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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cell. Infect. Microbiol.</journal-id>
<journal-title>Frontiers in Cellular and Infection Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cell. Infect. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">2235-2988</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fcimb.2021.712105</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Cellular and Infection Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Chronic Hepatitis C Pathogenesis: Immune Response in the Liver Microenvironment and Peripheral Compartment</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Rios</surname>
<given-names>Daniela Alejandra</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1386431"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Casciato</surname>
<given-names>Paola Cecilia</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1410335"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Caldirola</surname>
<given-names>Mar&#xed;a Soledad</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/81587"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Gaillard</surname>
<given-names>Mar&#xed;a Isabel</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/227867"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Giadans</surname>
<given-names>Cecilia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1410434"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ameigeiras</surname>
<given-names>Beatriz</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>De Matteo</surname>
<given-names>Elena Noem&#xed;</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Preciado</surname>
<given-names>Mar&#xed;a Victoria</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/772401"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Valva</surname>
<given-names>Pamela</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1116046"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Laboratory of Molecular Biology, Multidisciplinary Institute for Investigation in Pediatric Pathologies (IMIPP), CONICET-GCBA, Pathology Division, Ricardo Guti&#xe9;rrez Children&#x2019;s Hospital</institution>, <addr-line>Buenos Aires</addr-line>, <country>Argentina</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Liver Unit, Italian&#x2019;s Hospital of Buenos Aires</institution>, <addr-line>Buenos Aires</addr-line>, <country>Argentina</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Immunology Unit, Multidisciplinary Institute for Investigation in Pediatric Pathologies (IMIPP), CONICET-GCBA, Ricardo Guti&#xe9;rrez Children&#x2019;s Hospital</institution>, <addr-line>Buenos Aires</addr-line>, <country>Argentina</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Liver Unit, Ramos Mej&#xed;a Hospital</institution>, <addr-line>Buenos Aires</addr-line>, <country>Argentina</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Tonya Michelle Colpitts, Moderna Therapeutics, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Song Yang, Capital Medical University, China; David Hawman, National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH), United States</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Pamela Valva, <email xlink:href="mailto:valvapamela@conicet.gov.ar">valvapamela@conicet.gov.ar</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Virus and Host, a section of the journal Frontiers in Cellular and Infection Microbiology</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>03</day>
<month>08</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>11</volume>
<elocation-id>712105</elocation-id>
<history>
<date date-type="received">
<day>19</day>
<month>05</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>07</day>
<month>07</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Rios, Casciato, Caldirola, Gaillard, Giadans, Ameigeiras, De Matteo, Preciado and Valva</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Rios, Casciato, Caldirola, Gaillard, Giadans, Ameigeiras, De Matteo, Preciado and Valva</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Chronic hepatitis C (CHC) pathogenic mechanisms as well as the participation of the immune response in the generation of liver damage are still a topic of interest. Here, we evaluated immune cell populations and cytokines in the liver and peripheral blood (PB) to elucidate their role in CHC pathogenesis. B, CTL, Th, Treg, Th1, Th17, and NK cell localization and frequency were evaluated on liver biopsies by immunohistochemistry, while frequency, differentiation, and functional status on PB were evaluated by flow cytometry. TNF-&#x3b1;, IL-23, IFN-<italic>&#x3b3;</italic>, IL-1&#x3b2;, IL-6, IL-8, IL-17A, IL-21, IL-10, and TGF-&#x3b2; expression levels were quantified in fresh liver biopsy by RT-qPCR and in plasma by CBA/ELISA. Liver CTL and Th1 at the lobular area inversely correlated with viral load (r&#xa0;=&#xa0;&#x2212;0.469, <italic>p</italic> =0.003 and r = &#x2212;0.384, <italic>p</italic> = 0.040). Treg correlated with CTL and Th1 at the lobular area (r = 0.784, <italic>p</italic> &lt; 0.0001; r = 0.436, <italic>p</italic> = 0.013). Th17 correlated with hepatic IL-8 (r = 0.52, <italic>p</italic> &lt; 0.05), and both were higher in advanced fibrosis cases (Th17 <italic>p</italic> = 0.0312, IL-8 <italic>p</italic> = 0.009). Hepatic cytokines were higher in severe hepatitis cases (IL-1&#x3b2; <italic>p</italic> = 0.026, IL-23 <italic>p</italic> = 0.031, IL-8 <italic>p</italic> = 0.002, TGF-&#x3b2;, <italic>p</italic>= 0.037). Peripheral NK (<italic>p</italic> = 0.008) and NK <italic>dim</italic> (<italic>p</italic> = 0.018) were diminished, while NK <italic>bright</italic> (<italic>p</italic> = 0.025) was elevated in patients <italic>vs.</italic> donors. Na&#xef;ve Th (<italic>p</italic> = 0.011) and CTL (<italic>p</italic> = 0.0007) were decreased, while activated Th (<italic>p</italic>&#xa0;= 0.0007) and CTL (<italic>p</italic> = 0.0003) were increased. IFN-<italic>&#x3b3;</italic> production and degranulation activity in NK and CTL were normal. Peripheral cytokines showed an altered profile <italic>vs.</italic> donors, particularly elevated IL-6 (<italic>p</italic> = 0.008) and TGF-&#x3b2; (<italic>p</italic> = 0.041). Total hepatic CTLs favored damage. Treg could not prevent fibrogenesis triggered by Th17 and IL-8. Peripheral T-lymphocyte differentiation stage shift, elevated cytokine levels and NK-cell count decrease would contribute to global disease.</p>
</abstract>
<kwd-group>
<kwd>immunopathogenesis</kwd>
<kwd>HCV: Hepatitis C virus</kwd>
<kwd>chronic liver disease</kwd>
<kwd>inflammatory liver infiltrate</kwd>
<kwd>Treg: regulatory T lymphocytes</kwd>
<kwd>Th17</kwd>
<kwd>peripheral blood</kwd>
</kwd-group>
<counts>
<fig-count count="7"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="62"/>
<page-count count="18"/>
<word-count count="10269"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Chronic hepatitis C (CHC) is a progressive disease that may result in cirrhosis and/or hepatocellular carcinoma; therefore liver failure because of hepatitis C virus (HCV) infection is one of the most common reasons for liver transplantation (<xref ref-type="bibr" rid="B27">Manns et&#xa0;al., 2017</xref>).</p>
<p>CHC still represents a major global health problem affecting approximately 71 million people worldwide (<xref ref-type="bibr" rid="B39">Polaris Observatory HCV Collaborators, 2017</xref>); however, the real burden of HCV infection displays great uncertainty since most infected people remain undiagnosed and untreated. In this context one of the major current challenges is to carry out screening programs to assess CHC in the context of an asymptomatic infection (<xref ref-type="bibr" rid="B19">Hollande et&#xa0;al., 2020</xref>). Accordingly, the WHO goal of eliminating HCV by 2030 is based on three main actions: strengthening and increasing outreach screening; increasing access to treatment; and improving prevention (<xref ref-type="bibr" rid="B19">Hollande et&#xa0;al., 2020</xref>).</p>
<p>Given that there is no protective vaccine approved, the highly effective direct-acting antiviral agents (DAAs) are of great importance since they reach a dramatically high-sustained virological response (SVR) rate. Nevertheless, they cannot fully eradicate hepatocellular carcinoma risk, especially in HCV-cured patients with advanced liver disease, suggesting an accumulation of irreversible damages to the liver during long-term HCV infection (<xref ref-type="bibr" rid="B40">Reig et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B16">Goto et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B28">Massoud, 2020</xref>; <xref ref-type="bibr" rid="B43">Sangiovanni et&#xa0;al., 2020</xref>). Therefore, knowledge of the CHC pathogenic mechanisms as well as of the participation of the immune response in the generation of liver damage (<xref ref-type="bibr" rid="B52">Tang et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B27">Manns et&#xa0;al., 2017</xref>) is still a topic of interest.</p>
<p>It is well known that HCV poses a constant challenge to liver homeostasis, causing stress and inflammation (<xref ref-type="bibr" rid="B16">Goto et&#xa0;al., 2020</xref>). The liver microenvironment is extremely complex with numerous immune cell populations that, along with the cytokines they produce, play a central role in viral elimination; thus, the interplay between virus and host immune response may influence infection outcome (<xref ref-type="bibr" rid="B29">Mengshol et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B55">Valva et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B41">Rios et&#xa0;al., 2017</xref>). Remarkably, in the chronic stage the role of the immune cells becomes more complex since their functionality alteration would contribute to liver damage (<xref ref-type="bibr" rid="B20">Jenne and Kubes, 2013</xref>). However, the results in this regard are controversial, and the underlying mechanism by which various populations would be involved is still under discussion.</p>
<p>Natural killer (NK) cells, major cellular components of the antiviral innate immune system, display an important role in CHC pathogenesis. NK cells could be classified into two different subsets: NK <italic>dim</italic> cells are more cytolytic in nature, whereas NK <italic>bright</italic> cells usually have a predominant cytokine-producing phenotype (<xref ref-type="bibr" rid="B10">Cooper et&#xa0;al., 2001</xref>). These cells would exert a dual role in the pathogenesis: they could increase inflammation as a consequence of the elimination of infected hepatocytes, and they would also be involved in the regulation of the fibrogenic process (<xref ref-type="bibr" rid="B29">Mengshol et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B13">Fasbender et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B32">Njiomegnie et&#xa0;al., 2020</xref>).</p>
<p>T cells display a crucial role in determining spontaneous resolution <italic>versus</italic> virus persistence during acute infection. On one hand, cytotoxic T lymphocytes (CTL, CD8+ T cells) are essential effectors for the control of HCV infection since they participate in the elimination of infected cells by releasing cytotoxic granules and the expression of cell death-inducing receptor ligands. They also inhibit viral replication through non-cytolytic mechanisms, such as IFN-<italic>
<italic>&#x3b3;</italic>
</italic> and TNF-<italic>&#x3b1;</italic> secretion. However, it is postulated that in the chronic stage HCV-specific CTLs would be functionally impaired with respect to IFN-<italic>
