Luminal androgen receptor subtype and tumor-infiltrating lymphocytes groups based on triple-negative breast cancer molecular subclassification.

In our previous study, we developed a triple-negative breast cancer (TNBC) subtype classification that correlated with the TNBC molecular subclassification. In this study, we aimed to evaluate the predictor variables of this subtype classification on the whole slide and to validate the model's performance by using an external test set. We explored the characteristics of this subtype classification and investigated genomic alterations, including genomic scar signature scores. First, TNBC was classified into the luminal androgen receptor (LAR) and non-luminal androgen receptor (non-LAR) subtypes based on the AR Allred score (≥ 6 and < 6, respectively). Then, the non-LAR subtype was further classified into the lymphocyte-predominant (LP), lymphocyte-intermediate (LI), and lymphocyte-depleted (LD) groups based on stromal tumor-infiltrating lymphocytes (TILs) (< 20%, > 20% but < 60%, and ≥ 60%, respectively). This classification showed fair agreement with the molecular classification in the test set. The LAR subtype was characterized by a high rate of PIK3CA mutation, CD274 (encodes PD-L1) and PDCD1LG2 (encodes PD-L2) deletion, and a low homologous recombination deficiency (HRD) score. The non-LAR LD TIL group was characterized by a high frequency of NOTCH2 and MYC amplification and a high HRD score.

Prediction of homologous recombination deficiency from Oncomine Comprehensive Assay Plus correlating with SOPHiA DDM HRD Solution.

OBJECTIVE: Poly(ADP-ribose) polymerase (PARP) inhibitors are used for targeted therapy for ovarian cancer with homologous recombination deficiency (HRD). In this study, we aimed to develop a homologous recombination deficiency prediction model to predict the genomic integrity (GI) index of the SOPHiA DDM HRD Solution from the Oncomine Comprehensive Assay (OCA) Plus. We also tried to a find cut-off value of the genomic instability metric (GIM) of the OCA Plus that correlates with the GI index of the SOPHiA DDM HRD Solution. METHODS: We included 87 cases with high-grade ovarian serous carcinoma from five tertiary referral hospitals in Republic of Korea. We developed an HRD prediction model to predict the GI index of the SOPHiA DDM HRD Solution. As predictor variables in the model, we used the HRD score, which included percent loss of heterozygosity (%LOH), percent telomeric allelic imbalance (%TAI), percent large-scale state transitions (%LST), and the genomic instability metric (GIM). To build the model, we employed a penalized logistic regression technique. RESULTS: The final model equation is -21.77 + 0.200 × GIM + 0.102 × %LOH + 0.037 × %TAI + 0.261 × %LST. To improve the performance of the prediction model, we added a borderline result category to the GI results. The accuracy of our HRD status prediction model was 0.958 for the test set. The accuracy of HRD status using GIM with a cut-off value of 16 was 0.911. CONCLUSION: The Oncomine Comprehensive Assay Plus provides a reliable biomarker for homologous recombination deficiency.

Comprehensive Molecular Genetic Analysis in Glioma Patients by Next Generation Sequencing.

BACKGROUND: Glioma is caused by multiple genomic alterations. The evolving classification of gliomas emphasizes the significance of molecular testing. Next generation sequencing (NGS) offers the assessment of parallel combinations of multiple genetic alterations and identifying actionable mutations that guide treatment. This study comprehensively analyzed glioma patients using multi-gene NGS panels, providing powerful insights to inform diagnostic classification and targeted therapies. METHODS: We conducted a targeted panel-based NGS analysis on formalin-fixed and paraffin-embedded nucleic acids extracted from a total of 147 glioma patients. These samples underwent amplicon capture-based library preparation and sequenced using the Oncomine Comprehensive Assay platform. The resulting sequencing data were then analyzed using the bioinformatics tools. RESULTS: A total of 301 mutations, were found in 132 out of 147 tumors (89.8%). These mutations were in 68 different genes. In 62 tumor samples (42.2%), copy number variations (CNVs) with gene amplifications occurred in 25 genes. Moreover, 25 tumor samples (17.0%) showed gene fusions in 6 genes and intragenic deletion in a gene. Our analysis identified actionable targets in several genes, including 11 with mutations, 8 with CNVs, and 3 with gene fusions and intragenic deletion. These findings could impact FDA-approved therapies, NCCN guideline-based treatments, and clinical trials. CONCLUSION: We analyzed precisely diagnosing the classification of gliomas, detailing the frequency and co-occurrence of genetic alterations and identifying genetic alterations with potential therapeutic targets by NGS-based molecular analysis. The high-throughput NGS analysis is an efficient and powerful tool to comprehensively support molecular testing in neurooncology.

