Clinicopathological Significance of Cyclin-Dependent Kinase 2 (CDK2) in Ductal Carcinoma In Situ and Early-Stage Invasive Breast Cancers.

Cyclin-dependent kinase 2 (CDK2) is a key cell cycle regulator, with essential roles during G1/S transition. The clinicopathological significance of CDK2 in ductal carcinomas in situ (DCIS) and early-stage invasive breast cancers (BCs) remains largely unknown. Here, we evaluated CDK2's protein expression in 479 BC samples and 216 DCIS specimens. Analysis of CDK2 transcripts was completed in the METABRIC cohort (n = 1980) and TCGA cohort (n = 1090), respectively. A high nuclear CDK2 protein expression was significantly associated with aggressive phenotypes, including a high tumour grade, lymph vascular invasion, a poor Nottingham prognostic index (all p-values < 0.0001), and shorter survival (p = 0.006), especially in luminal BC (p = 0.009). In p53-mutant BC, high nuclear CDK2 remained linked with worse survival (p = 0.01). In DCIS, high nuclear/low cytoplasmic co-expression showed significant association with a high tumour grade (p = 0.043), triple-negative and HER2-enriched molecular subtypes (p = 0.01), Comedo necrosis (p = 0.024), negative ER status (p = 0.004), negative PR status (p < 0.0001), and a high proliferation index (p < 0.0001). Tumours with high CDK2 transcripts were more likely to have higher expressions of genes involved in the cell cycle, homologous recombination, and p53 signaling. We provide compelling evidence that high CDK2 is a feature of aggressive breast cancers. The clinical evaluation of CDK2 inhibitors in early-stage BC patients will have a clinical impact.

Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study.

BACKGROUND: Patients with a Breast Imaging Reporting and Data System (BI-RADS) 4 mammogram are currently recommended for biopsy. However, 70-80% of the biopsies are negative/benign. In this study, we developed a deep learning classification algorithm on mammogram images to classify BI-RADS 4 suspicious lesions aiming to reduce unnecessary breast biopsies. MATERIALS AND METHODS: This retrospective study included 847 patients with a BI-RADS 4 breast lesion that underwent biopsy at a single institution and included 200 invasive breast cancers, 200 ductal carcinoma in-situ (DCIS), 198 pure atypias, 194 benign, and 55 atypias upstaged to malignancy after excisional biopsy. We employed convolutional neural networks to perform 4 binary classification tasks: (I) benign vs. all atypia + invasive + DCIS, aiming to identify the benign cases for whom biopsy may be avoided; (II) benign + pure atypia vs. atypia-upstaged + invasive + DCIS, aiming to reduce excision of atypia that is not upgraded to cancer at surgery; (III) benign vs. each of the other 3 classes individually (atypia, DCIS, invasive), aiming for a precise diagnosis; and (IV) pure atypia vs. atypia-upstaged, aiming to reduce unnecessary excisional biopsies on atypia patients. RESULTS: A 95% sensitivity for the "higher stage disease" class was ensured for all tasks. The specificity value was 33% in Task I, and 25% in Task II, respectively. In Task III, the respective specificity value was 30% (vs. atypia), 30% (vs. DCIS), and 46% (vs. invasive tumor). In Task IV, the specificity was 35%. The AUC values for the 4 tasks were 0.72, 0.67, 0.70/0.73/0.72, and 0.67, respectively. CONCLUSION: Deep learning of digital mammograms containing BI-RADS 4 findings can identify lesions that may not need breast biopsy, leading to potential reduction of unnecessary procedures and the attendant costs and stress.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296-2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA),  L. E. Elshof et al., Eur J Cancer, 51, 1497-510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials. OBJECTIVE: To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance. METHODS: In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS. RESULTS: When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved. CONCLUSION: For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.

Non-mass-type ductal carcinoma in situ of the breast on ultrasound: Features and pathological analysis.

