text:
Perspectives on immunotherapy via oncolytic viruses

Background With few exceptions, current chemotherapy and radiotherapy protocols only obtain a slightly prolonged survival with severe adverse effects in patients with advanced solid tumors. In particular, most solid malignancies not amenable to radical surgery still carry a dismal prognosis, which unfortunately is also the case for relapsing disease after surgery. Even though targeted therapies obtained good results, clinical experience showed that tumors eventually develop resistance. On the other hand, earlier attempts of cancer immunotherapy failed to show consistent efficacy. More recently, a deeper knowledge of immunosuppression in the tumor microenvironment (TME) allowed the development of effective drugs: in particular, monoclonal antibodies targeting the so-called immune checkpoint molecules yielded striking and lasting effects in some tumors. Unfortunately, these monoclonal antibodies are not effective in a majority of patients and are ineffective in several solid malignancies. Furthermore, due to their mechanism of action, checkpoint inhibitors often elicit autoimmune-like disease. Main body The use of viruses as oncolytic agents (OVs) was considered in the past, while only recently OVs revealed a connection with immunotherapy. However, their antitumoral potential has remained largely unexplored, due to safety concerns and some limitations in the techniques to manipulate viruses. OV research was recently revived by a better knowledge of viral/cancer biology and advances in the methodologies to delete virulence/immune-escape related genes from even complex viral genomes or “to arm” OVs with appropriate transgenes. Recently, the first oncolytic virus, the HSV-1 based Talimogene Laherparepvec (T-VEC), was approved for the treatment of non-resectable melanoma in USA and Europe. Conclusion OVs have the potential to become powerful agents of cancer immune and gene therapy. Indeed, in addition to their selective killing activity, they can act as versatile gene expression platforms for the delivery of therapeutic genes. This is particularly true for viruses with a large DNA genome, that can be manipulated to address the multiple immunosuppressive features of the TME. This review will focus on the open issues, on the most promising lines of research in the OV field and, more in general, on how OVs could be improved to achieve real clinical breakthroughs in cancers that are usually difficult to treat by immunotherapy.

prognosis remains dismal [6,7]. Great expectations were associated with targeted therapies, such as small molecule tyrosine kinase inhibitors (TKIs) or monoclonal antibodies directed against receptors overexpressed by cancer cells. Even though these approaches obtained good results in selected patients, in terms of prolonged survival, with a good toxicity profile, it soon became evident that tumors usually develop resistance [8,9].
Another possible therapeutic strategy is immunotherapy. Although it has been known for quite a long time that the immune system can recognize and kill cancer cells, previous attempts of immunotherapy based on the administration of recombinant cytokines, anti-cancer vaccines or in vitro expanded tumor infiltrating lymphocytes (TILs) did not provide enough efficacy [10,11]. Still, there were some remarkable exceptions, as a small subset of metastatic melanoma and of clear cell renal carcinoma patients showed long-term remissions after treatment with high doses of recombinant interleukin 2 (rIL-2) [12]. In recent years, new light was shed on mechanisms involved in cancer immunology, and, especially, on the immunosuppressive features of the tumor microenvironment (TME), which mediate escape from tumoricidal immune responses. In particular, cancer has the ability to exploit mechanisms involved in the maintenance of immune peripheral tolerance, either i) directly, by expressing immune checkpoint molecule ligands which dampen the activity of cytotoxic T cells, such as Programmed Death Ligand-1 (PDL-1), or ii) indirectly, by recruiting immune cells with immunosuppressive features, such as CD4+ CD25+ Foxp3+ T regulatory cells (Tregs), immature myeloid-derived suppressor cells (MDSCs), or M2 macrophages [13,14]. These cells usually express checkpoint molecule ligands and secrete soluble cytokines (e.g. IL-10) or enzymes (arginase and IDO) that hinder cytotoxic T responses. These and other actors, like cancer associated fibroblasts and downregulation of MHC class I molecules by cancer cells, are probably playing a role in TME immunosuppression. Based on these considerations, new cancer immunotherapies were developed, based on checkpoint inhibition by means of monoclonal antibodies directed against Cytotoxic T Lymphocyte Antigen 4 (CTLA-4), Programmed Death-1 (PD-1), or its ligands PDL-1 and PDL-2 [15]. Anti-CTLA-4 humanized antibodies, as ipilimumab, were the first to show therapeutic efficacy against melanoma [16]. On the other hand, anti-PD1 and anti-PDL1 mAbs seem to have a broader spectrum of action (including NSCLC and possibly small subsets of pancreatic and breast cancer), while triggering less autoimmune toxicity [17]. However, also in cancer types considered susceptible to checkpoint inhibitors, more than 50% of patients fail to respond to treatment. In this context, the combination of different checkpoint inhibitors (anti-CTLA-4 and anti-PD1 Abs) yielded better results in melanoma patients, but with increased toxicity [18].
Oncolytic viruses (OVs) are defined as viruses able to selectively replicate in and kill cancer cells [19]. The history of OVs is quite long, since already at the beginning of the twentieth century physicians observed that cancer patients experienced partial disease remissions after natural infections [20]. It was, therefore, hypothesized that cancer cells were somehow more vulnerable to viral infections, and that attenuated viral strains could be used in cancer therapy. However, many factors, including safety concerns, the development of cytotoxic chemotherapy, and the lack of tools to manipulate viruses, hindered research in this field. In recent years OV studies were revived by better knowledge of viral gene function and advancements in molecular biology, which allow precise modifications of viral genomes to maximize both efficacy and safety. Over the last years a new paradigm emerged according to which OVs might also function as a form of immunotherapy [21]. Indeed, it has been shown that the proinflammatory stimuli provided by viruses can overcome the TME immunosuppression and, thereby, elicit a systemic antitumoral immune response. Such a response was observed also when OVs were injected locally (intratumoral injection), rather than systemically [22]. It was demonstrated that the first OV approved for cancer treatment in North America and Europe, the HSV-1 based talimogene laherparepvec (T-VEC), has an immunological mechanism of action, which also causes the regression of uninjected and uninfected metastases [23].
Nevertheless, OVs are still not powerful enough, especially for scarcely immunogenic or immunosuppressive solid tumors, which unfortunately are quite frequent in the population, like pancreatic adenocarcinoma, triple negative breast cancer, hepatocellular carcinoma [24][25][26]. This lack of efficacy is somehow unexpected, as OVs should make the TME significantly more immunogenic due to inflammation and the presence of viral antigens. Such a consideration fuels the feeling that major improvements in the OV therapy field are at hand. This review will focus on open issues regarding OVs, and especially their interaction with the TME and the host immune system. The answer to these questions will probably be crucial to fully exploit the therapeutic potential of OVs.

