09: Characterization of the lymphovascular invasion microenvironment reveals immune response dichotomy

Abstract Background: Metastasis is the leading cause of cancer related deaths in breast cancer patients. Lymphovascular invasion represents one of the earliest stages of metastasis wherein the cells are introduced to a very different and distinct microenvironment. Methods: We leveraged spatial techniques developed for limited specimens in archival tissue to study patient matched cross-sectional tumor samples from different stages of breast neoplasia including normal breast, ductal carcinoma in situ (DCIS), primary invasive carcinoma (IBC), lymphovascular invasion (LVI) and regional lymph node metastasis. We selected a set of 21 patients with ER+ breast cancer to generate cross-sectional samples of each of these stages, for a total of 331 samples. The areas of LVI were identified by a combination of H&E review and immunohistochemistry for podoplanin. We performed smart-3SEQ for gene expression profiling and light pass whole genome sequencing for DNA copy number alterations. Results: We profiled the spectrum of neoplasia for transcriptome-wide gene expression. Principal component analysis of all 252 DCIS, LVI, IBC, or metastasis samples using the top 500 genes with the highest variance demonstrated that clustering was roughly based on the diagnostic stage (i.e. DCIS, LVI, IBC, or metastasis). Differential gene expression profiling identified thousands of genes increased or decreased in expression across the transitional stages with the largest change in gene expression being the transition from normal breast to DCIS, dominated by gene expression down regulation. We next performed NMF clustering on 62 samples of LVI from 18 cases and identified two patterns of gene expression which define two subgroups. Gene ontology analysis revealed that one cluster was associated with increased proliferation and metabolism, whereas the second cluster was dominated by an immune response. When we analyzed the immune and proliferative LVI subgroups separately, we found that the immune profiles in the patient matched IBC and LVI samples from the LVI Immune cluster were similar, whereas the immune profiles in the patient matched IBC and LVI samples from the Proliferative cluster were significantly different. At the LVI stage, all immune cell populations estimated by CibersortX were decreased in the Proliferative LVI cluster. These changes were validated using immunofluorescence for proliferation (Ki67), T cells (CD3) and macrophages (CD68) on the same samples. Using the LVI centroids, we built a model that could predict the same clusters in the METABRIC IBC. Kaplan-Meier analysis showed a significant difference between groups, with the Proliferative-like IBC group having a worse prognosis than the Immune-like IBC group. Conclusions: We observed a dichotomy at the LVI stage with a more proliferative cluster that may escape the immune response and an immune cluster which has a microenvironment with a similar pattern to its primary IBC. The recognition of two groups of LVI, differing in immune association and proliferation, raises the possibility that the risk of metastasis could be different in these two groups, leading to different biological pathways of progression. Citation Format: Belén Rivero-Gutiérrez, Diego Mallo, Almudena Espín-Pérez, Sujay Vennam, Chunfang Zhu, Sushama Varma, Greg Scott, Joseph Foley, E Shelley Hwang, Carlo Maley, Robert West. Characterization of the lymphovascular invasion microenvironment reveals immune response dichotomy [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 PD2-09.

Expression of Cav-1, MCT1, and MCT4 in Ductal Carcinoma In Situ of the Breast and Their Associations With Clinicopathologic Features.

Loss of caveolin-1 (Cav-1) and upregulation of monocarboxylate transporters (MCTs, especially MCT1 and MCT4) in respectively tumor-associated stromal cells and malignant epithelial cells of invasive carcinoma have been found to play an important role in the metabolic coupling. However, this phenomenon has only been scarcely described in pure ductal carcinoma in situ (DCIS) of the breast. mRNA and protein expression levels of Cav-1, MCT1, and MCT4 in nine pairs of DCIS tissues and matched normal tissues were examined by quantitative real-time polymerase chain reaction, RNAscope in situ hybridization, and immunohistochemistry. Immunohistochemical staining of Cav-1, MCT1, and MCT4 in 79 DCIS samples was also done using tissue microarray. Cav-1 mRNA expression was significantly lower in DCIS tissues than in their corresponding normal tissues. In contrast, MCT1 and MCT4 mRNA expression levels were higher in DCIS tissues than in corresponding normal tissues. Low stromal Cav-1 expression was significantly associated with high nuclear grade. High epithelial MCT4 expression was associated with larger tumor size and human epidermal growth factor 2 positivity. At a mean follow-up of 10 years, patients with high epithelial MCT1/high epithelial MCT4 expression showed shorter disease-free survival than those with other expressions. No significant association was observed between stromal Cav-1 expression and epithelial MCT 1 or MCT4 expression. Changes in Cav-1, MCT1, and MCT4 are associated with carcinogenesis of DCIS. A high epithelial MCT1/high epithelial MCT4 expression might be associated with a more aggressive phenotype.

