PYRROLO[2,3-B]PYRAZINE COMPOUNDS AS CCCDNA INHIBITORS FOR THE TREATMENT OF HEPATITIS B VIRUS (HBV) INFECTION
20230248723 · 2023-08-10
Inventors
- Jitao David ZHANG (Basel, CH)
- Xingchun HAN (Shanghai, CN)
- Song YANG (Shanghai, CN)
- Miriam TRIYATNI (Basel, CH)
- Brian LEONARD (Basel, CH)
- Angelina WALLIER (Basel, CH)
- Josephine SCHMALER (Basel, CH)
- Daniel TURLEY (Basel, CH)
- Philipp TROPBERGER (Basel, CH)
- Samuel CROSET (Basel, CH)
Cpc classification
A61K31/4985
HUMAN NECESSITIES
International classification
A61K31/4985
HUMAN NECESSITIES
Abstract
The present invention relates to novel therapeutic agents against hepatitis B virus (HBV) infection, particularly inhibitors of viral covalently closed circular DNA (cccDNA) which is the key barrier for HBV cure. Accordingly, the invention provides the pyrrolo[2,3-b]pyrazine compounds of formula (I), as described and defined herein, for use in the treatment of HBV infection. The compounds provided herein are highly potent against HBV infection and enable an improved therapy, particularly of chronic HBV infection and HBV rebound. The present invention further relates to a novel screening assay for the identification of therapeutic agents against HBV infection, particularly cccDNA inhibitors, which is performed in hepatocyte-like cells that recapitulate the complete HBV life cycle following infection with patient-derived HBV.
##STR00001##
Claims
1. A method of treating a hepatitis B virus infection, the method comprising administering a compound of the following formula (I): ##STR00013## wherein: L.sup.1 is selected from —CO—N(R.sup.L1)—, —N(R.sup.L1)—CO—, —CO—, —N(R.sup.L1)—, —C(═O)O—, —O—C(═O)—, —SO—, —SO.sub.2—, —SO.sub.2—N(R.sup.L1)—, and —N(R.sup.L1)—SO.sub.2—; each R.sup.L1 is independently selected from hydrogen and C.sub.1-5 alkyl; R.sup.1 is C.sub.1-12 alkyl, C.sub.2-12 alkenyl or C.sub.2-12 alkynyl, wherein said alkyl, said alkenyl or said alkynyl is substituted with one or more groups R.sup.10, and further wherein said alkyl, said alkenyl or said alkynyl is optionally substituted with one or more groups R.sup.11; each R.sup.10 is independently selected from —OH, —O(C.sub.1-5 alkyl), and heterocyclyl having at least one oxygen ring atom; each R.sup.11 is independently selected from —O(C.sub.1-5 alkylene)-OH, —O(C.sub.1-5 alkylene)-O(C.sub.1-5 alkyl), —SH, —S(C.sub.1-5 alkyl), —S(C.sub.1-5 alkylene)-SH, —S(C.sub.1-5 alkylene)-S(C.sub.1-5 alkyl), —NH.sub.2, —NH(C.sub.1-5 alkyl), —N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), halogen, C.sub.1-5 haloalkyl, —O—(C.sub.1-5 haloalkyl), —CF.sub.3, —CN, —CHO, —CO—(C.sub.1-5 alkyl), —COOH, —CO—O—(C.sub.1-5 alkyl), —O—CO—(C.sub.1-5 alkyl), —CO—NH.sub.2, —CO—NH(C.sub.1-5 alkyl), —CO—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —NH—CO—(C.sub.1-5 alkyl), —N(C.sub.1-5 alkyl)-CO—(C.sub.1-5 alkyl), —SO.sub.2—NH.sub.2, —SO.sub.2—NH(C.sub.1-5 alkyl), —SO.sub.2—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —NH—SO.sub.2—(C.sub.1-5 alkyl), —N(C.sub.1-5 alkyl)-SO.sub.2—(C.sub.1-5 alkyl), carbocyclyl, and heterocyclyl, wherein said carbocyclyl and said heterocyclyl are each optionally substituted with one or more groups R.sup.12; and further wherein any two groups R.sup.11 that are bound to the same carbon atom may optionally form, together with the carbon atom that they are attached to, a 5- to 8-membered carbocyclic or heterocyclic ring, wherein said 5- to 8-membered carbocyclic or heterocyclic ring is optionally substituted with one or more groups R.sup.12; each R.sup.12 is independently selected from C.sub.1-5 alkyl, C.sub.2-5 alkenyl, C.sub.2-5 alkynyl, —(C.sub.0-3 alkylene)-OH, —(C.sub.0-3 alkylene)-O(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SH, —(C.sub.0-3 alkylene)-S(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH.sub.2, —(C.sub.0-3 alkylene)-NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-halogen, —(C.sub.0-3 alkylene)-(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-O—(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-CF.sub.3, —(C.sub.0-3 alkylene)-CN, —(C.sub.0-3 alkylene)-CHO, —(C.sub.0-3 alkylene)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-COOH, —(C.sub.0-3 alkylene)-CO—O—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-O—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—NH.sub.2, —(C.sub.0-3 alkylene)-CO—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—NH.sub.2, —(C.sub.0-3 alkylene)-SO.sub.2—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—SO.sub.2—(C.sub.1-5 alkyl), and —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-SO.sub.2—(C.sub.1-5 alkyl); R.sup.2 is selected from hydrogen, C.sub.1-5 alkyl, C.sub.2-5 alkenyl, C.sub.2-5 alkynyl, —(C.sub.0-3 alkylene)-OH, —(C.sub.0-3 alkylene)-O(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SH, —(C.sub.0-3 alkylene)-S(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH.sub.2, —(C.sub.0-3 alkylene)-NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-halogen, —(C.sub.0-3 alkylene)-(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-O—(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-CF.sub.3, —(C.sub.0-3 alkylene)-CN, —(C.sub.0-3 alkylene)-CHO, —(C.sub.0-3 alkylene)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-COOH, —(C.sub.0-3 alkylene)-CO—O—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-O—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—NH.sub.2, —(C.sub.0-3 alkylene)-CO—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—NH.sub.2, —(C.sub.0-3 alkylene)-SO.sub.2—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—SO.sub.2—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-SO.sub.2—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-carbocyclyl, and —(C.sub.0-3 alkylene)-heterocyclyl, wherein the carbocyclyl moiety of said —(C.sub.0-3 alkylene)-carbocyclyl and the heterocyclyl moiety of said-(C.sub.0-3 alkylene)-heterocyclyl are each optionally substituted with one or more groups R.sup.12; R.sup.3 is selected from hydrogen, C.sub.1-5 alkyl, and —CO(C.sub.1-5 alkyl); and R.sup.4 and R.sup.5 are each independently selected from hydrogen, C.sub.1-5 alkyl, C.sub.2-5 alkenyl, C.sub.2-5 alkynyl, —(C.sub.0-3 alkylene)-OH, —(C.sub.0-3 alkylene)-O(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SH, —(C.sub.0-3 alkylene)-S(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH.sub.2, —(C.sub.0-3 alkylene)-NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-halogen, —(C.sub.0-3 alkylene)-(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-O—(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-CF.sub.3, —(C.sub.0-3 alkylene)-CN, —(C.sub.0-3 alkylene)-CHO, —(C.sub.0-3 alkylene)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-COOH, —(C.sub.0-3 alkylene)-CO—O—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-O—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—NH.sub.2, —(C.sub.0-3 alkylene)-CO—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—NH.sub.2, —(C.sub.0-3 alkylene)-SO.sub.2—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—SO.sub.2—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-SO.sub.2—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-carbocyclyl, and —(C.sub.0-3 alkylene)-heterocyclyl, wherein the carbocyclyl moiety of said —(C.sub.0-3 alkylene)-carbocyclyl and the heterocyclyl moiety of said-(C.sub.0-3 alkylene)-heterocyclyl are each optionally substituted with one or more groups R.sup.12; or a pharmaceutically acceptable salt thereof.
2. The method of claim 1, wherein L.sup.1 is —CO—N(R.sup.L1)—.
3. The method of claim 1, wherein R.sup.1 is C.sub.2-10 alkyl, wherein said alkyl is substituted with one or more groups R.sup.10, and further wherein said alkyl is optionally substituted with one or more groups R.sup.11.
4. The method of claim 1, wherein R.sup.1 is —C(R.sup.13)(R.sup.13)—C(R.sup.13)(R.sup.13)—R.sup.10, wherein each R.sup.13 is independently selected from hydrogen, methyl and ethyl, wherein each R.sup.13 is optionally substituted with one or more groups R.sup.10, and wherein each R.sup.13 is optionally further substituted with one or more groups R.sup.11.
5. The method of claim 1, wherein each R.sup.10 is —OH.
6. The method of claim 1, wherein each R.sup.11 is independently selected from —SH, —S(C.sub.1-5 alkyl), —NH.sub.2, —NH(C.sub.1-5 alkyl), —N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), halogen, C.sub.1-5 haloalkyl, —O—(C.sub.1-5 haloalkyl), —CF.sub.3, and —CN; and further wherein any two groups R.sup.11 that are bound to the same carbon atom may optionally form, together with the carbon atom that they are attached to, a saturated 5- or 6-membered carbocyclic or heterocyclic ring, wherein said saturated 5- or 6-membered carbocyclic or heterocyclic ring is optionally substituted with one or more groups R.sup.12.
7. The method of claim 1, wherein R.sup.2 and R.sup.3 are each hydrogen.
8. The method of claim 1, wherein one of R.sup.4 and R.sup.5 is carbocyclyl or heterocyclyl, wherein said carbocyclyl or said heterocyclyl is optionally substituted with one or more groups R.sup.12, and the other one of R.sup.4 and R.sup.5 is selected from hydrogen, C.sub.1-5 alkyl, C.sub.2-5 alkenyl, C.sub.2-5 alkynyl, —(C.sub.0-3 alkylene)-OH, —(C.sub.0-3 alkylene)-O(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SH, —(C.sub.0-3 alkylene)-S(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH.sub.2, —(C.sub.0-3 alkylene)-NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-halogen, —(C.sub.0-3 alkylene)-(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-O—(C.sub.1-5 haloalkyl), —(C.sub.0-3 alkylene)-CF.sub.3, —(C.sub.0-3 alkylene)-CN, —(C.sub.0-3 alkylene)-CHO, —(C.sub.0-3 alkylene)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-COOH, —(C.sub.0-3 alkylene)-CO—O—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-O—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—NH.sub.2, —(C.sub.0-3 alkylene)-CO—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-CO—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-CO—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—NH.sub.2, —(C.sub.0-3 alkylene)-SO.sub.2—NH(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-SO.sub.2—N(C.sub.1-5 alkyl)(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-NH—SO.sub.2—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-N(C.sub.1-5 alkyl)-SO.sub.2—(C.sub.1-5 alkyl), —(C.sub.0-3 alkylene)-carbocyclyl, and —(C.sub.0-3 alkylene)-heterocyclyl, wherein the carbocyclyl moiety of said —(C.sub.0-3 alkylene)-carbocyclyl and the heterocyclyl moiety of said-(C.sub.0-3 alkylene)-heterocyclyl are each optionally substituted with one or more groups R.sup.12.
9. The method of claim 1, wherein R.sup.5 is cyclopropyl.
10. The method of claim 1, wherein R.sup.4 is hydrogen.
11. The method of claim 1, wherein said compound is a compound of the following formula (II): ##STR00014## wherein the groups R.sup.1, R.sup.L1, R.sup.2, R.sup.3 and R.sup.4 have the same meanings as in formula (I); or a pharmaceutically acceptable salt thereof.
12. The method of claim 1, wherein said compound is a compound having any one of the following formulae, or a pharmaceutically acceptable salt thereof: ##STR00015##
13. The method of claim 1, wherein said compound is a compound having any one of the following formulae, or a pharmaceutically acceptable salt thereof: ##STR00016##
14. The method of claim 1, wherein said compound is a compound of the following formula: ##STR00017## or a pharmaceutically acceptable salt thereof.
15.-18. (canceled)
19. The method of claim 1, wherein said hepatitis B virus infection is a chronic hepatitis B virus infection.
20.-21. (canceled)
22. A method of treating or suppressing hepatitis B virus reactivation, the method comprising administering a compound as defined in claim 1 to a subject in need thereof.
23. The claim 1, wherein the subject to be treated is a human.
24. (canceled)
25. A method of identifying an inhibitor of hepatitis B virus (HBV) cccDNA, the method comprising: providing stem cell-derived hepatocyte-like cells infected with HBV; subjecting a test compound to the stem cell-derived hepatocyte-like cells infected with HBV; determining the inhibitory effect of the test compound on HBsAg and HBeAg in the infected stem cell-derived hepatocyte-like cells; optionally determining the inhibitory effect of the test compound on albumin in the infected stem cell-derived hepatocyte-like cells and, if the test compound has been found to inhibit albumin, excluding it from further testing; if the test compound has been found to inhibit HBsAg and HBeAg, determining the inhibitory effect of the test compound on HBV pgRNA; if the test compound has been found to inhibit HBV pgRNA, determining the inhibitory effect of the test compound on HBV cccDNA; and if the test compound has been found to inhibit HBV cccDNA, selecting the test compound as an inhibitor of HBV cccDNA.
26. The method of claim 25, wherein the step of providing stem cell-derived hepatocyte-Ike cells infected with HBV comprises: treating induced pluripotent stem cells with the compound MB-1 or MB-2 or a pharmaceutically acceptable salt thereof ##STR00018## to obtain stem cell-derived hepatocyte-like cells; and infecting the cells thus obtained with a clinical HBV isolate to obtain the stem cell-derived hepatocyte-like cells infected with HBV.
27. The method of claim 25, wherein the stem cell-derived hepatocyte-like cells are infected with clinical HBV isolates from at least the HBV genotypes A, B, C and D.
Description
[0136] The invention is also described by the following illustrative figures. The appended figures show:
[0137]
[0138]
[0139]
[0140]
[0141]
[0142]
[0143]
[0144]
[0145]
[0146]
[0147]
[0148]
[0149]
[0150]
[0151]
[0152]
[0153]
[0154] The invention will now be described by reference to the following examples which are merely illustrative and are not to be construed as a limitation of the scope of the present invention.