Main text
As explained above, OVs are emerging as a new, promising form of immunotherapy. In recent years a remarkable array of different OVs has been tested in preclinical cancer models or in phase I/II clinical trials [27]. This plethora of viruses includes, among the others, attenuated strains of human pathogens, such as adenoviruses (AdVs) [28], herpes simplex type 1 (HSV-1) [29], vaccinia virus (VACV) [30], measles [31], mumps virus [32] and influenza A virus [33], or viruses that are naturally poorly pathogenic for humans, including the orthoreovirus strain T3D [34], Newcastle Disease Virus (NDV) [35], vesicular stomatitis virus (VSV) [36], Maraba Virus [37], the rodent H-1 parvovirus [38] and the picornavirus Mengovirus [39], a long list far from being complete [ Table 1]. Perhaps the most striking common feature of these heterogeneous OVs is their outstanding safety profile. Indeed, severe adverse effects were very rare and it was unusual that therapy had to be discontinued due to toxicity [40]. Unfortunately, safety was not always matched by efficacy, and so far only the HSV-1 based talimogene laherparepvec was effective enough to be authorized for routine clinical use. Also, efficacy was markedly higher in immunogenic tumors such as melanoma [41].
Therefore, despite the fact that OVs hold great therapeutic potential, it is clear that they need to be further improved. A better understanding of their in vivo mechanisms of action and pharmacokinetics, as well as a clearer picture of the complex interplay between viruses and host are some of the crucial aspects to be further elucidated to design safer and more effective OVs. Under this respect, different questions remain to be addressed: 1. How "attenuated" should an attenuated OV be? The question may sound trivial, the answer being "attenuated enough to replicate only in cancer cells". However, the application of this oversimplified principle can have dire consequences, as it does not consider the real complexity of tumors. Many OVs were designed to be able to replicate only in actively dividing cells, for example by deletion of specific genes (like HSV or VACV thymidine kinase and ribonucleotide reductase), according to the idea that cancer cells are actively replicating while healthy cells are not [42]. Unfortunately, many cancer cells within a tumor mass are not undergoing replication. To make things worse, many non-tumoral cells are present in the TME (including macrophages, endothelial cells, lymphocytes, fibroblasts, MDSCs). It has been shown that these cells do not support the replication of OVs designed according to the aforementioned principle and can, therefore, protect malignant cells from viral diffusion [43]. Furthermore, due to the well known cancer heterogeneity, it is hazardous to assume that all cancer cells in all patients will display the same specific molecular characteristic, like mutations within certain oncosuppressor genes and/or overexpression of single pathways [44] and to assume that OV specificity towards cancer cells could rely only on these features [45,46]. Indeed, evidence demonstrate that the increased susceptibility of cancer cells towards viral replication is the result of variable combinations of alterations mainly in antiviral response and cell cycle regulation pathways. Thus, a more sensible approach for generating OVs, when starting from well-known human pathogens, might be to attenuate them in such a way that they cannot cause the dangerous forms of disease they are associated with (Table 1). In the case of HSV-1, in immunocompetent adults nearly all severe morbidity and mortality is caused by dissemination and replication in neurons, resulting in encephalitis. Therefore, genome modifications that attenuate HSV-1 virulence in neurons might be sufficient to generate a safe OV, despite the fact that the virus retains, at least partially, its ability to replicate in "healthy" fibroblasts or epithelial cells. This feature might even be useful, as it enables the virus to be more effective in the TME, as appears to be in the case of T-VEC. 2. What defines a solid in vitro model to screen for selectivity of OVs towards cancer cells? This question persists despite the fact that, according to what we have suggested above, the focus could be shifted from "unable to replicate in nonmalignant cells" to "unable to replicate in specific target cells relevant for human disease" (neurons in the case of HSV). The problem is associated with the definition itself of "nonmalignant" applied to tissue culture cells. Cell lines, even when incapable of forming tumors once inoculated in immunosuppressed mice, are often immortalized and have very different features from their in vivo counterparts, which can lead to OVs replication in these "healthy" cells. Furthermore, cell lines (including cancer cell lines) are often unpredictable in their susceptibility to viral replication: even viruses with broad cell tropism will occasionally produce very low titers in some cell lines [unpublished observations]. This raises the issue of finding a real "healthy" cell line in which the OV under evaluation is not replicating because the cell line does not have malignant characteristics, rather than because that cell line is characterized by refractoriness to that virus. Primary cells, although technically more demanding, could partially overcome some of these difficulties. On the other hand, organoids derived from malignant and healthy tissue, that are becoming a widely employed in vitro model for several types of studies, would have the further advantage of letting cells grow in a 3D environment, more closely mimicking the in vivo situation [47]. Thus, organoids might represent  [48]. Still, this feature (especially the absence of a competent T cell response) profoundly alters the mechanism of action of OVs. In these models, direct oncolysis by the virus could actually be the main effector mechanism that prolongs survival of the animals, which is probably not what happens in human patients. On the other hand, the use of immunocompetent mice could partially overcome this difficulty. However, the differences between the murine and human immune systems are still a hurdle, especially when the ability of the OV of influencing the immune response against cancer cells is under evaluation. Humanized mice, i.e.completely immunodeficient mice which receive a human hematopoietic stem cells (HSC) transplant plus human fetal thymus and liver tissue to guarantee T cell maturation, could provide an answer to this difficult problem [49]. 4. What is the exact role of the host immune system/ OV interaction in determining the success of virotherapy for tumors? Some investigators argue that the immune system has a deleterious effect, since it could wipe away the OV, especially if deriving from a human pathogen widely present in the population, before it can kill a sufficient number of cancer cells. As a consequence, efforts were spent on concealing the virus from the immune system, or on using viruses for which a preexisting immunity in the general population is unlikely [50]. However, this concept is clearly rooted in the older paradigm of OVs directly killing cancer cells rather than in the recent idea of OVs as tools for immunotherapy. Indeed, recent data strongly suggest that the release of danger signals and inflammation due to OV replication, along with immune system activation against infected cells, account for an important part of the antitumoral potential of the OV itself [51]. Furthermore, in the case of T-VEC, no differences in therapeutic effects were observed between HSV-1 seronegative and seropositive patients. Recently, a study using a mouse model of melanoma treated with the paramyxovirus NDV showed enhanced antitumoral activity in mice with preexisting immunity to NDV [52]. Finally, after intratumoral treatment with T-VEC, it was observed that uninjected lesions, including some visceral metastases, underwent regression. In a recent clinical trial, regression was heralded by activated CD8+ lymphocytes infiltration and was enhanced by checkpoint inhibitors [53]. Such a pattern is consistent with an immune response elicited by viral injection in multiple accessible lesions but effective also against uninjected lesions in which the virus was not detectable. 5. What is the best route of administration for an OV? It is often stated that an ideal OV should be systemically injectable, for some good reasons: essentially, the possibility to infect both primary tumor and metastases, and the fact that this route is relatively non-invasive and injections can be frequently repeated [54]. However, although some OVs (VACV, T3D orthoreovirus, H-1 parvovirus), were administered intravenously to human patients without severe side effects, the most used route is the local (intratumoral) injection [55]. This is the case also for the only approved OV, T-VEC. Intratumoral delivery is usually chosen because of safety concerns after intravenous injection, or, especially in the case of HSV-1, to minimize the chance that preexisting circulating antibodies might neutralize the virus before it reaches its target, as discussed above [56]. Nevertheless, as mentioned above, in the case of T-VEC, despite the intratumoral injection, uninjected lesions and visceral metastases displayed a regression, likely due to the immune response elicited by the virus [41]. 6. Viruses have an important feature, which makes them particularly appealing as cancer therapeutics: they are not just cancer cell killers or a proinflammatory stimulus, but they can also serve as platforms for the delivery/expression of transgenes. This feature allows the development of OVs "armed" with therapeutic genes, some of which are already under evaluation in clinical trials. One example is again T-VEC that, in addition to specific mutations within viral genes, carries two copies of the human granulocyte-monocyte colony stimulating factor (hGM-CSF) encoding sequence, under the transcriptional control of the human CMV immediate early promoter [57]. However, most of these engineered viruses only express a single immunostimulatory cytokine or ligand [58,59]. As a result, these OVs do not exploit the wealth of information that was recently accumulated on cancer immunology and the TME [60], and may even be outdated. For instance, recent comprehensive reviews cast a dubious light on the usefulness of hGM-CSF in cancer immunotherapy [61]. The issue with cancer immunotherapy is not simply boosting a "sleeping" immune response, but the fact that cancer cells actively use immunosuppressive mechanisms and recruit tolerogenic cells. OVs could be used to locally deliver high and constant concentrations of single-chain antibodies or other protein ligands that disrupt those immunosuppressive features. Under this respect, many different strategies can be devised, including the expression of enzymes that degrade the abundant extracellular matrix present in some tumors (desmoplastic reaction) or of dominant negative forms of immunosuppressive cytokines (for example TGF-β) [62]. 7. More specifically, could there be space for engineered OVs expressing checkpoint inhibitors, as single chain antibodies, whole antibodies, or proteins that may have the same function? Potent immune checkpoint inhibitors (CKIs) which are delivered systemically are already available, and most investigators are focusing on synergism between existing checkpoint inhibitors and OVs [63]. However, CKIs expressed as therapeutic genes by OVs would probably have the advantage of a prolonged and localized delivery in the TME, which might, in principle, avoid the autoimmune side effects usually associated with systemic CKIs. 8. Is there the possibility of a more extensive cellspecific reprogramming of viruses? Ideally, once an OV reaches the TME, it should produce different effects in different types of cells. Of course, it should replicate in cancer cells and cause their death while sparing surrounding normal tissue and/ or non causing severe diseases. However there could be further nuances. For example, an OV could be designed to specifically trigger a Th1 phenotype in infected macrophages or to replicate also in cancer associated fibroblasts or endothelial cells that might become a more persistent "factory" of therapeutic gene products. Transgenes under the transcriptional control of cell-specific promoter might serve to this end. While "promoter retargeting" has been explored to enhance viral replication in cancer cells, such an approach to the diversity of the TME has not been investigated yet, at least to our knowledge.

