Distilling cancer biomarkers from the serum peptidome: high technology reading of tea leaves or an insight to clinical systems biology?

Contribution of the plasma and lymph Degradome and Peptidome to the MHC Ligandome

Every biological fluid, blood, interstitial fluid and lymph, urine, saliva, lacrimal fluid, nipple aspirate, and spinal fluid, contains a peptidome-degradome derived from the cellular secretome along with byproducts of the metabolic/catabolic activities of each parenchymal organ. Clement et al. (J Proteomics 78:172-187, 2013), Clement et al. (J Biol Chem 291:5576-5595, 2016), Clement et al. (PLoS One 5:e9863, 2010), Clement et al. (Trends Immunol 32:6-11, 2011), Clement et al. (Front Immunol 4:424, 2013), Geho et al. (Curr Opin Chem Biol 10, 50-55, 2006), Interewicz et al. (Lymphology 37:65‑72, 2004), Leak et al. (Proteomics 4:753‑765, 2004), Popova et al. (PLoS One 9:e110873, 2014), Zhou et al. (Electrophoresis 25:1289‑1298, 2004), D'Alessandro et al. (Shock 42:509‑517, 2014), Dzieciatkowska et al. (Shock 42:485‑498, 2014), Dzieciatkowska et al. (Shock 35:331‑338, 2011), Jordan et al. (J Surg Res 143:130‑135, 2007), Peltz et al. (Surgery 146:347‑357, 2009), Zurawel et al. (Clin Proteomics 8:1, 2011), Ling et al. (Clin Proteomics 6:175‑193, 2010), Sturm et al. (Nat Commun 4:1616, 2013). Over the last decade, qualitative and quantitative analysis of the biological fluids peptidome and degradome have provided a dynamic measurement of tissue homeostasis as well as the tissue response to pathological damage. Proteomic profiling has mapped several of the proteases and resulting degradation by-products derived from cell cycle progression, organ/tissue remodeling and cellular growth, physiological apoptosis, hemostasis, and angiogenesis. Currently, a growing interest lies in the degradome observed during pathological conditions such as cancer, autoimmune diseases, and immune responses to pathogens as a way to exploit biological fluids as liquid biopsies for biomarker discovery Dzieciatkowska et al. (Shock 42:485-498, 2014), Dzieciatkowska et al. (Shock 35:331-338, 2011), Ling et al. (Clin Proteomics 6:175-193, 2010), Ugalde et al. (Methods Mol Biol 622:3-29, 2010), Quesada et al. (Nucleic Acids Res 37:D239‑243, 2009), Cal et al. (Front Biosci 12, 4661-4669, 2007), Shen et al. (PLoS One 5:e13133, 2010a), Antwi et al. (Mol Immunol 46:2931-2937, 2009a), Antwi et al. (J Proteome Res 8:4722‑4731, 2009b), Bedin et al. (J Cell Physiol 231, 915‑925, 2016), Bery et al. (Clin Proteomics 11:13, 2014), Bhalla et al. (Sci Rep 7:1511, 2017), Fan et al. (Diagn Pathol 7:45, 2012a), Fang et al. (Shock 34:291‑298, 2010), Fiedler et al. (Clin Cancer Res 15:3812‑3819, 2009), Fredolini et al. (AAPS J 12:504‑518, 2010), Greening et al. (Enzymes 42:27‑64, 2017), He et al. (PLoS One 8:e63724, 2013), Huang et al. (Int J Gynecol Cancer 28:355‑362, 2018), Hashiguchi et al. (Med Hypotheses 73:760‑763, 2009), Liotta and Petricoin (J Clin Invest 116:26‑30, 2006), Petricoin et al. (Nat Rev Cancer 6:961‑967, 2006), Shen et al. (J Proteome Res 9:2339‑2346, 2010a), Shen et al. (J Proteome Res 5:3154‑3160, 2006), Smith (Clin Proteomics 11:23, 2014), Wang et al. (Oncotarget 8:59376‑59386, 2017), Yang et al. (Clin Exp Med 12:79‑87, 2012a), Yang et al. (J Clin Lab Anal 26:148‑154, 2012b), Yang et al. (Anat Rec (Hoboken) 293:2027‑2033, 2010), Zapico-Muniz et al. (Pancreas 39:1293‑1298, 2010), Villanueva et al. (Mol Cell Proteomics 5:1840‑1852, 2006), Robbins et al. (J Clin Oncol 23:4835‑4837, 2005), Klupczynska et al. (Int J Mol Sci 17:410, 2016). In this review, we focus on the current knowledge of the degradome/peptidome observed in two main biological fluids (plasma and lymph) during physiological and pathological conditions and its importance for immune surveillance.

