Development and external validation of a machine learning model for prediction of survival in extremity leiomyosarcoma.

PURPOSE: Machine learning (ML) models have been used to predict cancer survival in several sarcoma subtypes. However, none have investigated extremity leiomyosarcoma (LMS). ML is a powerful tool that has the potential to better prognosticate extremity LMS. METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was queried for cases of histologic extremity LMS (n = 634). Patient, tumor, and treatment characteristics were recorded, and ML models were developed to predict 1-, 3-, and 5-year survival. The best performing ML model was externally validated using an institutional cohort of extremity LMS patients (n = 46). RESULTS: All ML models performed best at the 1-year time point and worst at the 5-year time point. On internal validation within the SEER cohort, the best models had c-statistics of 0.75-0.76 at the 5-year time point. The Random Forest (RF) model was the best performing model and used for external validation. This model also performed best at 1-year and worst at 5-year on external validation with c-statistics of 0.90 and 0.87, respectively. The RF model was well calibrated on external validation. This model has been made publicly available at https://rachar.shinyapps.io/lms_app/ CONCLUSIONS: ML models had excellent performance for survival prediction of extremity LMS. Future studies incorporating a larger institutional cohort may be needed to further validate the ML model for LMS prognostication.

Liver metastasis restrains immunotherapy efficacy via macrophage-mediated T cell elimination.

Metastasis is the primary cause of cancer mortality, and cancer frequently metastasizes to the liver. It is not clear whether liver immune tolerance mechanisms contribute to cancer outcomes. We report that liver metastases diminish immunotherapy efficacy systemically in patients and preclinical models. Patients with liver metastases derive limited benefit from immunotherapy independent of other established biomarkers of response. In multiple mouse models, we show that liver metastases siphon activated CD8+ T cells from systemic circulation. Within the liver, activated antigen-specific Fas+CD8+ T cells undergo apoptosis following their interaction with FasL+CD11b+F4/80+ monocyte-derived macrophages. Consequently, liver metastases create a systemic immune desert in preclinical models. Similarly, patients with liver metastases have reduced peripheral T cell numbers and diminished tumoral T cell diversity and function. In preclinical models, liver-directed radiotherapy eliminates immunosuppressive hepatic macrophages, increases hepatic T cell survival and reduces hepatic siphoning of T cells. Thus, liver metastases co-opt host peripheral tolerance mechanisms to cause acquired immunotherapy resistance through CD8+ T cell deletion, and the combination of liver-directed radiotherapy and immunotherapy could promote systemic antitumor immunity.

Architectural Modification of Conformal PEG-Bottlebrush Coatings Minimizes Anti-PEG Antigenicity While Preserving Stealth Properties.

Poly(ethylene glycol) (PEG), a linear polymer known for its "stealth" properties, is commonly used to passivate the surface of biomedical implants and devices, and it is conjugated to biologic drugs to improve their pharmacokinetics. However, its antigenicity is a growing concern. Here, the antigenicity of PEG is investigated when assembled in a poly(oligoethylene glycol) methacrylate (POEGMA) "bottlebrush" configuration on a planar surface. Using ethylene glycol (EG) repeat lengths of the POEGMA sidechains as a tunable parameter for optimization, POEGMA brushes with sidechain lengths of two and three EG repeats are identified as the optimal polymer architecture to minimize binding of anti-PEG antibodies (APAs), while retaining resistance to nonspecific binding by bovine serum albumin and cultured cells. Binding of backbone- versus endgroup-selective APAs to POEGMA brushes is further investigated, and finally the antigenicity of POEGMA coatings is assessed against APA-positive clinical plasma samples. These results are applied toward fabricating immunoassays on POEGMA surfaces with minimal reactivity toward APAs while retaining a low limit-of-detection for the analyte. Taken together, these results offer useful design concepts to reduce the antigenicity of polymer brush-based surface coatings used in applications involving human or animal matrices.

Engineering the Surface Properties of a Zwitterionic Polymer Brush to Enable the Simple Fabrication of Inkjet-Printed Point-of-Care Immunoassays.

