Malignant Phyllodes Tumor Research Articles

Malignant Transformation of Recurrent Benign Phyllodes Tumor: A Case Report and comprehensive review of literature

Introduction: Phyllodes tumors (PTs) of the breast are rare fibroepithelial neoplasms, accounting for less than 1% of all breast tumors. The World Health Organization (WHO) classifies PTs into benign, borderline, or malignant categories based on histological features. While benign PTs generally have a favorable prognosis, they carry a risk of transformation into malignant variants, particularly in cases of recurrence. Case Presentation: A 33-year-old female presented with a recurrent benign PT, previously treated with lumpectomy on two occasions. Recent imaging suggested possible malignant transformation, and histopathological examination confirmed a malignant PT. Discussion: This case highlights the crucial role of imaging in the early detection of malignant transformation in PTs. Surgical management strategies are discussed, with an emphasis on the potential for recurrent benign tumors to progress to malignancy. Conclusion: Regular imaging and close follow-up are essential for early detection of malignant transformation in recurrent PTs, guiding timely and appropriate surgical intervention.

Larger than life: A case of a bleeding giant phyllodes tumor in a COVID-19 positive patient

Introduction: Phyllodes tumor of the breast, also known as cystosarcoma phyllodes, is a rare fibroepithelial tumor that accounts for about 0.3–1% of all breast tumors. Unlike most breast tumors that start from the ducts and gland, phyllodes tumor originates from the stroma. The classification of phyllodes tumor is less important on assessing the risk of recurrence as compared to the presence of tumor-free margins after surgical treatment. Case Report: A 54-year-old female presented at the emergency room with a large, bleeding, left breast mass. The patient tested positive for COVID-19 and was admitted previously at the isolation ward. After medical management of her current condition, the patient underwent wide excision (total mastectomy), left with en bloc resection of pectoralis major with delayed reconstruction via split thickness skin graft. This case is one of the few reported giant phyllodes tumor in the English literature, measuring 30 cm widest dimension. Conclusion: Malignant phyllodes tumor is a rare form of breast malignancy behaving like a sarcoma. A diagnostic dilemma may be encountered in patients with such tumors due to the rarity of these cases and the different presentation of the tumor. High suspicion shall be entertained for patients with breast masses which tend to appear like benign lesions but with sudden enlargement. Adequate surgical intervention shall be done ensuring tumor-free margins. Adjuvant therapy for malignant phyllodes tumor is still controversial but shall be entertained according to the patient’s actual case needs.

Clinical values of nuclear morphometric analysis in fibroepithelial lesions.

Fibroepithelial lesions (FELs) of the breast encompass a broad spectrum of lesions, ranging from commonly encountered fibroadenomas (FAs) to rare phyllodes tumors (PTs). Accurately diagnosing and grading these lesions is crucial for making management decisions, but it can be challenging due to their overlapping features and the subjective nature of histological assessment. Here, we evaluated the role of digital nuclear morphometric analysis in FEL diagnosis and prognosis. A digital nuclear morphometric analysis was conducted on 241 PTs and 59 FAs. Immunohistochemical staining for cytokeratin and Leukocyte common antigen (LCA) was used to exclude non-stromal components, and nuclear area, perimeters, calipers, circularity, and eccentricity in the stromal cells were quantified with QuPath software. The correlations of these features with FEL diagnosis and prognosis was assessed. All nuclear features, including area, perimeter, circularity, maximum caliper, minimum caliper and eccentricity, showed significant differences between FAs and benign PTs (p ≤ 0.002). Only nuclear area, perimeter, minimum caliper and eccentricity correlated significantly with PT grading (p ≤ 0.022). For differentiation of FAs from benign PTs, the model integrating all differential nuclear features demonstrated a specificity of 90% and sensitivity of 70%. For PT grading, the nuclear morphometric score showed a specificity of 78% and sensitivity of 96% for distinguishing benign/borderline from malignant PTs. In addition, a relationship of nuclear circularity was found with PT recurrence. The Kaplan-meier analysis, using the best cutoff determined by ROC curve, showed shorter event free survival in benign PTs with high circularity (chi-square = 4.650, p = 0.031). Our data suggested the digital nuclear morphometric analysis could have potentials to objectively differentiate different FELs and predict PT outcome. These findings could provide the evidence-based data to support the development of deep-learning based algorithm on nuclear morphometrics in FEL diagnosis.

