Well-Differentiated Liver Cancers Reveal the Potential Link Between ACE2 Dysfunction and Metabolic Breakdown.

doi:10.21203/rs.3.rs-797837/v1

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Well-Differentiated Liver Cancers Reveal the Potential Link Between ACE2 Dysfunction and Metabolic Breakdown.

https://doi.org/10.21203/rs.3.rs-797837/v1

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published 03 Feb, 2022

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Angiotensin-converting enzyme 2 (ACE2) is the receptor of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causing Coronavirus disease 2019 (COVID-19).Transmembrane serine protease 2 (TMPRSS2)is a coreceptor.Abnormal hepatic function in COVID-19 suggests specific or bystander liver disease.Because liver cancer cells express the ACE2viral receptor, they arewidely usedas models of SARS-CoV-2 infection in vitro. Therefore, the purpose of this study was to analyze ACE2 and TMPRSS2 expression and localization in human liver cancers and in non-tumor livers.We studiedACE2 and TMPRSS2 in two transcriptomic datasets totaling 1503 liver cancersand 47 non-tumor samplesand in tissue microarrays including 41 HCCs and five non-tumor samples by multiplex high-resolution confocal immunohistochemistryand quantitative image analysis.In liver cancers, wedetectedACE2 and TMPRSS2 at the biliary pole of tumor hepatocytes. In non-tumor livers, we identifiedACE2 in hepatocyte’s bile canaliculi, biliary epithelium,sinusoidal and capillary endothelial cells.Tumors carrying mutated β-catenin showedACE2 DNA hypomethylation and higher mRNA and protein expression, consistently with predicted β-catenin response sites in the ACE2 promoter.Finally, ACE2 and TMPRSS2 co-expression networkshighlightedhepatocyte-specific functions, oxidative stress and inflammation, suggesting a link between inflammation, ACE2 dysfunction and metabolic breakdown.

Epigenetics & Genomics

Immunology

liver metabolism

DNA methylation

DC-SIGNR

MRP2

CLEC4M

TMPRSS2

DPP4

SARS-CoV-2

hepatocellular carcinoma

multiplex immunohistochemistry

confocal slide scanning

CTNNB1

tumor transcriptomics

tumor classifications

functional expression networks

weighted gene correlation network analysis

tissue microarrays

the cancer genome atlas

Desert’s hepatocellular carcinoma classification

periportal

perivenous

stem

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes the Coronavirus disease 2019 (COVID-19)^1-3.SARS-CoV-2 is an enveloped RNA betacoronavirusphylogenetically similar to SARS-CoV and the Middle East Respiratory Syndrome Coronavirus (MERS-CoV).Although ~80% of SARS-CoV-2-infected individuals develop asymptomatic self-limited upper airway forms of COVID-19, approximately 15% need hospitalization and 5% develop severe disease with acute respiratory distress syndrome, immune dysregulation and a “cytokine storm” with disseminated intravascular coagulation^1,3,4. Approximately 50% of hospitalized patients present comorbidities: hypertension, type-2 diabetes and coronary heart disease^1-3,5,6.

The baseline prevalence of chronic liver disease in COVID-19 was about three percent in two meta-analyses assembling 3301 patients^7,8, but the mean prevalence of COVID-19 related liver dysfunction was about 20% (range 14-53%)^1,6-9. Liver dysfunction correlates with the extent of pulmonary lesions¹⁰. Patients with hepatocyte-type dysfunction at admission are at higher risk of progressing to severe COVID-19¹¹. After admission, antiviral drugs such as lopinavir and ritonavir are risk factors for liver damage¹¹. Autopsies suggested that SARS-CoV-2 infects and replicates within hepatocytes in severe COVID-19 cases^12-14 and SARS-CoV-2 RNA has been detected in the respiratory epithelium, kidney, liver, heart, brain, blood and stools in severe COVID-19 cases^15,16. In addition, crown-like viral particles with complete envelope and typical spikes have been observed in lung, kidney^16,17 and in hepatocytes¹⁴ suggesting multiorgan targeting of COVID-19.

