Proteogenomics: emergence and promise

Mass-spectrometric analysis of APOB polymorphism rs1042031 (G/T) and its influence on serum proteome of coronary artery disease patients: genetic-derived proteomics consequences

Genetic polymorphisms of apolipoprotein B gene (APOB) may result into serum proteomic perturbance in Coronary Artery Disease (CAD). The current case-control cohort of Pakistani subjects was designed to analyze the genetic influence of APOB rs1042031, (G/T) genotype on serum proteome. Subjects were categorized into two groups: CAD patients (n = 480) and healthy individuals (n = 220). For genotyping, tetra ARMS-PCR was carried out and validated through sequencing, whereas LC/MS-based proteomic analysis of serum samples was performed through label-free quantification. In initial step of genotyping, the frequencies of each genotype GG, GT, and TT were 70%, 27%, and 30% in CAD patients, while in control group, the subjects were 52%, 43%, and 5%, respectively, in CAD patients. The genotypic frequencies in patients vs. control groups found significantly different (p = 0.004), and a strong association of dominant alleles GG with the CAD was observed in both dominant (OR: 2.4 (1.71-3.34), p = 0.001) and allelic genetic models (OR: 2.0 (1.45-2.86), p = 0.001). In second step of label-free quantitation, a total of 40 significant proteins were found with altered expression in CAD patients. The enriched Gene Ontology (GO) terms of molecular functions and pathways of these protein showed upregulated pathways as follows: chylomicron remodeling and assembly, complement cascade activation, plasma lipoprotein assembly, apolipoprotein-A receptor binding, and metabolism of fat-soluble vitamins in G allele carrier of rs1042031 (G > T) vs. mutant T-allele carriers. This study provides better understanding of CAD pathobiology by proteogenomics of APOB. It evidences the influence of APOB rs1042031-dominant (GG) genotype with CAD patients.

The perennial fruit tree proteogenomics atlas: a spatial map of the sweet cherry proteome and transcriptome

Genome-wide transcriptome analysis provides systems-level insights into plant biology. Due to the limited depth of quantitative proteomics our understanding of gene-protein-complex stoichiometry is largely unknown in plants. Recently, the complexity of the proteome and its cell-/tissue-specific distribution have boosted the research community to the integration of transcriptomics and proteomics landscapes in a proteogenomic approach. Herein, we generated a quantitative proteome and transcriptome abundance atlas of 15 major sweet cherry (Prunus avium L., cv 'Tragana Edessis') tissues represented by 29 247 genes and 7584 proteins. Additionally, 199 984 alternative splicing events, particularly exon skipping and alternative 3' splicing, were identified in 23 383 transcribed regions of the analyzed tissues. Common signatures as well as differences between mRNA and protein quantities, including genes encoding transcription factors and allergens, within and across the different tissues are reported. Using our integrated dataset, we identified key putative regulators of fruit development, notably genes involved in the biosynthesis of anthocyanins and flavonoids. We also provide proteogenomic-based evidence for the involvement of ethylene signaling and pectin degradation in cherry fruit ripening. Moreover, clusters of genes and proteins with similar and different expression and suppression trends across diverse tissues and developmental stages revealed a relatively low RNA abundance-to-protein correlation. The present proteogenomic analysis allows us to identify 17 novel sweet cherry proteins without prior protein-level annotation evidenced in the currently available databases. To facilitate use by the community, we also developed the Sweet Cherry Atlas Database (https://grcherrydb.com/) for viewing and data mining these resources. This work provides new insights into the proteogenomics workflow in plants and a rich knowledge resource for future investigation of gene and protein functions in Prunus species.

Could Causal Discovery in Proteogenomics Assist in Understanding Gene-Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model

Genome-wide transcriptome analysis is a method that produces important data on plant biology at a systemic level. The lack of understanding of the relationships between proteins and genes in plants necessitates a further thorough analysis at the proteogenomic level. Recently, our group generated a quantitative proteogenomic atlas of 15 sweet cherry (Prunus avium L.) cv. ‘Tragana Edessis’ tissues represented by 29,247 genes and 7584 proteins. The aim of the current study was to perform a targeted analysis at the gene/protein level to assess the structure of their relation, and the biological implications. Weighted correlation network analysis and causal modeling were employed to, respectively, cluster the gene/protein pairs, and reveal their cause–effect relations, aiming to assess the associated biological functions. To the best of our knowledge, this is the first time that causal modeling has been employed within the proteogenomics concept in plants. The analysis revealed the complex nature of causal relations among genes/proteins that are important for traits of interest in perennial fruit trees, particularly regarding the fruit softening and ripening process in sweet cherry. Causal discovery could be used to highlight persistent relations at the gene/protein level, stimulating biological interpretation and facilitating further study of the proteogenomic atlas in plants.

