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Context.—Phyllodes tumor (PT) of the breast is a rare fibroepithelial neoplasm with risks of local recurrence and uncommon metastases. The classification proposed by the World Health Organization for PTs into benign, borderline, and malignant is based on a combination of several histologic features. The differential diagnosis between PT and fibroadenoma and the histologic grading of PT remain challenging. In addition, the molecular pathogenesis of PT is largely unknown. Objective.—To provide an updated overview of pathologic features, diagnostic terminology, and molecular alterations of PT. Data Sources.—Current English literature related to PT of the breast. Conclusions.—Phyllodes tumor shows a wide spectrum of morphology. There are no clearly distinct boundaries between PT and fibroadenoma. Strict histologic assessment of a combination of histologic features with classification can help to achieve the correct diagnosis and provide useful clinical information. The genomic landscapes of PT generated from genomic sequencing provide insights into the molecular pathogenesis of PT and help to improve diagnostic accuracy and identify potential drug targets in malignant PT.

Fibroepithelial lesions of the breast, comprising the fibroadenoma and phyllodes tumour, are a unique group of neoplasms that share histological characteristics but possess different clinical behaviour. The fibroadenoma is the commonest benign breast tumour in women, while the phyllodes tumour is rare and may be associated with recurrences, grade progression and even metastasis. The diagnosis of fibroadenoma is usually straightforward, with recognised histological variants such as the cellular, complex, juvenile and myxoid forms. The phyllodes tumour comprises benign, borderline and malignant varieties, graded using a constellation of histological parameters based on stromal characteristics of hypercellularity, atypia, mitoses, overgrowth and the nature of tumour borders. While phyllodes tumour grade correlates with clinical behaviour, interobserver variability in assessing multiple parameters that are potentially of different biological weightage leads to significant challenges in accurate grade determination and consequently therapy. Differential diagnostic considerations along the spectrum of fibroepithelial tumours can be problematic in routine practice. Recent discoveries of the molecular underpinnings of these tumours may have diagnostic, prognostic and therapeutic implications.

Fibroepithelial tumours of the breast are biphasic neoplasms composed of both epithelial and stromal elements, including the common fibroadenoma and the infrequent phyllodes tumour. The admixture of epithelium and stroma in the fibroadenoma shows intra- and pericanalicular patterns, and may display a variety of histological changes. Fibroadenoma variants include the cellular, juvenile, myxoid and complex forms. The cellular fibroadenoma may be difficult to distinguish from the benign phyllodes tumour. Stromal mitotic activity can be increased in fibroadenomas in the young and pregnant patients. Phyllodes tumours, neoplasms with the potential for recurrence, show an exaggerated intracanalicular growth pattern with broad stromal fronded architecture and stromal hypercellularity. They are graded into benign, borderline and malignant forms based on histological assessment of stromal features of hypercellularity, atypia, mitotic activity, overgrowth and the nature of the tumour borders. Classification of phyllodes tumours is imperfect, compounded by tumour heterogeneity with overlapping microscopic features among the different grades, especially in the borderline category. Malignant phyllodes tumours can metastasise and cause death. Determining which phyllodes tumours may behave aggressively has been difficult. The discovery of MED12 mutations in the pathogenesis of fibroepithelial tumours, together with other gene abnormalities in the progression pathway, has allowed refinements in diagnosis and prognosis.

Breast fibroepithelial lesions (FELs) comprising fibroadenomas (FAs) and phyllodes tumors (PTs) with varying degrees of malignancy, necessitate tailored surgical approaches. However, preoperative diagnosis of FELs remains challenging and their pathogenesis is not fully elucidated. By integrating methylation and expression data, we revealed substantial molecular deregulation common to FAs and PTs, impacting pathways central to genetic information processing and metabolism. Furthermore, we identified 86 genes exhibiting concurrent differential expression and methylation changes between FAs and PTs, some of which have been implicated in the malignant progression of disease. Subsequently, we constructed two gene-pair signatures: one comprising 158 pairs for distinguishing FAs from PTs, and another with 146 pairs for differentiating benign from malignant PTs. Both signatures achieved AUC exceeding 0.85 in independent surgical and core biopsy datasets. Finally, we identified 99 pathogenic genes exhibiting continuous up-regulation or down-regulation from FAs to malignant PTs. Significant associations were observed between these genes and key cancer-related biological pathways.

