Lipid peroxidation: Reactive carbonyl species, protein/DNA adducts, and signaling switches in oxidative stress and cancer.

Under the exposure of lipids to reactive oxygen species (ROS), lipid peroxidation proceeds non-enzymatically and generates an extremely heterogeneous mixture of reactive carbonyl species (RCS). Among them, HNE, HHE, MDA, methylglyoxal, glyoxal, and acrolein are the most studied and/or abundant ones. Over the last decades, significant progress has been achieved in understanding mechanisms of RCS generation, protein/DNA adduct formation, and their identification and quantification in biological samples. In our review, we critically discuss the advancements in understanding the roles of RCS-induced protein/DNA modifications in signaling switches to provide adaptive cell response under physiological and oxidative stress conditions. At non-toxic concentrations, RCS modify susceptible Cys residue in c-Src to activate MAPK signaling and Cys, Lys, and His residues in PTEN to cause its reversible inactivation, thereby stimulating PI3K/PKB(Akt) pathway. RCS toxic concentrations cause irreversible Cys modifications in Keap1 and IKKß followed by stabilization of Nrf2 and activation of NF-κB, respectively, for their nuclear translocation and antioxidant gene expression. Dysregulation of these mechanisms causes diseases including cancer. Alterations in RCS, RCS detoxifying enzymes, RCS-modified protein/DNA adducts, and signaling pathways have been implicated in various cancer types.

Differentially expressed non-coding RNAs and their regulatory networks in liver cancer.

The vast majority of human transcriptome is represented by various types of small RNAs with little or no protein-coding capability referred to as non-coding RNAs (ncRNAs). Functional ncRNAs include microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), which are expressed at very low, but stable and reproducible levels in a variety of cell types. ncRNAs regulate gene expression due to miRNA capability of complementary base pairing with mRNAs, whereas lncRNAs and circRNAs can sponge miRNAs off their target mRNAs to act as competitive endogenous RNAs (ceRNAs). Each miRNA can target multiple mRNAs and a single mRNA can interact with several miRNAs, thereby creating miRNA-mRNA, lncRNA-miRNA-mRNA, and circRNA-miRNA-mRNA regulatory networks. Over the past few years, a variety of differentially expressed miRNAs, lncRNAs, and circRNAs (DEMs, DELs, and DECs, respectively) have been linked to cancer pathogenesis. They can exert both oncogenic and tumor suppressor roles. In this review, we discuss the recent advancements in uncovering the roles of DEMs, DELs, and DECs and their networks in aberrant cell signaling, cell cycle, transcription, angiogenesis, and apoptosis, as well as tumor microenvironment remodeling and metabolic reprogramming during hepatocarcinogenesis. We highlight the potential and challenges in the use of differentially expressed ncRNAs as biomarkers for liver cancer diagnosis and prognosis.

Short Linear Motifs Orchestrate Functioning of Human Proteins during Embryonic Development, Redox Regulation, and Cancer.

Short linear motifs (SLiMs) are evolutionarily conserved functional modules of proteins that represent amino acid stretches composed of 3 to 10 residues. The biological activities of two short peptide segments of human alpha-fetoprotein (AFP), a major embryo-specific and cancer-related protein, have been confirmed experimentally. This is a heptapeptide segment LDSYQCT in domain I designated as AFP14-20 and a nonapeptide segment EMTPVNPGV in domain III designated as GIP-9. In our work, we searched the UniprotKB database for human proteins that contain SLiMs with sequence similarity to the both segments of human AFP and undertook gene ontology (GO)-based functional categorization of retrieved proteins. Gene set enrichment analysis included GO terms for biological process, molecular function, metabolic pathway, KEGG pathway, and protein-protein interaction (PPI) categories. We identified the SLiMs of interest in a variety of non-homologous proteins involved in multiple cellular processes underlying embryonic development, cancer progression, and, unexpectedly, the regulation of redox homeostasis. These included transcription factors, cell adhesion proteins, ubiquitin-activating and conjugating enzymes, cell signaling proteins, and oxidoreductase enzymes. They function by regulating cell proliferation and differentiation, cell cycle, DNA replication/repair/recombination, metabolism, immune/inflammatory response, and apoptosis. In addition to the retrieved genes, new interacting genes were identified. Our data support the hypothesis that conserved SLiMs are incorporated into non-homologous proteins to serve as functional blocks for their orchestrated functioning.

Evolutionary Conserved Short Linear Motifs Provide Insights into the Cellular Response to Stress.

