Proteome informatics for cancer research: from molecules to clinic

Platelet and Haemostasis are the Main Targets in Severe Cases of COVID-19 Infection; a System Biology Study

Introduction:

Many proteomics-based and bioinformatics-based efforts are made to detect the molecular mechanism of COVID-19 infection. Identification of the main protein targets and pathways of severe cases of COVID-19 infection is the aim of this study.

Methods:

Published differentially expressed proteins were screened and the significant proteins were investigated via protein-protein interaction network using Cytoscape software V. 3.7.2 and STRING database. The studied proteins were assessed via action map analysis to determine the relationship between individual proteins using CluePedia. The related biological terms were investigated using ClueGO and the terms were clustered and discussed.

Results:

Among the 35 queried proteins, six of them (FGA, FGB, FGG, and FGl1 plus TLN1 and THBS1) were identified as critical proteins. A total of 38 biological terms, clustered in 4 groups, were introduced as the affected terms. “Platelet degranulation” and “hereditary factor I deficiency disease” were introduced as the main class of the terms disturbed by COVID-19 virus.

Conclusion:

It can be concluded that platelet damage and disturbed haemostasis could be the main targets in severe cases of coronavirus infection. It is vital to follow patients’ condition by examining the introduced critical differentially expressed proteins (DEPs).

Molecular and biological functions of gingerol as a natural effective therapeutic drug for cervical cancer

Cervical cancer is one of the most common and important gynecological cancers, which has a global concern with an increasing number of patients and mortality rates. Today, most women in the world who suffer from cervical cancer are developing advanced stages of the disease. Smoking and even exposure to secondhand smoke, infections caused by the human papillomavirus, immune system dysfunction and high-risk individual-social behaviors are among the most important predisposing factors for this type of cancer. In addition, papilloma virus infection plays a more prominent role in cervical cancer. Surgery, chemotherapy or radical hysterectomy, and radiotherapy are effective treatments for this condition, the side effects of these methods endanger a person's quality of life and cause other problems in other parts of the body. Studies show that herbal medicines, including taxol, camptothecin and combretastatins, have been shown to be effective in treating cervical cancer. Ginger (Zingiber officinale, Zingiberaceae) is one of the plants with valuable compounds such as gingerols, paradols and shogoals, which is a rich source of antioxidants, anti-cancer and anti-inflammatory agents. Numerous studies have reported the therapeutic effects of this plant through various pathways in cervical cancer. In this article, we look at the signaling mechanisms and pathways in which ginger is used to treat cervical cancer.

FADD phosphorylation impaired islet morphology and function

Previous studies have indicated that Fas-FasL pathway and its downstream caspase-8 can regulate islet mass and insulin secretion. As a classical adaptor in Fas-FasL signaling, Fas-associated death domain-containing protein (FADD) takes part in many non-apoptosis processes regulated by its phosphorylation. However, its role in islets has not been evaluated to date. Here, through comparative proteomics and bioinformatic analysis on FADD phosphorylated (FADD-D) and wild-type (WT) MEFs, we found three proteins involved in islet differentiation and function were dysregulated due to FADD phosphorylation. The mouse model of FADD-D, which mimics constitutive phosphorylated FADD expression in mice, was further analyzed to address this issue. We confirmed the proteomic results by immunohistological analyses on pancreatic islets. In addition, we found that FADD-D mice displayed decreased islet area, and the glucose stimulated insulin secretion (GSIS) of FADD-D islets was impaired. These data suggest a novel role of FADD in islet development and insulin secretion.

Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

Background

The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic. Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature of transcriptional and translation regulatory mechanisms and the disparities between genomic and proteomic data from the same samples. In this study, we have examined tumor antigens as potential biomarkers for breast cancer using genomics and proteomics data from previously reported laser capture microdissected ER+ tumor samples.

Results

We applied proteogenomic analyses to study the genetic aberrations of 32 tumor antigens determined in the proteomic data. We found that tumor antigens that are aberrantly expressed at the genetic level and expressed at the protein level, are likely involved in perturbing pathways directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found to be perturbed.

Conclusion

Tumor antigens are a group of proteins recognized by the cells of the immune system. Specifically, they are recognized in tumor cells where they are present in larger than usual amounts, or are physiochemically altered to a degree at which they no longer resemble native human proteins. This proteogenomic analysis of 32 tumor antigens suggests that tumor antigens have the potential to be highly specific biomarkers for different cancers.