Conclusions
Cancer immunotherapy is establishing new paradigms in the treatment of advanced stage solid malignancies. Together with immune checkpoint inhibitors, OVs are increasingly recognized as a promising therapeutic tool in this field. The use of OVs on patients has become a clinical reality in the case of talimogene laherparepvec, also known as T-VEC, for metastatic melanoma, and recent Fig. 1 Schematic representation of cancer cells (cyan) in their immunosuppressive microenvironment, which they shape by secreting cytokines and growth factors. Immune checkpoint molecules and immunosuppressive enzymes released in the milieu inhibit cytotoxic T lymphocytes. Infection of cancer cells by an oncolytic virus (OV, gray) disrupts the immunosuppressive features of the microenvironment by triggering immunogenic cell death and releasing proinflammatory substances. OVs can also be armed with therapeutic genes targeting non malignant cells that support tumor growth and immune escape, such as cancer associated fibroblasts, M2 macrophages, myeloid derived suppressor cells (MDSCs), and regulatory T lymphocytes clinical trials strongly suggest that the combination of talimogene with CKIs could be particularly effective in this setting [23,53]. Despite this successes, OV treatment of cancers other than melanoma, which is usually considered a very immunogenic tumor, has given limited clinical results [64,65]. Several recent studies have been trying to characterize the antitumoral immune response after OV therapy both in mouse models and in patients enrolled in clinical trials [53,66]. However, current basic and translational research on OVs is mainly focused on safety (which, however, has never been a real issue over decades of clinical trials), on various combinations of OVs with chemo and radiotherapy or CKIs, and on the quest for "exotic" non-human viruses, whose ability to infect and lyse a significant number of human cancer cells in vivo remains questionable [67]. The feeling that OVs are not being exploited to their potential is increased by the lack of new ideas on the use of OVs as platforms to express factors aimed at increasing their killing ability and the immunomodulatory effect. Under this respect, there have not been many novelties in the last years, at least to our knowledge. Indeed, in the field of OVs, viral engineering has been mainly employed for the attenuation of the human pathogen under evaluation, for its transcriptional [68] or receptorial [69] retargeting, for the expression of suicide genes or single immunostimulatory cytokines (as in the case of talimogene). Thus, there is wide space for the design of innovative OVs to better achieve, for instance, TME modulation. The ideal candidate would be a large dsDNA virus that can allow the insertion of multiple transgenes within its genome, without losing its ability to replicate in and kill cancer cells, and for which "robust" gene editing techniques are available.
Finally, the big challenge that OVs are facing is the therapy of immunologically "cold" tumors which are usually failing to respond to checkpoint inhibitors due to the absence of a lymphocyte infiltrate. The presence of a virus (especially of a replication competent virus) can profoundly alter the TME by enhancing the immune cell infiltrate and generating proinflammatory cues. Is this enough to make cold tumors sensitive to immune checkpoint inhibition? It must be considered that these tumors often display an immunosuppressive immune cell infiltrate or a fibrotic microenvironment, which could protect malignant cells from the immunogenic stimuli provided by the virus. Armed OVs might be once again the solution to this problem. Indeed, therapeutic gene products, released at high concentrations in situ by infected cells, could synergize with OVs by killing immunosuppressive cells or inhibiting their activity. Furthermore, OVs could be engineered to express enzymes that degrade the fibrotic extracellular matrix, thus helping to tackle very "difficult" tumor microenvironments [ Fig. 1].


extfieldsofstudy: Biology Medicine

text:
Epigenetic and transcriptional profiling of triple negative breast cancer

The human HCC1806 cell line is frequently used as a preclinical model for triple negative breast cancer (TNBC). Given that dysregulated epigenetic mechanisms are involved in cancer pathogenesis, emerging therapeutic strategies target chromatin regulators, such as histone deacetylases. A comprehensive understanding of the epigenome and transcription profiling in HCC1806 provides the framework for evaluating efficacy and molecular mechanisms of epigenetic therapies. Thus, to study the interplay of transcription and chromatin in the HCC1806 preclinical model, we performed nascent transcription profiling using Precision Run-On coupled to sequencing (PRO-seq). Additionally, we mapped the genome-wide locations for RNA polymerase II (Pol II), the histone variant H2A.Z, seven histone modifications, and CTCF using ChIP-exo. ChIP-exonuclease (ChIP-exo) is a refined version of ChIP-seq with near base pair precision mapping of protein-DNA interactions. In this Data Descriptor, we present detailed information on experimental design, data generation, quality control analysis, and data validation. We discuss how these data lay the foundation for future analysis to understand the relationship between the nascent transcription and chromatin.

Background & Summary
Triple negative breast cancer (TNBC) is a highly aggressive and heterogeneous form of cancer 1 . TNBC is characterized by a lack of expression for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Because TNBC lacks these proteins, targeted drug therapies directed against ER, PR, and HER2 are not possible. Therefore, standard care typically includes surgical resection, radiation, and chemotherapy. Prognosis remains poor for TNBC patients receiving standard care, highlighting the need for new and innovative therapeutic strategies. Emerging efforts have focused on the epigenome as a therapeutic target for TNBC 2 . It is now clear that epigenetic mechanisms play an important role in the pathogenesis, maintenance, and therapeutic resistance of the disease 3 . Consistent with this notion, a recently proposed model for transcriptional addiction in cancer suggests that transcriptional and chromatin regulators are potential targets for therapeutic intervention using innovative approaches 4 .
Given that epigenetic and transcriptional regulators are implicated in the pathogenesis of TNBC, there is a need to better understand the mechanisms involved in the epigenetic modulation of genes expressed in TNBC 5 . Functional genomic approaches offer an unbiased, comprehensive glimpse into how transcriptional and chromatin regulators interact with the genome. For example, nascent transcriptional profiling (Precision Run-On sequencing, PRO-seq) and protein-DNA contact profiling (Chromatin Immunoprecipitation Exonuclease and sequencing, ChIP-exo) are state-of-the-art functional genomic tools that enable interrogation of global RNA synthesis and protein-DNA interactions, respectively 6,7 . PRO-seq and ChIP-exo studies generate scientifically valuable datasets due to their unique characteristics and reanalysis potential, which advances the sharing and reuse of scientific data.
PRO-seq and other nascent profiling approaches, such as GRO-seq, are more sensitive at detecting transcriptional responses than traditional assays like RNA-seq because they measure newly synthesized RNA, rather than the steady-state abundance of total RNA synthesis and degradation. This distinction is critical for detecting rapid transcriptional responses to stimuli, such as hormones and drug treatments 8,9 . In addition to using PRO-seq data to compute RNA synthesis rates 10 , other biological features may be inferred from the unique data structure, such as transcription factor (TF) binding and enhancer activity [11][12][13] . Furthermore, computational tools have been developed to mine PRO-seq (or related GROseq) data and provide de novo annotation of long noncoding RNAs, microRNAs, and enhancer RNAs [14][15][16][17] . Taken together, the reanalysis potential of PRO-seq data is high.
ChIP-exo displays improved resolution and sensitivity over the traditional ChIP-seq method 18 . Rather than sequencing from the distal sonication borders as in ChIP-seq, ChIP-exo enriched DNA fragments are sequenced from the left and right 5' DNA borders of the protein-DNA crosslink site. The precision of the resulting data can be leveraged to provide unique and ultra-high resolution insights into the functional organization of the genome 19 . For example, ChIP-exo was uniquely capable of spatially resolving divergent, initiating, paused, and elongating RNA polymerase II (Pol II) on a genome-wide scale [20][21][22] .
In this Data Descriptor, we provide a technical validation of twenty-two functional genomic data sets that interrogate the nascent transcription, Pol II binding, and chromatin architecture using the HCC1806 preclinical model for TNBC [24][25][26] . In this study, we focused on the TNBC HCC1806 cell line and have generated 2 PRO-seq data sets and 20 ChIP-exo data sets (2 biological replicates for each of the following targets: Pol II, H2A.Z, H3K4me3, H3K4me2, H3K4me1, H3K27ac, H3K9ac, H3K27me3, H4K20me1, and CTCF). ChIP-exo mapping of Pol II, a histone variant, and select histone modifications should enable other investigators to use these data sets for their own research to further understand the detailed interplay of Pol II and chromatin in ultra-high resolution in a preclinical model for breast cancer. On average, 36 million uniquely aligned reads were generated for each PRO-seq and ChIP-exo data set (Table 1). To facilitate interpretation of these data, we provide detailed information on experimental design ( Fig. 1), sequence quality control analyses (Fig. 2), and biological validation (Fig. 3).