<italic>&#x3b3;</italic>
</italic> production, proliferation, cytotoxicity, and degranulation potential (<xref ref-type="bibr" rid="B58">Wedemeyer et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B31">Neumann-Haefelin and Thimme, 2013</xref>; <xref ref-type="bibr" rid="B18">Heim and Thimme, 2014</xref>). For its part, T helper lymphocytes (Th, CD4+ T cells) act as central regulators of the adaptive immune response through augmenting CTL response and antigen-specific B lymphocytes, although they also seem to have altered functions and decreased proliferation activity during chronicity. It is well known that Th can be induced to differentiate towards Th1, Th17, or Treg cells, with distinct phenotypes and functions, depending on the stimuli received through their TCR, as well as signals from the cytokine milieu (<xref ref-type="bibr" rid="B45">Schmitt and Ueno, 2015</xref>). Moreover, recent <italic>in vitro</italic> studies showed that these differentiation stages are not definitive, but rather flexible in response to changes that occur in the microenvironment.</p>
<p>Th1 lymphocytes, which express the transcription factor Tbet, are considered mainly pro-inflammatory since they participate in cell-mediated immune response by secreting IFN-&#x3b3;, TNF-&#x3b1;, and IL-2 that stimulate macrophages and CTL function (<xref ref-type="bibr" rid="B45">Schmitt and Ueno, 2015</xref>; <xref ref-type="bibr" rid="B12">DuPage and Bluestone, 2016</xref>), and their differentiation is promoted by IL-12 and IFN-<italic>&#x3b3;</italic>. Treg lymphocytes, expressing CD25 and Foxp3, are considered immune response and inflammation suppressors since they act on the maintenance of self-tolerance by direct cell&#x2013;cell contact mechanisms and through the secretion of anti-inflammatory cytokines such as IL-10 and TGF-<italic>&#x3b2;</italic> (<xref ref-type="bibr" rid="B26">Lu et&#xa0;al., 2017</xref>). The peripheral blood Treg counts in CHC patients are variable, (<xref ref-type="bibr" rid="B3">Barjon et&#xa0;al., 2015</xref>) but liver Tregs in CHC patients are increased in comparison to those in non-infected individuals or to those who resolved HCV infection (<xref ref-type="bibr" rid="B9">Claassen et&#xa0;al., 2010</xref>). Notably, the precise role of Tregs in liver injury control is not clearly defined, since some studies described a high Treg frequency in cases with milder fibrosis (<xref ref-type="bibr" rid="B9">Claassen et&#xa0;al., 2010</xref>), while others reported association with more severe fibrosis stages (<xref ref-type="bibr" rid="B24">Langhans et&#xa0;al., 2013</xref>). Lastly, despite their opposite functional properties, Th17 cells and Tregs share similar developmental requirements, namely, the pleiotropic cytokine TGF-<italic>&#x3b2;</italic>. The key is the concentration-dependent function of TGF-<italic>&#x3b2;</italic>; at low concentrations TGF-<italic>&#x3b2;</italic> synergizes with IL-6 and IL-21 to promote IL-23 receptor (IL-23R) expression, favoring Th17 differentiation, whereas at high concentrations, TGF-<italic>&#x3b2;</italic> represses IL-23R and favors Foxp3+ Treg cells (<xref ref-type="bibr" rid="B34">Omenetti and Pizarro, 2015</xref>). For its part, Th17 subpopulation is characterized by ROR-<italic>
<italic>&#x3b3;</italic>
</italic> expression and IL-17A/F, IL-21, and IL&#x2212;22 secretion (<xref ref-type="bibr" rid="B45">Schmitt and Ueno, 2015</xref>; <xref ref-type="bibr" rid="B12">DuPage and Bluestone, 2016</xref>), which are considered mainly pro-inflammatory since they favor the recruitment of other immune inflammatory cells. Th17 lymphocytes have been implicated in the pathogenesis of other liver pathologies of different etiologies such as alcoholic hepatitis, primary biliary cirrhosis, and chronic hepatitis B (<xref ref-type="bibr" rid="B57">Veldhoen, 2017</xref>). As the balance between Th17 and Treg cells is very important for the immune homeostasis maintenance, and its dysfunction in liver has been proved to be associated with hepatic injury and disease, the study of Th17/Treg balance in chronic HCV infection is of great interest for understanding the pathogenesis.</p>
<p>On the other hand, investigations of patient samples instead of animal models are yet needed, since it is crucial to explore different aspects of the disease in its actual context. Likewise, the study of liver biopsies is currently infrequent given that tests are usually carried out in peripheral blood, but this does not necessarily reflect what happens at the site of infection. Therefore, in this study, we evaluated cellular and immune markers that may be involved in liver damage, allowing a comprehensive liver microenvironment analysis that will contribute to understanding the possible role of the immune system in CHC pathogenesis. Moreover, the peripheral compartment was also analyzed to get an integrated picture of this pathological condition.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and Methods</title>
<sec id="s2_1">
<title>Ethics Statement</title>
<p>The ethics committees of the hospitals reviewed and approved this study, which is in accordance with the human experimentation guidelines of the institutions and with the Helsinki Declaration of 1975, as revised in 1983. Written informed consent was obtained from all patients.</p>
</sec>
<sec id="s2_2">
<title>Patients and Samples</title>
<p>Liver biopsies and concomitant peripheral blood samples were collected from 48 adult na&#xef;ve of treatment patients with CHC infection who attended the Hospital Italiano de Buenos Aires and Hospital JM. Ramos Mej&#xed;a. Liver biopsies were divided into two portions: one fragment was formalin-fixed and paraffin-embedded (FFPE) and the other was conserved in Trizol at &#x2212;70&#xb0;C. The presence of anti-HCV antibodies in serum samples and HCV RNA in plasma in at least two separate occasions confirmed CHC infection (<xref ref-type="bibr" rid="B6">2002</xref>). Patients documented no other causes of liver disease, autoimmune or metabolic disorders, hepatocellular carcinoma or co-infection with HBV and/or HIV. Alcohol consumption (men &gt;30 g/day; women &gt;20 g/day) was applied as an exclusion criteria.</p>
<p>The clinical and biochemical data from patients (age, gender, risk factor for infection, viral load, genotype, AST and ALT values) were obtained from the medical records.</p>
<p>Peripheral blood samples from 40 healthy donors [age median (min.&#x2013;max.) 40 years (27&#x2013;71); gender Male : Female 1:1.05] without any known systemic or liver disease and/or HIV, and with normal biological liver test as well as with absence of anti-HCV antibodies, were also included as uninfected controls for the flow cytometry assays.</p>
<p>
<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Table S1</bold>
</xref> shows the detailed clinical, virological, and histological features of each HCV adult patient.</p>
</sec>
<sec id="s2_3">
<title>Histological Analysis</title>
<p>Histological sections were blindly evaluated by a pathologist (ENDM). Inflammatory activity and fibrosis were assessed using the modified Knodell scoring system (Histological Activity Index, HAI) and METAVIR (<xref ref-type="bibr" rid="B53">Theise et&#xa0;al., 2012</xref>).</p>
</sec>
<sec id="s2_4">
<title>Immunohistochemical Analysis</title>
<sec id="s2_4_1">
<title>HCV Liver Staining</title>
<p>Infected hepatocytes were evidenced by immunohistochemical detection of viral NS3 protein. Epitope retrieval was performed with sodium citrate buffer (0.01&#xa0;M, pH 6) in an autoclave for 3&#xa0;min (20&#xa0;psi). Endogenous biotin was blocked with Biotin Blocking System (Avidin/Biotin Blocking Kit, Vector Laboratories Inc, Burlingame, CA, USA). The primary mouse antibody for NS3 detection (1:25, clone MMM33, Abcam, Cambridge, UK) was incubated for 1&#xa0;h at 25&#xb0;C, and staining was obtained by applying the streptavidin&#x2013;biotin peroxidase (SBP) system and substrate-chromogen reagent (Vectastain Elite ABC and DAB Substrate Kit for Peroxidase, Vector Laboratories Inc, Burlingame, CA, USA). Immunostained and total hepatocytes were counted in 20&#xa0;high-power fields (&#xd7;1,000). No labelling was observed  without NS3 primary antibody, with isotype control or on chronic HBV infected liver samples.</p>
</sec>
<sec id="s2_4_2">
<title>Characterization and Quantification of the Inflammatory Liver Infiltrate</title>
<p>Infiltrate characterization was performed using appropriate antibodies: mouse anti-CD20 (L26, VENTANA, Roche, Basel, Switzerland), rabbit anti-CD8 (SP57, VENTANA, Roche, Basel, Switzerland), rabbit anti-CD56 (MRQ-42, VENTANA, Roche, Basel, Switzerland), rabbit anti-CD4 (SP35, VENTANA, Roche, Basel, Switzerland), mouse anti-Foxp3 (236A/E7, Abcam, Cambridge, UK), mouse anti-Tbet (4B10, BD Pharmingen, San Jose, CA, USA), and goat anti-IL-17A (AF-317-NA, R&amp;D Systems, Minneapolis, MN, USA). After epitope retrieval [sodium citrate buffer (0.01&#xa0;M, pH 6) in autoclave during 5&#xa0;min (20&#xa0;psi)], sections were incubated with each primary antibody and stained by applying PolyTek HRP anti-Mouse Polymerized Imaging System (PIR080, ScyTek Laboratories, Utah, USA), ultraView&#x2122; Universal DAB (cat. 760-500, VENTANA, Roche, Basel, Switzerland) or Cell &amp; Tissue Staining Goat Kit (cat. CTS008, R&amp;D Systems, Minneapolis, MN, USA) as appropriate according to the instructions of the manufacturer. Tonsil sections were used as positive controls, and isotype controls were performed. Immunostained and total cells with lymphocyte morphology were counted in all portal tracts of the tissue section (&#xd7;400), and frequencies were calculated as positive/total of the whole specimen. Immunostained cells were also counted in 10 random fields from lobular areas, and the results were expressed as immunostained cells/field (&#xd7;400).</p>
</sec>
</sec>
<sec id="s2_5">
<title>Quantitative qRT-PCR Analysis</title>
<p>Total RNA was isolated from liver samples using Epicentre Master Pure RNA Purification kit (Illumina, San Diego, CA, USA), according to the instructions of the manufacturer. A DNAse (RQ1 RNAse-free DNAse, Promega, Madison, WI, USA) treatment in all RNA samples was performed. The cDNA was reversed transcribed from 2 &#x3bc;g of RNA, using random 6-mer oligonucleotides (5 ng/&#x3bc;l) and Superscript II RT kit (Invitrogen, Waltham, MA, USA).</p>
<p>The design and validation of TNF-&#x3b1;, IL-23, IFN-<italic>&#x3b3;</italic>, IL-1&#x3b2;, IL-6, IL-8, IL-17A, IL-21, IL-10 and TGF-<italic>&#x3b2;</italic> specific primers are described in <xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Table S2</bold>
</xref>. A 1/10 aliquot of the cDNA reaction product (50&#xa0;ng input) was used in each duplicate qPCR reactions. qPCR was performed in a final volume of 25 &#xb5;l of Fast Start Universal Sybr Green Master Mix (Roche Diagnostics GmbH, Mannheim, Germany) including 5 &#xb5;l of diluted cDNA using a StepOne real-time (Applied Biosystems, Foster City, CA, USA). The endogenous HPRT or <italic>&#x3b2;</italic>-actin genes were used as endogenous controls for sample normalization (reference gene) according to the expression level of the studied gene. The normalized transcription values were calculated by the Pfaffl Method (<xref ref-type="bibr" rid="B37">Pfaffl, 2001</xref>). Results were expressed as fold change (FC).</p>
</sec>
<sec id="s2_6">
<title>Flow Cytometric Analysis</title>
<sec id="s2_6_1">
<title>Quantification of Peripheral Lymphocyte Populations</title>