Label-Free Detection of Breast Phyllodes Tumors Based onMultiphoton Microscopy.

Phyllodes tumors (PTs) are rare breast stroma neoplasms, and their accurate identification at various stages is essential for personalized patient treatment. In this study, multiphoton microscopy (MPM) with two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging was used for label-free detection and differentiation of PTs and normal breast tissue. An automated image processing strategy was developed to quantify changes in collagen fiber morphology within the stroma and boundary of PTs, establishing optical diagnostic characteristics of PTs using MPM. The results demonstrated that MPM could be used for the detection of different stages of PTs, and the morphological alterations in collagen fibers could serve as critical indicators of PT malignancy, offering new insights for the diagnosis and grading of benign, borderline, and malignant PTs. It lays the groundwork for the future application of compact MPM for the rapid detection and diagnosis of PTs.

MRI and CT imaging characteristics in parotid tumors with false-negative fine-needle aspirations

BackgroundsPreoperative imaging, particularly with magnetic resonance imaging (MRI) and computed tomography (CT) scans, plays a crucial role in distinguishing between benign and malignant parotid gland tumors, while the reliability of Ultrasound-Guided Fine Needle Aspiration (FNA) in diagnosing these masses remains a topic of debate.MethodsThis two-center retrospective analysis was conducted on 347 patients with parotid gland tumors who had FNA and preoperative imaging (CT or MRI). All patients underwent surgery and final histopathological examination was available, along with complete medical records between January 2008 and May 2023.ResultsAmong the 347 patients, 318 (92%) had benign and 10 (3%) had malignant tumors based on FNA, with 19 (5%) unsatisfactory specimens. Final histological diagnosis revealed 303 (87%) benign and 44 (13%) malignant lesions, with a false-negative rate of 10.6% for FNA. Multivariate analysis identified irregular shape and invasion as independent predictors of malignancy in patient with benign or unsatisfactory FNA results. The odds ratio for irregular shape was 3.06 and for invasion was 12.73.ConclusionImaging characteristics, such as irregular shape and invasion may indicate towards malignant parotid tumors, even in patients with false-negative benign findings in FNA.

Expression patterns of H3K27me3 for differentiation of breast fibroadenomas and phyllodes tumors.

Phyllodes tumors (PTs) are rare breast tumors showing overlapping features with fibroadenomas (FAs). Diagnosis on small biopsies is challenging. New diagnostic markers are needed. Here we evaluated immunohistochemical staining of histone 3 trimethyl-lysine-27 (H3K27me3) as a diagnostic and prognostic marker in a series of PTs. Surgically removed PTs at our institution (September 1990 and July 2022) and control FAs. Tissue micro-arrays (4 cores, 2 mm Ø) stained with H3K27me3, and scored with QuPath-derived H-score. Fisher exact test, Mann-Whitney U-test and chi-squared test used for group comparison. ROC analysis applied to define cutoffs. Cox proportional hazards models were used for assessing disease-free survival (DFS), overall survival (OS), and disease-specific survival (DSS) in PTs. We included 81 patients with PTs and 44 patients with FAs. QuPath-derived H-scores of stromal H3K27me3 were statically significantly lower in PTs than in FAs (p < 0.001). We identified exploratory cutoffs to discriminate FAs from benign and malignant PTs (AUC = 0.78 and 0.73, respectively). No associations between DFS, OS, or DSS and H3K27me3 expression were found. H3K27me3 expression differs between FAs and PTs, indicating potential as diagnostic marker, but it is not predictive for DFS, OS or DSS in PTs. Further validation is needed.