PRO-seq library preparation
PRO-seq was performed as previously described 7 with isolated nuclei from 25 million cells from two biological replicates. To enable comparisons to drug treatment experiments, cells were treated with vehicle (final 0.03% DMSO (dimethyl sulfoxide)) for 4 h prior to harvest.

ChIP-exo library preparation
ChIP-exo was performed as previously described 6 (EMD Millipore 07-449), H4K20me1 (Abcam ab9051), and CTCF (EMD Millipore 07-729). Two biological replicates were prepared for each ChIP target. To enable future comparisons to drug treatment experiments, cells were treated with vehicle (final 0.03% DMSO (dimethyl sulfoxide)) for 4 h prior to harvest. Libraries were sequenced using an Illumina NextSeq500 sequencer as single-end reads 50 or 75 nucleotides in length (Table 1).

Sequence read alignment and quality control
The base call quality for each sequenced read was assessed using the FastQC program (bioinformatics. babraham.ac.uk/projects/fastqc/) ( Fig. 2a and Supp. Figs. 1-3). Sequence reads (fastq files) were aligned to the human hg19 reference genome build using BWA-MEM algorithm with default parameters 27 . The resulting bam files were first sorted using the Samtools Sort function, and then bam index files were generated using the Samtools Index function 28 . The purpose of bam index files is to enable viewing of raw sequencing data in a genome browser. Next, genome-wide read coverage and enrichment were assesses using deepTOOLS fingerprint plots 29 ( Fig. 2b and Supp. Figs 4-6).

Biological validation
To estimate variance across biological replicates, the Pearson correlation coefficient for pairwise gene Reads Per Kilobase of genome per Million reads (RPKM) was computed (Fig. 2c, Supp. Fig. 7 HOMER (Hypergeometric Optimization of Motif EnRichment) suite 30 . Briefly, bam files were converted to tag directories using the makeTagDirectory function with the -genome, -checkGC, and -format options. To quantify and normalize tags within gene body regions to RPKM, the analyzeRepeats function was used with the -rpkm and -d options (2019SciDataVenters_RPKM.xlsx, Data Citation 1). bedTOOLS was used to convert files from bam to Bigwig, and then the ChAsE (Chromatin Analysis and Exploration) suite was used to display the read distribution relative to the TSS from Bigwig files (Fig. 3a,b, Supp. Fig. 8) 33 . Raw sequencing tags were binned, smoothed, and RPKM computed using the deepTOOLS genomeCoverage tool (20 bp bin, 100 bp sliding window) 29 . Smoothed RPKM signal was visualized with Integrative Genomics Viewer (IGV) (Fig. 3c) 32 .

Code availability
Below is a list of software used in this study.

Data Records
PRO-seq and ChIP-exo bigwig data files from merged replicates were deposited in the NCBI Gene Expression Omnibus (GEO) (Data Citation 2). GEO linked PRO-seq and ChIP-exo bam data files for each replicate were deposited in the Sequence Read Archive (SRA) (Data Citation 3). Table 1 contains sequencing statistics for each data set and linked to its SRA identification number.

Technical Validation
Overview of experimental design In this study, functional genomic experiments using HCC1806 cells were designed with two primary goals in mind. First, PRO-seq data sets were generated to specifically measure nascent transcription. Second, the ChIP targets (Pol II, H2A.Z, H3K4me3, H3K4me2, H3K4me1, H3K27ac, H3K9ac, H3K27me3, H4K20me1, and CTCF) were selected so that Pol II binding and chromatin architecture may be examined on a genome-scale at high precision ( Fig. 1). Histone modifications follow patterns of enrichment and delineate specific regions in the genome. For example, H3K4me1 and H3K27Ac are known to be found around distal enhancer regions, along with the histone variant H2A.Z. H3K4me1/2/3 and H3K9Ac are associated with promoter proximal regions, where H3K27ac and H2A.Z are also present 23,34-43 . H4K20me1 is critical for proper cell cycle progression and is typically depleted at promoters, but enriched in the body of genes 44 . Repressive marks and structural transcription factors, such as H3K27me3 and CTCF respectively, insulate regions of the genome that are not actively transcribed 35,45,46 . Taken together, reanalysis of this collection of data should enable new biological insights into chromatin dynamics in a pre-clinical breast cancer model. Below, we briefly describe the rationale and considerations for sequencing data analysis with respect to general read quality, genome alignment, ChIP enrichment, replicate correlation, and biological validation.

Raw sequence quality control analyses
To assess the quality of the raw sequencing data sets, base call scores were analyzed using the FastQC program and displayed as a box plot distribution at each base position (Fig. 2a and Supp. Figs. 1-3). The average base quality score for a majority of the data sets in the present study fell within the high confidence range (base quality score of 30-40, green region). Raw sequence reads were aligned to the hg19 build of the human genome. On average, 46 million total aligned reads were generated for each PRO-seq and ChIP-exo data sets ( Table 1). Because of the ambiguity of reads that align to multiple locations throughout the genome, we only retain uniquely aligned reads for subsequent analyses. On average, 36 million uniquely aligned reads were obtained per data set, representing an average unique alignment rate of 76%. Two critical questions for assessing ChIP sequencing data quality are: 1) how much of the genome is represented by a given experiment? and 2) to what extent did the ChIP assay enrich for specific regions of the genome? Typically, high genome coverage and strong ChIP enrichment are desirable in ChIP experiments. To determine genome coverage and ChIP enrichment simultaneously, we used the  H3K4me3, H3K4me2, H3K4me1, H3K27ac, H3K9ac, H3K27me3, H4K20me1, and CTCF). deepTOOLS suite to perform a fingerprint analysis (Fig. 2b). In the case of H2A.Z ChIP-exo (Fig. 2b), the fingerprint plot trace intersects the x-axis at 25, indicating 75% genome coverage. In fingerprint plots, a rightward deflection of the trace indicates the extent of ChIP enrichment. Given a point along the trace that is the point of intersection from the axes, the corresponding values on the x-and y-axes denote the percent of genome and the percent of all uniquely aligned reads, respectively. Together, these values reflect ChIP enrichment.
For example, the H2A.Z ChIP-exo fingerprint trace reveals that 10% of the genome is enriched with 60% of all uniquely aligned reads, suggesting strong enrichment in the H2A.Z ChIP-exo data set (Fig. 2b). Fingerprint plots for other replicates showed similar patterns of genome coverage and ChIP enrichment (Supp . Figs 4-6). Theoretically, complete genome coverage with no enrichment would be result in a trace with a slope equal to one that intersects the origin (eg: whole genome sequencing wherein 50% of the genome is contains 50% of all aligned reads).

Biological validation
After verifying the quality of the raw sequencing data, we next sought to provide evidence of biological validity for the data. First, we determined the extent to which biological replicates were reproducible using correlation scatter plots (Fig. 2c). For each gene, the RPKM was computed using the HOMER suite (Data Citation 1). Pearson correlation coefficients (R values) were computed for pairwise correlation plots of gene RPKM across biological replicates. For example, biological replicates for H2A.Z ChIP-exo analysis displayed an R value of 0.85, indicating high reproducibility (Fig. 2c). Overall, correlation analysis resulted in an average R-values of 0.86 (Supp. Fig. 7). Because CTCF is typically enriched in intergenic regions rather than within gene bodies, correlation analysis compared peak RPKM.
Given that certain histone modifications are consistently found at distinct regions of the stereotypical gene, analyzing global patterns of ChIP signal relative to TSSs is a useful method to assess biological validation 47 . For example, it is well established that once Pol II initiates transcription of genes in metazoans, Pol II moves into a stable paused state 30-50 bp downstream of the TSS. Nascent transcription profiling with PRO-seq enables quantification of RNA synthesis and largely coincides with Pol II ChIP-exo density. H3K4me1/2/3 and H3K9Ac are associated with promoter proximal regions, surrounding the TSS of active genes in combination with H3K27Ac. The histone variant H2A.Z is consistently incorporated into the + 1 nucleosome of actively transcribed genes. Distal to gene promoters, H3K4me1 and H3K27Ac have been used as predictive marks of enhancers, which regulate the transcription of their target genes in a distance and orientation independent manner.
Thus, to examine global patterns of ChIP enrichment, the Chromatin Analysis and Exploration (ChAsE) heatmap tool was used to align ChIP signal merged from both biological replicates to TSSs (Fig.  3a, sorted by max peak; and Supp. Fig. 8, sorted by max peak position). Quantification of signal density relative to TSSs is displayed as a composite plot below each heatmap (Fig. 3b). As expected, Pol II was strongly enriched at the pause site just downstream of the TSS. H2A.Z enrichment at the -1 and + 1 nucleosomes immediately flanked Pol II density. H3K4me2, H3K4me3, and H3K9ac were enriched at the + 1 nucleosome as well, but also spread into the body of gene, overlapping the + 1, + 2, and + 3 nucleosome positions. Interestingly, H3K27ac density was similar to H3K9ac but avoided the + 1 nucleosome position. H3K4me1 and H4K20me1 density excluded promoter regions, but were enriched further downstream into the gene body. In contrast to the other histone modifications and consistent with its association to gene repression, H3K27me3 was enriched at genes with the least Pol II and PROseq density. Lastly, as expected, gene bodies largely lacked CTCF signal. To examine individual examples of global patterns, RPKM normalized tracks for PRO-seq and ChIP-exo signal were displayed using the Integrative Genome Viewer (IGV), and displayed at the MYC gene locus (Fig. 3c). Finally, a comparison of Pol II ChIP-exo and ChIP-seq signal at promoters (Supp. Fig. 9) shows that Pol II ChIP-exo more clearly resolves adjacent peaks of Pol II enrichment corresponding to Pol II pausing just after the TSS and divergent transcription just upstream of the TSS. This is evident both as a genome-wide pattern (Supp. Fig. 9a,b) and in several anecdotal examples (Supp. Fig. 9c).
Taken together, the data presented in this Data Descriptor represents high quality next generation sequencing data that are biologically valid, and should be useful to future studies that seek to understand the interplay of Pol II and chromatin in high resolution on a global scale.