Polysulfide Serves as a Hallmark of Desmoplastic Reaction to Differentially Diagnose Ductal Carcinoma In Situ and Invasive Breast Cancer by SERS Imaging.

Pathological examination of formalin-fixed paraffin-embedded (FFPE) needle-biopsied samples by certified pathologists represents the gold standard for differential diagnosis between ductal carcinoma in situ (DCIS) and invasive breast cancers (IBC), while information of marker metabolites in the samples is lost in the samples. Infrared laser-scanning large-area surface-enhanced Raman spectroscopy (SERS) equipped with gold-nanoparticle-based SERS substrate enables us to visualize metabolites in fresh-frozen needle-biopsied samples with spatial matching between SERS and HE staining images with pathological annotations. DCIS (n = 14) and IBC (n = 32) samples generated many different SERS peaks in finger-print regions of SERS spectra among pathologically annotated lesions including cancer cell nests and the surrounding stroma. The results showed that SERS peaks in IBC stroma exhibit significantly increased polysulfide that coincides with decreased hypotaurine as compared with DCIS, suggesting that alterations of these redox metabolites account for fingerprints of desmoplastic reactions to distinguish IBC from DCIS. Furthermore, the application of supervised machine learning to the stroma-specific multiple SERS signals enables us to support automated differential diagnosis with high accuracy. The results suggest that SERS-derived biochemical fingerprints derived from redox metabolites account for a hallmark of desmoplastic reaction of IBC that is absent in DCIS, and thus, they serve as a useful method for precision diagnosis in breast cancer.

Abstract PR006: A living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts identifies multiple risk factors of invasive progression

Abstract Ductal Carcinoma in Situ (DCIS) is a non-invasive non-obligate precursor of invasive breast cancer (IBC). DCIS is usually treated by surgery combined with radiotherapy, which can have a large impact on the life of patients. However, many of these DCIS lesions would never progress into IBC. To reduce the overtreatment of DCIS, but assure proper treatment for high risk DCIS, it is crucial to understand the biology underlying DCIS. To study the biology of DCIS we established Mouse INtraDuctal (MIND) patient-derived xenograft (PDX) models by intraductally injecting patient DCIS material into the mammary ducts of female immunocompromised mice. We engrafted 130 samples, which have been incubated in vivo for a period of 12 months. We obtain a take rate of 88% with 46% of our models showing invasive progression. Histology and molecular subtyping by PAM50 classification are well preserved in the MIND models compared to the primary counterpart, ensuring that our MIND models represent the patient disease well. For 102 primary samples we obtained RNAseq profiles as well as for 64 matched MIND-PDX models. In addition whole exome-/panel sequencing data is generated from the same primary DCIS samples together with 12 matched MIND-PDX WES profiles as well as 60 matched Copy Number Variation (CNV) MIND-PDX profiles. Together these data revealed multiple biomarkers related to invasive progression, including factors such as high grade, solid growth, a high copy number aberrations burden, HER2, PTK6 & MYC amplifications and a high Ki67. On top of this we used whole mount imaging of the injected mammary glands extracted from our MIND-PDX models, showing two distinct growth patterns correlated with invasion. And as this is all done in the context of the PRECISION consortium this allows us to confirm and validate our findings in larger sequencing and imaging efforts of human samples. We have also successfully passaged 42 MIND-PDX models which showed minimal changes in pheno- and genotype over time indicating invasive behavior is an intrinsic phenotype of DCIS with minimal evolution, supporting a multiclonal evolution model. Moreover, this provided a collection of 19 stable sequentially transplantable DCIS MIND models including Luminal A, Luminal B, ER+/HER2+ and ER-/HER2+ models. Ultimately these models can be used to validate the biomarkers found to be related to invasive progression, as an example we proved the direct role of HER2 overexpression in invasive progression by inhibiting the HER2 receptor or by overexpressing HER2. In conclusion all this data together enabled us to create a well-characterized biobank of DCIS models with the unique opportunity to follow the natural progression, sequentially transplant 42 models, find genomic and transcriptomic profiles related to high risk DCIS and manipulate gene expression to validate the role of genes in DCIS progression. Citation Format: Stefan J. Hutten, Roebi de Bruijn, Catrin Lutz, Madelon Badoux, Timo Eijkman, Xue Chao, Marta Ciwinska, Andrea Herencia-Ropero, Petra Kristel, Lennart Mulder, Joyce Sanders, Mathilde Almekinders, Alba Llop-Gueverra, Helen R. Davies, Fariba Behbod, Serena Nik-Zainal, Violeta Serra, Jacco van Rheenen, Esther H. Lips, Lodewyk F.A. Wessels, Jelle Wesseling, Colinda Scheele, Jos Jonkers. A living biobank of patient-derived ductal carcinoma in situ (DCIS) Mouse-INtraDuctal (MIND) xenografts identifies multiple risk factors of invasive progression [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 PR006.

Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts.

Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.

Abstract 2979: ElevatedNRASexpression as a potential driver of DCIS progression to basal-like invasive breast cancer

Abstract Background: Ductal carcinoma in situ (DCIS) is the most common type of in situ premalignant breast cancers. What drives a subset of luminal DCIS to transition to basal invasive breast cancers is unclear. Basal-like invasive breast cancers are aggressive and associated with the shortest overall survival and time to distant metastasis. We have previously shown that N-Ras is highly expressed selectively in the basal-like subtypes of invasive breast cancers and can promote their growth and progression. In this study, we investigated whether NRAS expression at the DCIS stage can control transition from luminal DCIS to basal-like invasive breast cancers. Methods: Wilcoxon rank-sum test was conducted to assess the relative expression of NRAS in DCIS compared to invasive breast cancers in a patient cohort (GSE59248). NRAS levels were also determined by fluorescence in situ hybridization (FISH) in a collection of 21 patient tumor microarrays (TMAs) with concurrent normal, DCIS, and invasive breast cancer, and NRAS’s association with DCIS and invasive breast cancer was assessed by Wilcoxon signed rank test. How NRAS levels correlated with basal biomarkers in the TMAs, as well as in patient datasets GSE59248 and GSE3369 was determined by Pearson correlation. Gene expression changes in cell line were assessed by RNA-seq. Results: Invasive breast cancers showed higher NRAS mRNA levels, as compared to DCIS samples. These NRAShigh lesions were also enriched with basal-like features, such as basal gene expression signature, lower ER, higher p53 protein levels, and higher Ki67 levels. We have shown previously that N-Ras is a driver for tumor growth in SUM102 cells, which is a DCIS-like cell line model displaying basal-like features. Here we found that NRAS-silencing in these cells induced a shift to a luminal gene expression pattern as determined by PAM50. Conclusions: These data suggest that the rise of N-RAS levels in DCIS can not only mark but also control the emergence of basal-like features leading to more aggressive tumor activities. Targeting N-Ras and/or its downstream pathway may prevent the emergence of basal invasive breast cancers. Citation Format: Ze-yi Zheng, Hanan Elsarraj, Yang Hong, Jonathan T. Lei, Meenakshi Anurag, Yichao Shen, Flora Lo, Long Feng, Zifan Zhao, Xiang H. Zhang, Fariba Behbod, Eric C. Chang. ElevatedNRASexpression as a potential driver of DCIS progression to basal-like invasive breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2979.