EXAMPLES
Example 1: Phenotypic Screening in Stem Cell-Derived Hepatocyte-Like Cells that Recapitulate Complete HBV Life Cycle from Clinical Isolates to Discover cccDNA Inhibitors
Methods
Patient Sera Purification
[0155] HBV from sera of CHB individuals were purified using OptiPrep™ (Axis-Shield, Norway) density gradient. Briefly, OptiPrep™ stock solution (60%) was diluted to 50% and 10% in PBS; equal volume of each solution was then added into SW41 tubes (BD Biosciences). Linear gradient was performed by placing the tubes on Gradient Master 108™ (Biocomp) at setting: 800, 25 rpm for 30″. Two hundred microliter (200 μl) of serum was overlaid on the top of gradient and samples were centrifuged at 100,000×g for 2 hours at 4° C. Fractions (500 μl) were collected from the top, and aliquots for each fraction were analyzed for HBV DNA using core primers 5′-CTGTGCCTTGGGTGGCTTT (forward), 5′-AAGGAAAGAAGTCAGAAGGCAAAA (reverse), 56-FAM/AGCTCCAAATTCTTTATAAGGGTCGATGTCCATG/31ABlk_FQ/(probe) (Werle-Lapostolle et al., 2004) and HBsAg. Fractions containing the peak of HBV DNA were pooled and used as virus inoculum for all infection experiments. All fractions were stored at −80° C. until used.
iPS-Derived Hepatocyte-Like Cells (HLC)
[0156] Cryopreserved HLC were thawed and seeded according to manufacturer's recommendation. Briefly, cryopreserved cells were thawed in a 37° C. water bath for 2 min, and the content of cryovial was poured into the 15 ml tube containing 12 ml of 37° C. iCell Hepatocytes Medium B (KryoThaw Component A 7.8 ml, KryoThaw Component B 4.2 ml). The tube was inverted slowly (˜5 times) then centrifuged at 110×g at room temperature for 10 minutes. After medium was aspirated, 2 ml of RT iCell Hepatocytes Medium C (RPMI containing B27 supplement, Oncostatin M 20 ng/ml, dexamethasone 1 μM, and gentamicin 25 μg/ml) was added, and cells were counted. Cell suspension was then diluted in Medium C containing Matrigel 0.25 mg/ml at 1 million cells/ml. Cells were seeded onto a collagen 1-coated cell culture plate at 40,000 cells/well (384-well plate), or 100,000 cells/well (96-well plate), and cultured at 37° C. incubator in a humidified atmosphere with 5% CO.sub.2. Culture medium was replaced 24 hr post-plating with Medium D (RPMI containing B27 supplement, Oncostatin M 20 ng/ml, dexamethasone 0.1 μM, and gentamicin 25 μg/ml) containing Matrigel 0.25 mg/ml and 1 μM MB-1. Fresh medium and MB-1 was changed every 2 day.
HLC Maturation Screening
[0157] HLC are seeded on collagen 1-coated 96-well plates in 100 μl medium D containing Matrigel 0.25 mg/ml. The next day (day 1), compound library was added to cells at a final concentration 4 μM in 1% DMSO. Fresh medium and compound was replenished 2 days later (day 3). At day 4, cells were harvested using Cells-to-Ct lysis kit (Ambion/Thermo Fisher), total RNAs were reverse-transcribed, and the resulting cDNA products were loaded into the microfluidic 96.96 Dynamic Array™ IFC and assayed against 32 liver-enriched genes on Biomark HD system (Fluidigm). The relative gene expression was calculated from delta Ct values using house-keeping gene (PPIA) in DMSO control as reference; delta Ct values were then converted to fold-change values. Compounds that increased liver-enriched gene expression in HLC ≥3-fold compared to DMSO control were further tested in dose-response (1, 5, 10, and 50 μM). The secondary screen was performed as above using 96-liver enriched genes. The top candidate (MB-1) was used for all experiments utilizing HLC.
PXB-PHH
[0158] Fresh primary human hepatocytes (PXB-PHH) harvested from humanized mice (uPA/SCID mice)—herein called PHH—were obtained from PhoenixBio Co., Ltd (Japan). Cells were seeded on a collagen I-coated plate at the following cell density: 35,000 cells/well (384-well), 70,000 cells/well (96-well), or, 400,000 cells/well (24-well) in modified hepatocyte clonal growth medium (dHCGM). dHCGM is a DMEM medium containing 100 U/ml Penicillin, 100 μg/ml Streptomycin, 20 mM Hopes, 44 mM NaHCO.sub.3, 15 μg/ml L-proline, 0.25 μg/ml insulin, 50 nM Dexamethazone, 5 ng/ml EGF, 0.1 mM Asc-2P, 2% DMSO and 10% FBS (Ishida et al., 2015). Cells were cultured at 37° C. incubator in a humidified atmosphere with 5% CO.sub.2. Culture medium was replaced 24 h post-plating and every 2 days until harvest.
HBV Infection and Compound Treatment
[0159] Following 4 day of maturation with 1 μM MB-1, HLC were incubated with HBV (purified from CHB individuals) at multiplicity of infection (MOI) 10-40 without PEG for 24 hr; virus inoculum was removed the following day. HBV infection in PHH was performed at MOI 40+4% PEG. Compound treatment in HLC and PHH was started at day 3 post infection. Compound (in powder) was dissolved in DMSO; the final concentration of DMSO added to cells is 1%. Fresh compound was replenished every 2 day until cells were harvested at day 10 (PHH), or day 14 (HLC). Compound effect on HBV and cellular toxicity was measured by multiplex assay (HBsAg, HBeAg, albumin), branched DNA (pgRNA), or digital PCR (cccDNA) and depicted as % of inhibition compared to DMSO control. Graphs were prepared using Spotfire software.
High Throughput Screening (HTS)
[0160] HLC seeded in collagen 1-coated 384-well plates were treated with 1 μM MB-1 for 4 day (medium and compound was replenished every 2 day). At day 4, cells were infected with HBV (purified from sera of CHB individuals) at MOI 40 for 24 hr; virus inoculum was removed and fresh medium was added. At day 3 pi, compound library were added at final concentration of 4 μM in 1% DMSO; fresh medium and compound were replenished every 2 day until day 14. Throughout 18-day HTS assay, cells were cultured at 37° C. incubator in a humidified atmosphere with 5% CO.sub.2; all liquid handlings were carried out with robotic equipment in BSL3** facility. At day 14 pi, culture media were harvested and processed for multiplex assay. Approximately 20,000 compounds were screened in each run.
HTS Readouts
Multiplex Assay—Primary Readout
[0161] A custom, Luminex-based multiplex assay that simultaneously measured HBeAg, albumin, and HBsAg was developed by Radix BioSolutions (Georgetown, Tex.). This is a sandwich immunoassay; each capture antibody was coupled with xMAP™ Luminex magnetic beads. The dynamic ranges of analyte detection are as follows: HBeAg (1-316 ng/ml), albumin (3.1-10,000 ng/ml), and HBsAg (0.1-100 ng/ml) with coefficient variant (CV) 525%. Samples were read on FlexMAP 3D (Luminex) and analyzed by Genedata software. The table below showed that multiplexed beads and detection antibodies against each analyte did not cross-reactive between analytes (numbers reported as mean fluorescence intensity/MFI).
TABLE-US-00001 Conc. Standard ng/ml HBeAg HBsAg Albumin HBeAg 316 2901 85 61 3056 88 59 HBsAg 100 27 6865 60 29 7349 57 Albumin 10,000 27 68 5143 33 70 5607 Blank 0 31 69 63 27 65 57
pgRNA Assay (Branched DNA)—Secondary Readout
[0162] Levels of pgRNA in infected cells (96-well plate) were measured using QuantiGene Singleplex 2.0 assay (Affymetrix), a hybridization-based assay that utilizes the xMAP™ Luminex magnetic beads and branched DNA (bDNA) signal amplification technology. The assay is performed in 96-well plate according to manufacturer's recommendation. Briefly, cells were lysed and lysates were incubated with HBV probe sets panel at 50-55° C. for 30 min then stored at −80° C. Signal amplification is achieved via sequential hybridization of PreAmplifier, Amplifier, and Label Probe. After adding Streptavidin phycoerythrin (SAPE) substrate, the signal is read using a FlexMap 3D (Luminex) instrument.
cccDNA Assay (Digital PCR)—Third Readout
[0163] HBV-infected cells (in 384- or 96-well plate) were lysed with Cells-to-CT Lysis Reagents according to manufacturer's instruction (Thermo Scientific). To remove excess of RC-DNA, samples were digested with T5 exonuclease (10 U) (New England Biolabs), at 37° C. for 1 hr; enzyme was inactivated by heating the samples at 80° C. for 15 min. DNA samples (1.2 μl) were added into the digital PCR Master Mix (QuantStudio Digital PCR Kit, Thermo Scientific) containing cccDNA primers 5′-CTCCCCGTCTGTGCCTTCT (forward), 5′-GCCCCAAAGCCACCCAAG (reverse), and CGTCGCATGGAGACCACCGTGAACGCC (probe) (Werle-Lapostolle et al., 2004) in a total volume 5 μl, and loaded into dPCR array using AccuFill System (AB). Each sample was loaded into 4 subarrays/256 through-holes. Digital PCR assay was run on QuantStudio 12K Flex (AB) and data was analyzed by Digital Suite Software (AB).
cccDNA Assay (Southern Blot)—Confirmation/Fourth Readout
[0164] HLC or PHH were seeded in 12-well plate format and infected with HBV as described above. At day 10, HIRT extracts were prepared from cells as follows. Briefly, 500 μl HIRT lysis buffer was added to each well and lysates from three wells were combined to isolate protein-free HBV DNA following the standard HIRT extraction procedure (Cai et al., 2013). For Southern blot analysis, 0.2 μl of Quick-Load 1-kb DNA ladder (New England Biolabs), 2 μg of a 1×HBV genome-length (3.2 kb) PCR product (Primer P1/P2, Guenther et al., 1995), and 5 μg of HIRT-extracted DNA were loaded per lane and separated by electrophoresis in a 1.0% (wt/vol) agarose gel in 1× Tris-Acetate-EDTA buffer at 50V for 3.5 h. After electrophoresis, the DNA was depurinated, denatured, and neutralized as described (Cai et al., 2013) then transferred onto Hybond XL membrane (Amersham) using TurboBlotter system (GE Healthcare). HBV DNA was detected with a DIG-labeled (+) strand HBV RNA probe transcribed from a 1×HBV genome-length (3.2 kb) PCR product with T7 Promoter (HBV T7+Forward Primer 5′-TAATACGACTCACTATAGGGTTTTCACCTCTGCCTAATCATC-3′, HBV Reverse Primer 5′-CCTCTAGAGCGGCCGCAAAAAGTTGCATGGTGCTGGT-3′) using the DIG Northern Starter Kit (Roche) according to manufacturer's instructions. Mitochondrial DNA was detected with an RNA probe binding to the ND1 gene region of the mitochondrial genome (Ducluzeau et al., 1999). Hybridization, washes, and detection with CDP-Star (Roche) were carried out according to manufacturer's instructions. Images were acquired with a FUSION Fx (Vilber) and bands quantified by densitometry using the FUSION-CAPT software.
Immunostaining Immunostaining was performed using Image-iT™ Fixation/Permeabilization kit (Thermo Fisher, cat #R37602). At day 10 pi, cells were fixed in 1 ml of Fixative solution for 15 min at room temperature (RT), then washed three times with 2 ml of Wash buffer for 2-5 min. Cells were incubated with primary and subsequently, secondary, antibodies diluted in D-PBS buffer containing 3% BSA, fraction V, de-lipidated, New Zealand source, each for 1 hr at RT. Primary antibodies: anti-HBs mAb, MAK_M_RF18 (Roche) at 1.25 μg/mL, or, anti-HBV core antibody at 0.1 μg/mL (DAKO, Cat no. B0586). Secondary antibodies: goat anti-rabbit IgG (H+L) cross-adsorbed secondary antibody, Alexa Fluor 594 (Thermo Fisher cat no. A-11012), or, goat anti-mouse IgG (H+L) cross-adsorbed secondary antibody, Alexa Fluor 488 (Thermo Fisher cat no. A-11001) at 2 μg/ml. After three washes with 2 ml Wash buffer for 2-5 min, cells were incubated with Hoechst 33342, Trihydrochloride, Trihydrate (Thermo Fisher cat no. H3570) at 1 μg/ml for 15 min at RT. Immunostaining was analyzed with Axio Observer inverted microscope (Zeiss) and Zeiss ZEN Software.
Molecular Phenotyping
[0165] At day 3 pi, cells were treated with compound or 1% DMSO for 6 hr. Total RNA was extracted using RLT buffer (QIAGEN, Hombrechtikon, Switzerland) and samples were stored at −80° C. Ten (10) ng of total RNA from each biological replicate was reverse-transcribed; the cDNA product was amplified according to the protocol supplied with the Ion AmpliSeq™ RNA Library Kit (Life Technologies, Carlsbad, USA, Catalog number 4482335). After primer digestion, adapters and barcodes were ligated to the amplicons followed by magnetic bead purification. The purified library was amplified, purified and stored at −20° C. Amplicon size and DNA concentration was measured using an Agilent High Sensitivity DNA Kit (Agilent Technologies, Waldbronn, Germany) according to the manufacturer's guide. Pathway analysis was performed with the CAMERA method (Wu & Smyth, 2012) and gene sets in an internally available database (RONET) which integrates publicly available gene sets such as MSigDB (Liberzon et al., 2011) and REACTOME (Fabregat et al., 2016). Results of CAMERA are represented by enrichment scores, which are defined by the absolute log 10-transformed p-value returned by CAMERA multiplied by either +1 (positive regulation of the gene set) or −1 (negative regulation of the gene set).