extfieldsofstudy: Medicine Chemistry

text:
Antioxidant Barrier, Redox Status, and Oxidative Damage to Biomolecules in Patients with Colorectal Cancer. Can Malondialdehyde and Catalase Be Markers of Colorectal Cancer Advancement?

This study is the first to assess the diagnostic utility of redox biomarkers in patients with colorectal cancer (CRC). Antioxidant barrier (Cu,Zn-superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), glutathione reductase (GR), uric acid (UA), reduced glutathione (GSH)), redox status (total antioxidant (TAC)/oxidant status (TOS), ferric reducing ability (FRAP)), and oxidative damage products (advanced glycation end products (AGE), advanced oxidation protein products (AOPP), malondialdehyde (MDA)) were measured in serum/plasma samples of 50 CRC patients. The activity of SOD was significantly higher whereas the activity of CAT, GPx and GR was considerably lower in CRC patients compared to the control group (p < 0.0001). Levels of UA, TOS, and OSI and concentrations of AGE, AOPP, and MDA were significantly higher, and the levels of GSH, TAC, and FRAP were considerably lower in CRC patients compared to the healthy controls (p < 0.0001). AUC for CAT with respect to presence of lymph node metastasis was 0.7450 (p = 0.0036), whereas AUC for MDA according to the depth of tumour invasion was 0.7457 (p = 0.0118). CRC is associated with enzymatic/non-enzymatic redox imbalance as well as increased oxidative damage to proteins and lipids. Redox biomarkers can be potential diagnostic indicators of CRC advancement.

Introduction
Colorectal cancer (CRC) is one of the most common types of cancer and classified as the third most common cancer in the world. According to GLOBOCAN estimates, in 2020 the number of new cases of colorectal cancer will amount to over 1.8 million, and the number of deaths will come to 10,502,507 [1]. It is important to detect cancer at an early stage because the five-year relative survival rate for patients with stage I colorectal cancer is about 92%, whereas in patients with stage IV (with lymph node and distant metastases) is less than 10%. However, despite screening tests, i.e., faecal occult blood testing (FOBT) and colonoscopy ('gold standard' of CRC screening), the survival time of patients with colorectal cancer has not improved significantly [2]. The main cause of this fact is that colonoscopy is an invasive and limited method due to difficulties for patients before the test performance. On the other hand, faecal occult blood testing offers limited sensitivity, particularly at the initial stage of the disease [2]. Nevertheless, early detection and treatment of CRC may prevent further progression of invasive cancer as well as significantly reduce the percentage of patient mortality. Therefore, it is important to understand the biology of CRC and search for new diagnostic biomarkers enabling the detection of cancer at its early stage.
Colorectal cancer is a consequence of multiple genetic events. Nevertheless, the majority of CRC cases occur as a result of the CIN (chromosomal instability) pathway characterized by defects in chromosomal segregation, telomere stability, and DNA damage response [3]. One of the most important mechanisms responsible for DNA damage is oxidative stress [4]. This process is defined as an imbalance between the production of reactive oxygen (ROS) and nitrogen (RNS) species and the efficiency of enzymatic and non-enzymatic antioxidant protection [5]. Overproduction of ROS is a result of the exposure to risk factors including smoking, stress, alcohol, toxins and inflammatory process caused by metabolic diseases, as well as lifestyle factors, diet, and dysbiosis, which are also connected with the development of colorectal cancer [6,7]. Increase of ROS level may lead to redox imbalance and cause tumour initiation and progression by activation of redox-responsive signalling cascades that promote cell growth [8]. Moreover, ROS induce lipid and protein peroxidation. It is well known that oxidized proteins accumulate in cells and inhibit proteasome activity, thus increasing the accumulation of misfolded/damaged proteins and causing further structural and functional alterations of cell organelles [9]. It has been confirmed that oxidative stress is involved in the development of malignant tumours through genetic mutations and initiation of DNA damage; inhibition of apoptosis; as well as promotion of proliferation, differentiation, and migration of malignant cells [10]. The usefulness of oxidative stress biomarkers has been demonstrated in numerous systemic diseases such as obesity, insulin resistance, diabetes, chronic kidney disease, and dementia, as well as in some types of cancer such as gastric cancer, ovarian cancer, and melanoma [7,[11][12][13][14][15]. However, still little is known about the diagnostic utility of oxidative stress/redox parameters in patients with colorectal cancer. No study has also measured the total antioxidant/oxidant capacity in CRC patients. Therefore, the aim of our study was to evaluate the redox status, enzymatic and non-enzymatic antioxidants, as well as oxidative damage to proteins and lipids in colorectal cancer patients compared to the healthy controls. We are also the first to assess the diagnostic utility of oxidative stress parameters using the analysis of receiver operating characteristic (ROC) curve.

Patients
The research was approved by the Bioethics Committee of the Medical University of Bialystok, Poland (permission number R-I-002/48/2019). After a thorough explanation of the purpose of the study and possible risks, all the qualified patients consented in writing to participate in the experiment. The study was conducted in accordance with the World Medical Association Declaration of Helsinki for ethical principles for medical research involving human subjects. The study group consisted of 50 patients (19 women and 31 men) treated surgically for colorectal cancer in the 2nd Clinical Department of General and Gastroenterological Surgery at the Medical University of Bialystok Clinical Hospital in the years 2017-2018. Patients were selected based on the following criteria: patients of both sexes without coexistence of other systemic diseases who had not been treated by radio-or chemotherapy before the surgery. The time from diagnosing a patient with cancer to the surgery varied from a minimum of two days to a maximum of four weeks. The study material was collected from all patients before surgical resection of tumour. Differentiation and recognition of histological type of cancer were performed following the World Health Organization guidelines [16]. Tumour stage was determined according to the TNM classification standard of the Union for International Cancer Control. TNM classification of malignant tumours included pT (depth of invasion), pN (lymph node metastasis), and pM (distant metastasis) stages [17].
In the control group, selected by sex and age to match the study group, samples were obtained from 40 healthy subjects attending follow-up visits at the Specialist Dental Clinic (Department of Restorative Dentistry) at the Medical University of Bialystok from January 2018 to January 2019. Only patients with normal results of complete blood count and biochemical blood tests (Na + , K + , creatinine, INR, ALAT, ASPAT) were admitted to the control group.
The exclusion criterion in patients with CRC and the control group was any systemic or autoimmune disease (diabetes, insulin resistance, hypertension, coronary heart disease, rheumatoid arthritis, and psoriasis) as well as thyroid, lung, kidney, liver, gastrointestinal, and infectious diseases (HCV and HIV infection) as well as immunity disorders. Additionally, smokers and patients taking antibiotics, glucocorticosteroids, non-steroidal anti-inflammatory drugs (NSAIDs), vitamins, and dietary supplements for last 3 months were excluded from the study and the control groups. In addition, only subjects on a standard diet were qualified for the study (2000 calories; 55% carbohydrates, 30% fat, and 15% protein).
The number of patients in the study and the control group was set based on a previously conducted pilot study. The power of the study was set at 0.9.

