# New dimension in viral hepatitis research

Massimiliano Cocca, Barbara Testoni

► To cite this version:

Massimiliano Cocca, Barbara Testoni. New dimension in viral hepatitis research. eGastroenterology, 2024, 2 (3), pp.e100136. 10.1136/egastro-2024-100136. hal-05021379

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# New dimension in viral hepatitis research

Massimiliano Cocca ID,¹,²,³ Barbara Testoni ID ¹,²,³

**To cite:** Cocca M, Testoni B. New dimension in viral hepatitis research. *eGastroenterology* 2024;2:e100136. doi:10.1136/egastro-2024-100136

► Prepublication history for this paper is available online. To view these files, please visit the journal online (https://doi.org/10.1136/egastro-2024-100136).

MC and BT contributed equally.

Received 05 September 2024

Accepted 14 September 2024

## ABSTRACT

Chronic hepatitis B is the leading cause of hepatocellular carcinoma and a significant global health issue, affecting over 296 million people worldwide, with 15 million people coinfected with hepatitis delta virus (HDV) suffering accelerated disease progression. Recent advances in single-cell sequencing and spatial transcriptomics offer promising insights to improve the understanding of the liver's immune responses and hepatitis B virus (HBV)-infected cell distribution, with the final goal being the achievement of an HBV 'functional cure'. In this issue of *eGastroenterology*, Cross et al used the GeoMx nanostring digital spatial profiling (DSP) technology to study gene expression in the liver tissues of three patients (one HBV-monoinfected, one HBV/HDV coinfected and one HBV/human immunodeficiency virus (HIV) coinfected). Unlike other spatial transcriptomics techniques, GeoMx DSP allows targeted selection of specific tissue regions (regions of interest) for analysis, enabling precise gene expression mapping. The study revealed spatially distinct transcriptomic signatures related to immune features and viral burden, identifying a component of underinvestigated immune cells. Despite the small sample size, this proof-of-concept study demonstrates the feasibility of spatial transcriptomics in analysing HBV infections. Future advances, such as integrating viral proteins and nucleic acids, will enhance the understanding of spatial viral replication. Challenges in tissue processing, data analysis and costs remain before spatial transcriptomics can be applied as a diagnostic tool, but ongoing multiomics approaches offer promise for improved diagnosis and therapy.

Chronic hepatitis B (CHB) is a primary cause of hepatocellular carcinoma (HCC) and a major public health problem, being the most prevalent chronic infectious disease worldwide with more than 296 million individuals concerned.¹ Fifteen million chronic hepatitis B virus (HBV) carriers are also coinfected with hepatitis delta virus (HDV), resulting in an accelerated progression to cirrhosis and HCC. The management of HBV/HDV coinfected patients is limited by the low response rate to interferon therapy, and bulevirtide, an entry inhibitor, has received conditional approval from the European Medicines Agency (EMA).² Current treatments against CHB induce viral suppression but require lifelong regimens in most patients. 'HBV

functional cure', defined as sustained loss of HBV surface antigen (HBsAg) and HBV DNA off-therapy, is the grand prize of current therapeutic development since it is associated with improved liver disease outcomes.³ Eradicating or silencing of HBV genomes coupled with re-educating the liver microenvironment is considered key to establishing a sustained immune control of the infection. The World Health Organization (WHO) estimates that 8% of persons with human immunodeficiency virus (HIV) are also coinfected with HBV, a condition associated with accelerated liver disease progression and mortality.⁴ Paradoxically, despite the HIV-induced immunosuppression, the rates of HBV functional cure are higher in HIV/HBV coinfected persons compared with people infected with HBV alone.⁵

A major obstacle to the development of innovative and efficient therapeutic interventions against CHB is represented by the lack of comprehensive investigation on the interplay between intrahepatic viral burden and immune responses in relationship with liver microenvironment.