Abstract 5108: Copy number analysis of pure DCIS and association with recurrence

Abstract With the widespread adoption of breast cancer screening the incidence of pure ductal carcinoma in situ (DCIS) has increased. As DCIS is considered a non-obligate precursor of invasive ductal carcinoma most women with pure DCIS are treated with breast conserving surgery (BCS) +/- radiotherapy. However, for many this is likely to be overtreatment as only a minority will develop a subsequent ipsilateral recurrence. Studies also show that only ~60% of these ipsilateral recurrences are invasive disease with the remainder being pure DCIS. To predict which women are most likely to benefit from interventions, there is a need to identify biomarkers that are associated with invasive recurrence. Our aim was to assess whether copy number aberrations (CNAs) could be used to identify DCIS that was likely to recur as invasive disease or remain recurrence-free during long-time follow up. We performed somatic copy number profiling on 309 pure DCIS samples that had not developed an ipsilateral event (controls), 198 that had developed subsequent ipsilateral invasive disease (INV-cases) and 58 that had developed subsequent ipsilateral pure DCIS (DCIS-cases). The samples were obtained from two large nation-wide cohorts: the Sloane cohort, a prospective breast screening cohort from the UK with a median follow up of 12.5 years and a Dutch population based cohort, with a median follow up of 13 years. CNAs were assessed using the CytoSNP array or low pass whole genome sequencing and analyzed using GISTIC. Integrative cluster (IntClust) subtyping revealed that only 5 subtypes were well represented in DCIS compared to 10 in invasive disease and the distribution of clusters between INV-cases and controls was similar with the exception of IntClust 4, which was significantly more common in controls (P= 0.025, Fishers exact test). IntClust 4 is characterized to have low levels of genomic instability and a CNA-devoid. INV-cases were globally more aberrant than controls (P = 0.006, Wilcoxon test) as assessed by the chromosomal instability index (CIN) score. GISTIC identified 17 recurrent amplifications, 21 recurrent gains and 22 recurrent losses in the whole cohort. Six of these regions were more common in INV-cases compared to controls: amplifications at 17q24.1 and 8p11.23, losses at 1p36.13 and 11q23.2 ​and gains at 17q21.33​ and 16p (Nominal P < 0.05 and FDR < 0.1, Fishers exact test). Subgroup analysis of ER+, Her2- INV-cases versus controls revealed an additional differential CNA, amplification at 11q13.3 more common in cases. DCIS-cases had similar CNAs to INV-cases and were more aberrant than controls in terms of CIN score (P < 0.037, Wilcoxon test) but not as aberrant as INV-cases. In conclusion, we have identified potential CNAs that are associated with invasive recurrence. Further analysis will integrate gene expression with copy number data to identify which genes are being targeted by these CNAs in order to identify pathways important in progression of DCIS. Citation Format: Ahmed A. Ahmed, Maria Roman-Escorza, Tycho Bismeijer, Michael Sheinman, Vandna Shah, Rana Shami, Jeffrey R. Marks, Lorraine M. King, Anargyros Megalios, Lindy L. Visser, Marlous Hoogstraat, Helen R. Davies, Tapsi Kumar, Deborah Collyar, Hilary Stobart, Sarah Pinder, Nicholas N. Navin, Andrew Futreal, Serena Nik-Zainal, E. Shelley Hwang, Lodewyk F. Wessels, Esther H. Lips, Alastair Thompson, Jelle Wesseling, Elinor J. Sawyer. Copy number analysis of pure DCIS and association with recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5108.

MiR-145, miR-205 and miR-451: potential tumor suppressors involved in the progression of in situ to invasive carcinoma of the breast.

