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

Exploring the tumor microenvironment of breast cancer to develop a prognostic model and predict immunotherapy responses

Breast cancer is the most prevalent malignancy in women and exhibits significant heterogeneity. The tumor microenvironment (TME) plays a critical role in tumorigenesis, progression, and response to therapy. However, its impact on the prognosis and immunotherapy responses is incompletely understood. Using public databases, we conducted a comprehensive investigation of transcriptome and single-cell sequencing data. After performing immune infiltration analysis, we conducted consensus clustering, weighted gene co-expression network analysis (WGCNA), Cox regression, and least absolute shrinkage and selection operator (Lasso) regression to identify independent prognostic genes in breast cancer. Subsequently, we developed a prognostic model for patients with breast cancer. Tumor Immune Dysfunction and Exclusion (TIDE) values were used to assess patient's responsiveness to breast cancer. Based on single-cell RNA-sequencing data, we identified various cell types through cluster analysis and investigated the expression of prognostic model genes in each cell type. The drug sensitivity of targeted therapeutic agents for breast cancer treatment was analyzed in different cell types. We identified 12 independent prognostic genes associated with breast cancer and used these genes to construct a prognostic model. The prognostic model accurately discriminated between patients classified as high- and low-risk, providing precise prognostic predictions for individual patients. Additionally, our model exhibited a robust capacity to predict the immunotherapeutic response in breast cancer patients. Our investigation revealed a notable association between the proportion of endothelial cells (ECs) and patient prognosis in breast cancer. A prognostic model for breast cancer was formulated that showed close associations between prognosis and response to immunotherapy. For patients predicted by our model to not respond effectively to immunotherapeutic agents, it may be considered to combine immunotherapeutic agents with targeted therapeutic agents identified through our drug sensitivity analysis, which could potentially enhance treatment efficacy.

Multimodal data integration in early-stage breast cancer

The use of biomarkers in breast cancer has significantly improved patient outcomes through targeted therapies, such as hormone therapy anti-Her2 therapy and CDK4/6 or PARP inhibitors. However, existing knowledge does not fully encompass the diverse nature of breast cancer, particularly in triple-negative tumors. The integration of multi-omics and multimodal data has the potential to provide new insights into biological processes, to improve breast cancer patient stratification, enhance prognosis and response prediction, and identify new biomarkers. This review presents a comprehensive overview of the state-of-the-art multimodal (including molecular and image) data integration algorithms developed and with applicability to breast cancer stratification, prognosis, or biomarker identification. We examined the primary challenges and opportunities of these multimodal data integration algorithms, including their advantages, limitations, and critical considerations for future research. We aimed to describe models that are not only academically and preclinically relevant, but also applicable to clinical settings.

Evolutionary measures show that recurrence of DCIS is distinct from progression to breast cancer

BACKGROUND

Progression from pre-cancers like ductal carcinoma in situ (DCIS) to invasive disease (cancer) is driven by somatic evolution and is altered by clinical interventions. We hypothesized that genetic and/or phenotypic intra-tumor heterogeneity would predict clinical outcomes for DCIS since it serves as the substrate for natural selection among cells.

METHODS

We profiled two samples from two geographically distinct foci from each DCIS in both cross-sectional (n = 119) and longitudinal cohorts (n = 224), with whole exome sequencing, low-pass whole genome sequencing, and a panel of immunohistochemical markers.

RESULTS

In the longitudinal cohorts, the only statistically significant associations with time to non-invasive DCIS recurrence were the combination of treatment (lumpectomy only vs mastectomy or lumpectomy with radiation, HR 12.13, p = 0.003, Wald test with FDR correction), ER status (HR 0.16 for ER+ compared to ER-, p = 0.0045), and divergence in SNVs between the two samples (HR 1.33 per 10% divergence, p = 0.018). SNV divergence also distinguished between pure DCIS and DCIS synchronous with invasive disease in the cross-sectional cohort. In contrast, the only statistically significant associations with time to progression to invasive disease were the combination of the width of the surgical margin (HR 0.67 per mm, p = 0.043) and the number of mutations that were detectable at high allele frequencies (HR 1.30 per 10 SNVs, p = 0.02). No predictors were significantly associated with both DCIS recurrence and progression to invasive disease, suggesting that the evolutionary scenarios that lead to these clinical outcomes are markedly different.

CONCLUSIONS

These results imply that recurrence with DCIS is a clinical and biological process different from invasive progression.

B cells and energy metabolism in HER2-positive DCIS: insights into breast cancer progression from spatial-omics analyses

During breast tumor progression, the transition from ductal carcinoma in situ (DCIS) to invasive breast cancer is a critical step with large implications for prognosis. However, the mechanisms of invasion are still largely unknown. At the DCIS stage, there is an over-representation of HER2-positive lesions compared with invasive breast cancer. In this study, we investigated the associations between gene expression profiles in cancer cells and the immune microenvironment of HER2-positive DCIS and invasive breast tumors with concurrent DCIS using spatial transcriptomics. We found distinctly more B cells in the vicinity of DCIS ducts than in invasive tumor areas. There was higher expression of genes involved in energy metabolism in DCIS cancer cells than in invasive cancer cells and a positive correlation between expression of metabolic genes and B-cell abundance in DCIS. In contrast were processes related to epithelial to mesenchymal transition negatively correlated with B-cell abundance in DCIS. We also found significant correlation between expression of the B-cell-attracting chemokines CCL19, CCL21 and CXCL13 in stromal cells and B cell abundance in DCIS. This study indicates that B cells may play a protective role in the progression of HER2-positive DCIS to invasive breast cancer and that increased metabolic activity in intraductal cancer cells in combination with chemokines produced by stromal cells may influence the immune microenvironment of DCIS. These findings have implications for understanding HER2-positive breast cancer progression.