Cell entry of SARS-CoV and SARS-CoV-2 depends on the binding of the viral spike (S) protein to the Angiotensin-converting enzyme 2 (ACE2) and on the serine protease TMPRSS2 for S protein fusion^18,19.The rate of SARS-CoV-2 infection correlates with cell surface ACE2 expression^18,19. Importantly, Huh-7^18,20 human hepatocellular carcinoma (HCC) and HepG2 hepatoblastoma²⁰ cells are widely used models of SARS-CoV-2 infection because they express cell surface ACE2 and can be infected at high titers.

As liver cancer cells are in vitro models for the study of SARS-CoV-2 entry and cytopathic effects, we extensively studied mRNA, protein expression and localization of the viral receptors ACE2 and TMPRSS2 in human HCCs. This characterization will be useful to design in vitrostudies on virus entry, replication and metabolic alterations in liver cells.

Predominant expression of ACE2 and TMPRSS2 in well-differentiated HCCs

We first searched for relationships ofACE2 and TMPRSS2 mRNA expression levels with HCC aggressiveness. To this end, overall and disease-free survival analyses were carried out in the TCGA dataset (n= 370). After applying the exclusion criteria described in Supplementary Fig. 1A, the survival dataset consisted of 256 patients. In consistency with previous reports^21-23,higher ACE2and TMPRSS2 mRNA expression were associated with better overall and disease-free survival (Supplementary Fig. 1B and 2A). ACE2 and TMPRSS2mRNAs were also detected in 47 non-tumor livers in the TCGA dataset. WhereasACE2 mRNA expression was 1.7-fold higher in non-tumors livers than in HCCs, TMPRSS2 expression did not differ between both groups (Supplementary Fig. 2B).

In HCCs, the expression of genes associated with relatively good prognosis is frequently preserved in well-differentiated tumors because they maintain the phenotype of adult hepatocytes^24,25.To verify if this applied to ACE2 and TMPRSS2,we measured their expression levels in HCCs classified according to their likeness to normal hepatocytes. Thus classified, HCCs are divided into two major classes, namely “low-proliferation” and “high-proliferation”²⁵. Four HCC subclasses result from the interaction of, on one hand, the metabolic phenotype and, on the other hand, the proliferation/differentiation ratios of tumor cells^24,26. Hence, in the “low-proliferation” class of well-to-moderately differentiated HCCs, the periportal-type (PP) and perivenous-type (PV) subclasses refer to the preservation of the metabolic zonation phenotypes of normal hepatocytes^24,26. At the opposite end of the spectrum, in the “high-proliferation” class of moderately-to-poorly differentiated HCCs, the extracellular-matrix-type (ECM) and STEM-type subclasses, refer to tumors developing an important stromal and vascular support and expressing cancer stem cell markers^24,26. In this context, we found higher ACE2 mRNA expression in perivenous-type HCCs than in the other subclasses (Fig. 1A; Supplementary Fig. 2C)in both the Désert’s cDNA microarray meta-dataset (1133 HCCs)²⁶ (Fig.1A) and in the TCGA dataset (370 HCCs) (Supplementary Fig.2C). Of note, ACE2 mRNA expression was higher in HCCs expressing previously validated β-catenin pathway activationsignatures^26,27(Fig. 1B) and in HCCs carryingsequenced β-catenin (CTNNB1)activating mutations (Supplementary Fig.2C). In turn, TMPRSS2 was expressed at higher levels in periportal-type HCCs (Supplementary Fig. 2C, D), which we previously demonstrated to carry wild-type CTNNB1²⁶. The MERS-CoV receptor, DPP4, was also related to β-catenin pathway activation (Supplementary Fig. 2E-G). ACE2 DNA was hypomethylatedin tumors carrying CTNNB1 mutations (Fig. 1C), which is consistent with transcriptional activation of ACE2.By contrast, TMPRSS2was hyper-methylated in HCCs carrying CTNNB1 mutations (Supplementary Fig. 3A; Supplementary Table 2), which is consistent with transcriptional repression.Neither ACE2 nor DPP4 mRNA expression were related TERT and TP53 gene mutations, which are the two most frequent ones in HCCs (Supplementary Fig. 3C, D). In turn, TMPRSS2mRNA levels were higher in HCCs carrying wild-type TP53(Supplementary Fig. 3D), which is consistent with the above-described higher expression of TMPRSS2 in the well-differentiated, non-proliferative class of HCCs,where TP53 gene mutations are rare^26,28. Indeed, TP53 mutations are most frequent in poorly-differentiated HCCs (S2²⁹; G3³⁰), showing an aggressive, cancer stem cell phenotype^26,31.

