Modern Pathology最新文献

Accurate recurrence risk stratification is crucial for optimizing treatment plans for breast cancer patients. Current prognostic tools like Oncotype DX offer valuable genomic insights into hormone receptor-positive and human epidermal growth factor receptor-negative patients but are limited by cost and accessibility, particularly in underserved populations. In this study, we present Deep-Breast-Cancer-Recurrence (BCR)-Auto, a deep learning-based computational pathology approach that predicts breast cancer recurrence risk from routine hematoxylin and eosin-stained whole slide images. Our methodology was validated on 2 independent cohorts: The Cancer Genome Atlas Program breast cancer data set and an in-house data set from The Ohio State University. Deep-BCR-Auto demonstrated robust performance in stratifying patients into low- and high-recurrence risk categories. On The Cancer Genome Atlas Program breast cancer data set, the model achieved an area under the receiver operating characteristic curve of 0.827, significantly outperforming the existing weakly supervised models (P = .041). In the independent The Ohio State University data set, Deep-BCR-Auto maintained strong generalizability, achieving an area under the receiver operating characteristic curve of 0.832, along with 82.0% accuracy, 85.0% specificity, and 67.7% sensitivity. These findings highlight the potential of computational pathology as a cost-effective alternative for recurrence risk assessment, broadening access to personalized treatment strategies. This study underscores the clinical utility of integrating deep learning-based computational pathology into routine pathological assessment for breast cancer prognosis across diverse clinical settings.

Cyclin-dependent kinase 4 and 6 inhibitor (CDK4/6i) with endocrine therapy benefits patients with hormone receptor-positive, human epidermal growth receptor 2-negative breast carcinomas. However, most tumors develop resistance to CDK4/6i during the course of therapy. Although preclinical studies have proposed molecular mechanisms for the resistance, predictive markers are yet to be discovered. We investigated the tumor molecular profiling in 42 patients with advanced-stage breast carcinoma who received CDK4/6i therapy. The tumors carrying a GATA-binding protein 3 (GATA3) gene mutation, mainly a frameshift variant, showed a better treatment response compared with other tumors. Furthermore, we explored the potential underlying mechanism of this association. To that end, nuclear expression of p18, one of the INK family proteins, was found to be positively associated with the GATA3 mutation, as well as a CDK4/6i treatment response. Therefore, our study suggests that a GATA3 gene mutation, collaborating with p18 protein expression in tumor nuclei, may have a predictive value for CDK4/6i therapy in breast carcinoma.

Computational pathology-based models are becoming increasingly popular for extracting biomarkers from images of cancer tissue. However, their validity is often only demonstrated on a single unseen validation cohort, limiting insights into their generalizability and posing challenges for explainability. In this study, we developed models to predict overall survival using hematoxylin and eosin slides from formalin-fixed paraffin-embedded samples in head and neck squamous cell carcinoma. By validating our models across diverse squamous tumor entities, including head and neck (hazard ratio [HR], 1.58; 95% CI, 1.17-2.12; P = .003), esophageal (nonsignificant), lung (HR, 1.31; 95% CI, 1.13-1.52; P < .001), and cervical (HR, 1.39; 95% CI, 1.10-1.75; P = .005) squamous cell carcinomas, we showed that the predicted risk score captures relevant information for survival beyond head and neck squamous cell carcinoma. Correlation analysis indicated that the predicted risk score is strongly associated with various clinical factors, including human papillomavirus status, tumor volume, and smoking history, although the specific factors vary across cohorts. These results emphasize the relevance of comprehensive validation and in-depth assessment of computational pathology-based models to better characterize the underlying patterns they learn during training.

This investigation describes the clinicoradiologic, pathologic, and molecular features of a unique soft tissue tumor characterized by a peripheral shell of bone and composed of bland myoid spindle and epithelioid cells that are keratin-positive. Our study cohort consists of 6 men and 6 women, with a mean age of 32 years. The tumors arose in the extremities (n = 9) and proximal limb girdle (n = 3) and were equally distributed between deep and superficial soft tissues. Patients reported dull painless masses of several months to >10 years duration (mean: 2.9 years). Imaging demonstrated a complete or partial peripheral shell of bone that could extend centrally, and the tumor's mean size was 5.7 cm. Histologically, the tumors were composed of uniform, eosinophilic myoid spindled cells growing in sheets and intersecting fascicles, surrounded by mature lamellar and/or woven bone. Also present was an admixed component of intermediate-sized epithelioid cells with eosinophilic cytoplasm. Mitotic activity was consistently low. Immunohistochemistry showed strong multifocal staining for keratins, and 50% (5/10) showed focal staining for S100; however, all were negative for SMA, desmin, SOX10, ERG, and CD34. Genetic analysis by multiple targeted RNA sequencing panels was negative (n = 10); however, whole transcriptome sequencing (n = 8) revealed a recurrent and novel in-frame SRSF7::NFATC3 fusion in 4 tumors. Dual fluorescence in situ hybridization probes for SRSF7::NFATC3 successfully confirmed this fusion and identified a fifth case, which had not undergone whole transcriptome sequencing but was negative by a targeted RNA fusion panel. Methylation profiling (n = 8) demonstrated a shared epigenetic profile distinct from other entities. Clinical follow-up (n = 11) showed no evidence of recurrence after primary excision with a mean of 41.6 months. In summary, we describe a novel soft tissue tumor designated "ossifying spindled and epithelioid tumor" as a descriptive histologic term that also emphasizes its close radiologic mimic, ossifying fibromyxoid tumor. All cases have behaved in a benign fashion without recurrence following simple excision. Awareness of this entity is important, so that it can be distinguished from other neoplasms that have more aggressive biological potential.