<p>B lymphocytes (CD3&#x2212;CD19+), CTL (CD3+CD8+), NK (CD3&#x2212;CD56+), and Th cell (CD3+CD4+) frequencies were assessed using anti-CD45-500 (HI30, Bioscience, San Jose, CA, USA), anti-CD3-APC (SK7, Bioscience, San Jose, CA, USA), anti-CD19-PE-Cy7 (SJ25C1, BD Bioscience, San Jose, CA, USA), anti-CD8-APC-H7 (SK1, BD Bioscience, San Jose, CA, USA), CD56-PE (N901, Beckman Coulter, Chaska, MN, USA), and anti-CD4-V450 (RPA-4, BD Bioscience, San Jose, CA, USA) on fresh heparinized blood samples. Later, NK cells were discriminated in <italic>dim</italic> and <italic>bright</italic> subpopulations according to CD56 expression level.</p>
<p>PBMCs were isolated by Ficoll-Paque (Amersham Bioscience, Buckinghamshire, UK) to assess Th subpopulations. Treg (CD4+/CD25hi/Foxp3+) cells were evaluated using Foxp3 staining kit (cat 560133, BD Pharmingen, San Jose, CA, USA), while Th1 (CD4+/IFN-<italic>&#x3b3;</italic>+) and Th17 (CD4+/IL-17A+) using Human Th1/Th2/Th17 Phenotyping Kit (cat 560751, BD Pharmingen, San Jose, CA, USA), according to the instructions of the manufacturer. Th1 and Th17 staining was performed on both basal PBMCs and anti-CD3 (0.166 ng/&#xb5;l); IL-2 (0.08 pg/&#xb5;l) stimulated PBMCs for 18&#xa0;h in the presence of Golgi-Stop<sup>&#xae;</sup> (BD Pharmingen, San Jose, CA, USA). Gating strategies are shown in <xref ref-type="supplementary-material" rid="SM2">
<bold>Supplementary Material</bold>
</xref>.</p>
<p>Data were collected on a BD FACSCantoTM II cytometer (BD Biosciences, San Jose, CA, USA) and analyzed using BD FACSDiva &#x2122; Software. The analysis was performed with the FlowJo 7.6.2, and the results were expressed as counts in percentage (%) and absolute values (number of cells/&#xb5;l) and, depending on the test, as nMFI (&#x2018;Median Fluorescence Intensity&#x2019;).</p>
</sec>
<sec id="s2_6_2">
<title>T Lymphocyte Differentiation Status Assessment</title>
<p>To define T lymphocytes differentiation status, both CTL and Th lymphocyte subsets were distinguished from CD3+CD8+ and CD3+CD4+ gate, respectively as follows: activated T lymphocytes (HLA-DR+), na&#xef;ve (N; CD45RA+CD27+), central memory (CM; CD45RA&#x2212;CD27+), effector memory (EM; CD45RA&#x2212;CD27&#x2212;) and effectors (E; CD45RA+CD27&#x2212;) were evaluated using anti-CD45RA-FITC (L48, BD Bioscience, San Jose, CA, USA), anti-CD3-APC (SK7, BD Bioscience, San Jose, CA, USA), anti-CD8-APCH7 (SK1, BD Bioscience, San Jose, CA, USA), anti-CD4-V450 (RPA-T4, BD Bioscience, San Jose, CA, USA), anti-CD27-PerCP-Cy &#x2122; 5.5 (L128, BD Bioscience, San Jose, CA, USA), and anti-HLA-DR-PE (L243, Beckman Coulter, Chaska, MN, USA). Gating strategies are shown in <xref ref-type="supplementary-material" rid="SM2">
<bold>Supplementary Material</bold>
</xref>. For each status (N, CM, EM, E, activated) the results were expressed as counts in percentage (%) in relation to the Th and the CTL.</p>
</sec>
<sec id="s2_6_3">
<title>Functional Characterization of CTLs and NK Cells</title>
<p>IFN-<italic>&#x3b3;</italic> production and degranulation activity were evaluated in both CTL and NK cells.</p>
<p>The IFN-<italic>&#x3b3;</italic>-producing CTL subset was evaluated by means of a modification of the Th17/Th1 lymphocyte assay; for this purpose, anti-CD8-APC-H7 antibody (SK1, eBioscience, San Diego, CA, USA) was added to the precast antibody cocktail. On the other hand, IFN-<italic>&#x3b3;</italic> production by NK cells was performed in a separate assay since it requires a different stimulus. Briefly, PBMCs were cultured 16&#xa0;h in supplemented medium in the absence [basal tube] or presence of rIL&#x2212;12 (10 ng/ml; eBioscience, San Diego, CA, USA), rIL&#x2212;15 (2 ng/ml; eBioscience, San Diego, CA, USA), and rIL&#x2212;18 (10 ng/ml; eBioscience, San Diego, CA, USA) [stimulated tube]. During the last 4&#xa0;h, Golgi-Stop<sup>&#xae;</sup> (BD Pharmingen, San Jose, CA, USA) was added to the cultures, and then immunostaining was performed using: anti-CD56-APC (N901, Beckman Coulter, Chaska, MN, USA), anti-CD3-PE-Cy7 (UCHT1, BD Pharmingen, San Jose, CA, USA), and anti-IFN-<italic>&#x3b3;</italic>-PE (4S.B3, BD Pharmingen, San Jose, CA, USA).</p>
<p>The degranulation activity was determined by evaluating CD107a (LAMP-1) expression in PBMCs (<xref ref-type="bibr" rid="B4">Betts et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B2">Alter et&#xa0;al., 2004</xref>). Briefly, PBMCs were cultured in 1&#xa0;ml of supplemented medium for 18&#xa0;h at 37&#xb0;C 5% CO<sub>2</sub>. Then, cell suspension was separated into four tubes: isotype tube, basal tube, NK tube, and CTL tube. In the NK tube, K562 cells (a human cell line that does not express MHC I molecules) were added as stimulus to evaluate the degranulation activity of NK cells, while in the CTL tube, anti-CD3 (0.33 &#x3bc;g/&#x3bc;l) was added as a stimulus. After 3&#xa0;h of incubation at 37&#xb0;C 5% CO<sub>2</sub>, immunostaining using anti-CD107a-PE-Cy&#x2122;5 (H4A3, BD Bioscience, San Jose, CA, USA), anti-CD56-PE (N901, Beckman Coulter, Chaska, MN, USA), anti-CD3-APC (SK7, BD Bioscience, San Jose, CA, USA), anti-D8-FITC (SK1, Biolegend, San Diego, CA USA, USA), and IgG1&#x3ba;-PE-Cy&#x2122;5 (MOPC-21, BD Bioscience, San Jose, CA, USA, for isotype control) was carried out.</p>
<p>Gating strategies are shown in <xref ref-type="supplementary-material" rid="SM2">
<bold>Supplementary Material</bold>
</xref>. The results were expressed as counts in percentage (%) and absolute values (number of cells/&#xb5;l) and as nMFI. Additionally, in both CTL and NK cell degranulation activity assays, the response extent was determined by calculating CD107a expression difference (delta) between baseline and stimulated (frequency and nMFI). Moreover, the increase in the response was also evaluated as [% response in the stimulated tube &#x2212; (% response of the basal tube)/% response of the basal tube].</p>
</sec>
<sec id="s2_6_4">
<title>Peripheral Cytokine Quantification</title>
<p>Cytokine levels (IL-6, TNF-&#x3b1;, IFN-<italic>&#x3b3;</italic>, IL-17A, IL-10, IL-8, IL-1&#x3b2;, and TGF-<italic>&#x3b2;</italic>1) were evaluated in plasma samples obtained from EDTA anticoagulated peripheral blood.</p>
<p>IL-6, TNF-&#x3b1;, IFN-<italic>&#x3b3;</italic>, IL-17A, and IL-10 were assessed using a commercial cytometric bead array (CBA) kit, the CBA Human Th1/Th2/Th17 kit (BD Bioscience, San Jose, CA, USA); IL-8 and IL-1&#x3b2; were assessed using the CBA Human Inflammatory Cytokine Kit (BD Bioscience, San Jose, CA, USA) following the instructions of the manufacturer. The standard curve and sample concentration calculation was performed with the FCAP Array software (BD Bioscience, San Jose, CA, USA); results were expressed as pg/ml.</p>
<p>On the other hand, TGF-<italic>&#xdf;</italic>1 was determined by a commercial quantitative sandwich enzyme linked immunosorbent assay (ELISA) (Quantikine,  R&amp;D Systems, Minneapolis, MN, USA) according to the instructions of the manufacturer. The calibration curve values were adjusted to a four-parameter logistic. TGF-<italic>&#xdf;</italic>1 concentration was determined from the constructed standard curve and expressed as pg/ml.</p>
</sec>
</sec>
<sec id="s2_7">
<title>Statistical Analysis</title>
<p>Statistical analysis was performed using GraphPad Prism version 5.01 (GraphPad Software Inc). To compare the means between groups, Student&#x2019;s t-test or ANOVA (Newman&#x2013;Keuls post-tests) was performed. To determine differences between groups not normally distributed, medians were compared using the Mann&#x2013;Whitney U test or Kruskal&#x2013;Wallis test (Dunn&#x2019;s post-tests). To determine the differences in variables measured in the same group under different conditions (for example, basal <italic>vs.</italic> stimulated), a paired t-test or the Wilcoxon signed range test was used, depending on whether the distribution complied with normality or not, respectively. Pearson&#x2019;s correlation coefficient was used to measure the degree of association between continuous, normally distributed variables. The degree of association between non-normally distributed variables was assessed using Spearman&#x2019;s non-parametric correlation. In all cases, Shapiro&#x2013;Wilk test was used to evaluate normal distribution. P-values &lt;0.05 were considered statistically significant. <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S3</bold>
</xref> shows the dataset analyzed during the current study.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Characterization of Liver Microenvironment</title>
<p>Three components of liver pathogenesis in CHC were considered in this manuscript: liver HCV infection, the inflammatory infiltrate, and the cytokine milieu. Clinical, virological, and histological features of the patients are described in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Clinical, virological and histological patient features.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" colspan="2" align="left"/>
<th valign="top" align="center">Chronic HCV Patients (n = 48)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Age (years)</bold> median (min.&#x2013;max.)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">54 (32&#x2013;72)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Gender</bold>
</td>
<td valign="top" align="left">Male: Female</td>
<td valign="top" align="center">1:1</td>
</tr>
<tr>
<td valign="top" rowspan="7" align="left">
<bold>Risk factor for HCV infection %</bold> (n/total)</td>
<td valign="top" align="left">Drug abuse</td>
<td valign="top" align="center">18.75 (9/48)</td>
</tr>
<tr>
<td valign="top" align="left">Transfusion</td>
<td valign="top" align="center">16.68 (8/48)</td>
</tr>
<tr>
<td valign="top" align="left">Sexual</td>
<td valign="top" align="center">8.33 (4/48)</td>
</tr>
<tr>
<td valign="top" align="left">Hemodialysis</td>
<td valign="top" align="center">2.08 (1/48)</td>
</tr>
<tr>
<td valign="top" align="left">Occupational</td>
<td valign="top" align="center">2.08 (1/48)</td>
</tr>
<tr>
<td valign="top" align="left">Tattoo</td>
<td valign="top" align="center">2.08 (1/48)</td>
</tr>
<tr>
<td valign="top" align="left">Unknown</td>
<td valign="top" align="center">50 (24/48)</td>
</tr>
<tr>
<td valign="top" rowspan="6" align="left">
<bold>Genotype %</bold> (n)</td>
<td valign="top" align="left">1a</td>
<td valign="top" align="center">41.67 (20/48)</td>
</tr>
<tr>
<td valign="top" align="left">1b</td>
<td valign="top" align="center">41.67 (20/48)</td>
</tr>
<tr>
<td valign="top" align="left">2</td>
<td valign="top" align="center">6.25 (3/48)</td>
</tr>
<tr>
<td valign="top" align="left">3a</td>
<td valign="top" align="center">6.25 (3/48)</td>
</tr>
<tr>
<td valign="top" align="left">4</td>
<td valign="top" align="center">2.08 (1/48)</td>
</tr>
<tr>
<td valign="top" align="left">ND</td>
<td valign="top" align="center">2.08 (1/48)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Viral load (IU/ml)</bold> median</td>
<td valign="top" align="left"/>
<td valign="top" align="center">1160000</td>
</tr>
<tr>
<td valign="top" align="left">(min.&#x2013;max.)</td>
<td valign="top" align="left"/>
<td valign="top" align="center">(343&#x2013;82,400,000)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>ALT (IU/L)</bold> median (min.&#x2013;max.)</td>
<td valign="top" align="left"/>
<td valign="top" align="center">70 (10&#x2013;330).</td>
</tr>
<tr>
<td valign="top" align="left">% (n/total)</td>
<td valign="top" align="left">Elevated</td>
<td valign="top" align="center">80.85 (38/47)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>AST (IU/L)</bold> median (min.&#x2013;max.)</td>
