Management Strategies for Patients With Epithelioid Hemangioendothelioma: Charting an Indolent Disease Course.

BACKGROUND: Epithelioid hemangioendothelioma (EHE) is a malignant vascular neoplasm representing ∼1% of sarcomas. Due to its rarity, its clinical course is not well characterized and optimal treatment remains unknown. MATERIALS AND METHODS: This was a retrospective review of patients with EHE treated at Stanford University between 1998 and 2020. Demographic characteristics, pathology results, treatment modalities, and clinical outcomes were collected from the electronic medical records. RESULTS: A total of 58 patients had a mean age of 50.6 years and a slight female predominance (52%). Primary disease sites were liver (33%), soft tissue (29%), lung (14%), bone (9%), and mediastinum (9%). A majority (55%) had advanced or metastatic disease. Median overall survival (OS) was 16.9 years, with OS 89% at 1 year, 68% at 5 years, and 64% at 10 years. The longest median OS was associated with soft tissue sites and shortest with lung and mediastinal disease (P=0.03). The localized disease had improved median OS compared with metastatic disease (P=0.02). There was no OS difference between tumors >3 cm and those equal or smaller (P=0.85). Surgery was a common treatment (71%), while radiation and ablation were sometimes used (28% and 9%, respectively). The median time to initiating therapy of any kind was 68 days. The median time to systemic therapy was 114 days. CONCLUSIONS: We report on the clinical characteristics and outcomes of patients with EHE at a large academic center. Treatment options included surgical excision, liver transplant, ablation, radiation, and systemic therapy. A subset of patients had indolent disease not requiring treatment upfront.

ReDU: a framework to find and reanalyze public mass spectrometry data.

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

Computational Removal of Undesired Mass Spectral Features Possessing Repeat Units via a Kendrick Mass Filter.

Polymers are a common component of chemical background which complicates data analysis and can impair interpretation. Undesired chemical background cannot always be addressed via pre-analytical methods, chromatography, or existing data processing methods. The Kendrick mass filter (KMF) is presented for the computational removal of undesired signals present in MS1 spectra. The KMF is analogous to mass defect filtering but utilizes homology information via Kendrick mass scaling in combination with chromatographic retention time and the number of observed signals. The KMF is intended to assist in situations in which current data processing methods to remove background, e.g., blank subtraction, are either not possible or effective. The major parameters affecting KMF were investigated using PEG 400 and NIST standard reference material 1950 (metabolites in human plasma). Further exploration of the KMF performance was tested using an extract of a swab known to contain polymers. An illustrative real-world example of skin analysis with polymeric signal is discussed. The KMF is also able to provide a high-level view of the compositionality of data regarding the presence of signals with repeat units and indicate the presence of different polymers. Graphical Abstract ᅟ.