Colitis as the Initial Presentation of Eosinophilic Granulomatosis with Polyangiitis.

A male patient in his early sixties with recurrent diarrhea was transferred to our hospital. The patient did not have any pulmonary or upper respiratory symptoms. He was noted to have peripheral eosinophilia. Further workup revealed a negative antineutrophilic cytoplasmic antibody titer but a positive myeloperoxidase antibody and positive proteinase 3 antibodies. A colon biopsy also revealed eosinophilic-rich granulomas in the mucosa, confirming a diagnosis of eosinophilic granulomatosis with polyangiitis. On cardiac imaging, eosinophilic myocarditis was also discovered. To treat active severe EGPA, the patient received high-dose corticosteroids and intravenous cyclophosphamide. The occurrence of gastrointestinal involvement as an initial manifestation of eosinophilic granulomatosis with polyangiitis is infrequent, emphasizing the significance of its recognition. This case underscores the importance of identifying and diagnosing such atypical presentations to facilitate timely and appropriate management.

NuCLS: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer.

BACKGROUND: Deep learning enables accurate high-resolution mapping of cells and tissue structures that can serve as the foundation of interpretable machine-learning models for computational pathology. However, generating adequate labels for these structures is a critical barrier, given the time and effort required from pathologists. RESULTS: This article describes a novel collaborative framework for engaging crowds of medical students and pathologists to produce quality labels for cell nuclei. We used this approach to produce the NuCLS dataset, containing >220,000 annotations of cell nuclei in breast cancers. This builds on prior work labeling tissue regions to produce an integrated tissue region- and cell-level annotation dataset for training that is the largest such resource for multi-scale analysis of breast cancer histology. This article presents data and analysis results for single and multi-rater annotations from both non-experts and pathologists. We present a novel workflow that uses algorithmic suggestions to collect accurate segmentation data without the need for laborious manual tracing of nuclei. Our results indicate that even noisy algorithmic suggestions do not adversely affect pathologist accuracy and can help non-experts improve annotation quality. We also present a new approach for inferring truth from multiple raters and show that non-experts can produce accurate annotations for visually distinctive classes. CONCLUSIONS: This study is the most extensive systematic exploration of the large-scale use of wisdom-of-the-crowd approaches to generate data for computational pathology applications.

Somatic-Type Yolk Sac Tumor Arising as a Predominant Component of Bladder Urothelial Carcinoma.

Germ cell differentiation has been described in association with somatic tumors arising from several organ systems; rare cases arising from urothelium have been reported. Here we present a 62-year-old male with a remote history of lung cancer, a left adrenal gland mass, and a 5.6 cm left bladder wall mass; cystoscopy demonstrated a large papillary mass on the left anterior bladder wall. A transurethral resection specimen was sent for review in consultation and showed extensive papillary structures with thin fibrovascular cores lined by neoplastic cells with clear cytoplasm. These neoplastic cells were diffusely positive for pancytokeratin, CDX2 (caudal-type homebox 2), SALL4 (sal-like transcription factor 4), glypican-3, AFP (alpha-fetoprotein), while negative for PAX-8 (paired box gene 8), NKX3.1 (NK3 homeobox 1), PSA (prostate specific antigen), TTF-1 (thyroid transcription factor 1), Napsin A, inhibin, and OCT4 (octamer-binding transcription factor 4). Conventional urothelial conventional carcinoma and focal squamous differentiation were also identified as minor components. Urothelial carcinoma was focally positive for GATA3 (GATA-binding protein 3) and p63; SALL4 and glypican-3 were negative. Overall findings supported a yolk sac tumor with a smaller component of squamous cell carcinoma (<1%). Subsequent cystectomy showed similar morphologic features and immunoprofile in addition to foci of urothelial carcinoma and urothelial carcinoma in situ. No chromosome 12p abnormalities were identified by fluorescent in-situ hybridization study. A diagnosis of yolk sac tumor derived from urothelial carcinoma was made. Yolk sac tumor should be considered in the differential diagnosis of a high-grade urothelial carcinoma, particularly when glandular or other unusual architectural patterns are present. A somatic origin with underlying genomic instability similar to what has been described in the uterus and ovaries is suggested.

Predictors of Survival among Early Onset Pancreatic Adenocarcinoma Patients A Tertiary Care Center Experience.

OBJECTIVES: To characterize clinical features of early onset pancreatic adenocarcinoma (EOPC) patients and explore prognostic factors affecting their survival. Methods: Retrospective review of 95 patients, 45 years old, who presented to the University of Alabama Hospitals with pancreatic adenocarcinoma from September 1998 to June 2018. Results: Median survival time was 12.9 months for all patients. Obesity, male gender, race, and tumor location were not associated with survival. Smoking at time of diagnosis increased risk of death by three folds (HR 3.05, 95% CI, 1.45 - 6.40). Risk of death decreased by 64% (HR 0.36, 95% CI, 0.16 - 0.78) if patients underwent surgery. Median survival was 119.5 months for stage I, 29.9 months for stage II, 23.23 months for stage III, and 6.3 months for stage IV patients. The survival benefit of chemotherapy was only significant with the use of FOLFIRINOX. Conclusions: Some established prognostic features in typical pancreatic adenocarcinoma patients are not predictive of survival in young patients. Cigarette smoking, a known risk factor for the development of EOPC, is also a significant predictor of survival in this patient population. Efforts to improve prognosis of EOPC include early detection, tobacco control, individualized treatment protocols, and studying the biological behavior.

Biochemical Predictors of Response to Neoadjuvant Therapy in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is becoming increasingly more common. Treatment for PDAC is dependent not only on stage at diagnosis, but complex anatomical relationships. Recently, the therapeutic approach to this disease has shifted from upfront surgery for technically resectable lesions to a neoadjuvant therapy first approach. Selecting an appropriate regimen and determining treatment response is crucial for optimal oncologic outcome, especially since radiographic imaging has proven unreliable in this setting. Tumor biomarkers have the potential to play a key role in treatment planning, treatment monitoring, and surveillance as an adjunct laboratory test. In this review, we will discuss common chemotherapeutic options, mechanisms of resistance, and potential biomarkers for PDAC. The aim of this paper is to present currently available biomarkers for PDAC and to discuss how these markers may be affected by neoadjuvant chemotherapy treatment. Understanding current chemotherapy regiments and mechanism of resistance can help us understand which markers may be most affected and why; therefore, determining to what ability we can use them as a marker for treatment progression, prognosis, or potential relapse.