<td valign="top" align="left"/>
<td valign="top" align="center">56 (14&#x2013;296)</td>
</tr>
<tr>
<td valign="top" align="left">% (n/total)</td>
<td valign="top" align="left">Elevated</td>
<td valign="top" align="center">63.83 (30/47)</td>
</tr>
<tr>
<td valign="top" rowspan="4" align="left">
<bold>Hepatitis<sup>1</sup>%</bold> (n/total)</td>
<td valign="top" align="left">Minimal</td>
<td valign="top" align="center">2.27 (1/44)</td>
</tr>
<tr>
<td valign="top" align="left">Mild</td>
<td valign="top" align="center">18.18 (8/44)</td>
</tr>
<tr>
<td valign="top" align="left">Moderate</td>
<td valign="top" align="center">59.09 (26/44)</td>
</tr>
<tr>
<td valign="top" align="left">Severe</td>
<td valign="top" align="center">20.46 (9/44)</td>
</tr>
<tr>
<td valign="top" rowspan="6" align="left">
<bold>Fibrosis stage<sup>2</sup>%</bold> (n/total)</td>
<td valign="top" align="left">F0</td>
<td valign="top" align="center">4.55 (2/44)</td>
</tr>
<tr>
<td valign="top" align="left">F1</td>
<td valign="top" align="center">31.82 (14/44)</td>
</tr>
<tr>
<td valign="top" align="left">F2</td>
<td valign="top" align="center">29.54 (13/44)</td>
</tr>
<tr>
<td valign="top" align="left">F3</td>
<td valign="top" align="center">25.00 (11/44)</td>
</tr>
<tr>
<td valign="top" align="left">F4</td>
<td valign="top" align="center">9.09 (4/44)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Advanced Fibrosis (&#x2265;3)</bold>
</td>
<td valign="top" align="center">34.09 (15/44)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ND, not determined; ALT, alanine aminotransferase; AST, aspartate aminotransferase; normal ALT and AST levels for adult patients were &#x2264;40 and &#x2264;42 IU/L, respectively when testing was done at 37&#xb0;C. <sup>1</sup>Hepatitis classification: minimal (HAI&#x2264;&#xa0;3), mild (HAI 4&#x2013;6), moderate (HAI 7&#x2013;12) and severe hepatitis (HAI&gt;12). <sup>2</sup>Fibrosis according to METAVIR. Four patients have a non-evaluable liver biopsy and therefore no information is available about liver damage.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>HCV-NS3 Detection in Liver Biopsies</title>
<p>A cytoplasmic, mainly perinuclear, NS3 immunostaining with a granular pattern of variable intensity was observed. Some cases displayed both portal&#x2013;periportal (P&#x2013;P) and lobular arrangement, while others showed only P&#x2013;P distribution (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). The infected hepatocyte frequency was variable among cases [median: 0.052 (min.&#x2013;max: 0.005&#x2013;0.338)]. It did not display an association with liver damage (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S1A</bold>
</xref>), and no correlation with viral load or transaminases was detected (NS3 <italic>vs.</italic> viral load: r = &#x2212;0.059, <italic>p</italic> = 0.765; NS3 <italic>vs.</italic> AST: r = 0.096, <italic>p</italic>&#xa0;= 0.602; NS3 <italic>vs.</italic> ALT: r = &#x2212;0.011, <italic>p</italic> = 0.952).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Immunostaining of NS3 and liver infiltrating lymphocyte populations on formalin-fixed paraffin embedded liver biopsies. Representative images of NS3+ hepatocytes <bold>(A, B)</bold>, CD20+ <bold>(C, D)</bold>, CD8+ <bold>(E, F)</bold>, CD56+ <bold>(G, H)</bold>, CD4+ <bold>(I, J)</bold>, Tbet+ <bold>(K, L)</bold>, Foxp3+ <bold>(M, N)</bold> and IL-17A+ <bold>(O, P)</bold> lymphocytes. Portal&#x2013;periportal tract <bold>(A, C, E, G, I, K, M, O)</bold> and lobular area <bold>(B, D, F, H, J, L, N, P)</bold>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-712105-g001.tif"/>
</fig>
</sec>
<sec id="s3_3">
<title>Analysis of the Inflammatory Infiltrate</title>
<p>Immunolabeling of B lymphocytes (CD20+), CTL (CD8+), NK cells (CD56+), Th lymphocytes (CD4+), and Th1 (Tbet+), Treg (Foxp3+) and Th17 (IL-17A+) at P&#x2013;P areas was observed with scattered lymphocytes in the lobular region (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Concerning P&#x2013;P cell frequency, Th lymphocytes were predominant followed by CTL, B lymphocytes, and NK cells. When analyzing Th subset frequency, Th17 showed the lowest counts (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S1B</bold>
</xref>). On the other hand, there was predominance of CTL and Th1 at the lobular area, together with absence of B lymphocytes and NK cells (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S1B</bold>
</xref>).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Quantification of liver cell populations.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Cell population</th>
<th valign="top" align="center">Portal&#x2013;periportal area</th>
<th valign="top" align="center">Lobular area</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Th</bold>
</td>
<td valign="top" align="center">0.66 (0.04&#x2013;0.85)</td>
<td valign="top" align="center">0.20 (0&#x2013;5.78)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>CTL</bold>
</td>
<td valign="top" align="center">0.48 (0.15&#x2013;0.75)</td>
<td valign="top" align="center">2.00 (0&#x2013;15.00)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>B</bold>
</td>
<td valign="top" align="center">0.25 (0&#x2013;0.62)</td>
<td valign="top" align="center">0 (0&#x2013;2.20)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>NK</bold>
</td>
<td valign="top" align="center">0.01 (0&#x2013;0.09)</td>
<td valign="top" align="center">0 (0&#x2013;0.50)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Th1</bold>
</td>
<td valign="top" align="center">0.09 (0&#x2013;0.39)</td>
<td valign="top" align="center">1.20 (0&#x2013;12.57)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Treg</bold>
</td>
<td valign="top" align="center">0.11 (0&#x2013;0.29)</td>
<td valign="top" align="center">0.30 (0&#x2013;1.90)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Th17</bold>
</td>
<td valign="top" align="center">0.07 (0.01&#x2013;0.26)</td>
<td valign="top" align="center">0.20 (0&#x2013;1.50)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Results are expressed as: a) portal&#x2013;periportal frequencies: immunostained/total cells; b)&#xa0;lobular frequencies: immunostained cells/field (&#xd7;400).</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>CTL and Th1 cells are well known components of the antiviral immune response. In this cohort despite their lobular predominance, they did not correlate with the number of infected hepatocytes, but they disclosed a negative correlation with viral load (r = &#x2212;0.469, <italic>p</italic> = 0.003 and r = &#x2212;0.384, <italic>p</italic> = 0.040; respectively) (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). Since viral load mirrored HCV liver replication, this could indirectly suggest CTL and Th1 immune control of the liver process.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>
<bold>(A)</bold> Relationship between viral load and frequency of both lobular CTL and Th1. Correlation between viral load and the frequency of lobular CTL (a) and Th1 (b). <bold>(B)</bold> Relationship between Treg lymphocytes with both CTL and Th1. Correlation between the frequency of Treg with CTL (a) and Th1 (b) at portal-periportal area. Correlation between the frequency of Treg with CTL (c) and Th1 (d) at lobular area. Spearman&#x2019;s nonparametric correlation was used to compare these data sets.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-712105-g002.tif"/>
</fig>
<p>When evaluating the interrelation among different hepatic immune cells, Treg depicted a positive correlation with CTL and Th1 at the P&#x2013;P area (CTL <italic>vs.</italic> Treg: r = 0.438, <italic>p</italic> = 0.005; Th1 <italic>vs.</italic> Treg: r = 0.497, <italic>p</italic> = 0.004) and lobular area (CTL <italic>vs.</italic> Treg: r = 0.784, <italic>p</italic> &lt; 0.0001; Th1 <italic>vs.</italic> Treg: r = 0.436, <italic>p</italic> = 0.013) (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>), which would indicate that Treg may control effector lymphocytes (CTL and Th1).</p>
<p>Concerning liver damage (<xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3A&#x2013;J</bold>
</xref>), P&#x2013;P Th17 was the only lymphocyte subset that seemed to be related to liver damage; in fact Th17 lymphocytes were associated with advanced fibrosis (<italic>p</italic> = 0.0312) (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3E</bold>
</xref>). Total P&#x2013;P lymphocytes correlated with inflammatory activity (r = 0.376, <italic>p</italic> = 0.014) (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S1C-a</bold>
</xref>) and depicted an augmented profile in severe fibrosis (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3F</bold>
</xref>) which was consistent with the association between inflammatory activity and fibrosis severity (<italic>p</italic> = 0.04) (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S1 C-b</bold>
</xref>). Besides Th17 and CTL correlated with transaminase levels (CTL <italic>vs.</italic> AST: r = 0.412, <italic>p</italic> = 0.008; CTL <italic>vs.</italic> ALT: r = 0.403, <italic>p</italic> = 0.009; Th17 <italic>vs.</italic> AST: r = 0.594, <italic>p</italic> &lt; 0.0001) (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S1D</bold>
</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Relationship between intrahepatic infiltrate and liver damage. Portal&#x2013;periportal cell population frequencies related to hepatitis <bold>(A&#x2013;C)</bold> and fibrosis severity <bold>(D&#x2013;F)</bold>. Lobular cell population frequencies related to hepatitis <bold>(G, H)</bold> and fibrosis severity <bold>(I, J)</bold>. Th, CTL, B lymphocytes and NK cell <bold>(A, D, G, I)</bold>; Th subpopulation <bold>(B, E, H, J)</bold>; and total portal lymphocytes <bold>(C, F)</bold>. MM, minimal&#x2013;mild; MS, moderate&#x2013;severe hepatitis. Advanced fibrosis (F&#x2265;3) according to METAVIR. The results are depicted in box plots. Horizontal lines within boxes indicate medians. Horizontal lines outside the boxes represent the 5 and 95 percentiles. Mean is indicated as +. Mann&#x2013;Whitney U test was used to compare all data sets, except for portal&#x2013;periportal CTL, B, Th1, and Treg cells <italic>vs.</italic> hepatitis severity, and CTL and B cell <italic>vs.</italic> fibrosis severity for which Student&#x2019;s t-test was applied.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-712105-g003.tif"/>
</fig>
</sec>
<sec id="s3_4">
<title>Quantification of Liver Cytokine Expression</title>
<p>Pro-inflammatory cytokines TNF-&#x3b1;, IL-23, IFN-<italic>&#x3b3;</italic>, IL-1&#x3b2;, IL-6, IL-8, IL-17A, and IL-21, as well as anti-inflammatory IL-10 and TGF-<italic>&#x3b2;</italic> expression were quantified in fresh liver biopsy samples. The relative expression of different cytokines was variable (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A-a</bold>
