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

Multiplex characterization of circulating tumor cells from ductal carcinoma in situ patients suggests early tumor dissemination

While ducal carcinoma in situ (DCIS) is considered to be pre-invasive, some patients will develop metastatic disease after a long disease-free interval. The prevailing dogma posits that invasive local recurrence is the source of subsequent metastasis, and thus the goal of DCIS therapy is the prevention of local recurrence. Recently, this paradigm has been called into question by the observation that some women develop metastatic disease in the absence of local recurrence or even following bilateral mastectomies, suggesting early cancer dissemination in some patients. If the presence of circulating tumor cells (CTCs) can be verified on some patients with pure DCIS, then dissemination may be occurring earlier than previously thought, suggesting that these patients might require additional monitoring or treatment. Here, we present a workflow to isolate and characterize CTCs from DCIS patients. Using a high throughput size based inertial focusing microfluidic device, the Labyrinth, we isolated and identified CTCs in 66.6 % (12/18) of DCIS patients with an average of 1.337 CTCs per five mL. Immunofluorescence staining and single cell qPCR of CTCs reveal mesenchymal characteristics of the cells that may contribute to their ability to migrate and metastasize. Preliminary targeted DNA sequencing revealed single nucleotide variations previously found in DCIS samples. Overall, this data supports the hypothesis that cancer dissemination is occurring in a subset of DCIS patients earlier than previously thought. Additionally, the molecular characterization of CTC in DCIS patients may provide important information on their biological characteristics and associated clinical behavior.

Ultrasound characteristics comparison and development of a predictive nomogram for intraductal papilloma and ductal carcinoma in situ: a retrospective cohort study

Background

Intraductal Papilloma (IDP) and Ductal Carcinoma In Situ (DCIS) are significant benign and pre-invasive breast lesions, respectively. This study aimed to investigate ultrasound features and develop a predictive nomogram for discriminating between IDP and DCIS.

Methods

Conducted at Quanzhou First Hospital over a three-year period, 389 patients were enrolled with detailed ultrasound examinations and confirmed pathological diagnoses. IDP was classified into Grades 3, 4, and 5, whereas DCIS presented with a mass-like morphology. Patients meeting the inclusion criteria underwent rigorous analysis, with exclusion criteria eliminating those with incomplete imaging data or confounding comorbidities. Ultrasound characteristics, including lesion size, shape, margin, and echogenicity, etc., were systematically evaluated and compared between the two groups. Univariate and multivariate logistic regression analyses were conducted to identify significant risk factors. Subsequently, based on these characteristics, both static and dynamic nomograms were developed. The performance of the nomograms was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA).

Results

The study cohort included 272 patients in the training set and 117 in the validation set. Significant differences were observed between IDP and DCIS in age, size, shape, aspect ratio, margin, duct dilatation, and microcalcification (P < 0.05). Logistic regression analyses identified age, size, aspect ratio, margin, microcalcification, and duct dilatation as independent risk factors. Compared to DCIS, IDP is associated with younger age, smaller size, clearer margins, fewer microcalcifications, and more ductal dilation. The performance of the nomogram developed to predict IDP and DCIS showed an AUC of 0.918 in the training set and 0.888 in the validation set. The calibration curve indicates a strong fit of the predictive model in the validation set, with the Hosmer-Lemeshow test showing high consistency between predicted and actual probabilities (training set, P = 0.875; validation set, P = 0.751). Additionally, DCA confirms the clinical utility of the model.

Conclusion

The nomogram incorporating key predictors provides a valuable tool for differentiating between IDP and DCIS based on ultrasound characteristics. This approach aids in clinical decision-making and potentially reduces unnecessary biopsies.

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.

Three-Dimensional Models: Biomimetic Tools That Recapitulate Breast Tissue Architecture and Microenvironment to Study Ductal Carcinoma In Situ Transition to Invasive Ductal Breast Cancer

Diagnosis of ductal carcinoma in situ (DCIS) presents a challenge as we cannot yet distinguish between those lesions that remain dormant from cases that may progress to invasive ductal breast cancer (IDC) and require therapeutic intervention. Our overall interest is to develop biomimetic three-dimensional (3D) models that more accurately recapitulate the structure and characteristics of pre-invasive breast cancer in order to study the underlying mechanisms driving malignant progression. These models allow us to mimic the microenvironment to investigate many aspects of mammary cell biology, including the role of the extracellular matrix (ECM), the interaction between carcinoma-associated fibroblasts (CAFs) and epithelial cells, and the dynamics of cytoskeletal reorganization. In this review article, we outline the significance of 3D culture models as reliable pre-clinical tools that mimic the in vivo tumor microenvironment and facilitate the study of DCIS lesions as they progress to invasive breast cancer. We also discuss the role of CAFs and other stromal cells in DCIS transition as well as the clinical significance of emerging technologies like tumor-on-chip and co-culture models.

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.