Rare Presentation of Extraskeletal Osteosarcoma Mimicking Phyllodes Tumor

Abstract Introduction/Objective A 57-year-old female presented with a palpable mass in the left breast, measuring up to 9 cm by ultrasound. core needle biopsy identified an atypical spindle cell lesion. The differential diagnosis included a metaplastic carcinoma, borderline phyllodes tumor, malignant phyllodes tumor with potential sarcomatous transformation. Methods/Case Report Histological examination of the tumor was performed, and immunohistochemical stains were conducted to characterize the lesion. Further consultation with a specialized pathologist at the University of Michigan was sought to confirm the diagnosis. Molecular analysis was performed to assess for specific genetic alterations and expression patterns. The histological examination revealed a proliferation of atypical spindle cells forming a fascicular and storiform pattern, with numerous large, pleomorphic, multinucleated tumor cells and a high mitotic rate. Immunohistochemical stains showed strong positivity for CD10 and vimentin, with focal weak expression for desmin, and negativity for a broad panel of cytokeratins and other markers. Consultation with Dr. Abbott at the University of Michigan supported the diagnosis of extraskeletal osteosarcoma. Molecular analysis revealed PD-L1 expression and absence of NTRK gene fusions. FISH analysis showed suggestive alterations including loss of BRAF gene, loss of MYC, and suggestive gains or polysomy of PTEN gene. Results (if a Case Study enter NA) NA Conclusion The case represents a rare presentation of extraskeletal osteosarcoma in the breast, with distinctive histological and immunohistochemical features. The comprehensive workup including histology, immunohistochemistry, and molecular analysis aids in accurate diagnosis and potential therapeutic implications. Further research may elucidate the underlying mechanisms and treatment options for this uncommon malignancy.

Comparison of the Mitotic Count With Various Proliferative Markers for the Effective Differentiation of Benign, Borderline, and Malignant Phyllodes Tumors

Comparison of the Mitotic Count With Various Proliferative Markers for the Effective Differentiation of Benign, Borderline, and Malignant Phyllodes Tumors

Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study.

The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preoperative work-up relies on MR images and fine needle aspiration biopsy, but these diagnostic tools have low sensitivity and specificity, often leading to surgery for diagnostic purposes. The aim of this paper is (1) to develop a machine learning algorithm based on MR images characteristics to automatically classify parotid gland tumours and (2) compare its results with the diagnoses of junior and senior radiologists in order to evaluate its utility in routine practice. While automatic algorithms applied to parotid tumours classification have been developed in the past, we believe that our study is one of the first to leverage four different MRI sequences and propose a comparison with clinicians. In this study, we leverage data coming from a cohort of 134 patients treated for benign or malignant parotid tumours. Using radiomics extracted from the MR images of the gland, we train a random forest and a logistic regression to predict the corresponding histopathological subtypes. On the test set, the best results are given by the random forest: we obtain a 0.720 accuracy, a 0.860 specificity, and a 0.720 sensitivity over all histopathological subtypes, with an average AUC of 0.838. When considering the discrimination between benign and malignant tumours, the algorithm results in a 0.760 accuracy and a 0.769 AUC, both on test set. Moreover, the clinical experiment shows that our model helps to improve diagnostic abilities of junior radiologists as their sensitivity and accuracy raised by 6 % when using our proposed method. This algorithm may be useful for training of physicians. Radiomics with a machine learning algorithm may help improve discrimination between benign and malignant parotid tumours, decreasing the need for diagnostic surgery. Further studies are warranted to validate our algorithm for routine use.

Unusual Presentation of Malignant Phyllodes Tumor with Metastasis to Axillary Nodes - A Case Report and Review of Literature

Unusual Presentation of Malignant Phyllodes Tumor with Metastasis to Axillary Nodes - A Case Report and Review of Literature

Machine Learning Differentiates between Benign and Malignant Parotid Tumors with Contrast-enhanced Ultrasound Features

BackgroundContrast-enhanced ultrasound (CEUS) is frequently used to distinguish benign parotid tumors (BPT) from malignant parotid tumors (MPT). Introducing machine learning (ML) may enable clinicians to preoperatively diagnose parotid tumors precisely. PurposeWe aimed to estimate the diagnostic capability of ML in differentiating BPT from MPT.Study Design, Setting, and Sample: A retrospective cohort study was conducted at the Third Affiliated Hospital of Soochow University. Patients who underwent parotidectomy and CEUS for untreated parotid tumors were included. Patients with recurrent tumors, inadequate specimens, or chemoradiotherapy were excluded. Predictor VariablePredictor variable was preoperative diagnosis coded as BPT and MPT based on the Support Vector Machine (SVM) algorithms, laboratory and CEUS variables. Outcome VariableOutcome variable was pathological diagnosis coded as BPT and MPT. CovariateCovariate was demographics. AnalysesA senior surgeon labeled patients’ tumors as BPT or MPT, creating a clinical diagnosis. Patients were randomly divided into training (70%) and testing (30%) sets. After developing the SVM models using training set, we evaluated their diagnostic performance on testing set with the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity. Delong’s test was used to compare the AUC of SVM models, laboratory and CEUS variables. ResultsThe sample included 48 patients, and the testing set comprised 12 (25%) BPTs and 3 (6.25%) MPTs. Three CEUS variables (width, arrival time (AT) and time to peak (TTP)) and three laboratory variables (lymphocyte count (LC), D-dimer, prognostic nutritional index (PNI)) were identified through recursive feature elimination. Tested on the testing set, the SVM models with linear, polynomial, and radial kernels showed identical performance (AUC = 0.972, accuracy = 93.3%, PPV = 75%, NPV = 100%, sensitivity = 100%, specificity = 91.7%). They had larger AUC than SVM with sigmoid kernel (P = 0.18), width (P = 0.03), LC (P = 0.02), D-dimer (P < 0.01), PNI (P = 0.03), AT (P = 0.02), TTP (P = 0.04), CEUS diagnosis (P < 0.01), and clinical diagnosis (P < 0.01). ConclusionThe SVM algorithm differentiated BPT from MPT better than laboratory and CEUS variables.

