Longitudinal CSF proteomics identifies NPTX2 as a prognostic biomarker of Alzheimer's disease.

INTRODUCTION: Biomarkers that reflect pathologic processes affecting neuronal function during preclinical and early stages of Alzheimer's disease (AD) are needed to aid drug development. METHODS: A targeted, stable isotope, quantitative mass spectrometry-based investigation of longitudinal changes in concentrations of previously identified candidate biomarkers was performed in cerebrospinal fluid (CSF) of Alzheimer's Disease Neuroimaging Initiative participants who were classified as cognitively normal (CN; n = 76) or with mild cognitive impairment (MCI; n = 111) at baseline. RESULTS: Of the candidate biomarkers, the CSF concentration of neuronal pentraxin 2 (NPTX2), a protein involved in synaptic function, exhibited rates of change that were significantly different between three comparison groups (i.e., CN vs. MCI participants; AD pathology positive vs. negative defined by phosphorylated tau181/amyloid beta1-42 ratio; and clinical progressors vs. non-progressors). The rate of change of NPTX2 also significantly correlated with declining cognition. DISCUSSION: CSF NPTX2 concentration is a strong prognostic biomarker candidate of accelerated cognitive decline with potential use as a therapeutic target.

Discovery of a putative blood-based protein signature associated with response to ALK tyrosine kinase inhibition.

BACKGROUND: ALK tyrosine kinase inhibition has become a mainstay in the clinical management of ALK fusion positive NSCLC patients. Although ALK mutations can reliably predict the likelihood of response to ALK tyrosine kinase inhibitors (TKIs) such as crizotinib, they cannot reliably predict response duration or intrinsic/extrinsic therapeutic resistance. To further refine the application of personalized medicine in this indication, this study aimed to identify prognostic proteomic biomarkers in ALK fusion positive NSCLC patients to crizotinib. METHODS: Twenty-four patients with advanced NSCLC harboring ALK fusion were administered crizotinib in a phase IV trial which included blood sampling prior to treatment. Targeted proteomics of 327 proteins using MRM-MS was used to measure plasma levels at baseline (including pre-treatment and early treatment blood samples) and assess potential clinical association. RESULTS: Patients were categorized by duration of response: long-term responders [PFS ≥ 24 months (n = 7)], normal responders [3 < PFS < 24 months (n = 10)] and poor responders [PFS ≤ 3 months (n = 5)]. Several proteins were identified as differentially expressed between long-term responders and poor responders, including DPP4, KIT and LUM. Next, using machine learning algorithms, we evaluated the classification potential of 40 proteins. Finally, by integrating the different analytic methods, we selected 22 proteins as potential candidates for a blood-based prognostic signature of response to crizotinib in NSCLC patients harboring ALK fusion. CONCLUSION: In conjunction with ALK mutation, the expression of this proteomic signature may represent a liquid biopsy-based marker of long-term response to crizotinib in NSCLC. Expanding the utility of prognostic biomarkers of response duration could influence choice of therapy, therapeutic sequencing, and potentially the need for alternative or combination therapy.Trial registration ClinicalTrials.gov, NCT02041468. Registered 22 January 2014, https://clinicaltrials.gov/ct2/show/NCT02041468?term=NCT02041468&rank=1.

Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome.

A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dynamic range of member taxa, the need for well-annotated metagenomic databases, and high inter-protein sequence redundancy and similarity. In this study, an approach was developed for assessment of biological phenotype and metabolic status, as a functional complement to DNA sequence analysis. Fecal samples were prepared and analysed by tandem mass spectrometry and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. In total, 15,250 unique peptides were sequenced and assigned to 2154 metaclusters, which were then assigned to pathways and functional groups. Differences were noted in several pathways, consistent with the dominant genera observed in different subjects. Although this study was not powered to draw conclusions from the comparisons, the results obtained demonstrate the applicability of this approach and provide the methods needed for performing semi-quantitative comparisons of human fecal microbiome composition, physiology and metabolism, as well as a more detailed assessment of microbial composition in comparison to 16S rRNA gene sequencing.

Host Protein Biomarkers Identify Active Tuberculosis in HIV Uninfected and Co-infected Individuals.

Biomarkers for active tuberculosis (TB) are urgently needed to improve rapid TB diagnosis. The objective of this study was to identify serum protein expression changes associated with TB but not latent Mycobacterium tuberculosis infection (LTBI), uninfected states, or respiratory diseases other than TB (ORD). Serum samples from 209 HIV uninfected (HIV(-)) and co-infected (HIV(+)) individuals were studied. In the discovery phase samples were analyzed via liquid chromatography and mass spectrometry, and in the verification phase biologically independent samples were analyzed via a multiplex multiple reaction monitoring mass spectrometry (MRM-MS) assay. Compared to LTBI and ORD, host proteins were significantly differentially expressed in TB, and involved in the immune response, tissue repair, and lipid metabolism. Biomarker panels whose composition differed according to HIV status, and consisted of 8 host proteins in HIV(-) individuals (CD14, SEPP1, SELL, TNXB, LUM, PEPD, QSOX1, COMP, APOC1), or 10 host proteins in HIV(+) individuals (CD14, SEPP1, PGLYRP2, PFN1, VASN, CPN2, TAGLN2, IGFBP6), respectively, distinguished TB from ORD with excellent accuracy (AUC = 0.96 for HIV(-) TB, 0.95 for HIV(+) TB). These results warrant validation in larger studies but provide promise that host protein biomarkers could be the basis for a rapid, blood-based test for TB.