The relationship of red cell enzymes to red cell life-span

Red cells are replaced before they become senescent. It is probable that red cell destruction is controlled by a biologic clock, essentially independent of metabolism, rather than by metabolic failure. The appearance of neo-antigens on the external surface of the red cell could be this "clock."     

Bringing Down Cancer Aircraft: Searching for Essential Hypomutated Proteins in Skin Melanoma

We propose an approach to detection of essential genes/proteins required for cancer cell survival. A gene is considered essential if a mutation with high impact upon the function of encoded protein causes death of the cancer cell. We draw an analogy between essential cancer proteins and well-known Abraham Wald’s work on estimating the plane critical areas using data on survivability of aircraft encountering enemy fire. Wald reasoned that parts with no bullet holes on the airplanes returned to the airbase from a combat flight are the most crucial ones for the airplane functioning: a hit in one of these parts downs an airplane, so it does not return back for the survey. We have envisaged that the airplane surface is a cancer genome and the bullets are somatic mutations with high impact upon protein function. Similarly we propose that genes specifically essential for tumor cell survival should carry less high-impact mutations in cancer cells compared to polymorphisms found in normal cells. We used data on mutations from the Cancer Genome Atlas and polymorphisms found in healthy humans (from 1000 Genomes Project) to predict 91 protein-coding genes essential for melanoma. These genes were selected according to several criteria, including negative selection, expression in melanocytes and decrease in the proportion of high-impact mutations in cancer compared with normal cells. The Gene Ontology analysis revealed enrichment of essential proteins related to membrane and cell periphery. We speculate that this could be a sign of immune system-driven negative selection of cancer neo-antigens. Another finding is the overrepresentation of semaphorin receptors, which can mediate distinctive signaling cascades and are involved in various aspects of tumor development. Cytokine receptors CCR5 and CXCR1 were also identified as cancer essential proteins and this is confirmed by other studies. Overall, our goal was to illustrate the idea of detecting proteins whose sequence integrity and functioning is important for cancer cell survival. Hopefully, this prediction of essential cancer proteins may point to new targets for anti-tumor therapies.     

Challenges and promise at the interface of metaproteomics and genomics: an overview of recent progress in metaproteogenomic data analysis

Introduction: The study of microbial communities based on the combined analysis of genomic and proteomic data – called metaproteogenomics – has gained increased research attention in recent years. This relatively young field aims to elucidate the functional and taxonomic interplay of proteins in microbiomes and its implications on human health and the environment.

Areas covered: This article reviews bioinformatics methods and software tools dedicated to the analysis of data from metaproteomics and metaproteogenomics experiments. In particular, it focuses on the creation of tailored protein sequence databases, on the optimal use of database search algorithms including methods of error rate estimation, and finally on taxonomic and functional annotation of peptide and protein identifications.

Expert opinion: Recently, various promising strategies and software tools have been proposed for handling typical data analysis issues in metaproteomics. However, severe challenges remain that are highlighted and discussed in this article; these include: (i) robust false-positive assessment of peptide and protein identifications, (ii) complex protein inference against a background of highly redundant data, (iii) taxonomic and functional post-processing of identification data, and finally, (iv) the assessment and provision of metrics and tools for quantitative analysis.     

Stimulation of Autochthonous Lymphocytes by Cells from Normal and Leukaemic Lines

THE mixed lymphocyte reaction (MLR) can possibly be regarded as an in vitro form of an in vivo phenomenon reflecting the recognition of “non-self” tumour specific or neo-antigens on the surface of lymphoid cells. A reaction similar to the normal MLR but of greater magnitude occurs when irradiated lymphoid cells from lymphoblastoid cell lines (LCL) are added to freshly isolated peripheral lymphocytes from allogeneic individuals^1,2. The intense stimulation which occurred in every case when irradiated cells from various LCL were added to lymphocytes from a large number of individuals³ suggested the presence of extra surface determinants on the cells, which are not present on normal freshly isolated cells. We have investigated whether freshly isolated lymphoid cells could detect and respond to extra antigenic determinants on the surface of cell lines derived more than 3 months earlier from their own lymphoid cells.     

Developing dendritic cell polynucleotide vaccination for prostate cancer immunotherapy.

Immunotherapy has been successfully used to treat some human malignancies, principally melanoma and renal cell carcinoma. Genetic-based cancer immunotherapies were proposed which prime T lymphocyte recognition of unique neo-antigens arising from specific mutations. Genetic immunization (polynucleotide vaccination, DNA vaccines) is a process whereby gene therapy methods are used to create vaccines and immunotherapies. Recent findings indicate that genetic immunization works indirectly via a bone marrow derived cell, probably a type of dendritic antigen presenting cell (APC). Direct targeting of genetic vaccines to these cells may provide an efficient method for stimulating cellular and humoral immune responses to infectious agents and tumor antigens. Initial studies have provided monocytic-derived dendritic cell (DC) isolation and culture techniques, simple methods for delivering genes into these cells, and have also uncovered potential obstacles to effective cancer immunotherapy which may restrict the utility of this paradigm to a subset of patients.     