Postoperative surgical margin results of the phyllodes tumors from a tertiary hospital.

Phyllodes tumors in the breast are exceptionally uncommon fibroepithelial tumors. In the literature, they are typically categorized as benign phyllodes tumor, borderline phyllodes tumor, and malignant phyllodes tumor. This study aims to assess and present the clinical and surgical outcomes of patients diagnosed with phyllodes tumor. The outcomes of patients aged 18 years and above diagnosed with phyllodes tumor between 2006 and 2023 were retrospectively reviewed. Patients were grouped as benign phyllodes tumor and borderline/malignant phyllodes tumor and compared by clinical and surgical results. Of all 57 patients with phyllodes tumor, 64.9% (n=37) were benign phyllodes tumor and 35.1% (n=20) were borderline/malignant phyllodes tumor [22.8% (n=13) borderline phyllodes tumor and 12.3% (n=7) malignant phyllodes tumor]. When the patients were divided into two groups as benign phyllodes tumor and borderline/malignant phyllodes tumor and compared, our cumulative (total) recurrence rate was 14.0%, with final surgical margin width between groups [(0<final surgical margin<2 mm vs final surgical margin≥2 mm) (p=0.154)] and recurrence [(8.1% benign phyllodes tumor vs 25.0% borderline/malignant phyllodes tumor) (p=0.080)]; there was no significant difference between our rates. Phyllodes tumors of the breast can be followed up with a narrow negative surgical margin (0 mm<final surgical margin<2 mm). However, after the initial surgery, re-excision is recommended for positive margins, while a wider surgical margin (≥10 mm) is not necessary for excision.

The usefulness of evaluating PTEN expression for accurate grading of phyllodes tumors

Phyllodes tumors (PTs) are classified as benign, borderline, or malignant based on histologic characteristics. However, because histological criteria are subjective and diagnosis requires integrating multiple findings, discrepancies often occur between observers. Therefore, it is necessary to discover biomarkers based on the molecular characteristics of PTs. This study aimed to identify dysregulated microRNAs (miRNAs) in PTs through miRNA profiling and determine whether expression of their target genes could be useful as PT biomarkers. MiRNA profiling was performed on 13 PTs (three malignant, three borderline, seven benign) and six fibroadenomas, and predicted target genes of dysregulated miRNAs were selected using three computation algorithms. The expression of two miRNAs, miR-155 and miR-200c, was 1.69-fold and 1.61-fold higher, respectively, in borderline and malignant PT groups than in the benign PT group (p < 0.05). KEGG pathway analysis revealed that the 374 target genes of these two miRNAs (miR-155 and miR200c) participated in several signaling pathways, adherens junction, cell cycle, and pathway in cancer. Immunohistochemical staining for PTEN, one of candidate target genes of miR-200c, was performed on whole slides of PT tissue classified as malignant (n = 9), borderline (n = 12), or benign (n = 21). Stromal tumor cells of high-grade PTs (borderline and malignant) had significantly lower PTEN expression than those of low-grade PTs (benign) (p-value ≤0.001). Semiquantitative analysis of PTEN expression, score 0–8, revealed that it correlated with histologic findings. Low PTEN expression (s-score of 6 or less) was used as a diagnostic criterion for high-grade PTs, it showed 100 % sensitivity and 95.2 % specificity in 42 cases of PTs. Currently, PT grading based solely on subjective histologic findings is challenging, but semiquantitative PTEN expression analysis could provide a more accurate and objective way to grade PTs.