Effect of APOB polymorphism rs562338 (G/A) on serum proteome of coronary artery disease patients: a "proteogenomic" approach

In the current study, APOB (rs1052031) genotype-guided proteomic analysis was performed in a cohort of Pakistani population. A total of 700 study subjects, including Coronary Artery Disease (CAD) patients (n = 480) and healthy individuals (n = 220) as a control group were included in the study. Genotyping was carried out by using tetra primer-amplification refractory mutation system-based polymerase chain reaction (T-ARMS-PCR) whereas mass spectrometry (Orbitrap MS) was used for label free quantification of serum samples. Genotypic frequency of GG genotype was found to be 90.1%, while 6.4% was for GA genotype and 3.5% was for AA genotypes in CAD patients. In the control group, 87.2% healthy subjects were found to have GG genotype, 11.8% had GA genotype, and 0.9% were with AA genotypes. Significant (p = 0.007) difference was observed between genotypic frequencies in the patients and the control group. The rare allele AA was found to be strongly associated with the CAD [OR: 4 (1.9-16.7)], as compared to the control group in recessive genetic model (p = 0.04). Using label free proteomics, altered expression of 60 significant proteins was observed. Enrichment analysis of these protein showed higher number of up-regulated pathways, including phosphatidylcholine-sterol O-acyltransferase activator activity, cholesterol transfer activity, and sterol transfer activity in AA genotype of rs562338 (G>A) as compared to the wild type GG genotype. This study provides a deeper insight into CAD pathobiology with reference to proteogenomics, and proving this approach as a good platform for identifying the novel proteins and signaling pathways in relation to cardiovascular diseases.

Can Hemp Help? Low-THC Cannabis and Non-THC Cannabinoids for the Treatment of Cancer

Cannabis has been used to relieve the symptoms of disease for thousands of years. However, social and political biases have limited effective interrogation of the potential benefits of cannabis and polarised public opinion. Further, the medicinal and clinical utility of cannabis is limited by the psychotropic side effects of ∆⁹-tetrahydrocannabinol (∆⁹-THC). Evidence is emerging for the therapeutic benefits of cannabis in the treatment of neurological and neurodegenerative diseases, with potential efficacy as an analgesic and antiemetic for the management of cancer-related pain and treatment-related nausea and vomiting, respectively. An increasing number of preclinical studies have established that ∆⁹-THC can inhibit the growth and proliferation of cancerous cells through the modulation of cannabinoid receptors (CB1R and CB2R), but clinical confirmation remains lacking. In parallel, the anti-cancer properties of non-THC cannabinoids, such as cannabidiol (CBD), are linked to the modulation of non-CB1R/CB2R G-protein-coupled receptors, neurotransmitter receptors, and ligand-regulated transcription factors, which together modulate oncogenic signalling and redox homeostasis. Additional evidence has also demonstrated the anti-inflammatory properties of cannabinoids, and this may prove relevant in the context of peritumoural oedema and the tumour immune microenvironment. This review aims to document the emerging mechanisms of anti-cancer actions of non-THC cannabinoids.

RNA-Seq and iTRAQ reveal multiple pathways involved in storage root formation and development in sweet potato (Ipomoea batatas L.)

BACKGROUND

Sweet potato (Ipomoea batatas L.) is the sixth most important food crop in the world. The formation and development of storage roots in sweet potato is a highly complicated and genetically programmed process. However, the underlying mechanisms of storage root development have not yet been elucidated.

