Brochado et al. J Biomed Sci (2021) 28:23 https://doi.org/10.1186/s12929-021-00718-6 RESEARCH Open Access HCV eradication with IFN‑based therapy does not completely restore gene expression in PBMCs from HIV/HCV‑coinfected patients Óscar Brochado1, Isidoro Martínez1*, Juan Berenguer2,3, Luz Medrano1, Juan González‑García4,5, María Ángeles Jiménez‑Sousa1, Ana Carrero2,3, Víctor Hontañón4,5, Jordi Navarro6,7, Josep M. Guardiola8, Amanda Fernández‑Rodríguez1† and Salvador Resino1*† on behalf of the GESIDA Study Group Abstract Objective: To evaluate the impact of hepatitis C virus (HCV) elimination via interferon (IFN)-based therapy on gene expression profiles related to the immune system in HIV/HCV-coinfected patients. Methods: We conducted a prospective study in 28 HIV/HCV-coinfected patients receiving IFN-based therapy at baseline (HIV/HCV-b) and week 24 after sustained virological response (HIV/HCV-f ). Twenty-seven HIV-monoinfected patients (HIV-mono) were included as a control. RNA-seq analysis was performed on peripheral blood mononuclear cells (PBMCs). Genes with a fold-change (FC) ≥ 1.5 (in either direction) and false discovery rate (FDR) ≤ 0.05 were iden‑ tified as significantly differentially expressed (SDE). Results: HIV/HCV-b showed six SDE genes compared to HIV-mono group, but no significantly enriched pathways were observed. For HIV/HCV-f vs. HIV/HCV-b, we found 58 SDE genes, 34 upregulated and 24 downregulated in the HIV/HCV-f group. Of these, the most overexpressed were CXCL2, PDCD6IP, ATP5B, IGSF9, RAB26, and CSRNP1, and the most downregulated were IFI44 and IFI44L. These 58 SDE genes revealed two significantly enriched pathways (FDR < 0.05), one linked to Epstein-Barr virus infection and another related to p53 signaling. For HIV/HCV-f vs. HIV- mono group, we found 44 SDE genes that revealed 31 enriched pathways (FDR < 0.05) related to inflammation, cancer/cell cycle alteration, viral and bacterial infection, and comorbidities associated with HIV/HCV-coinfection. Five genes were overrepresented in most pathways (JUN, NFKBIA, PIK3R2, CDC42, and STAT3). Conclusion: HIV/HCV-coinfected patients who eradicated hepatitis C with IFN-based therapy showed profound gene expression changes after achieving sustained virological response. The altered pathways were related to inflam‑ mation and liver-related complications, such as non-alcoholic fatty liver disease and hepatocellular carcinoma, under‑ scoring the need for active surveillance for these patients. Keywords: HIV/HCV coinfection, Gene expression, Immune system, HCV clearance, Interferon therapy, PBMCs Introduction *Correspondence: imago@isciii.es; sresino@isciii.es Hepatitis C virus (HCV) infection is a leading cause of † Amanda Fernández-Rodríguez and Salvador Resino contributed equally chronic liver disease worldwide [1]. HCV and human to this work 1 immunodeficiency virus (HIV) share transmission routes Unidad de Infección Viral E Inmunidad, Centro Nacional de Microbiología, Instituto de Salud Carlos III (Campus Majadahonda), and many HIV-infected individuals are coinfected with Carretera Majadahonda-Pozuelo, Km 2.2, 28220 MajadahondaMadrid, HCV [2]. HIV/HCV-coinfected patients develop chronic Spain hepatitis C over decades of infection, but the cirrhosis Full list of author information is available at the end of the article © The Author(s) 2021. 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The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Brochado et al. J Biomed Sci (2021) 28:23 Page 2 of 14 progression is faster than in HCV-monoinfected patients Patients and methods [3], leading to higher rates of liver-related events (LREs) Study subjects such as liver decompensation, end-stage liver disease, We carried out a prospective study (before and after hepatocellular carcinoma (HCC), and liver-related death design) on 28 HIV/HCV-coinfected patient samples col- [4–7]. Chronic HCV infection promotes inflammation, lected between 2012 and February 2016. In this study, immune activation, and dysregulation of immune func- patients were a subgroup from the GESIDA 3603b study tion [8, 9], which boosts the development of LRE and (see Additional file 7: Appendix S1) previously described other comorbidities in infected people [7–9]. HIV infec- [40]. The study was carried out strictly following the Dec- tion also aggravates the dysregulation of the immune sys- laration of Helsinki and was approved by the Research tem [7, 8], since many disturbances remain in patients Ethics Committee of the Instituto de Salud Carlos III infected with HIV after suppressive antiretroviral ther- (CEI PI 23_2011). Before enrolment, all the participants apy (ART), such as deficits in T-cell functions [10–15], signed written consent. immune activation [13], inflammation [16], and dysbiosis The selection criteria of HIV/HCV-coinfected patients [17–19]. All these immunological alterations increase the were: 1) chronic HCV and HIV infection; 2) starting IFN- risk of AIDS, non-AIDS-related events, and death [20, based therapy (peg-IFN-α/ribavirin or peg-IFN-α/riba- 21]. virin/DAAs) and achieving SVR; 3) CD4+ T cell ≥200 For over a decade, interferon (IFN)-based therapy was cells/µL; 4) stable ART ≥6 months; 4) frozen PBMCs the mainstay of antiviral treatment against HCV. How- samples available. The exclusion criteria were: 1) hepa- ever, the appearance of direct-acting antivirals (DAAs) titis B virus coinfection; 2) acute hepatitis C; 3) hepatic has revolutionized HCV therapy because it has allowed decompensation; 4) HCC. almost all treated patients to achieve sustained