Short linear motifs (SLiMs) are evolutionarily conserved functional modules of proteins composed of 3 to 10 residues and involved in multiple cellular functions. Here, we performed a search for SLiMs that exert sequence similarity to two segments of alpha-fetoprotein (AFP), a major mammalian embryonic and cancer-associated protein. Biological activities of the peptides, LDSYQCT (AFP14-20) and EMTPVNPGV (GIP-9), have been previously confirmed under in vitro and in vivo conditions. In our study, we retrieved a vast array of proteins that contain SLiMs of interest from both prokaryotic and eukaryotic species, including viruses, bacteria, archaea, invertebrates, and vertebrates. Comprehensive Gene Ontology enrichment analysis showed that proteins from multiple functional classes, including enzymes, transcription factors, as well as those involved in signaling, cell cycle, and quality control, and ribosomal proteins were implicated in cellular adaptation to environmental stress conditions. These include response to oxidative and metabolic stress, hypoxia, DNA and RNA damage, protein degradation, as well as antimicrobial, antiviral, and immune response. Thus, our data enabled insights into the common functions of SLiMs evolutionary conserved across all taxonomic categories. These SLiMs can serve as important players in cellular adaptation to stress, which is crucial for cell functioning.

Predictive biomarkers for systemic therapy of hepatocellular carcinoma.

Introduction: Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the third cancer-related cause of death worldwide. In recent years, several systemic therapy drugs including sorafenib, lenvatinib, regorafenib, cabozantinib, ramucicurab, nivilumab, and pembrolizumab have been approved by FDA for advanced HCC. However, their insufficient efficacy, toxicity, and drug resistance require clinically applicable and validated predictive biomarkers.Areas covered: Our review covers the recent advancements in the identification of proteomic/genomic/epigenomic/transcriptomic biomarkers for predicting HCC treatment efficacy with the use of multi-kinase inhibitors (MKIs), CDK4/6 inhibitors, and immune checkpoint inhibitors (ICIs). Alpha-fetoprotein, des-carboxyprothrombin, vascular endothelial growth factor, angiopoietin-2, and dysregulated MTOR, VEGFR2, c-KIT, RAF1, PDGFRß have the potential of proteomic/genomic biomarkers for sorafenib treatment. Alanine aminotransferase, aspartate aminotransferase, and albumin-bilirubin grade can predict the efficacy of other MKIs. Rb, p16, and Ki-67, and genes involved in cell cycle regulation, CDK1-4, CCND1, CDKN1A, and CDKN2A have been proposed for CD4/6 inhibitors, while dysregulated TERT, CTNNB1, TP53 FGF19, and TP53 are found to be predictors for ICI efficacy.Expert opinion: There are still limited clinically applicable and validated predictive biomarkers to identify HCC patients who benefit from systemic therapy. Further prospective biomarker validation studies for HCC personalized systemic therapy are required.

Genomic Landscape of Liquid Biopsy for Hepatocellular Carcinoma Personalized Medicine.

Hepatocellular carcinoma (HCC) is the sixth most frequently diagnosed cancer and the third leading cause of cancer-related deaths worldwide. Advanced-stage HCC patients have poor survival rates and this requires the discovery of novel clear biomarkers for HCC early diagnosis and prognosis, identifying risk factors, distinguishing HCC from non-HCC liver diseases, and assessment of treatment response. Liquid biopsy has emerged as a novel minimally invasive approach to enable monitoring tumor progression, metastasis, and recurrence. Since the liquid biopsy analysis has relatively high specificity and low sensitivity in cancer early detection, there is a risk of bias. Next-generation sequencing (NGS) technologies provide accurate and comprehensive gene expression and mutational profiling of liquid biopsies including cell-free circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and genomic components of extracellular vesicles (EVs) including micro-RNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs). Since HCC is a highly heterogeneous cancer, HCC patients can display various genomic, epigenomic, and transcriptomic patterns and exhibit varying sensitivity to treatment options. Identification of individual variabilities in genomic signatures in liquid biopsy has the potential to greatly enhance precision oncology capabilities. In this review, we highlight and critically discuss the latest progress in characterizing the genomic landscape of liquid biopsy, which can advance HCC personalized medicine.

Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine.