RESULTS

To better understand the molecular mechanisms involved in storage root development, a combined analysis of the transcriptome and proteome of sweet potato fibrous roots (F) and storage roots at four different stages (D1, D3, D5 and D10) was performed in the present study. A total of 26,273 differentially expressed genes were identified in a comparison between the fibrous root library and four storage root libraries, while 2558 proteins showed a 1.0-fold or greater expression difference as indicated by isobaric tags for relative and absolute quantitation (iTRAQ) analysis. The combination of the transcriptome and proteome analyses and morphological and physiological data revealed several critical pathways involved in storage root formation and development. First, genes/proteins involved in the development of meristems/cambia and starch biosynthesis were all significantly upregulated in storage roots compared with fibrous roots. Second, multiple phytohormones and the genes related to their biosynthesis showed differential expression between fibrous roots and storage roots. Third, a large number of transcription factors were differentially expressed during storage root initiation and development, which suggests the importance of transcription factor regulation in the development of storage roots. Fourth, inconsistent gene expression was found between the transcriptome and proteome data, which indicated posttranscriptional regulatory activity during the development of storage roots.

CONCLUSION

Overall, these results reveal multiple events associated with storage root development and provide new insights into the molecular mechanisms underlying the regulatory networks involved in storage root development.

Engineering ClpS for selective and enhanced N-terminal amino acid binding

One of the central challenges in the development of single-molecule protein sequencing technologies is achieving high-fidelity sequential recognition and detection of specific amino acids that comprise the peptide sequence. An approach towards achieving this goal is to leverage naturally occurring proteins that function through recognition of amino (N)-terminal amino acids (NAAs). One such protein, the N-end rule pathway adaptor protein ClpS, natively recognizes NAAs on a peptide chain. The native ClpS protein has a high specificity albeit modest affinity for the amino acid Phe at the N-terminus but also recognizes the residues Trp, Tyr, and Leu at the N-terminal position. Here, we employed directed evolution methods to select for ClpS variants with enhanced affinity and selectivity for two NAAs (Phe and Trp). Using this approach, we identified two promising variants of the Agrobacterium tumefaciens ClpS protein with native residues 34-36 ProArgGlu mutated to ProMetSer and CysProSer. In vitro surface binding assays indicate that the ProMetSer variant has enhanced affinity for Phe at the N-terminus with sevenfold tighter binding relative to wild-type ClpS, and that the CysProSer variant binds selectively to Trp over Phe at the N-terminus while having a greater affinity for both Trp and Phe. Taken together, this work demonstrates the utility of engineering ClpS to make it more effective for potential use in peptide sequencing applications.

Targeting Oncogenic Signaling in Mutant FLT3 Acute Myeloid Leukemia: The Path to Least Resistance

The identification of recurrent driver mutations in genes encoding tyrosine kinases has resulted in the development of molecularly-targeted treatment strategies designed to improve outcomes for patients diagnosed with acute myeloid leukemia (AML). The receptor tyrosine kinase FLT3 is the most commonly mutated gene in AML, with internal tandem duplications within the juxtamembrane domain (FLT3-ITD) or missense mutations in the tyrosine kinase domain (FLT3-TKD) present in 30–35% of AML patients at diagnosis. An established driver mutation and marker of poor prognosis, the FLT3 tyrosine kinase has emerged as an attractive therapeutic target, and thus, encouraged the development of FLT3 tyrosine kinase inhibitors (TKIs). However, the therapeutic benefit of FLT3 inhibition, particularly as a monotherapy, frequently results in the development of treatment resistance and disease relapse. Commonly, FLT3 inhibitor resistance occurs by the emergence of secondary lesions in the FLT3 gene, particularly in the second tyrosine kinase domain (TKD) at residue Asp835 (D835) to form a ‘dual mutation’ (ITD-D835). Individual FLT3-ITD and FLT3-TKD mutations influence independent signaling cascades; however, little is known about which divergent signaling pathways are controlled by each of the FLT3 specific mutations, particularly in the context of patients harboring dual ITD-D835 mutations. This review provides a comprehensive analysis of the known discrete and cooperative signaling pathways deregulated by each of the FLT3 specific mutations, as well as the therapeutic approaches that hold the most promise of more durable and personalized therapeutic approaches to improve treatments of FLT3 mutant AML.