</xref>). Interestingly, IL-17A was undetectable in most cases which agreed with Th17 low frequency evaluated by immunohistochemistry.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Liver cytokine expression level. <bold>(A)</bold> Heat map of liver cytokine expression level (a). Each row corresponds to the cytokine indicated at the top, and each column represents one case. The data are normalized, and the results are expressed as a Z-score (Xi-/SD), which is assigned a color scale that goes from black (lowest values) to yellow (highest values). The white boxes correspond to the cases without data. Correlation matrix of cytokines (b) and correlation matrix between infiltrate cell populations and intrahepatic cytokine levels (c). (b, c) are schematic representation: the numbers inside the boxes indicate the Spearman correlation coefficients (r) only for those pairs of cytokines that show statistical significance (<italic>p</italic> &lt; 0.05). The squares inside the boxes graphically represent the value of r: the light blue color indicates r values between 0 and 1 (positive correlation), and the red color indicates values between &#x2212;1 and 0 (negative correlation), while its size increases as r increases towards values close to |1|. <bold>-</bold>P, portal&#x2013;periportal; -L, lobular. Panel <bold>(B)</bold> Relationship between intrahepatic cytokine levels and liver damage. Expression levels of intrahepatic cytokines in relation to hepatitis (a) and fibrosis (b) severity. MM, minimal&#x2013;mild; MS, moderate&#x2013;severe hepatitis. Advanced fibrosis (F&#x2265;3) according to METAVIR. The results are depicted in box plots. Horizontal lines within boxes indicate medians. Horizontal lines outside the boxes represent the 5 and 95 percentiles. Mean is indicated as +. FC, fold change. Mann&#x2013;Whitney U test was used to compare all data sets, except for IL-1&#x3b2; and IL-23 <italic>vs.</italic> hepatitis severity for which Student&#x2019;s t-test was applied.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-712105-g004.tif"/>
</fig>
<p>Two correlation matrixes were performed, the first one linked cytokine to each other (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4A, B</bold>
</xref>) and the second one related each cytokine with each immune cell population (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4 A-c</bold>
</xref>). Interestingly, among the cytokines two clear groups were delineated: Group 1 (G1), included IFN-<italic>&#x3b3;</italic>, TNF-&#x3b1;, IL-1&#x3b2;, IL-8, and TGF-<italic>&#x3b2;</italic>, and Group 2 (G2) included IL-6, IL-21, and IL-10. IL-23 presented a particular behavior given that it correlated with TGF-<italic>&#x3b2;</italic>, IL-1&#x3b2;, and IFN-<italic>&#x3b3;</italic> from G1, and IL-10 from G2. When considering the ability of the hepatic milieu to condition the permanence of the Th subpopulations or to influence their differentiation and plasticity, TGF-<italic>&#x3b2;</italic>, IL-21, IL-&#x3b2;, and IL-6 were quantitatively related to Th17 frequency. These cytokines had an opposite behavior, namely TGF-<italic>&#x3b2;</italic> and IL-1&#x3b2; depicted direct correlation with Th17, while IL-6 and IL-21 an inverse one (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A-c</bold>
</xref>). Of note Tregs showed no relationship with TGF-<italic>&#x3b2;</italic>.</p>
<p>Regarding the relation between cytokines and their producer cells, IFN-<italic>&#x3b3;</italic> and TNF-&#x3b1; showed no correlation with CTL, Th1, or NK cells, while Treg did not correlate with TGF-<italic>&#x3b2;</italic> and IL-10 expression. Strikingly, IL-21 was inversely correlated with Th17 frequency; nevertheless, it should be considered that other cell subsets could also produce IL-21. On the other hand, it ought to be noted that the inverse correlation of IL-21 with Th, CTL, B, and Treg frequency as well as the correlation of IL-10 with Th and CTL could indicate a negative effect of these cytokines on the inflammatory infiltrate (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A-c</bold>
</xref>). Finally, infected hepatocyte frequency inversely correlated with IL-10 and IL-21 expression levels (r = &#x2212;0.495, <italic>p</italic> = 0.006; r = &#x2212;0.446, <italic>p</italic> = 0.023, respectively) indicating their possible role on viral control (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S1E</bold>
</xref>).</p>
<p>When analyzing the relation of cytokines and liver damage, a trend to higher values in those cases with more severe hepatitis was observed, but it turned out to be significant only for IL-1&#x3b2; (<italic>p</italic> = 0.026), IL-23 (<italic>p</italic> = 0.031), IL-8 (<italic>p</italic> = 0.002), and TGF-&#x3b2; (<italic>p</italic> = 0.037); while concerning fibrosis severity only IL-8 was associated with advanced fibrosis (<italic>p</italic> = 0.009) (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>). Moreover, IL-8 also displayed a positive correlation with P&#x2013;P and lobular Th17 frequency (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A-c</bold>
</xref>), which, as mentioned above, depicted an association with fibrosis severity too (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3E</bold>
</xref>). Finally, TGF-<italic>&#x3b2;</italic>, TNF-&#x3b1;, IL-1&#x3b2;, and IL-8 displayed positive correlations with transaminase levels [AST <italic>vs</italic>, a) TGF-&#x3b2;: r = 0.554, <italic>p</italic> = 0.0002; b) TNF-&#x3b1;: r = 0.492, <italic>p</italic> = 0.001; c) IL-1&#x3b2;: r = 0.444, <italic>p</italic> = 0.005; d) IL-8: r = 0.439, <italic>p</italic> = 0.006; and ALT <italic>vs</italic>: e)&#xa0;TGF-&#x3b2;: r = 0.318, <italic>p</italic> = 0.043; f) TNF-&#x3b1;: r = 0.355, <italic>p</italic> = 0.020].</p>
</sec>
<sec id="s3_5">
<title>Evaluation of the Peripheral Immune Response</title>
<sec id="s3_5_1">
<title>Quantification of Peripheral Lymphocytes Frequency</title>
<p>The comparative analysis of T and B lymphocyte populations did not reveal significant differences between donors and patients (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>) and depicted the same frequency proportion as described for portal hepatic infiltrate (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S2A</bold>
</xref>). In contrast, NK cells showed a significant decrease in absolute values (<italic>p</italic> = 0.008) in patients accompanied by a decreased in NK <italic>dim</italic> (<italic>p</italic> = 0.02 percentage and <italic>p</italic> = 0.018 absolute value) along with an increase in NK <italic>bright</italic> (<italic>p</italic> = 0.025 percentage value) (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Quantification of peripheral cell populations.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Cell population</th>
<th valign="top" colspan="2" align="center">Percentage value (%)</th>
<th valign="top" rowspan="2" align="center">
<italic>p-</italic>value</th>
<th valign="top" colspan="2" align="center">Absolute value (cells/&#xb5;l)</th>
<th valign="top" rowspan="2" align="center">
<italic>p-</italic>value</th>
</tr>
<tr>
<th valign="top" align="center">Donor</th>
<th valign="top" align="center">HCV</th>
<th valign="top" align="center">Donor</th>
<th valign="top" align="center">HCV</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Th</bold>
</td>
<td valign="top" align="center">46.00</td>
<td valign="top" align="center">44.50</td>
<td valign="top" rowspan="2" align="center">0.606</td>
<td valign="top" align="center">940.4</td>
<td valign="top" align="center">822.8</td>
<td valign="top" rowspan="2" align="center">0.185</td>
</tr>
<tr>
<td valign="top" align="center">(29.00&#x2013;51.0)</td>
<td valign="top" align="center">(18.00&#x2013;68.00)</td>
<td valign="top" align="center">(576.0&#x2013;2144.0)</td>
<td valign="top" align="center">(187.9&#x2013;2747.0)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>CTL</bold>
</td>
<td valign="top" align="center">26.00</td>
<td valign="top" align="center">26.00</td>
<td valign="top" rowspan="2" align="center">0.957</td>
<td valign="top" align="center">664.6</td>
<td valign="top" align="center">537.6</td>
<td valign="top" rowspan="2" align="center">0.101</td>
</tr>
<tr>
<td valign="top" align="center">(19.00&#x2013;37.00)</td>
<td valign="top" align="center">(11.00&#x2013;63.00)</td>
<td valign="top" align="center">(332.8&#x2013;1169.0)</td>
<td valign="top" align="center">(181.2&#x2013;1017.0)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>B</bold>
</td>
<td valign="top" align="center">10.50</td>
<td valign="top" align="center">12.00</td>
<td valign="top" rowspan="2" align="center">0.148</td>
<td valign="top" align="center">237.0</td>
<td valign="top" align="center">255.8</td>
<td valign="top" rowspan="2" align="center">0.531</td>
</tr>
<tr>
<td valign="top" align="center">(7.00&#x2013;16.80)</td>
<td valign="top" align="center">(1.30&#x2013;31.20)</td>
<td valign="top" align="center">(115.2&#x2013;506.5)</td>
<td valign="top" align="center">(27.81&#x2013;601.7)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>NK</bold>
</td>
<td valign="top" align="center">13.55</td>
<td valign="top" align="center">9.00</td>
<td valign="top" rowspan="2" align="center">0.056</td>
<td valign="top" align="center">346.0</td>
<td valign="top" align="center">201.0</td>
<td valign="top" rowspan="2" align="center">0.008</td>
</tr>
<tr>
<td valign="top" align="center">(5.60&#x2013;32.00)</td>
<td valign="top" align="center">(1.30&#x2013;31.00)</td>
<td valign="top" align="center">(94.60&#x2013;755.0)</td>
<td valign="top" align="center">(35.02&#x2013;626.6)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>NK <italic>dim</italic>
</bold>
</td>
<td valign="top" align="center">97.80</td>
<td valign="top" align="center">91.30</td>
<td valign="top" rowspan="2" align="center">0.025</td>
<td valign="top" align="center">335.1</td>
<td valign="top" align="center">129.0</td>
<td valign="top" rowspan="2" align="center">0.018</td>
</tr>
<tr>
<td valign="top" align="center">(89.30&#x2013;99.10)</td>
<td valign="top" align="center">(69.60&#x2013;97.50)</td>
<td valign="top" align="center">(84.50&#x2013;480.8)</td>
<td valign="top" align="center">(52.47&#x2013;376.0)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>NK <italic>bright</italic>
</bold>
</td>
<td valign="top" align="center">2.20</td>
<td valign="top" align="center">8.00</td>
<td valign="top" rowspan="2" align="center">0.025</td>
<td valign="top" align="center">9.80</td>
<td valign="top" align="center">15.45</td>
<td valign="top" rowspan="2" align="center">0.165</td>
</tr>
<tr>
<td valign="top" align="center">(0.90&#x2013;10.70)</td>
<td valign="top" align="center">(3.10&#x2013;31.10)</td>
<td valign="top" align="center">(2.40&#x2013;24.30)</td>
<td valign="top" align="center">(2.84&#x2013;43.07)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Th1</bold>
</td>
<td valign="top" align="center">3.50</td>
<td valign="top" align="center">3.75</td>
<td valign="top" rowspan="2" align="center">0.380</td>
<td valign="top" align="center">33.97</td>
<td valign="top" align="center">28.85</td>
<td valign="top" rowspan="2" align="center">0.586</td>
</tr>
<tr>
<td valign="top" align="center">(0.39&#x2013;17.80)</td>
<td valign="top" align="center">(0.77&#x2013;15.30)</td>
<td valign="top" align="center">(2.23&#x2013;136.4)</td>
<td valign="top" align="center">(5.57&#x2013;167.0)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Treg</bold>
</td>
<td valign="top" align="center">4.84</td>
<td valign="top" align="center">4.45</td>
<td valign="top" rowspan="2" align="center">0.687</td>
<td valign="top" align="center">48.50</td>
<td valign="top" align="center">35.60</td>
<td valign="top" rowspan="2" align="center">0.064</td>
</tr>
<tr>
<td valign="top" align="center">(1.65&#x2013;8.33)</td>
<td valign="top" align="center">(1.82&#x2013;9.79)</td>
<td valign="top" align="center">(30.34&#x2013;131.2)</td>
<td valign="top" align="center">(14.40&#x2013;181.6)</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Th17</bold>
</td>
<td valign="top" align="center">0.51</td>
<td valign="top" align="center">0.38</td>
<td valign="top" rowspan="2" align="center">0.078</td>
<td valign="top" align="center">4.12</td>
<td valign="top" align="center">3.28</td>
<td valign="top" rowspan="2" align="center">0.128</td>