Differentiating Uterine Sarcoma From Atypical Leiomyoma on Preoperative Magnetic Resonance Imaging Using Logistic Regression Classifier: Added Value of Diffusion-Weighted Imaging-Based Quantitative Parameters.

OBJECTIVE: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). MATERIALS AND METHODS: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). RESULTS: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10-3 mm²/s vs. 1.23 ± 0.25 10-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). CONCLUSION: The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

Clinical Practice Recommendations for the Use of Next-Generation Sequencing in Patients with Solid Cancer: A Joint Report from KSMO and KSP.

In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

High Expression of NRF2 and Low Expression of KEAP1 Predict Worse Survival in Patients With Operable Triple-Negative Breast Cancer.

PURPOSE: Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer. Currently, no effective treatment options for this condition exist. Nuclear factor erythroid 2-related factor 2 (NRF2), encoded by nuclear factor erythroid-derived 2-like 2 (NFE2L2) gene and its endogenous inhibitor, Kelch-like ECH-associated protein 1 (KEAP1), both participate in cellular defense mechanisms against oxidative stress and contribute to chemoresistance and tumor progression in numerous types of cancers. This study aimed to evaluate the expression patterns of NRF2 and KEAP1 and their prognostic value in operable TNBC. METHODS: Tissue microarrays were prepared using tumor tissues collected from 203 patients with TNBC who underwent surgery. Immunohistochemical staining analyses of NRF2 and KEAP1 were performed. The expression of each immunomarker was categorized into two groups (low or high) based on the median H-score. We analyzed the association between the expression of each immunomarker and clinicopathological information to predict survival. A total of 225 TNBC samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were used to validate our results. RESULTS: NRF2 immunoreactivity was detected in the nucleus and was associated with histologic grade and Ki-67 index, whereas KEAP1 immunoreactivity was detected in the cytoplasm and was associated with the Ki-67 index. Survival analyses showed that NRF2 and KEAP1 expressions were independent prognostic factors for overall survival (OS) (hazard ratio [HR], 2.45 and 0.30; p = 0.015 and 0.016, respectively) and disease-free survival (HR, 2.27 and 0.42; p = 0.019 and 0.022, respectively). NFE2L2 mRNA expression was an independent prognostic factor for OS (HR, 0.59; p = 0.009) in the METABRIC dataset. CONCLUSION: High NRF2 and low KEAP1 expressions independently predicted poor survival in patients with operable TNBC. Further investigations are warranted to examine the possible therapeutic benefits of targeting the KEAP1-NRF2 pathway for TNBC treatment.

Enhanced Risk Stratification in Early-Stage Endometrial Cancer: Integrating POLE through Droplet Digital PCR and L1CAM.