Motivated by the lack of adventitious protein adsorption on zwitterionic polymer brushes that promise low noise and hence high analytical sensitivity for surface-based immunoassays, we explored their use as a substrate for immunoassay fabrication by the inkjet printing of antibodies. We observed that a poly(sulfobetaine)methacrylate brush on glass is far too hydrophilic to enable the noncovalent immobilization of antibodies by inkjet printing. To circumvent this limitation, we developed a series of hybrid zwitterionic-cationic surface coatings with tunable surface wettability that are suitable for the inkjet printing of antibodies but also have low protein adsorption. We show that in a microarray format in which both the capture and detection antibodies are discretely printed as spots on these hybrid brushes, a point-of-care sandwich immunoassay can be carried out with an analytical sensitivity and dynamic range that is similar to or better than those of the same assay fabricated on a PEG-like brush. We also show that the hybrid polymer brushes do not bind anti-PEG antibodies that are ubiquitous in human blood, which can be a problem with immunoassays fabricated on PEG-like coatings.

MiPanda: A Resource for Analyzing and Visualizing Next-Generation Sequencing Transcriptomics Data.

The Michigan Portal for the Analysis of NGS data portal (http://mipanda.org) is an open-access online resource that provides the scientific community with access to the results of a large-scale computational analysis of thousands of high-throughput RNA sequencing (RNA-seq) samples. The portal provides access to gene expression profiles, enabling users to interrogate expression of genes across myriad normal and cancer tissues and cell lines. From these data, tissue- and cancer-specific expression patterns can be identified. Gene-gene coexpression profiles can also be interrogated. The current portal contains data for over 20,000 RNA-seq samples and will be continually updated.

Inkjet-printed point-of-care immunoassay on a nanoscale polymer brush enables subpicomolar detection of analytes in blood.

The ELISA is the mainstay for sensitive and quantitative detection of protein analytes. Despite its utility, ELISA is time-consuming, resource-intensive, and infrastructure-dependent, limiting its availability in resource-limited regions. Here, we describe a self-contained immunoassay platform (the "D4 assay") that converts the sandwich immunoassay into a point-of-care test (POCT). The D4 assay is fabricated by inkjet printing assay reagents as microarrays on nanoscale polymer brushes on glass chips, so that all reagents are "on-chip," and these chips show durable storage stability without cold storage. The D4 assay can interrogate multiple analytes from a drop of blood, is compatible with a smartphone detector, and displays analytical figures of merit that are comparable to standard laboratory-based ELISA in whole blood. These attributes of the D4 POCT have the potential to democratize access to high-performance immunoassays in resource-limited settings without sacrificing their performance.

Poly(oligo(ethylene glycol) methyl ether methacrylate) Brushes on High-κ Metal Oxide Dielectric Surfaces for Bioelectrical Environments.

Advances in electronics and life sciences have generated interest in "lab-on-a-chip" systems utilizing complementary metal oxide semiconductor (CMOS) circuitry for low-power, portable, and cost-effective biosensing platforms. Here, we present a simple and reliable approach for coating "high-κ" metal oxide dielectric materials with "non-fouling" (protein- and cell-resistant) poly(oligo(ethylene glycol) methyl ether methacrylate (POEGMA) polymer brushes as biointerfacial coatings to improve their relevance for biosensing applications utilizing advanced electronic components. By using a surface-initiated "grafting from" strategy, POEGMA films were reliably grown on each material, as confirmed by ellipsometric measurements and X-ray photoelectron spectroscopy (XPS) analysis. The electrical behavior of these POEGMA films was also studied to determine the potential impact on surrounding electronic devices, yielding information on relative permittivity and breakdown field for POEGMA in both dry and hydrated states. We show that the incorporation of POEGMA coatings significantly reduced levels of nonspecific protein adsorption compared to uncoated high-κ dielectric oxide surfaces as shown by protein resistance assays. These attributes, combined with the robust dielectric properties of POEGMA brushes on high-κ surfaces open the way to incorporate this protein and cell resistant polymer interface into CMOS devices for biomolecular detection in a complex liquid milieu.

Correction: Individual Case Analysis of Postmortem Interval Time on Brain Tissue Preservation.

[This corrects the article DOI: 10.1371/journal.pone.0151615.].