</tr>
<tr>
<td valign="top" align="center">(0.12&#x2013;1.90)</td>
<td valign="top" align="center">(0.03&#x2013;0.94)</td>
<td valign="top" align="center">(1.60&#x2013;19.99)</td>
<td valign="top" align="center">(0.32&#x2013;13.83)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>The results are expressed as median (min.-max.).</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>As to liver damage, none of the peripheral lymphocyte population percentages disclosed differences with respect to hepatitis or fibrosis severity (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S2B</bold>
</xref>). The same was observed in the analysis of absolute and nMFI values.</p>
</sec>
<sec id="s3_5_2">
<title>Peripheral T Lymphocyte Differentiation and Functional Characterization of NK Cells and CTLs</title>
<p>The distribution of na&#xef;ve, central memory, effector memory, effectors and activated CTL and Th lymphocytes was determined. As shown in <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>, a decrease in the frequency of both na&#xef;ve Th and CTL (<italic>p</italic> = 0.011 and <italic>p</italic> = 0.0007, respectively) and an increase of activated lymphocytes (<italic>p</italic> = 0.0007 and <italic>p</italic> = 0.0003, respectively) were observed in CHC patients. In turn, a trend to higher frequency of effector memory CTL (<italic>p</italic> = 0.07) and Th (<italic>p</italic> = 0.009) was demonstrated (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>T lymphocyte differentiation and functional characterization of NK cells. <bold>(A)</bold> Comparison of lymphocytes differentiation stages between donors and patients. Th (a) and CTL (b). Results are expressed as percentage values. N, na&#xef;ve; CM, central memory; EM, effector memory; E, effector; A, activated. Student&#x2019;s t-test was used to compare all data sets except for na&#xef;ve Th and activated Th, and effector CTL for which Mann&#x2013;Whitney U test was applied. Panel <bold>(B)</bold> IFN-<italic>&#x3b3;</italic> production capacity (a, b) and degranulation activity of NK cells (c&#x2013;h). IFN-<italic>&#x3b3;</italic> production of NK cells in patients and donors (a, b). Percentage values (a), and intensity of expression (b). CD107a expression in total NK cells in percentage values (c&#x2013;e) and in intensity of expression (f&#x2013;h). Comparison of the response between basal conditions and before the stimulus per case in donors (c and f) and in patients (d, g). Comparison of basal CD107a expression in total NK cells, stimulated and magnitude of response (delta) between donor <italic>vs.</italic> patient (e and h). Results are expressed as percentage values (c&#x2013;e) and intensity of expression (f&#x2013;h). D, donor. When it corresponds, the results are depicted in box plots. Horizontal lines within boxes indicate medians. Horizontal lines outside the boxes represent the 5 and 95 percentiles. Mean is indicated as +. Mann&#x2013;Whitney U test (a, b, e, h) and Wilcoxon test (c, d, f, g) were used to compare all data sets. <italic>The analysis of absolute values displayed similar results to the percentage values, but it is not shown to simplify their visualization</italic>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-712105-g005.tif"/>
</fig>
<p>With regard to NK functionality, IFN-<italic>&#x3b3;</italic> production was similar between patients and donors [45.50% (min.&#x2013;max: 5.74&#x2013;91.00) <italic>vs.</italic> 54.0% (min.&#x2013;max: 5.38&#x2013;96.90), respectively], and the same applied to NK subsets, namely NK <italic>dim</italic> [patients: 37.55% (min.&#x2013;max.: 5.09&#x2013;90.59%) <italic>vs.</italic> donors: 51.50% (min.&#x2013;max: 4.75&#x2013;97.40%)], and NK <italic>bright</italic> [patients: 87.65% (min.&#x2013;max: 25.50&#x2013;98.10%) <italic>vs.</italic> donors: 91.90% (min.&#x2013;max: 37.30&#x2013;98.40%)] (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B-a</bold>
</xref>). The nMFI analysis demonstrated similar cytokine production capacity in patients and donors both in total NK and in its subpopulations (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B-b</bold>
</xref>). The NK degranulation activity showed a similar significant response against stimulus in patients and donors (percentage value: donor <italic>p</italic> = 0.016, HCV <italic>p</italic> = 0.0005; nMFI: donor <italic>p</italic> = 0.001, HCV: <italic>p</italic> = 0.001) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B-c, d, f, g</bold>
</xref>). The median of frequency increase was 1.49-fold (min.&#x2013;max: 0.05&#x2013;37.10) in patients <italic>vs.</italic> 0.84 (min.&#x2013;max: 0.50&#x2013;11, 70) in donors, while the median increase in CD107a expression intensity (nMFI) was 0.85 times (min.&#x2212;max: 0.0&#x2013;4.70) in patients <italic>vs.</italic> 1.0 times (min.&#x2013;max: 0.20&#x2013;7.0) in donors. The response magnitude (delta) in the NK degranulation activity assay was similar between patients and donors (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B-e, h</bold>
</xref>
<bold>)</bold>. In summary, these observations indicated that NK functionality was not impaired in HCV infection, since IFN-<italic>&#x3b3;</italic> production and degranulation activity were not altered.</p>
<p>In relation to liver damage, NK cells IFN-<italic>&#x3b3;</italic> production and degranulation activity showed no association with either fibrosis or hepatitis (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S3</bold>
</xref>). Nonetheless, the lowest basal degranulation percentages were found in those cases with advanced fibrosis, but, when considering the nMFI, an inverse profile was observed, with significantly higher values in NK (<italic>p</italic> = 0.016) and NK <italic>dim</italic> (<italic>p</italic> = 0.021), conceivably as a compensating mechanism (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S3B-j, k</bold>
</xref>).</p>
<p>Concerning CTL functionality, IFN-<italic>&#x3b3;</italic> production showed no differences between patients and donors [HCV: 8.17% (min.&#x2212;max.: 5.66&#x2212;18.30) <italic>vs.</italic> donors of 10.10% (min.&#x2212;max: 1.65&#x2212;18.60) in percentage value; HCV: 9.58 (7.77&#x2013;18.71) <italic>vs.</italic> donors: 11.75 (5.49&#x2013;18.96) in nMFI (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6A, B</bold>
</xref>)]. Related to degranulation activity, the basal expression of CD107a showed no significant differences between patients and donors (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6E, H</bold>
</xref>), while the stimulus triggered a significant degranulation increase in both groups (percentage value: HCV, <italic>p</italic> = 0.0005; donors, <italic>p</italic> = 0.014; nMFI: HCV, <italic>p</italic> = 0.0005; donor, <italic>p</italic> = 0.006) (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6C, D, F, G</bold>
</xref>). The median increase in percentage was of 0.60-fold (min.&#x2212;max: 0.15&#x2212;4.00) in patients and 0.26-fold (min.&#x2212;max.: &#x2212;0.12 to 397) in the donors, and in nMFI the median increase was 1.20-fold (min.&#x2212;max: 0.10&#x2013;3.0) in patients and 0.70-fold (min.&#x2212;max.: &#x2212;0.10 to 2.20) in the donors. The response magnitude (delta) in percentage values was significantly elevated in patients (<italic>p</italic> = 0.004) (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6E</bold>
</xref>). These results would indicate that CTL functionality was not impaired in HCV infection since IFN-<italic>&#x3b3;</italic> production and the ability to degranulate in response to the stimulus were not altered, but HCV patient demonstrated a greater magnitude of degranulation activity in response to the stimulus.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Functional characterization of CTLs. IFN-<italic>&#x3b3;</italic> production capacity <bold>(A, B)</bold> and degranulation activity of CTLs <bold>(C&#x2013;H</bold>). IFN-<italic>&#x3b3;</italic> production of CTLs in patients and donors <bold>(A, B)</bold>. Percentage values <bold>(A)</bold> and intensity of expression <bold>(B)</bold>. CD107a expression in CTLs in percentage values <bold>(C&#x2013;E)</bold> and in intensity of expression <bold>(F&#x2013;H)</bold>. Comparison of the response between basal conditions and before the stimulus per case in donors <bold>(C, F)</bold> and in patients <bold>(D, G)</bold>. Comparison of CD107a basal expression in CTLs, stimulated and magnitude of response (delta) between donor <italic>vs.</italic> patient <bold>(E, H)</bold>. Results are expressed as percentage values <bold>(C&#x2013;E)</bold> and intensity of expression <bold>(F&#x2013;H)</bold>. D, donor. When it corresponds, the results are depicted in box plots. Horizontal lines within boxes indicate medians. Horizontal lines outside the boxes represent the 5 and 95 percentiles. Mean is indicated as +. Student&#x2019;s t-test <bold>(A, E)</bold>, Wilcoxon test <bold>(C, D, G)</bold>, paired t-test <bold>(F)</bold> and Mann&#x2013;Whitney U test <bold>(B, H)</bold> were used to compare different data sets. <italic>The analysis of absolute values displayed similar results to the percentage values, but it is not shown to simplify their visualization</italic>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-712105-g006.tif"/>
</fig>
<p>Finally, in relation to liver damage, CTL IFN-<italic>&#x3b3;</italic> production in response to the stimulus did not show any relationship (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S4A</bold>
</xref>). Regarding degranulation activity in response to the stimulus, no differences were observed in the percentage of CTL CD107a+ according to fibrosis severity (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S4B-c</bold>
</xref>), but nMFI was significantly high in cases with more severe fibrosis (<italic>p</italic> = 0.008) (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S4B-d</bold>
</xref>). In turn, delta response was greater both in percentage and nMFI values in patients with higher severity of fibrosis (<italic>p</italic> = 0.016; <italic>p</italic> = 0.008, respectively) (<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S4B-c, d</bold>
</xref>).</p>
</sec>
</sec>
<sec id="s3_6">
<title>Quantification of Peripheral Cytokines</title>
<p>The heat map (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A-a</bold>
</xref>) pointed out that cytokine levels showed a large dispersion among patients. When compared with donors, three cytokine groups may be distinguished: a) those with values below the detection limit in donors and most patients (IL-1&#x3b2; and IL-17A) (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A-b</bold>
</xref>); b) those with values below the detection limit in most donors, but increased in patients (IL-10 and IL-8) (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A-c</bold>
</xref>); and c) those with values above the detection limit in both groups with a particular trend to higher values in patients (TNF-&#x3b1;, IFN-<italic>&#x3b3;</italic>, IL-6, and TGF-<italic>&#x3b2;</italic>) (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A-d</bold>