virologi- Additionally, 27 HIV-monoinfected patients (HIV- cal responses (SVR) [22–25]. HCV clearance after peg- mono) were used as a control group, matched by gender IFN-α/ribavirin treatment decreases the risk of clinical and age with the HIV/HCV-coinfected patient group. events and death in HIV/HCV-coinfected patients [26, Individuals in the HIV-mono group were negative for 27]. However, liver fibrosis regression after SVR with HCV and HBV infections and had undetectable HIV viral peg-IFN-α/ribavirin is slow since some of the cured load and ­CD4+ >500 cells/µl (normal standard for HIV- patients maintain a low rate of liver fibrosis progression infected patients). We included this HIV-mono group as [28, 29] and develop LREs [30–32], making monitoring a reference point for HIV-monoinfected patients with of the cirrhotic patient necessary after the eradication of stable HIV disease. HCV. Moreover, peg-IFN-α/ribavirin treatment is asso- ciated with numerous side effects, some of which may Clinical data and Samples require long-term follow-up [33]. This concern is even Clinical data were collected prospectively using an online greater for HIV/HCV-coinfected patients since, in this form. Subsequently, the database was monitored to verify population, peg-IFN-α/ribavirin therapy shows higher the data collected. Peripheral venous blood samples were rates of adverse side effects. collected in EDTA tubes, and PBMCs were isolated by Transcriptome analysis has emerged as a key tool Ficoll-Paque gradient. The viable PBMCs were stored in for profiling the immune response against pathogens. liquid nitrogen at the Spanish HIV HGM BioBank until Peripheral blood transcriptome analysis may provide use. The clinical data and samples used in this study were relevant information on the host response in chronic from the beginning of HCV treatment (HIV/HCV-b) and hepatitis C [34] and after overcoming HCV infection 24 weeks after SVR (HIV/HCV-f ). via spontaneous HCV clearance [35], peg-IFN-α/ribavi- rin treatment [36], or DAA therapy [37, 38]. There is lit- The RNeasy Minikit (Qiagen™) was used for total RNA tle information about the long-term impact of successful RNA extraction, library preparation, and sequencing peg-IFN-α/ribavirin treatment on the peripheral blood transcriptome. The only article found on this topic shows extraction from PBMCs following the manufacturer’s that inflammatory gene expression persists in peripheral instructions. Then, the RNA quantity and quality were blood mononuclear cells (PBMCs) after achieving SVR evaluated by Nanodrop 2000 and 2100 Bioanalyzer with peg-IFN treatment [39]. RNA NANO assay (Agilent). Only those samples with an RNA integrity number higher than 7.5 were selected for sequencing. DNAse treatment was performed with Objective the RNase-free DNase Set (Qiagen). Poly-A RNA librar- We aimed to evaluate the impact of HCV elimination via ies and sequencing were performed at the Centre for IFN-based therapy on gene expression profiles related to Genomic Regulation in Barcelona (Spain). Briefly, the immune system in HIV/HCV-coinfected patients. Brochado et al. J Biomed Sci (2021) 28:23 Page 3 of 14 Illumina’s TruSeq Stranded mRNA Sample Prep Kit v2 We used FastQC (v. 0.11.8) for the quality control test. was used on 500 nanograms of total RNA for library The adapter trimming step was carried out with Trim- synthesis. In this way, coding and multiple forms of non- momatic (v. 0.33). TopHat (v. 2.0.14) with GRCH38 was coding RNAs are captured because of polyadenylation. used as a reference genome to perform the alignment and Ten libraries were multiplexed and pooled on each line of HTSeq for count extraction (v. 0.6.1). the Illumina HiSeq2500 sequencer to obtain an average of 25 million reads per sample, with a single read, 50nts Genes selected for analysis (1x50), approach. Figure 1 shows the flowchart of the gene selection pro- We followed a specific bioinformatics pipeline that cess. The bioinformatics analysis identified a gene uni- has been set out in detail in Additional file 1:Table S1. verse composed of 27,173 different genes. Samples Fig. 1 Flowchart of the study design. A total of 27,173 genes were identified by RNA sequencing. Of these, 4723 genes from the immune system were selected from InnateDB, and 3935 genes were selected for differential expression analysis. The FilterByExpr function was applied for each comparison: a HIV/HCV-b vs. HIV-mono, 521 genes were selected, six were SDE genes not involved in any biological pathway; b HIV/HCV-f vs. HIV/ HCV-b, 1124 genes were selected, 58 were SDE genes involved in two biological pathways; c HIV/HCV-f vs. HIV-mono, 504 genes were selected, 44 were SDE genes involved in 31 biological pathways. HIV, human immunodeficiency virus; HCV, hepatitis C virus; HIV/HCV-b, HIV/HCV-coinfected patients at baseline; HIV/HCV-f, HIV/HCV-coinfected patients 24 weeks after SVR; HIV-mono, HIV-monoinfected patients; SDE, significantly differentially expressed Brochado et al. J Biomed Sci (2021) 28:23 Page 4 of 14 showed an average of about 24 million reads, from which of spurious results. Significantly differentially expressed 99.07% of them mapped to the genome. Raw sequence (SDE) genes were those with FDR ≤0.05 and log2-FC data are publicly available at the ArrayExpress repository ≤ − 0.584 (1.5-fold downregulated) or log2-FC ≥0.584 (EMBL-EBI; https://​www.​ebi.​ac.