Blood Collection
Fasting venous blood (10 mL) was collected from all patients on empty stomach and upon overnight rest. The S-Monovette®K3 EDTA blood collection system (Sarstedt, Germany) was used for this. Blood was centrifuged at 1500× g for 10 min at +4 • C (MPW 351, MPW Med. Instruments, Warsaw, Poland) and the top layer (plasma) was taken. In order to prevent sample oxidation, 0.5 M butylated hydroxytoluene (20 µL/2 mL plasma or serum) was added [18]. Until redox determinations, all samples were stored at −80 • C.

Determination of Redox Markers
All the assays were performed in duplicate samples. The activity of enzymatic antioxidants was analysed in the serum samples, while the total antioxidant/oxidant status as well as concentrations of non-enzymatic antioxidants and oxidative damage products-in the plasma samples. The absorbance/ florescence was measured using Infinite M200 PRO Multimode Microplate Reader (Tecan). The results were standardized to 100 mg of total protein. The content of total protein was estimated colorimetrically at 562 nm wavelength via the bicinchoninic acid (BCA) method [19]. A commercial kit was used (Thermo Scientific PIERCE BCA Protein Assay; Rockford, IL, USA).

Enzymatic and Non-Enzymatic Antioxidants
The activity of copper-zinc-superoxide dismutase (SOD, E.C. 1.15.1.1) was analysed colorimetrically at 480 nm wavelength by measuring the inhibition of adrenaline oxidation to adrenochrome [20]. One unit of SOD activity was defined as the amount of enzyme inhibiting adrenaline oxidation by 50%. The activity of catalase (CAT, E.C. 1.11.1.6) was estimated colorimetrically at 240 nm wavelength by measuring the rate of hydrogen peroxide decomposition [21]. One unit of CAT activity was defined as the amount of enzyme that decomposes 1 mmol of hydrogen peroxide per 1 min. The activity of glutathione peroxidase (GPx, E.C. 1.11.1.9) was analysed colorimetrically at 340 nm wavelength based on the reduction of organic peroxides in the presence of reduced nicotinamide adenine dinucleotide phosphate (NADPH) [22]. One unit of GPx activity was defined as the amount of enzyme catalysing the oxidation of 1 µmol of NADPH per 1 min. The activity of glutathione reductase (GR, E.C. 1.8.1.7) was determined colorimetrically at 340 nm wavelength by measuring the decrease in NADPH absorbance [23]. One unit of GR activity was defined as the quantity of enzyme that catalyses the oxidation of 1 µmol of NADPH per 1 min.
The level of uric acid (UA) was estimated colorimetrically at 590 nm wavelength. Commercial kit from BioAssay Systems, Harward, CA, USA (QuantiChromTM Uric Acid DIUA-250 kit) was used. The level of reduced glutathione (GSH) was measured colorimetrically based on the reaction of GSH from the sample with 5,5 -dithiobis-2-nitrobenzoic acid (DTNB) [24]. The absorbance of the resulting complex was measured at 412 nm wavelength.

Total Antioxidant/Oxidant Status
The total antioxidant capacity/status (TAC) was analysed colorimetrically based on the reaction of ABTS (2,2-azinobis-3-ethylbenzothiazoline-6-sulfonic acid) radical cation with antioxidants contained in the plasma [25]. TAC levels were calculated from the calibration curve for 6-hydroxy-2,5,7,8tetramethylchroman-2-carboxylic acid (Trolox). The total oxidant status (TOS) was measured bichromatically (560/800 nm) based on the oxidation of Fe 2+ to Fe 3+ in the presence of the oxidants contained in the plasma [26]. TOS levels were expressed as micromolar hydrogen peroxide equivalent per litre. Oxidative stress index (OSI) was calculated by dividing TOS level by TAC level (TOS/TAC ratio) and expressed in % [27].

Oxidative Damage Products
The content of advanced glycation end products (AGE) was estimated fluorimetrically by measuring AGE-specific fluorescence at 350 nm/440 nm wavelength in 96-well black bottom microplates [29]. For AGE determination, plasma samples were diluted 1:50 (v/v) in phosphate buffered saline (0.02 M, pH 7.0). The concentration of advanced oxidation protein products (AOPP) was analysed colorimetrically at 340 nm wavelength by measuring the oxidative capacity of iodine ion [29]. For AOPP determination, plasma samples were diluted 1:50 (v/v) in in phosphate buffered saline (0.02 M, pH 7.0).

H + E Staining
Histopathological diagnosis (histological type, the grade of histological malignancy, as well as clinical-anatomical advancement) has been established based on haematoxylin-eosin (H + E) staining. Each tumour was cut along a line that was parallel to the longest tumour axis. In this way, 4 to 8 slices contained cancer and adjacent macroscopically unchanged tissues of 1-1.5 cm in size were taken. Tissues were fixed in 10% buffered formalin within 24 to 48 hours. The specimens were embedded in paraffin at a temperature of 56 • C. Paraffin blocks were cut into 4 µm thick sections. The obtained sections were stained with H + E and reviewed by two independent pathologists on a microscope Olympus CX22 (200× or 400× magnification).

Statistical Analysis
Statistical analysis was performed using the Statistica 10.0 system (StatSoft, Krakow, Poland) and GraphPad Prism 7.0 (GraphPad Software). The Shapiro-Wilk test was used to examine normal distribution. For normal distribution of the results, a Student's t-test was used. In the lack of normal distribution of the results, the Mann-Whitney U test was used. The correlations between the measured parameters were analysed by Pearson correlation coefficient. Statistical significance was established at p < 0.05. The diagnostic value of oxidative stress parameters and the optimum cut-off values were determined based on receiver operating characteristic (ROC) analysis.

Clinical Findings
The study included 50 patients with colorectal cancer and 40 healthy people matched by age and sex with the study group. In all CRC patients the tumour differentiation grade was G2 (moderately differentiated). A total of 40 patients had adenocarcinoma and 10 patients had a mucinous adenocarcinoma ( Figure 1A,B). Differentiation and recognition of histological type of cancer were performed following the World Health Organization guidelines [16], while tumour stage was determined according to the TNM classification standard of the Union for International Cancer Control. There was no significant relationship between age and sex of patients with clinical and demographic parameters. Detailed patient characteristics are summarized in Table 1.
Biomolecules 2019, 9, 637 5 of 18 measured parameters were analysed by Pearson correlation coefficient. Statistical significance was established at p < 0.05. The diagnostic value of oxidative stress parameters and the optimum cut-off values were determined based on receiver operating characteristic (ROC) analysis.

Clinical Findings
The study included 50 patients with colorectal cancer and 40 healthy people matched by age and sex with the study group. In all CRC patients the tumour differentiation grade was G2 (moderately differentiated). A total of 40 patients had adenocarcinoma and 10 patients had a mucinous adenocarcinoma ( Figure 1A,B). Differentiation and recognition of histological type of cancer were performed following the World Health Organization guidelines [16], while tumour stage was determined according to the TNM classification standard of the Union for International Cancer Control. There was no significant relationship between age and sex of patients with clinical and demographic parameters. Detailed patient characteristics are summarized in Table 1.

Antioxidant Defence
In order to assess the antioxidant barrier, we evaluated the activity of antioxidant enzymes (i.e., Cu,Zn-superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and glutathione reductase (GR)) and concentration of non-enzymatic antioxidants (uric acid (UA), and reduced glutathione (GSH)). SOD activity was significantly higher, whereas CAT activity was considerably lower in the serum of patients with colorectal cancer compared to the control group (p < 0.0001, p < 0.0001, respectively). The concentration of UA in plasma was significantly higher in the study group than in the controls (p < 0.05). There was a statistically significant increase in the activity of GPx, GR and GSH in colorectal cancer patients compared to healthy controls (p < 0.0001, p < 0.0001, p < 0.0001) (Figure 2).