MicroRNAs (miRNAs) control diverse biologic processes during tumor progression. This study was conducted to identify miRNAs that are implicated in progression of in situ to invasive breast cancer (IBC) and to evaluate their association with clinicopathological features of ductal carcinoma in situ (DCIS). We performed miRNA microarray analyses to find differentially expressed miRNAs between DCIS and IBC in a test set, and validated expression levels of selected miRNAs using a different set of tumors. Finally, we evaluated the relationship between clinicopathological features and the expression of selected miRNAs in DCIS samples. We found that miR-145-5p, miR-205-5p and miR-451a are significantly down-regulated in IBC compared to DCIS in the whole group, and in the estrogen receptor (ER)-positive and ER-negative subgroups. In a validation set, miR-145, miR-205, and miR-451 also showed lower expression levels in IBC than in DCIS, irrespective of ER status. Moreover, their expression levels were significantly lower in the invasive component compared to the in situ component within same tumors. MiR-145, miR-205 and miR-451 commonly showed lower expression levels in DCIS with positive HER2 status and high Ki-67 proliferation index. Especially, miR-145 and miR-205 showed lower expression levels in DCIS with microinvasion, compared to pure DCIS. In addition, lower miR-205 expression level was associated with high nuclear grade, comedo type necrosis, and hormone receptor negativity. Our study showed that miR-145, miR-205 and miR-451 expression decreased in IBC compared to DCIS, and their expression levels were low in DCIS with high-risk features for progression, implying their contributions in the progression of DCIS to invasive carcinoma as tumor suppressors.

Abstract P5-06-02: A gene expression meta-analysis identifies microenvironment differences in cellular composition and cell-cell interactions associated with breast cancer invasion

Abstract Background: The invasion of malignant cells into surrounding stroma is the histological hallmark differentiating invasive ductal carcinoma (IDC) from ductal carcinoma in situ (DCIS). The associated variations in the cellular composition and interactions in the tumor microenvironment, and how those mediate invasion are poorly understood. Systematic analyses of gene expression differences between DCIS and IDC are rare, confounded by cellular heterogeneity, and limited to few cases unable to distinguish stromal from epithelial contributions or compare pure DCIS from those synchronous with IDC. To address these problems we have assembled multiple datasets from publicly available gene expression studies of microdissected DCIS and IDC samples. Methods: The transcriptome from 192 regions microdissected from 140 cases was assembled from 5 published studies and included DCIS (83 epithelial, 22 stromal) and IDC (67 epithelial, 20 stromal) cases. Differences in infiltration of 10 immune cell types were measured using expression signatures. Expression subtypes were determined from the PAM50 signatures of epithelial regions using the genefu package. Gene Set Enrichment Analysis (GSEA) was performed using the gene sets in the Hallmark and Reactome collections. Cell-cell interactions between stromal and epithelial regions were measured using the co-expression of 1175 curated pairs of ligand-receptor genes and compared between DCIS and IDC using a permutation test. The corresponding interacting cell types were identified using RNA sequencing of 5444 single nuclei extracted from fine needle aspirates of two excised DCIS specimens. Results: Of the measured immune cell types, B cells showed a progressive depletion from normal to DCIS to IDC stroma. Pure IDC regions were significantly less likely to be the Luminal A subtype compared to synchronous IDC/DCIS and pure DCIS (p=0.0008). IFN signaling was higher in IDC epithelium suggesting possible differences in immune visibility between these two diseases. Higher calcium and glutamate signaling is observed in the DCIS stroma compared to IDC, calcium signaling has been implicated as both essential to normal breast function and as a positive effector of IDC proliferation. The expression-based measurement of stromal-epithelial interactions identified 99 and 115 ligand-receptor interactions enriched in DCIS and IDC, respectively (FDR<0.1). To precisely identify the corresponding interacting cell types, the expression profile of cells within the DCIS microenvironment was determined using single-nucleus RNA sequencing from two DCIS patients. The analysis identified 9 cell types, including luminal, basal, macrophage, adipocyte and endothelial, and 54% of the candidate cell-cell interactions could be mapped to at least one cell type pair. Based on these cell type mappings, interactions between luminal cells and fibroblasts were gained in IDC while those involving the vascular endothelium were lost, including interactions between CD24 and P-selectin, an interaction involved in leukocyte recruitment. Increased macrophage autocrine interactions were identified in both IDC stroma and epithelium through urokinase-urokinase receptor gene co-expression, an interaction previously associated with a transition to the M2 phenotype. Conclusions: The meta-analysis combined with novel computational methods, improves our ability to characterize the micro-environment of DCIS specimens, typically hard to study. Changes in cellular dynamics involving both immune and non-immune cell types suggest that mechanisms other than direct immune escape accompany progression. Citation Format: Adam Officer, Andre Dempsey, Farnaz Hasteh, Michal Slyper, Asa Segerstolpe, Joanna Klughammer, Judit Jane-Valbuena, Orit Rozenblatt-Rosen, Lyndsay Murrow, Zev Gartner, Aviv Regev, Christina Yau, Pablo Tamayo, Olivier Harismendy. A gene expression meta-analysis identifies microenvironment differences in cellular composition and cell-cell interactions associated with breast cancer invasion [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-06-02.