​uk/​array​expre​ss/) under (1.5-fold upregulated). the accession number E-MTAB-10232. From this initial gene universe, we proposed to analyze Results 4723 genes related to the immune system according to Patient characteristics at baseline InnateDB (Additional file 2:Table S2), a public database Table 1 shows the baseline characteristics of the patients of human immune genes (www.​innat​edb.​com). However, included in this study. Overall, HIV/HCV-coinfected we only found 3935 (83%) genes in our initial gene uni- patients showed higher alcohol intake values, HIV acqui- verse out of the total listed in the InnateDB (Fig. 1). sition by injection drug use, and FIB4. Also, HIV/HCV- coinfected individuals had lower values of CD4+ T-cells Calculation of the sample size than HIV-monoinfected patients. The sample size for each group was calculated according to the RNASeqPower [41], which established a minimum Differences in gene expression at baseline (HIV/HCV‑b vs. of 25.6 samples per group to reject the null hypothesis HIV‑mono) (the two groups are equal). Calculates were performed A total of 521 genes fitted the expression criteria for the using the following parameters: 25 million reads per sam- comparison between HIV/HCV-b vs. HIV-mono group ple, an estimated dispersion of 0.4, an alpha of 0.05, and a (Fig. 1), but only six SDE genes were found (Fig. 2a, minimum fold change of 1.5. Thus, the longitudinal study full description in Additional file 3:Table S3A): four (28 vs. 28) and the independent comparisons (28 vs. 27) upregulated in the HIV/HCV-b group (IL23A, FKBP15, showed a statistical power of 0.92. CALR, and DDIT3) and two downregulated (TLR5 and STXBP1). The analysis of the enriched pathways did not Statistical analysis show statistically significant results. We used the Statistical Package for the Social Sciences (SPSS) v22.0 software (IBM Corp., Chicago, USA) to per- Changes in gene expression during follow‑up (HIV/HCV‑f form descriptive statistical analyzes of the study popu- vs. HIV/HCV‑b) lations. Differences were calculated by Mann-Whitney A total of 1124 genes fulfilled the expression criteria tests and Pearson’s chi-squared test. (Fig. 1), and 58 genes were SDE (Fig. 2b, full description We used the R statistical package version v3.4.1 (R in Additional file 3:Table S3B). Thirty-four genes were Foundation for Statistical Computing, Vienna, Austria) upregulated in the HIV/HCV-f group, but only six genes for gene expression analysis. The Trimmed Mean of M were higher than 2-fold (CXCL2, PDCD6IP, ATP5B, (TMM) was used to normalize the data (R-package edgeR IGSF9, RAB26, and CSRNP1). Twenty-four genes were v3.20.9) after selecting genes by using the list of immune downregulated in the HIV/HCV-f group, but only two system-related genes (see the previous section). We car- genes were less than 0.5-fold (IFI44 and IFI44L). ried out the TMM normalization for each of the com- We searched for significantly enriched pathways in parisons (HIV/HCV-b vs. HIV-mono, HIV/HCV-f vs. the SDE genes list, and two significant pathways were HIV/HCV-b, and HIV/HCV-f vs. HIV-mono). Next, we identified (Additional file 4:Table S4; q-value <0.05). used the FilterByExpr function with default parameters One was the Epstein-Barr virus infection pathway to apply a minimum expression criterion and select just (q-value=0.025), represented by four upregulated genes those genes well represented among all samples. Finally, (CDKN1A, NFKB2, RELB, and PDIA3) and two down- we explored the gene expression between groups by regulated genes (BID and HLA-A). The other was the p53 a generalized linear mixed model (GLMM) for paired signaling pathway (q-value= 0.025), represented by two samples and a generalized linear model (GLM) for non- SDE upregulated genes (CDKN1A and PMAIP1) and two paired comparison (R-package lme4 V. 1.1-23), both downregulated genes (BID and TP73). with a negative binomial distribution. Finally, we used NetworkAnalyst v3.0 to find enriched pathways and Differences in gene expression at the end of the follow‑up networks. to the control group (HIV/HCV‑f vs. HIV‑mono) We calculated the fold-change (FC) and log2-FC for Finally, 504 genes fulfilled the expression criteria when each gene for measuring the changes in different groups. comparing HIV/HCV-f vs. HIV-mono (Fig. 1), and 44 P-values were two-tailed and corrected for multiple test- genes were SDE (Fig. 2c, full description in Additional ing using the false discovery rate (FDR) with the Benja- file 3: Table S3C). Twenty-six SDE genes were upregu- mini and Hochberg method (q-values) to reduce the risk lated in the HIV/HCV-f group, but only five were higher Brochado et al. J Biomed Sci (2021) 28:23 Page 5 of 14 Table 1 Clinical, epidemiological, and virological characteristics of HIV and HIV/HCV-coinfected patients HIV HIV/HCV p-value No 27 28 Age (years) 51 (46; 53) 48.5 (45.5; 53) 0.272 Gender (male) 16 (59.3%) 19 (67.9%) 0.508 BMI (kg/m2) 25 (23.4; 26.7) 24 (20.8; 26) 0.125 BMI ≥ 25 (kg/m2) 14 (51.9%) 9 (32.1%) 0.139 Diabetes 4 (14.8%) 2 (7.1%) 0.362 High alcohol intake 1 (3.7%) 13 (46.4%) < 0.001 HIV acquired by IVDU 0 (0%) 22 (78.6%) < 0.001 Prior AIDS 10 (37%) 8 (28.6%) 0.504 Years since HIV infection 22.5 (17.5; 26.5) – Years since HCV diagnosis 13 (12; 23) – Previous HCV therapy (IFNα + rib) 13 (46.4%) – Antiretroviral therapy 27 (100%) 28 (100%) 0.999 PI-based 6 (22.2%) 6(21.43%) 0.019 2NRTI + II-based 3 (11.1%) 11 (39.3%) 2NRTI + PI-based 0 (0%) 3 (10.7%) 2NRTI + NNRTI-based 16 (59.3%) 7 (25%) Others 2 (7.4%) 1 (3.6%) HIV markers Nadir CD4 + T-cells 261 (99; 402) 185 (72; 269) 0.155 Nadir CD4 + T-cells < 200 cells/mm3 11 (44%) 15 (53.6%) 0.487 CD4 + T-cells 804 (685; 1036) 678.5 (446.5; 906) 0.026 CD4 + T-cells < 500 cells/mm3 0 (0%) 