In line with the higher ACE2and DPP4mRNA expression in HCCs showing increased β-catenin pathway activation and CTNNB1 activating mutations, in silico analysis of 5,000 base pairs upstream of the transcription start sites of ACE2 and DPP4 DNAs revealed putative T-cell factor 4/LEF-1 consensus transcription factor binding sites, respectively (Fig. 1D; Supplementary Fig. 4A, B).

ACE2is immunodetected in moderately-to-well-differentiated HCCs preserving hepatocyte polarization and carrying CTNNB1 mutations.

In consistency with the above findings, immunohistochemistry followed by quantitative image analysis in tissue microarray of 41 HCCs revealed that the expression of ACE2 and of the marker of β-catenin pathway activation GLUL (glutamine synthetase) were correlated (Spearman’s R= 0.42; p= 0.00001). Both ACE2 and GLUL were 3.6 folds higher in HCCs carrying activating CTNNB1mutations than in tumors carrying wild-type CTNNB1 (Fig. 1, E-H).

HCCs with mutated CTNNB1 are frequently cholestatic and contain pseudo-glandular structures with bile plugs, where hepatocytes preserve the basal and apical poles³¹. Co-immunolabeling for ACE2 and ABCC2 (a.k.a. MRP2, a marker of the biliary pole in hepatocytes) in HCCs, detected ACE2 at the biliary pole and within the lumen of pseudo-glandular tumor structures and in slit-like bile canaliculi (Fig. 2, A,B).By contrast, ACE2 was not detected at the basal hepatocyte pole, which was highlighted by the capillary endothelial cell marker CD34 (Fig. 2C). As expected, the antibodies used detected high levels of ACE2 in the apical intestinal epithelium, Bowman’s capsule and convoluted tubes in the kidney; in turn, TMPRSS2 was detected in the apical compartment of the epithelial lining of prostatic glands (Supplementary Fig. 5). In HCCs, TMPRSS2 was also detected at the apical pole of pseudo-glandular formations or within slit-like trabecular structures and in cell-cell borders (Supplementary Fig. 6). Neither ACE2 (Supplementary Fig. 6) nor TMPRSS2 (not shown) were detected in myofibroblasts.

In five non-tumor samples from patients undergoing resection of colon cancer metastases and with minimal inflammatory changes in the liver, ACE2 was co-detected with the sinusoidal endothelial cell marker CLEC4M (a.k.a. DC-SIGNR) (Fig. 3, A, C, E) and the bile canaliculi marker ABCC2 (a.k.a. MRP2) (Fig. 3, B, D, F). The presence of ACE2 within bile canaliculi is consistent with the facts that the extracellular part of ACE2 can be cleaved off the cell surface by ADAM17, thus shedding functional ACE2 fragments³²;and that ACE2 is an abundant component of the normal human bile proteome³³. Also, ACE2 was co-detected with CD34 in capillary vessels of the periportal vascular plexus (Fig. 3G). By contrast, ACE2 was not detected in CD68-positive sinusoidal cells (Kupffer cells, Fig. 3H) or ACTA2-positive vascular smooth muscle cells or myofibroblasts (Fig. 3I,J).

