In situ identification and localization of IGHA2 in the breast tumor microenvironment by mass spectrometry

Reconstructing the ancestral gene pool to uncover the origins and genetic links of Hmong-Mien speakers

BACKGROUND

Hmong-Mien (HM) speakers are linguistically related and live primarily in China, but little is known about their ancestral origins or the evolutionary mechanism shaping their genomic diversity. In particular, the lack of whole-genome sequencing data on the Yao population has prevented a full investigation of the origins and evolutionary history of HM speakers. As such, their origins are debatable.

RESULTS

Here, we made a deep sequencing effort of 80 Yao genomes, and our analysis together with 28 East Asian populations and 968 ancient Asian genomes suggested that there is a strong genetic basis for the formation of the HM language family. We estimated that the most recent common ancestor dates to 5800 years ago, while the genetic divergence between the HM and Tai-Kadai speakers was estimated to be 8200 years ago. We proposed that HM speakers originated from the Yangtze River Basin and spread with agricultural civilization. We identified highly differentiated variants between HM and Han Chinese, in particular, a deafness-related missense variant (rs72474224) in the GJB2 gene is in a higher frequency in HM speakers than in others.

CONCLUSIONS

Our results indicated complex gene flow and medically relevant variants involved in the HM speakers' evolution history.

The Expression of Non B Cell-Derived Immunoglobulins

Although V(D)J recombination and immunoglobulin (Ig) production are traditionally recognised to occur only in B lymphocytes and plasma cells, the expression of Igs in non-lymphoid cells, which we call non B cell-derived Igs (non B Igs), has been documented by growing studies. It has been demonstrated that non B-Igs can be widely expressed in most cell types, including, but not limited to, epithelial cells, cardiomyocytes, hematopoietic stem/progenitor cells, myeloid cells, and cells from immune-privileged sites, such as neurons and spermatogenic cells. In particular, malignant tumour cells express high level of IgG. Moreover, different from B-Igs that mainly localised on the B cell membrane and in the serum and perform immune defence function mainly, non B-Igs have been found to distribute more widely and play critical roles in immune defence, maintaining cell proliferation and survival, and promoting progression. The findings of non B-Igs may provide a wealthier breakthrough point for more therapeutic strategies for a wide range of immune-related diseases.

Comparison of Non B-Ig and B-Ig

Immunoglobulin (Ig) has been widely acknowledged to be produced solely by B-lineage cells. However, growing evidence has demonstrated the expression of Ig in an array of cancer cells, as well as normal cells including epithelial cells, epidermal cells, mesangial cells, monocytes, and neutrophils. Ig has even been found to be expressed in non-B cells at immune-privileged sites such as neurons and spermatogenic cells. Despite these non-B cell-derived Igs (non-B-Igs) sharing the same symmetric structures with conventional Igs (B-Igs), further studies have revealed unique characteristics of non-B-Ig, such as restricted variable region and aberrant glycosylation. Moreover, non-B-Ig exhibits properties of promoting malignant behaviours of cancer cells, therefore it could be utilised in the clinic as a potential therapeutic biomarker or target. The elucidation of the generation and regulation of non-B-Ig will certainly broaden our understanding of immunology.