Conquering Overtreatment of DCIS: Lessons from PRECISION

As we cannot reliably distinguish indolent, low-risk ductal carcinoma in situ (DCIS) from potentially progressive, high-risk DCIS, all women with DCIS diagnosis undergo intensive treatment without any benefit. The PREvent ductal Carcinoma In Situ Invasive Overtreatment Now team was established to unravel DCIS biology and develop new multidisciplinary approaches for accurate risk stratification to tackle the global problem of DCIS overdiagnosis and overtreatment. See related article by Bressan et al., p. 16 See related article by Stratton et al., p. 22 See related article by Goodwin et al., p. 34.

Patient-Derived Xenografts of Breast Cancer

Patient-derived xenografts (PDX) of breast cancer, obtained from the engraftment of tumour samples into immunodeficient mice, are the most effective preclinical models for studying the biology of human breast cancer and for the evaluation of new anti-cancer treatments. Notably, breast cancer PDX preserve the phenotypic and molecular characteristics of the donor tumours and reproduce the diversity of breast cancer. This preservation of breast cancer biology involves a number of different aspects, including tumour architecture and morphology, patterns of genomic alterations and gene expression, mutational status, and intra-tumour heterogeneity. For these reasons, these models have a strong predictive value in the translation of cancer therapeutics into clinical settings and can be considered as powerful and clinically relevant research tools for the identification of new treatments, mechanisms of drug resistance, and predictive biomarkers. PDX models have also been successfully used to analyse breast cancer metastasis and persister cancer cells surviving chemotherapy. Limitations of breast cancer PDX include the lack of a human immune system and the low take rate, especially for estrogen receptor (ER) and HER2-positive subtypes.

Models for Studying Ductal Carcinoma In Situ Progression

An estimated 55,720 new cases of ductal carcinoma in situ (DCIS) will be diagnosed in 2023 in the USA alone because of the increased use of screening mammography. The treatment goal in DCIS is early detection and treatment with the hope of preventing progression into invasive disease. Previous studies show progression into invasive cancer as well as reduction in mortality from treatment is not as high as previously thought. So, are we overdiagnosing and over-treating DCIS? An understanding of the natural progression of DCIS is paramount to address this. The purpose of this chapter is to describe various models that have been developed to simulate the processes involved in DCIS to invasive ductal carcinoma (IDC) transition. While each model possesses a unique set of strengths and weaknesses, they have collectively contributed to the current understanding of the molecular and cellular mechanisms underlying this transition. Even though much has been learned, continued advancement of the current models to best match the composition of DCIS epithelial and stromal microenvironment including the extracellular matrix (ECM), stromal cell types, and immune microenvironment will be essential. These advances will undoubtedly pave the way toward a full understanding of mechanisms associated with progression and in predicting when a DCIS lesion remains indolent and when triggers tip in the balance toward progression to malignancy.

Heterogeneity-driven phenotypic plasticity and treatment response in branched-organoid models of pancreatic ductal adenocarcinoma

In patients with pancreatic ductal adenocarcinoma (PDAC), intratumoural and intertumoural heterogeneity increases chemoresistance and mortality rates. However, such morphological and phenotypic diversities are not typically captured by organoid models of PDAC. Here we show that branched organoids embedded in collagen gels can recapitulate the phenotypic landscape seen in murine and human PDAC, that the pronounced molecular and morphological intratumoural and intertumoural heterogeneity of organoids is governed by defined transcriptional programmes (notably, epithelial-to-mesenchymal plasticity), and that different organoid phenotypes represent distinct tumour-cell states with unique biological features in vivo. We also show that phenotype-specific therapeutic vulnerabilities and modes of treatment-induced phenotype reprogramming can be captured in phenotypic heterogeneity maps. Our methodology and analyses of tumour-cell heterogeneity in PDAC may guide the development of phenotype-targeted treatment strategies.

A comprehensive luminal breast cancer patient-derived xenografts (PDX) library to capture tumor heterogeneity and explore the mechanisms of resistance to CDK4/6 inhibitors

Breast cancer (BC) is marked by significant genetic, morphological and clinical heterogeneity. To capture this heterogeneity and unravel the molecular mechanisms driving tumor progression and drug resistance, we established a comprehensive patient-derived xenograft (PDX) biobank, focusing particularly on luminal (estrogen receptor, ER+) and young premenopausal patients, for whom PDX models are currently scarce. Across all BC subtypes, our efforts resulted in an overall success rate of 17% (26 established PDX lines out of 151 total attempts), specifically 15% in luminal, 12% in human epidermal growth factor receptor 2 positive (HER2+) and 35% in triple negative BC. These PDX mirrored morphologic and genetic features of BC from which they originated, serving as a reliable tool to investigate drug resistance and test therapeutic strategies. We focused on understanding resistance to CDK4/6 inhibitors (CDK4/6i), which are crucial in the treatment of patients with advanced luminal BC. Treating a sensitive luminal BC PDX with the CDK4/6i palbociclib revealed that, despite initial tumor shrinkage, some tumors might eventually regrow under drug treatment. RNA sequencing, followed by gene set enrichment analyses, unveiled that these PDXs have become refractory to CDK4/6i, both at biological and molecular levels, displaying significant enrichment in proliferation pathways, such as MTORC1, E2F and MYC. Using organoids derived from these PDX (PDxO), we observed that acquisition of CDK4/6i resistance conferred cross-resistance to endocrine therapy and that targeting MTORC1 was a successful strategy to overcome CDK4/6i resistance. Considered together, these results indicate that our PDX models may serve as robust tools to elucidate the molecular basis of BC disease progression and, by providing the possibility to simultaneously test different therapies on the same tumor, to surmount treatment resistance. While this approach is of course not feasible in the clinic, its exploitation in PDX may expedite the identification and development of more successful therapies for patients with advanced luminal BC. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Genomic profiling of a multi-lineage and multi-passage patient-derived xenograft biobank reflects heterogeneity of ovarian cancer

