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Background. DCIS consists of a molecularly heterogeneous group of premalignant lesions, with variable risk of invasive progression. Understanding biomarkers for invasive progression could help individualize treatment recommendations based upon tumor biology. As part of the NCI Human Tumor Atlas Network (HTAN), we conducted comprehensive genomic analyses on two large DCIS case-control cohorts. Methods. We performed smart3-seq and low-pass whole genome sequencing on two independent, retrospective, longitudinally sampled DCIS case-control cohorts. TBCRC 038 was a multicenter cohort diagnosed with DCIS between 1998 and 2016 at one of the Translational Breast Cancer Research sites; the RAHBT (Resource of Archival Human Breast Tissue) cohort included women identified through the St. Louis Breast Tissue Repository, and the Women’s Health Repository diagnosed between 1997 and 2001. We studied the spectrum of molecular changes present and sought genomic predictors of subsequent ipsilateral breast events (iBEs: DCIS recurrence or invasive progression) in both DCIS epithelium and stroma in formalin fixed paraffin embedded tissue. We generated de novo tumor and stroma-centric subtypes for DCIS that represents fundamental transcriptomic organization. Copy number analysis was performed using low-pass DNA sequencing. Non-negative matrix factorization (NMF) was applied to the RNA expression of all coding genes to identify clusters. A negative-binomial regression model was used to identify differentially expressed genes. Results. We analyzed 677 DCIS samples from 481 patients with 7.1 years median follow-up. In TBCRC samples, we identified three clusters via NMF in TBCRC referred to as ER low, quiescent, and ER high. The ER-low cluster had significantly higher levels of ERBB2 and lower levels of ESR1 compared to quiescent and ER-high clusters. Quiescent cluster lesions were less proliferative and less metabolically active than ER high and ER low subtypes. These findings were replicated in the RAHBT cohort. Focusing on the stromal component of DCIS from laser capture microdissection in RAHBT samples, we identified four distinct DCIS-associated stromal clusters. A “normal-like” stromal cluster with ECM organization and PI3K-AKT signaling; a “collagen-rich” stromal cluster; a “desmoplastic” stromal cluster with high fibroblast and total myeloid abundance, mostly associated with macrophages and myeloid dendritic cells (mDC); and an “immune-dense” stromal cluster. Further, we compared differentially expressed genes in patients with or without subsequent iBEs within 5 years of diagnosis. Hypothesizing that the resulting 812 DE genes (DESeq2) represent multiple routes to subsequent iBEs, we leveraged NMF to identify paths to progression. In both TBCRC and RAHBT cohorts, poor outcome groups exhibited increased ER, MYC signaling, and oxidative phosphorylation, supporting that these pathways are important for DCIS recurrence and progression. Conclusion. Comprehensive genomic profiling in two independent DCIS cohorts with longitudinal outcomes shows distinct DCIS stromal expression patterns and immune cell composition. RNA expression profiles reveal underlying tumor biology that is associated with later iBEs in both cohorts. These studies provide new insight into DCIS biology and will guide the design of diagnostic strategies to prevent invasive progression. Citation Format: Siri H Strand, Belén Rivero-Gutiérrez, Kathleen E Houlahan, Jose A Seoane, Lorraine M King, Tyler Risom, Lunden Simpson, Sujay Vennam, Aziz Khan, Timothy Hardman, Bryan E Harmon, Fergus J Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla F McAuliffe, Julie Nangia, Joanna Lee, Jennifer Tseng, Anna Maria Storniolo, Alastair Thompson, Gaorav Gupta, Robyn Burns, Deborah J Veis, Katherine DeSchryver, Chunfang Zhu, Magdalena Matusiak, Jason Wang, Shirley X Zhu, Jen Tappenden, Daisy Yi Ding, Dadong Zhang, Jingqin Luo, Shu Jiang, Sushama Varma, Cody Straub, Sucheta Srivastava, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeffrey R Marks, Graham A Colditz, E Shelley Hwang, Robert B West. The Breast PreCancer Atlas DCIS genomic signatures define biology and correlate with clinical outcomes: An analysis of TBCRC 038 and RAHBT cohorts [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 GS4-07.