Results
[0166] Identification of a Small Molecule that Enhanced Maturation of HLC
[0167] To fully manifest the potential of HLC as a disease-relevant assay for HBV drug discovery, they have to meet the following criteria: hepatocyte-likeness, scalability, assay robustness, and reproducibility. It is well known that HLC still display immature phenotypes i.e. resemble more fetal than adult, hepatocytes (Baxter et al., 2015; Godoy et al., 2015; Goldring et al., 2017). The difficulties to obtain fully mature HLC with current protocols are multifactorial, including variability of donor origin (Kajiwara et al., 2012; Heslop et al., 2017), and culture conditions that poorly emulate the complexity of liver architecture including liver zonation (Goldring et al., 2017). Indeed, hepatocytes differentially expressed key liver genes and consequently, different metabolic functions, depending on their location along the porto-central axis of the liver (Halpern et al., 2017; Soto-Gutierrez et al., 2017; Torre et al., 2010). Another critical issue for the application of HLC in drug discovery is scalability; billions of cells (with high purity and minimal batch-to-batch variability) are needed to run HTS and subsequent iterative rounds of hit follow up. The inventors chose HLC from a commercial source (CDI, Madison, Wis.) and their first effort was to improve its maturation using a small molecule library consisting of ˜700 biologically active compounds. Cells were cultured according to manufacturer's recommendation (Lu et al., 2016) and incubated with compound library (4 μM). To identify hits that enhanced hepatic maturation, the inventors applied a two-step screening cascade based on up-regulation of 32 (first screen) or 96 (second screen) liver-enriched genes (see
TABLE-US-00002 TABLE 1 List of liver-enriched genes used for primary (32) and secondary (96) screens in Hepatic Maturation Screen First screen (32 genes) Second screen (96 genes) Gene Gene Gene Gene Symbol Description Symbol Description Symbol Description Symbol Description SLC10A1 Bile Acid Synthesis ABCB1 Transporters CYP2C9 Phase 1 metabolizing FN1 EMT mesenchymal enzymes KRT19 Biliary Epithelial Markers ABCB11 Transporters CYP2D6 Phase 1 metabolizing S100A4 EMT mesenchymal enzymes AFP General hepatocyte ABCC1 Transporters CYP2E1 Phase 1 metabolizing OCLN EMT Epithelial enzymes DLK1 General hepatocyte ABCC2 Transporters CYP3A4 Phase 1 metabolizing TJP1 EMT Epithelial enzymes DPP4 General hepatocyte SLC01B3 Transporters CYP3A5 Phase 1 metabolizing CDH1 EMT enzymes FM02 General hepatocyte SLC3A1 Transporters CYP3A7 Phase 1 metabolizing FOXC2 EMT enzymes FM03 General hepatocyte TBC1D9 Transporters GCLC Others SLUG EMT IFI16 General hepatocyte CEBPa Transcription factors GCLM Others SNAIL EMT NAT2 General hepatocyte FOXA1/A2 Transcription factors NFE2L2 Others FGA Clotting factors THRSP General hepatocyte GATA4 Transcription factors CPS1 Mitochondrial GCKR Carbohydrate Metabolism Metabolism PPIA Housekeeping HNF1a Transcription factors HMGCS2 Mitochondrial PCK2 Carbohydrate Metabolism Metabolism RPLPO Housekeeping HNF4a Transcription factors CLDN1 Junction protein SLC37A4 Carbohydrate Metabolism GJA1 Junction protein HNF6a Transcription factors GJB1 Junction protein GGT1 Biliary Markers CYP2C19 Phase 1 metabolizing enzymes LIN28B Transcription factors PPIA Housekeeping SOX9 Biliary Markers CYP2C8 Phase 1 metabolizing enzymes Nanog Transcription factors RPLPO Housekeeping SPP1 Biliary Markers CYP2D6 Phase 1 metabolizing enzymes NR1I2 Transcription factors AAT General hepatocyte KRT18 Biliary Epithelial Markers CYP2E1 Phase 1 metabolizing enzymes NR1I3 Transcription factors AFP General hepatocyte KRT19 Biliary Epithelial Markers CYP3A4 Phase 1 metabolizing enzymes OCT3/4 Transcription factors ALB General hepatocyte KRT7 Biliary Epithelial Markers CYP3A5 Phase 1 metabolizing enzymes SOX17 Transcription factors DLK1 General hepatocyte KRT8 Biliary Epithelial Markers CYP3A7 Phase 1 metabolizing enzymes ASPGR1 Receptors DPP4 General hepatocyte CYP7A1 Bile Acid Synthesis GSTA1 Phase 2 metabolizing enzymes RXR Receptors FM03 General hepatocyte NR1H4 Bile Acid Synthesis GSTP1 Phase 2 metabolizing enzymes CP Plasma Proteins IFI16 General hepatocyte SLC10A1 Bile Acid Synthesis CEBPa Transcription factors HAMP Plasma Proteins NAT2 General hepatocyte APOF Transporters GATA4 Transcription factors LRP1 Plasma Proteins TAT General hepatocyte GST1M1 Phase 2 metabolizing enzymes HNF6a Transcription factors GSTA1 Phase 2 metabolizing TF General hepatocyte SULT 1A1 Phase 2 metabolizing enzymes enzymes LIN28B Transcription factors GSTA2 Phase 2 metabolizing THRSP General hepatocyte CYP1A2 Phase 1 metabolizing enzymes enzymes NR1I2 Transcription factors GSTP1 Phase 2 metabolizing TTR General hepatocyte GJA1 Junction protein enzymes NR1I3 Transcription factors UGT1A1 Phase 2 metabolizing VIM General hepatocyte ACTB Housekeeping enzymes ABCB1 Transporters CYP2A6 Phase 1 metabolizing APOB Fatty Acid /cholesterol GAPDH Housekeeping enzymes ABCC2 Transporters CYP2B6 Phase 1 metabolizing CCND1 EMT nuclear B-catenin FM02 General hepatocyte enzymes APOF Transporters CYP2C19 Phase 1 metabolizing MMP7 EMT nuclear B-catenin CDH13 EMT Epithelial enzymes SLC3A1 Transporters CYP2C8 Phase 1 metabolizing COL1A1 EMT mesenchymal GCK Carbohydrate enzymes Metabolism
TABLE-US-00003 TABLE 2 List of 237 liver-enriched genes (liver signatures, specificity Gini index >0.7) that are upregulated by MB-1 (Part I) MB-1 0.5 μM MB-1 5 μM Gene ID Description Gene Symbol 2 hour 24 hour 7 day 2 hour 24 hour 7 day MAX 2938 glutathione S-transferase alpha 1 GSTA1 0.24 4.23 24.58 1.56 7.48 31.63 31.63 389434 iodotyrosine deiodinase IYD −1.25 12.21 12.43 0.75 21.44 18.22 21 44 7276 transthyretin TTR 0.08 2.3 10.99 −0.27 3.43 20.53 20.53 563 alpha-2-glycoprotein 1, zinc-binding AZGP1 −0.86 1.5 13.49 0.75 3.05 9.89 19.89 27165 glutaminase 2 GLS2 1.56 8.8 6.62 0.53 18.17 11.68 18.17 118471 proline rich acidic protein 1 PRAP1 −0.69 3.17 14.80 0.92 4.70 17.93 17.93 10 N-acetyltransferase 2 NAT2 −084 3.06 11.30 −1.15 8.45 16.77 16.77 2161 coagulation factor XII F12 −0.22 3.94 11.77 0.05 8.34 16.35 16.35 1776 deoxyribonuclease 1 like 3 DNASE1L3 −3.7 6.02 2.24 7.62 15.86 3.42 15.86 92292 glycine-N-acyltransferase like 1 GLYATL1 −1.40 8.04 6.10 −1.43 15.45 9.29 15.45 8608 retinol dehydrogenase 16 RDH16 0.13 6.92 4.23 1.93 14.76 6.54 14.76 6359 C-C motif chemokine ligand 15 CCL15 2.42 8.52 7.01 1.84 14.72 9.18 14.72 1373 carbamoyl-phosphate synthase 1 CPS1 0.27 4.44 9.95 −0.22 5.96 14.54 14.54 164656 transmembrane serine protease 6 TMPRSS6 −0.4 5.55 10.36 0.83 9.99 14.46 14.46 18 4-aminobutyrate aminotransferase ABAT 0.4 9.12 4.76 −0.05 14.19 8.35 14.19 8856 nuclear receptor subfamily 1 group I NR1I2 0.07 7.74 5.22 −0.70 14.11 9.34 14.11 member 2 5009 ornithine carbamoyltransferase OTC 2.26 4.51 10.37 −2.45 8.61 14.06 14.06 64241 ATP binding cassette subfamily G ABCG8 −0.07 8.03 4.34 1.00 13.95 5.74 13.95 member 8 3242 4-hydroxyphenylpyruvate dioxygenase HPC 0.78 5.9 10.14 1.87 11.69 13.93 13.93 346606 monoacylglycerol O-acyltransferase 3 MOGAT3 0.51 6.41 10.45 0.48 11.58 13.93 13.93 2203 fructose-bisphosphatase 1 FBP1 −0.25 3.09 8.27 −0.07 9.95 13.54 13.54 5207 6-phosphofructo-2-kinase/fructose- PFKFB1 058 4.9 8.94 −1.19 7.32 13.52 13.52 2,6-biphosphatase 1 54898 ELOVL fatty acid elongase 2 ELOVL2 0.08 7.59 3.21 1.20 13.47 8.5 13.47 259 alpha-1-microglobulin/bikunin AMBP 0.28 0.64 5.10 −0.24 2.97 13 24 13.24 precursor 1962 enoyl-CoA hydratase and 3- EHHADH 1.00 5.80 6.83 0.24 10.39 13.14 13.14 hydroxyacyl CoA dehydrogenase 335 apolipoprotein A1 APOA1 −0.42 3.85 9.25 1.27 6.04 12.94 12.94 1557 cytochrome P450 family 2 subfamily C CYP2C19 −0.58 1.79 4.27 1.02 2.88 1292 12.92 member 19 213 albumin ALB −0.21 3.5 8.33 −0 96 6.19 12.79 12.79 23475 quinolinate phosphoribosyltransferase QPRT −0.41 7.96 4.77 0.01 12.78 7 28 12.78 6718 aldo-keto reductase family 1 member AKR1D1 0.83 6.77 5.29 1.03 12.61 7.82 12.61 D1 6718 aldo-keto reductase family 1 member AKR1D1 0.83 6.77 5.29 1.03 12.61 782 12.61 D1 83758 retinol binding protein 5 RBP5 0.78 5.76 8.97 0.19 7.48 12.56 12.56 10157 aminoadipate-semialdehyde synthase AASS −1.29 2.2 829 1.02 −0.97 12 39 12.39 1244 ATP binding cassette subfamily C ABCC2 0.2 4.37 4.32 −1.98 12.21 5.35 12.21 member 2 54490 UDP glucuronosyltransferase family 2 UGT2B28 0.96 4.63 4.9 1.59 12.19 8.06 12.19 member B28 26998 fetuin B FETUB −1.85 5.16 8.24 −0.24 9.52 11.90 11.90 92840 receptor accessory protein 6 REEP6 0.27 4.42 6.66 1.39 10.43 11.85 11.85 345 apolipoprotein C3 APOC3 −1.41 3.88 9.75 −0.26 4.65 11.61 11.61 5267 serpin family A member 4 SERPINA4 −0.79 3.9 3.30 1.27 10.41 11.57 11.57 2159 coagulation factor X F10 0.29 3.23 7.45 1.59 3.15 11.56 11.56 54576 UDP glucuronosyltransferase family 1, UGT1A8 1.14 0.42 4.76 −0.39 1.86 11.35 11.35 polypeptide A8 [ 875 cystathionine-beta-synthase CBS 0.28 2.10 5.82 1.09 3.2 11.35 11.35 9970 nuclear receptor subfamily 1 group I NR1I3 −1.49 6.49 6.95 1.45 11.34 10.54 11.34 member 3 2819 glycerol-3-phosphate dehydrogenase GPD1 −1.12 1.91 8.31 −0.40 5.76 11.29 11.29 1 6822 sulfotransferase family 2A member 1 SULT2A1 −1.32 6.13 3.35 0 82 11.04 5.41 11.04 2940 glutathione S-transferase alpha 3 GSTA3 1.71 3.68 6.36 1.49 5.57 10.99 10.99 8424 gamma-butyrobetaine hydroxylase 1 BBOX1 −0.69 5.44 3.71 0.19 10.78 1.92 10.78 58510 proline dehydrogenase 2 PRODH2 −1.37 4.60 5.40 −0.75 10.68 7.92 10.68 220001 von Willebrand factor C and EGF VWCE 0.90 5.79 3.99 2.04 10.67 6.75 10.67 domains 570 bile acid-CoA:amino acid N- BAAT 0.03 4.42 4.35 0.11 10.59 4.53 10.59 acyltransferase 570 bile acid-CoA:amino acid N- BAAT 0.03 4.42 4.35 0.11 10.59 453 10.59 acyltransferase 27329 angiopoietin like 3 ANGPTL3 −1.25 6.17 7.93 1.56 10.33 10.39 10.39 1733 iodothyronine deiodinase 1 DIO1 −0.88 6.04 8.02 0.51 8.74 10.37 10.37 79799 UDP glucuronosyltransferase family 2 UGT2A3 0.52 3.51 7.23 0.7 7.07 10.32 10.32 member A3 84647 phospholipase A2 group XIIB PLA2G12B −0.2 6.2 5.93 0.84 10.29 7.03 10.29 196410 methyltransferase like 7B METTL7B 1.01 5.30 4.63 1.88 10.10 6.02 10.10 462 serpin family C member 1 SERPINC1 −0.72 1.97 7.63 0 86 2.33 10.03 10.03 9388 lipase G, endothelial type