</xref>). In the last group it is important to highlight that IL-6 and TGF-&#x3b2; increased significantly (<italic>p</italic> = 0.008 and <italic>p</italic> = 0.041; respectively).</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Peripheral cytokine level. <bold>(A)</bold> Heat map of peripheral cytokine expression levels (a) and comparison of circulating cytokine levels between patients and donors (b&#x2013;d). (a) Each row corresponds to the cytokine indicated at the top, and each column represents one case. The data are normalized, and the results are expressed as a Z-score (Xi-/SD), which is assigned a color scale from black (lowest values) to yellow (highest values). The white boxes correspond to the cases without data. (b&#x2013;d) Cytokine levels in patients and donors: IL-1&#x3b2; and IL-17A (b), IL-10 and IL-8 (c), and TNF-&#x3b1;, IFN-<italic>&#x3b3;</italic>, IL-6, and TGF-<italic>&#x3b2;</italic> (d). D donor. Results are plotted on dot diagrams, the middle horizontal line indicates the mean, and the outer horizontal lines represent the SD. Mann&#x2013;Whitney U test was used to compare data sets. <bold>(B)</bold> Relationship between circulating cytokine levels and liver damage. Circulating levels of cytokines in relation to hepatitis (a&#x2013;d) and fibrosis (e&#x2013;h) severity. MM, minimal&#x2013;mild; MS, moderate&#x2013;severe hepatitis. Advanced fibrosis (F&#x2265;3) according to METAVIR. The results are depicted in box plots. Horizontal lines within boxes indicate medians. Horizontal lines outside the boxes represent the 5 and 95 percentiles. Mean is indicated as +. Mann&#x2013;Whitney U test was used to compare data sets.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fcimb-11-712105-g007.tif"/>
</fig>
<p>Finally, cytokine levels did not display correlation between intrahepatic and peripheral compartments. In relation to liver damage, plasma IL-8 showed a trend of association with hepatitis severity (<italic>p</italic> = 0.056) (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7B-a)</bold>
</xref>. On the other hand, circulating TGF-<italic>&#x3b2;</italic> higher levels were observed in those cases with lower fibrosis severity (<italic>p</italic> = 0.040) (<xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7B-h</bold>
</xref>).</p>
<p>
<xref ref-type="supplementary-material" rid="SM3">
<bold>Supplementary Figure S5</bold>
</xref> showed a schematic representation of the results.</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>The immune response has a dual role during the course of HCV infection, so in this manuscript we intended to evaluate the potential interplay between the virus and the liver immune microenvironment in CHC. Both intrahepatic and peripheral immune response components were analyzed in relation to virological and histological parameters to assess its possible role in the pathogenesis. To determine if the inflammatory process was localized or if immunological alterations occurred at the systemic level, the results of the evaluated parameters in both compartments were integrated.</p>
<p>We demonstrated that most liver infection cases displayed NS3 expression, but in a very low number of hepatocytes. The scarce number of HCV+ hepatocytes observed reinforced previous findings of our group (<xref ref-type="bibr" rid="B55">Valva et&#xa0;al., 2014</xref>) and agreed with other authors that also observed low frequencies of infected hepatocytes using different labeling techniques (<xref ref-type="bibr" rid="B44">Sansonno et&#xa0;al., 2004</xref>; <xref ref-type="bibr" rid="B25">Liang et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B59">Wieland et&#xa0;al., 2014</xref>). According to this observation, liver parenchymal affection seemed not to be very extensive since a high proportion of the hepatocytes remained uninfected. In agreement with Liang et&#xa0;al., it could be hypothesized that the immune response participates in liver infection control (<xref ref-type="bibr" rid="B25">Liang et&#xa0;al., 2009</xref>). In this regard, our previous findings support this assumption since pediatric patients who showed a less preponderant hepatic immune response than adults displayed the highest frequencies of infected hepatocytes (<xref ref-type="bibr" rid="B55">Valva et&#xa0;al., 2014</xref>). Consistent with this hypothesis, CTL and Th1 lymphocytes, central components of the antiviral immune response (<xref ref-type="bibr" rid="B29">Mengshol et&#xa0;al., 2007</xref>), displayed a lobular predominance and negative correlation with viral load, which could indicate a possible control of liver viral replication. However, a lack of correlation between liver CTL frequency and the number of infected hepatocytes was observed which may have two different explanations. First, considering that viral replication is a dynamic process, the detection of viral antigens indicates that the cells are infected but does not take into account how many viral particles are contained in each cell. Second, it could be possible that CTLs are not all virus-specific, so they could also eliminate uninfected hepatocytes, which is known as &#x2018;bystander killing&#x2019; (<xref ref-type="bibr" rid="B49">Spengler and Nattermann, 2007</xref>). The whole CTL population might influence liver damage generation, which could be suggested by the positive correlation between CTL frequency and transaminase levels. Therefore, although the immune response participates in viral replication control, it seems to be also implicated in liver damage generation. In the present cohort, intrahepatic inflammatory cytokines, especially IL-1&#x3b2;, IL-8, and TGF-&#x3b2;, presented a profile tending to higher values in cases with most severe hepatitis, together with positive correlations of TGF-&#x3b2;, TNF-&#x3b1;, IL-1&#x3b2;, and IL-8 with transaminase levels denoting the idea of the involvement of the immune response in liver damage. Furthermore, the total portal lymphocyte count, which accounts for the magnitude of the infiltrates, correlated with the inflammatory activity, which in turn showed significantly higher values in cases with advanced fibrosis. Consequently, these observations all together support the idea that the immune response is involved in generating liver damage and particularly that the inflammation would contribute to liver fibrogenesis.</p>
<p>Regarding the possible role of each studied lymphocyte population in relation to liver damage, only Th17 lymphocytes seemed to be involved in CHC pathogenesis. In spite of its known inflammatory potential and its participation in various autoimmune and liver pathologies (<xref ref-type="bibr" rid="B35">Paquissi, 2017</xref>; <xref ref-type="bibr" rid="B57">Veldhoen, 2017</xref>), the role of Th17 lymphocytes in CHC pathogenesis has not yet been fully clarified. In this series we described a low frequency of intrahepatic Th17 lymphocytes compared to the other Th subpopulations evaluated; however, portal Th17 lymphocytes were associated with biochemical and histological parameters of liver damage, namely plasma AST levels and increased severity of fibrosis. Therefore, although Th17 cells were less frequent than the others, just their presence at the right time of the development of the chronic process might mediate mechanisms that may lead to or contribute to fibrogenesis. Additionally, intrahepatic Th17 lymphocyte frequency correlated with IL-8 liver expression, and both of them displayed an association with fibrosis severity, suggesting possible involvement in liver fibrogenesis which was also described in <italic>in vitro</italic> studies by other authors. In this sense, it has been described that the main function of both IL-17A and IL-17F is the recruitment of neutrophils and macrophages (<xref ref-type="bibr" rid="B57">Veldhoen, 2017</xref>). It has been demonstrated <italic>in vitro</italic> that these cytokines are capable of inducing the secretion of chemokines such as CCL7 and CXCL8 (IL-8) (<xref ref-type="bibr" rid="B57">Veldhoen, 2017</xref>). In turn, IL-8 has been widely related to various liver pathologies, and it is postulated that, in addition to promoting the recruitment of neutrophils, it would contribute to the activation of stellate cells, and consequently to liver fibrogenesis (<xref ref-type="bibr" rid="B62">Zimmermann et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B60">Xu et&#xa0;al., 2014</xref>). Regarding the role of Th17 cells at the peripheral compartment, they were also underrepresented; likewise IL-17 was undetectable in most studied samples as described by other authors (<xref ref-type="bibr" rid="B14">Foster et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B47">Sousa et&#xa0;al., 2012</xref>). Besides, their peripheral frequency did not display an association with liver damage parameters, supporting the idea of a localized contribution to the pathogenesis.</p>
<p>As previously mentioned, Th17 lymphocytes represents the Treg counterpart since they share differentiation process mediators and these Th subsets could be also repolarized (<xref ref-type="bibr" rid="B12">DuPage and Bluestone, 2016</xref>). In the studied cohort, TGF-&#x3b2;, IL-21, IL-6, and IL-1&#x3b2; combined with hepatic expression favor a Th17 scenario, although the individual role of each cytokine as well as their effect on the Treg lymphocytes remains to be elucidated. This is important since the hepatic cytokine milieu could generate a bias towards a certain lymphocyte profile, which in turn favors or controls liver damage, hence delineating the course of the disease.</p>
<p>In relation to Treg lymphocytes, although its role is still controversial (<xref ref-type="bibr" rid="B9">Claassen et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B51">Sturm et&#xa0;al., 2010</xref>), their significant presence, especially at portal tracts, in CHC liver biopsies could denote their involvement in immune response modulation. The correlations between Treg with both CTL and Th1, at portal and lobular areas, could suggest that there could be an increase recruitment or differentiation towards a Treg profile induced by the inflammatory state established in the liver; their presence could favor the control of effector lymphocytes (CTL and Th1). In this sense, the lack of association between CTL and Th1 with hepatitis or fibrosis severity could be interpreted as a consequence of Treg modulation by inhibiting Th1 and CTL actions and in turn preventing liver damage generation. Further, supporting this theory, the negative correlations between hepatic IL-10 expression and both portal Th and lobular CTL would denote their participation in the control of inflammation (<xref ref-type="bibr" rid="B3">Barjon et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B12">DuPage and Bluestone, 2016</xref>). Interestingly, this modulation is not observed in the peripheral blood compartment, reinforcing the idea of an action that occurred at the infection site but not in a generalized manner.</p>
<p>In a comprehensive approach of the liver microenvironment, it is important to consider the interplay between intrahepatic cytokines and the hepatic producer lymphocyte populations. First, the absence of a quantitative relationship between IFN-<italic>
<italic>&#x3b3;</italic>
</italic> or TNF-&#x3b1; expression levels and the CTL or Th1 frequency could indicate that these cells may have variable activation status and consequently an uneven level of cytokine production. Furthermore, it is important to highlight that during the chronic stage of the infection, various authors have reported an exhaustion of both CTL and Th, so their functions could be compromised (<xref ref-type="bibr" rid="B22">Kroy et&#xa0;al., 2014</xref>). However, it may be also possible that the observed discrepancy is based on the fact that CTL or Th1 is not the main source of IFN-<italic>
<italic>&#x3b3;</italic>
