Integrative proteomic and phosphoproteomic profiling of prostate cell lines

Molecular Insights into the Breast and Prostate Cancer Cells in Response to the Change of Extracellular Zinc

Zinc dyshomeostasis is manifested in breast and prostate cancer cells. This study attempted to uncover the molecular details prodded by the change of extracellular zinc by employing a panel of normal and cancerous breast and prostate cell lines coupled with the top-down proteomics with two-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry. The protein samples were generated from MCF-7 breast cancer cells, MCF10A normal breast cells, PC3 prostate cancer cells, and RWPE-1 normal prostate cells with or without exogenous zinc exposure in a time course (T0 and T120). By comparing the cancer cells vs respective normal epithelial cells without zinc treatment (T0), differentially expressed proteins (23 upregulated and 18 downregulated in MCF-7 cells; 14 upregulated and 30 downregulated in PC3 cells) were identified, which provides insights into the intrinsic differences of breast and prostate cancer cells. The dynamic protein landscapes in the cancer cells prodded by the extracellular zinc treatment reveal the potential roles of the identified zinc-responsive proteins (e.g., triosephosphate isomerase, S100A13, tumour proteins hD53 and hD54, and tumour suppressor prohibitin) in breast and prostate cancers. This study, for the first time, simultaneously investigated the two kinds of cancer cells related to zinc dyshomeostasis, and the findings shed light on the molecular understanding of the breast and prostate cancer cells in response to extracellular zinc variation.

Integrative Analysis of Transcriptome, Proteome, and Phosphoproteome Reveals Potential Roles of Photosynthesis Antenna Proteins in Response to Brassinosteroids Signaling in Maize

Brassinosteroids are a recently discovered group of substances that promote plant growth and productivity. Photosynthesis, which is vital for plant growth and high productivity, is strongly influenced by brassinosteroid signaling. However, the molecular mechanism underlying the photosynthetic response to brassinosteroid signaling in maize remains obscure. Here, we performed integrated transcriptome, proteome, and phosphoproteomic analyses to identify the key photosynthesis pathway that responds to brassinosteroid signaling. Transcriptome analysis suggested that photosynthesis antenna proteins and carotenoid biosynthesis, plant hormone signal transduction, and MAPK signaling in CK VS EBR and CK VS Brz were significantly enriched in the list of differentially expressed genes upon brassinosteroids treatment. Consistently, proteome and phosphoproteomic analyses indicated that photosynthesis antenna and photosynthesis proteins were significantly enriched in the list of differentially expressed proteins. Thus, transcriptome, proteome, and phosphoproteome analyses showed that major genes and proteins related to photosynthesis antenna proteins were upregulated by brassinosteroids treatment in a dose-dependent manner. Meanwhile, 42 and 186 transcription factor (TF) responses to brassinosteroid signals in maize leaves were identified in the CK VS EBR and CK VS Brz groups, respectively. Our study provides valuable information for a better understanding of the molecular mechanism underlying the photosynthetic response to brassinosteroid signaling in maize.

Exosome secretion and cellular response of DU145 and PC3 after exposure to alpha radiation

Exosomes are spherical membrane nanovesicles secreted from cells, and they play an important role in tumor immune response, metastasis, angiogenesis, and survival. Studies investigating exosomes isolated from cells exposed to photon radiation commonly used in conventional radiotherapy demonstrate the influence of this type of radiation on exosome characteristics and secretion. There is currently no research investigating the effects of densely ionizing particles such as protons and alpha radiation on exosomes. Thus we have evaluated the cellular response of human prostate cancer cells exposed to 0, 2, and 6 Gy of alpha radiation emitted from the Am-241 source. Irradiated PC3 and DU145 cell lines, characterized by differences in radiosensitivity, were studied using apoptosis, LDH, and IL-6 assays. Additionally, the corresponding concentration and size of isolated exosomes were measured using NTA. We found that exposure to ionizing radiation resulted in gross changes in viability and cell damage. There were increased amounts of apoptotic or necrotic cells as a function of radiation dose. We demonstrated that irradiated PC3 cells secrete higher quantities of exosomes compared to DU145 cells. Additionally, we also found no statistical difference in exosome size for control and irradiated cells.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic.

MECHANISTIC AND DATA-DRIVEN MODELS OF CELL SIGNALING: TOOLS FOR FUNDAMENTAL DISCOVERY AND RATIONAL DESIGN OF THERAPY

A full understanding of cell signaling processes requires knowledge of protein structure/function relationships, protein-protein interactions, and the abilities of pathways to control phenotypes. Computational models offer a valuable framework for integrating that knowledge to predict the effects of system perturbations and interventions in health and disease. Whereas mechanistic models are well suited for understanding the biophysical basis for signal transduction and principles of therapeutic design, data-driven models are particularly suited to distill complex signaling relationships among samples and between multivariate signaling changes and phenotypes. Both approaches have limitations and provide incomplete representations of signaling biology, but their careful implementation and integration can provide new understanding for how manipulating system variables impacts cellular decisions.

The role of proteomics in the multiplexed analysis of gene alterations in human cancer

INTRODUCTION

Proteomics has played a pivotal role in identifying proteins perturbed in disease conditions when compared with healthy samples. Study of dysregulated proteins aids in identifying diagnostic markers and potential therapeutic targets. Cancer is an outcome of interplay of several such disarrayed proteins and molecular pathways which perturb cellular homeostasis, resulting in transformation. In this review, we discuss various facets of proteomic approaches, including tools and technological advancements, aiding in understanding differentially expressed molecules and signaling mechanisms.