PCSK5M452I is a recessive hypomorph exclusive to MCF10DCIS.com cells

The most widely used cell line for studying ductal carcinoma in situ (DCIS) premalignancy is the transformed breast epithelial cell line, MCF10DCIS.com. During its original clonal isolation and selection, MCF10DCIS.com acquired a heterozygous M452I mutation in the proprotein convertase PCSK5, which has never been reported in any human cancer. The mutation is noteworthy because PCSK5 matures GDF11, a TGFβ-superfamily ligand that suppresses progression of triple-negative breast cancer. We asked here whether PCSK5M452I and its activity toward GDF11 might contribute to the unique properties of MCF10DCIS.com. Using an optimized in-cell GDF11 maturation assay, we found that overexpressed PCSK5M452I was measurably active but at a fraction of the wildtype enzyme. In a PCSK5 -/- clone of MCF10DCIS.com reconstituted with different PCSK5 alleles, PCSK5M452I was mildly defective in anterograde transport. However, the multicellular organization of PCSK5M452I addback cells in 3D matrigel cultures was significantly less compact than wildtype and indistinguishable from a PCSK5T288P null allele. Growth of intraductal MCF10DCIS.com xenografts was similarly impaired along with the frequency of comedo necrosis and stromal activation. In no setting did PCSK5M452I exhibit gain-of-function activity, leading us to conclude that it is hypomorphic and thus compensated by the remaining wildtype allele in MCF10DCIS.com.

Implications

This work reassures that an exotic PCSK5 mutation is not responsible for the salient characteristics of the MCF10DCIS.com cell line.

Eco-evolutionary Guided Pathomics Analysis to Predict DCIS Upstaging

Cancers evolve in a dynamic ecosystem. Thus, characterizing cancer's ecological dynamics is crucial to understanding cancer evolution and can lead to discovering novel biomarkers to predict disease progression. Ductal carcinoma in situ (DCIS) is an early-stage breast cancer characterized by abnormal epithelial cell growth confined within the milk ducts. In this study, we show that ecological analysis of hypoxia and acidosis biomarkers can significantly improve prediction of DCIS upstaging. First, we developed a novel eco-evolutionary designed approach to define habitats in the tumor intraductal microenvironment based on oxygen diffusion distance. Then, we identified cancer cells with metabolic phenotypes attributed to their habitats, including CA9 for hypoxia responding phenotype, and LAMP2b for acid adapted phenotype. Traditionally these markers have shown limited predictive capabilities for DCIS progression, if any. However, when analyzed from an ecological perspective, their power to differentiate between non-upstaged and upstaged DCIS increased significantly. Second, we discovered distinct niches with spatial patterns of these biomarkers and used the distribution of such niches to predict patient upstaging. The niches were characterized by pattern analysis of both cellular and spatial features. With a 5-fold validation on the biopsy cohort, we trained a random forest classifier to achieve the area under curve (AUC) of 0.74. Our results affirm the importance of tumor ecological features in eco-evolutionary-designed approaches for novel biomarkers discovery.

Vaccines for cancer prevention: exploring opportunities and navigating challenges

Improved understanding of cancer immunology has gradually brought increasing attention towards cancer-preventive vaccines as an important tool in the fight against cancer. The aim of this approach is to reduce cancer occurrence by inducing a specific immune response targeting tumours at an early stage before they can fully develop. The great advantage of preventive cancer vaccines lies in the potential to harness a less-compromised immune system in vaccine recipients before their immune responses become affected by the advanced status of the disease itself or by aggressive treatments such as chemotherapy. Successful implementation of immunoprevention against oncogenic viruses such as hepatitis B and papillomavirus has led to a dramatic decrease in virally induced cancers. Extending this approach to other cancers holds great promise but remains a major challenge. Here, we provide a comprehensive review of preclinical evidence supporting this approach, encouraging results from pioneering clinical studies as well as a discussion on the key aspects and open questions to address in order to design potent prophylactic cancer vaccines in the near future.

Complex rearrangements fuel ER+ and HER2+ breast tumours

Breast cancer is a highly heterogeneous disease whose prognosis and treatment as defined by the expression of three receptors-oestrogen receptor (ER), progesterone receptor and human epidermal growth factor receptor 2 (HER2; encoded by ERBB2)-is insufficient to capture the full spectrum of clinical outcomes and therapeutic vulnerabilities. Previously, we demonstrated that transcriptional and genomic profiles define eleven integrative subtypes with distinct clinical outcomes, including four ER+ subtypes with increased risk of relapse decades after diagnosis1,2. Here, to determine whether these subtypes reflect distinct evolutionary histories, interactions with the immune system and pathway dependencies, we established a meta-cohort of 1,828 breast tumours spanning pre-invasive, primary invasive and metastatic disease with whole-genome and transcriptome sequencing. We demonstrate that breast tumours fall along a continuum constrained by three genomic archetypes. The ER+ high-risk integrative subgroup is characterized by complex focal amplifications, similar to HER2+ tumours, including cyclic extrachromosomal DNA amplifications induced by ER through R-loop formation and APOBEC3B-editing, which arise in pre-invasive lesions. By contrast, triple-negative tumours exhibit genome-wide instability and tandem duplications and are enriched for homologous repair deficiency-like signatures, whereas ER+ typical-risk tumours are largely genomically stable. These genomic archetypes, which replicate in an independent cohort of 2,659 primary tumours, are established early during tumorigenesis, sculpt the tumour microenvironment and are conserved in metastatic disease. These complex structural alterations contribute to replication stress and immune evasion, and persist throughout tumour evolution, unveiling potential vulnerabilities.