从蛋白质基因组学视角出发的精准肿瘤学

癌症是一种机制复杂的异质性疾病,需要有针对性的精准医疗策略。精准医疗的发展离不开基因组学的飞速发展,但基因组学在分子表型分析中具有一定的局限性,蛋白质基因组学应运而生。蛋白质基因组学是蛋白质组学和基因组学的融合学科。文中描述了基因组学分析的局限性,强调了蛋白质基因组学的重要性,旨在从蛋白质基因组的视角重新了解精准肿瘤学。此外,还简要介绍了蛋白质基因组学在精准肿瘤学中的应用,对相关的公共数据项目进行了描述,最后,提出了现阶段需要克服的困难。     

Proteogenomics meets cancer immunology: mass spectrometric discovery and analysis of neoantigens

Cancer proteogenomics is an emerging field that aims to identify and quantify protein sequence changes associated with the cancer genome. Besides being involved in cancer development and progression, such protein variants may serve as neoantigens, which provide the T-cell response against tumors. Mass spectrometry-based proteogenomics may be a promising tool for finding neoantigens in individual specimens. It is partly based on a technical background accumulated from mass spectrometric studies of peptide ligands of major histocompatibility complex proteins. Examples of the use of mass spectrometry in neoantigen identification are reviewed in this article. Some experimental workflows are discussed, which may use shotgun and targeted proteomics for translational human studies of neoepitopes, such as cancer vaccine development and checkpoint therapy response prediction.     

Proteogenomics approaches for studying cancer biology and their potential in the identification of acute myeloid leukemia biomarkers

Introduction: Mass spectrometry (MS)-based proteomics has become an indispensable tool for the characterization of the proteome and its post-translational modifications (PTM). In addition to standard protein sequence databases, proteogenomics strategies search the spectral data against the theoretical spectra obtained from customized protein sequence databases. Up to date, there are no published proteogenomics studies on acute myeloid leukemia (AML) samples.

Areas covered: Proteogenomics involves the understanding of genomic and proteomic data. The intersection of both datatypes requires advanced bioinformatics skills. A standard proteogenomics workflow that could be used for the study of AML samples is described. The generation of customized protein sequence databases as well as bioinformatics tools and pipelines commonly used in proteogenomics are discussed in detail.

Expert commentary: Drawing on evidence from recent cancer proteogenomics studies and taking into account the public availability of AML genomic data, the interpretation of present and future MS-based AML proteomic data using AML-specific protein sequence databases could discover new biological mechanisms and targets in AML. However, proteogenomics workflows including bioinformatics guidelines can be challenging for the wide AML research community. It is expected that further automation and simplification of the bioinformatics procedures might attract AML investigators to adopt the proteogenomics strategy.     

蛋白质基因组学：运用蛋白质组技术注释基因组

随着高通量DNA测序技术的飞速发展,越来越多的物种完成了基因组测序．定位编码基因、确定编码基因结构是基因组注释的基本任务,然而以往的基因组注释方法主要依赖于DNA及RNA序列信息．为了更加精确地解读完成测序的基因组,我们需要整合多种类型的组学数据进行基因组注释．近年来,基于串联质谱技术的蛋白质组学已经发展成熟,实现了对蛋白质组的高覆盖,使得利用串联质谱数据进行基因组注释成为可能．串联质谱数据一方面可以对已注释的基因进行表达验证,另一方面还可以校正原注释基因,进而发现新基因,实现对基因组序列的重新注释．这正是当前进展较快的蛋白质基因组学的研究内容．利用该方法系统地注释已完成测序的基因组已成为解读基因组的一个重要补充．本文综述了蛋白质基因组学的主要研究内容和研究方法,并展望了该研究方向未来的发展．     

Fractal Analysis of Binding and Dissociation Kinetics and Interactions of Cancer Markers on Biosensor Surfaces

A fractal analysis is presented for the binding and dissociation of different cancer markers on biosensor surfaces. The data analyzed include putrescine in solution to PDDA/APTES/MWCNT/Puo-modified GCE (glassy carbon electrode) () and vascular endothelial growth factor (VEGF) in solution to the soluble form of the VEGF receptor (SFlt-1 or VEGF-1) immobilized on a sensor chip (). Single- and dual-fractal models were used to fit the data. Values of the binding and dissociation rate coefficient(s), affinity values, and the fractal dimensions were obtained from the regression analysis provided by Corel Quattro Pro 8.0 (). The binding rate coefficients and the affinity values are sensitive to the degree of heterogeneity on the sensor chip surface. Predictive equations are developed for the binding rate coefficient as a function of the heterogeneity present on the biosensor chip surface. The analysis presented provides physical insights into these cancer biomarker-receptor reactions occurring on the different biosensor surfaces.     