While it appears evident that the distribution of HBV-infected cells is not homogeneous across the liver lobule, recent attempts using multiplex immunofluorescence approaches have provided limited information on the interplay between viral burden and liver microenvironment.⁶⁻⁷

The implementation of fine needle aspirates (FNAs) coupled with single-cell sequencing or high-sensitive techniques for HBV detection has recently paved the way to groundbreaking studies on liver HBV persistence and immune responses.⁸⁻¹⁰ However, FNAs do not preserve liver tissue architecture, thus missing the liver spatial information.

Spatial transcriptomics (ST) has gained momentum in the last quinquennium,¹¹ becoming increasingly used either to enrich information provided by bulk RNA-seq or single-cell RNA-seq approaches through deconvolution methods,¹² ¹³ or to provide, by itself, a spatial reference for single-cell

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© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

¹INSERM U1052, CNRS UMR-5286, Cancer Research Center of Lyon, Lyon, France

²University of Lyon, Université Claude-Bernard (UCBL), Lyon, France

³The Lyon Hepatology Institute EVEREST, Lyon, France

**Correspondence to**
Dr Barbara Testoni;
barbara.testoni@inserm.fr and
Dr Massimiliano Cocca;
massimiliano.cocca@inserm.fr
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expression and cell-to-cell communication insights¹⁴ and
help researchers go from ‘causative loci’ to ‘causative
location’ when dealing with pathological phenotypes.

In this issue of *eGastroenterology*, Cross *et al*¹⁵ applied an ST approach using the GeoMx nanostring digital spatial profiling (DSP) technology to investigate the gene expression patterns associated with selected topographies of HBV-infected cells in the liver of three representative chronically infected patients (one HBV-monoinfected, one HBV/HDV coinfected and one HBV/HIV coinfected).

Different from other sequencing-based ST tech-
niques,¹⁶ ¹⁷ which provide a fixed grid of capture spots,
the GeoMX DSP platform allows the manual definition of
specific areas of the tissue (ie, regions of interest, ROIs),
where barcodes attached to tissue messenger RNAs can
be released and aspirated by a microcapillary pipette.
These barcodes can be collected and converted into a
next-generation sequencing compatible library for direct
counting. In this way, barcodes (a surrogate for bound
detection of oligonucleotides) can be mapped to ROIs
to provide a digital readout of gene expression within
the tissue context.¹⁸ ROIs can be selected by the user to
leverage any a priori knowledge of the tissue/phenotype,
providing a ‘target sequencing’-like approach.¹⁸ Although
the resolution achieved at the time of writing is still in the
order of 50–100 cells per ROI (almost an order of magni-
tude bigger than the 10x Visium, its direct competitor¹⁷),
the targeted ROI selection strategy allows for the precise
capture of the gene expression profile of the histological
structure of interest. Moreover, fluorescently labelled
antibodies can be used to segment discontinuous cells
(eg, HBsAg staining and CD45 staining in Cross *et al*¹⁵) to
perform differential expression analysis. Conversely, this
approach is not suited to obtain a map of gene expression
across the entire tissue and could introduce bias due to
the manual selection of ROIs. Like its 10x counterpart,
the expression profiles generated by the GeoMX DSP still
represent a composite, bulk-like, collection of cells; there-
fore, it is imperative to apply computational approaches
to deconvolve the cellular composition of the generated
profiles.

The proof-of-concept study presented by Cross *et al*¹⁵ provides an example of a state-of-the-art analysis workflow: (1) differentially expressed genes are identified comparing ROIs in a ‘case-control’ style; (2) pathways over-representation analysis is performed exploiting the Gene Ontology data sets; (3) a weighted gene correlation network analysis is applied to the expression values to identify clusters of genes ‘moving together’; and (4) a cell deconvolution method is used to increase the resolution to the picture the authors are providing.

This kind of workflow should be regarded as the stan-
dard approach to provide a solid starting point to investi-
gate a tissue microenvironment also in small collections
of samples.