A morphometric signature to identify ductal carcinoma in situ with a low risk of progression

Ductal carcinoma in situ (DCIS) may progress to ipsilateral invasive breast cancer (iIBC), but often never will. Because DCIS is treated as early breast cancer, many women with harmless DCIS face overtreatment. To identify features associated with progression, we developed an artificial intelligence-based DCIS morphometric analysis pipeline (AIDmap) on hematoxylin-eosin-stained (H&E) tissue sections. We analyzed 689 digitized H&Es of pure primary DCIS of which 226 were diagnosed with subsequent iIBC and 463 were not. The distribution of 15 duct morphological measurements was summarized in 55 morphometric variables. A ridge regression classifier with cross validation predicted 5-years-free of iIBC with an area-under the curve of 0.67 (95% CI 0.57-0.77). A combined clinical-morphometric signature, characterized by small-sized ducts, a low number of cells and a low DCIS/stroma ratio, was associated with outcome (HR = 0.56; 95% CI 0.28-0.78). AIDmap has potential to identify harmless DCIS that may not need treatment.

From ductal carcinoma in situ to invasive breast cancer: the prognostic value of the extracellular microenvironment

Ductal carcinoma in situ (DCIS) is a noninvasive breast disease that variably progresses to invasive breast cancer (IBC). Given the unpredictability of this progression, most DCIS patients are aggressively managed similar to IBC patients. Undoubtedly, this treatment paradigm places many DCIS patients at risk of overtreatment and its significant consequences. Historically, prognostic modeling has included the assessment of clinicopathological features and genomic markers. Although these provide valuable insights into tumor biology, they remain insufficient to predict which DCIS patients will progress to IBC. Contemporary work has begun to focus on the microenvironment surrounding the ductal cells for molecular patterns that might predict progression. In this review, extracellular microenvironment alterations occurring with the malignant transformation from DCIS to IBC are detailed. Not only do changes in collagen abundance, organization, and localization mediate the transition to IBC, but also the discrete post-translational regulation of collagen fibers is understood to promote invasion. Other extracellular matrix proteins, such as matrix metalloproteases, decorin, and tenascin C, have been characterized for their role in invasive transformation and further demonstrate the prognostic value of the extracellular matrix. Importantly, these extracellular matrix proteins influence immune cells and fibroblasts toward pro-tumorigenic phenotypes. Thus, the progressive changes in the extracellular microenvironment play a key role in invasion and provide promise for prognostic development.

Development and Validation of Dynamic 5-Year Breast Cancer Risk Model Using Repeated Mammograms

PURPOSE

Current image-based long-term risk prediction models do not fully use previous screening mammogram images. Dynamic prediction models have not been investigated for use in routine care.

METHODS

We analyzed a prospective WashU clinic-based cohort of 10,099 cancer-free women at entry (between November 3, 2008 and February 2012). Follow-up through 2020 identified 478 pathology-confirmed breast cancers (BCs). The cohort included 27% Black women. An external validation cohort (Emory) included 18,360 women screened from 2013, followed through 2020. This included 42% Black women and 332 pathology-confirmed BC excluding those diagnosed within 6 months of screening. We trained a dynamic model using repeated screening mammograms at WashU to predict 5-year risk. This opportunistic screening service presented a range of mammogram images for each woman. We applied the model to the external validation data to evaluate discrimination performance (AUC) and calibrated to US SEER.

RESULTS

Using 3 years of previous mammogram images available at the current screening visit, we obtained a 5-year AUC of 0.80 (95% CI, 0.78 to 0.83) in the external validation. This represents a significant improvement over the current visit mammogram AUC 0.74 (95% CI, 0.71 to 0.77; P < .01) in the same women. When calibrated, a risk ratio of 21.1 was observed comparing high (>4%) to very low (<0.3%) 5-year risk. The dynamic model classified 16% of the cohort as high risk among whom 61% of all BCs were diagnosed. The dynamic model performed comparably in Black and White women.

CONCLUSION

Adding previous screening mammogram images improves 5-year BC risk prediction beyond static models. It can identify women at high risk who might benefit from supplemental screening or risk-reduction strategies.

Defining precancer: a grand challenge for the cancer community

The term 'precancer' typically refers to an early stage of neoplastic development that is distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting in abnormal cells that are at least partially self-sustaining and function outside of normal cellular cues that constrain cell proliferation and survival. Although such cells are often histologically distinct from both the corresponding normal and invasive cancer cells of the same tissue origin, defining precancer remains a challenge for both the research and clinical communities. Once sufficient molecular and phenotypic changes have occurred in the precancer, the tissue is identified as a 'cancer' by a histopathologist. While even diagnosing cancer can at times be challenging, the determination of invasive cancer is generally less ambiguous and suggests a high likelihood of and potential for metastatic disease. The 'hallmarks of cancer' set out the fundamental organizing principles of malignant transformation but exactly how many of these hallmarks and in what configuration they define precancer has not been clearly and consistently determined. In this Expert Recommendation, we provide a starting point for a conceptual framework for defining precancer, which is based on molecular, pathological, clinical and epidemiological criteria, with the goal of advancing our understanding of the initial changes that occur and opportunities to intervene at the earliest possible time point.

Analysis of ductal carcinoma in situ by self-reported race reveals molecular differences related to outcome

BACKGROUND

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated.

METHODS

We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n = 99) and White (n = 191) women in a large DCIS case-control cohort study with longitudinal follow up.

RESULTS

Gene expression and pathway analyses suggested that different genes and pathways are involved in diagnosis and ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups.

CONCLUSIONS

Our results suggest that different molecular mechanisms drive initiation and subsequent ipsilateral breast events in Black versus White women.