Peptidome analysis of human milk from women delivering macrosomic fetuses reveals multiple means of protection for infants

Breastfeeding is associated with a lower incidence of obesity, diabetes, and cardiovascular disease later in life. While macrosomic infants have a higher risk of developing obesity and other metabolic disorders. Breast milk may contain special nutrients to meet the different growth needs of different infants. Whether mothers make breast milk different to meet the requirement of macrosomic infants is still unknown. Here, we conducted a comparison between mothers delivering macrosomic and non-macrosomic infants in colostrum endogenous peptides. More than 400 peptides, originating from at least 34 protein precursors, were identified by Liquid Chromatography/Mass Spectrometry (LC/MS). Out of these, 29 peptides found to be significant differently expressed (|fold change| ≥ 3, P < 0.01). Blastp analysis revealed 41 peptides may have established biological activities, which exhibit immunomodulating, antibacterial action, antioxidation, opioid agonist and antihypertensive activity. Furthermore, we found that peptide located at β-Casein 24-38 AA has antimicrobial effect against E. coli, Y. enterocolitica and S. aureus. While, κ-Casein 89-109 AA-derived peptide plays as a regulator of preadipocyte proliferation. The profile of endogenous peptides from macrosomic term infants is different from non-macrosomic terms. This different peptide expression potentially has specific physiological function to benefit macrosomic infants. Finally, we believe that our research is a meaningfull finding which may add to the understanding of milk peptide physiological action.

Proteomics as a Tool for Clinically Relevant Biomarker Discovery and Validation

The excitement associated with clinical applications of proteomics was initially focused on its potential to serve as a vehicle for both biomarker discovery and drug discovery and routine clinical sample analysis. Some approaches were thought to be able to “identify” mass spectral characteristics that distinguished between control and disease samples, and thereafter it was believed that the same tool could be employed to screen samples in a high-throughput clinical setting. However, this has been difficult to achieve, and the early promise is yet to be fully realized. While we see an important place for mass spectrometry in drug and biomarker discovery, we believe that alternative strategies will prove more fruitful for routine analysis. Here we discuss the power and versatility of 2D gels and mass spectrometry in the discovery phase of biomarker work but argue that it is better to rely on immunochemical methods for high-throughput validation and routine assay applications.

Peptidome analysis of human skim milk in term and preterm milk

The abundant proteins in human milk have been well characterized and are known to provide nutritional, protective, and developmental advantages to both term and preterm infants. Due to the difficulties associated with detection technology of the peptides, the expression of the peptides present in human milk is not known widely. In recent years, peptidome analysis has received increasing attention. In this report, the analysis of endogenous peptides in human milk was done by mass spectrometry. A method was also developed by our researchers, which can be used in the extraction of peptide from human milk. Analysis of the extracts by LC-MS/MS resulted in the detection of 1000-3000Da peptide-like features. Out of these, 419 peptides were identified by MS/MS. The identified peptides were found to originate from 34 proteins, of which several have been reported. Analysis of the peptides' cleavage sites showed that the peptides are cleaved with regulations. This may reflect the protease activity and distribution in human body, and also represent the biological state of the tissue and provide a fresh source for biomarker discovery. Isotope dimethyl labeling analysis was also used to test the effects of premature delivery on milk protein composition in this study. Differences in peptides expression between breast milk in term milk (38-41weeks gestation) and preterm milk (28-32weeks gestation) were investigated in this study. 41 Peptides in these two groups were found expressed differently. 23 Peptides were present at higher levels in preterm milk, and 18 were present at higher levels in term milk.

Proteomic applications in ecotoxicology

Within the growing body of proteomics studies, issues addressing problems of ecotoxicology are on the rise. Generally speaking, ecotoxicology uses quantitative expression changes of distinct proteins known to be involved in toxicological responses as biomarkers. Unlike these directed approaches, proteomics examines how multiple expression changes are associated with a contamination that is suspected to be detrimental. Consequently, proteins involved in toxicological responses that have not been described previously may be revealed. Following identification of key proteins indicating exposure or effect, proteomics can potentially be employed in environmental risk assessment. To this end, bioinformatics may unveil protein patterns specific to an environmental stress that would constitute a classifier able to distinguish an exposure from a control state. The combined use of sets of marker proteins associated with a given pollution impact may prove to be more reliable, as they are based not only on a few unique markers which are measured independently, but reflect the complexity of a toxicological response. Such a proteomic pattern might also integrate some of the already established biomarkers of environmental toxicity. Proteomics applications in ecotoxicology may also comprise functional examination of known classes of proteins, such as glutathione transferases or metallothioneins, to elucidate their toxicological responses.

Human body fluid proteome analysis

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.

Data processing and classification analysis of proteomic changes: a case study of oil pollution in the mussel, Mytilus edulis

BACKGROUND

Proteomics may help to detect subtle pollution-related changes, such as responses to mixture pollution at low concentrations, where clear signs of toxicity are absent. The challenges associated with the analysis of large-scale multivariate proteomic datasets have been widely discussed in medical research and biomarker discovery. This concept has been introduced to ecotoxicology only recently, so data processing and classification analysis need to be refined before they can be readily applied in biomarker discovery and monitoring studies.