LIPG −0.30 5.09 5.95 −1.81 10.00 7.9 10.00 6554 solute carrier family 10 member 1 SLC10A1 −1.72 4.34 8.83 0.52 3.78 9.94 9.94 6554 solute carrier family 10 member 1 SLC10A1 −1.72 4.34 8.83 0.52 3 78 9.94 9.94 344 apolipoprotein C2 APOC2 1.89 2.47 8.77 1.04 3.30 9.93 9.93 1576 cytochrome P450 family 3 subfamily A CYP3A4 −0.34 6.2 5.13 1.69 9.52 9.89 9.89 member 4 5264 phytanoyl-CoA 2-hydroxylase PHYH 0.07 5.45 6.63 0.27 5.89 9.86 9.86 5002 solute carrier family 22 member 18 SLC22A18 −0.46 4.45 8.07 1.62 5.91 9.78 9.78 6539 solute carrier family 6 member 12 SLC6A12 −0.47 5.16 2.52 0.46 9.76 3.59 9.76 51268 pipecolic acid and sarcosine oxidase PIPOX −0.32 5.58 7.01 0.49 8.68 9.75 9.75 80168 monoacylglycerol O-acyltransferase 2 MOGAT2 −0.69 5.78 3.70 −1.22 9.69 5.70 9.69 216 aldehyde dehydrogenase 1 family member A1 ALDH1A1 −0.6 4.83 5.76 0.41 8.76 9.68 9.68 23498 3-hydroxyanthranilate 3,4-dioxygenase HAAO 0.78 4.78 4.84 2.34 9.44 9.26 9.44 7498 xanthine dehydrogenase XDH 0.3 0.31 3.40 0.37 2.30 9.37 9.37 3990 lipase C, hepatic LIPC 0.29 5.86 3.68 2.37 9.27 5.6 9.27 3172 hepatocyte nuclear factor 4 alpha HNF4A 0.29 5.58 5.67 0.13 9.11 7.48 9.11 2165 coagulation factor XIII B chain F13B −0.47 3.88 9.06 −0.76 4.46 9.10 9.10 635 betaine-homocysteine S-methyltransferase BHMT 1.99 5.00 4.67 2.85 9.06 9.03 9.06 1551 cytochrome P450, family 3, subfamily A, polypeptide 7 CYP3A7 −0.70 5.2 5.83 0.10 8.99 8.28 8.99 1579 cytochrome P450, family 4, subfamily A, polypeptide 11 CYP4A11 −0.61 2.82 5.32 0.19 8.96 3.8 8.96 5919 retinoic acid receptor responder (tazarotene induced) 2 RARRES2 0.23 2.74 5.37 1.17 6.31 8.94 8.94 8309 acyl-CoA oxidase 2, branched chain ACOX2 0.70 5.29 2.92 2.62 8.93 3.63 8.93 8630 hydroxysteroid (17-beta) dehydrogenase 6 HSD17B6 1.27 5.32 3.02 0.87 8.90 4.07 8.90 8630 hydroxysteroid (17-beta) dehydrogenase 6 homolog (mouse) HSD17B6 1.27 5.32 3.02 0.87 8.90 4.07 8.90 197 alpha-2-HS-glycoprotein AHSG 0.08 3.31 7.12 0.65 2.98 8.89 8.89 8991 selenium binding protein 1 SELENBP1 0.43 4.15 6.03 0.15 7.85 8.87 8.87 10840 aldehyde dehydrogenase 1 family, member L1 ALDH1L1 0.01 3.85 5.17 −1.04 6.17 8.79 8.79 27141 cell death-inducing DFFA-like effector b CIDEB 0.43 3.69 8.05 −0.07 4.98 8.77 8.77 79814 agmatine ureohydrolase (agmatinase) AGMAT −0.66 5.03 4.68 0.22 8.77 6.46 8.77 6568 solute carrier family 17 (organic anion transporter), member 1 SLC17A1 0.76 −1.55 1.84 1.46 −1.37 8.76 8.76 6694 secreted phosphoprotein 2,24 kDa SPP2 0.57 0.07 2.89 0.04 0.86 8.72 8.72 5313 pyruvate kinase, liver and RBC PKLR −0.61 5.00 3.99 1.44 8.71 4.6 8.71 229 aldolase B, fructose-bisphosphate ALDOB 1.11 4.58 4.25 2.49 8.69 6.73 8.69 3931 lecithin-cholesterol acyltransferase LCAT −0.05 1.88 5.09 2.47 4.90 8.64 8.64 6360 chemokine (C-C motif) ligand 16 CCL16 −0.94 6.39 8.61 −1.38 6.68 8.38 8.6 57733 glucosidase, beta, acid 3 GBA3 0.07 4.33 7.05 1.30 6.27 8.60 8.60 57733 glucosidase, beta, acid 3 (cytosolic) GBA3 0.07 4.33 7.05 1.30 6.27 8.60 8.60 1559 cytochrome P450, family 2, subfamily C, polypeptide 9 CYP2C9 −0.97 2.30 2.13 −0.82 8.54 6.65 8.54 10991 solute carrier family 38, member 3 SLC38A3 0.54 5.02 5.46 2.1 7.14 8.51 8.51 55532 solute carrier family 30, member 10 SLC30A10 0.49 5.01 3.38 1.22 8.49 7.97 8.49 54658 UDP glucuronosyltransferase 1 family, polypeptide A1 UGT1A1 0.77 3.61 0.79 −1.06 8.41 5.00 8.41 5444 paraoxonase 1 PON1 −2.09 3.44 4.69 0.10 8.29 7.53 8.29 2998 glycogen synthase 2 (liver) GYS2 1.14 4.68 4.38 2.43 8.24 2.97 8.24 4547 microsomal triglyceride transfer protein MTTP −1.41 6.74 3.92 −2.34 8.19 4.85 8.19 64816 cytochrome P450, family 3, subfamily A, polypeptide 43 CYP3A43 −0.75 4.43 3.70 0.24 8.09 6.23 8.09 5950 retinol binding protein 4, plasma RBP4 −1.44 1.93 5.77 0.6 3.07 8.04 8.04 55937 apolipoprotein M APOM −1.22 1.88 5.46 −0.34 2.25 7.97 7.97 55244 solute carrier family 47, member 1 SLC47A1 −1.05 4.37 5.17 0.07 6.16 7.96 7.96 646282 alpha-2-glycoprotein 1, zinc-binding pseudogene 1 AZGP1P1 −0.16 2.78 5.24 −0.39 3.70 7.96 7.96 10864 solute carrier family 22 (organic anion transporter), member 7 SLC22A7 0.08 5.12 3.82 0.44 7.95 4.16 7.95 197257 lactate dehydrogenase D LDHD −0.28 4.87 4.34 0.18 7.87 7.20 7.87 6999 tryptophan 2,3-dioxygenase TDO2 −1.32 5.69 3.47 0.86 7.87 3.89 7.87 6296 acyl-CoA synthetase medium-chain family member 3 ACSM3 −0.52 2.00 5.20 0.16 2.18 7.70 7.70 2705 gap junction protein, beta 1, 32 kDa GJB1 0.24 4.12 2.72 0.76 7.65 4.6 7.65 368 ATP-binding cassette, sub-family C (CFTR/MRP), member 6 ABCC6 0.06 4.68 3.08 2.24 7.57 4.54 7.57 54988 acyl-CoA synthetase medium-chain family member 5 ACSM5 −0.81 3.08 4.89 −0.49 5.92 7.55 7.55 55908 chromosome 19 open reading frame 80 C19Orf80 0.30 3.28 −0.67 1.99 7.55 0.34 7.55 5624 protein C (inactivator of coagulation factors Va and Villa) PROC 0.06 4.22 2.37 1.08 7.53 3.42 7.53 130 alcohol dehydrogenase 6 (class V) ADH6 −0.71 4.26 2.76 −0.59 7.52 3.94 7.52 57678 glycerol-3-phosphate acyltransferase, mitochondrial GPAM 0.64 2.91 3.31 0.38 6.68 7.47 7.47 1577 cytochrome P450, family 3, subfamily A, polypeptide 5 CYP3A5 −0.03 4.42 5.41 1.54 7.28 7.46 7.46 1562 cytochrome P450, family 2, subfamily C, polypeptide 18 CYP2C18 −0.19 0.55 0.37 0.25 7.45 3.29 7.45 9027 N-acetyltransferase 8 (GCN5-related, putative) NAT8 1.32 2.55 2.12 0.95 7.44 6.11 7.44 51733 ureidopropionase, beta UPB1 0.69 3.62 0.40 −1.39 7.29 −0.13 7.29 15283 klotho beta KLB −2.30 4.06 2.26 −1.29 7.25 4.45 7.25 140828 long intergenic non-protein coding RNA 261 LINC00261 −2.00 2.37 3.26 −1.16 6.71 7.24 7.24 8529 cytochrome P450, family 4, subfamily F, polypeptide 2 CYP4F2 0.32 3.32 6.30 0.83 1.51 7.23 7.23 27232 glycine N-methyltransferase GNMT −1.03 3.14 6.10 0.62 1.82 7.22 7.22 3273 histidine-rich glycoprotein HRG 0.19 2.67 5.58 2.06 3.83 7.21 7.21 5053 phenylalanine hydroxylase PAH 1.02 4.13 5.46 0.4 6.52 7.18 7.18 3795 ketohexokinase (fructokinase) KHK −0.65 3.32 2.79 0.50 7.14 4.52 7.14 83597 receptor (chemosensory) transporter protein 3 RTP3 −0.39 2.52 3.87 0.08 4.04 7.10 7.10 2538 glucose-6-phosphatase, catalytic subunit G6PC 0.39 4.25 3.03 1.11 7.06 4.35 7.06 2153 coagulation factor V (proaccelerin, labile factor) F5 −0.30 3.35 4.35 1.99 6.24 7.04 7.04 6580 solute carrier family 22 (organic cation transporter), member 1 SLC22A1 −0.23 3.68 4.70 0.31 6.95 6.80 6.95 653190 ATP-binding cassette, sub-family C, member 6 pseudogene 1 ABCC6P1 0.38 4.95 3.48 −0.67 6.91 5.50 6.91 (functional) 1544 cytochrome P450, family 1, subfamily A, polypeptide 2 CYP1A2 0.23 1.93 1.56 1.46 2.91 6.91 6.91 3081 homogentisate 1,2-dioxygenase HGD 0.52 4.25 2.82 0.09 6.91 4.66 6.9 79962 DnaJ (Hsp40) homolog, subfamily C, member 22 DNAJC22 −0.77 3.08 2.39 0.10 6.87 5.13 6.87 64240 ATP-binding cassette, sub-family G (WHrTE), member 5 ABCG5 −1.02 3.92 4.73 0.25 6.85 6.63 6.85 10786 solute carrier family 17 (organic anion transporter), member 3 SLC17A3 −0.91 −1.36 1.31 0.46 −0.54 6.78 6.78 10786 solute carrier family 17 (sodium phosphate), member 3 SLC17A3 −0.91 −1.36 1.31 −0.46 −0.54 6.78 6.78 189 alanine-glyoxylate aminotransferase AGXT −0.77 2.89 4.06 0.33 3.01 6.70 6.70 554235 aspartate dehydrogenase domain containing ASPDH 0.19 3.12 3.25 −1.62 6.63 6.66 6.66 2053 epoxide hydrolase 2, cytoplasmic EPHX2 −1.17 3.83 2.56 0.70 6.66 5.28 6.66 3171 forkhead box A3 FOXA3 1.40 4.36 4.51 0.68 5.52 6.54 6.54 173 afamin AFM 0.05 2.95 2.32 −0.10 6.54 0.96 6.54 2706 gap junction protein, beta 2, 26 kDa GJB2 0.89 5.61 5.64 1.10 5.34 6.51 6.51 6514 solute carrier family 2 (facilitated glucose transporter), SLC2A2 1.84 3.51 3.20 1.09 6.50 4.48 6.50 member 2 134526 acyl-CoAthioesterase 12 ACOT12 −0.29 3.09 1.64 −1.06 6.49 2.75 6.49 10841 formimidoyltransferase cyclodeaminase FTCD 0.04 4.29 4.57 1.39 5.77 6.37 6.37 10841 formimidoyltransferase cyclodeaminase FTCD 0.04 4.29 4.57 1.39 5.77 6.37 6.37 5105 phosphoenolpyruvate carboxykinase 1 PCK1 0.54 3.35 6.37 2.87 2.39 5.53 6.37 124 alcohol dehydrogenase 1A (class I), alpha ADH1A −0.31 2.95 2.72 −0.33 6.36 4.73 6.36 polypeptide 116519 apolipoprotein A5 APOA5 0.13 2.43 6.35 1.6 5.75 6.19 6.35 3827 kininogen 1 KNG1 −0.38 2.74 4.5 0.43 2.96 6.34 6.34 1370 carboxypeptidase N subunit 2 CPN2 −1.46 2.84 2.21 −0.2 6.33 3.45 6.33 1491 cystathionine gamma-lyase CTH 2.68 2 3.01 2.22 2.4 6.31 6.31 10555 1-acylglycerol-3-phosphate O-acyltransferase 2 AGPAT2 0.4 3.09 6.19 0.59 3.92 5.81 6.19 131669 urocanate hydratase 1 UROC1 0.79 1.76 2.73 0.67 3.15 6.17 6.17 3818 kallikrein B1 KLKB1 0.42 3.88 2.85 0.95 6.15 3.23 6.15 127 alcohol dehydrogenase 4 (class II), pi polypeptide ADH4 1.67 1.41 2.07 1.03 3.56 6.11 6.11 7263 thiosulfate sulfurtransferase TST 0.37 2.87 4.66 0.84 2.63 6.1 6.1 5340 plasminogen PLG 0.13 1.94 3.95 0.53 2.52 6.07 6.07 341 apolipoprotein C1 APOC 0.63 2.2 4.64 1.6 3.12 6.04 6.04 51181 dicarbonyl and L-xylulose reductase DCXR 0.17 2.54 3.03 −0.28 4.03 6.04 6.04 122664 tubulin polymerization promoting protein family TPPP2 −2.09 1.4 2.21 −1.47 3.4 6.01 6.01 member 2 1807 dihydropyrimidinase DPYS −0.7 3.81 1.88 −1.41 6 2.83 6 2644 GTP cyclohydrolase I feedback regulator GCHFR 0.51 4.28 3.38 1.67 5.96 5.08 5.96 10249 glycine-N-acyltransferase GLYAT 1.15 −0.35 2.9 −1.78 1.42 5.93 5.93 1 alpha-1-B glycoprotein A1BG −0.25 1.28 5.91 0.44 1.01 4.63 5.91 123876 acyl-CoA synthetase medium chain family ACSM2A −0.4 2.03 4.79 −0.86 1.99 5.9 5.9 member 2A 5174 PDZ domain containing 1 PDZK1 −0.38 4.43 3.7 0.24 5.8 4.26 5.8 337 apolipoprotein A4 APOA4 −0.34 2.09 2.83 2.32 5.77 1.33 5.77 761 carbonic anhydrase 3 CA3 −0.32 2.46 1.63 0.55 4.66 5.74 5.74 763 carbonic anhydrase 5A CA5A −1.99 3.26 4.39 0.91 4.15 5.73 5.73 445 argininosuccinate synthase 1 ASS1 −0.36 0.89 4.23 0.73 1.11 5.72 5.72 151531 uridine phosphorylase 2 UPP2 0.91 3.18 3.86 1.64 4.23 5.66 5.66 130013 aminocarboxymuconate semialdehyde ACMSD 0.65 0.49 3.62 −0.17 2.69 5.65 5.65 decarboxylase 5244 ATP binding cassette subfamily B member 4 ABCB4 −0.28 3.71 3.98 0.12 5.65 5.32 5.65 866 serpin family A member 6 SERPINA6 −1.33 3.36 2.37 1.46 5.6 3.28 5.6 7104 transmembrane 4 L six family member 4 TM4SF4 −1.6 2.22 1.14 0.98 5.59 3.8 5.59 6898 tyrosine aminotransferase TAT −0.3 3.46 3.44 0.93 5.59 5.32 5.59 7363 UDP glucuronosyltransferase family 2 member B4 UGT2B4 0.5 0.78 3.52 0.66 3.4 5.54 5.54 2160 coagulation