Systematic assessment of HER2 status in ductal carcinoma in situ of the breast: a perspective on the potential clinical relevance

In many countries, hormone receptor status assessment of ductal carcinoma in situ (DCIS) is routinely performed, as hormone receptor-positive DCIS patients are eligible for adjuvant anti-hormonal treatment, aiming to reduce the ipsilateral and contralateral breast cancer risk. Although HER2 gene amplification and its associated HER2 protein overexpression constitute a major prognostic and predictive marker in invasive breast carcinoma, its use in the diagnosis and treatment of DCIS is less straightforward. HER2 immunohistochemistry is not routinely performed yet, as the role of HER2-positivity in DCIS biology is unclear. Nonetheless, recent data challenge this practice. Here, we discuss the value of routine HER2 assessment for DCIS. HER2-positivity correlates strongly with DCIS grade: around four in five HER2-positive DCIS show high grade atypia. As morphological DCIS grading is prone to interobserver variability, HER2 immunohistochemistry could render grading more robust. Several studies showed an association between HER2-positive DCIS and ipsilateral recurrence risk, albeit currently unclear whether this is for overall, in situ or invasive recurrence. HER2-positive DCIS tends to be larger, with a higher risk of involved surgical margins. HER2-positive DCIS patients benefit more from adjuvant radiotherapy: it substantially decreases the local recurrence risk after lumpectomy, without impact on overall survival. HER2-positivity in pure biopsy-diagnosed DCIS is associated with increased upstaging to invasive carcinoma after surgery. HER2 immunohistochemistry on preoperative biopsies might therefore provide useful information to surgeons, favoring wider excisions. The time seems right to consider DCIS subtype-dependent treatment, comprising appropriate local treatment for HER2-positive DCIS patients and de-escalation for hormone receptor-positive, HER2-negative DCIS patients.

Evolutionary Measures Show that Recurrence of DCIS is Distinct from Progression to Breast Cancer

Progression from pre-cancers like ductal carcinoma in situ (DCIS) to invasive disease (cancer) is driven by somatic evolution and is altered by clinical interventions. We hypothesized that genetic and/or phenotypic intra-tumor heterogeneity would predict clinical outcomes for DCIS since it serves as the substrate for natural selection among cells. We profiled two samples from two geographically distinct foci from each DCIS in both cross-sectional (N = 119) and longitudinal cohorts (N = 224), with whole exome sequencing, low-pass whole genome sequencing, and a panel of immunohistochemical markers. In the longitudinal cohorts, the only statistically significant predictors of time to non-invasive DCIS recurrence were the combination of treatment (lumpectomy only vs mastectomy or lumpectomy with radiation, HR = 12.13, p = 0.003, Wald test with FDR correction), ER status (HR = 0.16 for ER+ compared to ER-, p = 0.0045), and divergence in SNVs between the two samples (HR = 1.33 per 10% divergence, p = 0.018). SNV divergence also distinguished between pure DCIS and DCIS synchronous with invasive disease in the cross-sectional cohort. In contrast, the only statistically significant predictors of time to progression to invasive disease were the combination of the width of the surgical margin (HR = 0.67 per mm, p = 0.043) and the number of mutations that were detectable at high allele frequencies (HR = 1.30 per 10 SNVs, p = 0.02). These results imply that recurrence with DCIS is a clinical and biological process different from invasive progression.

The SEMA3F-NRP1/NRP2 axis is a key factor in the acquisition of invasive traits in in situ breast ductal carcinoma

BACKGROUND

A better understanding of ductal carcinoma in situ (DCIS) is urgently needed to identify these preinvasive lesions as distinct clinical entities. Semaphorin 3F (SEMA3F) is a soluble axonal guidance molecule, and its coreceptors Neuropilin 1 (NRP1) and NRP2 are strongly expressed in invasive epithelial BC cells.

METHODS

We utilized two cell line models to represent the progression from a healthy state to the mild-aggressive or ductal carcinoma in situ (DCIS) stage and, ultimately, to invasive cell lines. Additionally, we employed in vivo models and conducted analyses on patient databases to ensure the translational relevance of our results.

RESULTS

We revealed SEMA3F as a promoter of invasion during the DCIS-to-invasive ductal carcinoma transition in breast cancer (BC) through the action of NRP1 and NRP2. In epithelial cells, SEMA3F activates epithelialmesenchymal transition, whereas it promotes extracellular matrix degradation and basal membrane and myoepithelial cell layer breakdown.

CONCLUSIONS

Together with our patient database data, these proof-of-concept results reveal new SEMA3F-mediated mechanisms occurring in the most common preinvasive BC lesion, DCIS, and represent potent and direct activation of its transition to invasion. Moreover, and of clinical and therapeutic relevance, the effects of SEMA3F can be blocked directly through its coreceptors, thus preventing invasion and keeping DCIS lesions in the preinvasive state.

How much do we know about the metastatic process?

Cancer cells can leave their primary sites and travel through the circulation to distant sites, where they lodge as disseminated cancer cells (DCCs), even during the early and asymptomatic stages of tumor progression. In experimental models and clinical samples, DCCs can be detected in a non-proliferative state, defined as cellular dormancy. This state can persist for extended periods until DCCs reawaken, usually in response to niche-derived reactivation signals. Therefore, their clinical detection in sites like lymph nodes and bone marrow is linked to poor survival. Current cancer therapy designs are based on the biology of the primary tumor and do not target the biology of the dormant DCC population and thus fail to eradicate the initial or subsequent waves of metastasis. In this brief review, we discuss the current methods for detecting DCCs and highlight new strategies that aim to target DCCs that constitute minimal residual disease to reduce or prevent metastasis formation. Furthermore, we present current evidence on the relevance of DCCs derived from early stages of tumor progression in metastatic disease and describe the animal models available for their study. We also discuss our current understanding of the dissemination mechanisms utilized by genetically less- and more-advanced cancer cells, which include the functional analysis of intermediate or hybrid states of epithelial-mesenchymal transition (EMT). Finally, we raise some intriguing questions regarding the clinical impact of studying the crosstalk between evolutionary waves of DCCs and the initiation of metastatic disease.