AIMS: The aims of this study were to investigate the ultrasound features of non-mass-type ductal carcinoma in situ (DCIS) of the breast and conduct a pathological analysis. MATERIAL AND METHODS: Ultrasound images of 32 cases of non-mass-type DCIS of the breast, collected between September 2014 and June 2016, were analyzed. The characteristics of the lesions, including border, internal echogenicity, local glandular hyperplasia, micro-calcification, and intra-tumoral blood flow resistance index (RI), were analyzed, and a concurrent pathological analysis was conducted. RESULTS: Obvious local glandular hyperplasia was commonly observed in the 32 cases of non-mass-type DCIS of the breast. The internal echogenicity varied in intensity, exhibiting a "leopard pattern" or "zebra pattern." Color Doppler imaging revealed abundant blood flow signals within the lesion with an RI of >0.7. Isolated duct dilatation and micro-calcifications were occasionally observed within the lesions. High-grade DCIS was the predominant pathological type of non-mass-type DCIS. CONCLUSIONS: Non-mass-type DCIS of the breast often presents with obvious local glandular hyperplasia and varying internal echogenicity. High-grade DCIS is the frequent pathological type. Color Doppler imaging and RI measurement can assist in diagnosing non-mass-type DCIS of the breast.

Expression of immune-related genes and breast cancer recurrence in women with ductal carcinoma in situ.

BACKGROUND AND AIM: Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer with highly variable clinical behavior, but risk stratification is still challenging. We sought to identify immune-related gene expression signatures of pure DCIS associated with different risks of breast cancer recurrence. METHODS: A retrospective nested case-control study of 143 pure DCIS was performed including 70 women with subsequent ipsilateral breast event (IBE, in situ or invasive; cases) and 73 DCIS women with no IBE and matched for age, tumor size, treatment, hormone receptors/HER2 status, and follow-up time (controls). RNA was extracted from DCIS samples and subjected to next-generation sequencing gene expression analysis of 395 immune-related genes. Correlations between DCIS immune-related gene expression and IBE were analyzed using weighted Cox regression for nested case-control data. RESULTS: Eight immune-related genes were differentially expressed between cases and controls. MAGEA10 expression (present vs. absent) and high expression levels of IFNA17 and CBLB (Q4 vs. Q1) were observed more frequently in DCIS of women with subsequent IBE, mainly invasive (p-valueFDR < 0.05). Conversely, expression of IL3RA1, TAGAP, TNFAIP8, and high expression levels of CCL2 and LRP1 were associated with a lower risk of IBE (p-valueFDR < 0.05). CONCLUSION: This exploratory analysis of pure DCIS showed significant differences in immune-related gene expression profiles between women with and with no subsequent IBE, particularly as invasive IBE. These results, after additional validation, could improve risk stratification and management of DCIS patients.

Outcomes of atypical (B3) core biopsy lesions diagnosed across BreastScreen NSW, Australia.

INTRODUCTION: Atypical or B3 lesions comprise a heterogeneous group of uncertain malignant potential. B3 lesions diagnosed on core biopsy are usually recommended for diagnostic open biopsy. Identifying factors which could allow conservative management of B3 lesions would be helpful in avoiding unnecessary surgery. The aim of this study was to identify the upgrade rate to malignancy for B3 core biopsy lesions and to compare characteristics of lesions which were malignant and benign at excision. METHOD: This retrospective study used data from BreastScreen New South Wales (NSW), Australia, of women who were diagnosed with B3 lesions on needle biopsy from 2011 to 2019. RESULTS: During the study period, 1927 B3 lesions were included. The upgrade rate to malignancy was 26.4%. Of the malignant lesions on excision, 29.6% were invasive and 69.2% were in situ. The rates of upgrade to invasive cancer and DCIS varied substantially with the core biopsy lesion type. Lesions with atypia on core biopsy had significantly higher upgrade rates to malignancy at 34.7% compared to 13.6% for lesions without atypia (p < 0.0001). Lesions with malignant pathology were significantly larger than those with benign pathology (difference = 5.1 mm (95% CI 2.7-7.5 mm), p < 0.001). CONCLUSIONS: The overall upgrade rate of B3 lesions to malignancy was 26.4%. The majority of the lesions were upgraded to DCIS instead of invasive cancer. Upgrade rates varied by lesion type. Lesions with atypia had significantly higher upgrade rates to cancer compared to lesions without atypia. Malignant lesions were significantly larger than benign lesions.

Progression from ductal carcinoma in situ to invasive breast cancer: molecular features and clinical significance.