8 (28.6%) 0.003 HIV-RNA > 50 cp/mL 0 (0%) 0 (0%) – HCV markers HCV genotype   1 18 (64.3%) –   2 1 (3.6%)   3 8 (28.6%)   4 1 (3.6%)   ­Log10 HCV-RNA (IU/mL) 6.3 (5.8; 6.6) –   HCV-RNA > 850.000 IU/mL 19 (67.9%) – Non-invasive fibrosis indexes   FIB-4 1 (0.9; 1.2) 2.6 (1.9; 3.2) < 0.001   FIB-4 ≥ 3.25 0 (0%) 7 (25%) 0.006   LSM (Kpa) 11.9 (9.7; 19.2) –   F0–F1 (< 7.1 kPa) 2 (7.1%) –   F2 (7.1–9.4 kPa) 5 (17.9%)   F3 (9.5–12.4 kPa) 8 (28.6%)   F4 (≥ 12.5 kPa) 13 (46.4%) Statistics: The values are expressed as the absolute number (percentage) and median (interquartile range). P-values were calculated by Mann–Whitney and chi- squared tests HCV, hepatitis C virus; HCV-RNA, HCV plasma viral load; HIV, human immunodeficiency virus; LSM, liver stiffness measure; HIV-RNA, HIV plasma viral load; IVDU, intravenous drug user; AIDS, acquired immune deficiency syndrome; IFNα + rib, interferon-alpha plus ribavirin; NNRTI, non-nucleoside analogue HIV reverse transcriptase inhibitor; NRTI, nucleoside analogue HIV reverse; BMI, body mass index than 2-fold upregulated (KLF6, HSPA5, JUN, PRRC2C, The pathway analysis showed 31 enriched pathways and PPP1R15A). Eighteen SDE genes were downregu- related to four main topics (Fig. 3, full description in lated, but none were less than 0.5-fold. Additional file 5:Table S5): (i) inflammation, (ii) cancer/ cell cycle alteration, (iii) viral and bacterial infection, Brochado et al. J Biomed Sci (2021) 28:23 Page 6 of 14 Fig. 2 Volcano plots for differentially expressed genes between groups: a HIV/HCV-b versus HIV-mono, b HIV/HCV-f versus HIV/HCV-b, c HIV/HCV-f versus HIV-mono. Volcano-plot discriminates by FDR and log2(FC). The red vertical lines represent the cut-off of FC 1.5 and the blue horizontal line indicates the cut-off of FDR = 0.05. Green dots represent genes significantly altered with FDR ≤ 0.05 and absolute FC ≥ 1.5. FDR, false discovery rate for multiple comparisons using Benjamini and Hochberg procedure; FC, fold-change; HIV, human immunodeficiency virus; HCV, hepatitis C virus; HIV/HCV-b, HIV/HCV-coinfected patients at baseline; HIV/HCV-f, HIV/HCV-coinfected patients 24 weeks after SVR; HIV-mono, HIV-monoinfected patients and (iv) comorbidities related to HIV/HCV-coinfection. (HIV/HCV-f vs. HIV/HCV-b). Unexpectedly some genes Overall, five genes were overrepresented among the also remained overexpressed or suppressed after HCV majority of the altered pathways (JUN, NFKBIA, PIK3R2, clearance with respect to the HIV-monoinfected patients CDC42, and STAT3). (HIV/HCV-f vs. HIV-mono). However, HIV/HCV-b Finally, the HIV/HCV-b vs. HIV-mono and the HIV/ showed only discrete expression differences from the HCV-f vs. HIV-mono comparisons had four upregulated HIV-mono, and no significantly enriched pathways were genes in common (IL23A, FKBP15, CALR, and DDIT3) found. and one downregulated gene (STXBP1) (Fig. 4, Addi- tional file 3: Table S3). Therefore, these five SDE genes HIV/HCV‑b vs. HIV‑mono remained deregulated at 24-week after SVR. Additionally, Unexpectedly, when HIV/HCV-b and HIV-mono were three SDE genes were upregulated (HSPA5, KLF6, and compared, we found only six SDE genes and no biologi- PRRC2C), and four downregulated (MKL1, AMIGO3, cal pathways overrepresented, indicating that HCV infec- LHX4, and ITGB7) both in the HIV/HCV-f vs. HIV/ tion had a moderate impact on PBMCs gene expression HCV-b and the HIV/HCV-f vs. HIV-mono comparisons in HIV/HCV-coinfected patients. Kottilil et al. showed (Fig. 4, Additional file 3:Table S3). that although HCV mono-infection induces significant PBMC gene expression changes related to immunoregu- Changes in metabolic, HIV‑related disease, and liver latory and proinflammatory pathways, the differences disease profiles (HIV/HCV‑f vs. HIV/HCV‑b) between HIV/HCV-coinfected and HIV-monoinfected At the end of follow-up, we found significant increases patients were small [42]. Our results also agree with in levels of cholesterol (p=0.022), ­CD4+ T-cells/mm3 previous findings showing that HCV infection leads to (p=0.026), and albumin (p=0.045); while values of LSM hyporesponsiveness of PBMCs [43, 44]. Furthermore, (p=0.002), FIB4 (p<0.001), AST (p<0.001), and ALT continuous stimulation of TLR2, TLR4, and TLR5 has (p<0.001) significantly decreased (Table 2). been shown to lead to monocyte tolerance [45]. All the upregulated genes in the HIV/HCV-b group Discussion (IL23A, FKBP15, CALR, and DDIT3) are associated This study shows that the gene expression profile in with HCV infection. IL23A is a crucial cytokine in the PBMCs of HIV/HCV-coinfected patients 24 weeks after immune and inflammatory response that plays an essen- achieving SVR (HIV/HCV-f ) was significantly different tial role in HCV infection. Its increase may enhance the from either HIV/HCV-coinfected patients before initia- antiviral activity of IFN-based therapy by modulating the tion of IFN-based therapy (HIV/HCV-b) or the control molecules expressed by Th17 cells in patients infected HIV group (HIV-mono). The highest differences were with HCV [46]. HCV promotes significant changes in the identified after HCV eradication compared to baseline endoplasmic reticulum (ER) [47]. CALR is a chaperone Brochado et al. J Biomed Sci (2021) 28:23 Page 7 of 14 Fig. 3 The chord-diagram represents connections between SDE genes (left-side) and pathways (right-side) in comparing HIV/HCV-f versus HIV-mono. Red corresponds to inflammation, green corresponds to cell cycle alteration and cancer, blue corresponds to viral and bacterial infection, and black corresponds to complications related to