Towards targeting the breast cancer immune microenvironment

The tumour immune microenvironment is shaped by the crosstalk between cancer cells, immune cells, fibroblasts, endothelial cells and other stromal components. Although the immune tumour microenvironment (TME) serves as a source of therapeutic targets, it is also considered a friend or foe to tumour-directed therapies. This is readily illustrated by the importance of T cells in triple-negative breast cancer (TNBC), culminating in the advent of immune checkpoint therapy in combination with cytotoxic chemotherapy as standard of care for both early and advanced-stage TNBC, as well as recent promising signs of efficacy in a subset of hormone receptor-positive disease. In this Review, we discuss the various components of the immune TME in breast cancer and therapies that target or impact the immune TME, as well as the complexity of host physiology.

Biomarkers in Cancer Screening: Promises and Challenges in Cancer Early Detection

Cancer continues to be one the leading causes of death worldwide, primarily due to the late detection of the disease. Cancers detected at early stages may enable more effective intervention of the disease. However, most cancers lack well-established screening procedures except for cancers with an established early asymptomatic phase and clinically validated screening tests. There is a critical need to identify and develop assays/tools in conjunction with imaging approaches for precise screening and detection of the aggressive disease at an early stage. New developments in molecular cancer screening and early detection include germline testing, synthetic biomarkers, and liquid biopsy approaches.

Epigenetic activation of SOX11 is associated with recurrence and progression of ductal carcinoma in situ to invasive breast cancer

BACKGROUND

Risk of recurrence and progression of ductal carcinoma in situ (DCIS) to invasive cancer remains uncertain, emphasizing the need for developing predictive biomarkers of aggressive DCIS.

METHODS

Human cell lines and mouse models of disease progression were analyzed for candidate risk predictive biomarkers identified and validated in two independent DCIS cohorts.

RESULTS

RNA profiling of normal mammary and DCIS tissues (n = 48) revealed that elevated SOX11 expression correlates with MKI67, EZH2, and DCIS recurrence score. The 21T human cell line model of DCIS progression to invasive cancer and two mouse models developing mammary intraepithelial neoplasia confirmed the findings. AKT activation correlated with chromatin accessibility and EZH2 enrichment upregulating SOX11 expression. AKT and HER2 inhibitors decreased SOX11 expression along with diminished mammosphere formation. SOX11 was upregulated in HER2+ and basal-like subtypes (P < 0.001). Longitudinal DCIS cohort (n = 194) revealed shorter recurrence-free survival in SOX11+ than SOX11- patients (P = 0.0056 in all DCIS; P < 0.0001 in HER2+ subtype) associated with increased risk of ipsilateral breast event/IBE (HR = 1.9, 95%CI = 1.2-2.9; P = 0.003).

DISCUSSION

Epigenetic activation of SOX11 drives recurrence of DCIS and progression to invasive cancer, suggesting SOX11 as a predictive biomarker of IBE.

Ductal carcinoma in situ of the breast: finding the balance between overtreatment and undertreatment

Ductal carcinoma in situ (DCIS) accounts for 15-25% of all breast cancer diagnoses. Its prognosis is excellent overall, the main risk being the occurrence of local breast events, as most cases of DCIS do not progress to invasive cancer. Systematic screening has greatly increased the incidence of this non-obligate precursor of invasion, lending urgency to the need to identify DCIS that is prone to invasive progression and distinguish it from non-invasion-prone DCIS, as the latter can be overdiagnosed and therefore overtreated. Treatment strategies, including surgery, radiotherapy, and optional endocrine therapy, decrease the risk of local events, but have no effect on survival outcomes. Active surveillance is being evaluated as a possible new option for low-risk DCIS. Considerable efforts to decipher the biology of DCIS have led to a better understanding of the factors that determine its variable natural history. Given this variability, shared decision making regarding optimal, personalised treatment strategies is the most appropriate course of action. Well designed, risk-based de-escalation studies remain a major need in this field.

Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

Update on Management of Ductal Carcinoma in Situ

Ductal carcinoma in situ (DCIS) represents 18% to 25% of all diagnosed breast cancers, and is a noninvasive, nonobligate precursor lesion to invasive cancer. The diagnosis of DCIS represents a wide range of disease, including lesions with both low and high risk of progression to invasive cancer and recurrence. Over the past decade, research on the topic of DCIS has focused on the possibility of tailoring treatment for patients according to their risk for progression and recurrence, which is based on clinicopathologic, biomolecular and genetic factors. These efforts are ongoing, with recently completed and continuing clinical trials spanning the continuum of cancer care. We conducted a review to identify recent advances on the topic of diagnosis, risk stratification and management of DCIS. While novel imaging techniques have increased the rate of DCIS diagnosis, questions persist regarding the optimal management of lesions that would not be identified with conventional methods. Additionally, among trials investigating the potential for omission of surgery and use of active surveillance, 2 trials have completed accrual and 2 clinical trials are continuing to enroll patients. Identification of novel genetic patterns is expanding our potential for risk stratification and aiding our ability to de-escalate radiation and systemic therapies for DCIS. These advances provide hope for tailoring of DCIS treatment in the near future.

Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery

DNA variation analysis has become indispensable in many aspects of modern biomedicine, most prominently in the comparison of normal and tumor samples. Thousands of samples are collected in local sequencing efforts and public databases requiring highly scalable, portable, and automated workflows for streamlined processing. Here, we present nf-core/sarek 3, a well-established, comprehensive variant calling and annotation pipeline for germline and somatic samples. It is suitable for any genome with a known reference. We present a full rewrite of the original pipeline showing a significant reduction of storage requirements by using the CRAM format and runtime by increasing intra-sample parallelization. Both are leading to a 70% cost reduction in commercial clouds enabling users to do large-scale and cross-platform data analysis while keeping costs and CO2 emissions low. The code is available at https://nf-co.re/sarek.