ACE2 and TMPRSS2 co-expression networkshighlight metabolic functions typical of normal hepatocytes.

By Weighted Gene Correlation Network Analysis³⁴comparing periportal-type (n= 342) and perivenous-type (n=225) HCCs within the Désert’s dataset (n= 1133), wefound thatACE2 and TMPRSS2were related through interacting metabolic functions (Fig. 4A), including detoxification, aminoacid catabolism, lipid metabolism, fatty acid oxidation and catabolism of organic compounds, which is probably related to the carboxypeptidase functions of ACE2, involved in the degradation of inflammatory polypeptides^35,36(Fig. 4B). These findings are in line with the above-described expression of ACE2 and TMPRSS2 in well-to-moderately differentiated HCCs preserving the metabolic programs of adult hepatocytes.Next, we specifically investigated the ACE2 co-expression network in HCCs and analyzed associated gene functions. Not surprisingly, ACE2was associated with hepatocyte-specific functions such as aminoacid metabolism, xenobiotic detoxification, fatty acid uptake and oxidation. High ACE2 expression was associated with low expression levels of oxidative stress markers and cytokine-mediated inflammatory signals (Supplementary Fig. 7A,B). These findings raise the hypothesis of a link between inflammation, ACE2 dysfunction and metabolic breakdown that may be relevant to the pathogenesis of COVID-19.

In this work, we show that ACE2 and TMPRSS2 mRNA and protein are detected preferentially in well-to-moderately differentiated HCCs. In particular, ACE2 is detected at the biliary pole in tumors preserving hepatocyte polarization.By contrast, in non-tumor livers, ACE2 is detected not only in the epithelial lining of bile ducts andwithin hepatocyte’s bile canaliculi, but also inthe CLEC4M-positive sinusoidal endothelium and the CD34-positive capillary vessels of the periportal plexus.TMPRSS2, in turn, is not detected in normal liver, but is present at the biliary pole in well-to-moderately differentiated HCCs, which is consistent with the functional association of ACE2 and TMPRSS2 through periportal and perivenous metabolic networks.Of note, high-resolution 500-nm optical sections revealed ACE2 within hepatocyte’s bile canaliculi in histologically normal liver.This finding agrees with the high content of N-glycosylated, lectin-binding ACE2 in the normal human bile proteome³³and with the role of ACE2 in aminoacid uptake in the gut and in the regulation of the splanchnic blood flow³⁵.

In HCCs carrying activating β-catenin(CTNNB1) mutations, ACE2 DNA is hypomethylated, and ACE2 mRNA expression upregulated. Conversely, TMPRSS2 mRNA is lower in HCCs carrying mutated CTNNB1 and its DNA hypermethylated. This finding agrees with the fact that only ACE2 (and DPP4, but not TMPRSS2) contain TCF/LEF-1 binding sitesthat are predicted to respond to β-catenin transcriptional activation.Neither ACE2, nor DPP4 or TMPRSS2 are associated to TERT or TP53 gene mutations. On the contrary, HCCs containing mutated TP53 show relatively lower levels of TMPRSS2(Supplementary Fig. 3D).This association does not necessarily imply a direct regulation of TMPRSS2 by TP53,but may be coincidental. In fact, well-differentiated, periportal-type HCCs express the highest levels of TMPRSS2 and, as we previously showed, have the lowest prevalence of TP53 mutations²⁶. Nonetheless, the relationships ofACE2 and TMPRSS2with histological, transcriptomic and genomicHCC subclassesconverge to demonstrate that well-to-moderately differentiated tumors express the highest levels of this SARS-CoV-2 receptor and co-receptor couple.