Ductal carcinoma in situ; Tumor microenvironment; Whole genome sequencing Carcinoma ductal in situ; Microambiente tumoral; Secuenciación del genoma completo Carcinoma ductal in situ; Microambient tumoral; Seqüenciació del genoma complet 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. This publication is part of the HTAN (Human Tumor Atlas Network) Consortium paper package. A list of HTAN members is available at humantumoratlas.org/htan-authors/. R01 CA185138-01 (E.S.H.); U2C CA-17-035 Pre-Cancer Atlas (PCA) Research Centers (E.S.H., R.B.W., C.M., K.P., G.A.C., K.O.); UO1 CA214183 (J.R.M.); DOD BC132057 (E.S.H., C.M.); BCRF 19-074 (E.S.H.); BCRF 19-028 (G.A.C.); PRECISION CRUK Grand Challenge (E.S.H.); R01CA193694 (R.B.W., G.A.C.), BCRF PPI-18-006 (R.B.W.). AEI RYC2019- 026576-I, "LaCaixa" Foundation LCF/PR/PR17/51120011 (J.A.S.). S.H.S. was supported by the Lundbeck Foundation (R288-2018-35) and the Danish Cancer Society (R229-A13616). K.E.H. was supported by a CIHR Banting Postdoctoral Fellowship. TBCRC 038 was conducted by the TBCRC, which receives major funding support from The Breast Cancer Research Foundation and Susan G. Komen. Some results in this paper are based upon data generated by the TCGA Research Network.

Intra-tumoral heterogeneity (ITH) could represent clonal evolution where subclones with greater fitness confer more malignant phenotypes and invasion constitutes an evolutionary bottleneck. Alternatively, ITH could represent branching evolution with invasion of multiple subclones. The two models respectively predict a hierarchy of subclones arranged by phenotype, or multiple subclones with shared phenotypes. We delineate these modes of invasion by merging ancestral, topographic, and phenotypic information from 12 human colorectal tumors (11 carcinomas, 1 adenoma) obtained through saturation microdissection of 325 small tumor regions. The majority of subclones (29/46, 60%) share superficial and invasive phenotypes. Of 11 carcinomas, 9 show evidence of multiclonal invasion, and invasive and metastatic subclones arise early along the ancestral trees. Early multiclonal invasion in the majority of these tumors indicates the expansion of co-evolving subclones with similar malignant potential in absence of late bottlenecks and suggests that barriers to invasion are minimal during colorectal cancer growth., Invasion is a critical step in tumor development. Here, in colorectal cancer, the authors show that multiclonal invasion of the muscularis mucosae is pervasive, suggesting that invasive capacity is not a significant bottleneck in the evolution of the disease.

SUMMARYDuctal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes by analyzing 677 DCIS samples from 481 patients with 7.1 years median follow-up from the Translational Breast Cancer Research Consortium (TBCRC) 038 study and the Resource of Archival Breast Tissue (RAHBT) cohorts. We identified 812 genes associated with ipsilateral recurrence within 5 years from treatment and developed a classifier that was predictive of 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 were 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.HIGHLIGHTS⍰ Development of a new classifier for DCIS recurrence or progression⍰ Outcome associated pathways identified across multiple data types and compartments⍰ Four stroma-specific signatures identified⍰ CNAs characterize DCIS subgroups associated with high risk invasive cancers

Most tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however, it is difficult to accurately sequence DNA from FFPE samples. We developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants (SNVs) from whole exome sequencing using small amounts of DNA extracted from archival FFPE samples of breast cancers. We optimized this strategy using 28 pairs of technical replicates. After optimization, the mean similarity between replicates increased 5-fold, reaching 88% (range 0-100%), with a mean of 21.4 SNVs (range 1-68) per sample, representing a markedly superior performance to existing algorithms. We found that the SNV-identification accuracy declined when there was less than 40ng of DNA available and that insertion-deletion variant calls are less reliable than single base substitutions. As the first application of the new algorithm, we compared samples of ductal carcinoma in situ (DCIS) of the breast to their adjacent invasive ductal carcinoma (IDC) samples. We observed an increased number of mutations (paired-samples sign test, pKey PointsThe sequencing of reduced quantities of DNA extracted from FFPE samples leads to substantial sequencing errors that require correction in order to obtain accurate detection of somatic mutations.We developed and validated a new bioinformatic algorithm to robustly identify somatic single nucleotide variants using small amounts of DNA extracted from archival FFPE samples of breast cancers.Variant calling software packages need to be optimized to reduce the impact of sequencing errors. Our bioinformatics pipeline represents a significant methodological advance compared to the currently available bioinformatic tools used for the analysis of small FFPE samples.