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity

Tumors with the same diagnosis can have different molecular profiles and response to treatment. It remains unclear when and why these differences arise. Somatic genomic aberrations occur within the context of a highly variable germline genome. Interrogating 5870 breast cancer lesions, we demonstrated that germline-derived epitopes in recurrently amplified genes influence somatic evolution by mediating immunoediting. Individuals with a high germline-epitope burden in human epidermal growth factor receptor 2 (HER2/ERBB2) are less likely to develop HER2-positive breast cancer compared with other subtypes. The same holds true for recurrent amplicons defining three aggressive estrogen receptor (ER)-positive subgroups. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show that the germline genome plays a role in dictating somatic evolution.

Spatial Biology of Breast Cancer

Spatial findings have shaped on our understanding of breast cancer. In this review, we discuss how spatial methods, including spatial transcriptomics and proteomics and the resultant understanding of spatial relationships, have contributed to concepts regarding cancer progression and treatment. In addition to discussing traditional approaches, we examine how emerging multiplex imaging technologies have contributed to the field and how they might influence future research.

Deciphering the spatial landscape and plasticity of immunosuppressive fibroblasts in breast cancer

Although heterogeneity of FAP+ Cancer-Associated Fibroblasts (CAF) has been described in breast cancer, their plasticity and spatial distribution remain poorly understood. Here, we analyze trajectory inference, deconvolute spatial transcriptomics at single-cell level and perform functional assays to generate a high-resolution integrated map of breast cancer (BC), with a focus on inflammatory and myofibroblastic (iCAF/myCAF) FAP+ CAF clusters. We identify 10 spatially-organized FAP+ CAF-related cellular niches, called EcoCellTypes, which are differentially localized within tumors. Consistent with their spatial organization, cancer cells drive the transition of detoxification-associated iCAF (Detox-iCAF) towards immunosuppressive extracellular matrix (ECM)-producing myCAF (ECM-myCAF) via a DPP4- and YAP-dependent mechanism. In turn, ECM-myCAF polarize TREM2+ macrophages, regulatory NK and T cells to induce immunosuppressive EcoCellTypes, while Detox-iCAF are associated with FOLR2+ macrophages in an immuno-protective EcoCellType. FAP+ CAF subpopulations accumulate differently according to the invasive BC status and predict invasive recurrence of ductal carcinoma in situ (DCIS), which could help in identifying low-risk DCIS patients eligible for therapeutic de-escalation.

Advances and challenges in cancer immunoprevention and immune interception

Invasive cancers typically evade immune surveillance through profound local and systemic immunosuppression, preventing their elimination or control. Targeting immune interventions to prevent or intercept premalignant lesions, before significant immune dysregulation has occurred, may be a more successful strategy. The field of cancer immune interception and prevention is nascent, and the scientific community has been slow to embrace this potentially most rational approach to reducing the global burden of cancer. This may change due to recent promising advances in cancer immunoprevention including the use of vaccines for the prevention of viral cancers, the use of cancer-associated antigen vaccines in the setting of precancers, and the development of cancer-preventative vaccines for high-risk individuals who are healthy but carry cancer-associated heritable genetic mutations. Furthermore, there is increasing recognition of the importance of cancer prevention and interception by national cancer organizations. The National Cancer Institute (NCI) recently released the National Cancer Plan, which includes cancer prevention among the top priorities of the institute. The NCI's Division of Cancer Prevention has been introducing new funding opportunities for scientists with an interest in the field of cancer prevention: The Cancer Prevention-Interception Targeted Agent Discovery Program and The Cancer Immunoprevention Network. Moreover, the Human Tumor Atlas Network is spearheading the development of a precancer atlas to better understand the biology of pre-invasive changes, including the tissue microenvironment and the underlying genetics that drive carcinogenesis. These data will inform the development of novel immunoprevention/immuno-interception strategies. International cancer foundations have also started recognizing immunoprevention and immune interception with the American Association for Cancer Research, Cancer Research UK and the Society for Immunotherapy of Cancer each implementing programming focused on this area. This review will present recent advances, opportunities, and challenges in the emerging field of cancer immune prevention and immune interception.

Treg cells as a protective factor for Hashimoto`s thyroiditis: a Mendelian randomization study

Background and objectives

Hashimoto's thyroiditis (HT), a chronic autoimmune disorder impacting thyroid function, is a growing public health concern. The relationship between Treg cells and HT has been extensively studied, with Treg cells considered crucial in suppressing HT progression. However, these studies have mainly been observational, limiting our understanding of Treg cells' impact on HT risk. Leveraging large datasets, we utilized Mendelian randomization (MR) analysis to examine the causal association between Treg cell biomarkers and HT, providing additional validation for these relationships.

Methods

Comprehensive two-sample Mendelian randomization analysis was performed to determine the causal association between Treg cells signatures and HT in this study. Based on publicly available genetic data, we explored causal associations between 165 Treg cells signatures and HT risk.

Results

The European cohort study has identified five Treg cell phenotypes that causally protect against HT risk. Resting Treg %CD4 (OR = 0.975, 95% CI = 0.954~0.998, P = 0.030); CD4 on resting Treg (OR = 0.938, 95% CI = 0.882~0.997, P = 0.041; CD28- CD8dim %CD8dim (OR = 0.983, 95% CI = 0.969~0.998, P = 0.030); CD25 on CD39+ resting Treg (OR = 0.926, 95% CI = 0.864~0.991, P = 0.026); 5) CD28 on activated & secreting Treg (OR = 0.969, 95% CI = 0.942~0.996, P = 0.025). The Asian cohort study has identified four Treg cell phenotypes negatively correlated with the risk of HT. CD25hi %T cell (OR = 0.635, 95% CI = 0.473~852, P = 0.002); CD4 Treg %CD4 (OR = 0.829, 95% CI = 0.687~1.000, P = 0.050); CD127-CD8br %T cell (OR = 0.463, 95% CI =0.311~0.687, P< 0.001); CD3 on resting Treg (OR = 0.786, 95% CI = 0.621~0.994, P = 0.044).