The above findings agree with further observations in this work: the ACE2 co-expression network included liver-enriched genes involved in hepatocyte-specific functions, such as aminoacid metabolism (GNMT), xenobiotic detoxification (CYP3A4), fatty acid uptake, bile acid reconjugation(SLC27A5), enterohepatic circulation of bile acids and cholesterol homeostasis (SLC10A1). ACE2 was also co-expressed with SIRT1 and CD36 and the fatty acid oxidation enzymes ACADL, EHHADH, ACADM and ECI2, and alternative glucose metabolism pathways (CRYL1), as well as enzymes involved in gluconeogenesis (PCK2). This network is in line with the role of ACE2 as a regulator of fatty acid uptake in hepatocytes through the angiotensin_1-7-MAS1-SIRTUIN1-CD36 axis³⁷. Indeed, ACE2 knock-out mice show low levels of peripheral lipid uptake, but high hepatocyte uptake of triglycerides, resulting in steatosis, lipid peroxidation, oxidative stress and inflammation³⁷. In turn, the induction of oxidative stress by ACE2 deficiency may be related to its effects on glucose and lipid metabolism because the ACE2/Ang_1-7/MAS axis increases glucose uptake, decreasing insulin resistance. Thus, ACE2 knock-out mice exhibit high oxidative stress, whereas exposure to Ang_1-7 reduces oxidative stress in liver cells through insulin signaling³⁸.Taken together, this body of evidence matches the metabolic landscape of HCCs carrying activating CTNNB1 mutations. These tumors oxidize fatty acids as a source of energy to feed the oxidative phosphorylation pathway³⁹, but resist to oxidative stress⁴⁰ and suppress inflammation⁴¹.

ACE2 expression was related to gene functions that smother inflammation. Indeed, ACE2 was related to low levels of the inflammation-related transcripts BIRC3, MSN, MMP9, LTB, TNFRSF4, IL4R, CCL20and IL32, among others (Supplementary Table 3). ACE2 exerts anti-inflammatory effects through carboxyterminal cleavage of vasoactive polypeptides, such as Apelin-13, which induces vasodilation, and des-arg9-bradykinin, a neutrophil chemoattractant⁴².In turn, deletion of ACE2 leads to tissue injury and oxidative stress, through upregulation of the AT1 receptor and inflammatory cytokines like IL1β, IL6, IL17, RANTES, ICAM1, TNFα, TNFRSF1A and downregulation of the anti-inflammatory cytokine IL10⁴³. This picture is surprisingly similar to that seen in the spectrum going from immune dysregulation to macrophage activation syndrome in moderate-to-severe COVID-19^4,44.

The anti-inflammatory role of ACE2 goes well with its up-regulation in response to liver injury, such as bile-duct ligation⁴⁵and with the evidence that ACE2 produced by hepatocytes limits fibrogenesis through degradation of AngII to Ang_1-7³⁵.In human liver cirrhosis, ACE2 protein is increased by >90 folds in hepatocytes. In vitro, hypoxia increases ACE2 activity in hepatocytes, enhancing acetylcholine-induced vasodilatation³⁶. As hypoxia activates Wnt/β-catenin signaling, it would be interesting to investigate whether ACE2 expression in perivenous hepatocytes depends on β-catenin^32,46.

This body of matching data suggests that ACE2 may regulate energy metabolism, protecting against oxidative stress and inflammation. As both TMPRSS2 and ACE2 are functionally connected through metabolic pathways in the liver,it may be reasonable to hypothesize that ACE2 depletion resulting from SARS-CoV-2 infection¹⁸ may contribute to metabolic dysfunction and inflammation.Our results point to the relevance of further studies on the signaling pathways and pathological contexts leading to cell surface ACE2 availability and to the possible impact of viral infection on the disruption of theACE2 metabolic network.