RESULTS

Data sets obtained from a case study of oil pollution in the Blue mussel were investigated for differential protein expression by retentate chromatography-mass spectrometry and decision tree classification. Different tissues and different settings were used to evaluate classifiers towards their discriminatory power. It was found that, due the intrinsic variability of the data sets, reliable classification of unknown samples could only be achieved on a broad statistical basis (n > 60) with the observed expression changes comprising high statistical significance and sufficient amplitude. The application of stringent criteria to guard against overfitting of the models eventually allowed satisfactory classification for only one of the investigated data sets and settings.

CONCLUSION

Machine learning techniques provide a promising approach to process and extract informative expression signatures from high-dimensional mass-spectrometry data. Even though characterisation of the proteins forming the expression signatures would be ideal, knowledge of the specific proteins is not mandatory for effective class discrimination. This may constitute a new biomarker approach in ecotoxicology, where working with organisms, which do not have sequenced genomes render protein identification by database searching problematic. However, data processing has to be critically evaluated and statistical constraints have to be considered before supervised classification algorithms are employed.

Selective binding and enrichment for low-molecular weight biomarker molecules in human plasma after exposure to nanoporous silica particles

The present manuscript describes a biomarker capturing strategy based on nanoporous silica particles. The method is shown to enrich the yield of species in the low-molecular weight proteome (LMWP), allowing detection of small peptides in the low-nanomolar range. Plasma samples were exposed to the silica particles, and the captured molecular species were profiled using MALDI-TOF. Mass spectra of the silica-treated human plasma samples showed a significant enrichment in MALDI-TOF protein profiles in the LMWP. Preliminary results indicated good level of reproducibility in plasma profiles with CVs on peak heights ranging from 6.3 to 14.7%. The MALDI-TOF signature changed significantly when the characteristics of the nanoporous silica were altered. The facile sample pretreatment before MS analysis, coupled to the potential for tailoring the surface properties of silica supports, hold promise for improving the recovery of low-abundance serum biomarkers.

Translating genomic biomarkers into clinically useful diagnostics

The landmark sequencing of the human genome has ushered in a new field of large-scale research. Advances in understanding the molecular basis of disease have opened up new opportunities to develop genomics-based tools to diagnose, predict disease onset or recurrence, tailor treatment options, and assess treatment response. Although still in the early stages of research and development, genomic biomarker research has the capability of providing a comprehensive insight into pathophysiological processes as well as more precise predictors of outcome not previously attainable with traditional biomarkers. Before genomic biomarkers are incorporated into clinical practice, several issues will need to be addressed in order to generate the necessary levels of evidence to demonstrate analytical and clinical validity and utility. In addition, efforts will be needed to educate health professionals and the public about genomics-based tools, revise regulatory oversight mechanisms, and ensure privacy safeguards of the information generated from these new tests.

A systems approach to clinical oncology: focus on breast cancer

During the past decade, genomic microarrays have been applied with some success to the molecular profiling of breast tumours, which has resulted in a much more detailed classification scheme as well as in the identification of potential gene signature sets. These gene sets have been applied to both the prognosis and prediction of outcome to treatment and have performed better than the current clinical criteria. One of the main limitations of microarray analysis, however, is that frozen tumour samples are required for the assay. This imposes severe limitations on access to samples and precludes large scale validation studies from being conducted. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), on the other hand, can be used with degraded RNAs derived from formalin-fixed paraffin-embedded (FFPE) tumour samples, the most important and abundant source of clinical material available. More recently, the novel DASL (cDNA-mediated Annealing, Selection, extension and Ligation) assay has been developed as a high throughput gene expression profiling system specifically designed for use with FFPE tumour tissue samples.However, we do not believe that genomics is adequate as a sole prognostic and predictive platform in breast cancer. The key proteins driving oncogenesis, for example, can undergo post-translational modifications; moreover, if we are ever to move individualization of therapy into the practical world of blood-based assays, serum proteomics becomes critical. Proteomic platforms, including tissue micro-arrays (TMA) and protein chip arrays, in conjunction with surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF/MS), have been the technologies most widely applied to the characterization of tumours and serum from breast cancer patients, with still limited but encouraging results. This review will focus on these genomic and proteomic platforms, with an emphasis placed on the utilization of FFPE tumour tissue samples and serum, as they have been applied to the study of breast cancer for the discovery of gene signatures and biomarkers for the early diagnosis, prognosis and prediction of treatment outcome. The ultimate goal is to be able to apply a systems biology approach to the information gleaned from the combination of these techniques in order to select the best treatment strategy, monitor its effectiveness and make changes as rapidly as possible where needed to achieve the optimal therapeutic results for the patient.