</italic> or TNF-&#x3b1; production in the liver. In addition, the absence of correlation between IL-10 and TGF-&#x3b2; liver expression and Treg frequency could be due to diverse activation status in cases with different liver damage severity or due to the contribution of other cell types not evaluated in this study, such as macrophages and Kupffer cells (<xref ref-type="bibr" rid="B17">Hartling et&#xa0;al., 2016</xref>).</p>
<p>At last, it is interesting to discuss the intrahepatic expression of the pleiotropic cytokine IL-21, mainly produced by Th17 and Th follicular (Thf) lymphocytes (<xref ref-type="bibr" rid="B50">Spolski and Leonard, 2014</xref>). Based on peripheral blood assays, it was proposed that IL-21 in CHC would be protective since it stimulated CTL activity thereby promoting viral elimination and limiting liver damage (<xref ref-type="bibr" rid="B21">Kared et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B8">Cachem et&#xa0;al., 2017</xref>). However, there are no previous studies evaluating intrahepatic IL-21 in CHC. In this cohort an inverse relationship between IL-21 liver expression and frequency of infected hepatocytes was described, which would support the hypothesis of the protective role of IL-21. In turn, IL-21 showed negative correlations with most of the evaluated lymphocyte populations, namely B lymphocytes, Th, CTL, Treg, and Th17 indicating that it participated in some way by limiting inflammation. Likewise, IL-10 would also participate in infection control given its inverse correlation with infected hepatocytes, although the underlying mechanism is not clear from the global analysis of our results.</p>
<p>Even though CHC is mainly a liver disease, adult patients have also been reported to present extrahepatic manifestations, which could be a consequence of immunological disorders. Advanced CHC could be accompanied by the presence of cryoglobulins that cause renal, dermatological, hematological, and rheumatic complications (<xref ref-type="bibr" rid="B52">Tang et&#xa0;al., 2016</xref>). Interestingly, in the peripheral blood assays performed in this series, no differences in T and B lymphocyte counts were observed between patients and non-infected donors, which would indicate at first glance that the infection did not alter the distribution of lymphoid populations. However, the ability of the virus to infect lymphocytes (<xref ref-type="bibr" rid="B15">Gismondi et&#xa0;al., 2013</xref>) and the persistent antigenic stimulation might cause alterations in T lymphocyte differentiation status (<xref ref-type="bibr" rid="B23">Kuniholm et&#xa0;al., 2014</xref>). In this sense, a decrease in both Th and CTL na&#xef;ve lymphocytes and an increase in EM phenotype and activated lymphocytes (DR+) were described in our cohort. Yet, if it is considered that the number of peripheral HCV-specific lymphocytes is extremely low (<xref ref-type="bibr" rid="B1">Alanio et&#xa0;al., 2015</xref>), this alteration in the distribution could be a consequence of a non-specific activation. Hence, in accordance with Alanio et&#xa0;al., one plausible explanation could be that peripheral lymphocytes would have a lower threshold for TCR activation due to HCV persistent stimulation which generates hyperactivation of non-HCV specific na&#xef;ve lymphocytes (<xref ref-type="bibr" rid="B1">Alanio et&#xa0;al., 2015</xref>). These alterations would have implications in the immune response not only against HCV, but also against other pathogens or vaccines (<xref ref-type="bibr" rid="B7">Burke Schinkel et&#xa0;al., 2016</xref>) and could even be related to the presence of extrahepatic manifestations associated with chronic HCV infection (<xref ref-type="bibr" rid="B1">Alanio et&#xa0;al., 2015</xref>). To reinforce activated peripheral status observed, the evaluation of circulating cytokines in this series showed an altered profile compared to non-infected donors, with an increase in both pro- and anti-inflammatory cytokines that could also condition the establishment of an adequate immune response, even against other stimuli. Although peripheral immune response seemed to be altered, neither lymphocyte population frequency nor cytokine levels displayed an association with liver damage parameters. The only exception was the association of TGF-&#x3b2; with less severe fibrosis stages in CHC patients, which was previously described by our group (<xref ref-type="bibr" rid="B54">Valva et&#xa0;al., 2011</xref>). TGF-&#x3b2; exerted fibrogenic effects on stellate cells as well as modulatory effects on the immune response. Since fibrogenesis is considered a long process and fibrosis the final picture, a higher level of TGF-<italic>&#xdf;</italic> in lower liver fibrosis stages may reflect fibrogenesis rather than fibrosis (<xref ref-type="bibr" rid="B30">Nelson et&#xa0;al., 1997</xref>; <xref ref-type="bibr" rid="B46">Soliman et&#xa0;al., 2010</xref>).</p>
<p>To deepen understanding of the peripheral CTL role, given that many authors have described a dysfunctional IFN-<italic>
<italic>&#x3b3;</italic>
</italic> production in HCV-specific CTLs (<xref ref-type="bibr" rid="B48">Spangenberg et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B36">Penna et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B42">Saha et&#xa0;al., 2013</xref>), IFN-<italic>
<italic>&#x3b3;</italic>
</italic> secretion activity was explored, but no differences between HCV patients and non-infected donors arose, and no relation with liver damage severity was evidenced, perhaps due to the assessment of the total CTL instead of the HCV-specific CTL IFN-<italic>
<italic>&#x3b3;</italic>
</italic> secretion. CTL degranulation activity did not seem to be impaired in HCV patients; moreover, the response (as the delta) was even greater in patients. In addition, this difference was accentuated in those cases with more severe fibrosis. Therefore, the inflammatory context may predispose CTLs to trigger an exaggerated degranulation activity against stimuli. The above results would indicate that CTL functionality was not impaired in HCV infection.</p>
<p>Concerning peripheral NK cells, a significant decrease of peripheral NK cells was observed in CHC samples of patients, which is in accordance with many authors (<xref ref-type="bibr" rid="B33">Oliviero et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B11">Dessouki et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B38">Podhorzer et&#xa0;al., 2017</xref>). It is proven that NK cells can be classified into two subpopulations with complementary mechanisms, the NK <italic>bright</italic> and the NK <italic>dim</italic>, and an imbalance between them could affect liver damage generation (<xref ref-type="bibr" rid="B61">Yoon et&#xa0;al., 2016</xref>). In this study an altered balance between peripheral NK subpopulations, with an increase of NK <italic>bright</italic> and a decrease in NK <italic>dim</italic> was found as described by other authors (<xref ref-type="bibr" rid="B5">Bonorino et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B11">Dessouki et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B38">Podhorzer et&#xa0;al., 2017</xref>). Given different functions of these two subpopulations, we evaluated whether the observed altered proportion resulted in a diminished cytotoxic activity and an augmented IFN-<italic>
<italic>&#x3b3;</italic>
</italic> production capacity or if their functions were conserved. Both total NK cells and NK subpopulations showed conserved IFN-<italic>
<italic>&#x3b3;</italic>
</italic> production capacity and degranulation activity in CHC patients as previously described by <xref ref-type="bibr" rid="B56">Varchetta et&#xa0;al. (2012)</xref>. Interestingly, those cases with more severe fibrosis presented lower basal degranulation percentages interpreted as fewer cells that spontaneously degranulated, but they showed higher basal levels of CD107a expression intensity perhaps as a compensatory mechanism.</p>
<p>In conclusion, according to our results total portal lymphocytes contributed to the establishment of the inflammatory liver microenvironment, as reflected by liver infiltrates, and participated in the delicate balance of promoting and moderating liver injury in CHC. The presence of liver CTLs, despite inhibiting viral replication, would favor liver damage. Additionally, as a consequence of liver inflammation and cytokine augmentation at the site of infection, the presence of intrahepatic Treg may suggest their regulatory function to ameliorate liver damage. However, after a long inflammatory process, these cells seemed to be not fully efficient in protecting the final worsening of the liver parenchyma. In turn, despite their low number, Th17 lymphocytes tended to promote fibrogenesis. Furthermore, although the manifestations of chronic infection were mainly at the hepatic level, and the peripheral immune response would not have a clear role in generating liver damage, the peripheral alterations would contribute to the pathogenesis of the global disease. Indeed, the T lymphocyte differentiation stage alteration, the plasma cytokine levels, as well as the decrease in NK cells, could condition the establishment of an effective response against other pathogens or even favor the development of extrahepatic manifestations.</p>
<p>The availability of liver biopsy samples from na&#xef;ve of treatment patients allowed the evaluation of microenvironment features at baseline. Understanding which immune components in the cellular repertoire are important for successful immune responses lays the foundation for future studies evaluating CHC patients during and after DAA treatment in order to understand the new immune scenario when the virus is no longer found. Our results could help to address several open questions remaining for the management of HCV infection in a comprehensive manner.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM2">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s6">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Ricardo Gutierrez Children Hospitals&#x2019; ethics committees. The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s7">
<title>Author Contributions</title>
<p>DAR and CGG designed and performed research, analyzed data and wrote the manuscript. PV obtained funding, designed, and performed research, analyzed data, performed statistical analysis and corrected the manuscript. MSC and MIG performed flow cytometric assay and analysis. PCC and BA participated in the drafting of the work and assisted in clinical data interpretation and analysis. ENDM performed histological characterization and immunostaining evaluation. MVP obtained funding, designed research, analyzed data and corrected the manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This work was funded in part by grants from the National Agency for Scientific and Technology Promotion (ANPCyT) (PICT 2014 N&#xb0;1144, PICT 2014 N&#xb0;1553, PICT 2017 N&#xb0;713), MINCYT (Argentina)-CONACYT (Mexico) (ME/13/43) and National Research Council (CONICET) (PIP 2014). CG is a CONICET doctoral fellow. PV, MP, PC, and EM are members of the CONICET Research Career Program. EM is a member of the Research Career of Buenos Aires City Government.</p>
</sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
<back>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fcimb.2021.712105/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fcimb.2021.712105/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet_1.xlsx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="Presentation_1.pdf" id="SM2" mimetype="application/pdf"/>
<supplementary-material xlink:href="Presentation_2.pdf" id="SM3" mimetype="application/pdf"/>
</sec>
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