Background: Heterogeneity is a hallmark of human cancers that is apparent both between and within individual tumors. Intra-tumor heterogeneity provides the genetic fuel for natural selection in clonal evolution and cancer progression. Tumors with high levels of genetic heterogeneity are hypothesized to be more likely to progress to invasion and metastasis Methods: We measured the mutational loads from separate areas of pure DCIS and compared this to genetic heterogeneity in DCIS lesions that co-exist with invasive cancer, as a surrogate for progression. Cases of pure DCIS and DCIS diagnosed concurrent with invasive cancer were identified. Two areas of DCIS from each case a minimum of 0.8 cm apart and control tissues were macro-dissected and the DNA extracted from FFPE samples. To analyze the data, we developed new bioinformatics methods that allowed analysis of small amounts of degraded DNA extracted from FFPE samples across multiple regions. Our bioinformatics pipeline was optimized on a series of 28 independent technical replicates of the same DNA sample sequenced twice, as training tools to find the best filtering parameters. Results: Whole exome sequencing was performed on two geospatially separated blocks for each case (41 pure DCIS and 30 DCIS adjacent to invasive disease). Minimum coverage for inclusion in this study was 40X over at least 50% of the exome. We used the ratio of private mutations (only in 1 area) to public (found in both areas) mutations as a measure of intra-tumor heterogeneity. Overall mutational load of DCIS was not a significant predictor to progression; however notably, DCIS adjacent to invasive disease patients had a higher ratio of private/public mutations (heterogeneity) in coding domains (Mann-Whitney p=0.016. Functional analysis of mutated coding genes (DAVID 6.8) shows a statistically significant enrichment in signal transduction, olfactory receptors (G-protein-coupled receptors) and cell-matrix interactions in both tumor types, after FDR correction. DCIS adjacent to invasive disease had an enrichment of mutated genes involved in additional cellular functions such as microtubule activity (fold enrichment =7.6, FDR=0.002), protein-protein interactions (fold enrichment =3.65, FDR=5.11E-04) and extracellular matrix remodeling (fold enrichment =8.3, FDR=0.02). Conclusion: We present an approach to measure clonal heterogeneity using a bulk sequencing strategy applied to geospatially distinct foci of DCIS. Our findings suggest that functional heterogeneity may play an important evolutionary role as a driver for invasive progression. Citation Format: Fortunato A, Mallo D, King L, Hardman T, Hall A, Marks JR, Hwang S, Maley CC. Genetic heterogeneity of DCIS is a predictor of invasive cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-06-12.

Pure ductal carcinoma in situ (DCIS) is being diagnosed more frequently through breast screening programmes and is associated with an increased risk of developing invasive breast cancer. We assessed the clonal relatedness of 143 cases of pure DCIS and their subsequent events using a combination of whole exome, targeted and copy number sequencing, supplemented by single cell analysis. Unexpectedly, 18% of all invasive events after DCIS were clonally unrelated to the primary DCIS. Single cell sequencing of selected pairs confirmed our findings. In contrast, synchronous DCIS and invasive disease (n=44) were almost always (93%) clonally related. This challenges the dogma that almost all invasive events after DCIS represent invasive transformation of the initial DCIS and suggests that DCIS could be an independent risk factor for developing invasive disease as well as a precursor lesion. Our findings support a paradigm shift that confirms a more complex role for DCIS than previously recognized, and that the future management of DCIS should take into account both the precursor and risk factor implications of this diagnosis.