Applications of MALDI-MS/MS-Based Proteomics in Biomedical Research

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is one of the most widely used techniques in proteomics to achieve structural identification and characterization of proteins and peptides, including their variety of proteoforms due to post-translational modifications (PTMs) or protein-protein interactions (PPIs). MALDI-MS and MALDI tandem mass spectrometry (MS/MS) have been developed as analytical techniques to study small and large molecules, offering picomole to femtomole sensitivity and enabling the direct analysis of biological samples, such as biofluids, solid tissues, tissue/cell homogenates, and cell culture lysates, with a minimized procedure of sample preparation. In the last decades, structural identification of peptides and proteins achieved by MALDI-MS/MS helped researchers and clinicians to decipher molecular function, biological process, cellular component, and related pathways of the gene products as well as their involvement in pathogenesis of diseases. In this review, we highlight the applications of MALDI ionization source and tandem approaches for MS for analyzing biomedical relevant peptides and proteins. Furthermore, one of the most relevant applications of MALDI-MS/MS is to provide "molecular pictures", which offer in situ information about molecular weight proteins without labeling of potential targets. Histology-directed MALDI-mass spectrometry imaging (MSI) uses MALDI-ToF/ToF or other MALDI tandem mass spectrometers for accurate sequence analysis of peptide biomarkers and biological active compounds directly in tissues, to assure complementary and essential spatial data compared with those obtained by LC-ESI-MS/MS technique.

A novel pyroptosis-related indicator of immune infiltration features and prognosis in breast cancer

Breast cancer is the most common malignancy in women, and there is evidence for the dual role of cell pyroptosis in tumor development. However, little is known about the relationship between cell pyroptosis and breast cancer and its prognostic value. We aimed to construct a prognostic model using cell-pyroptosis-related genes to provide innovative insights into the prognosis and treatment of breast cancer. We screened candidate genes for pyroptosis using public databases and identified 10 cell pyroptosis signature genes with the random forest method. Finally, a nomogram for predicting 1-, 3-, and 5-year survival probabilities was constructed. The differences in immune cell distributions between survival periods were similar across the breast cancer datasets. The 10 identified key pyroptosis factors showed a significant correlation with Her2, tumor–node–metastasis (TNM) stage, and survival of breast cancer. The risk scores correlated positively with the infiltration features of naive B cells, CD8+ T cells, atpdelnd mast cells, while they correlated negatively with those of M0 macrophages and dendritic cells. In conclusion, our findings confirm that cell pyroptosis is closely associated with breast cancer. Importantly, the prognostic complex values generated from the 10 cell-pyroptosis-related genes based on various clinical features may provide an important basis for future studies on the prognosis of breast cancer.

A Novel Signature Integrated of Immunoglobulin, Glycosylation and Anti-Viral Genes to Predict Prognosis for Breast Cancer

Background: Aberrant glycosylation is significantly related to the occurrence, progression, metastasis, and drug resistance of tumors. It is essential to identify glycosylation and related genes with prognostic value for breast cancer.

Objective: We aimed to construct and validate a prognostic model based on glycosylation and related genes, and further investigate its prognosis values in validation set and external independent cohorts.

Materials and Methods: The transcriptome and clinical data of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA, n = 1072), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1451), and GSE2741 (n = 120). Glycosylation-related genes were downloaded from the Genecards website. Differentially expressed glycosylation-related geneswere identified by comparing the tumor tissues with the adjacent tissues. The TCGA data were randomly divided into training set and validation set in a 1:1 ratio for further analysis. The glycosylation risk-scoring prognosis model was constructed by univariate and multivariate Cox regression analysis, followed by confirmation in TCGA validation, METABRIC, and GEO datasets. Gene set enrichment analysis (GSEA) and Gene ontology analysis for identifying the affected pathways in the high- and low-risk groups were performed.

Results: We attained 1072 breast cancer samples from the TCGA database and 786 glycosylation genes from the Genecards website. A signature contains immunoglobulin, glycosylation and anti-viral related genes was constructed to separate BRCA patients into two risk groups. Low-risk patients had better overall survival than high-risk patients (p < 0.001). A nomogram was constructed with risk scores and clinical characteristics. The area under time-dependent ROC curve reached 0.764 at 1 year, 0.744 at 3 years, and 0.765 at 5 years in the training set. Subgroup analysis showed differences in OS between the high- and low-risk patients in different subgroups. Moreover, the risk score was confirmed as an independent prognostic indicator of BRCA patients and was potentially correlated with immunotherapy response and drug sensitivity.