Abstract P5-01-01: Intraductal patient-derived xenograft models of ductal carcinoma in situ (DCIS) to distinguish indolent DCIS from aggressive DCIS

Abstract Ductal Carcinoma in Situ (DCIS) is a starting lesion in the milk duct of the breast, which accounts for 25% of all ‘breast cancers’ detected. DCIS is usually treated by surgery combined with radiotherapy, which can have a large impact on the life of patients. However, there is little to no evidence that treatment of low and intermediate grade DCIS reduces mortality, while women diagnosed with DCIS do perceive their risk of dying the same as patients with invasive disease. To reduce the negative perception and the overtreatment of DCIS, but assure proper treatment for high risk DCIS, it is crucial to understand the biology underlying DCIS. In order to study the biology of DCIS we established patient-derived xenograft (PDX) models by intraductally injecting fresh patient DCIS material into the mammary ducts of female immunocompromised mice (Mouse Mammary Intraductal(MIND)). To date, 150 primary DCIS patient samples were engrafted and >100 have been incubated in vivo for a period of 12 months. Using this method we obtain a take rate of 89% with 36% of our models showing progression. Histology and molecular subtyping by PAM50 classification are well preserved in the outgrown PDX lesions compared to the original human counterpart, ensuring that our models are a good representation of the patient disease. For >80 primary samples we obtained RNAseq as well as >50 matched PDX profiles. In addition WES or WGS data is generated from the same primary DCIS samples together with 10 matched PDX WES profiles as well as >40 matched CNV PDX profiles. On top of this we used whole mount imaging, in order to create 3D sections of the injected mammary glands extracted from our PDX models, showing two distinct growth patterns correlated with invasion. And as this is all done in the context of the PRECISION consortium this allows us to confirm and validate our findings in larger sequencing and imaging efforts of human samples. Besides collecting large amounts of data which we can now link to DCIS progression we have successfully sequentially transplanted >25 of our PDX models in order to create models that can be shared with the scientific community and can be manipulated to validate the role of genes in DCIS progression. As an example we took HER2 overexpression, which in our models was found to be associated to progressive disease. On the one hand we treated three progressive HER2 overexpressing DCIS PDX models with a HER2-antibody Herceptin showing a massive decline in growth, while on the other hand we infected two indolent HER2 negative DCIS PDX models with a HER2-GFP lentivirus showing a transformation to HER2 positive progressive growth. In conclusion all this data together enables us to create a well-characterized biobank of DCIS models of which we can follow the progression, sequentially transplant >25 models, find mutational and expression profiles related to high risk DCIS and manipulate gene expression to validate the role of genes in DCIS progression. Citation Format: Jelle Wesseling, Stefan Hutten, Catrin Lutz, Colinda Scheele, Madelon Badoux, Timo Eijkman, Roebi de Bruijn, Mathilde Almekinders, Joyce Sanders, Esther Lips, Jacco van Rheenen, Jos Jonkers, Grand challenge PRECISION consortium. Intraductal patient-derived xenograft models of ductal carcinoma in situ (DCIS) to distinguish indolent DCIS from aggressive DCIS [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-01-01.

