👤 Vineet Vaibhav

One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature. Show less

Leptospirosis is a zoonotic infectious disease of tropical, subtropical and temperate zones, which is caused by the pathogenic spirochetes of genus Leptospira. Although this zoonosis is generally not considered as fatal, the pathogen can eventually cause severe infection with septic shock, multi-organ failure and lethal pulmonary hemorrhages leading to mortality. In this study, we have performed a proteomic analysis of serum samples from leptospirosis patients (n=6), febrile controls (falciparum malaria) (n=8) and healthy subjects (n=18) to obtain an insight about disease pathogenesis and host immune responses in leptospiral infections. 2DE and 2D-DIGE analysis in combination with MALDI-TOF/TOF MS revealed differential expression of 22 serum proteins in leptospirosis patients compared to the healthy controls. Among the identified differentially expressed proteins, 8 candidates exhibited different trends compared to the febrile controls. Functional analysis suggested the involvement of differentially expressed proteins in vital physiological pathways, including acute phase response, complement and coagulation cascades and hemostasis. This is the first report of analysis of human serum proteome alterations in leptospirosis patients, which revealed several differentially expressed proteins, including α-1-antitrypsin, vitronectin, ceruloplasmin, G-protein signaling regulator, apolipoprotein A-IV, which have not been reported in context of leptospirosis previously. This study will enhance our understanding about leptospirosis pathogenesis and provide a glimpse of host immunological responses. Additionally, a few differentially expressed proteins identified in this study may further be investigated as diagnostic or prognostic serum biomarkers for leptospirosis. This article is part of a Special Issue entitled: Integrated omics. Show less