AIM: In order to enhance risk stratification in early-stage endometrial cancer (EC), we conducted molecular classification using surrogate markers, including the POLE droplet digital polymerase chain reaction (ddPCR) and L1CAM immunohistochemistry (IHC). METHOD: We analyzed archival tumor tissue from 183 early-stage EC patients. POLE pathogenic mutations of P286R, V411L, S297F, A456P, and S459F within exons 9, 13, and 14 were detected using a ddPCR, while the mismatch repair (MMR) status was determined by MMR protein IHC and MSI tests. Additionally, we conducted IHC for p53 and L1CAM. RESULTS: The 183 ECs were categorized into four subgroups: POLE-mutated (15.9%), MMR-deficient (29.0%), p53-abnormal (8.7%), and non-specific molecular profile (NSMP, 46.4%). We further subcategorized the NSMP subgroup into NSMP-L1CAMneg (41.5%) and NSMP-L1CAMpos (4.9%), which we refer to as the molecular L1CAM classification. The molecular L1CAM classification was an independent prognostic factor for recurrence-free survival (RFS) and overall survival (OS) (p < 0.001, each). CONCLUSION: Integrating molecular L1CAM classification can enhance risk stratification in early-stage EC, providing valuable prognostic information to guide treatment decisions and improve patient outcomes. POLE ddPCR might be a cost-effective and easy-to-perform test as an alternative to POLE NGS.

Single-center study on clinicopathological and typical molecular pathologic features of metastatic brain tumor.

BACKGROUND: The metastatic brain tumor is the most common brain tumor. The aim of this study was to demonstrate the clinicopathological and molecular pathologic features of brain metastases (BM). METHODS: A total of 269 patients were diagnosed with BM through surgical resection at Seoul St. Mary's Hospital from January 2010 to March 2020. We reviewed the clinicopathological features and molecular status of primary and metastatic brain tissues using immunohistochemistry and molecular pathology results. RESULTS: Among 269 patients, 139 males and 130 females were included. The median age of primary tumor was 58 years (range, 13 to 87 years) and 86 patients (32.0%) had BM at initial presentation. Median BM free interval was 28.0 months (range, 1 to 286 months). The most frequent primary site was lung 46.5% (125/269), and followed by breast 15.6% (42/269), colorectum 10.0% (27/269). Epidermal growth factor receptor (EGFR) mutation was found in 50.8% (32/63) and 58.0% (40/69) of lung primary and BM, respectively. In both breast primary and breast cancer with BM, luminal B was the most frequent subtype at 37.9% (11/29) and 42.9% (18/42), respectively, followed by human epidermal growth factor receptor 2 with 31.0% (9/29) and 33.3% (14/42). Triple-negative was 20.7% (6/29) and 16.7% (7/42), and luminal A was 10.3% (3/29) and 7.1% (3/42) of breast primary and BM, respectively. In colorectal primary and colorectal cancer with BM, KRAS mutation was found in 76.9% (10/13) and 66.7% (2/3), respectively. CONCLUSIONS: We report the clinicopathological and molecular pathologic features of BM that can provide useful information for understanding the pathogenesis of metastasis and for clinical trials based on the tumor's molecular pathology.

Prognostic impact of 18F-FDG PET/CT in pathologic stage II invasive ductal carcinoma of the breast: re-illuminating the value of PET/CT in intermediate-risk breast cancer.

BACKGROUND: The aim of this study is to investigate the impact of 18F-FDG PET/CT on prognosis of stage II invasive ductal carcinoma (IDC) of the breast primarily treated with surgery. METHODS: The clinical records of 297 consecutive IDC with preoperative PET/CT and pathologically staged II in surgery from 2013 to 2017 were retrospectively reviewed. The maximum standardized uptake value (SUVmax), peak standardized uptake value (SUVpeak), tumor-to-liver ratio (TLR), and metabolic tumor volume (MTV) were measured. Association of clinicopathologic factors (age, T stage, N stage, AJCC pathologic stage of IIA or IIB, pathologic prognostic stage, grade, hormonal receptor status, HER2 status, Ki-67, and adjuvant therapy) and PET parameters with DFS was assessed using the Cox proportional hazards model. RESULTS: There were 35 recurrences and 10 deaths at a median follow-up of 49 months (range 0.8 ~ 87.3). All PET parameters were significantly associated with DFS in univariate analysis but in multivariate analysis, SUVpeak was the only factor significantly associated with DFS (hazard ratio 2.58, 95% confidence interval 1.29-5.15, P = 0.007). In cohorts with higher values of SUVpeak or TLR, patients who received adjuvant chemotherapy had significantly superior DFS. CONCLUSION: Metabolic parameters derived from preoperative PET/CT was significantly associated with recurrence in stage II IDC primarily treated with surgery. PET/CT can be a powerful prognostic tool in conjunction with novel staging systems and current biomarkers for patients undergoing contemporary therapy. Our results urge to reconsider the currently underestimated value of PET/CT confined to diagnostic aspect and to newly recognize its prognostic impact in these intermediate-risk breast cancer.