A System-wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells

Intrinsic and/or acquired resistance represents one of the great challenges in targeted cancer therapy. A deeper understanding of the molecular biology of cancer has resulted in more efficient strategies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has also been observed in colorectal cancer patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block intrinsic resistance to BRAF inhibitors. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant colorectal cancer cells as a model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both known and novel responses. We primarily observe widespread up-regulation of receptor tyrosine kinases and metabolic pathways upon BRAF inhibition. These findings point to mechanisms by which the drug-treated cells switch energy sources and enter a quiescent-like state as a defensive response, while additionally compensating for the MAPK pathway inhibition.

Cell-Free DNA Blood Collection Tubes Are Appropriate for Clinical Proteomics: A Demonstration in Colorectal Cancer

BACKGROUND

Optimized blood collection tubes (BCT) have been developed to expand the utility of plasma cell-free DNA (cfDNA) and are in clinical use. The appropriateness of plasma collected and stored in these tubes for proteomic analysis is unknown.

METHODS

Paired blood samples were collected in BCT and traditional K3EDTA (EDTA) tubes from healthy controls and from colorectal cancer (CRC) patients before and after surgery, and stored for between 45 min and 48 h at room temperature. Plasma proteins were analyzed following high-abundant plasma protein depletion in quantitative discovery and targeted proteomics by liquid chromatography tandem-mass spectrometry (LC-MS/MS).

RESULTS

BCT reduced cellular protein contamination in healthy controls over time, and increased the number of high confident low-abundant protein identifications in CRC blood samples compared to matched samples collected in EDTA tubes. The known CRC plasma protein biomarker, carcinoembryonic antigen (CEA), showed elevated levels across patients pre-operatively when collected and stored in BCT compared to EDTA tubes. Emerging CRC biomarkers, Dickkopf-3 (DKK3) and Gelsolin (GSN), showed elevated levels pre-operatively when collected in BCT.

CONCLUSIONS

Optimized BCT are appropriate for low-abundant plasma protein analysis and can be used with confidence for clinical proteomics.

Proteogenomics Gets onto the Regulation of mRNA Decoding and Translation into Protein

Proteogenomics, the integrative analysis of the proteome and the genome, increasingly provides protein-level insights about the regulation of gene expression and protein translation. Armengaud et al. (Proteomics 2017, 17, 1700211) nicely illustrate this trend with the first in-depth proteomic analysis of the eukaryotic and unicellular intestinal parasite Blastocystis sp. Not only this work constitutes an important milestone toward the proteogenomics profile of this human pathogen, but also it demonstrates at the protein level the occurrence of a specific mechanism of mRNA decoding. GU-rich motifs located downstream of mRNA polyadenylation sites create termination codons that ultimately result in the synthesis of proteins with lower molecular weight than predicted from gene sequence. Thus, the scope of proteogenomics now extends to the regulation of mRNA translation into proteins, providing a proof of concept for future studies in multicellular eukaryotes such as humans and plants.

Variant peptide detection utilizing mass spectrometry: laying the foundations for proteogenomic identification and validation

BACKGROUND

Proteogenomics is an emerging field at the intersection of genomics and proteomics. Many variant peptides corresponding to single nucleotide variations (SNVs) are associated with specific diseases. The aim of this study was to demonstrate the feasibility of proteogenomic-based variant peptide detection in disease models and clinical specimens.

METHODS

We sought to detect p53 single amino acid variant (SAAV) peptides in breast cancer tumor samples that have been previously subjected to sequencing analysis. Initially, two cancer cell lines having a cellular tumor antigen p53 (TP53) mutation and one wild type for TP53 were analyzed by selected reaction monitoring (SRM) assays as controls. One pool of wild type and one pool of mutated for TP53 cytosolic extracts were assayed with a shotgun proteogenomic workflow. Furthermore, 18 individual samples having a mutation in TP53 were assayed by SRM.

RESULTS

Two mutant p53 peptides were successfully detected in two cancer cell lines as expected from their DNA sequence. Wild type p53 peptides were detected in both cytosolic pools, however, none of the mutant p53 peptides were identified. Mutations at the protein level were detected in two cytosolic extracts and whole tumor lysates from the same patients by SRM analysis. Six thousand and six hundred and twenty eight non-redundant proteins were identified in the two cytosolic pools, thus greatly improving a previously reported cytosolic proteome.