HIV/HCV-coinfection. HIV, human immunodeficiency virus; HCV, hepatitis C virus; HIV/HCV-b, HIV/HCV-coinfected patients at baseline; HIV/HCV-f, HIV/HCV-coinfected patients 24 weeks after SVR; HIV-mono, HIV-monoinfected patients; SDE, significantly differentially expressed that interacts with HCV to correctly fold their glycopro- STXBP1 is a protein crucial in vesicle docking and fusion. teins, avoiding the appearance of chronic stress in the ER Its downregulation seems to be related to a lower HCV when the folding capacity of cellular proteins is exceeded release [52] and a lower cytolytic T lymphocyte activity [48]. FKBP15 is a binding protein directly involved in [53]. TLR5 recognizes explicitly bacterial flagellin. How- regulating endosome trafficking, which HCV hijacks to ever, stimulation of TLR2 by bacterial products induces produce viral particles [49]. Therefore, a higher FKBP15 TLR5 downregulation in human monocytes [45]. In this expression may be related to the higher activation of the sense, chronic hepatitis C increases bacterial translo- endosome-based secretory pathway for a higher virus cation to the blood, and downregulation of TLR5 may production through exosome pathways. Besides, FKBP15 be beneficial for the host in the context of persistent has been identified as mutated in HCV-infected cirrhotic immune stimulation by reducing the immune response liver and is associated with HCC [50]. DDIT3 is another and the associated immunopathology. gene related to the ER that is activated by the HCV core Finally, TLR5 was down-regulated by more than two- protein after promoting ER stress [51]. fold in the HIV/HCV-b group, but its expression was nor- All the downregulated regulated genes (TLR5 and malized at the end of the study when HCV eradication STXBP1) have also been linked to HCV infection. reduces microbial translocation in HIV/HCV-coinfected Brochado et al. J Biomed Sci (2021) 28:23 Page 8 of 14 patients’ immunological response, increasing inflamma- tion and immune activation [55]. However, these SDE genes deregulated in the EBV pathway are also involved in many other immune pathways that may have been affected after HCV treatment. On the one hand, BID and HLA-A were downregu- lated after HCV eradication. BID encodes a proapoptotic member of the Bcl-2 protein family, and its downregu- lation may indicate a decrease of apoptosis after HCV clearance with HCV therapy. Liver BID suppression improves inflammation and liver fibrosis in experimen- tal NASH [56] and can protect from the development of HCC [57, 58]. HLA-A is a member of the major histo- compatibility complex (MHC) from class Ia involved in antigen presentation to ­CD8+ T cells during an immune response [59]. A decrease of HLA-A expression may be related to a reduction of C­ D8+ T cell response after HCV clearance with HCV therapy. However, increased HLA-A Fig. 4 Venn diagram of the SDE genes in the three comparisons expression levels are related to poor control of HIV analyzed in the study: a HIV/HCV-b versus HIV-mono, b HIV/HCV-f through HLA-E induction and the inhibition of NK cells versus HIV/HCV-b, c HIV/HCV-f versus HIV-mono. The number in [60]. Therefore, the downregulation of BID and HLA-A each circle corresponds to the number of SDE genes in the different genes could improve liver disease and immune response. comparisons. The overlapping numbers are the number of SDE genes shared between the different comparisons. The non-overlapping On the other hand, CDKN1A, NFKB2, RELB, and numbers are the unique SDE genes in each comparison. HIV, human PDIA3 genes were upregulated after HCV eradication. immunodeficiency virus; HCV, hepatitis C virus; HIV/HCV-b, HIV/ CDKN1A encodes p21, a known inhibitor of the cell HCV-coinfected patients at baseline; HIV/HCV-f, HIV/HCV-coinfected cycle, linked to senescence arrest and regulated by p53. patients 24 weeks after SVR; HIV-mono, HIV-monoinfected patients In the liver, p21 overexpression is related to the arrest of liver regeneration and the development of NAFLD, liver fibrosis, and cirrhosis [61]. However, p21 may have two patients [54]. The remaining five SDE genes (IL23A, contradictory functions related to HCC (tumor suppres- FKBP15, CALR, DDIT3, and STXBP1) stayed deregulated sor or promoter), depending on its subcellular localiza- at the end of follow-up, indicating that the ER-related and tion [62]. Thus, its nuclear location is associated with a exosome pathways may remain altered after HCV elimi- tumor suppression function. Besides, IFN may keep p21 nation with IFN-based therapy. Therefore, of the six SDE in the nucleus, where it develops its anti-hepatocar- genes, when HCV infection disappears, only the expres- cinogenesis role [62]. Therefore, p21 upregulation after sion of TLR5 was normalized. However, the biological IFN-treatment may be associated with a reduced risk of significance of this result is difficult to ascertain since the HCC compared to the baseline. P21 also has an antiviral genes did not group in any biological pathway. Besides, function, and its upregulation blocks HIV replication in the expression differences with respect to the HIV-mono HIV-infected patients with elite control phenotype [63, group were small (FC<2). 