factor XI F11 −1.73 3.2 2.68 −0.14 5.52 3.27 5.52 388503 complement component 3 precursor pseudogene C3P1 −2.46 0.49 4.22 −3.05 0.98 5.52 5.52 80781 collagen type XVIII alpha 1 chain COL18A1 −0.76 4.9 4.42 −0.3 4.47 5.46 5.46 129807 neuraminidase 4 NEU4 0.99 2.1 3.21 1.15 5.45 5.23 5.45 290 alanyl aminopeptidase, membrane ANPEP −0.54 3.4 5.04 0.19 4.02 5.44 5.44 387601 solute carrier family 22 member 25 SLC22A25 −1.87 3.01 2.04 1.4 5.41 3.11 5.41 170392 oncoprotein induced transcript 3 OIT3 0.39 3.43 3.86 −0.6 5.03 5.41 5.41 81494 complement factor H related 5 CFHR5 0.08 1.83 1.71 1.16 5.41 0.38 5.41 3960 galectin 4 LGALS4 −0.72 0.84 4.05 −0.63 3.19 5.41 5.41 64757 mitochondrial amidoxime reducing component 1 MARC1 −0.5 3.26 0.8 −0.76 5.33 0.39 5.33 1548 cytochrome P450 family 2 subfamily A member 6 CYP2A6 0.34 −1.42 1.67 −0.75 −0.8 5.3 5.3 1109 aldo-keto reductase family 1 member C4 AKR1C4 −0.45 2.34 2.73 −0.91 5.26 4.42 5.26 1109 aldo-keto reductase family 1 member C4 AKR1C4 −0.45 2.34 2.73 −0.9 5.26 4.42 5.26 8858 protein Z, vitamin K dependent plasma PROZ −2.02 4.25 4.35 −0.74 4.7 5.22 5.22 glycoprotein 3053 serpin family D member 1 SERPIND1 0.03 3.07 3.39 1.38 3.25 5.21 5.21 3950 leukocyte cell derived chemotaxin 2 LECT2 −1.55 1.86 1.45 1.54 5.16 4.59 5.16 116285 acyl-CoA synthetase medium chain family ACSM1 0.42 0.5 4.5 −0.71 1.26 5.02 5.02 member 1 29974 APOBEC1 complementation factor A1CF 0.38 2.49 2.27 2.94 4.95 2.26 4.95 23562 claudin 14 CLDN14 −0.75 3.71 2.5 −2.09 4.86 4.89 4.89 145264 serpin family A member 12 SERPINA12 0.66 0.75 1.78 −1.11 3.73 4.83 4.83 91703 aminoacylase 3 ACY3 −1.18 2.54 1.42 −2.96 3.99 4.82 4.82 7274 alpha tocopherol transfer protein TTPA −0.61 3.24 1.93 0.36 4.79 2.41 4.79 2642 glucagon receptor GCGR −0.89 −1.11 2.17 −0.53 0.02 4.77 4.77 127845 golgi transport 1A GOLT1A −0.91 1.5 2.24 1.63 4.75 4.18 4.75 10878 complement factor H-related 3 CFHR3 4.06 2.58 1.03 4.74 1.11 −1.77 4.74 10747 mannan binding lectin serine peptidase 2 MASP2 −0.46 2.08 4.73 0.18 −1.95 2.45 4.73 114770 peptidoglycan recognition protein 2 PGLYRP2 0.03 1.19 1.59 −0.25 2.45 4.71 4.71 9154 solute carrier family 28 member 1 SLC28A1 −0.29 1.62 0.71 0.23 4.68 2.28 4.68 1581 cytochrome P450 family 7 subfamily A member 1 CYP7A1 −1.35 2.25 1.41 −0.8 4.68 1.71 4.68 10599 solute carrier organic anion transporter family SLCO1B1 −2.24 −0.86 2.97 −0.35 4.67 3.93 4.67 member 1B1 ] 1549 cytochrome P450 family 2 subfamily A member 7 CYP2A7 1.26 1.03 2.17 1.44 0.16 4.66 4.66 5104 serpin family A member 5 SERPINA5 −0.91 2.57 −0.19 −0.77 4.64 3.84 4.64 7018 transferrin TF 0.18 2.88 2.94 −1.95 1.91 4.61 4.6 1565 cytochrome P450 family 2 subfamily D member 6 CYP2D6 0.44 0.67 0.74 −0.96 4.59 3.06 4.59 10998 solute carrier family 27 member 5 SLC27A5 −0.63 1.1 3.02 0.21 3.51 4.59 4.59 2328 flavin containing monooxygenase 3 FMO3 0.94 0.6 1.89 −1.2 0.89 4.58 4.58 3697 inter-alpha-trypsin inhibitor heavy chain 1 ITIH1 −0.35 3.52 2.09 0.74 4.56 2.47 4.56 13 arylacetamide deacetylase AADAC −2.02 2.33 2.31 −1.99 4.52 1.62 4.52 5092 pterin-4 alpha-carbinolamine dehydratase 1 PCBD1 0.66 0.52 −1.6 1.15 4.51 −0.28 4.51 1036 cysteine dioxygenase type 1 CDO1 0.35 4.31 1.15 −0.7 4.5 0.83 4.5 51085 MLX interacting protein like MLXIPL 0.85 2.29 3.48 0.37 4.47 4.34 4.47 432 asialoglycoprotein 1 ASGR1 −0.34 3.45 1.16 −0.04 4.46 0.48 4.46 350 apolipoprotein H (beta-2-glycoprotein I) APOH 0.06 2.08 2.68 0.28 3.14 4.44 4.44 1757 sarcosine dehydrogenase SARDH −0.76 2.83 3.22 0.03 3.48 4.44 4.44 51179 hydroxyacid oxidase 2 (long chain) HAO2 0.47 1.6 4.42 0.26 2.21 4.26 4.42 733 complement component 8, gamma polypeptide C8G −0.01 2.14 4.39 0.24 2.22 3.23 4.39 4051 cytochrome P450, family 4, subfamily F, polypeptide 3 CYP4F3 0.18 4.38 3.27 0.43 2.79 3.58 4.38 257407 chromosome 2 open reading frame 72 C2orf72 −2.19 1.88 1.98 −1.32 4.34 2.91 4.34 3175 one cut homeobox 1 ONECUT1 −1.7 0.35 −0.26 0.33 4.28 2.74 4.28 3294 hydroxysteroid (17-beta) dehydrogenase 2 HSD17B2 −2.09 −0.29 0.08 −0.3 4.24 −1.55 4.24 3158 3-hydroxy-3-methyglutaryl-CoA synthase 2 HMGCS2 −0.74 2.79 3.57 0.03 3.2 4.22 4.22 (mitochondrial) 1644 dopa decarboxylase (aromatic L-amino acid decarboxylase) DDC −2.08 3.42 3.49 −3.45 4.21 3.81 4.21 64902 alanine-glyoxylate aminotransferase 2 AGXT2 0.36 3.82 4.19 −0.01 3.85 3.78 4.19 10866 HLA complex P5 (non-protein coding) HCP5 1.11 1.69 1.02 −0.1 4.18 −0.06 4.18 55811 adenylate cyclase 10 (soluble) ADCY10 −0.27 2.39 1.17 −0.6 0.24 4.14 4.14 283600 solute carrier family 25, member 47 SLC25A47 −2.09 −0.44 1.38 −2.5 0.27 4.08 4.08 2330 flavin containing monooxygenase 5 FMO5 −0.8 3.74 3.79 −0.05 4.02 3.72 4.02
[0168] Next, the inventors asked whether MB-1 treatment of HLC enabled robust HBV infection from clinical isolates. HBV particles were purified from serum of CHB individual using Nycodenz™ gradient. This step successfully separated HBV Dane particles from excess of HBsAg empty particles (see
TABLE-US-00004 TABLE 3 HBV infection in HLC: Comparison between patient-derived vs HepG2.2.15-derived HBV (96-well). HLC seeded in 96-well were infected either with patient-derived HBV, or cell culture-derived (HepG2.2.15) virus, at the indicated MOIs, in the presence of MB-1 or 1% DMSO. Viral kinetics (HBsAg released into culture medium) was measured every 2 day until day 14 pi. Day HBsAg HBV Source pi Condition MOI (ng/ml) Patient- 1 DMSO 10 0.33 +/− 0.07 derived 3 0.10 +/− 0.01 8 0.11 +/− 0.05 11 0.23 +/− 0.05 14 0.13 +/− 0.03 1 MB-1 0.34 +/− 0.06 3 0.93 +/− 0.25 8 5.87 +/− 1.34 11 14.31 +/− 2.02 14 10.39 +/− 1.46 HepG2.2.15 1 DMSO 0.05 +/− 0.01 3 0.06 +/− 0.01 8 0.04 +/− 0.01 11 0.05 +/− 0.01 14 0.06 +/− 0.01 1 MB-1 0.05 +/− 0.01 3 0.06 +/− 0.01 8 0.08 +/− 0.01 11 0.10 +/− 0.01 14 0.09 +/− 0.01 1 100 414.13 +/− 1.68 3 8.12 +/− 2.21 8 0.36 +/− 0.11 11 0.73 +/− 0.20 14 0.43 +/− 0.18 Uninfected 1 0 0.20 +/− 0.08 3 0.17 +/− 0.07 8 0.24 +/− 0.08 11 0.24 +/− 0.10 14 0.20 +/− 0.08
HLCs as a Disease-Relevant Assay for HBV Drug Discovery
[0169] To be considered as a disease-relevant assay for HBV drug discovery, HLC assay ideally has to be comparable to PHH, can be miniaturized in 384-well plate, and amenable for testing clinical HBV samples of diverse GTs.
[0170] Productive HBV infection can be assessed by various viral markers that represent key steps in HBV life cycle (see
[0171] The inventors infected HLC and PHH (in 96-well plate) with identical virus inoculum (MOI 40) and followed the kinetics of HBV infection based on 5 viral readouts during a 14-day assay. The levels of all HBV markers in HLC are remarkably comparable to those observed in PHH (see
TABLE-US-00005 TABLE 4 Kinetics of HBV infection in HLC and PHH (96-well plate format): HLC and PHH seeded in 96-well were infected with identical virus inoculum (patient-derived HBV, MOI 40). Kinetics of viral infection in both cell types was measured every 2 days until day 14 pi using various markers (HBsAg, HBeAg, HBV DNA, pgRNA, and cccDNA). Cell Day cccDNA pgRNA HBV DNA type pi Albumin (ng/ml) (×10.sup.3 copies/well) (×10.sup.3 copies/well) (×10.sup.6 copies/ml) HBeAg (ng/ml) HBsAg (ng/ml) HLC 2 852.46 +/− 10.29 0.61 +/− 0.39 10.18 +/− 5.15 9.03 +/− 1.39 0.28 +/− 0.06 2.59 +/− 0.71 6 920.50 +/− 21.84 6.36 +/− 1.29 45.98 +/− 71.57 1.63 +/− 1.91 0.87 +/− 0.12 15.91 +/− 3.39 10 945.76 +/− 27.63 12.13 +/− 4.38 816.61 +/− 181.82 2.36 +/− 4.36 3.81 +/− 0.42 15.10 +/− 1.72 14 859.66 +/− 19.56 13.17 +/− 1.20 963.11 +/− 275.93 3.87 +/− 3.28 10.96 +/− 2.40 37.34 +/− 4.05 PHH 2 809.64 +/− 26.91 2.17 +/− 2.26 19.51 +/− 0.5 5.42 +/− 1.05 0.29 +/− 0.04 2.65 +/− 0.66 6 945.77 +/− 29.08 14.64 +/− 2.14 333.39 +/− 7.15 8.34 +/− 1.44 0.96 +/− 0.14 7.61 +/− 0.76 10 966.67 +/− 25.47 11.62 +/− 2.65 649.41 +/− 181.18 2.41 +/− 6.29 10.15 +/− 0.50 38.82 +/− 4.75 14 1034.86 +/− 7.66 11.47 +/− 4.09 1409.88 +/− 275.92 4.54 +/− 8.53 17.20 +/− 0.44 51.79 +/− 3.65
[0172] The inventors further showed that HLC are able to support infection of a wide range of clinical HBV isolates. Purified HBV from 17 CHB sera (GT A-D) were used to infect HLC (in 384-well plate) at MOI 40. Ten out of 17 isolates propagated very efficiently with HBsAg and HBeAg levels widely ranged between 2-150 ng/ml and 1-22 ng/ml, respectively (see
The First HTS on HLC to Identify Novel cccDNA Inhibitors
[0173] A phenotypic screening in HLC infected with patient-derived HBV would theoretically increase the likelihood to discover bona fide cccDNA inhibitors, but such HTS requires rigorous feasibility assessment before it can be launched. First, HLC assay duration (14-day) is far longer than other cell-based phenotypic screenings (1-3 days) which increases the technical complexity and potential assay variability. HLC assay performance (Z′ factor) was assessed by performing ˜7,000 HBV infections (at MOI 40 in 384-well plates). The Z′ factor is a statistical measure of assay quality that takes into account both assay robustness and signal variability (standard deviation); assay with a Z′ factor >0.5 is considered highly suitable for conducting a HTS (Zhang et al., 1999). The Z′ factors of three analytes (HBsAg 0.6; HBeAg 0.45; albumin 0.8) (see
[0174] A schematic of the HTS assay and the screening cascade is shown in
HLC Hit Validation in PHH Identified Novel cccDNA Destabilizers
[0175] To increase the efficiency of HLC hit profiling, the screening cascade were carried out in PHH (see
Molecular Profiling Revealed that cccDNA Destabilizers Induced Broad Modulation of Host Pathways
[0176] The major challenges of phenotypic discoveries are target identification and understanding compound's mode-of-action (MOA) that may affect their safety assessment (Moffat et al., 2017). Most often, this information is not available at post HTS when hit triaging is routinely based on chemical structure (chemotype) clustering and compound potency. Small molecules can also bind to several targets (polypharmacology), increasing off-target safety risks (Peters et al., 2012). In the absence of molecular targets, phenotypic discoveries would benefit from early compound profiling at transcriptomic or phenotypic levels as part of hit prioritization to identify potential safety liabilities of hit series and to develop de-risking strategies if needed (Moffat et al., 2017).