CONCLUSIONS

In the current study we show the great potential of using proteogenomics for the direct identification of cancer-associated mutations in clinical samples and we discuss current limitations and future perspectives.

Harnessing the power of proteomics for identification of oncogenic, druggable signalling pathways in cancer

INTRODUCTION

Genomic and transcriptomic profiling of tumours has revolutionised our understanding of cancer. However, the majority of tumours possess multiple mutations, and determining which oncogene, or even which pathway, to target is difficult. Proteomics is emerging as a powerful approach to identify the functionally important pathways driving these cancers, and how they can be targeted therapeutically. Areas covered: The authors provide a technical overview of mass spectrometry based approaches for proteomic profiling, and review the current and emerging strategies available for the identification of dysregulated networks, pathways, and drug targets in cancer cells, with a key focus on the ability to profile cancer kinomes. The potential applications of mass spectrometry in the clinic are also highlighted. Expert opinion: The addition of proteomic information to genomic platforms - 'proteogenomics' - is providing unparalleled insight in cancer cell biology. Application of improved mass spectrometry technology and methodology, in particular the ability to analyse post-translational modifications (the PTMome), is providing a more complete picture of the dysregulated networks in cancer, and uncovering novel therapeutic targets. While the application of proteomics to discovery research will continue to rise, improved workflow standardisation and reproducibility is required before mass spectrometry can enter routine clinical use.

Proteogenomic studies on cancer drug resistance: towards biomarker discovery and target identification

INTRODUCTION

Chemoresistance is a major obstacle for current cancer treatment. Proteogenomics is a powerful multi-omics research field that uses customized protein sequence databases generated by genomic and transcriptomic information to identify novel genes (e.g. noncoding, mutation and fusion genes) from mass spectrometry-based proteomic data. By identifying aberrations that are differentially expressed between tumor and normal pairs, this approach can also be applied to validate protein variants in cancer, which may reveal the response to drug treatment. Areas covered: In this review, we will present recent advances in proteogenomic investigations of cancer drug resistance with an emphasis on integrative proteogenomic pipelines and the biomarker discovery which contributes to achieving the goal of using precision/personalized medicine for cancer treatment. Expert commentary: The discovery and comprehensive understanding of potential biomarkers help identify the cohort of patients who may benefit from particular treatments, and will assist real-time clinical decision-making to maximize therapeutic efficacy and minimize adverse effects. With the development of MS-based proteomics and NGS-based sequencing, a growing number of proteogenomic tools are being developed specifically to investigate cancer drug resistance.

Proteomics in India: the clinical aspect

Proteomics has emerged as a highly promising bioanalytical technique in various aspects of applied biological research. In Indian academia, proteomics research has grown remarkably over the last decade. It is being extensively used for both basic as well as translation research in the areas of infectious and immune disorders, reproductive disorders, cardiovascular diseases, diabetes, eye disorders, human cancers and hematological disorders. Recently, some seminal works on clinical proteomics have been reported from several laboratories across India. This review aims to shed light on the increasing use of proteomics in India in a variety of biological conditions. It also highlights that India has the expertise and infrastructure needed for pursuing proteomics research in the country and to participate in global initiatives. Research in clinical proteomics is gradually picking up pace in India and its future seems very bright.

Proteogenomics for the Comprehensive Analysis of Human Cellular and Serum Antibody Repertoires

The vast repertoire of immunoglobulins produced by the immune system is a consequence of the huge amount of antigens to which we are exposed every day. The diversity of these immunoglobulins is due to different mechanisms (including VDJ recombination, somatic hypermutation, and antigen selection). Understanding how the immune system is capable of generating this diversity and which are the molecular bases of the composition of immunoglobulins are key challenges in the immunological field. During the last decades, several techniques have emerged as promising strategies to achieve these goals, but it is their combination which appears to be the fruitful solution for increasing the knowledge about human cellular and serum antibody repertoires.In this chapter, we address the diverse strategies focused on the analysis of immunoglobulin repertoires as well as the characterization of the genomic and peptide sequences. Moreover, the advantages of combining various -omics approaches are discussed through review different published studies, showing the benefits in clinical areas.