64]. NFKB2 encodes the nuclear factor kappa-B (NF-κB) p100, a subunit of the NF-κB complex, which may func- HIV/HCV‑f vs. HIV/HCV‑b groups tion as a repressor or transcriptional activator, depend- Gene expression in PBMCs from HIV/HCV-coinfected ing on its dimerization partner. As a transcriptional patients showed the deregulation of 58 genes after repressor, NF-κB2 may support the establishment of HIV achieving SVR. These SDE genes represent two biologi- latency, while as a transcriptional activator, it may facili- cal pathways, Epstein-Barr virus (EBV) infection and p53 tate HIV transcription [65]. NF-κB2 has an essential role signaling. in HCC pathogenesis [66] and NAFLD [67]. RELB also EBV establishes a latent infection in over 90% of human encodes a transcription factor that interacts with NF-κB2, adults, alternating between episodes of latency and reac- and it may also facilitate HIV transcription [65, 68]. RelB tivation inside B-lymphocytes, which may lead to the expression is increased in chronic hepatitis C and pro- malignant transformation of B cells. Thus, EBV has been motes liver fibrosis [69, 70]. PDIA3 encodes an isomerase linked to a broad spectrum of human malignancies [55]. enzyme that participates in the synthesis of glycopro- Additionally, EBV coinfection may alter HIV-infected teins such as HLA-I. It is a redox sensor by activating Brochado et al. J Biomed Sci (2021) 28:23 Page 9 of 14 Table 2 Summary of metabolic, HIV disease, and liver disease characteristics in HIV/HCV-coinfected patients at baseline and the end of follow-up Variable–median (IQR) Baseline Final p-value Metabolic profile Glucose (mg/dL) 97.5 (83.8; 103) 93 (86.5; 96.5) 0.967 Triglycerides (mg/dL) 108 (78.5; 169.5) 145 (99.5; 189.3) 0.063 Cholesterol (mg/dL) 169 (139.5; 194.5) 183.5 (169.8; 208.5) 0.022 LDL (mg/dL) 104 (76.3; 118.8) 110 (97; 135) 0.071 HDL (mg/dL) 48 (36; 56.5) 36 (33; 50) 0.119 HIV disease profile  ­CD4+ T-cells/mm3 678 (446; 911) 827 (588; 1131) 0.026  ­CD8+ T-cells/mm3 946 (555; 1356) 1093 (840; 1308) 0.531 HIV-viral load > 50 copies/mL (%) 0/28 (0%) 4/26 (15.4%) 0.982 Liver disease profile LSM (kPa) 11.9 (9.6; 19.9) 7.6 (5.9; 13.9.) 0.002 FIB4 2.6 (1.9; 3.2) 1.7 (1.2; 2.1) 0.000 AST (UI/L) 61 (42.5; 79.3) 19 (13.8; 25) 0.000 ALT (UI/L) 71.5 (56; 100.5) 33.5 (26.5; 42) 0.000 GGT (UI/L) 41 (35.5; 44) 33.5 (26.5; 42) 0.951 Alkaline phosphatase (UI/L) 94.5 (78; 117) 95 (85; 120) 0.381 INR 1 (1; 1.1) 1 (0.95; 1.1) 0.353 Bilirubin (mg/dL) 0.6 (0.5; 1.15) 0.6 (0.4; 0.8) 0.177 Albumin (g/dL) 4.3 (3.9; 4.6) 4.5 (4.2; 4.7) 0.045 Statistics: The values are expressed as the median (IQR, interquartile range). P-values were calculated by generalized linear mixed models (GLMM) for paired samples HCV, hepatitis C virus; HIV, human immunodeficiency virus; LSM, liver stiffness measure; LDL, low-density lipoprotein; HDL, high-density lipoprotein; LSM; liver stiffness measure; FIB4; fibrosis-4 index; ALT, alanine aminotransferase; AST, aspartate transaminase; GGT, gamma-glutamyl transferase; INR, international normalized ratio mTORC1, and it regulates cell growth, death, and signal encodes a pro-apoptotic protein of the Bcl-2 family that transduction via STAT3 [71]. PDIA3 deregulation is asso- is regulated by p53. PMAIP1 overexpression is linked ciated with diverse pathological conditions [71]. PDIA3 to NASH and fibrosis histological criteria [79], which overexpression can promote liver fibrosis [72] and HCC could indicate a worse prognosis of liver disease. How- [73, 74]. Overall, the upregulation of CDKN1A, NFKB2, ever, in vitro studies have shown PMAIP1 plays a crucial RELB, and PDIA3 indicates a worse prognosis of liver role in hepatocarcinogenesis by limiting cancer cell sur- disease and an impaired immune response against HIV. vival [80] and an anti-tumoral function [81]. Therefore, We have also identified SDE genes related to the p53 PMAIP1 upregulation after HCV eradication would be signaling pathway. P53 is a tumor suppressor protein that related to a reduced risk of HCC in these patients. restricts tumorigenesis by regulating cell cycle arrest, Finally, we found several 2-fold deregulated genes. senescence, and apoptosis. The p53 signaling pathway HIV/HCV-f showed two highly downregulated genes has been previously associated with HCV infection as (IFI44 and IFI44L) and six highly upregulated genes p53 function is disrupted by direct interaction with (CXCL2, PDCD6IP, ATP5B, IGSF9, RAB26, and CSRNP1) viral particles [75] or by the host immune response [76]. compared to HIV/HCV-b. For the sake of brevity, we Thus, p53 function disruption contributes to hepatocel- have discussed these genes in Additional file 6:Table S6. lular carcinogenesis. Two genes of this pathway were downregulated (BID and TP73) and two upregulated HIV/HCV‑f vs. HIV‑mono (CDKN1A and PMAIP1). BID and CDKN1A are both The comparison of HIV/HCV-f vs. HIV-mono also involved in the pathway of EBV infection that has been revealed the upregulation of inflammatory and carcino- previously discussed. TP73 encodes p73, which is con- genic genes after HCV clearance. Specifically, we found sidered a p53-related transcription factor involved in cell 44 SDE genes and 31 significantly enriched pathways cycle regulation and apoptosis. TP73 is up-regulated in related to inflammation, cancer, complications associ- tumors of HCC patients [77], and lower p73 expression is ated with HIV/HCV coinfection, and viral and bacterial related to higher survival in HCC patients [78]. PMAIP1 infections. Brochado et al. J Biomed Sci (2021) 28:23 Page 10 of 14 Overall, five upregulated SDE genes were overrep- profiling on these cells [94, 95], but none of these genes resented in most pathways (JUN, NFKBIA, PIK3R2, were identified as differentially expressed after HCV CDC42, and STAT3). JUN encodes a subunit of the AP-1 eradication. transcription factor that promotes inflammation and On the other hand, HCV elimination