In the last ten years, the field of proteomics has expanded at a rapid rate. A range of exciting new technology has been developed and enthusiastically applied to an enormous variety of biological questions. However, the degree of stringency required in proteomic data generation and analysis appears to have been underestimated. As a result, there are likely to be numerous published findings that are of questionable quality, requiring further confirmation and/or validation. This manuscript outlines a number of key issues in proteomic research, including those associated with experimental design, differential display and biomarker discovery, protein identification and analytical incompleteness. In an effort to set a standard that reflects current thinking on the necessary and desirable characteristics of publishable manuscripts in the field, a minimal set of guidelines for proteomics research is then described. These guidelines will serve as a set of criteria which editors of PROTEOMICS will use for assessment of future submissions to the Journal.

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The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP’s tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.

Imaging using MS has the potential to deliver highly parallel, multiplexed data on the specific localization of molecular ions in tissue samples directly, and to measure and map the variations of these ions during development and disease progression or treatment. There is an intrinsic potential to be able to identify the biomarkers in the same experiment, or by relatively simple extension of the technique. Unlike many other imaging techniques, no a priori knowledge of the markers being sought is necessary. This review concentrates on the use of MALDI-MS for MS imaging (MSI) of proteins and peptides, with an emphasis on mammalian tissue. We discuss the methodologies used, their potential limitations, overall experimental considerations and progress that has been made towards establishing MALDI-MSI as a routine technique for the spatially resolved measurement of peptides and proteins. As well as determining the local abundance of individual molecular ions, there is the potential to determine their identity within the same experiment using relatively simple extensions of the basic techniques. In this way MSI offers an important opportunity for biomarker discovery and identification.

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal of all the common malignancies and markers for early detection or targets for treatment of this disease are urgently required. The disease is characterised by a strong stromal response, with cancer cells usually representing a relatively small proportion of the cells in the tumor mass. We therefore performed laser capture microdissection (LCM) to enrich for both normal and malignant pancreatic ductal epithelial cells. Proteins extracted from these cells were then separated by two-dimensional gel electrophoresis (2-DE). The limited amounts of protein in the LCM procured samples necessitated the detection of 2-DE resolved proteins by silver staining. Consequently, loading equivalent amounts of protein onto gels was essential. However, we found that conventional means of measuring total protein in the samples were not sufficiently accurate. We therefore adopted a strategy in which the samples were first separated by one-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis, stained with silver stain and subjected to densitometry. Evaluation of the staining intensity was then used to normalise the samples. We found that the protein profiles from undissected normal pancreas and LCM-acquired non-malignant ductal epithelial cells from the same tissue block were different, underpinning the value of LCM in our analysis. The comparisons of protein profiles from nonmalignant and malignant ductal epithelial cells revealed nine protein spots that were consistently differentially regulated. Five of these proteins showed increased expression in tumor cells while four showed diminished expression in these cells. One of the proteins displaying enhanced expression in tumor cells was identified as the calcium-binding protein, S100A6. To determine the incidence of S100A6 overexpression in pancreatic cancer, we carried out immunohistochemical analysis on sections from a pancreas cancer tissue array containing 174 duplicate normal and malignant pancreatic tissue samples, from 46 pancreas cancer patients. Normal pancreatic ductal epithelia were either devoid of detectable S100A6 or showed weak expression only. Moderately or poorly differentiated tumors, by contrast, showed a higher incidence and a higher level of S100A6 expression. These observations indicate that the combination of LCM with 2-DE provides an effective strategy to discover proteins that are differentially expressed in PDAC.