Total Antioxidant/Oxidant Status
To assess the redox status, we focused on total antioxidant capacity (TAC), total oxidant status (TOS), and ferric reducing ability of plasma (FRAP). Furthermore, we also calculated oxidative stress index (OSI) by dividing TOS level by TAC level (TOS/TAC ratio). In the plasma of patients with colorectal cancer, TAC and FRAP levels were significantly lower compared to the control group (p < 0.0001). We observed considerable increase in TOS in the plasma of study group patients compared to healthy controls (p < 0.0001). The OSI value in colorectal cancer patients was significantly higher than in the healthy controls (p < 0.0001) ( Figure 3). glutathione (GSH)). SOD activity was significantly higher, whereas CAT activity was considerably lower in the serum of patients with colorectal cancer compared to the control group (p < 0.0001, p < 0.0001, respectively). The concentration of UA in plasma was significantly higher in the study group than in the controls (p < 0.05). There was a statistically significant increase in the activity of GPx, GR and GSH in colorectal cancer patients compared to healthy controls (p < 0.0001, p < 0.0001, p < 0.0001) ( Figure 2).

Total Antioxidant/Oxidant Status
To assess the redox status, we focused on total antioxidant capacity (TAC), total oxidant status (TOS), and ferric reducing ability of plasma (FRAP). Furthermore, we also calculated oxidative stress index (OSI) by dividing TOS level by TAC level (TOS/TAC ratio). In the plasma of patients with colorectal cancer, TAC and FRAP levels were significantly lower compared to the control group (p < 0.0001). We observed considerable increase in TOS in the plasma of study group patients compared to healthy controls (p < 0.0001). The OSI value in colorectal cancer patients was significantly higher than in the healthy controls (p < 0.0001) (Figure 3).

Oxidative Damage Products
To assess the oxidative stress, we used oxidative damage products of proteins (i.e., advanced glycation end products (AGE), advanced oxidation protein products (AOPP)) and lipids (malondialdehyde (MDA)). There was a statistically significant increase in AGE fluorescence in

Oxidative Damage Products
To assess the oxidative stress, we used oxidative damage products of proteins (i.e., advanced glycation end products (AGE), advanced oxidation protein products (AOPP)) and lipids (malondialdehyde (MDA)). There was a statistically significant increase in AGE fluorescence in plasma of colorectal cancer patients compared to AGE fluorescence in the control group (p < 0.0001). AOPP and MDA concentrations were also considerably higher in the plasma of the study group than in the control group (p < 0.0001, p < 0.0001) (Figure 4).

ROC Analysis
ROC analysis was performed in the study to assess the diagnostic value of oxidative stress biomarkers in the diagnostics of colorectal cancer (Tables 2-4). We demonstrated that all determined redox parameters differentiate CRC patients from healthy controls to a large extent. We also proved that oxidative stress biomarkers are useful in the differential diagnosis of CRC patients. Particular attention should be paid to CAT for which AUC in the presence of lymph node metastasis was 0.7450 with cut-off value >61.61 nmol H2O2/min/100 mg protein, 65.00% sensitivity and 66.67% specificity (Table 3, Figure 4). We also showed a very high diagnostic value of MDA determination (AUC 0.7457, p = 0.0118) in differentiating the group of patients with CRC at stage pT2 of tumour invasion from patients with stage pT3 CRC. The cut-off value was <9.361 mg/100 mg protein with sensitivity of 72.00% and specificity of 71.43% (Table 4, Figure 5).

ROC Analysis
ROC analysis was performed in the study to assess the diagnostic value of oxidative stress biomarkers in the diagnostics of colorectal cancer (Tables 2-4). We demonstrated that all determined redox parameters differentiate CRC patients from healthy controls to a large extent. We also proved that oxidative stress biomarkers are useful in the differential diagnosis of CRC patients. Particular attention should be paid to CAT for which AUC in the presence of lymph node metastasis was 0.7450 with cut-off value >61.61 nmol H 2 O 2 /min/100 mg protein, 65.00% sensitivity and 66.67% specificity (Table 3, Figure 4). We also showed a very high diagnostic value of MDA determination (AUC 0.7457, p = 0.0118) in differentiating the group of patients with CRC at stage pT2 of tumour invasion from patients with stage pT3 CRC. The cut-off value was <9.361 mg/100 mg protein with sensitivity of 72.00% and specificity of 71.43% (Table 4, Figure 5).

Correlations
The results of all statistically significant correlations are presented in Table 5. Interestingly, we observed a positive correlation between MDA and CEA level as well as between MDA and depth of tumour invasion (pT) in CRC patients. Interestingly, the concentration of MDA remarkably positively correlated with CRP levels. We also demonstrated a negative correlation between AGE and UA and

Correlations
The results of all statistically significant correlations are presented in Table 5. Interestingly, we observed a positive correlation between MDA and CEA level as well as between MDA and depth of tumour invasion (pT) in CRC patients. Interestingly, the concentration of MDA remarkably positively correlated with CRP levels. We also demonstrated a negative correlation between AGE and UA and the number of eosinophils as well as between GPx and CEA. Moreover, there were also statistically negative correlations between AGE and neutrophils, SOD and monocytes, and TOS and basophiles.

