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Considering the high expression of B7-H3 (CD276) on diffuse intrinsic pontine glioma (DIPG) and preliminary evidence that repeated locoregional delivery of CAR T cells to patients with CNS tumors was feasible and tolerable, we open the phase 1 trial BrainChild-03 (NCT04185038). Children with DIPG in Dose Regimen 1 received 40 intraventricular B7H3CAR doses, with the two patients enrolling post-progression surviving >400 days from initial CAR T infusion. To evaluate for immune and tumor responses that may correlate with clinical and radiographic evaluations, we performed targeted proteomic analysis on serial CSF and serum biospecimens. MRM-MS is a targeted mass spectrometry that provides sensitive measurement of proteins in cancer tissues and fluids. In 2 patients with longitudinal biospecimens, we identified 50 CSF and 59 serum proteins above level of detection. In general, there were fewer serum fluctuations compared to the CSF, supporting that intracranial delivery provides local immune activation. Sharp fluctuations of several immunoregulatory peptides were measured in the CSF at pre and post infusion timepoints, including BCL10, CXCL13, TIM-3, ICOSLG, and PD-L2. Notably, several analytes tracked consistently in the CSF of both patients, including markers of macrophage maturation and immune cell recruitment, including CD14, CD163, CD44, CSF-1, CXCL13 and VCAM-1. B7-H3 was detected in the CSF and serum of both patients. S005, who progressed on protocol therapy, had a sharp increase in B7-H3 in the CSF during Course 2, while S008, who had clinical improvement on protocol therapy, had consistently lower B7-H3 present. Notably, serum B7-H3 steadily declined in both patients over time, with the exception of a transient increase in S005 between Courses 4 and 5. Future work for all enrolled patients with DIPG will explore the correlation of these targeted proteomic measurements with clinical end points for potential use as markers of efficacy of therapy or adverse events.

We proposed to perform a proteomic screen of a retroviral-expressed human breast cancer cDNA library in an attempt to identify novel secreted or shed proteins as candidate soluble biomarkers in human breast cancer. Although we encountered difficulties in generating a viable cDNA library, we were able to show that C-terminal HA-epitope tagged proteins can be efficiently expressed in human breast cancer cell lines by retroviral gene transfer. In addition, human breast cancer cells have an active ectodomain sheddase machinery and are capable of releasing large amounts of over-expressed protein. Future studies will be done to perfect our retroviral expression vectors and to subclone pre-made cDNA libraries into suitable expression vectors.

We describe an integrated suite of algorithms and software for general accurate mass and time (AMT) tagging data analysis of mass spectrometry data. The AMT approach combines identifications from liquid chromatography (LC) tandem mass spectrometry (MS/MS) data with peptide accurate mass and retention time locations from high-resolution LC-MS data. Our workflow includes the traditional AMT approach, in which MS/MS identifications are located in external databases, as well as methods based on more recent hybrid instruments such as the LTQ-FT or Orbitrap, where MS/MS identifications are embedded with the MS data. We demonstrate our AMT workflow's utility for general data synthesis by combining data from two dissimilar biospecimens. Specifically, we demonstrate its use relevant to serum biomarker discovery by identifying which peptides sequenced by MS/MS analysis of tumor tissue may also be present in the plasma of tumor-bearing and control mice. The analysis workflow, referred to as msInspect/AMT, extends and combines existing open-source platforms for LC-MS/MS (CPAS) and LC-MS (msInspect) data analysis and is available in an unrestricted open-source distribution.

Recent improvements in mass spectrometry (MS) technology led to an explosive amount of MS data collected and shared. A typical liquid chromatography/mass spectrometry (LC/MS) "image" from the instrument used in this study consists of 4 GB of data. To reduce the bit rate required to code the MS data below that of the authors' previous (lossless) algorithm, we introduce a technique for near-lossless compression. It guarantees that each decompressed sample differs from its original value by no more than a user-specified quantity defined as the target maximum absolute distortion (MAD). We evaluate the proposed method by introducing feature-based metrics applied to the decompressed MS data and show that the MAD-based compression outperforms a traditional coding algorithm aimed at minimizing the mean squared error.

The open-source Computational Proteomics Analysis System (CPAS) contains an entire data analysis and management pipeline for Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS) proteomics, including experiment annotation, protein database searching and sequence management, and mining LC-MS/MS peptide and protein identifications. CPAS architecture and features, such as a general experiment annotation component, installation software, and data security management, make it useful for collaborative projects across geographical locations and for proteomics laboratories without substantial computational support.