MR Image Fusion-Based Parotid Gland Tumor Detection.

The differentiation of benign and malignant parotid gland tumors is of major significance as it directly affects the treatment process. In addition, it is also a vital task in terms of early and accurate diagnosis of parotid gland tumors and the determination of treatment planning accordingly. As in other diseases, the differentiation of tumor types involves several challenging, time-consuming, and laborious processes. In the study, Magnetic Resonance (MR) images of 114 patients with parotid gland tumors are used for training and testing purposes by Image Fusion (IF). After the Apparent Diffusion Coefficient (ADC), Contrast-enhanced T1-w (T1C-w), and T2-w sequences are cropped, IF (ADC, T1C-w), IF (ADC, T2-w), IF (T1C-w, T2-w), and IF (ADC, T1C-w, T2-w) datasets are obtained for different combinations of these sequences using a two-dimensional Discrete Wavelet Transform (DWT)-based fusion technique. For each of these four datasets, ResNet18, GoogLeNet, and DenseNet-201 architectures are trained separately, and thus, 12 models are obtained in the study. A Graphical User Interface (GUI) application that contains the most successful of these trained architectures for each data is also designed to support the users. The designed GUI application not only allows the fusing of different sequence images but also predicts whether the label of the fused image is benign or malignant. The results show that the DenseNet-201 models for IF (ADC, T1C-w), IF (ADC, T2-w), and IF (ADC, T1C-w, T2-w) are better than the others, with accuracies of 95.45%, 95.96%, and 92.93%, respectively. It is also noted in the study that the most successful model for IF (T1C-w, T2-w) is ResNet18, and its accuracy is equal to 94.95%.

Validation Study of the Newly Proposed Refined Diagnostic Criteria for Malignant Phyllodes Tumor With 136 Borderline and Malignant Phyllodes Tumor Cases.

The World Health Organization (WHO) diagnostic criteria for malignant phyllodes tumor (MPT) may miss a significant number of MPTs with metastatic potential. New refined diagnostic criteria (Refined Criteria) for MPT were recently proposed. The aim of this study is to validate the Refined Criteria. This validation study included 136 borderline (borderline phyllodes tumor [BoPT]) and MPT cases that were not included in the initial study. We evaluated tumor classifications based on both the Refined Criteria and the WHO criteria. The Refined Criteria defines MPT when these criteria are met (1) stromal overgrowth with ≥ 1 feature(s) of marked stromal cellularity, marked stromal cytologic atypia, or ≥10 mitoses per 10 high-power fields (10 mitoses/10 HPFs) or (2) marked stromal cellularity with ≥1 feature(s) of marked stromal cytologic atypia, ≥10 mitoses/10 HPFs or permeative border. The WHO criteria require all 5 morphologic features (stromal overgrowth, permeative border, marked stromal cellularity, marked stromal cytologic atypia, and ≥10 mitoses/10 HPFs) for an MPT diagnosis. Using the Refined Criteria, none of the 61 BoPTs developed metastasis and 40.0% of the 75 MPTs developed metastases; local recurrence was seen in 11.5% BoPTs and 25.3% MPTs. Using the WHO criteria, 9.6% of the 94 BoPTs developed metastases and 50.0% of the 42 MPTs developed metastases; 14.9% of the BoPTs had local recurrence and 28.6% of the MPTs had local recurrence. Nine (30.0%) of the 30 tumors that developed distant metastases were diagnosed as BoPTs by the WHO criteria. When we combined the 75 MPTs from this validation cohort with the 65 MPT cases from the published data using the Refined Criteria, 50 (35.7%) of the 140 MPTs developed metastases, whereas 8 cases with metastases were <5 cm. In the univariate analysis with log-rank test, stromal overgrowth, marked stromal cellularity, marked stromal cytologic atypia, ≥10 mitoses/10 HPFs, presence of heterologous components other than liposarcomatous component, and presence of stromal necrosis were significantly associated with the risk of metastasis (all with P < 0.05). In multivariate analysis with Cox proportional hazard regression, stromal overgrowth and marked stromal cellularity were significantly associated with metastasis (both with P < 0.001). The Refined Criteria are superior to the WHO criteria in predicting the clinical outcomes of BoPTs and MPTs. Using the Refined Criteria, 35.7% of 140 patients with MPT developed metastases, whereas none (0%) of the patients with BoPT developed metastases. Patients with MPT have a high metastatic rate; these patients may benefit from systemic chemotherapy or targeted therapies. In contrast, patients with BoPT may be managed with complete local excision alone without chemotherapy.