Ductal carcinoma in situ (DCIS) represents pre-invasive breast carcinoma. In untreated cases, 25-60% DCIS progress to invasive ductal carcinoma (IDC). The challenge lies in distinguishing between non-progressive and progressive DCIS, often resulting in over- or under-treatment in many cases. With increasing screen-detected DCIS in these years, the nature of DCIS has aroused worldwide attention. A deeper understanding of the biological nature of DCIS and the molecular journey of the DCIS-IDC transition is crucial for more effective clinical management. Here, we reviewed the key signaling pathways in breast cancer that may contribute to DCIS initiation and progression. We also explored the molecular features of DCIS and IDC, shedding light on the progression of DCIS through both inherent changes within tumor cells and alterations in the tumor microenvironment. In addition, valuable research tools utilized in studying DCIS including preclinical models and newer advanced technologies such as single-cell sequencing, spatial transcriptomics and artificial intelligence, have been systematically summarized. Further, we thoroughly discussed the clinical advancements in DCIS and IDC, including prognostic biomarkers and clinical managements, with the aim of facilitating more personalized treatment strategies in the future. Research on DCIS has already yielded significant insights into breast carcinogenesis and will continue to pave the way for practical clinical applications.

[Clinicopathological characteristics and immune microenvironment of breast squamous cell carcinoma].

Objective: To investigate the clinicopathological characteristics of breast squamous cell carcinoma and to analyze the relationship between its immune microenvironment tumor infiltrating lymphocytes (TILs) and prognosis. Methods: Forty-four cases of primary squamous cell carcinoma of the breast diagnosed and treated in the First Affiliated Hospital of Air Force Medical University, Xi'an, China from January 2006 to July 2022 were selected. Their clinicopathological characteristics were analyzed. The cell composition of TILs was evaluated using immunohistochemistry (Mainly markers of B lymphocytes, T lymphocytes and plasma cells). The relationship between TILs and prognosis was also analyzed. Results: The 44 patients of breast squamous cell carcinoma were all female and all were invasive carcinoma. Eight cases (8/44, 18.2%) were squamous cell carcinoma, while 36 cases (36/44, 81.8%) were mixed squamous cell carcinoma. The mixed components included non-specific carcinoma and spindle cell metaplastic carcinoma (17 cases each). One case contained ductal carcinoma in situ of the breast and 1 case contained tubular carcinoma. The proportion of squamous cell carcinoma was 10% to 90%. The cases with pure squamous cell carcinoma often had a large cystic cavity, which was lined by atypical squamous epithelium, while infiltrating squamous cell carcinoma nests were seen in the breast tissue around the cystic cavity. Immunohistochemical staining showed that p63 and CK5/6 were expressed in the squamous cell carcinoma component, but ER, PR and HER2 were not, except for one case of HER2 1+. The positive rates of TRPS1 and PDL-1 were 76% and less than 1%, respectively. Fifteen cases were in the high TILs group (TILs≥30%) and 29 cases were in the low TILs group (TILs<30%). Twenty-three patients were followed up for 5 to 118 months. Among them, 12 died within 3 years and 9 were alive at the end of the follow up. There was no significant difference in TNM stage, TILs and prognosis between simple squamous cell carcinoma and mixed squamous cell carcinoma. Conclusions: Breast squamous cell carcinoma can be divided into simple squamous cell carcinoma and mixed squamous cell carcinoma. There are differences in gross findings and histology between the simple and mixed squamous cell carcinoma of the breast. Sufficient samples should be taken to avoid missing the diagnosis of a minor squamous component. The prognosis of patients with high TILs is significantly better than that of patients with low TILs. The expression rate of TRPS1 in primary squamous cell carcinoma of breast is high and helpful to the differential diagnosis from metastatic squamous cell carcinoma.

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.

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

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

Clinicopathological Predictors of Positive Resection Margins in Breast-Conserving Surgery.