Discussion
Our study is the first to assess the diagnostic utility of redox biomarkers in patients with colorectal cancer. We have demonstrated disturbances in enzymatic and non-enzymatic antioxidants as well as enhanced oxidation of proteins and lipids in serum/plasma of CRC subjects. Moreover, we assume that catalase and malondialdehyde-a product of lipid peroxidation-may be potential non-invasive biomarkers differentiating tumour invasion depth or indicating the occurrence of lymph node metastasis.
One of the most important mechanisms associated with carcinogenesis is oxidative stress. This phenomenon is defined as alterations in gene expression, cell metabolism, and cell homeostasis caused by overproduction of ROS and disturbances in antioxidant mechanisms [31]. Antioxidant enzymes form our first line of defence against oxidative damage. A critical ROS-scavenging enzyme is superoxide dismutase (SOD) which converts superoxide anion to hydrogen peroxide and molecular oxygen. In our study, SOD activity was significantly higher in patients with colorectal cancer, which suggests an adaptive response to increased formation of ROS and RNS. Similarly, in patients with CRC, we observed a considerably higher concentration of uric acid, the most important plasma non-enzymatic antioxidant. It is well known that strengthening the antioxidant barrier is the basic mechanism protecting the body against enhanced production of free radicals and associated oxidative stress. Indeed, in CRC subjects, ROS overproduction occurs through alterations in mitochondrial function/energy metabolism as well as enzyme inactivation during the tumourigenesis [32]. However, the activity/concentration of other enzymatic (CAT, GR, GPx) and non-enzymatic (GSH) antioxidants was significantly lower in patients with CRC compared to healthy people. Therefore, antioxidant reserves could be exhausted in CRC subjects, which predisposes them to redox imbalance as well as oxidative damage. It has been demonstrated that colon tumour tissue produces particularly large amounts of hydrogen peroxide (H 2 O 2 ) [33]. Although H 2 O 2 is not a free radical, it can pass through the cell membrane and-in the presence of transition metal ions (e.g. Cu 2+ and Fe 2+ )-transform into a hydroxyl radical [10]. Hydroxyl radical has very high biological reactivity and is destroys macromolecules (proteins, lipids, DNA/RNA) as well as cell structures. However, H 2 O 2 can also react with superoxide anion in Haber-Weiss reaction, which further boosts the formation of hydroxyl radicals [8,34]. Therefore, it is not surprising that we have observed decreased activity of GPx and CAT, the enzymes responsible for the elimination of hydrogen peroxide. Moreover, it can be assumed that free radicals, such as superoxide anion, hydroxyl, alkoxyl, and peroxyl radicals, could inactivate antioxidant enzymes through its structural modification and finally lead to decreasing the activity of CAT, GPx, and GR [35].
Enzymatic and non-enzymatic antioxidants closely interact with each other. Therefore, it is difficult to deduce the redox status based on the evaluation of individual antioxidants alone. Consequently, we were the first to evaluate the biomarkers characterizing the resultant antioxidant capacity (TAC, FRAP, TOS, OSI) in colorectal cancer patients. Indeed, TAC and FRAP reflect the total content of antioxidants, while TOS is the sum of all oxidants contained in the sample [25,26,28]. In our work, we found lower TAC and FRAP levels, which indicates weakened antioxidant barrier resulting from excessive free radical production (↑TOS in CRC patients). Moreover, oxidative stress index (OSI) was significantly higher in colorectal cancer patients. It is well known that OSI provides more information about the interactions between oxidants and ROS-scavengers [34]. Therefore, enhanced OSI level in CRC patients suggests that oxidation processes outweigh the antioxidant protection. Due to the shift of redox balance to the oxidation side, patients with CRC are particularly sensitive to oxidative stress and oxidative damage. Indeed, the colon intestinal mucosa is constantly exposed to pro-oxidative and carcinogenic factors derived from the diet as well as bacteria [36]. Human gut microflora contains up to 500 bacteria species that can generate ROS and RNS [37]. Moreover, a high-fat/high-carbohydrate diet can induce systemic oxidative stress [38]. It is believed that inflammation and oxidative stress associated with metabolic disturbances constitute an environment conducive to the development of CRC [39]. Thus, it is a not surprising increase in the CRC incidence in patients with obesity, insulin resistance as well as metabolic syndrome [40,41].
ROS overproduction increases with cancer progression and results in lipid peroxidation and protein oxidative damage [42]. Malondialdehyde (MDA)-the final product of lipoperoxidation-is a highly electrophilic molecule that reacts with cell nucleophiles to form MDA adducts and MDA oligomers. Furthermore, malondialdehyde reacts with several nucleic acids forming deoxyguanosine (dG), deoxyadenosine (dA), and deoxycytidine (dC) adducts [43]. It was shown that MDA-DNA oxidation products have pro-mutagenic properties and induce mutations in oncogenes/tumour suppressor genes in human tumours [44]. In our study, MDA level was significantly higher in colorectal cancer patients compared to the healthy controls. Among the many lipid peroxidation products, such as MDA, 4-hydroxy-2-nonenal (4-HNE), 4-hydroxyhexenal (4-HHE), and 8-isoprostanes (8-isoP), MDA is the one with the highest mutagenicity and carcinogenicity [43]. However, increased formation of ROS/RNS in CRC patients also leads to enhanced oxidative damage to proteins and polypeptides. Protein oxidation can lead to ROS-induced modifications of amino acid residues/prosthetic groups of enzymes, as well as fragmentation/aggregation of proteins in the cell [45]. The most frequently evaluated biomarkers of oxidative protein damage are advanced oxidation protein products (AOPPs) and advanced glycation end products (AGEs). AOPPs are dityrosine containing crosslinked protein products. It was demonstrated that AOPPs trigger oxidative ignition of monocytes, neutrophils, and T lymphocytes, resulting in a highly up regulation of dendritic cells [46]. Under these conditions, the NfkB signalling pathway is also activated, which not only increases the production of pro-inflammatory cytokines, but also enhances free radical formation [31]. AGEs have a very similar structure to AOPPs. Therefore, both AGEs and AOPPs stimulate proinflammatory response (by interacting with receptor for advanced glycation end products, RAGE) and induce transendothelial chemotaxis of human monocytes [31]. Therefore, AGEs and AOPPs enhance the release of tumour necrosis factor α (TNF-α), interleukin-1 (IL-1) and interleukin-6 (IL-6). AGEs can also increase thrombogenicity and permeability of endothelial cells, i.e., factors that mark the participation of advanced glycation end products in cancer proliferation and/or cancer progression [46]. In this study, all the assessed protein modification markers (AGE, AOPP) were significantly higher in colorectal cancer patients as compared to the control group. To date, no data was found about AOPP and AGE level in plasma/serum samples of colorectal cancer patients. However, increased oxidative protein damage has been observed in gastric cancer [47], thyroid cancer [48], breast cancer [49], and oral squamous cell carcinoma [50], which correlates with cancer progression and tumour metastasis. The fact is not surprising as oxidatively modified proteins tend to form aggregates resistant to degradation by proteolytic enzymes. This promotes the accumulation of altered proteins in cells and leads to a gradual loss of their structure and biological function [34]. Indeed, disturbances in protein breakdown processes are involved in the development of progressive cancer [47]. Therefore, should antioxidants be used in patients with CRC? Recent studies indicate that supplementation with antioxidants can both inhibit as well as intensify tumour initiation/progression [51][52][53][54]. Interestingly, as demonstrated in the epidemiological studies, an increasing amount of antioxidants in the diet generally does not improve the prognosis of cancer patients [51,53]. In addition, it has been proven that oxidative stress increases in metastasizing cells as well as reduces distant metastasis, which opens new possibilities in the treatment of colorectal cancer patients [51]. However, there is a need for further research in this area in both the in vitro model as well as clinical trials.
Despite the available diagnostic methods for colorectal cancer detection, an ideal non-invasive biomarker of CRC has not been discovered yet [55,56]. The most commonly evaluated laboratory indicator of CRC is carcinoembryonic antigen (CEA) discovered over 50 years ago [57]. Although CEA increased in about 60% to 85% colorectal cancer patients, its specificity was 90% but sensitivity only 40 to 75%. Moreover, the content of carcinoembryonic antigen rarely increased in stage I CRC and appeared to be unable to differentiate benign lesions with malignant polyps [57]. Therefore, carcinoembryonic antigen cannot be used as a standard biomarker in colorectal cancer diagnosis and is not recommended for screening tests. This is also confirmed by the results of our study, in which CEA remained within reference values range: 72% of CRC patients. Thus, further development of non-invasive diagnostic methods is essential as it would enable early diagnosis at pre-and postoperative stages and offer a wider selection of most suitable therapeutic methods and post-treatment follow-up for a given patient.
Considering that oxidative stress is the cause of numerous human diseases, redox biomarkers are becoming increasingly common in the clinical practice. The diagnostic usefulness of redox indicators has been demonstrated in genetic diseases (e.g. Down syndrome, ataxia-telangiectasia) [58,59], metabolic disorders (obesity, insulin resistance, type 1 and 2 diabetes) [12,60], inflammatory diseases (chronic kidney disease and non-alcoholic fatty liver disease) [13,61], as well as in some types of cancer, such as gastric cancer, ovarian cancer, and melanoma. In the present study, we were the first to demonstrate the usefulness of redox biomarkers in the diagnosis and/or assessment of CRC severity. We observed that all of the determined redox parameters significantly distinguish CRC patients from the healthy controls (with very high sensitivity and specificity). Furthermore, we also demonstrated the usefulness of redox biomarkers in differential diagnosis of CRC patients. Indeed, ROC analysis showed that CAT clearly indicates the occurrence of lymph node metastasis or its lack in these patients. Also noteworthy is the positive correlation between CAT activity and CA 19-9 level. It is well known that cancer features such as nodal status (pN) and depth of primary tumour infiltration (pT) are the most important prognostic factors for local recurrence and distant metastasis in cancer patients [62]. However, the only reliable test to assess and confirm the cancer stage is the histopathological analysis of resected tumour and the surrounding tissues. Therefore, the discovery of new biomarkers to be assayed in serum/plasma samples may be helpful in pre-operative diagnosis and would enable non-invasive evaluation of cancer advancement, thereby facilitating the choice of appropriate treatment, and improvement of CRC patients' survival rate. Additionally, we demonstrated a very high diagnostic value of MDA determination in colorectal cancer diagnosis. In a group of CRC patients, the evaluation of plasma MDA allows to distinguish those with depth of tumour invasion at stage pT2 from patients with stage pT3 (AUC 0.7133, p = 0.037). Thus, our results suggest that lipid peroxidation in CRC patients is enhanced with the increase of depth of tumour invasion. The differences between both groups may be associated with high cytotoxic potential of MDA that reveals intensified operation as a carcinogenic agent and promoter of CRC development and progression [47]. It is probable that MDA cytotoxicity increases along with cancer advancement, which may indicate that MDA can be engaged in cancer growth and connected with depth of colon wall infiltration. We concluded that MDA may be a useful marker in CRC advancement evaluation. Our observations are also confirmed by a positive correlation between MDA and CEA/CRP levels, as well as between MDA and depth of tumour invasion in CRC patients.
Finally, it is also worth considering certain limitations of our experiment. The evaluated redox biomarkers are not specific to colon cancer alone, so they can only be used after the elimination of other oxidative stress-related disorders. Additionally, the activity/concentration of antioxidants and the concentration of oxidation modification products were evaluated only in serum/plasma samples, which offers our results only an approximate value. However, the undoubted advantage of our work is a carefully selected group of CRC/control patients without any accompanying diseases as well as the fact that blood CAT and MDA can be used in non-invasive CRC diagnostics. Our experiment is also a starting point for further clinical trials assessing the diagnostic utility of redox biomarkers in a larger population of colorectal cancer patients.

Conclusions
Colorectal cancer is associated with enzymatic and non-enzymatic redox imbalance as well as increased oxidative damage to proteins and lipids as compared to healthy controls. Catalase and malondialdehyde can be potential non-invasive biomarkers indicating tumour invasion depth or presence of lymph node metastasis.