GAPP: A Proteogenomic Software for Genome Annotation and Global Profiling of Post-translational Modifications in Prokaryotes

Although the number of sequenced prokaryotic genomes is growing rapidly, experimentally verified annotation of prokaryotic genome remains patchy and challenging. To facilitate genome annotation efforts for prokaryotes, we developed an open source software called GAPP for genome annotation and global profiling of post-translational modifications (PTMs) in prokaryotes. With a single command, it provides a standard workflow to validate and refine predicted genetic models and discover diverse PTM events. We demonstrated the utility of GAPP using proteomic data from Helicobacter pylori, one of the major human pathogens that is responsible for many gastric diseases. Our results confirmed 84.9% of the existing predicted H. pylori proteins, identified 20 novel protein coding genes, and corrected four existing gene models with regard to translation initiation sites. In particular, GAPP revealed a large repertoire of PTMs using the same proteomic data and provided a rich resource that can be used to examine the functions of reversible modifications in this human pathogen. This software is a powerful tool for genome annotation and global discovery of PTMs and is applicable to any sequenced prokaryotic organism; we expect that it will become an integral part of ongoing genome annotation efforts for prokaryotes. GAPP is freely available at https://sourceforge.net/projects/gappproteogenomic/.

Tissue-specific Proteogenomic Analysis of Plutella xylostella Larval Midgut Using a Multialgorithm Pipeline

The diamondback moth, Plutella xylostella (L.), is the major cosmopolitan pest of brassica and other cruciferous crops. Its larval midgut is a dynamic tissue that interfaces with a wide variety of toxicological and physiological processes. The draft sequence of the P. xylostella genome was recently released, but its annotation remains challenging because of the low sequence coverage of this branch of life and the poor description of exon/intron splicing rules for these insects. Peptide sequencing by computational assignment of tandem mass spectra to genome sequence information provides an experimental independent approach for confirming or refuting protein predictions, a concept that has been termed proteogenomics. In this study, we carried out an in-depth proteogenomic analysis to complement genome annotation of P. xylostella larval midgut based on shotgun HPLC-ESI-MS/MS data by means of a multialgorithm pipeline. A total of 876,341 tandem mass spectra were searched against the predicted P. xylostella protein sequences and a whole-genome six-frame translation database. Based on a data set comprising 2694 novel genome search specific peptides, we discovered 439 novel protein-coding genes and corrected 128 existing gene models. To get the most accurate data to seed further insect genome annotation, more than half of the novel protein-coding genes, i.e. 235 over 439, were further validated after RT-PCR amplification and sequencing of the corresponding transcripts. Furthermore, we validated 53 novel alternative splicings. Finally, a total of 6764 proteins were identified, resulting in one of the most comprehensive proteogenomic study of a nonmodel animal. As the first tissue-specific proteogenomics analysis of P. xylostella, this study provides the fundamental basis for high-throughput proteomics and functional genomics approaches aimed at deciphering the molecular mechanisms of resistance and controlling this pest.

Endocrine therapy resistance in estrogen receptor (ER)-positive breast cancer

Estrogen receptor (ER)-positive breast cancer represents the majority (∼70%) of all breast malignancies. In this subgroup of breast cancers, endocrine therapies are effective both in the adjuvant and recurrent settings, although resistance remains a major issue. Several high-throughput approaches have been used to elucidate mechanisms of resistance and to derive potential predictive markers or alternative therapies. In this review, we cover the state-of-the-art of endocrine-resistance biomarker discovery with regard to the latest technological developments, and discuss current opportunities and restrictions for their implementation into a clinical setting.

Deciphering the complexity of the cancer proteome for diagnostic applications

The proteome is the most functional component encoded in the genome, yet most features of the proteome that are deregulated in cancer cannot be predicted from genomic analysis alone. These include post-translational modifications (PTMs), sub-cellular localization, networks and circuitry, formation of complexes, and functional activity, all of which could play a role or be affected as part of tumorigenesis. Thus, there is a substantial opportunity to elucidate protein alterations in cancer and to translate knowledge into diagnostics and therapeutics. The progress made in mining the cancer proteome for diagnostic applications and the path forward are herein reviewed.