This proof-of-concept study has the merit of demon-
strating the feasibility and utility of ST in analysing gene

expression patterns, immune cell composition and
biological processes at high resolution within the liver
microenvironment. The use of anti-HBsAg and CD45
immunostaining to drive ROI selection allowed the
identification of tissue regions with different balances
between viral burden and extent of immune infiltration.
Although the small number of samples and the high
intrasample and intersample variability severely limit the
generalisation of the conclusions, it is worth noting that
spatially discrete transcriptomic signatures relating to
immune features could be identified. Moreover, insights
were provided on underinvestigated immune subsets,
namely γδT cells, αβT cells, mature B cells and inflamma-
tory macrophages, whose proportions differed between
samples. Further advances in the interpretations of these
types of results will come once multiple viral proteins (eg,
HBsAg, HBV core antigen (HBcAg), HDV antigens) and
even viral nucleic acids would be included in the work-
flow, thus allowing a precise understanding of the spatial
distribution of cells harbouring active viral replication.

Besides the results provided by Cross *et al*¹⁵ in their study, which, limited in sample size as it is, represent one of the early applications of the GeoMx DSP technology on HBV samples with coinfection, a question is still lingering: how can we leverage the insights provided by ST to improve diagnosis and eventually tailor therapeutic interventions?

Many challenges remain to be addressed so that ST
approaches could become a proper diagnostic tool,
mainly in the tissue processing and data analysis, but also
from a cost-related side. On a technical side, there is still
the need for independent assessment of performances
to quantify the contribution of biological and technical
sources of variability. Moreover, there is a need for bench-
marks to ensure the stability of the platform and compati-
bility of data collected at different times. Additionally, the
data analysis has a long turnaround time, more consistent
with the research time span than with the one required
for a laboratory developed test.

Ideally, the best approach would be to apply ST tech-
niques to representative cohorts, increasing, for example,
the power to identify meaningful intergroup variation by
sampling different regions from the same sample, gener-
ating expression profiles for a bigger subpopulation of
cells (obviously, this calls for the additional control of
any batch effect introduced, with additional steps of
data normalisation or quality controls). Results from the
analyses performed on cohorts, also related to response
to treatments, could then inform researchers and guide
them in identifying novel diagnostic biomarkers or drug
targets that could be validated using techniques already
available in a laboratory context, providing an instrument
that will be cost-effective and more likely to be included
in the diagnostic process (figure 1).

The work of Cross *et al*¹⁵ testifies the ‘spatial’ revolution occurring in the hepatology field¹⁴ ¹⁹ ²⁰ and is expected to also transform basic and translational research in viral hepatitis. The use of formalin-fixed, paraffin-embedded (FFPE) material opens the possibility of investigating
<figure><img src="image_4.png" /><figcaption>**Figure 1** Workflow aiming at implementing spatial approaches into clinical development. Created with Biorender.com. FNA, fine needle aspirate; POC, proof-of-concept.</figcaption></figure>

large stored collections of samples. The implementation of multiomics approaches, coupling proteomics, transcriptomics and metabolomics and their integration with other modalities such as ATAC-seq (assay for transposase accessible chromatin sequencing) or ChIP-seq (chromatin immunoprecipitation sequencing) is already on the way and is expected to provide unprecedented insights into the virus-host interactions in the liver.

X Barbara Testoni @TestoniResearch

**Contributors** Writing—original draft: MC, BT. Writing—review and editing: MC, BT. Guarantor: BT.

**Funding** MC and BT are supported by grants provided by the 'Agence Nationale pour la Recherche sur le SIDA et les hepatites virales et les maladies infectieuses emergentes' (ANRSIMIE) under grant agreements ECTZ143165 and ECTZ210845, and by the French National Agency for Research (ANR, grant IHU EVEREST: ANR-23-IAHU-0008).

**Competing interests** BT receives funding from Assembly Biosciences, Beam Therapeutics, BlueJay Therapeutics and Aligos.

**Patient and public involvement** Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

**Patient consent for publication** Not required.

**Ethics approval** Not applicable.

**Provenance and peer review** Commissioned; internally peer reviewed.

**Open access** This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

**ORCID iDs**

Massimiliano Cocca http://orcid.org/0000-0002-1127-7596

Barbara Testoni http://orcid.org/0000-0001-5588-5465

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