The aim of this study was to evaluate the long-term efficacy of a single ultrasound-guided high-intensity focused ultrasound (US-HIFU) treatment in patients with breast fibroadenoma (FA) in terms of volume and pain reduction as well as palpation findings. From december 2013 until november 2014 27 women with a symptomatic FA were treated in one HIFU-session. Follow-up visits were performed after 7 days, 6 months and 1, 2, 3 and 5 years with clinical examination and ultrasound. One year after the procedure, a core needle biopsy of the residual lesion was offered. There was a significant volume reduction 6 months after HIFU from 1083.10 to 347.13 mm 3 (p < 0.0001) with a mean volume reduction ratio (VRR) of 61.63%. Thereafter the FAs showed a further, but no longer significant decrease in size. One patient with an initial incomplete ablation and histologically confirmed persistent vital cells after 1 year showed a strong regrowth after 3 years. Excluding this patient from analysis, the mean VRR at months 12, 24, 36, and 60 was 86.44%, 94.44%, 94.90%, and 97.85%, respectively. Before HIFU, 59.26% of the patients had pain (22.33/100 VAS) which decreased to 6.56/100 after 12 months and remained reduced over the 5 year follow up period. A decrease in palpability from 85.19 to 7.69% was observed within 24 months. A single HIFU intervention let to a substantial reduction in size, pain, and palpability with its most potential effect during the first 12 months. Subsequently, the observed effect remained stable over a 5 year follow up period. Incomplete initial treatment was associated with the risk of regrowth.

The workload of breast cancer pathological diagnosis is very heavy. The purpose of this study is to establish a nomogram model based on pathological images to predict the benign and malignant nature of breast diseases and to validate its predictive performance. In retrospect, a total of 2,723 H&E-stained pathological images were collected from 1,474 patients at Qingdao Central Hospital between 2019 and 2022. The dataset consisted of 509 benign tumor images (adenosis and fibroadenoma) and 2,214 malignant tumor images (infiltrating ductal carcinoma). The images were divided into a training set (1,907) and a validation set (816). Python3.7 was used to extract the values of the R channel, G channel, B channel, and one-dimensional information entropy from all images. Multivariable logistic regression was used to select variables and establish the breast tissue pathological image prediction model. The R channel value, B channel value, and one-dimensional information entropy of the images were identified as independent predictive factors for the classification of benign and malignant pathological images (P < 0.05). The area under the curve (AUC) of the nomogram model in the training set was 0.889 (95% CI: 0.869, 0.909), and the AUC in the validation set was 0.838 (95% CI: 0.7980.877). The calibration curve results showed that the calibration curve of this nomogram model was close to the ideal curve. The decision curve results indicated that the predictive model curve had a high value for auxiliary diagnosis. The nomogram model for the prediction of benign and malignant breast diseases based on pathological images demonstrates good predictive performance. This model can assist in the diagnosis of breast tissue pathological images.

Breast fibroepithelial lesions are biphasic tumors which comprise the common benign fibroadenomas (FAs) and the rarer phyllodes tumors (PTs). This study analyzed 262 (42%) conventional FAs, 45 (7%) cellular FAs, and 321 (51%) benign PTs contributed by the International Fibroepithelial Consortium, using a previously curated 16 gene panel. Benign PTs were found to possess a higher number of mutations, and higher rates of cancer driver gene alterations than both groups of FAs, in particular MED12, TERT promoter, RARA, FLNA, SETD2, RB1, and EGFR. Cases with MED12 mutations were also more likely to have TERT promoter, RARA, SETD2, and EGFR. There were no significant differences detected between conventional FAs and cellular FAs, except for PIK3CA and MAP3K1. TERT promoter alterations were most optimal in discriminating between FAs and benign PTs. Our study affirms the role of sequencing and key mutations that may assist in refining diagnoses of these lesions.