Abstract P5-01-03: Mouse-intraductal (MIND): An in vivo model for studying the underlying mechanisms of DCIS malignancy

Abstract Background: Due to widespread adoption of screening mammography, there has been a significant increase in new diagnoses of ductal carcinoma in situ (DCIS). However, DCIS prognosis remains unclear. Methods: To address this gap, we developed an in vivo model, Mouse-INtraDuctal (MIND), by which patient-derived DCIS epithelial cells are injected intraductally and allowed to progress naturally in mice. The source of DCIS samples reflected clinical practice as predominantly high grade (70%), but also included intermediate grade (27%) and low grade (3%). Thirty-seven patient samples were injected into 202 mouse mammary glands and evaluated for invasive progression at a median duration of 9 months. The expression of clinically relevant biomarkers (ER, PR, Ki-67, HER2 and p53) on patient DCIS FFPE sections and xenografts’ extent of in vivo growth were evaluated for their utility in predicting DCIS invasive progression in the xenografts. Targeted DNA sequencing using Tempus XT oncology assay was used on patient DCIS in order to find a unique pattern of cancer related gene mutations that predicted DCIS invasiveness in the xenografts. Results: Similar to human DCIS, the cancer cells formed in situ lesions inside the mouse mammary ducts and mimicked all histologic subtypes including micropapillary, papillary, cribriform, solid, and comedo. Among 37 patient samples injected into 202 xenografts, at median duration of 9 months, 20 samples (54%) injected into 95 xenografts showed in vivo invasive progression while 17 (46%) samples injected into 107 xenografts remained noninvasive. Among the 20 samples that showed invasive progression in the MIND model, 9 patient samples injected into 54 xenografts exhibited a mixed pattern in which some xenografts showed invasive progression while others remained noninvasive. The mean duration of follow-up was not significantly different among the progressed, non-progressed or mixed groups (ANOVA; p-value=0.44). Among the clinically relevant biomarkers, only elevated progesterone receptor expression in patient DCIS and extent of in vivo growth in xenografts predicted an invasive outcome in the xenografts. Tempus XT oncology assay was used on 16 patient DCIS FFPE sections including eight patient DCIS that showed invasive progression (P), five patient DCIS that remained non-invasive (NP) and three patient DCIS that showed a mixed pattern (M) in the xenografts. Variant severity was called using SnpSift which is a program for identifying phenotype-relevant variants and predicts the severity of SNPs based on their effect on gene expression and function. COSMIC database was also used to identify mutations with pathogenic scores >0.5. Analysis of the frequency of cancer related pathogenic mutations showed no significant differences (P=27, NP=79, M=43, Kruskal-Wallis: P value=>0.05). There were also no differences in the frequency of low, moderate or high severity mutations (P= 25 highly severe, 120 moderately severe and 50 low-severity; NP=9 highly severe, 58 moderately severe and 28 low severity; M=3 highly severe, 33 moderately severe and 14 low severity; Kruskal-Wallis; P value >0.05). Conclusions: Highly severe and pathogenic variants in the patient’s DCIS were not associated with whether the DCIS developed into invasive lesions or remained non-invasive in the MIND models. These results are in agreement with previous studies that showed no significant differences in frequency of non-synonymous mutations and CNAs when comparing pure DCIS with synchronous IDC-DCIS. The MIND models are in immunocompromised mice, so the contribution of the immune system to DCIS progression may not recapitulate cancer progression in an immunocompetent state. However, the MIND model suggests that genetic changes in the DCIS are not the primary driver for the development of invasive disease. Citation Format: Aditi Rastogi, Jerome Lin, Yan Hong, Darlene Limback, Hanan S. Elsarraj, Haleigh Harper, Haley Haines, Hayley Hansford, Michael Ricci, Carolyn Kaufman, Emily Wedlock, Mingchu Xu, Jianhua Zhang, Lisa May, Terri Cusick, Marc Inciardi, Mark Redick, Jason Gatewood, Onalisa Winblad, Allison Aripoli, Ashley Huppe, Christa Balanoff, Jamie Wagner, Amanda Amin, Kelsey E. Larson, Lawrence Ricci, Ossama Tawfik, Hana Razek, Ruby O Meierotto, Rashna Madan, Andrew K. Godwin, Jeffrey Thompson, Susan G. Hilsenbeck, Andy Futreal, Alastair Thompson, E. Shelley Hwang, Fang Fan, Nicholas Navin, Fariba Behbod, Grand Challenge PRECISION Consortium. Mouse-intraductal (MIND): An in vivo model for studying the underlying mechanisms of DCIS malignancy [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-01-03.