[0177] The inventors applied a transcriptomic profiling assay to evaluate how different classes of cccDNA destabilizers modulate cellular pathways in PHH. Molecular phenotyping is a gene expression assay based on a panel of 917 pathway reporter genes that represent 154 human signalling and metabolic networks (Zhang et al., 2017). These pathway reporter genes are involved in 53% of the annotated gene-gene interactions, either acting as upstream transcriptional regulators or downstream regulatory targets in these interactions. Modulation of reporter genes expression following compound treatment allowed a multiplex view of pathways involved in various biological processes of interest, including those that lead to adverse side effects (Zhang et al., 2017). The inventors tested compound 7 and reference compound 1 (together with their respective less active isomers) and two marketed HBV drugs, entecavir (ETV, a nucleoside analog with good safety profiles) and interferon-α (an immunomodulator associated with various side effects) as controls in this assay. PHH were infected with HBV (or DMSO), and 3 days later, incubated with each drug at its 1×IC90 value for 6 hours. Total cellular RNA was extracted, and the primary responses of reporter genes against each drug were measured using AmpliSeq-RNA method. As expected, ETV induced minor changes, in line with its MOA as a direct-acting-antiviral. In contrast, Roferon strongly induced interferon-α and -λ signalling pathways and downstream pathways of IFN signalling (see
Potency of cccDNA Destabilizers Across Different HBV Genotypes
[0178] Most of HBV in vitro studies, including evaluation of compound antiviral activity, are performed in hepatoma cell lines (HepaRG or HepG2-NTCP) infected with cell culture-derived HBV (e.g. HepG2.2.15-derived virus, GT D). As evaluation of cccDNA destabilizers was performed with patient-derived HBV GT D in PHH (see
TABLE-US-00006 TABLE 5 Potency of cccDNA destabilizer (compound 7) against patient-derived HBV (GT A-D) in PHH. Cells were infected with each virus (MOI 40, in triplicate, 384-well plate), and at 3 day pi, compound 7 was added at 3-fold dilutions starting from 156 μM. Assay readouts were performed at day 10 pi to measure compound activity on HBsAg, HBeAg, HBV DNA, pgRNA and cccDNA. Albumin is a surrogate for in vitro cellular tox. Antiviral activity of compound 7 against patient−derived HBV (GT A−D) in PHH In vitro tox HBV HBsAg IC50 (μM) HBeAg IC50 (μM) HBV DNA IC50 (μM) pgRNA IC50 (μM) cccDNA IC50 (μM) albumin IC50 (μM) GT N Median SD N Median SD N Median SD N Median SD N Median SD N Median SD A 4 0.33 0.09 4 0.4 0.09 3 0.025 0.007 3 3.58 1.3 3 7.15 0.1 4 20.26 1.81 B 4 0.34 0.03 4 0.31 0.03 3 0.023 0.002 3 3.13 0.57 3 6.56 0.85 4 19.24 1.67 C 4 0.3 0.08 4 0.35 0.04 3 0.02 0.003 3 1.64 0.14 3 6.2 1.71 4 23.16 1.84 D 4 0.3 0.06 4 0.31 0.02 3 0.023 0.004 3 1.35 0.52 3 6.69 0.77 4 23.72 1.32
[0179] Altogether, these results indicate that compound potency against HBV could be influenced by source of virus inoculum. Further tests with a large number of HBV isolates from diverse genotypes can be conducted to confirm this finding.
TABLE-US-00007 TABLE 6 Effect of source of virus inoculum (patient- vs HepG2.2.15-derived HBV) and cell type (PHH vs HepaRG) on compound 7 Activity of compound 7 against patient- and HepG2.2.15-derived HBV in In vitro tox HepaRG and PHH albumin IC50 Cell Virus HBV HBsAg IC50 (μM) HBeAg IC50 (μM) pgRNA IC50 (μM) cccDNA IC50 (μM) (μM) type Source GT MOI N Median SD N Median SD N Median SD N Median SD N Median SD HepaRG Patient D 40 3 0.67 0.01 3 0.41 0.1 3 1.93 0.02 3 below LLOQ 3 23.35 0.63 125 3 0.88 0.16 3 0.52 0.15 3 4.62 0.7 3 7.05 0.2 3 25.71 1.73 HepG2.2.15 D 40 3 9.01 0.24 3 6.11 0.76 3 16.81 0.71 3 25.87 0.72 3 24.93 2.15 125 3 10.34 0.85 3 6.55 0.86 3 26.63 0.56 3 27.21 0.42 3 26.56 1.25 PHH Patient D 40 3 0.44 0.02 3 0.32 0.13 3 1.48 0.08 3 6.41 0.25 3 23.71 1.43 125 3 0.8 0.54 3 0.57 0.18 3 2.87 1.92 3 6.78 0.66 3 20.49 0.35 HepG2.2.15 D 40 3 9.98 0.33 3 15.35 0.36 3 12.8 0.53 3 24.96 0.45 3 21.1 1.17 125 3 8.98 0.46 3 15.86 0.43 3 11.28 0.8 3 25.16 0.73 3 20.17 1.07
DISCUSSION
[0180] Despite being the 7.sup.th cause of deaths in the world (Stanaway et al., 2016), WHO recognized that viral hepatitis is “largely ignored as a health and development priority until recently”. Indeed, <5% of chronic viral hepatitis worldwide is diagnosed while only ˜1% of viral hepatitis individuals received treatment (WHO, 2016). Even in the US (HBV prevalence ˜1.29 million cases), <35% of HBV infections are diagnosed and only 45% of eligible CHB patients received treatment (Buckley & Strom, 2017). Without expanded intervention, the number of people living with CHB infection is estimated to remain at the current high levels for the next 40-50 years, with a cumulative 20 millions deaths occurring between 2015 and 2030 (WHO 2016). Consequently, global strategies are required to cure HBV (Revill et al., 2016; WHO, 2016). As HBV DNA integration events into the host chromosome may occur during the early phase of infection (Mason et al., 2016), a true cure, defined as HBV eradication including intrahepatic cccDNA and integrated HBV DNA, may not be feasible (Lok et al., 2017). Instead, a functional cure which allows cessation of treatment without risk of virological relapse and of liver disease progression is deemed an attainable goal (Lok et al., 2017). A functional cure is defined as sustained, undetectable HBsAg and HBV DNA in serum after completion of a finite course of treatment, leading to resolution of residual liver injury, and a decrease risk of HCC over time. Several levels of functional cure are envisioned, including complete silencing of cccDNA transcription, elimination of cccDNA, and complete resolution of liver damage (Lok et al., 2017).
[0181] Targeting cccDNA will most likely require perturbations of the cccDNA minichromosome network. HBV hijacks host factors to establish cccDNA and to regulate its transcriptional activity. For instance, host DNA damage response system is involved in conversion of HBV RC-DNA (from incoming virions) to cccDNA in the newly infected cells (Nassal, 2015; Schreiner & Nassal, 2017). Once cccDNA is formed, it recruits histone and non-histone proteins as well as viral proteins to establish its functional unit, the minichromosome (Guo & Guo, 2015; Levrero, 2009; Nassal, 2015; Schreiner & Nassal, 2017). cccDNA minichromosome can exist in two different topology, most likely with different sets of interacting partners that relate to its transcriptional activity (Newbold et al., 1995). Conceivably, chemical perturbations of cccDNA-host interactome may lead to cccDNA instability and/or silencing of its transcriptional activity; however, the crucial interacting partners required for cccDNA stability and functions are elusive and cccDNA biology is still poorly understood. In this regard, phenotypic screening poses a powerful approach to discover novel cccDNA inhibitors in a target-agnostic manner. However, cccDNA drug discovery efforts have been hampered by the lack of robust infection systems. Notwithstanding its role as the gold standard for HBV assay, PHH is not routinely used due to its rapid dedifferentiation in culture (Frazcek et al., 2013) and large donor-to-donor variability in their susceptibility to HBV (Mabit et al., 1996). For almost three decades, HBV experimental systems had mostly been contingent on non-infection systems, such as HepG2 cell lines engineered to express HBV from a transgene (Sureau et al., 1986; Sells et al., 1987; Ladner et al., 1997; Guo et al., 2007). The discovery of HepaRG, a hepatoma cell line that supports natural HBV infection (Gripon et al., 2002), and NTCP, the HBV receptor (Yan et al, 2012) represent new tools, i.e. infection systems for HBV, that allowed studies of viral entry and cccDNA biology following natural infection. The rapid advancement of iPS technologies (Shi et al., 2017), including HLC, has enabled development of novel disease models that are expected to be more physiologically-relevant than tumor cell lines, and consequently, better recapitulate human disease biology.
[0182] The use of physiological systems in drug discovery is considered as one of the first steps to increase the translatability of preclinical findings into the clinic (Eglen & Reisine, 2011; Vincent et al., 2015; Horvath et al., 2016; Ursu et al., 2017). Indeed, the high attrition rates of new drug candidates across therapeutic areas had raised the concerns on the effectiveness of preclinical models used in drug discovery (Vincent et al., 2015; Horvath et al., 2016). For instance, during 2008-2015, the failure rates of drug candidates in phase II and III trials due to the lack of efficacy were consistently between 50-60% (Arrowsmith & Miller, 2013; Harrison, 2016). Two major drug discovery strategies, phenotypic and target-based screenings, are routinely performed in immortalized/tumor cell lines, often engineered to overexpress a molecular target of interest. A large number of tumor cell lines display substantial genetic abnormalities and altered host pathways, to the extent that there is poor correlation between cell lines and patient-derived cells (Uhlen et al., 2015; Vincent et al., 2015). Overexpression of a molecular target, aimed to provide an assay with acceptable signal-to-noise ratio, also led to an artificially high level of protein that affect pathway activation and signalling not occurred in physiological condition, resulting in discrepancy between in vitro and in vivo activity (Eglen et al., 2008). In contrast, endogenous targets in primary cells are tacitly assumed to be expressed, at the levels and within the cellular environment, that more resemble those found in human. Consequently, biological activity of compound in primary cells is expected to be more predictive for its activity in vivo (Eglen & Reisine, 2011; Vincent et al., 2015; Horvath et al., 2016; Ursu et al., 2017).
[0183] HLC could potentially represent the next generation of HBV in vitro infection system. However, existing HLC are still immature (Baxter et al., 2015; Godoy et al., 2015) and showed poor susceptibility to HBV (Shlomai et al., 2014; Kaneko et al., 2016; Samurai et al., 2017). To fully manifest the promise of HLC for HBV drug discovery, HLC maturation needs to be improved. The identification of a small molecule (MB-1) that enhances hepatic maturation of HLC represents a first step in this direction. MB-1 is not a “magic bullet”; further maturation of HLC is still needed and this most likely will require combination of several approaches including culture conditions that closely emulate liver architecture (Goldring et al., 2017). Hepatocytes in the liver are highly heterogeneous in their gene expression patterns and exhibited clear gradients based on their location within the hepatic lobule (liver zonation) (Soto-Gutierrez et al., 2017; Torre et al., 2010); ˜50% of liver genes are, in fact, zonated (Halpern et al., 2017). It may be not surprising that HLC in a monolayer culture can only emulate some, but not all of ˜500 vital functions ascribed to liver (Goldring et al., 2017).
[0184] HLC support robust HBV infection of clinical isolates from various GTs with low MOI (10-40) even in the absence of PEG (polyethylene glycol, a fusogenic agent commonly used for infection of cell culture-derived HBV) and importantly, is comparable to that observed in PHH. The use of patient-derived HBV from various GTs in drug discovery is important for several reasons. HBV GT affects viral pathogenesis, disease progression and treatment response. Mixed GT infection and inter-GT recombination, in particular among GT A and C, are increasingly recognized among CHB infections, and these may have roles in pathogenesis and treatment response as well (Lin & Kao, 2017). The inventors and others (Mabit et al., 1996; Sozzi et al., 2016) observed that HBV GTs displayed marked differences in replication activity and protein secretion; such differences may affect their susceptibility to compounds with novel MOAs. A sole reliance on one HBV GT for compound screening may potentially lead to overestimation of compound potency across HBV GTs and subtypes. In addition, laboratory strain of various pathogens are known to rapidly adapt to in vitro conditions and often lost important pathophysiological characteristics (Bukh et al., 2002; Fux et al., 2005; Horvath et al., 2016).
[0185] Performing a 14-day HTS assay on HLC is not trivial. The major advantages of tumor cell line-based HTS platforms engineered to overexpress target of interest are homogeneity and reproducibility, as almost all cells express the target of interest, providing robust and reproducible signal required for HTS. On the other hand, the reproducibility of natural HBV infection in vitro is challenging, even in PHH (Mabit et al., 1996). The present study showed that HLC assay is highly reproducible with Z′ scores 0.6 (HBsAg), 0.45 (HBeAg), and 0.8 (albumin). Of note, Z′ factor >0.5 for HTS assay is considered as a high bar for complex cellular-based assays such as those associated with iPS-derived cells (Engle & Vincent, 2014). To identify novel cccDNA inhibitors in the setting of natural infection, a screening cascade was designed based on the premise that cccDNA-active compounds could sequentially be identified through its more abundant, transcriptional products (HBsAg, HBeAg, and pgRNA). This approach successfully discovered several cccDNA-active hit series in PHH as confirmed by Southern Blot assay. Of note, others have reported that circulating pgRNA and HBV core-related antigen (HBcrAg) in the plasma of CHB individuals could be used as proxy readouts for cccDNA transcriptional activity in the liver (Wang et al., 2016; Chen et al., 2017).
[0186] Assessment of compound potency based on various HBV markers offered several important insights. First, the cccDNA destabilizer (compound 7) was equally potent against four clinical HBV isolates (GT A-D) in PHH, but displayed a hierarchy of potency against various HBV markers (HBV DNA IC50<<HBsAg & HBeAg & pgRNA IC50<cccDNA IC50). This shift in potency may reflect either the abundance/half-life of HBV marker, the dynamic range of assay, or the difficulty to inhibit the target. Indeed, cccDNA is very stable (half-life 33-57 days) in the cell (Nassal, 2015). In contrast, HBV DNA-containing virions in the blood have a short half-life (˜4.4 hours) (Murray et al., 2006) which may partly explain the higher potency of compound 7 against HBV DNA than other HBV markers. Thus, measurement of the cccDNA IC50 is critical for accurate assessment of compound potency.