with IFN-based insulin resistance. JUN overexpression promotes liver therapy does not lead to the restoration of normal fibrosis and correlates with progression from steatosis physiological conditions in some cases. As previously to NASH [82]. NFKBIA encodes an inhibitor of NF-κB. discussed, some SDE genes and enriched pathways are NFKBIA overexpression is related to steatosis develop- related to increased inflammation and the development ment by induction of hepatocyte apoptosis and secre- of NASH, NAFLD, or HCC. This may be due to multi- tion of TNF-α and IL-1β by Kupffer cells [83]. Together ple factors, some of which are the following: with bacterial translocation, these mediators can acti- Firstly, IFN treatment was usually dispensed to vate hepatic stellate cells and promote liver fibrosis and patients in advanced stages of liver disease (F ≥2), establish the conditions for the development of HCC where severe liver damage already exists and may not [84]. Moreover, NFKBIA overexpression may attenu- completely reverse after reaching SVR. Persistent histo- ate NF-κB signaling and enhance HIV-1 latency [85, logical inflammation, which may contribute to hepatic 86]. PIK3R2 encodes a negative regulatory protein of the fibrosis and carcinogenesis, was detected several PI3K pathway. Increased PIK3R2 expression has been years after successful IFN-based therapy [96]. Besides, found in cancer, and it has been proposed as an onco- HCV elimination after DAAs therapy does not restore gene [87]. CDC42 encodes a Rho GTPase that regulates the epigenetic changes related to HCC development the cell cycle, and its overexpression is related to the induced by HCV infection [97, 98], which indicates development of fibrosis [88], NAFLD [89], and HCC [90]. that the failure to normalize the liver injury after HCV STAT3 encodes a transcription factor that regulates pro- elimination is not unique to IFN-based treatment. In liferation, cell survival, and the immune response. STAT3 our study, the follow-up time of HIV/HCV-coinfected signaling is related to liver inflammation, injury, steatosis, patients was long enough (24 weeks after SVR) to fibrosis, and HCC [91], and it is overexpressed in patients observe an increase in plasma cholesterol levels at the with NASH [92] and HCC [93]. end of follow-up. This finding is consistent with data The HIV/HCV-f group showed five SDE genes that recently published by Carrero et al. [99], which reports were 2-fold upregulated with respect to the HIV-mono an increase in plasma cholesterol and cardiovascular (KLF6, HSPA5, JUN, PRRC2C, and PPP1R15A). A brief risk in HIV/HCV-coinfected patients who achieved discussion of these genes is provided in Additional SVR with IFN-based therapy. However, we have not file 6:Table S6. observed the development of other adverse outcomes, such as the development of NAFLD or HCC. Consequences of HCV elimination by IFN‑based therapy Secondly, it may be due to the immunomodulatory Overall, our results revealed that HCV elimination after effects of IFN-based treatment. In this regard, our find- IFN-based treatment positively and negatively affects ings are in line with previous investigations. For example, HIV/HCV-coinfected patients. IFN treatment induces a robust cytokine response medi- On the one hand, IFN-based therapy eliminates ated by STAT1, NF-κB and JNK signaling pathways in HCV infection, improving some aspects of inflamma- PBMCs of HCV-infected patients with SVR compared to tion, immune activation, and liver disease progression. non-responder patients [100]. An inflammatory response Thus, we found an improvement at the end of follow- was also observed in PMBCs after successful IFN treat- up in non-invasive markers of liver disease (liver stiff- ment of HCV infection [39]. Moreover, as previously ness, FIB-4, AST, ALT, and albumin) and a significant commented, we have reported in this cohort (GESIDA increase in C­ D4+ T-cells/mm3, improving the patient’s 3603b study) that a large number of biomarkers did not health status. Besides, we have recently described in improve after achieving SVR with IFN-based therapy, this cohort (GESIDA 3603b study) a decrease in some staying away from the values of the HIV control group plasma and T-cell biomarkers related to inflamma- [40]. tion and immune activation in HIV/HCV-coinfected Thirdly, another possible explanation resides in the patients after achieving SVR with IFN-based treat- elimination of HCV itself. Chronic hepatitis C profoundly ment. Still, most biomarkers in plasma and T-cell did affects the host immune response and other physiological not improve and were far from normalization com- processes [101]. Therefore, HCV elimination may induce pared to HIV-monoinfected patients [40]. Moreover, undesired effects in the already severely affected immune we explored the specific signatures of lymphocytes T system and liver physiology, particularly in the context of ­C D4+ and ­ C D8+, based on previous transcriptome HIV coinfection. Brochado et al. J Biomed Sci (2021) 28:23 Page 11 of 14 Limitations of the study Additional file 1: Table S1. Bioinformatics pipeline to analyze raw sequences from RNA-seq of HIV/HCV-infected and HIV-monoinfected Our study has some limitations. Therefore, our con- patients. clusions should be interpreted with caution: (i) The Additional file 2: Table S2. List of 4723 genes related to the immune sys‑ number of patients per group was limited, which could tem according to InnateDB, a public database of human immune genes prevent the detection of small differences between (www.​innat​edb.