Conclusion: We identified a novel signature integrated of immunoglobulin (IGHA2), glycosylation-related (SLC35A2) and anti-viral gene (BST2) that was an independent prognostic indicator for BRCA patients. The risk-scoring model could be used for predicting prognosis and immunotherapy in BRCA, thus providing a powerful instrument for combating BRCA.

Machine learning-aided protein identification from multidimensional signatures

The ability to determine the identity of specific proteins is a critical challenge in many areas of cellular and molecular biology, and in medical diagnostics. Here, we present a macine learning aided microfluidic protein characterisation strategy that within a few minutes generates a three-dimensional fingerprint of a protein sample indicative of its amino acid composition and size and, thereby, creates a unique signature for the protein. By acquiring such multidimensional fingerprints for a set of ten proteins and using machine learning approaches to classify the fingerprints, we demonstrate that this strategy allows proteins to be classified at a high accuracy, even though classification using a single dimension is not possible. Moreover, we show that the acquired fingerprints correlate with the amino acid content of the samples, which makes it is possible to identify proteins directly from their sequence without requiring any prior knowledge about the fingerprints. These findings suggest that such a multidimensional profiling strategy can lead to the development of a novel method for protein identification in a microfluidic format.

Immunoglobulin Expression in Cancer Cells and Its Critical Roles in Tumorigenesis

Traditionally, immunoglobulin (Ig) was believed to be produced by only B-lineage cells. However, increasing evidence has revealed a high level of Ig expression in cancer cells, and this Ig is named cancer-derived Ig. Further studies have shown that cancer-derived Ig shares identical basic structures with B cell-derived Ig but exhibits several distinct characteristics, including restricted variable region sequences and aberrant glycosylation. In contrast to B cell-derived Ig, which functions as an antibody in the humoral immune response, cancer-derived Ig exerts profound protumorigenic effects via multiple mechanisms, including promoting the malignant behaviors of cancer cells, mediating tumor immune escape, inducing inflammation, and activating the aggregation of platelets. Importantly, cancer-derived Ig shows promising potential for application as a diagnostic and therapeutic target in cancer patients. In this review, we summarize progress in the research area of cancer-derived Ig and discuss the perspectives of applying this novel target for the management of cancer patients.

Disorders of Calcium and Phosphorus Metabolism and the Proteomics/Metabolomics-Based Research

Since calcium and phosphorus play vital roles in a multitude of physiologic systems, disorders of calcium and phosphorus metabolism always lead to severe consequences such as skeletal-related and cardiovascular morbidity, or even life-threatening. Physiologically, the maintenance of calcium and phosphorus homeostasis is achieved via a variety of concerted actions of hormones such as parathyroid hormone (PTH), vitamin D, and fibroblast growth factor (FGF23), which could be regulated mainly at three organs, the intestine, kidney, and bone. Disruption of any organ or factor might lead to disorders of calcium and phosphorus metabolism. Currently, lacking of accurate diagnostic approaches and unknown molecular basis of pathophysiology will result in patients being unable to receive a precise diagnosis and personalized treatment timely. Therefore, it is urgent to identify early diagnostic biomarkers and develop therapeutic strategies. Fortunately, proteomics and metabolomics offer promising tools to discover novel indicators and further understanding of pathological mechanisms. Therefore, in this review, we will give a systematic introduction on PTH-1,25(OH)₂D-FGF23 axis in the disorders of calcium and phosphorus metabolism, diagnostic biomarkers identified, and potential altered metabolic pathways involved.