Conclusion

Our study has demonstrated the close connection between Treg cells and HT by genetic means, thus providing foundational basis for future research.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Surgical De-Escalation for Re-Excision in Patients with a Margin Less Than 2 mm and a Diagnosis of DCIS

The current surgical guidelines recommend an optimal margin width of 2 mm for the management of patients diagnosed with ductal carcinoma in situ (DCIS). However, there are still many controversies regarding re-excision when the optimal margin criteria are not met in the first resection. The purpose of this study is to understand the importance of surgical margin width, re-excision, and treatments to avoid additional surgery on locoregional recurrence (LRR). The study is retrospective and analyzed surgical margins, adjuvant treatments, re-excision, and LRR in patients with DCIS who underwent breast-conserving surgery (BCS). A total of 197 patients were enrolled. Re-operation for a close margin rate was 13.5%, and the 3-year recurrence was 7.6%. No difference in the LRR was reported among the patients subjected to BCS regardless of the margin width (p = 0.295). The recurrence rate according to margin status was not significant (p = 0.484). Approximately 36.9% (n: 79) patients had resection margins < 2 mm. A sub-analysis of patients with margins < 2 mm showed no difference in the recurrence between the patients treated with a second surgery and those treated with radiation (p = 0.091). The recurrence rate according to margin status in patients with margins < 2 mm was not significant (p = 0.161). The margin was not a predictive factor of LRR p = 0.999. Surgical re-excision should be avoided in patients with a focally positive margin and no evidence of the disease at post-surgical imaging.

Employing a Risk Assessment Tool for Shared Decision-Making in Breast Cancer Screening

Background: The existing guidelines for breast cancer screening incorporate assessing individual risk but contain no universally recommended risk assessment tool in the primary care setting. Local Problem: A family planning program utilizing nurses and nurse practitioners for assessment, education, and referral lacked a risk assessment tool for assessing breast cancer risk. Methods: A breast cancer risk assessment tool was implemented in practice. Interventions: The interventions involved assessing the patient's risks, providing education on risk reduction strategies, and determining the need for clinical breast exams and referrals for mammography. Results: The study demonstrated a clear correlation between the number of breast cancer risks identified and the extent of education provided to patients based on their specific risk profiles (0 vs. 1.5 risks; 2 vs. 4.6 educational components). Among patients under age 35, 80% opted for a clinical breast exam, while 100% of patients age 40 and above agreed to both clinical breast exams and referrals for mammography after discussing individual risks. Conclusions: The use of a breast cancer risk assessment tool provided an evidence-based foundation for the shared decision-making conversation between patient and nurse/provider on risk reduction. The discussion included current evidence on the risk versus benefit of age-based screening options for breast cancer, allowing for an informed decision made jointly between the patient and provider.

Artificial intelligence-based morphometric signature to identify ductal carcinoma in situ with low risk of progression to invasive breast cancer

Ductal carcinoma in situ (DCIS) may progress to ipsilateral invasive breast cancer (iIBC), but often never will. Because DCIS is treated as early breast cancer, many women with harmless DCIS face overtreatment. To identify these women that may forego treatment, we hypothesized that DCIS morphometric features relate to the risk of subsequent iIBC. We developed an artificial intelligence-based DCIS morphometric analysis pipeline (AIDmap) to detect DCIS as a pathologist and measure morphological structures in hematoxylin-eosin-stained (H&E) tissue sections. These were from a case-control study of patients diagnosed with primary DCIS, treated by breast-conserving surgery without radiotherapy. We analyzed 689 WSIs of DCIS of which 226 were diagnosed with subsequent iIBC (cases) and 463 were not (controls). The distribution of 15 duct morphological measurements in each H&E was summarized in 55 morphometric variables. A ridge regression classifier with cross validation predicted 5-years-free of iIBC with an area-under the curve of 0.65 (95% CI 0.55-0.76). A morphometric signature based on the 30 variables most associated with outcome, identified lesions containing small-sized ducts, low number of cells and low DCIS/stroma area ratio. This signature was associated with lower iIBC risk in a multivariate regression model including grade, ER, HER2 and COX-2 expression (HR = 0.56; 95% CI 0.28-0.78). AIDmap has potential to identify harmless DCIS that may not need treatment.

Chromatin insulation orchestrates matrix metalloproteinase gene cluster expression reprogramming in aggressive breast cancer tumors

BACKGROUND

Triple-negative breast cancer (TNBC) is an aggressive subtype that exhibits a high incidence of distant metastases and lacks targeted therapeutic options. Here we explored how the epigenome contributes to matrix metalloprotease (MMP) dysregulation impacting tumor invasion, which is the first step of the metastatic process.

METHODS

We combined RNA expression and chromatin interaction data to identify insulator elements potentially associated with MMP gene expression and invasion. We employed CRISPR/Cas9 to disrupt the CCCTC-Binding Factor (CTCF) binding site on an insulator element downstream of the MMP8 gene (IE8) in two TNBC cellular models. We characterized these models by combining Hi-C, ATAC-seq, and RNA-seq with functional experiments to determine invasive ability. The potential of our findings to predict the progression of ductal carcinoma in situ (DCIS), was tested in data from clinical specimens.

RESULTS

We explored the clinical relevance of an insulator element located within the Chr11q22.2 locus, downstream of the MMP8 gene (IE8). This regulatory element resulted in a topologically associating domain (TAD) boundary that isolated nine MMP genes into two anti-correlated expression clusters. This expression pattern was associated with worse relapse-free (HR = 1.57 [1.06 - 2.33]; p = 0.023) and overall (HR = 2.65 [1.31 - 5.37], p = 0.005) survival of TNBC patients. After CRISPR/Cas9-mediated disruption of IE8, cancer cells showed a switch in the MMP expression signature, specifically downregulating the pro-invasive MMP1 gene and upregulating the antitumorigenic MMP8 gene, resulting in reduced invasive ability and collagen degradation. We observed that the MMP expression pattern predicts DCIS that eventually progresses into invasive ductal carcinomas (AUC = 0.77, p < 0.01).