​com). groups and increase the risk of false positives results. Additional file 3: Table S3. Summary of significant differentially However, the GLMM approach properly accounts for expressed genes (FC ≥1.5; FDR ≤0.05) in peripheral blood mononuclear cells: A) HIV/HCV-b versus HIV-mono. B) HIV/HCV-coinfected at week 24 the random effect in our model, limiting the false-pos- (HIV/HCV-f ) after SVR versus at baseline (HIV/HCV-b). C) HIV/HCV-f versus itive rate and increasing the statistical power. (ii) Our HIV-mono. study had a prospective observational design and may Additional file 4: Table S4. Summary of significant KEGG pathways (FDR introduce biases. (iii) Another limitation of this study ≤0.05) in the HIV/HCV-f versus HIV/HCV-b comparison. was the lack of other control groups that could give our Additional file 5: Table S5. Summary of significant KEGG pathways (FDR findings more robustness. So, we lack an HCV mono- ≤0.05) in the HIV/HCV-f versus HIV-mono comparison. infected group of patients with similar liver disease Additional file 6: Table S6. Summary of the most deregulated SDE genes (absolute FC ≥2 and FDR ≤0.05). characteristics to the HIV/HCV group. This control Additional file 7: Appendix S1. The GESIDA 3603b Cohort Study Group. group would help to elucidate gene expression profiles related to the immune system after the HCV clear- ance with IFN treatment without HIV interaction. Nor Acknowledgements We want to acknowledge the patients in this study for their participation and were available a group of HCV/HIV-coinfected patients to the Spanish HIV HGM BioBank integrated into the Spanish AIDS Research who failed the IFN treatment or HCV/HIV-coinfected Network (RIS) and collaborating Centers for the generous gifts of clinical sam‑ patients receiving DAA treatment (IFN-free treatment) ples used in this work. This study would not have been possible without the collaboration of all medical and nursing staff and data managers who have as controls. These control group options would have taken part in the project (see Additional file 7: Appendix S1, which shows all helped us to elucidate whether the differences observed collaborators). We also want to thank the Bioinformatics Unit at the Institute of in this study were due to the effect of HCV clearance Health Carlos III for their valuable support for the bioinformatics analysis. or IFN treatment per se. iv) iv) This work is an associa- Authors’ contributions tion study and lacks mechanistic exploration or func- Conceptualization: SR, AFR. Data curation: JB, JGG, AC, VH, JN, JMG. Formal tional validation. Functional validation by quantitative analysis: OBK, SR, IM, AFR. Funding acquisition: JB, JGG, and SR. Investigation and methodology: LMM, OBK, and AFR. Project Administration: JB. Supervi‑ PCR is not usually necessary when using a large num- sion and visualization: SR. Writing – original draft preparation: IM, AFR, and ber of biological replicates. Given the complex virus- SR. Writing – Review & Editing: MAJS. All authors read and approved the final host interactions, it is difficult to know which genetic manuscript. changes are truly clinically important and contribute to Funding clinical outcomes. This study was supported by grants from Instituto de Salud Carlos III (ISCII; Grant Numbers PI20/00474 and PI17/00657 to JB, PI20/00507 and PI17/00903 to JGG, PI18CIII/00020 to AFR, and PI20CIII/00004 and PI17CIII/00003 to SR). The study was also funded by the RD16CIII/0002/0002 and RD16/0025/0017, Conclusions and RD16/0025/0018 projects as part of the Plan Nacional R + D + I and co- HIV/HCV-coinfected patients who eradicated chronic funded by ISCIII- Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER). JB is an investigator from the Programa de hepatitis C with peg-IFN-α/ribavirin therapy showed Intensificación de la Actividad Investigadora en el Sistema Nacional de Salud profound gene expression changes in PBMCs, which (I3SNS), Ref. INT16/00100. seem to be related to inflammation and liver-related Availability of data and materials complications, such as NASH and HCC. Our findings The datasets used and analyzed during the current study are available from may be influenced by the long-term impact of IFN ther- the corresponding authors upon reasoned request. HIV/HCV-coinfected apy, although a rebound effect due to HCV elimination patients’ raw sequences data are publicly available at the ArrayExpress repository (EMBL-EBI; https://​www.​ebi.​ac.​uk/) under the accession number itself could not be ruled out. Prospective studies should E-MTAB-8275. The raw RNA sequences of HIV-infected patients can also be be carried out to monitor the long-term normalization accessed under the accession number E-MTAB-8249. of gene expression profiles and clinical evolution in these patients who achieved successful SVR after IFN-based Declarations regimens. Ethics approval and consent to participate The study was conducted following the Declaration of Helsinki, and patients Supplementary Information gave their written consent. The Institutional Review Board and the Research The online version contains supplementary material available at https://​doi.​ Ethics Committee of the Instituto de Salud Carlos III (ISCIII) approved the study org/​10.​1186/​s12929-​021-​00718-6. (CEI PI 23_2011). Brochado et al. J Biomed Sci (2021) 28:23 Page 12 of 14 Consent for publication 14. DaFonseca S, Niessl J, Pouvreau S, Wacleche VS, Gosselin A, Cleret- Not applicable. Buhot A, Bernard N, Tremblay C, Jenabian MA, Routy JP, et al. 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