Discovery of Prognostic Markers for Early-Stage High-Grade Serous Ovarian Cancer by Maldi-Imaging

With regard to relapse and survival, early-stage high-grade serous ovarian (HGSOC) patients comprise a heterogeneous group and there is no clear consensus on first-line treatment. Currently, no prognostic markers are available for risk assessment by standard targeted immunohistochemistry and novel approaches are urgently required. Here, we applied MALDI-imaging mass spectrometry (MALDI-IMS), a new method to identify distinct mass profiles including protein signatures on paraffin-embedded tissue sections. In search of prognostic biomarker candidates, we compared proteomic profiles of primary tumor sections from early-stage HGSOC patients with either recurrent (RD) or non-recurrent disease (N = 4; each group) as a proof of concept study. In total, MALDI-IMS analysis resulted in 7537 spectra from the malignant tumor areas. Using receiver operating characteristic (ROC) analysis, 151 peptides were able to discriminate between patients with RD and non-RD (AUC > 0.6 or < 0.4; p < 0.01), and 13 of them could be annotated to proteins. Strongest expression levels of specific peptides linked to Keratin type1 and Collagen alpha-2(I) were observed and associated with poor prognosis (AUC > 0.7). These results confirm that in using IMS, we could identify new candidates to predict clinical outcome and treatment extent for patients with early-stage HGSOC.

Identification of a six-gene signature associated with tumor mutation burden for predicting prognosis in patients with invasive breast carcinoma

Background

Breast cancer (BC) is one of the most common cancers with high mortality worldwide. In the present study, through bioinformatics analysis, we aimed to identify new biomarkers to predict the survival rate of BC patients.

Methods

Differentially expressed genes (DEGs) between low- and high-tumor mutation burden (TMB) groups were identified by using The Cancer Genome Atlas (TCGA) dataset and integrated analysis. Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the protein-protein interaction (PPI) network, were applied to predict the function of these above DEGs. Then, the Cox proportional hazard model was developed to screen DEGs. Based on the prognostic signature, survival analysis was used on The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. Finally, the single-sample gene set enrichment (ssGSEA) analysis was employed to estimate immune cells related to this signature.

Results

To create a prognostic signature, 6 DEGs were identified. The results revealed that the survival time of patients with high-risk scores based on the expression of the six-gene signature was dramatically shorter than that of patients with low-risk scores in BC. Furthermore, survival analysis and multivariate cox analysis indicated that the six-gene signature was an independent prognostic factor of BC. Then, we built a nomogram that integrated the clinicopathological factors with the six-gene signature to predict the survival probability of BC patients. We eventually predicted the 20 most vital small molecule drugs by CMap, and Nadolol was considered as the most promising small molecule to treat BC. Moreover, ssGSEA analysis showed that the 6 genes were closely associated with immune cells.

Conclusions

We constructed a six-gene signature associated with TMB that can improve the prognosis prediction and could be seen as a biomarker for BC patients.

Imaging Mass Spectrometry and Proteome Analysis of Marek's Disease Virus-Induced Tumors

The highly oncogenic alphaherpesvirus Marek's disease virus (MDV) causes immense economic losses in the poultry industry. MDV induces a variety of symptoms in infected chickens, including neurological disorders and immunosuppression. Most notably, MDV induces transformation of lymphocytes, leading to T cell lymphomas in visceral organs with a mortality of up to 100%. While several factors involved in MDV tumorigenesis have been identified, the transformation process and tumor composition remain poorly understood. Here we developed an imaging mass spectrometry (IMS) approach that allows sensitive visualization of MDV-induced lymphoma with a specific mass profile and precise differentiation from the surrounding tissue. To identify potential tumor markers in tumors derived from a very virulent wild-type virus and a telomerase RNA-deficient mutant, we performed laser capture microdissection (LCM) and thereby obtained tumor samples with no or minimal contamination from surrounding nontumor tissue. The proteomes of the LCM samples were subsequently analyzed by quantitative mass spectrometry based on stable isotope labeling. Several proteins, like interferon gamma-inducible protein 30 and a 70-kDa heat shock protein, were identified that are differentially expressed in tumor tissue compared to surrounding tissue and naive T cells. Taken together, our results demonstrate for the first time that MDV-induced tumors can be visualized using IMS, and we identified potential MDV tumor markers by analyzing the proteomes of virus-induced tumors.IMPORTANCE Marek's disease virus (MDV) is an oncogenic alphaherpesvirus that infects chickens and causes the most frequent clinically diagnosed cancer in the animal kingdom. Not only is MDV an important pathogen that threatens the poultry industry but it is also used as a natural virus-host model for herpesvirus-induced tumor formation. In order to visualize MDV-induced lymphoma and to identify potential biomarkers in an unbiased approach, we performed imaging mass spectrometry (IMS) and noncontact laser capture microdissection. This study provides a first description of the visualization of MDV-induced tumors by IMS that could be applied also for diagnostic purposes. In addition, we identified and validated potential biomarkers for MDV-induced tumors that could provide the basis for future research on pathogenesis and tumorigenesis of this malignancy.