Hepatocellular carcinoma (HCC) is the most common primary cancer of the liver with high morbidity and mortality rates worldwide. Since 1963, when alpha-fetoprotein (AFP) was discovered as a first HCC serum biomarker, several other protein biomarkers have been identified and introduced into clinical practice. However, insufficient specificity and sensitivity of these biomarkers dictate the necessity of novel biomarker discovery. Remarkable advancements in integrated multiomics technologies for the identification of gene expression and protein or metabolite distribution patterns can facilitate rising to this challenge. Current multiomics technologies lead to the accumulation of a huge amount of data, which requires clustering and finding correlations between various datasets and developing predictive models for data filtering, pre-processing, and reducing dimensionality. Artificial intelligence (AI) technologies have an enormous potential to overcome accelerated data growth, complexity, and heterogeneity within and across data sources. Our review focuses on the recent progress in integrative proteomic profiling strategies and their usage in combination with machine learning and deep learning technologies for the discovery of novel biomarker candidates for HCC early diagnosis and prognosis. We discuss conventional and promising proteomic biomarkers of HCC such as AFP, lens culinaris agglutinin (LCA)-reactive L3 glycoform of AFP (AFP-L3), des-gamma-carboxyprothrombin (DCP), osteopontin (OPN), glypican-3 (GPC3), dickkopf-1 (DKK1), midkine (MDK), and squamous cell carcinoma antigen (SCCA) and highlight their functional significance including the involvement in cell signaling such as Wnt/ß-catenin, PI3K/Akt, integrin αvß3/NF-κB/HIF-1α, JAK/STAT3 and MAPK/ERK-mediated pathways dysregulated in HCC. We show that currently available computational platforms for big data analysis and AI technologies can both enhance proteomic profiling and improve imaging techniques to enhance the translational application of proteomics data into precision medicine.

Metabolic Heterogeneity of Cancer Cells: An Interplay between HIF-1, GLUTs, and AMPK.

It has been long recognized that cancer cells reprogram their metabolism under hypoxia conditions due to a shift from oxidative phosphorylation (OXPHOS) to glycolysis in order to meet elevated requirements in energy and nutrients for proliferation, migration, and survival. However, data accumulated over recent years has increasingly provided evidence that cancer cells can revert from glycolysis to OXPHOS and maintain both reprogrammed and oxidative metabolism, even in the same tumor. This phenomenon, denoted as cancer cell metabolic plasticity or hybrid metabolism, depends on a tumor micro-environment that is highly heterogeneous and influenced by an intensity of vasculature and blood flow, oxygen concentration, and nutrient and energy supply, and requires regulatory interplay between multiple oncogenes, transcription factors, growth factors, and reactive oxygen species (ROS), among others. Hypoxia-inducible factor-1 (HIF-1) and AMP-activated protein kinase (AMPK) represent key modulators of a switch between reprogrammed and oxidative metabolism. The present review focuses on cross-talks between HIF-1, glucose transporters (GLUTs), and AMPK with other regulatory proteins including oncogenes such as c-Myc, p53, and KRAS; growth factor-initiated protein kinase B (PKB)/Akt, phosphatydyl-3-kinase (PI3K), and mTOR signaling pathways; and tumor suppressors such as liver kinase B1 (LKB1) and TSC1 in controlling cancer cell metabolism. The multiple switches between metabolic pathways can underlie chemo-resistance to conventional anti-cancer therapy and should be taken into account in choosing molecular targets to discover novel anti-cancer drugs.

Elucidating Binding Sites and Affinities of ERα Agonists and Antagonists to Human Alpha-Fetoprotein by In Silico Modeling and Point Mutagenesis.

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting a variety of hydrophobic ligands, including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth, which can be attributed to its estrogen-binding ability. Despite AFP having long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP-ligand interaction remains obscure. In our study, we constructed a homology-based 3D model of human AFP (HAFP) with the purpose of molecular docking of ERα ligands, three agonists (17ß-estradiol, estrone and diethylstilbestrol), and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on the ligand-docked scoring functions, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity binding sites were located (i) in a tunnel formed within HAFP subdomains IB and IIA and (ii) on the opposite side of the molecule in a groove originating from a cavity formed between domains I and III, while (iii) the third low-affinity binding site was found at the bottom of the cavity. Here, 100 ns molecular dynamics (MD) simulation allowed us to study their geometries and showed that HAFP-estrogen interactions were caused by van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP-antiestrogen binding. Molecular mechanics/Generalized Born surface area (MM/GBSA) rescoring method exploited for estimation of binding free energies (ΔGbind) showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP-ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues, along with two disulfide bonds (Cys224-Cys270 and Cys269-Cys277), have key roles in both HAFP-estrogen and HAFP-antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein-ligand interactions and anticancer therapy strategies based on ERα-binding ligands.