BACKGROUND: Ductal carcinoma in situ (DCIS) is associated with risk of positive resection margins following breast-conserving surgery (BCS) and subsequent reoperation. Prior reports grossly underestimate the risk of margin positivity with IBC containing a DCIS component (IBC + DCIS) due to patient-level rather than margin-level analysis. OBJECTIVE: The aim of this study was to delineate the relative risk of IBC + DCIS compared with pure IBC (without a DCIS component) on margin positivity through detailed margin-level interrogation. METHODS: A single institution, retrospective, observational cohort study was conducted in which pathology databases were evaluated to identify patients who underwent BCS over 5 years (2014-2019). Margin-level interrogation included granular detail into the extent, pathological subtype and grade of disease at each resection margin. Predictors of a positive margin were computed using multivariate regression analysis. RESULTS: Clinicopathological details were examined from 5454 margins from 909 women. The relative risk of a positive margin with IBC + DCIS versus pure IBC was 8.76 (95% confidence interval [CI] 6.64-11.56) applying UK Association of Breast Surgery guidelines, and 8.44 (95% CI 6.57-10.84) applying the Society of Surgical Oncology/American Society for Radiation Oncology guidelines. Independent predictors of margin positivity included younger patient age (0.033, 95% CI 0.006-0.060), lower specimen weight (0.045, 95% CI 0.020-0.069), multifocality (0.256, 95% CI 0.137-0.376), lymphovascular invasion (0.138, 95% CI 0.068-0.208) and comedonecrosis (0.113, 95% CI 0.040-0.185). CONCLUSIONS: Compared with pure IBC, the relative risk of a positive margin with IBC + DCIS is approximately ninefold, significantly higher than prior estimates. This margin-level methodology is believed to represent the impact of DCIS more accurately on margin positivity in IBC.

Atypia Involving Fibroadenomas: Outcomes and Upgrade Rates.

OBJECTIVE: Fibroadenomas (FAs) involved by atypia are rare. Consensus guidelines for management of FAs involved by atypia when diagnosed on image-guided biopsy do not exist because of limited data reporting surgical upgrade rates to ductal carcinoma in situ (DCIS) or invasive malignancy. Therefore, these lesions commonly undergo surgical excision. METHODS: This single-institution retrospective study identified cases of FAs involved by atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), and/or lobular carcinoma in situ (LCIS) diagnosed on image-guided biopsy between January 2014 and April 2023 to determine upgrade rates. Cases with incidental atypia adjacent to but not involving FAs were excluded. RESULTS: Among 1736 FAs diagnosed on image-guided biopsy, 32 cases (1.8%) were FAs involved by atypia including 43.8% (14/32) ALH, 28.1% (9/32) ADH, 18.8% (6/32) LCIS, 6.3% (2/32) LCIS + ALH, and 3.1% (1/32) unspecified atypia. The most common imaging finding was a mass. Most cases, 81.3% (26/32), underwent subsequent surgical excisional biopsy. A single case of ADH involving and adjacent to an FA was upgraded to FA involved by low-grade DCIS on excision for an overall surgical upgrade rate of 3.8%. There were no cases upgraded to invasive malignancy. For those omitting surgical excision, there was no subsequent malignancy diagnosis at the FA biopsy site over a mean follow-up of 73 months. CONCLUSION: Cases of radiologic-pathologic concordant FAs involved by atypia have a low upgrade rate of 3.8% and should undergo multidisciplinary review. Larger multi-institutional analysis is needed to determine whether guidelines for excision of atypia should apply to atypia involving FAs.

Using the DNA Integrity Number to Analyze DNA Quality in Specimens Collected from Liquid-Based Cytology after Fine-Needle Aspiration of Breast Tumors and Lesions.

INTRODUCTION: Cancer genome analysis using next-generation sequencing requires adequate and high-quality DNA samples. Genomic analyses were conventionally performed using formalin-fixed paraffin-embedded sections rather than cytology samples such as cell block or smear specimens. Specimens collected from liquid-based cytology (LBC) have the potential to be sources of high-quality DNA suitable for genetic analysis even after long-term storage. METHODS: We collected breast tumor/lesion fractions from 92 residual LBC specimens using fine-needle aspiration (FNA) biopsy, including breast carcinoma (1 invasive carcinoma and 4 ductal carcinomas in situ), papillomatous lesion (5 intraductal papillomas), and fibroepithelial lesion (19 phyllodes tumors and 53 fibroadenomas) samples, and others (1 ductal adenoma, 1 hamartoma, 1 fibrocystic disease, and 7 unknown). DNA was extracted from all samples and subjected to DNA integrity number (DIN) score analysis. RESULTS: Average DIN score collected from 92 LBC specimens was significantly higher score. In addition, high-quality DNA with high DIN values (7.39 ± 0.80) was successfully extracted more than 12 months after storage of residual LBC specimens. CONCLUSION: Residual LBC specimens collected from FNA of the breast were verified to carry high-quality DNA and could serve as an alternate source for genetic analysis.

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

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

Immune cell infiltrate in ductal carcinoma in situ and the risk of dying from breast cancer: case-control study.