Multiplex assay for multiomics advances in personalized-precision medicine

Building the future of precision medicine is the main focus in cancer domain. Clinical trials are moving toward an array of studies that are more adapted to precision medicine. In this domain, there is an enhanced need for biomarkers, monitoring devices, and data-analysis methods. Omics profiling using whole genome, epigenome, transcriptome, proteome, and metabolome can offer detailed information of the human body in an integrative manner. Omes profiles reflect more accurately real-time physiological status. Personalized omics analyses both disease as a whole and the main disease processes, for a better understanding of the individualized health. Through this, multi-omic approaches for health monitoring, preventative medicine, and personalized treatment can be targeted simultaneously and can lead clinicians to have a comprehensive view on the diseasome.

Drought-Tolerant Brassica rapa Shows Rapid Expression of Gene Networks for General Stress Responses and Programmed Cell Death Under Simulated Drought Stress

Production of oilseed rape/canola (Brassica napus) is increasingly threatened by dry conditions while the demand for vegetable oil is increasing. Brassica rapa is a genetically diverse ancestor of B. napus, and is readily crossed with B. napus. Recently, we reported promising levels of drought tolerance in a wild type of B. rapa which could be a source of drought tolerance for B. napus. We analysed global gene expression by messenger RNA sequencing in seedlings of the drought-tolerant and a drought-sensitive genotype of B. rapa under simulated drought stress and control conditions. A subset of stress-response genes were validated by reverse transcription quantitative PCR. Gene ontology enrichment analysis and pathway enrichment analysis revealed major differences between the two genotypes in the mode and onset of stress responses in the first 12 h of treatment. Drought-tolerant plants reacted uniquely and rapidly by upregulating genes associated with jasmonic acid and salicylic acid metabolism, as well as genes known to cause endoplasmic reticulum stress and induction of programmed cell death. Conversely, active responses in drought-sensitive plants were delayed until 8 or 12 h after stress application. The results may help to identify biomarkers for selection of breeding materials with potentially improved drought tolerance.

MALDI imaging mass spectrometry reveals multiple clinically relevant masses in colorectal cancer using large-scale tissue microarrays

For identification of clinically relevant masses to predict status, grade, relapse and prognosis of colorectal cancer, we applied Matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS) to a tissue micro array containing formalin-fixed and paraffin-embedded tissue samples from 349 patients. Analysis of our MALDI-IMS data revealed 27 different m/z signals associated with epithelial structures. Comparison of these signals showed significant association with status, grade and Ki-67 labeling index. Fifteen out of 27 IMS signals revealed a significant association with survival. For seven signals (m/z 654, 776, 788, 904, 944, 975 and 1013) the absence and for eight signals (m/z 643, 678, 836, 886, 898, 1095, 1459 and 1477) the presence were associated with decreased life expectancy, including five masses (m/z 788, 836, 904, 944 and 1013) that provided prognostic information independently from the established prognosticators pT and pN. Combination of these five masses resulted in a three-step classifier that provided prognostic information superior to univariate analysis. In addition, a total of 19 masses were associated with tumor stage, grade, metastasis and cell proliferation. Our data demonstrate the suitability of combining IMS and large-scale tissue micro arrays to simultaneously identify and validate clinically useful molecular marker. Copyright © 2017 John Wiley & Sons, Ltd.