Proteogenomic Analysis of Single Amino Acid Polymorphisms in Cancer Research

The integration of genomics and proteomics has led to the emergence of proteogenomics, a field of research successfully applied to the characterization of cancer samples. The diagnosis, prognosis and response to therapy of cancer patients will largely benefit from the identification of mutations present in their genome. The current state of the art of high throughput experiments for genome-wide detection of somatic mutations in cancer samples has allowed the development of projects such as the TCGA, in which hundreds of cancer genomes have been sequenced. This huge amount of data can be used to generate protein sequence databases in which each entry corresponds to a mutated peptide associated with certain cancer types. In this chapter, we describe a bioinformatics workflow for creating these databases and detecting mutated peptides in cancer samples from proteomic shotgun experiments. The performance of the proposed method has been evaluated using publicly available datasets from four cancer cell lines.

Creating reference gene annotation for the mouse C57BL6/J genome assembly

Annotation on the reference genome of the C57BL6/J mouse has been an ongoing project ever since the draft genome was first published. Initially, the principle focus was on the identification of all protein-coding genes, although today the importance of describing long non-coding RNAs, small RNAs, and pseudogenes is recognized. Here, we describe the progress of the GENCODE mouse annotation project, which combines manual annotation from the HAVANA group with Ensembl computational annotation, alongside experimental and in silico validation pipelines from other members of the consortium. We discuss the more recent incorporation of next-generation sequencing datasets into this workflow, including the usage of mass-spectrometry data to potentially identify novel protein-coding genes. Finally, we will outline how the C57BL6/J genebuild can be used to gain insights into the variant sites that distinguish different mouse strains and species.

Matching Kidneys and Urines: Establishing Noninvasive Surrogates of Intrarenal Events in Primary Glomerulonephritis

Kidney biopsy is the gold standard procedure for providing diagnostic and prognostic information for patients with glomerular-based diseases, however, the utility of this procedure for assessing longitudinal disease activity is limited. The intense search for noninvasive biomarkers of kidney disease activity and injury is driven in large part by the inherent risks of the kidney biopsy procedure and limited information derived from the morphologic description of biopsy findings. Furthermore, gaps in our understanding of the core intrarenal molecular processes underlying the development and progression of glomerular-based diseases has limited the development of effective targeted therapy. In this review, we discuss the potential utility of molecular analysis of the urine to provide a dynamic window into intrarenal molecular and morphologic responses. We focus on molecular analysis of the urine to identify noninvasive surrogate markers of kidney responses, with the goal of using these biomarkers as more sensitive indicators of progression and tissue-level responses to therapeutic interventions in patients with primary glomerulonephritis.

Proteotranscriptomic Profiling of 231-BR Breast Cancer Cells: Identification of Potential Biomarkers and Therapeutic Targets for Brain Metastasis

Brain metastases are a devastating consequence of cancer and currently there are no specific biomarkers or therapeutic targets for risk prediction, diagnosis, and treatment. Here the proteome of the brain metastatic breast cancer cell line 231-BR has been compared with that of the parental cell line MDA-MB-231, which is also metastatic but has no organ selectivity. Using SILAC and nanoLC-MS/MS, 1957 proteins were identified in reciprocal labeling experiments and 1584 were quantified in the two cell lines. A total of 152 proteins were confidently determined to be up- or down-regulated by more than twofold in 231-BR. Of note, 112/152 proteins were decreased as compared with only 40/152 that were increased, suggesting that down-regulation of specific proteins is an important part of the mechanism underlying the ability of breast cancer cells to metastasize to the brain. When matched against transcriptomic data, 43% of individual protein changes were associated with corresponding changes in mRNA, indicating that the transcript level is a limited predictor of protein level. In addition, differential miRNA analyses showed that most miRNA changes in 231-BR were up- (36/45) as compared with down-regulations (9/45). Pathway analysis revealed that proteome changes were mostly related to cell signaling and cell cycle, metabolism and extracellular matrix remodeling. The major protein changes in 231-BR were confirmed by parallel reaction monitoring mass spectrometry and consisted in increases (by more than fivefold) in the matrix metalloproteinase-1, ephrin-B1, stomatin, myc target-1, and decreases (by more than 10-fold) in transglutaminase-2, the S100 calcium-binding protein A4, and l-plastin. The clinicopathological significance of these major proteomic changes to predict the occurrence of brain metastases, and their potential value as therapeutic targets, warrants further investigation.