A Case Report of HER2-Amplification in the Breast Without Histological Abnormality.

Atypical ductal hyperplasia and low-grade ductal carcinoma in situ (DCIS) are regarded as precursor lesions of estrogen receptor (ER)-positive invasive breast cancer. In HER2-amplified invasive breast cancer, a precursor lesion before DCIS has not yet been described. Here we introduce a case of HER2-positive lobules in the breast without histological abnormality. A 39-year-old premenopausal woman visited a hospital due to identification of microcalcifications on screening mammography. The subsequent biopsy confirmed high-grade DCIS. She underwent wide excision, and a residual high-grade DCIS with a size of 1.4 cm was found. The tumor cells were hormone receptor positive and HER2 negative on immunohistochemical (IHC) staining. Around DCIS, there were terminal duct lobular units (TDLUs) showing strong HER2 positivity on IHC. These HER2-positive lobules were 7 mm away from the high-grade DCIS and was 1.1 mm in size. These HER2-positive lobules showed no histologic abnormality and had no difference compared with the surrounding normal TDLUs. Nevertheless, in addition to showing HER2 overexpression in IHC, HER2 amplification was also identified in HER2 silver in situ hybridization. HER2 amplification plays an important role in breast cancer development, and HER2 amplification is known to occur as an early event in cancer development. There have been studies identifying driver mutations in normal tissues of other organs. These findings suggest that HER2 amplification in the breast without histological abnormality could occur, and the HER2-positive lobules could be "at risk" for transformation into the precursor lesion of HER2-positive breast cancer, although the biological significance of these findings is unclear.

Prediction of BRAF V600E variant from cancer gene expression data.

Background: BRAF inhibitors have been approved for the treatment of melanoma, non-small cell lung cancer, and colon cancer. Real-time polymerase chain reaction or next-generation sequencing were clinically used for BRAF variant detection to select who responds to BRAF inhibitors. The prediction of BRAF variants using gene expression data might be an alternative test when the direct variant sequencing test is not feasible. In this study, we built a prediction model to detect BRAF V600 variants with mRNA gene expression data in various cancer types. Methods: We adopted a penalized logistic regression for the BRAF V600E variants prediction model. Ten times bootstrap resampling was done with a combined target variable and cancer type stratification. Data preprocessing included knnimputation for missing value imputation, YeoJohnson transformation for skewness correction, center, and scale for standardization, synthetic minority over-sampling technique for class imbalance. Hyperparameter optimization with a grid search was undertaken for model selection in terms of area under the precision-recall. Results: The area under the curve of the receiver operating characteristic curve on the test set was 0.98 in thyroid carcinoma, 0.90 in colon adenocarcinoma, and 0.85 in cutaneous melanoma. The area under the precision-recall of the test set was 0.98 in thyroid carcinoma, 0.71 in colon adenocarcinoma, and 0.65 in cutaneous melanoma. Conclusions: Our penalized logistic regression model can predict BRAF V600E variants with good performance in thyroid carcinoma, cutaneous melanoma, and colon adenocarcinoma.

Prediction of homologous recombination deficiency from cancer gene expression data.