Abstract P3-08-05: Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer

Abstract Background: Simultaneous ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC) is very common. However, it is not clear how often these histologies are clonally related or the mechanism by which DCIS evolves into IBC. In this study we evaluated tissue samples of DCIS and IBC by DNA and RNA sequencing from 39 patients with concurrent disease.Methods: Patients were identified from the Swedish Cancer Institute Breast Cancer Database starting sequentially with 2018 backwards to identify candidates with simultaneous DCIS and IBC. Individual pathologic review was performed from the cohort of patients who had had modified radical mastectomy to select 50 cases for analysis of normal breast, DCIS, and invasive disease. Sequencing was performed using the Tempus xT solid tumor assay (DNA-seq of 648 genes at 500x coverage, full transcriptome RNA-seq). The mutations identified by this assay include germline and/or somatic single nucleotide variants, insertions/deletions, and copy number variations. Results: Thirty-nine cases had adequate tissue for both DCIS and IBC for DNA and 31 for RNA analysis. DCIS and IBC were in the same quadrant of the breast for all cases. All IBC cases were ductal carcinoma. 38/39 IBC were estrogen receptor (ER) positive, 33/39 were progesterone receptor (PR) positive. 5 were HER2/neu amplified (three ER+/PR-, 1 ER+/PR+, 1 ER/PR-). 32/39 had Ki67 of 20% or less (IQR 14(9,19.5)). 35/39 were T1 or T2. Three were T3 and one T4. 21/39 were N0, 4/39 N1mic, 9/39 N1a, 3/33 N2a 2/39 N3a.For DCIS 24/39 had both genomic variants and copy number changes (V+C+), 7/39 were V+C-, 5/39 were V-C+ and 3/39 V-C-. For IBC 25/39 were V+C+, 7/39 were V+C-, 6/39 were V-C+, and 1/39 V-C-. In total, there were 36 unique genomic variants seen in DCIS but not the corresponding invasive sample. In contrast, there were 32 total unique variants seen in invasive but not the corresponding DCIS and 38 variants were seen in both samples. The one BRCA variant seen in both samples of a single patient was BRCA1 p.Q284, a known pathogenic variant but gBRCA normal. There were 86 copy number changes seen in DCIS but not IBC, 75 copy number changes seen in IBC but not DCIS and 47 copy number changes seen in both DCIS and IBC. 24/39 patients shared at least one common variant and 22/39 shared at least one copy number change. 4/39 had no copy changes in either sample but all of these had genomic variants. 5/39 had no variants in either sample but all of these had copy number changes. PIK3CA was seen in 2/39 IBC, 2/39 DCIS and 2/39 in both. TMB IQR was 1.6(1.1, 3.4) for IBC and 2.1 (1.1,3.2) for DCIS. All samples tested for MSI were stable. Only one patient had identical genomic variants and copy changes in both DCIS and IBC. The most frequent changes were: RNA sequencing revealed 1178 genes with significant gene expression differences between paired DCIS and IBC (q<0.001). RNA-seq data was quantified using Kallisto and differential gene expression was assessed using DESeq2. Pathway enrichment was performed using rank GSEA against the MSigDB C2 collection (filtered to KEGG, Reactome and Biocarta pathways only). Upregulated pathways in DCIS involved more immunogenic pathways while IBC upregulated pathways involved proliferation and cell cycling. Conclusions: The transition from DCIS to IBC is a dynamic process. How much of these differences are the result of tumor heterogeneity and temporal factors as opposed to truly separate clones will require more study. This could have significant implications for the treatment of DCIS. VariantGain/Loss of FunctionIBC onlyDCIS onlySame in BothTotalTP53Loss53614MAP3K1Loss51511GATA3Gain3249KM2TCLoss0538PTENLoss2237Copy ChangeMCL1 (1q21.2)Gain68822CKS1B (1q21.3)Gain95619ERRB2 (17q12)Gain0459JAK1 (1p31.3)Loss2428IKZF1 (7p12.1)Loss2327 Citation Format: Henry G Kaplan, Anna B Berry, Alexa Dowdell, Brian Piening. Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-08-05.