[0187] Intriguingly, compound 7 was far less potent against HepG2.2.15-derived virus. While the molecular target of compound 7 is unknown, phenotypic screens often identified hits that target host factors; one may hypothesize that compound 7 may target the host factor(s) required for the maintenance and transcriptional activity of cccDNA. Indeed, upon viral entry, HBV hijacks various host factors to establish cccDNA minichromosome and to regulate its transcriptional activity (Nassal, 2015). It is plausible that the reduced potency of compound 7 against HepG2.2.15-derived HBV may reflect the differences in host factors required for cccDNA maintenance and functions of both types of viruses. HepG2.2.15-derived HBV is generated in a recombinant HepG2 cell line that is perpetually passaged under antibiotic selection. Of note, HepG2 is a human hepatoma cell line reported to have poor mimicry to primary hepatocytes (Uhlen et al., 2015 and this study,
[0188] The discovery of compounds able to trigger partial cccDNA degradation is exciting, but also daunting without knowing their molecular targets, or potential off-target activities. Pharmacological assessment of potential safety liabilities is routinely performed by screening compounds against panels of safety-relevant targets. Attributable to the cost and throughput, such screenings are usually performed on a small number of key compounds at an advanced stage of lead optimization. Any safety finding at this point either requires considerable modifications of an already optimized compound, or even, the reason for attrition (Peters et al., 2012). Indeed, non-clinical toxicology was the highest cause of attrition for >800 preclinical compounds from 4 major pharma, accounting for 40% of the failures (Waring et al., 2015). It is therefore desirable to assess compound off-target activity early during hit selection after an HTS and during hit-to-lead phase (Peters et al., 2012; Moffat et al., 2017). As shown in this study, a transcriptomic profiling assay could be used for such purpose, not only in hepatocytes, but also in other cell types e.g. cardiomyocytes, thus broadening its application as part of in vitro toxicity tools.
[0189] In summary, the inventors provided the proof-of-concept that the HLC platform represents a paradigm change for HBV drug discovery that could potentially lead to discoveries of novel therapies for HBV cure. In parallel, continued efforts to improve hepatic maturation of HLC is needed as it will benefit not only HBV drug discovery and disease modelling, but also in vitro toxicology. As drug discovery effort is a very long process (on average, it takes 13.5 years from target identification to regulatory approval) (Paul et al., 2010) with huge investment, implementation of disease-relevant assays and other tools for safety de-risking should be initiated early and throughout compound progression to prevent costly attrition such as undesired findings discovered late in the clinic.
Example 2: Activity of Pyrrolo[2,3-b]Pyrazine Compounds Against Patient-Derived HBV in Primary Human Hepatocytes (PHH)
[0190] Various pyrrolo[2,3-b]pyrazine compounds of formula (I) were tested for their activity against HBV in PHH (patient-derived HBV, GT D), which is the gold standard of disease-relevant HBV models, following the procedure described in Example 1.
[0191] The structures of the tested compounds and their respective compound IDs are indicated in the following:
##STR00011## ##STR00012##
[0192] The activities of these compounds on HBeAg, HBsAg, albumin, pgRNA and cccDNA, as determined in PHH (patient-derived HBV, GT A-D), are shown in
TABLE-US-00008 TABLE 7 Antiviral activity of pyrrolo[2,3-b]pyrazine compounds 1 to 9 against patient-derived HBV (GT D) in PHH. Antiviral activity of pyrrolo[2,3-b]pyrazine series against patient-derived HBV (GT D) in PHH In vitro tox Cmpd HBsAg IC50 (μM) HBeAg IC50 (μM) pgRNA IC50 (μM) cccDNA IC50 (μM) albumin IC50 (μM) ID N Median SD N Median SD N Median SD N Median SD N Median SD 1 3 0.17 0.22 4 0.17 0.17 3 14.21 1.28 3 52.67 3.21 3 18.68 1.73 2 5 0.68 0.37 6 0.68 0.21 3 0.43 0.09 4 30.1 10.97 4 24.16 5.36 3 11 3.62 0.63 8 3.58 0.27 3 12.81 1.32 5 43.73 4.35 6 33.42 6.78 4 7 0.68 0.54 4 0.68 0.09 3 6.93 0.82 3 63.66 11.72 4 47.95 9.64 5 3 5.61 0.69 4 2.95 0.53 3 100 0 4 159.6 9.05 3 135 13.45 6 5 0.75 0.1 5 0.49 0.2 3 15.67 1.4 3 166 0 4 166 0 7 11 0.45 0.59 13 0.39 0.24 3 1.49 0.09 10 6.76 0.73 13 20.85 3.32 8 4 1.22 0.7 4 2.29 0.28 3 1.96 0.33 6 30.75 1.69 5 31.9 8.11 9 8 0.51 0.28 6 0.68 0.21 3 1.29 0.24 4 49.18 3.74 6 21.33 9.21 N, number of repeat; SD, standard deviation.
[0193] As shown above, all of the compounds 1 to 9 according to the present invention were found to inhibit HBsAg and HBeAg with IC50 values <10 μM. Compounds 2, 4, 7, 8 and 9 showed an advantageously high inhibitory effect on pgRNA (with IC50<10 μM), and compound 7 was particularly potent in reducing cccDNA levels (with IC50<10 μM). It has thus been demonstrated that the compounds of formula (I), including in particular the above-depicted compounds 1 to 9, can be used in the treatment of HBV infection. A particularly advantageous activity against HBV has been demonstrated for compounds 2, 4, 7, 8 and 9, and especially for compound 7.
[0194] Compound 7 was further tested for its activity against patient-derived HBV GT A-D in PHH. Briefly, PHH seeded in 384-well plate were infected with patient-derived HBV (GT A-D) at MOI 40 in triplicate. At day 3 pi, compound 7 was added in 3-fold dilutions, starting at 156 μM. 1% DMSO was used as negative control. Fresh medium and compound was replenished every 2 day and cells were harvested at day 10 pi.
[0195] The results thus obtained are shown in
[0196] Thus, compound 7 was found to exhibit potent cccDNA inhibitory activity against all 4 major HBV genotypes A to D, which further confirms that the compounds of formula (I), including in particular compound 7, allow an advantageously improved therapy of HBV infection.
REFERENCES
[0197] Baxter, M., Withey, S., Harrison, S., Segeritz, C. P., Zhang, F., Atkinson-Dell, R., Rowe, C., Gerrard, D. T., Sison-Young, R., Jenkins, R., et al. (2015). Phenotypic and functional analyses show stem cell-derived hepatocyte-like cells better mimic fetal rather than adult hepatocytes. J. Hepatol. 62, 581-589. doi: 10.1016/j.jhep.2014.10.016. [0198] Buckley, G. J., & Strom, B. L (eds). (2017). A National Strategy for the elimination of Hepatitis B and C: Phase Two Report. National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice, Committee on a National Strategy for the Elimination of Hepatitis B and C. Washington (DC): National Academies Press (US); 2017 Mar. 28. [0199] Bukh, J., Pietschmann, T., Lohmann, V., Krieger, N., Faulk, K., Engle, R. E., Govindarajan, S., Shapiro, M., St Claire, M., and Bartenschlager, R. (2002). Mutations that permit efficient replication of hepatitis C virus RNA in Huh-7 cells prevent productive replication in chimpanzees. Proc. Nati. Acad. Sci. USA 99, 14416-14421. [0200] Buster, E. H. C. J., Hansen, B. E., Lau, G. K. K., Piratvisuth, T., Zeuzem, S., Steyerberg, E. W., and Janssen, H. L. A. (2009). Factors that predict response of patients with Hepatitis B e antigen-positive chronic Hepatitis B to peginterferon-alfa. Gastroenterol. 137, 2002-2009. [0201] Cai, D., Nie, H., Yan, R., Guo, J. T., Block, T. M., and Guo, H. (2013) A southern blot assay for detection of hepatitis B virus covalently closed circular DNA from cell cultures. Methods Mol. Biol. 1030, 151-161. [0202] Chen, C. J., Yang, H. I., Su, J., Jen, C. L., You, S. L., Lu, S. N., Huang, G. T., Iloeje, U. H., REVEAL-HBV Study Group. (2006). Risk of Hepatocellular Carcinoma Across a Biological Gradient of Serum Hepatitis B Virus DNA Level. JAMA. 295, 65-73. [0203] Chen, E. Q., Feng, S., Wang, M. L., Liang, L. B., Zhou, L. Y., Du, L. Y., Yan, L. B., Tao, C. M., and Tang, H. (2017). Serum hepatitis B core-related antigen is a satisfactory surrogate marker of intrahepatic covalently closed circular DNA in chronic hepatitis B. Sci. Rep. 7, 173. doi: 10.1038/s41598-017-00111-0. [0204] D'Aiuto, L., Williamson, K., Dimitrion, P., McNulty, J., Brown, C. E., Dokuburra, C. B., Nielsen, A. J., Lin, W. J., Piazza, P., Schurdak, M. E., et al. (2017). Comparison of three cell-based drug screening platforms for HSV-1 Infection. Antiviral Res. 142, 136-140. doi: 10.1016/j.antiviral.2017.03.016. [0205] Ducluzeau, P. H., Lachaux, A., Bouvier, R., Streichenberger, N., Stepien, G., and Mousson, B. (1999). Depletion of mitochondrial DNA associated with infantile cholestasis and progressive liver fibrosis. J. Hepatol. 30, 149-155. [0206] Easterbrook, J., Lu, C., Sakai, Y., and Li, A. P. (2001). Effects of organic solvents on the activities of cytochrome P450 isoforms, UDP-Dependent Glucuronyl transferase, and phenol sulfotransferase in human hepatocytes. Drug Met. Dis. 29, 141-144. [0207] Eglen, R. M., Gilchrist, A., and Reisine, T. (2008). The Use of Immortalized Cell Lines in GPCR Screening: The Good, Bad and Ugly. Comb. Chem. High Throughput Screen 11, 560-565. [0208] Eglen, R. M, and Reisine, T. (2011). Primary Cells and Stem Cells in Drug Discovery: Emerging Tools for High-Throughput Screening. Assay Drug Dev. Technol. 9(2), 108-124. [0209] Engle, S. J, and Vincent, F. (2014). Small Molecule Screening in Human Induced Pluripotent Stem Cell-derived Terminal Cell Types. J. Biol. Chem. 289, 4562-4570. [0210] Fraczek, J., Bolleyn, J., Vanhaecke, T., Rogiers, V., and Vinken, M. (2013). Primary hepatocyte cultures for pharmacotoxicological studies: At the busy crossroad of various anti-dedifferentiation strategies. Arch. Toxicol 87, 577-610. [0211] Fux, C. A., Shirtliff, M., Stoodley, P., and Costerton, J. W. (2005). Can laboratory reference strains mirror ‘real-world’ pathogenesis? Trends in Microbiol. 13, 58-63. [0212] GBD 2013 Mortality and Causes of Death Collaborators. (2015). Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 385, 117-1171. [0213] Godoy, P., Schmidt-Heck, W., Natarajan, K., Lucendo-Villarin, B., Szkolnicka, D., Asplund, A., Björquist, P., Widera, A., Stöber, R., Campos, G., Hammad, S., et al. (2015). Gene networks and transcription factor motifs defining the differentiation of stem cells into hepatocyte-like cells. J. Hepatol 63, 934-42. doi: 10.1016/j.jhep.2015.05.013. [0214] Goldring, C., Antoine. D. J., Bonner, F., Crozier, J., Denning, C., Fontana, R. J., Hanley, N. A., Hay, D. C., Ingelman-Sundberg, M., Juhila, S., et al. (2017). Stem Cell-Derived Models to Improve Mechanistic Understanding and Prediction of Human Drug-Induced Liver Injury. Hepatology 65, 710-721. doi: 10.1002/hep.28886. [0215] Gripon, P., Rumin, S., Urban, S., Le Seyec, J., Glaise, D., Cannie, I., Guyomard, C., Lucas, J., Trepo, C., and Guguen-Guillouzo, C. (2002). Infection of a human hepatoma cell line by hepatitis B virus. PNAS 99, 15655-15660. [0216] Guenther, S., Li, B. C., Miska, S., Krueger, D. H., Meisel, H. & Will, H. (1995). A novel method for efficient amplification of whole hepatitis B virus genomes permits rapid functional analysis and reveals deletion mutants in immunosuppressed patients. J. Virol. 69, 5437-5444. [0217] Guo, J-T., and Guo, H. (2015). Metabolism and function of hepatitis B virus cccDNA: Implications for the development of cccDNA-targeting antiviral therapeutics. Antiviral Res. 122, 91-100. [0218] Guo, H., Jiang, D., Zhou, T., Cuconati, A., Block, T. M., and Guo, J-T. (2007). Characterization of the Intracellular Deproteinized Relaxed Circular DNA of Hepatitis B Virus: an Intermediate of Covalently Closed Circular DNA Formation. J. Virol. 81, 12472-12484. [0219] Halpern, K. B., Shenhav, R., Matcovitch-Natan, O., Toth, B., Lemze, D., Golan, M., Massasa, E. E., Baydatch, S., Landen, S., Moor, A. E., et al. (2017). Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature 542, 352-356. doi: 10.1038/nature21065. [0220] Harrison, R. K. (2016). Phase II and phase III failures: 2013-2015. Nat. Rev. Drug Discov. 