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Phosphorylation events within cancer cells often become dysregulated, leading to oncogenic signaling and abnormal cell growth. Phosphopeptides derived from aberrantly phosphorylated proteins that are presented on tumors and not on normal tissues by human leukocyte antigen (HLA) class I molecules are promising candidates for future cancer immunotherapies, because they are tumor specific and have been shown to elicit cytotoxic T cell responses. Robust phosphopeptide enrichments that are suitable for low input amounts must be developed to characterize HLA-associated phosphopeptides from clinical samples that are limited by material availability. We present two complementary mass spectrometry–compatible, iron(III)-immobilized metal affinity chromatography (IMAC) methods that use either nitrilotriacetic acid (NTA) or iminodiacetic acid (IDA) in-house-fabricated columns. We developed these protocols to enrich for subfemtomole-level phosphopeptides from cell line and human tissue samples containing picograms of starting material, which is an order of magnitude less material than what is commonly used. In addition, we added a peptide esterification step to increase phosphopeptide specificity from these low-input samples. To date, hundreds of phosphopeptides displayed on melanoma, ovarian cancer, leukemia and colorectal cancer have been identified using these highly selective phosphopeptide enrichment protocols in combination with a program called ‘CAD Neutral Loss Finder’ that identifies all spectra containing the characteristic neutral loss of phosphoric acid from phosphorylated serine and threonine residues. This methodology enables the identification of HLA-associated phosphopeptides presented by human tissue samples containing as little as nanograms of peptide material in 2 d.

Background Electron Transfer Dissociation [ETD] can dissociate multiply charged precursor polypeptides, providing extensive peptide backbone cleavage. ETD spectra contain charge reduced precursor peaks, usually of high intensity, and whose pattern is dependent on its parent precursor charge. These charge reduced precursor peaks and associated neutral loss peaks should be removed before these spectra are searched for peptide identifications. ETD spectra can also contain ion-types other than c and z˙. Modifying search strategies to accommodate these ion-types may aid in increased peptide identifications. Additionally, if the precursor mass is measured using a lower resolution instrument such as a linear ion trap, the charge of the precursor is often not known, reducing sensitivity and increasing search times. We implemented algorithms to remove these precursor peaks, accommodate new ion-types in noise filtering routine in OMSSA and to estimate any unknown precursor charge, using Linear Discriminant Analysis [LDA]. Results Spectral pre-processing to remove precursor peaks and their associated neutral losses prior to protein sequence library searches resulted in a 9.8% increase in peptide identifications at a 1% False Discovery Rate [FDR] compared to previous OMSSA filter. Modifications to the OMSSA noise filter to accommodate various ion-types resulted in a further 4.2% increase in peptide identifications at 1% FDR. Moreover, ETD spectra when searched with charge states obtained from the precursor charge determination algorithm is shown to be up to 3.5 times faster than the general range search method, with a minor 3.8% increase in sensitivity. Conclusion Overall, there is an 18.8% increase in peptide identifications at 1% FDR by incorporating the new precursor filter, noise filter and by using the charge determination algorithm, when compared to previous versions of OMSSA.

An integrated software package for testing infants in a habituation procedure is described. The software is written for an Apple II computer with a minimum of 64K of memory. Additional interface cards are required for timing responses and displaying dynamic stimuli. The software is divided into four independent modules: (1) Configure Experiment allows the experimenter to design a specific experiment. (2) Run Experiment controls the running of a previously configured habituation experiment. (3) Calculate Reliability allows a second observer to score the subject for the purpose of computing reliability. (4) Data Summary and Formatting provides a summary of the results and allows the user to flexibly format the data for reading by various statistical packages.