BACKGROUND: Studies identifying risk factors for death from breast cancer after ductal carcinoma in situ (DCIS) are rare. In this retrospective nested case-control study, clinicopathological factors in women treated for DCIS and who died from breast cancer were compared with those of patients with DCIS who were free from metastatic disease. METHODS: The study included patients registered with DCIS without invasive carcinoma in Sweden between 1992 and 2012. This cohort was linked to the National Cause of Death Registry. Of 6964 women with DCIS, 96 were registered with breast cancer as cause of death (cases). For each case, up to four controls (318; women with DCIS, alive and without metastatic breast cancer at the time of death of the corresponding case) were selected randomly by incidence density sampling. Whole slides of tumour tissue were evaluated for DCIS grade, comedo necrosis, and intensity of periductal lymphocytic infiltrate. Composition of the immune cell infiltrate, expression of oestrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki-67 were scored on tissue microarrays. Clinical information was obtained from medical records. Information on date, site, and histological characteristics of local and distant recurrences was obtained from medical records for both cases and controls. RESULTS: Tumour tissue was analysed from 65 cases and 195 controls. Intense periductal lymphocytic infiltrate around DCIS was associated with an increased risk of later dying from breast cancer (OR 2.21. 95% c.i. 1.01 to 4.84). Tumours with more intense lymphocytic infiltrate had a lower T cell/B cell ratio. None of the other biomarkers correlated with increased risk of breast cancer death. CONCLUSION: The immune response to DCIS may influence the risk of dying from breast cancer.

Rate of residual tumor after repeat surgery for positive margins in ductal carcinoma in Situ, and predictive factors.

AIMS: To evaluate the rate of residual tumor in re-excision specimen of patients with positive margins in ductal carcinoma in situ (DCIS) following breast-conservative surgery, and to identify predictive factors of residual tumor. MATERIAL AND METHODS: We conducted a monocentric, retrospective study, from January 2010 to December 2020. All 103 patients who underwent re-excision for positive margins in DCIS following breast-conservative surgery for in situ or invasive breast carcinoma were included. Positive margins were defined as inferior to 2 mm from the DCIS component. Two groups were defined, depending on the presence of residual tumor or not, and were compared on their clinical and histopathological characteristics to identify predictive factors of residual tumor. RESULTS: Residual tumor was found in re-excision specimen of 46 patients (44.7 %). The risk of residual tumor was increased in patients with more than 2 tumor foci (aOR: 12.4; 95 % CI: 1.2 -124.1; p = 0.032) and in those with extensive margin involvement (aOR: 3.2; 95 % CI: 1.3-8.2; p = 0.013). Finally, surgery performed after 2013 was associated with a lower risk of residual tumor (aOR: 0.23; 95 % CI: 0.09-0.058; p = 0.002). CONCLUSION: The rate of residual tumor in re-excision specimen of patients with positive margins in DCIS is high. Both the number of tumor foci and the extension of positive margins were identified as risk factors. Finally, the surgical learning curve for this procedure seems to be significantly correlated with the risk of residual tumor and needs to be considered.

Personalizing the Treatment of Women with Ductal Carcinoma In Situ (DCIS) Using the DCIS Score: A Qualitative Study on Score Use.

BACKGROUND: A twelve-gene molecular expression assay (DCIS score) may help guide radiation oncology treatment under specific circumstances. We undertook a study to examine radiation oncologist (RO), surgeon, and decision maker views on implementing the DCIS score in practice for women with low-risk DCIS. METHODS: We conducted a qualitative study involving telephone interviews that were audio-recorded and transcribed. Two researchers conducted a thematic analysis of transcripts. RESULTS: Twenty-eight individuals (ROs, breast cancer surgeons, and cancer policy decision makers) were invited to participate; 22 out of the 28 people (79%) agreed. The final sample included 20 participants: 11 of 13 (85%) ROs, 5 of 7 (71%) surgeons, and 4 of 8 (50%) decision makers. Most ROs expressed concerns about overtreatment but could not predict with certainty which low-risk patients could safely avoid radiation. The DCIS score was viewed as contributing valuable personalized risk information as part of treatment decision making that included clinicopathological factors and women's preferences. Future implementation would require guidelines with input from the oncology team. CONCLUSIONS: ROs had concerns about the overtreatment of women with DCIS, but lacked the tools to reliably predict which women could safely avoid radiation. By providing oncologists and women with personalized tumor information, the DCIS score was an important component of treatment decision making.