Clinical applications of MALDI imaging technologies in cancer and neurodegenerative diseases

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) enables localization of analytes of interest along with histology. More specifically, MALDI-IMS identifies the distributions of proteins, peptides, small molecules, lipids, and drugs and their metabolites in tissues, with high spatial resolution. This unique capacity to directly analyze tissue samples without the need for lengthy sample preparation reduces technical variability and renders MALDI-IMS ideal for the identification of potential diagnostic and prognostic biomarkers and disease gradation. MALDI-IMS has evolved rapidly over the last decade and has been successfully used in both medical and basic research by scientists worldwide. In this review, we explore the clinical applications of MALDI-IMS, focusing on the major cancer types and neurodegenerative diseases. In particular, we re-emphasize the diagnostic potential of IMS and the challenges that must be confronted when conducting MALDI-IMS in clinical settings. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Nodal metastasis signatures in breast cancer

Although the molecular taxonomy of invasive breast cancer is based on heterogeneous histologic types, pathologic nodal (pN) stage remains one of the most important independent prognostic factors. Although node-positive number (NPN) has been widely as an accepted staging algorithm of pN stage, the node-positive ratio (NPR) in totally resected axillary nodes has been considered as another reasonable indicator. We aimed to identify signatures to play a predictive role in nodal metastasis for analytic validation between the primary breast cancers with positive node metastasis and those with negative node metastasis. We validated expression profiles of surrogate candidates extracted from the prior 2D MALDI-TOF data for invasive breast cancer using fluorescence/silver in situ hybridization (FISH/SISH) and immunohistochemistry (IHC) in 151 primary breast cancers accompanied with 102 metastatic nodal tissues. Cox proportional hazards regression analyses indicated that event factors (recurrence or metastasis) were significantly more frequent in cases with CCDN1, c-myc gene amplification, IgHA2 low expression. CCDN1 gene amplification (OR: 5.702, p=0.0006), IgHA2 low expression (OR: 0.16, p=0.0184) remained significant factors for events on multivariate analyses. WDR⁺/ERK⁺⁺ was significantly detected in higher pN stage (averaging 6.5 regional nodes or 43% of NPR), while seldom found in pN0-1. In conclusion, both overexpression of WDR1 and p-ERK in the primary breast cancer could play a role in the nodal signature over pN2-3.

MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology

Histopathological diagnoses have been done in the last century based on hematoxylin and eosin staining. These methods were complemented by histochemistry, electron microscopy, immunohistochemistry (IHC), and molecular techniques. Mass spectrometry (MS) methods allow the thorough examination of various biocompounds in extracts and tissue sections. Today, mass spectrometry imaging (MSI), and especially matrix-assisted laser desorption ionization (MALDI) imaging links classical histology and molecular analyses. Direct mapping is a major advantage of the combination of molecular profiling and imaging. MSI can be considered as a cutting edge approach for molecular detection of proteins, peptides, carbohydrates, lipids, and small molecules in tissues. This review covers the detection of various biomolecules in histopathological sections by MSI. Proteomic methods will be introduced into clinical histopathology within the next few years.

Mechano-stimulated modifications in the chloroplast antioxidant system and proteome changes are associated with cold response in wheat

BACKGROUND

Mechanical wounding can cause morphological and developmental changes in plants, which may affect the responses to abiotic stresses. However, the mechano-stimulation triggered regulation network remains elusive. Here, the mechano-stimulation was applied at two different times during the growth period of wheat before exposing the plants to cold stress (5.6 °C lower temperature than the ambient temperature, viz., 5.0 °C) at the jointing stage.