Ductal carcinoma in situ (DCIS) is the most commonly diagnosed precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes to identify predictors of subsequent ipsilateral breast events. We analyzed 677 DCIS samples from 481 patients with 7.1 years median follow-up from two independent cohorts. We made observations on DNA, RNA, and protein expression, and generated a de novo clustering scheme for DCIS that represents the fundamental transcriptomic organization at this early stage of breast neoplasia. Distinct DCIS stromal expression patterns and immune cell compositions were identified. We also found RNA expression patterns that correlate with later events in both cohorts. 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.

PURPOSE Primary endocrine therapy for ductal carcinoma in situ (DCIS) as a potential alternative to surgery has been understudied. This trial explored the feasibility of a short-term course of letrozole and sought to determine whether treatment results in measurable radiographic and biologic changes in estrogen receptor (ER)–positive DCIS. PATIENTS AND METHODS A phase II single-arm multicenter cooperative-group trial was conducted in postmenopausal patients diagnosed with ER-positive DCIS without invasion. Patients were treated with letrozole 2.5 mg per day for 6 months before surgery. Breast magnetic resonance imaging (MRI) was obtained at baseline, 3 months, and 6 months. The primary end point was change in 6-month MRI enhancement volume compared with baseline. RESULTS Overall, 79 patients were enrolled and 70 completed 6 months of letrozole. Of these, 67 patients had MRI data available for each timepoint. Baseline MRI volumes ranged from 0.004 to 26.3 cm3. Median reductions from baseline MRI volume (1.4 cm3) were 0.6 cm3 (61.0%) at 3 months ( P < .001) and 0.8 cm3 (71.7%) at 6 months ( P < .001). Consistent reductions were seen in median baseline ER H-score (228; median reduction, 15.0; P = .005), progesterone receptor H-score (15; median reduction, 85.0; P < .001), and Ki67 score (12%; median reduction, 6.3%; P = .007). Of the 59 patients who underwent surgery per study protocol, persistent DCIS remained in 50 patients (85%), invasive cancer was detected in six patients (10%), and no residual DCIS or invasive cancer was seen in nine patients (15%). CONCLUSIONS In a cohort of postmenopausal women with ER-positive DCIS, preoperative letrozole resulted in significant imaging and biomarker changes. These findings support future trials of extended endocrine therapy as primary nonoperative treatment of some DCIS.

Intra-tumoral heterogeneity (ITH) could represent clonal evolution where subclones with greater fitness confer more malignant phenotypes and invasion constitutes an evolutionary bottleneck. Alternatively, ITH could represent branching evolution with invasion of multiple subclones. The two models respectively predict a hierarchy of subclones arranged by phenotype, or multiple subclones with shared phenotypes. We delineated these modes of invasion by merging ancestral, topographic, and phenotypic information from 12 human colorectal tumors (11 carcinomas, 1 adenoma) obtained through saturation microdissection of 325 small tumor regions. The majority of subclones (29/46, 60%) shared superficial and invasive phenotypes. Of 11 carcinomas, 9 showed evidence of multiclonal invasion, and invasive and metastatic subclones arose early along the ancestral trees. Early multiclonal invasion in the majority of these tumors indicates the expansion of co-evolving subclones with similar malignant potential in absence of late bottlenecks, and suggests that barriers to invasion are minimal during colorectal cancer growth.

Canine immunocastration development has been of interest for many years as a complementary strategy to surgical castration. The purpose of this paper was to verify the effect of a recombinant vaccine for dog immunocastration. Two tests were done, one under controlled conditions and a second under field conditions. Animals were injected with 1 mL of 500 &micro, g GnRXG/Q recombinant protein, 500 &micro, g of low molecular weight chitosan as adjuvant, 1 mL NaCl 0.9% q.s. In the first trial, eight Beagle male dogs between the ages of 1 and 3 comprised the sample, randomly divided into two groups: vaccinated group (n = 7) and control group (n = 2). The second trial had 32 dogs with owners. In the first controlled conditions trial, the vaccine produced specific antibodies that remained until the end of the trial (day 270), inducing reduced testosterone and spermiogram changes in the immunized animals. In a second trial, on the field, specific immunity was induced, which remained high up to day 150. The vaccine also reduced sexual agonistic and marking behaviors. This new vaccine proved to be safe, immunogenic, capable of reducing gonadal functionality, and had a positive effect on inducing reduced sexual, agonistic, and marking behavior of the animals.