Machine learning-assisted diagnosis of parotid tumor by using contrast-enhanced CT imaging features

PurposeThis study aims to develop a machine learning diagnostic model for parotid gland tumors based on preoperative contrast-enhanced CT imaging features to assist in clinical decision-making. Materials and methodsClinical data and contrast-enhanced CT images of 144 patients with parotid gland tumors from the Peking University School of Stomatology Hospital, collected from January 2019 to December 2022, were gathered. The 3D slicer software was utilized to accurately annotate the tumor regions, followed by exploring the correlation between multiple preoperative contrast-enhanced CT imaging features and the benign or malignant nature of the tumor, as well as the type of benign tumor. A prediction model was constructed using the k-nearest neighbors (KNN) algorithm. ResultsThrough feature selection, four key features—morphology, adjacent structure invasion, boundary, and suspicious cervical lymph node metastasis—were identified as crucial in preoperative discrimination between benign and malignant tumors. The KNN prediction model achieved an accuracy rate of 94.44 %. Additionally, six features including arterial phase CT value, age, delayed phase CT value, pre-contrast CT value, venous phase CT value, and gender, were also significant in the classification of benign tumors, with a KNN prediction model accuracy of 95.24 %. ConclusionThe machine learning model based on preoperative contrast-enhanced CT imaging features can effectively discriminate between benign and malignant parotid gland tumors and classify benign tumors, providing valuable reference information for clinicians.

Genomic landscape of malignant phyllodes tumors reveals multiple targetable opportunities.

Malignant phyllodes tumors (MPT) are rare fibroepithelial breast cancers with no known effective systemic therapy; metastatic progression portends a dismal prognosis. We sought to describe the genomic landscape of MPTs through genomic profiling and immunotherapeutic biomarker analysis. Cases of sequenced MPT were identified from a Clinical Laboratory Improvement Amendments-certified, College of American Pathologists-accredited laboratory (Foundation Medicine). All cases underwent genomic profiling using adaptor ligation-based, next-generation sequencing assay of 324 genes. Tumor agnostic immunotherapy biomarkers, microsatellite instability, tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) expression were evaluated. Fisher's Exact Tests and analysis of variance were used to test for differences between groups and for continuous variables as appropriate. Of 135 MPT cases identified; 94 (69.6%) were localized/locally recurrent and 41 (30.4%) were metastatic. Median age was 54 years (range 14-86). The median TMB was 2.5 mut/Mb and 3 were TMB-high (≥10 mut/Mb). 21.4% were PD-L1+ via Dako 22C3 assay (CPS ≥1). Most commonly altered genes included TERT-promoter (69.7%), CDKN2A (45.9%), TP53 (37.8%), NF1 (35.6%), CDKN2B (33.3%), MED12 (28.9%), MTAP (27.7%), KMT2D (22.2%), PIK3CA (20.0%), PTEN (18.5%), and RB1 (18.5%). Several tumors harboring genomic alterations with US Food and Drug Administration-approved indications in other tumor types were found including NF1, PIK3CA, EGFR Exon 19/20 insertions, and BRAF V600E mutations. In the largest genomic evaluation of MPT to date, multiple clinically actionable mutations were found. Routine sequencing of metastatic MPT may provide additional information to guide treatment decisions and clinical trial enrollment.

The Largest Phyllodes Breast Tumor in The World: A Case Report

Phyllodes tumor of the breast is an uncommon fibroepithelial neoplasm constituting 0.3% to 0.5% of female breasttumors. Complete wide local excision is frequently used for treatment and risk reduction in local recurrence. This article aims to report the largest phyllodes breast tumor ever reported worldwide. We report the case of a 24-year-old Thai woman was admitted to our hospital with a massive ulcerofungating right breast mass. Her physical examination revealed a 59 cm diameter mass over her right upper body, in which most parts were infected and ulcerated. A right mastectomy was then performed after the patient had already been treated with intravenous antibiotics for infection control and when her nutrition status had improved. This was followed by Vacuum-Assisted closure of the wound, and split-thickness skin graft, which could be performed after there was a good granulation growth at the wound base. Additionally, after histopathology examination, a 59x53x26 cm malignant Phyllodes tumor with free margins, weighing 14,500 grams, in which there was around 20% tumor necrosis, 12/10 high power fields (HPFs) of Mitosis, and the unaffected nipple was observed. The patient was discharged from the hospital after 45 days, and there was no evidence of local and distant recurrence after a one-year follow-up. Phyllodes tumors are considered unusual fibroepithelial breast tumors that have various biological behaviors, in which surgical resection is a major option for treatment.