Oxidative Stress and Advanced Lipoxidation and Glycation End Products (ALEs and AGEs) in Aging and Age-Related Diseases.

Oxidative stress is a consequence of the use of oxygen in aerobic respiration by living organisms and is denoted as a persistent condition of an imbalance between the generation of reactive oxygen species (ROS) and the ability of the endogenous antioxidant system (AOS) to detoxify them. The oxidative stress theory has been confirmed in many animal studies, which demonstrated that the maintenance of cellular homeostasis and biomolecular stability and integrity is crucial for cellular longevity and successful aging. Mitochondrial dysfunction, impaired protein homeostasis (proteostasis) network, alteration in the activities of transcription factors such as Nrf2 and NF-κB, and disturbances in the protein quality control machinery that includes molecular chaperones, ubiquitin-proteasome system (UPS), and autophagy/lysosome pathway have been observed during aging and age-related chronic diseases. The accumulation of ROS under oxidative stress conditions results in the induction of lipid peroxidation and glycoxidation reactions, which leads to the elevated endogenous production of reactive aldehydes and their derivatives such as glyoxal, methylglyoxal (MG), malonic dialdehyde (MDA), and 4-hydroxy-2-nonenal (HNE) giving rise to advanced lipoxidation and glycation end products (ALEs and AGEs, respectively). Both ALEs and AGEs play key roles in cellular response to oxidative stress stimuli through the regulation of a variety of cell signaling pathways. However, elevated ALE and AGE production leads to protein cross-linking and aggregation resulting in an alteration in cell signaling and functioning which causes cell damage and death. This is implicated in aging and various age-related chronic pathologies such as inflammation, neurodegenerative diseases, atherosclerosis, and vascular complications of diabetes mellitus. In the present review, we discuss experimental data evidencing the impairment in cellular functions caused by AGE/ALE accumulation under oxidative stress conditions. We focused on the implications of ALEs/AGEs in aging and age-related diseases to demonstrate that the identification of cellular dysfunctions involved in disease initiation and progression can serve as a basis for the discovery of relevant therapeutic agents.

Reactive Oxygen and Nitrogen Species-Induced Protein Modifications: Implication in Carcinogenesis and Anticancer Therapy.

Cancer is a complex disorder extremely dependent on its microenvironment and highly regulated by multiple intracellular and extracellular stimuli. Studies show that reactive oxygen and nitrogen species (RONS) play key roles in cancer initiation and progression. Accumulation of RONS caused by imbalance between RONS generation and activity of antioxidant system (AOS) has been observed in many cancer types. This leads to alterations in gene expression levels, signal transduction pathways, and protein quality control machinery, that is, processes that regulate cancer cell proliferation, migration, invasion, and apoptosis. This review focuses on the latest advancements evidencing that RONS-induced modifications of key redox-sensitive residues in regulatory proteins, that is, cysteine oxidation/S-sulfenylation/S-glutathionylation/S-nitrosylation and tyrosine nitration, represent important molecular mechanisms underlying carcinogenesis. The oxidative/nitrosative modifications cause alterations in activities of intracellular effectors of MAPK- and PI3K/Akt-mediated signaling pathways, transcription factors (Nrf2, AP-1, NFκB, STAT3, and p53), components of ubiquitin/proteasomal and autophagy/lysosomal protein degradation systems, molecular chaperones, and cytoskeletal proteins. Redox-sensitive proteins, RONS-generating enzymes, and AOS components can serve as targets for relevant anticancer drugs. Chemotherapeutic agents exert their action via RONS generation and induction of cancer cell apoptosis, while drug resistance associates with RONS-induced cancer cell survival; this is exploited in selective anticancer therapy strategies. Cancer Res; 78(21); 6040-7. ©2018 AACR.

Human EGF-derived direct and reverse short linear motifs: conformational dynamics insight into the receptor-binding residues.