Introduction. The natural history of preinvasive breast cancer, or ductal carcinoma in situ (DCIS) remains poorly understood. Overcoming this gap would allow risk-appropriate treatment for patients diagnosed with DCIS. We used a multiregional sequencing approach in combination with mathematical modeling to characterize the evolutionary dynamics of DCIS initiation and progression. Methods. We analyzed a cohort of 18 patients diagnosed with DCIS, either with (n=9) or without (n=9) synchronous invasive cancer. Based on whole exome sequencing, tumor-specific mutation panels were constructed, each targeting 29-75 mutations (median: 60). From each tumor, and using selective ultraviolet radiation fractionation (SURF), we microdissected small spots (encompassing 1-3 duct cross-sections) from 3-4 spatially separated microscope sections (mean slide separation: 1.25cm, range: 0.34-6.0cm). Spots were spatially registered and genotyped based on targeted sequencing of the tumor-specific mutation panels. For each tumor, we performed unsupervised clonal deconvolution of the spot genotypes (CloneFinder) and constructed phylogenetic subclone trees. To quantify the spatial patterns of subclonal mutations, we introduced a dispersion index (DI), ranging from low (DI=0%) to high (DI=100%). To provide a spatio-temporal context for the heterogeneity patterns we developed a family of stochastic mathematical models of DCIS initiation and progression. Thereby, we embedded the evolutionary dynamics of tumor cell expansion in the branching topology of mammary ductal trees. Results. A total of 485 microdissected spots (median per tumor: 23, range: 10-50) were spatially registered and sequenced (median depth: 9,000x). All tumors were multiclonal, containing a median of 5 subclones (range: 2-14). Surprisingly, the correlation between spatial and genomic distances of spots was low. Individual subclones were diffusely dispersed across tumors. DCIS with synchronous DCIS and invasive cancer (mixed DCIS) had a higher mutation dispersion (DI=84.7%) than those without (pure DCIS, DI=70.5%; p=0.03, Wilcoxon rank-sum test). Mixed DCIS also had a higher fraction of spots containing more than one subclone than pure DCIS (median: 30.4% vs 0%, p=0.03). Among 7 mixed DCIS with invasive spots, 5 showed evidence of multiclonal invasion, that is more than one invading subclones were found in both in situ and invasive regions of the tumor. Mathematical modeling analyses show that the observed spatial patterns of genetic heterogeneity are consistent with a single expansion of mixing subclones across the ductal tree architecture. Conclusions. Our findings provide novel insights into the early growth and invasion dynamics of DCIS lesions. Further, we identified potential evolutionary markers for the delineation between indolent (pure) and aggressive (mixed) DCIS. This constitutes an important step towards identification of patients with low-risk DCIS who could be appropriately managed with less aggressive treatment. Citation Format: Marc D. Ryser, Inmaculada C. Sorribes, Matthew Greenwald, Ethan Wu, Allison Hall, Diego Mallo, Lorraine M. King, Timothy Hardman, Lunden Simpson, Carlo C. Maley, Jeffrey R. Marks, Darryl Shibata, E. Shelley Hwang. Inferring the evolutionary dynamics of ductal carcinoma in situ through multi-regional sequencing and mathematical modeling [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PR02.