Targeted DNA Sequencing in Diagnosis of Malignant Phyllodes Tumors With Emphasis on Tumors With Keratin and p63 Expression

The differential diagnosis of malignant spindle cell neoplasms in the breast most frequently rests between malignant phyllodes tumor (MPT) and metaplastic carcinoma (MBC). Diagnosis of MPT can be challenging due to diffuse stromal overgrowth, keratin (CK) and/or p63 immunopositivity, and absent CD34 expression, which can mimic MBC, especially in core biopsies. Distinction of MPT from MBC has clinical implications, with differences in surgical approach, chemotherapy, and radiation. In this study, we evaluated MPTs (78 tumors, 64 patients) for stromal CK, p63, and CD34 expression and profiled a subset (n = 31) by targeted next-generation DNA sequencing, with comparison to MBC (n = 44). Most MPTs (71%) were CK+ and/or p63+, including 32% CK+ (25/77 focal) and 65% p63+ (32/66 focal, 10/66 patchy, and 1/66 diffuse). Thirty percent of MPTs expressed both CK and p63 (20/66), compared with 95% of MBCs (40/42, P < .001). CK and/or p63 were positive in CD34+ and CD34− MPTs. Recurrent genetic aberrations in MPTs involved TERT, TP53, MED12, CDKN2A, chromatin modifiers, growth factor receptors/ligands, and phosphoinositide-3 kinase (PI-3K) and MAPK pathway genes. Only MED12 (39%, 12/31) and SETD2 (13%, 4/31) were exclusively mutated in MPTs and not MBCs (P < .001 and P = .044, respectively), whereas PIK3R1 mutations were only found in MBCs (37%, 13/35, P < .001). Comparative literature review additionally identified ARID1B, EGFR, FLNA, NRAS, PDGFRB, RAD50, and RARA alterations enriched or exclusively in MPTs vs MBCs. MED12 was mutated in MPTs with diffuse stromal overgrowth (53%, 9/17), CD34− MPTs (41%, 7/17), and CK+ and/or p63+ MPTs (39%, 9/23), including 36% of CD34− MPTs with CK and/or p63 expression. Overall, MED12 mutation and/or CD34 expression were observed in 68% (21/31) MPTs, including 61% (14/23) of CK+ and/or p63+ tumors. Our results emphasize the prevalence of CK and p63 expression in MPTs and demonstrate the diagnostic utility of next-generation DNA sequencing, especially in MPTs with confounding factors that can mimic MBC.

Margin Width and Local Recurrence in Patients with Phyllodes Tumors of the Breast.

Optimal surgical margin width for patients with phyllodes tumors (PTs) of the breast remains debated. The aim of this study was to assess the influence of margin width on long-term local recurrence risk. This was a single-institution retrospective review of patients with confirmed PT treated from 2008-2015. Margins were defined as positive (ink on tumor), narrow (no tumor at inked margin but < 10mm), or widely free (>/= 10mm). LR rates were estimated by the Kaplan-Meier method. Among 117 female patients, histology included 55 (47%) benign, 29 (25%) borderline, and 33 (28%) malignant PT. Final margins were positive in 16 (14%), narrow in 32 (27%), widely free in 64 (55%), and unknown in 5 (4%) patients. Compared with margins > 10 mm, patients with positive and narrow margins had a higher LR risk [HR 10.57 (95% CI 2.48-45.02) and HR 5.66 (95% CI 1.19-26.99), respectively]. Among benign PTs, the 10-year LR-free rates were 100%, 94%, and 66% for widely negative, narrow, and positive margins, respectively (p = 0.056). For borderline/malignant PT, the 10-year LR-free rates were 93% and 57% for widely negative and narrow margins, respectively (p = 0.02), with no difference in LR between narrow and positive margin groups (p = 1.00). For benign PTs, a margin of no ink on tumor appears sufficient to optimize local control. In patients with borderline or malignant PTs, achieving a wide surgical margin may remain important as narrower margins were associated with LR rates comparable to those with positive margins.