Short linear motifs (SLiMs) have been recognized to perform diverse functions in a variety of regulatory proteins through the involvement in protein-protein interactions, signal transduction, cell cycle regulation, protein secretion, etc. However, detailed molecular mechanisms underlying their functions including roles of definite amino acid residues remain obscure. In our previous studies, we demonstrated that conformational dynamics of amino acid residues in oligopeptides derived from regulatory proteins such as alpha-fetoprotein (AFP), carcino-embryonic antigen (CEA), and pregnancy specific ß1-glycoproteins (PSGs) contributes greatly to their biological activities. In the present work, we revealed the 22-member linear modules composed of direct and reverse AFP14-20-like heptapeptide motifs linked by CxxGY/FxGx consensus motif within epidermal growth factor (EGF), growth factors of EGF family and numerous regulatory proteins containing EGF-like modules. We showed, first, the existence of similarity in amino acid signatures of both direct and reverse motifs in terms of their physicochemical properties. Second, molecular dynamics (MD) simulation study demonstrated that key receptor-binding residues in human EGF in the aligned positions of the direct and reverse motifs may have similar distribution of conformational probability densities and dynamic behavior despite their distinct physicochemical properties. Third, we found that the length of a polypeptide chain (from 7 to 53 residues) has no effect, while disulfide bridging and backbone direction significantly influence the conformational distribution and dynamics of the residues. Our data may contribute to the atomic level structure-function analysis and protein structure decoding; additionally, they may provide a basis for novel protein/peptide engineering and peptide-mimetic drug design.

Pregnancy-Specific ß1-Glycoproteins: Combined Biomarker Roles, Structure/Function Relationships and Implications for Drug Design.

BACKGROUND: Pregnancy specific ß1-glycoproteins (PSGs) have long been recognized as trophoblast quality and embryo viability markers. However, biological roles of PSGs remain obscure, and structure/function relationships to other feto-placental proteins as well as implications for drug design have not been reviewed. This review summarizes and discusses advances in 45-year studies of PSGs with focus on the latest achievements and the challenges for future investigations. METHODS: Literature search was performed to review the majority of recent PSG studies with emphasis on usage of high-throughput integrated proteomic profiling technologies, systems biology and bioinformatics approaches that enhance novel biomarker and drug target discovery as well as protein structure/activity analysis. RESULTS: Clinical significance and screening performance improved when PSG measurements were combined with those of other placenta-derived proteins: hCG, hPL, PAPP-A, and proMBP. Nevertheless, analysis of protein co-expression and co-localization data and the involvement of PSGs in protein interaction networks are being introduced to discover novel, specific and high-sensitive, gestational/cancer biomarkers. Despite biological roles of PSGs are not fully understood, there are evidences of that they exhibit immunomodulatory, antiinflammatory and proangiogenic effects. Investigation of structure/function relationships showed that PSGs may function in cooperative/coordinated manner with numerous regulatory proteins including alpha-fetoprotein and transforming growth factors-ß; this is provided by the presence of conserved short linear motifs (SLiMs) such as RGD, PXXP and AFP14-20-like (YXCX) ones. CONCLUSION: PSG-derived peptides may be used as a rationale to design novel drugs that mimic SLiMs involved in protein-protein interactions to inhibit domain-motif binding and to block cell signaling, and/or exert immunomodulatory, anti-inflammatory and proangiogenic effects.

Modeling of three dimensional structure of human alpha-fetoprotein complexed with diethylstilbestrol: docking and molecular dynamics simulation study.

It has been long experimentally demonstrated that human alpha-fetoprotein (HAFP) has an ability to bind immobilized estrogens with the most efficiency for synthetic estrogen analog - diethylstilbestrol (DES). However, the question remains why the human AFP (HAFP), unlike rodent AFP, cannot bind free estrogens. Moreover, despite the fact that AFP was first discovered more than 50 years ago and is presently recognized as a "golden standard" among onco-biomarkers, its three-dimensional (3D) structure has not been experimentally solved yet. In this work using MODELLER program, we generated 3D model of HAFP on the basis of homology with human serum albumin (HSA) and Vitamin D-binding protein (VTDB) with subsequent molecular docking of DES to the model structure and molecular dynamics (MD) simulation study of the complex obtained. The model constructed has U-shaped structure in which a cavity may be distinguished. In this cavity the putative estrogen-binding site is localized. Validation by RMSD calculation and with the use of PROCHECK program showed good quality of the model and stability of extended region of four alpha-helical structures that contains putative hormone-binding residues. Data extracted from MD simulation trajectory allow proposing two types of interactions between amino acid residues of HAFP and DES molecule: (1) hydrogen bonding with involvement of residues S445, R452, and E551; (2) hydrophobic interactions with participation of L138, M448, and M548 residues. A suggestion is made that immobilization of the hormone using a long spacer provides delivery of the estrogen molecule to the binding site and, thereby, facilitates interaction between HAFP and the hormone.