Role of Fas-associated death domain-containing protein (FADD) phosphorylation in regulating glucose homeostasis: from proteomic discovery to physiological validation

Fas-associated death domain-containing protein (FADD), a classical apoptotic signaling adaptor, participates in different nonapoptotic processes regulated by its phosphorylation. However, the influence of FADD on metabolism, especially glucose homeostasis, has not been evaluated to date. Here, using both two-dimensional electrophoresis and liquid chromatography linked to tandem mass spectrometry (LC/MS/MS), we found that glycogen synthesis, glycolysis, and gluconeogenesis were dysregulated because of FADD phosphorylation, both in MEFs and liver tissue of the mice bearing phosphorylation-mimicking mutation form of FADD (FADD-D). Further physiological studies showed that FADD-D mice exhibited lower blood glucose, enhanced glucose tolerance, and increased liver glycogen content without alterations in insulin sensitivity. Moreover, investigations on the molecular mechanisms revealed that, under basal conditions, FADD-D mice had elevated phosphorylation of Akt with alterations in its downstream signaling, leading to increased glycogen synthesis and decreased gluconeogenesis. Thus, we uncover a novel role of FADD in the regulation of glucose homeostasis by proteomic discovery and physiological validation.

The Cytotoxicity Mechanism of 6-Shogaol-Treated HeLa Human Cervical Cancer Cells Revealed by Label-Free Shotgun Proteomics and Bioinformatics Analysis

Cervical cancer is one of the most common cancers among women in the world. 6-Shogaol is a natural compound isolated from the rhizome of ginger (Zingiber officinale). In this paper, we demonstrated that 6-shogaol induced apoptosis and G2/M phase arrest in human cervical cancer HeLa cells. Endoplasmic reticulum stress and mitochondrial pathway were involved in 6-shogaol-mediated apoptosis. Proteomic analysis based on label-free strategy by liquid chromatography chip quadrupole time-of-flight mass spectrometry was subsequently proposed to identify, in a non-target-biased manner, the molecular changes in cellular proteins in response to 6-shogaol treatment. A total of 287 proteins were differentially expressed in response to 24 h treatment with 15 μM 6-shogaol in HeLa cells. Significantly changed proteins were subjected to functional pathway analysis by multiple analyzing software. Ingenuity pathway analysis (IPA) suggested that 14-3-3 signaling is a predominant canonical pathway involved in networks which may be significantly associated with the process of apoptosis and G2/M cell cycle arrest induced by 6-shogaol. In conclusion, this work developed an unbiased protein analysis strategy by shotgun proteomics and bioinformatics analysis. Data observed provide a comprehensive analysis of the 6-shogaol-treated HeLa cell proteome and reveal protein alterations that are associated with its anticancer mechanism.

Data processing and analysis for protein microarrays

Protein microarrays are a high-throughput technology capable of generating large quantities of proteomics data. They can be used for general research or for clinical diagnostics. Bioinformatics and statistical analysis techniques are required for interpretation and reaching biologically relevant conclusions from raw data. We describe essential algorithms for processing protein microarray data, including spot-finding on slide images, Z score, and significance analysis of microarrays (SAM) calculations, as well as the concentration dependent analysis (CDA). We also describe available tools for protein microarray analysis, and provide a template for a step-by-step approach to performing an analysis centered on the CDA method. We conclude with a discussion of fundamental and practical issues and considerations.

Serologic markers of effective tumor immunity against chronic lymphocytic leukemia include nonmutated B-cell antigens

Patients with chronic lymphocytic leukemia (CLL) who relapse after allogeneic transplant may achieve durable remission following donor lymphocyte infusion (DLI), showing the potency of donor-derived immunity in eradicating tumors. We sought to elucidate the antigenic basis of the effective graft-versus-leukemia (GvL) responses associated with DLI for the treatment of CLL by analyzing the specificity of plasma antibody responses developing in two DLI-treated patients who achieved long-term remission without graft-versus-host disease. By probing high-density protein microarrays with patient plasma, we discovered 35 predominantly intracellular antigens that elicited high-titer antibody reactivity greater in post-DLI than in pre-DLI plasma. Three antigens-C6orf130, MDS032, and ZFYVE19-were identified by both patients. Along with additional candidate antigens DAPK3, SERBP1, and OGFOD1, these proteins showed higher transcript and protein expression in B cells and CLL cells compared with normal peripheral blood mononuclear cells. DAPK3 and the shared antigens do not represent minor histocompatibility antigens, as their sequences are identical in both donor and tumor. Although ZFYVE19, DAPK3, and OGFOD1 elicited minimal antibody reactivity in 12 normal subjects and 12 chemotherapy-treated CLL patients, 5 of 12 CLL patients with clinical GvL responses were serologically reactive to these antigens. Moreover, antibody reactivity against these antigens was temporally correlated with clinical disease regression. These B-cell antigens represent promising biomarkers of effective anti-CLL immunity.