Fractal analysis of binding and dissociation kinetics and interactions of cancer markers on biosensor surfaces

A fractal analysis is presented for the binding and dissociation of different cancer markers on biosensor surfaces. The data analyzed include putrescine in solution to PDDA/APTES/MWCNT/Puo-modified GCE (glassy carbon electrode) (8) and vascular endothelial growth factor (VEGF) in solution to the soluble form of the VEGF receptor (SFlt-1 or VEGF-1) immobilized on a sensor chip (1). Single- and dual-fractal models were used to fit the data. Values of the binding and dissociation rate coefficient(s), affinity values, and the fractal dimensions were obtained from the regression analysis provided by Corel Quattro Pro 8.0 (13). The binding rate coefficients and the affinity values are sensitive to the degree of heterogeneity on the sensor chip surface. Predictive equations are developed for the binding rate coefficient as a function of the heterogeneity present on the biosensor chip surface. The analysis presented provides physical insights into these cancer biomarker-receptor reactions occurring on the different biosensor surfaces.     

A Molecular Basis for the Presentation of Phosphorylated Peptides by HLA-B Antigens

As aberrant protein phosphorylation is a hallmark of tumor cells, the display of tumor-specific phosphopeptides by Human Leukocyte Antigen (HLA) class I molecules can be exploited in the treatment of cancer by T-cell-based immunotherapy. Yet, the characterization and prediction of HLA-I phospholigands is challenging as the molecular determinants of the presentation of such post-translationally modified peptides are not fully understood. Here, we employed a peptidomic workflow to identify 256 unique phosphorylated ligands associated with HLA-B*40, -B*27, -B*39, or -B*07. Remarkably, these phosphopeptides showed similar molecular features. Besides the specific anchor motifs imposed by the binding groove of each allotype, the predominance of phosphorylation at peptide position 4 (P4) became strikingly evident, as was the enrichment of basic residues at P1. To determine the structural basis of this observation, we carried out a series of peptide binding assays and solved the crystal structures of HLA-B*40 in complex with a phosphorylated ligand or its nonphosphorylated counterpart. Overall, our data provide a clear explanation to the common motif found in the phosphopeptidomes associated to different HLA-B molecules. The high prevalence of phosphorylation at P4 is dictated by the presence of the conserved residue Arg62 in the heavy chain, a structural feature shared by most HLA-B alleles. In contrast, the preference for basic residues at P1 is allotype-dependent and might be linked to the structure of the A pocket. This molecular understanding of the presentation of phosphopeptides by HLA-B molecules provides a base for the improved prediction and identification of phosphorylated neo-antigens, as potentially used for cancer immunotherapy.     

Confidence interval about the response at the stationary point of a response surface, with an application to preclinical cancer therapy

A method of calculating a confidence interval about the response at the stationary point of a response surface is presented. We show that the technique can also be used to calculate a confidence region about the location of the stationary point. The procedure is applied, via Cox's proportional-hazards model, to the analysis of survival data from a preclinical cancer chemotherapy experiment involving the combination of two drugs. It is seen that the results can be useful in determining the existence of a therapeutic synergism.     

Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes

Multi-omics approaches are novel frameworks that integrate multiple omics datasets generated from the same patients to better understand the molecular and clinical features of cancers. A wide range of emerging omics and multi-view clustering algorithms now provide unprecedented opportunities to further classify cancers into subtypes, improve the survival prediction and therapeutic outcome of these subtypes, and understand key pathophysiological processes through different molecular layers. In this review, we overview the concept and rationale of multi-omics approaches in cancer research. We also introduce recent advances in the development of multi-omics algorithms and integration methods for multiple-layered datasets from cancer patients. Finally, we summarize the latest findings from large-scale multi-omics studies of various cancers and their implications for patient subtyping and drug development.     

Proteogenomics: needs and roles to be filled by proteomics in genome annotation

While genome sequencing efforts reveal the basic building blocksof life, a genome sequence alone is insufficient for elucidatingbiological function. Genome annotation—the process ofidentifying genes and assigning function to each gene in a genomesequence—provides the means to elucidate biological functionfrom sequence. Current state-of-the-art high-throughput genomeannotation uses a combination of comparative (sequence similaritydata) and non-comparative (ab initio gene prediction algorithms)methods to identify protein-coding genes in genome sequences.Because approaches used to validate the presence of predictedprotein-coding genes are typically based on expressed RNA sequences,they cannot independently and unequivocally determine whethera predicted protein-coding gene is translated into a protein.With the ability to directly measure peptides arising from expressedproteins, high-throughput liquid chromatography-tandem massspectrometry-based proteomics approaches can be used to verifycoding regions of a genomic sequence. Here, we highlight severalways in which high-throughput tandem mass spectrometry-basedproteomics can improve the quality of genome annotations andsuggest that it could be efficiently applied during the genecalling process so that the improvements are propagated throughthe subsequent functional annotation process.