OBJECTIVE: Homologous recombination deficiency (HRD) is the main mechanism of tumorigenesis in some cancers. HRD causes abnormal double-strand break repair, resulting in genomic scars. Some scoring HRD tests have been approved as companion diagnostics of polyadenosine diphosphate-ribose polymerase (PARP) inhibitor treatment. This study aimed to build an HRD prediction model using gene expression data from various cancer types. METHODS: The cancer genome atlas data were used for HRD prediction modeling. A total of 10,567 cases of 33 cancer types were included, and expression data from 5128 out of 20,502 genes were included as predictors. A penalized logistic regression model was chosen as a modeling technique. RESULTS: The area under the curve of the receiver operating characteristic curve of HRD status prediction was 0.98 for the training set and 0.93 for the test set. The accuracy of HRD status prediction was 0.93 for the training set and 0.88 for the test set. CONCLUSIONS: Our study suggests that the HRD prediction model based on penalized logistic regression using gene expression data can be used to select patients for treatment with PARP inhibitors.

Molecular and immunohistochemical comparison between primary gastrointestinal mucosal melanomas and atypical gastrointestinal stromal tumors.

BACKGROUND: It is sometimes challenging to differentiate between gastrointestinal (GI) mucosal melanoma and gastrointestinal stromal tumors (GISTs) because they share some similarities in histological and molecular features. In this study, we investigated their clinicopathological and molecular features. METHODS: Four primary GI mucosal melanomas and 4 atypical GISTs resected from 2017 to 2019 were included. Electronic medical records and histology slides were reviewed and, if needed, immunohistochemical stainings were additionally done. Somatic mutations were analyzed using whole exome sequencing (WES) with tumors and matched normal tissues. RESULTS: By immunohistochemistry, GISTs were positive for CD117 (4 of 4), DOG1 (4 of 4), and CD34 (2 of 4). In contrast, melanomas were positive for CD117 (2 of 4), HMB-45 (4 of 4), Melan-A (4 of 4), and S100 protein (3 of 4). Using WES, the KIT mutation was detected in 2 of 4 GISTs and 1 of 4 melanomas, all of which showed strong CD117 immunoreactivity. PDGFRA mutation was detected in 2 of 4 GISTs but 0 of 4 melanomas. TP53, NF1, RB1, TERT, and KMT2D mutations were detected in 1 of 4 melanomas but 0 of 4 GISTs. A patient with KIT-mutated melanoma was treated with Gleevec and has remained disease-free for 1 year. CONCLUSIONS: GISTs and GI melanomas have a wide histopathological spectrum. Appropriate ancillary studies can be helpful for proper diagnosis and optimal treatment.

Growth Pattern of Hepatic Metastasis as a Prognostic Index Reflecting Liver Metastasis-Associated Survival in Breast Cancer Liver Metastasis.

Breast cancer with liver metastasis (BCLM) frequently cause hepatic failure owing to extensive liver metastasis compared to other cancers; however, there are no clinicopathologic or radiologic parameters for estimating BCLM prognosis. We analyzed the relationship between radiologic and clinicopathologic characteristics with survival outcomes in BCLM. During 2009-2019, baseline and final abdomen computed tomography or liver magnetic resonance imaging of BCLM patients were reviewed. Liver metastasis patterns were classified as oligometastasis (≤3 metastatic lesions), non-confluent or confluent mass formation, infiltration, and pseudocirrhosis. Thirty-one surgical or biopsy specimens for liver metastasis were immunostained for L1 adhesion molecule (L1CAM), Yes-associated protein 1/Transcriptional co-activator with PDZ-binding motif (YAP/TAZ), and ß1-integrin. Out of 156 patients, 77 initially had oligometastasis, 58 had nonconfluent mass formation, 14 had confluent mass formation, and 7 had infiltrative liver metastasis. Confluent or infiltrative liver metastasis showed inferior liver metastasis-associated survival (LMOS) compared to others (p = 0.001). Positive staining for L1CAM and YAP/TAZ was associated with inferior survival, and YAP/TAZ was related to final liver metastasis. Initial hepatic metastasis was associated with LMOS, especially confluent mass formation, and infiltrative liver metastasis pattern was associated with poor survival. Positive staining for YAP/TAZ and L1CAM was associated with inferior LMOS, and YAP/TAZ was related to final liver metastasis.