CONCLUSION

Our study demonstrates how the activation of an IE near the MMP8 gene determines the regional transcriptional regulation of MMP genes with opposing functional activity, ultimately influencing the invasive properties of aggressive forms of breast cancer.

Advances in Mapping Tumor Progression from Precancer Atlases

Tissue profiling technologies present opportunities for understanding transition from precancerous lesions to malignancy, which may impact risk stratification, prevention, and even cancer treatment. A human precancer atlas building effort is ongoing to tackle the significant challenge of decoding the heterogeneity among cells, specimens, and patients. Here, we discuss the findings resulting from atlases built across precancer types, including those found in colon, breast, lung, stomach, cervix, and skin, using bulk, single-cell, and spatial profiling strategies. We highlight two main themes that emerge across precancer types: the ordering of molecular events that occur during tumor progression and the fluctuation of microenvironmental response during precancer progression. We further highlight the key challenges of data integration across large cohorts of patients, and the need for computational tools to reliably annotate and quality control high-volume, high-dimensional data.

Subtypes of high-grade breast ductal carcinoma in situ (DCIS): incidence and potential clinical impact

OBJECTIVE

The purpose of this study was to investigate and classify the molecular subtypes of high-grade ductal carcinoma in situ (DCIS) and identify possible high-risk subtypes. The heterogenicity of DCIS with variable clinical and histopathological presentations has been recognized. Nevertheless, only histopathological grading and diameter are currently implemented in clinical decision-making following the diagnosis of DCIS. The molecular subtypes of DCIS and their IHC surrogate markers have not been defined in conventional treatment guidelines and recommendations. We applied the definitions of molecular subtypes according to the IHC surrogate markers defined for IBC and subclassified high-grade DCIS, accordingly.

METHODS

Histopathological specimens were collected, revised, and regraded from 494 patients diagnosed with DCIS between 1996 and 2018. Other in situ and papillary lesions observed in breast biopsies were excluded from this study. 357 high-grade DCIS cases were submitted to IHC analysis. The markers investigated were ER, PR, HER2, and Ki67.

RESULTS

45 cases were classified as grade 1, 19 as grade 2, and 430 as grade 3. Sixty patients with high-grade DCIS had an additional invasive component in the surgical specimen. Thirty-three patients were diagnosed with recurrent DCIS or invasive cancer (minimum one year after their primary DCIS diagnosis). The proportions of luminal A and luminal B HER2-negative subtypes varied depending on whether 2011 or 2013 St. Gallen Consensus Conference guidelines were adopted. Luminal A was the most prevalent subtype, according to both classifications. The luminal B HER2-positive subtype was found in 22.1% of cases, HER2-enriched subtype in 21.8%, and TPN subtype in 5.6%. There were strong indications that HER2-enriched subtype was significantly more frequent among DCIS with invasive component (p = 0.0169).

CONCLUSIONS

High-grade DCIS exhibits all the molecular subtypes previously identified in IBC, but with a somewhat different distribution in our cohort. HER2-enriched subtype is substantially related to the presence of an invasive component in DCIS; consequently, it is regarded as a high-risk entity.

Extensive review on breast cancer its etiology, progression, prognostic markers, and treatment

As the most frequent and vulnerable malignancy among women, breast cancer universally manifests a formidable healthcare challenge. From a biological and molecular perspective, it is a heterogenous disease and is stratified based on the etiological factors driving breast carcinogenesis. Notably, genetic predispositions and epigenetic impacts often constitute the heterogeneity of this disease. Typically, breast cancer is classified intrinsically into histological subtypes in clinical landscapes. These stratifications empower physicians to tailor precise treatments among the spectrum of breast cancer therapeutics. In this pursuit, numerous prognostic algorithms are extensively characterized, drastically changing how breast cancer is portrayed. Therefore, it is a basic requisite to comprehend the multidisciplinary rationales of breast cancer to assist the evolution of novel therapeutic strategies. This review aims at highlighting the molecular and genetic grounds of cancer additionally with therapeutic and phytotherapeutic context. Substantially, it also renders researchers with an insight into the breast cancer cell lines as a model paradigm for breast cancer research interventions.

A living biobank of patient-derived ductal carcinoma in situ mouse-intraductal xenografts identifies risk factors for invasive progression

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer (IBC). Due to a lack of biomarkers able to distinguish high- from low-risk cases, DCIS is treated similar to early IBC even though the minority of untreated cases eventually become invasive. Here, we characterized 115 patient-derived mouse-intraductal (MIND) DCIS models reflecting the full spectrum of DCIS observed in patients. Utilizing the possibility to follow the natural progression of DCIS combined with omics and imaging data, we reveal multiple prognostic factors for high-risk DCIS including high grade, HER2 amplification, expansive 3D growth, and high burden of copy number aberrations. In addition, sequential transplantation of xenografts showed minimal phenotypic and genotypic changes over time, indicating that invasive behavior is an intrinsic phenotype of DCIS and supporting a multiclonal evolution model. Moreover, this study provides a collection of 19 distributable DCIS-MIND models spanning all molecular subtypes.

Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity

Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individual's germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes in ERBB2, encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.

Towards the development of DCIS risk prediction models

Ductal carcinoma in situ (DCIS) has a variable natural history, with a poorly understood biology. In this issue of Cancer Cell, Strand et. al. use two well-annotated DCIS repositories to identify an 812-gene classifier that associates with high risk of DCIS recurrence and define novel DCIS subtypes that informs future studies.