AREAS COVERED

In this review, we have taken the approach of documenting the different methods of proteomic studies, ranging from labeling techniques, data analysis methods, and the nature of molecule detected. We summarize each technique and provide a glimpse of cancer research carried out using them, highlighting the advantages and drawbacks in comparison with others. Literature search using online resources, such as PubMed and Google Scholar were carried out for this approach.

EXPERT OPINION

Technological advancements in proteomics studies have come a long way from the study of two-dimensional mapping of proteins separated on gels in the early 1970s. Higher precision in molecular identification and quantification (high throughput), and greater number of samples analyzed have been the focus of researchers.

Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes

Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.

A proteomic platform to identify off-target proteins associated with therapeutic modalities that induce protein degradation or gene silencing

Novel modalities such as PROTAC and RNAi have the ability to inadvertently alter the abundance of endogenous proteins. Currently available in vitro secondary pharmacology assays, which evaluate off-target binding or activity of small molecules, do not fully assess the off-target effects of PROTAC and are not applicable to RNAi. To address this gap, we developed a proteomics-based platform to comprehensively evaluate the abundance of off-target proteins. First, we selected off-target proteins using genetics and pharmacology evidence. This process yielded 2813 proteins, which we refer to as the “selected off-target proteome” (SOTP). An iterative algorithm was then used to identify four human cell lines out of 932. The 4 cell lines collectively expressed ~ 80% of the SOTP based on transcriptome data. Second, we used mass spectrometry to quantify the intracellular and extracellular proteins from the selected cell lines. Among over 10,000 quantifiable proteins identified, 1828 were part of the predefined SOTP. The SOTP was designed to be easily modified or expanded, owing to the rational selection process developed and the label free LC–MS/MS approach chosen. This versatility inherent to our platform is essential to design fit-for-purpose studies that can address the dynamic questions faced in investigative toxicology.

Phosphoproteomic strategies in cancer research: a minireview

Understanding the cellular processes is central to comprehend disease conditions and is also true for cancer research. Proteomic studies provide significant insight into cancer mechanisms and aid in the diagnosis and prognosis of the disease. Phosphoproteome is one of the most studied complements of the whole proteome given its importance in the understanding of cellular processes such as signaling and regulations. Over the last decade, several new methods have been developed for phosphoproteome analysis. A significant amount of these efforts pertains to cancer research. The current use of powerful analytical instruments in phosphoproteomic approaches has paved the way for deeper and sensitive investigations. However, these methods and techniques need further improvements to deal with challenges posed by the complexity of samples and scarcity of phosphoproteins in the whole proteome, throughput and reproducibility. This review aims to provide a comprehensive summary of the variety of steps used in phosphoproteomic methods applied in cancer research including the enrichment and fractionation strategies. This will allow researchers to evaluate and choose a better combination of steps for their phosphoproteome studies.

An overview of advances in multi-omics analysis in prostate cancer

Prostate cancer (PCa) is a deadly disease for men, and studies of all types of omics data are necessary to promote precision medicine. The maturity of sequencing technology, the improvements of computer processing power, and the progress achieved in omics analysis methods have improved research efficiency and saved research costs. The occurrence and development of PCa is due to multisystem and multilevel pathological changes. Although omics research at a single level is important, this approach often has limitations. In contrast, the combined analysis of multiple types of omics data can better analyze PCa changes as a whole, thus ensuring the validity of research results to the greatest extent. This paper introduces the applications of single omics in PCa and then summarizes research progress in the combined analysis of two or more types of omics data, so as to systematically and comprehensively analyze the necessity of combined analysis of multiple omics data in PCa.

DNA damage response signaling pathways and targets for radiotherapy sensitization in cancer

Radiotherapy is one of the most common countermeasures for treating a wide range of tumors. However, the radioresistance of cancer cells is still a major limitation for radiotherapy applications. Efforts are continuously ongoing to explore sensitizing targets and develop radiosensitizers for improving the outcomes of radiotherapy. DNA double-strand breaks are the most lethal lesions induced by ionizing radiation and can trigger a series of cellular DNA damage responses (DDRs), including those helping cells recover from radiation injuries, such as the activation of DNA damage sensing and early transduction pathways, cell cycle arrest, and DNA repair. Obviously, these protective DDRs confer tumor radioresistance. Targeting DDR signaling pathways has become an attractive strategy for overcoming tumor radioresistance, and some important advances and breakthroughs have already been achieved in recent years. On the basis of comprehensively reviewing the DDR signal pathways, we provide an update on the novel and promising druggable targets emerging from DDR pathways that can be exploited for radiosensitization. We further discuss recent advances identified from preclinical studies, current clinical trials, and clinical application of chemical inhibitors targeting key DDR proteins, including DNA-PKcs (DNA-dependent protein kinase, catalytic subunit), ATM/ATR (ataxia–telangiectasia mutated and Rad3-related), the MRN (MRE11-RAD50-NBS1) complex, the PARP (poly[ADP-ribose] polymerase) family, MDC1, Wee1, LIG4 (ligase IV), CDK1, BRCA1 (BRCA1 C terminal), CHK1, and HIF-1 (hypoxia-inducible factor-1). Challenges for ionizing radiation-induced signal transduction and targeted therapy are also discussed based on recent achievements in the biological field of radiotherapy.