Avoiding unnecessary intraoperative sentinel lymph node frozen section biopsy of patients with early breast cancer.

Purpose: After the publication of the ACOSOG (American College of Surgeons Oncology Group) Z0011 trial, the rate of axillary lymph node dissection has reduced. Thus, the need for intraoperative frozen section biopsy of sentinel lymph nodes (SLNs) has become controversial. We identified patients for whom intraoperative SLN frozen section biopsy could be omitted and found that frozen section biopsy rate can be reduced. Methods: We reviewed the records of patients with tumors ≤5 cm in diameter who underwent breast-conserving surgery between January 2013 and December 2019 at Seoul St. Mary's Hospital. Clinicopathological and imaging characteristics were compared according to number of positive SLNs (0-2 SLNs positive vs. ≥3 SLNs positive). Results: A total of 1,983 patients were included in this study. Thirty-two patients (1.6%) had at least 3 positive SLNs. Patients with ≥3 positive SLNs had significantly larger tumors and were more frequently high-grade tumors (P < 0.001 and P = 0.002, respectively). Identification of suspicious lymph nodes on imaging studies was also associated with the presence of ≥3 positive SLNs (hazard ratio, 11.54; 95% confidence interval, 4.42-30.10). All patients with none or only 1 suspicious lymph node on any imaging modality (n = 647, 32.6%) had 0-2 positive SLNs. Also, among patients with clinical T1-stage tumors and at least 2 suspicious lymph nodes on only 1 imaging modality (n = 514, 25.9%), only 2 cases had ≥3 positive SLNs. Conclusion: We found that intraoperative SLN frozen biopsy could be omitted in patients using tumor size and axillary lymph node status on imaging modality.

Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach.

BACKGROUND: Studies correlating specific genetic mutations and treatment response are ongoing to establish an effective treatment strategy for gastric cancer (GC). To facilitate this research, a cost- and time-effective method to analyze the mutational status is necessary. Deep learning (DL) has been successfully applied to analyze hematoxylin and eosin (H and E)-stained tissue slide images. AIM: To test the feasibility of DL-based classifiers for the frequently occurring mutations from the H and E-stained GC tissue whole slide images (WSIs). METHODS: From the GC dataset of The Cancer Genome Atlas (TCGA-STAD), wild-type/mutation classifiers for CDH1, ERBB2, KRAS, PIK3CA, and TP53 genes were trained on 360 × 360-pixel patches of tissue images. RESULTS: The area under the curve (AUC) for the receiver operating characteristic (ROC) curves ranged from 0.727 to 0.862 for the TCGA frozen WSIs and 0.661 to 0.858 for the TCGA formalin-fixed paraffin-embedded (FFPE) WSIs. The performance of the classifier can be improved by adding new FFPE WSI training dataset from our institute. The classifiers trained for mutation prediction in colorectal cancer completely failed to predict the mutational status in GC, indicating that DL-based mutation classifiers are incompatible between different cancers. CONCLUSION: This study concluded that DL could predict genetic mutations in H and E-stained tissue slides when they are trained with appropriate tissue data.

A multicenter study of interobserver variability in pathologic diagnosis of papillary breast lesions on core needle biopsy with WHO classification.