Differential protein expression analysis using stable isotope labeling and PQD linear ion trap MS technology

An isotope tags for relative and absolute quantitation (iTRAQ)-based reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS) method was developed for differential protein expression profiling in complex cellular extracts. The estrogen positive MCF-7 cell line, cultured in the presence of 17beta-estradiol (E2) and tamoxifen (Tam), was used as a model system. MS analysis was performed with a linear trap quadrupole (LTQ) instrument operated by using pulsed Q dissociation (PQD) detection. Optimization experiments were conducted to maximize the iTRAQ labeling efficiency and the number of quantified proteins. MS data filtering criteria were chosen to result in a false positive identification rate of <4%. The reproducibility of protein identifications was approximately 60%-67% between duplicate, and approximately 50% among triplicate LC-MS/MS runs, respectively. The run-to-run reproducibility, in terms of relative standard deviations (RSD) of global mean iTRAQ ratios, was better than 10%. The quantitation accuracy improved with the number of peptides used for protein identification. From a total of 530 identified proteins (P < 0.001) in the E2/Tam treated MCF-7 cells, a list of 255 proteins (quantified by at least two peptides) was generated for differential expression analysis. A method was developed for the selection, normalization, and statistical evaluation of such datasets. An approximate approximately 2-fold change in protein expression levels was necessary for a protein to be selected as a biomarker candidate. According to this data processing strategy, approximately 16 proteins involved in biological processes such as apoptosis, RNA processing/metabolism, DNA replication/transcription/repair, cell proliferation and metastasis, were found to be up- or down-regulated.

ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization

Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines. ImmunoGrid modules share common conceptual models and ontologies. The ImmunoGrid portal offers access to educational simulators where previously defined cases can be displayed, and to research simulators that allow the development of new, or tuning of existing, computational models. The portal is accessible at <igrid-ext.cryst.bbk.ac.uk/immunogrid>.

Human papillomavirus in cervical cancer screening: important role as biomarker

Cervical cytology screening has reduced cervical cancer morbidity and mortality but shows important shortcomings in terms of sensitivity and specificity. Infection with distinct types of human papillomavirus (HPV) is the primary etiologic factor in cervical carcinogenesis. This causal relationship has been exploited for the development of molecular technologies for viral detection to overcome limitations linked to cytologic cervical screening. HPV testing has been suggested for primary screening, triage of equivocal Pap smears or low-grade lesions and follow-up after treatment for cervical intraepithelial neoplasia. Determination of HPV genotype, viral load, integration status and RNA expression could further improve the effectiveness of HPV-based screening and triage strategies. The prospect of prophylactic HPV vaccination stresses the importance of modification of the current cytology-based screening approach.

A concentration-dependent analysis method for high density protein microarrays

Protein microarray technology is rapidly growing and has the potential to accelerate the discovery of targets of serum antibody responses in cancer, autoimmunity and infectious disease. Analytical tools for interpreting this high-throughput array data, however, are not well-established. We developed a concentration-dependent analysis (CDA) method which normalizes protein microarray data based on the concentration of spotted probes. We show that this analysis samples a data space that is complementary to other commonly employed analyses, and demonstrate experimental validation of 92% of hits identified by the intersection of CDA with other tools. These data support the use of CDA either as a preprocessing step for a more complete proteomic microarray data analysis or as a stand-alone analysis method.

Comparative study on transduction and toxicity of protein transduction domains

BACKGROUND AND PURPOSE

Protein transduction domains (PTDs), such as Tat, antennapedia homeoprotein (Antp), Rev and VP22, have been extensively utilized for intracellular delivery of biologically active macromolecules in vitro and in vivo. There is little known, however, about the relative transduction efficacy, cytotoxicity and internalization mechanism of individual PTDs.

EXPERIMENTAL APPROACH

We examined the cargo delivery efficacies of four major PTDs (Tat, Antp, Rev and VP22) and evaluated their toxicities and cell internalizing pathways in various cell lines.

KEY RESULTS

The relative order of the transduction efficacy of these PTDs conjugated to fluorescein was Rev>Antp>Tat>VP22, independent of cell type (HeLa, HaCaT, A431, Jurkat, MOLT-4 and HL60 cells). Antp produced significant toxicity in HeLa and Jurkat cells, and Rev produced significant toxicity in Jurkat cells. Flow cytometric analysis demonstrated that the uptake of PTD-fluorescein conjugate was dose-dependently inhibited by methyl-beta-cyclodextrin, cytochalasin D and amiloride, indicating that all four PTDs were internalized by the macropinocytotic pathway. Accordingly, in cells co-treated with 'Tat-fused' endosome-disruptive HA2 peptides (HA2-Tat) and independent PTD-fluorescent protein conjugates, fluorescence spread throughout the cytosol, indicating that all four PTDs were internalized into the same vesicles as Tat.

CONCLUSIONS AND IMPLICATIONS

These findings suggest that macropinocytosis-dependent internalization is a crucial step in PTD-mediated molecular transduction. From the viewpoint of developing effective and safe protein transduction technology, although Tat was the most versatile carrier among the peptides studied, PTDs should be selected based on their individual characteristics.

Biochemical informatics methods for diagnosis and disease management

New technological advances are beginning to have a direct impact on many aspects of healthcare, including screening, diagnosis, treatment, and disease management. A multidisciplinary approach permits the development of sophisticated patient-centered models that rely on bioinformatics, molecular biology, analytical and biochemistry, and healthcare informatics. In the work described here, a decision support model based on neural networks is used to combine results from laboratory tests with clinical parameters to produce a prognostic model for metastatic carcinoma. In addition, techniques for drug design and development are presented that can lead to medications that target specific cancer cells.