RESULTS

Results showed that mechano-stimulation at the Zadoks growth stage 26 activated the antioxidant system, and substantially, maintained the homeostasis of reactive oxygen species. In turn, the stimulation improved the electron transport and photosynthetic rate of wheat plants exposed to cold stress at the jointing stage. Proteomic and transcriptional analyses revealed that the oxidative stress defense, ATP synthesis, and photosynthesis-related proteins and genes were similarly modulated by mechano-stimulation and the cold stress.

CONCLUSIONS

It was concluded that mechano-stimulated modifications of the chloroplast antioxidant system and proteome changes are related to cold tolerance in wheat. The findings might provide deeper insights into roles of reactive oxygen species in mechano-stimulated cold tolerance of photosynthetic apparatus, and be helpful to explore novel approaches to mitigate the impacts of low temperature occurring at critical developmental stages.

Agriproteomics of Bread Wheat: Comparative Proteomics and Network Analyses of Grain Size Variation

Agriproteomics signifies the merging of agriculture research and proteomics systems science and is impacting plant research and societal development. Wheat is a frequently consumed foodstuff, has highly variable grain size that in effect contributes to wheat grain yield and the end-product quality. Very limited information is available on molecular basis of grain size due to complex multifactorial nature of this trait. Here, using liquid chromatography-mass spectrometry, we investigated the proteomics profiles from grains of wheat genotypes, Rye selection 111 (RS111) and Chinese spring (CS), which differ in their size. Significant differences in protein expression were found, including 33 proteins uniquely present in RS111 and 32 only in CS, while 54 proteins were expressed from both genotypes. Among differentially expressed proteins, 22 were upregulated, while 21 proteins were downregulated in RS111 compared to CS. Functional classification revealed their role in energy metabolism, seed storage, stress tolerance and transcription. Further, protein interactive network analysis was performed to predict the targets of identified proteins. Significantly different interactions patterns were observed between these genotypes with detection of proteins such as Cyp450, Sus2, and WRKY that could potentially affect seed size. The present study illustrates the potentials of agriproteomics as a veritable new frontier of plant omics research.

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.

Proteomic profiling of the tumor microenvironment: recent insights and the search for biomarkers

Although gain of oncogene functions and loss of tumor suppressor functions are driving forces in tumor development, the tumor microenvironment, comprising the extracellular matrix, surrounding stroma, signaling molecules and infiltrating immune and other cell populations, is now also recognized as crucial to tumor development and metastasis. Many interactions at the tumor cell-environment interface occur at the protein level. Proteomic approaches are contributing to the definition of the protein constituents of the microenvironment and their sources, modifications, interactions and turnover, as well as providing information on how these features relate to tumor development and progression. Recently, proteomic studies have revealed how cancer cells modulate the microenvironment through their secreted proteins and how they can alter their protein constituents to adapt to the microenvironment. Moreover, the release of proteins from the microenvironment into the circulatory system has relevance for the development of blood-based cancer diagnostics. Here, we review how proteomic approaches are being applied to studies of the tumor microenvironment to decipher tumor-stroma interactions and to elucidate the role of host cells in the tumor microenvironment.

Promise of personalized omics to precision medicine

The rapid development of high-throughput technologies and computational frameworks enables the examination of biological systems in unprecedented detail. The ability to study biological phenomena at omics levels in turn is expected to lead to significant advances in personalized and precision medicine. Patients can be treated according to their own molecular characteristics. Individual omes as well as the integrated profiles of multiple omes, such as the genome, the epigenome, the transcriptome, the proteome, the metabolome, the antibodyome, and other omics information are expected to be valuable for health monitoring, preventative measures, and precision medicine. Moreover, omics technologies have the potential to transform medicine from traditional symptom-oriented diagnosis and treatment of diseases toward disease prevention and early diagnostics. We discuss here the advances and challenges in systems biology-powered personalized medicine at its current stage, as well as a prospective view of future personalized health care at the end of this review.