BACKGROUND: Papillary breast lesions (PBLs) comprise diverse entities from benign and atypical lesions to malignant tumors. Although PBLs are characterized by a papillary growth pattern, it is challenging to achieve high diagnostic accuracy and reproducibility. Thus, we investigated the diagnostic reproducibility of PBLs in core needle biopsy (CNB) specimens with World Health Organization (WHO) classification. METHODS: Diagnostic reproducibility was assessed using interobserver variability (kappa value, κ) and agreement rate in the pathologic diagnosis of 60 PBL cases on CNB among 20 breast pathologists affiliated with 20 medical institutions in Korea. This analysis was performed using hematoxylin and eosin (H&E) staining and immunohistochemical (IHC) staining for cytokeratin 5 (CK5) and p63. The pathologic diagnosis of PBLs was based on WHO classification, which was used to establish simple classifications (4-tier, 3-tier, and 2-tier). RESULTS: On WHO classification, H&E staining exhibited 'fair agreement' (κ = 0.21) with a 47.0% agreement rate. Simple classifications presented improvement in interobserver variability and agreement rate. IHC staining increased the kappa value and agreement rate in all the classifications. Despite IHC staining, the encapsulated/solid papillary carcinoma (EPC/SPC) subgroup (κ = 0.16) exhibited lower agreement compared to the non-EPC/SPC subgroup (κ = 0.35) with WHO classification, which was similar to the results of any other classification systems. CONCLUSIONS: Although the use of IHC staining for CK5 and p63 increased the diagnostic agreement of PBLs in CNB specimens, WHO classification exhibited a higher discordance rate compared to any other classifications. Therefore, this result warrants further intensive consensus studies to improve the diagnostic reproducibility of PBLs with WHO classification.

Imaging characteristics of young age breast cancer (YABC) focusing on pathologic correlation and disease recurrence.

The purpose of this study is to investigate imaging characteristics of young age breast cancer (YABC) focusing on correlation with pathologic factors and association with disease recurrence. From January 2017 to December 2019, patients under 40 years old who were diagnosed as breast cancer were enrolled in this study. Morphologic analysis of tumor and multiple quantitative parameters were obtained from pre-treatment dynamic contrast enhanced breast magnetic resonance imaging (DCE-MRI). Tumor-stroma ratio (TSR), microvessel density (MVD) and endothelial Notch 1 (EC Notch 1) were investigated for correlation with imaging parameters. In addition, recurrence associated factors were assessed using both clinico-pathologic factors and imaging parameters. A total of 53 patients were enrolled. Several imaging parameters derived from apparent diffusion coefficient (ADC) histogram showed negative correlation with TSR; and there was negative correlation between MVD and Ve in perfusion analysis. There were nine cases of recurrences with median interval of 16 months. Triple negative subtype and low CD34 MVD positivity in Notch 1 hotspots showed significant association with tumor recurrence. Texture parameters reflecting tumor sphericity and homogeneity were also associated with disease recurrence. In conclusion, several quantitative MRI parameters can be used as imaging biomarkers for tumor microenvironment and can predict disease recurrence in YABC.

Comparison of the Incidence of Capsular Formation in Two-Stage, Implant-Based Breast Reconstruction Using an Insertion Funnel and Sizer.

PURPOSE: Capsular formation around breast implants can produce various complications, including erythema, tenderness, discomfort, and breast deformation. Moreover, the capsule is thought to be correlated with breast implant-associated anaplastic large cell lymphoma. The proposed technique of capsule reduction can prevent some of these complications. Thus, the authors suggest a no-touch technique in two-stage, implant-based breast reconstruction. Patients and Methods. This single-center retrospective study evaluated the medical records and digitalized pathological slides of patients who underwent two-stage, implant-based breast reconstruction between February 2018 and May 2019. The selected patients were divided into group A and group B. Group A underwent a no-touch technique that included the following two steps: (1) using a sizer as the frame to create the submuscular and acellular dermal matrix (ADM) pocket for expander insertion and (2) inserting the expander through the funnel. After the second stage of implant insertion, the capsule was harvested for biopsy of the ADM, chest wall, and muscle. RESULTS: This study included 33 breasts (31 patients): 18 in group A and 15 in group B. The capsular thicknesses of the ADM, the chest wall, and the muscle of group A were significantly thinner than those in group B. Pearson's correlation coefficient indicated negative correlations between capsular thickness and age; underlying disease; lesion side; interval of two-stage implant insertion; size of the expander; and radiotherapy, chemotherapy, or hormone therapy. CONCLUSION: To reduce the incidence of capsular formation following breast reconstruction using prostheses, a no-touch technique that uses a funnel and sizer to avoid implant contact is both efficient and beneficial.