15, 817-818. doi:10.1038/nrd.2016.184 [0221] Heslop, J. A., Kia, R., Pridgeon, C. S., Sison-Young, R. L., Liloglou, T., Elmasry, M., Fenwick, S. W., Mills, J. S., Kitteringham, N. R., Goldring, C. E., and Park, B. K. (2017). Donor-Dependent and Other Nondefined Factors Have Greater Influence on the Hepatic Phenotype Than the Starting Cell Type in Induced Pluripotent Stem Cell Derived Hepatocyte-Like Cells. Stem Cells Trans. Med. 6, 1321-1331. [0222] Horvath P., Aulner N., Bickle M., Davies A. M., Nery E. D., Ebner D., Montoya M. C., Ostling P., PietiAinen V., Price L. S., et al. (2016). Screening out irrelevant cell-based models of disease. Nat. Rev. Drug Discov. 15, 751-769. doi: 10.1038/nrd.2016.175 [0223] Iloeje, U. H., Yang, H. I., Su, J., Jen, C. L., You, S. L., Chen, C. J., and the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer—In HBV (the REVEAL-HBV) Study Group. (2006). Predicting cirrhosis risk based on the level of circulating hepatitis B viral load. Gastroenterology 130, 678-686. [0224] Iloeje, U. H., Yang, H. I., Jen, C. L., Su, J., Wang, L. Y., You, S. L., and Chen, C. J. for the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer-Hepatitis B Virus Study Group. (2007). Risk and Predictors of Mortality Associated With Chronic Hepatitis B Infection. Clin. Gasteroenterol. Hepatol. 5, 921-931. [0225] Ishida, Y., Yamasaki, C., Yanagi, A., Yoshizane, Y., Fujikawa, K., Watashi, K., Abe, H., Wakita, T., Hayes, C. N., Chayama, K., and Tateno, C. 2015. Novel robust in vitro hepatitis B virus infection model using fresh human hepatocytes isolated from humanized mice. Am J Pathol. 185, 1275-85. doi: 10.1016/j.ajpath.2015.01.028. [0226] Kajiwara, M., Aoi, T., Okita, K., Takahashi, R., Inoue, H., Takayama, N., Endo, H., Eto, K., Toguchida, J, Uemoto, S., and Yamanaka, S. (2012). Donor-dependent variations in hepatic differentiation from human-induced pluripotent stem cells. PNAS 109, 12538-12543. [0227] Kaneko, S., Kakinuma, S., Asahina, Y., Kamiya, A., Miyoshi, M., Tsunoda, T., Nitta, S., Asano, Y., Nagata, H., Otani, S., et al. (2016). Human induced pluripotent stem cell-derived hepatic cell lines as a new model for host interaction with hepatitis B virus. Sci. Rep. 6, 29358. doi: 10.1038/srep29358. [0228] Kumar R., Pérez-Del-Pulgar S., Testoni B., Lebossé F., and Zoulim F. (2016). Clinical relevance of the study of hepatitis B virus covalently closed circular DNA. Liver Int. 36 Suppl 1, 72-77. doi: 10.1111/liv.13001. [0229] Kuypers, J., and Jerome, K. R. (2017). Applications of Digital PCR for Clinical Microbiology. J. Clin. Microb. pii: JCM.00211-17. doi: 10.1128/JCM.00211-17 [0230] Ladner, S. K., Otto, M. J., Barker, C. S., Zaifert, K., Wang, G. H., Guo, J. T., Seeger, C., and King, R. W. (1997). Inducible expression of human hepatitis B virus (HBV) in stably transfected hepatoblastoma cells: A novel system for screening potential inhibitors of HBV replication. Antimicrob. Agents Chemother. 41, 1715-1720. [0231] Laras, A., Koskinas, J., Dimou, E., Kostamena, A., and Hadziyannis, S. J. (2006). Intrahepatic Levels and Replicative Activity of covalently closed circular Hepatitis B Virus DNA in chronically infected patients. Hepatology 44, 694-702. [0232] Levrero, M., Pollicino, T., Petersen, J., Belloni, L., Raimondo, G., and Dandri, M. (2009). Control of cccDNA function in hepatitis B infection. J. Hepatol. 51, 581-592. [0233] Lin, C. L., and Kao, J. H. (2017). Natural history of acute and chronic hepatitis B: The role of HBV genotypes and mutants. Best Pract. Res. Clin. Gastroenterol. 31, 249-255. doi: 10.1016/j.bpg.2017.04.010. [0234] Liu, F., Wang, X. W., Chen, L., Hu, P., Ren, H., and Hu, H. D. (2016). Systematic review with meta-analysis: development of hepatocellular carcinoma in chronic hepatitis B patients with hepatitis B surface antigen seroclearance. Aliment. Pharmacol. Ther. 43, 1253-1261. [0235] Lok, A. S., Zoulim, F., Dusheiko, G., and Ghany, M. G. (2017). Hepatitis B cure: From discovery to regulatory approval. J. Hepatol. doi: 10.1016j.jhep.2017.05.008. [0236] Locarnini, S., and Zoulim, F. (2010). Molecular genetics of HBV infection. Antiviral Ther. 15 (Suppl 3), 3-14. [0237] Lu, J., Einhorn, S., Venkatarangan, L., Miller, M., Mann, D. A., Watkins, P. B., and LeCluyse, E. (2015). Morphological and Functional Characterization and Assessment of iPSC-Derived Hepatocytes for In Vitro Toxicity Testing. Toxicol. Sci. 147, 39-54. [0238] Mabit, H., Vons, C., Dubancher, S., Cape, F., Franco, D., and Petit, M. A. (1996). Primary cultured normal human hepatocytes for hepatitis B virus receptor studies. J. Hepatol. 24, 403-412. [0239] Mason, W. S., Gill, U. S., Litwin, S., Zhou, Y., Peri, S., Pop, O., Hong, M. L., Naik, S., Quaglia, A., Bertoletti, A., and Kennedy, P. T. (2016). HBV DNA Integration and Clonal Hepatocyte Expansion in Chronic Hepatitis B Patients Considered Immune Tolerant. Gastroenterology. 151, 986-998.e4. doi: 10.1053/j.gastro.2016.07.012. [0240] Moffat, J. G., Vincent, F., Lee, J. A., Eder, J., and Prunotto, M. (2017). Opportunities and challenges in phenotypic drug discovery: an industry perspective. Nat. Rev. Drug Discov. July 7. doi: 10.1038/nrd.2017.111. [0241] Nassal M. (2015). HBV cccDNA: viral persistence reservoir and key obstacle for a cure of chronic hepatitis B. Gut 64, 1972-84. doi: 10.1136/gutjnl-2015-309809. [0242] Newbold, J. E., Xin, H., Tencza, M., Sherman, G., Dean, J., Bowden, S., and Locarnini, S. (1995). The Covalently Closed Duplex Form of the Hepadnavirus Genome Exists In Situ as a Heterogeneous Population of Viral Minichromosomes. J. Virol. 69, 3350-3357. [0243] Paul, S. M., Mytelka, D. S., Dunwiddie, C. T., Persinger, C. C., Munos, B. H., Lindborg, S. R., and Schacht, A. L. (2010). How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat. Rev. Drug Discov. 9, 203-214. [0244] Peters, J. U., Hert, J., Bissantz, C., Hillebrecht, A., Gerebtzoff, G., Bendels, S., Tillier, F., Migeon, J., Fischer, H, Guba, W., and Kansy, M. (2012). Can we discover pharmacological promiscuity early in the drug discovery process? Drug Discov. Today. 17, 325-335. doi: 10.1016/j.drudis.2012.01.001. [0245] Pontecorvo, G., Riddle, P. N., and Hales, A. (1977). Time and mode of fusion of human fibroblasts treated with polyethylene glycol (PEG). Nature 265, 257-258. doi:10.1038/265257a0 [0246] Rajoriya, N., Combo, C., Zoulim, F., and Janssen, H. L. A. (2017). How viral genetic variants and genotypes influence disease and treatment outcome of chronic hepatitis B. Time for an individualized approach? J. Hepatol. pii: S0168-8278(17)32154-2. doi: 10.1016/j.jhep.2017.07.011. [0247] Revill P., Testoni B., Locarnini S., and Zoulim F. (2016). Global strategies are required to cure and eliminate HBV infection. Nat. Rev. Gastroenterol. Hepatol. 13, 239-248. doi: 10.1038/nrgastro.2016.7. [0248] Sakurai F., Mitani S., Yamamoto T., Takayama K., Tachibana M., Watashi K., Wakita T., Iijima S., Tanaka Y., and Mizuguchi H. (2017). Human induced-pluripotent stem cell-derived hepatocyte-like cells as an in vitro model of human hepatitis B virus infection. Sci. Rep. 7, 45698. doi: 10.1038/srep45698. [0249] Schreiner, S., and Nassal, M. (2017). A Role for the Host DNA Damage Response in Hepatitis B Virus cccDNA Formation and Beyond? Viruses 9,125. doi:10.3390/v9050125 [0250] Schweitzer, A., Horn, J., Mikolajczyk, R T., Krause, G., and Ott, J. J. (2015). Estimations of worldwide prevalence of chronic hepatitis B virus infection: a systematic review of data published between 1965 and 2013. Lancet 386, 1546-1555. doi: 10.1016/S0140-6736(16)30579-7. [0251] Seeger, C., and Mason, W. (2000). Hepatitis B virus biology. Microbiol. Molec. Biol. Rev. 64, 51-58. [0252] Sells, M. A., Chen, M. L., and Acs, G. (1987). Production of hepatitis B virus particles in Hep G2 cells transfected with cloned hepatitis B virus DNA. Proc. Nati. Acad. Sci. USA 84, 1005-1009. [0253] Shi Y., Inoue H., Wu J. C., and Yamanaka S. (2017). Induced pluripotent stem cell technology: a decade of progress. Nat. Rev Drug Discov. 16, 115-130. doi: 10.1038/nrd.2016.245. [0254] Shlomai, A., Schwartz, R. E., Ramanan, V., Bhatta, A., de Yong, Y. P., Bhatia, S. N., and Rice, C. M. (2014). Modeling host interactions with hepatitis B virus using primary and induced pluripotent stem cell-derived hepatocellular systems. PNAS 111, 12193-12198. [0255] Soto-Gutierrez, A., Gough, A., Vernetti, L. A., Taylor, D. L., and Monga, S. P. (2017). Pre-clinical and clinical investigations of metabolic zonation in liver diseases: The potential of microphysiology systems. Exp. Biol. Med. 0, 1-12. DOI: 10.1177/1535370217707731 [0256] Sozzi, V., Walsh, R., Littlejohn, M., Colledge, D., Jackson, K., Warner, N., Yuen, L., Locarnini, S. A., and Revill, P. A. (2016). In Vitro Studies Show that Sequence Variability Contributes to Marked Variation in Hepatitis B Virus Replication, Protein Expression, and Function Observed across Genotypes. J. Virol. 90, 10054-10064. [0257] Stanaway, J. D., Flaxman, A. D., Naghavi, M., Fitzmaurice, C., Vos, T., Abubakar, I., Abu-Raddad, L. J, Assadi, R., Bhala, N., Cowie, B., et al. (2016). The global burden of viral hepatitis from 1990 to 2013: findings from the Global Burden of Disease Study 2013. Lancet. 388, 1081-1088. doi: 10.1016/S0140-6736(16)30579-7. [0258] Sureau, C., Romet-Lemonne, J. L., Mullins, J. I., and Essex, M. (1986). Production of hepatitis B virus by a differentiated human hepatoma cell line after transfection with cloned circular HBV DNA. Cell 47, 37-47. [0259] Tang, H., and McLachlan, A. (2001). Transcriptional regulation of hepatitis B virus by nuclear hormone receptors is a critical determinant of viral tropism. PNAS 98, 1841-1846. [0260] Torre, C., Perret, C., and Colnot, S. (2010). Molecular determinants of liver zonation. Prog. Mol. Biol. Transl. Sci. 97, 127-150. [0261] Uhlen M., Fagerberg, L., Hallström B. M., Lindskog, C., Oksvold P., Mardinoglu A., Sivertsson A., Kampf C., Sjöstedt E., Asplund A., et al. (2015). Tissue-based map of the human proteome. Science 347, 1260419. doi:10.1126/science. 1260419. [0262] Ursu, A., Schöler, H. R., and Waldmann, H. (2017). Small-molecule phenotypic screening with stem cells. Nat. Chem. Biol. 13, 560-563. [0263] Vincent F., Loria P., Pregel, M., Stanton R., Kitching L., Nocka K., Doyonnas R., Steppan C., Gilbert A., Schroeter T., and Peakman M. C. (2015). Developing predictive assays: The phenotypic screening “rule of 3”. Sci. Transl. Med. 7, 293ps15. doi: 10.1126/scitranslmed.aab1201 [0264] Wang, J., Shen, T., Huang, X., Kumar, G. R., Chen, X., Zeng, Z., Zhang, R., Chen, R., Li, T., Zhang, T., et al. (2016). Serum hepatitis B virus RNA is encapsidated pregenome RNA that may be associated with persistence of viral infection and rebound. J. Hepatol. 65, 700-10. doi: 10.1016/j.jhep.2016.05.029. [0265] Waring, M. J., Arrowsmith, J., Leach, A. R., Leeson P. D., Mandrell S., Owen R. M., Pairaudeau G., Pennie W. D., Pickett S. D., Wang J., Wallace O., and Weir A. (2015). An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat. Rev. Drug Discov. 14, 475-486. doi:10.1038/nrd4609. [0266] Werle-Lapostolle, B., Bowden, S., Locarnini, S., Wursthorn, K., Petersen, J., Lau, G., Trepo, C., Marcellin, P., Goodman, Z., Delaney, W. E., et al. (2004). Persistence of cccDNA During the Natural History of Chronic Hepatitis B and Decline During Adefovir Dipivoxil Therapy. Gastroenterology 126, 1750-1758. [0267] WHO. (2016). Global Health Sector Strategy on Viral Hepatitis, 2016-2021: Toward Ending Viral Hepatitis. WHO, Geneva, Switzerland. [0268] Yan, H., Zhong, G., Xu, G., He, W., Jing, Z., Gao, Z., Huang, Y., Qi, Y., Peng, B., Wang, H., et al. (2012). Sodium taurocholate cotransporting polypeptide is a functional receptor for human hepatitis B and D virus. Elife 1, e00049. doi: 10.7554/eLife.00049. [0269] Zhang, J. D., Hatje, K., Sturm, G., Broger, C., Ebeling, M., Burtin, M., Terzi, F., Pomposiello, S. I., and Badi, L. (2017). Detect tissue heterogeneity in gene expression data with BioQC. BMC Genomics 18, 277. doi: 10.1186/s12864-017-3661-2 [0270] Zhang, J. H., Chung, T. D. Y., and Oldenburg, K. R. (1999). A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J. Biomol. Screen. 4, 67-73. [0271] Zhang, X., Lu W., Zheng Y., Wang W., Bai L., Chen L., Feng Y., Zhang Z., and Yuan Z. (2016). In situ analysis of intrahepatic virological events in chronic hepatitis B virus infection. J Clin. Invest. 126, 1079-1092. doi:10.1172/JCI83339.