Genetic diversity both between and within individual tumors constitutes a challenge to personalized cancer medicine. Intra-tumor heterogeneity provides the genetic fuel for natural selection in clonal evolution and cancer progression. Tumors with high levels of genetic heterogeneity are hypothesized to be more likely to demonstrate aggressive behavior and progress to invasion and metastasis. We analyzed the mutational loads from separate areas of pure DCIS and compared this to genetic heterogeneity in DCIS lesions found adjacent to invasive and metastatic cancer. Two spatially distinct areas of DCIS from each case were macro-dissected and the DNA extracted from FFPE samples. To analyze the data, we developed new bioinformatics methods that allowed analysis of small amounts of degraded DNA extracted from FFPE samples across multiple regions. Our bioinformatics pipeline was optimized on a series of 28 independent technical replicates of the same DNA sample sequenced twice, as training tools to find the best filtering parameters. Whole exome sequencing was performed on each of the two geospatially separated samples for each case. Minimum coverage for inclusion in this study was 40X over at least 50% of the exome. We used the ratio of private mutations (only in 1 area) to public (found in both areas) mutations as a measure of intra-tumor heterogeneity. We present an approach to measure clonal heterogeneity using a bulk sequencing strategy applied to geospatially distinct foci of DCIS. We found statistically significant difference between DCIS adjacent to invasive disease and metastatic patients' genetic divergence (t-test, p=0.013). Our findings suggest that genetic and functional heterogeneity may play an important evolutionary role as a driver for invasive progression. Citation Format: Angelo Fortunato, Diego Mallo, Lorraine King, Timothy Hardman, Allison Hall, Jeffrey R. Marks, Shelley Shelley Hwang, Carlo C. Maley. Genetic and functional heterogeneity of DCIS as predictors of invasive cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2502.

Introduction. Ductal carcinoma in situ (DCIS) of the breast has a limited propensity to progress to invasive breast cancer. However, due to a lack of markers that predict the risk of progression to invasive cancer, many DCIS patients may receive unnecessary surgery. Here, we explore whether the multiclonal intratumoral heterogeneity commonly observed in invasive breast cancers is also present in the precursor DCIS, and whether it differs between pure DCIS (without concurrent invasion) and mixed DCIS (with concurrent invasion). Methods. A total of 19 tumors (10 pure, 9 mixed) were analyzed. Based on whole exome sequencing, tumor-specific mutation panels were identified and contained a median of 60 point mutations per tumor (range: 35-80). From each tumor, 3-4 histologic sections were obtained, with a mean distance between slides of 1.26cm (range: 0.34-6.0cm). Individual DCIS ducts were microdissected from the sections using selective ultraviolet radiation fractionation (SURF); median number of ducts per tumor was 23 (range: 10-50). For each duct, the tumor specific mutation panel was assayed using targeted deep sequencing (median depth: 9,000x). Clonal deconvolution within each tumor was performed using the software package CloneFinder. Individual glands were classified as multiclonal if they contained 2 or more tumor subclones. In addition, the following evolutionary measures were computed for each tumor: (i) clone diversity as the mean pairwise Hamming distance between all ducts; (ii) clonal mixing as the number of clones that were present in more than one section. Comparisons between pure and mixed cases were performed using a two-sided Wilcoxon rank sum test. Results. All DCIS lesions were multiclonal. The number of subclones per tumor ranged from 2 to 9 overall, with a median of 5 and 6 subclones in pure and mixed DCIS, respectively (p-value for difference=.1). The median fraction of multiclonal glands per tumor was higher in mixed vs. pure DCIS (10% vs. 0%; p=.03). Median subclone diversity was higher in mixed vs. pure DCIS (1.48 vs. 1.04; p=.03), and the fraction of mixing subclones trended higher in mixed DCIS (median: 63%, range: 38-100%) compared to pure DCIS (median: 37%, range: 0-80%; p=.1). Subclones were spatially extensive: 18/19 tumors had at least one subclone that spanned across the analyzed sections, covering a mean distance of 2.5cm. Conclusions. All analyzed DCIS cases were multiclonal and individual subclones were found to span large regions of the tumor. Despite small sample sizes we found differences between pure and mixed DCIS. In particular, mixed DCIS harbored a higher fraction of multiclonal glands and a higher subclone diversity between individual ducts. Our findings characterize the evolutionary dynamics of breast cancer initiation and may provide evolutionary markers that distinguish indolent (pure) and progressive (mixed) disease. As such, this line of work has the potential to risk-stratify DCIS lesions. Citation Format: Marc D. Ryser, Inmaculada C. Sorribes, Matthew Greenwald, Allison Hall, Diego Mallo, Lorraine M. King, Timothy Hardman, Lunden Simpson, Carlo C. Maley, Jeffrey R. Marks, Darryl Shibata, E. Shelley Hwang. Ductal carcinoma in situ is a multiclonal disease [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2683.