Patients, samples and datasets

Human hepatocellular carcinoma (HCC): immunohistochemistry was performed on a tissue microarray composed of 41 HCC cases and two histologically normal liver controls, for which the exon 3 of β-catenin (CTNNB1) had been Sanger-sequenced, as we previously described²⁶. In addition, three formalin-fixed, paraffin-embedded non-tumor liver tissue blocks from patients undergoing resection of liver metastases from extra-hepatic cancers were added to the immunohistochemistry analysis. Tissue samples and patient data were collected and anonymized after obtaining written informed consent from the patients. De-identification was performed in accordance with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. The study was approved by Inserm’s Institutional Advisory Board (approval number 19-630). Research involving human research participants has been performed in accordance with the Declaration of Helsinki. All experiments were performed in accordance with relevant guidelines and regulations. Two different immunohistochemical methods were used to detect primary antibodies: peroxidase-labeled secondary antibodies, revealed by a chromogenic substrate or multiplex immunofluorescence followed by analysis with a confocal slide scanner. The Désert’s microarray meta-dataset composed of 1133 human HCCs was previously described²⁶.In this dataset, HCCs expressing a β-catenin-activated transcriptomic program were identified with a 5-gene signature composed of GLUL, LGR5, ODAM, VNN1 and HAL, which predicts activating CTNNB1 mutations with high sensitivity (0.86-0.91) and specificity (0.83-1.0)²⁶. β-catenin pathway activation was confirmed with an independent 23-gene signature²⁷. The publicly available TCGA dataset was composed of 370 HCCs and 47 matching non-tumor samples. RNA sequencing, mutation and methylation data were extracted as described²⁶, using the TCGAbiolinks R package. Raw mRNA expression was median-normalized (DESeq R package). DNA methylation was quantile-normalized (preprocessCore R package); probes with B-value over 0.8 or under 0.2 were respectively considered as hypermethylated or hypomethylated. The R-package Limma was used to identify differential methylation.

See Supplementary Information for a detailed description of immunohistochemical methods and statistical analyses and Supplementary Table 1 for primary, secondary antibodies, fluorochromes used, epitope unmasking and incubation conditions.

ACE2, Angiotensin-converting enzyme 2; Ang, Angiotensin; CLEC4M, C-Type Lectin Domain Family 4 Member M; DPP4, Dipeptidyl Peptidase 4; COVID-19, Coronavirus disease 2019; CTNNB1,β-catenin; HCC, Hepatocellular carcinoma; LSECs, MERS-CoV, Middle East Respiratory Syndrome Coronavirus; SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2; TCGA, The Cancer Genome Atlas; TMPRSS2, Transmembrane serine protease 2.

Acknowledgements: We thank Caroline Aninat, LatifaBousarghin, Pierre-Jean Ferron and Olivier Loréal for insightful discussions; Michèle Le Guennec, Patricia Jouas, Adina Pascu and Thomas Poussou for logistics and administrative support.

Financial support:Inserm; Univ Rennes 1; Ministère de l’Enseignement Supérieur; Institut National du Cancer, grant # INCA_12688; Ligue Nationale Contre le Cancer 2018, Comités d’Ille-et-Vilaine et Vendée.

Data availability: Datasets analyzed in this study are available at The Cancer Genome Atlas or at the Gene Expression Omnibus databases. Accession numbers and standard, publicly available R packages used are provided in the main text and supplementary files. The procedures applied for merging nine publicly available transcriptomic datasets into a meta-dataset totaling 1133 hepatocellular carcinomas have been previously published²⁶.A filtered, normalized and batch-effect-correcteduser-friendly version of this meta-dataset is available from the corresponding author upon reasonable request.

Contributors: Study design, OM, LD, LC, AC, BC; meta-datasets merge and pretreatment, LD, RD; database search, LD, LC, CL, OM;anatomic pathology analysis, BT, LC, OM; immunohistochemistry, GG; statistics, LD,LC, OM; image analysis, LC, OM; data analysis, LD, LC, OM; manuscript preparation, LD, LC, OM; manuscript editing, all authors.

Competing interests: None

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No competing interests reported.

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published 03 Feb, 2022

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Well-Differentiated Liver Cancers Reveal the Potential Link Between ACE2 Dysfunction and Metabolic Breakdown.

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