Objective To assess the diagnostic performance of FFDM-based and DBT-based radiomics models to differentiate breast phyllodes tumors from fibroadenomas. Methods 192 patients (93 phyllodes tumors and 99 fibroadenomas) who underwent mammography were retrospectively enrolled. Radiomic features were respectively extracted from FFDM and the clearest slice of DBT images. A least absolute shrinkage and selection operator (LASSO) regression was used to select radiomics features. A combined model was constructed by radiomics and radiological signatures. Machine learning classification was done using logistic regression based on radiomics or radiological signatures (clinical model). Four radiologists were tested on phyllodes tumors and fibroadenomas with and without optimal model assistance. The area under the receiver operating characteristic (ROC) curve (AUC) was computed to assess the performance of each model or radiologist. The Delong test and McNemar's test were performed to compare the performance. Results The combined model yielded the highest performance with an AUC of 0.948 (95%CI: 0.889-1.000) in the testing set, slightly higher than the FFDM-radiomics model (AUC of 0.937, 95%CI: 0.841-0.984) and the DBT-radiomics model (AUC of 0.860, 95%CI: 0.742-0.936) and significantly superior to the clinical model (AUC of 0.719, 95%CI: 0.585-0.829). With the combined model aid, the AUCs of four radiologists were improved from 0.808 to 0.914 (p=0.079), 0.759 to 0.888 (p=0.015), 0.717 to 0.846 (p=0.004), and 0.629 to 0.803 (p=0.001). Conclusion Radiomics analysis based on FFDM and DBT shows promise in differentiating phyllodes tumors from fibroadenomas.

Background When needle core biopsies (NCBs) of the breast reveal fibroepithelial lesions (FELs), excision is often performed to rule out a phyllodes tumor (PT), despite low malignancy rates. Consequently, the natural history of observed FELs is not well described. We analyzed the malignancy risk in excised FELs and the natural history of FELs undergoing active surveillance (AS). Methods We retrospectively studied the pathology and imaging records of 215 patients with FELs ( n  = 252) diagnosed on NCB. Incidence of growth was determined by Kaplan–Meier method. Results Of 252 FELs, 80% were immediately excised and 20% underwent AS. Of the excised FELs, 198 (98%) were benign: fibroadenoma (FA) or benign breast tissue in 137 (68%), benign PT in 59 (29%), or LCIS in 2 (1%). Borderline PT or malignant lesions were found in 4 (2%). On ultrasound, malignant and borderline PTs were larger than benign lesions [median 3.9 vs 1.3 cm, p  = 0.006]. Fifty FELs underwent AS, with a median follow-up of 17 (range 2–79) months. The majority remained stable or decreased in size: at 2 years, only 35% increased in volume by ≥ 50%. Of those tumors undergoing AS that were later excised ( n  = 4), all were benign. Conclusions Almost all FELs (98%) were benign on surgical excision, and the majority undergoing AS remained stable, with benign pathology if later excised. Most FELs on NCB can be safely followed with US, with surgery reserved for patients with FELs that are large, symptomatic, or growing. This could spare most women with FELs unnecessary surgery.

Fibroepithelial lesions of the breast (FELs) are a heterogeneous group of neoplasms exhibiting a histologic spectrum ranging from fibroadenomas (FAs) to malignant phyllodes tumors (PTs). Despite published histologic criteria for their classification, it is common for such lesions to exhibit overlapping features, leading to subjective interpretation and interobserver disagreements in histologic diagnosis. Therefore, there is a need for a more objective diagnostic modality to aid in the accurate classification of these lesions and to guide appropriate clinical management. In this study, the expression of 750 tumor-related genes was measured in a cohort of 34 FELs (5 FAs, 9 cellular FAs, 9 benign PTs, 7 borderline PTs, and 4 malignant PTs). Differentially expressed gene analysis, gene set analysis, pathway analysis, and cell type analysis were performed. Genes involved in matrix remodeling and metastasis (e.g., MMP9, SPP1, COL11A1), angiogenesis (VEGFA, ITGAV, NFIL3, FDFR1, CCND2), hypoxia (ENO1, HK1, CYBB, HK2), metabolic stress (e.g., UBE2C, CDKN2A, FBP1), cell proliferation (e.g., CENPF, CCNB1), and the PI3K-Akt pathway (e.g., ITGB3, NRAS) were highly expressed in malignant PTs and less expressed in borderline PTs, benign PTs, cellular FAs, and FAs. The overall gene expression profiles of benign PTs, cellular FAs, and FAs were very similar. Although a slight difference was observed between borderline and benign PTs, a higher degree of difference was observed between borderline and malignant PTs. Additionally, the macrophage cell abundance scores and CCL5 were significantly higher in malignant PTs compared with all other groups. Our results suggest that the gene-expression-profiling-based approach could lead to further stratification of FELs and may provide clinically useful biological and pathophysiological information to improve the existing histologic diagnostic algorithm.