Ovarian cancer (OC) manifests as a complex disease characterized by inter- and intra-patient heterogeneity. Despite enhanced biological and genetic insights, OC remains a recalcitrant malignancy with minimal survival improvement. Based on multi-site sampling and a multi-lineage patient-derived xenograft (PDX) establishment strategy, we present herein the establishment of a comprehensive PDX biobank from histologically and molecularly heterogeneous OC patients. Comprehensive profiling of matched PDX and patient samples demonstrates that PDXs closely recapitulate parental tumors. By leveraging multi-lineage models, we reveal that the previously reported genomic disparities of PDX could be mainly attributed to intra-patient spatial heterogeneity instead of substantial model-independent genomic evolution. Moreover, DNA damage response pathway inhibitor (DDRi) screening uncovers heterogeneous responses across models. Prolonged iterative drug exposure recapitulates acquired drug resistance in initially sensitive models. Meanwhile, interrogation of induced drug-resistant (IDR) models reveals that suppressed interferon (IFN) response and activated Wnt/β-catenin signaling contribute to acquired DDRi drug resistance.

Ductal carcinoma in situ develops within clonal fields of mutant cells in morphologically normal ducts

Mutations are abundantly present in tissues of healthy individuals, including the breast epithelium. Yet it remains unknown whether mutant cells directly induce lesion formation or first spread, leading to a field of mutant cells that is predisposed towards lesion formation. To study the clonal and spatial relationships between morphologically normal breast epithelium adjacent to pre-cancerous lesions, we developed a three-dimensional (3D) imaging pipeline combined with spatially resolved genomics on archival, formalin-fixed breast tissue with the non-obligate breast cancer precursor ductal carcinoma in situ (DCIS). Using this 3D image-guided characterization method, we built high-resolution spatial maps of DNA copy number aberration (CNA) profiles within the DCIS lesion and the surrounding normal mammary ducts. We show that the local heterogeneity within a DCIS lesion is limited. However, by mapping the CNA profiles back onto the 3D reconstructed ductal subtree, we find that in eight out of 16 cases the healthy epithelium adjacent to the DCIS lesions has overlapping structural variations with the CNA profile of the DCIS. Together, our study indicates that pre-malignant breast transformations frequently develop within mutant clonal fields of morphologically normal-looking ducts. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

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.

MYC is a clinically significant driver of mTOR inhibitor resistance in breast cancer

Targeting the PI3K-AKT-mTOR pathway is a promising therapeutic strategy for breast cancer treatment. However, low response rates and development of resistance to PI3K-AKT-mTOR inhibitors remain major clinical challenges. Here, we show that MYC activation drives resistance to mTOR inhibitors (mTORi) in breast cancer. Multiomic profiling of mouse invasive lobular carcinoma (ILC) tumors revealed recurrent Myc amplifications in tumors that acquired resistance to the mTORi AZD8055. MYC activation was associated with biological processes linked to mTORi response and counteracted mTORi-induced translation inhibition by promoting translation of ribosomal proteins. In vitro and in vivo induction of MYC conferred mTORi resistance in mouse and human breast cancer models. Conversely, AZD8055-resistant ILC cells depended on MYC, as demonstrated by the synergistic effects of mTORi and MYCi combination treatment. Notably, MYC status was significantly associated with poor response to everolimus therapy in metastatic breast cancer patients. Thus, MYC is a clinically relevant driver of mTORi resistance that may stratify breast cancer patients for mTOR-targeted therapies.

Mouse intraductal modeling of primary ductal carcinoma in situ

Mouse intraductal modeling enables efficient in vivo propagation of pre-invasive breast cancer lesions and provides a suitable micro-environment for creating patient-derived tumor xenograft models of estrogen-receptor-positive breast cancer. Here, we present a protocol for mouse intraductal modeling of primary ductal carcinoma in situ (DCIS). We describe steps for processing primary DCIS tissues and performing intraductal injections. We then detail procedures for processing intraductal lesions for 3D whole-mount imaging or serial transplantation using magnetic bead sorting. For complete details on the use and execution of this protocol, please refer to Hutten et al. (2023).1.