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, 171 (2), 641-53

Analysis of Liver Repair Mechanisms in Alagille Syndrome and Biliary Atresia Reveals a Role for Notch Signaling

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Analysis of Liver Repair Mechanisms in Alagille Syndrome and Biliary Atresia Reveals a Role for Notch Signaling

Luca Fabris et al. Am J Pathol.

Abstract

Patients with Alagille syndrome (AGS), a genetic disorder of Notch signaling, suffer from severe ductopenia and cholestasis, but progression to biliary cirrhosis is rare. Instead, in biliary atresia (BA) severe cholestasis is associated with a pronounced "ductular reaction" and rapid progression to biliary cirrhosis. Given the role of Notch in biliary development, we hypothesized that defective Notch signaling would influence the reparative mechanisms in cholestatic cholangiopathies. Thus we compared phenotype and relative abundance of the epithelial components of the hepatic reparative complex in AGS (n = 10) and BA (n = 30) using immunohistochemistry and computer-assisted morphometry. BA was characterized by an increase in reactive ductular and hepatic progenitor cells, whereas in AGS, a striking increase in intermediate hepatobiliary cells contrasted with the near absence of reactive ductular cells and hepatic progenitor cells. Hepatocellular mitoinhibition index (p21(waf1)/Ki67) was similar in AGS and BA. Fibrosis was more severe in BA, where portal septa thickness positively correlated with reactive ductular cells and hepatic progenitor cells. AGS hepatobiliary cells failed to express hepatic nuclear factor (HNF) 1beta, a biliary-specific transcription factor. These data indicate that Notch signaling plays a role in liver repair mechanisms in postnatal life: its defect results in absent reactive ductular cells and accumulation of hepatobiliary cells lacking HNF1beta, thus being unable to switch to a biliary phenotype.

Figures

Figure 1
Figure 1
Immunohistochemistry for CK7 in a BA sample, showing the coexistence of the three different epithelial cell types in ductular reaction. Insets: RDCs (A), IHBCs (B), and HPCs (C). Original magnification: ×200; insets: ×400 (A), ×600 (B and C). Their different morphological properties and classification are detailed in Materials and Methods.
Figure 2
Figure 2
Morphometric quantification of the enrichment in RDCs (G), IHBCs (H), and HPCs (I) in AGS and BA. Representative examples of liver samples immunostained by CK19 (A–C) and CK7 (D–F) from patients with AGS, BA at transplant, and BA at Kasai are shown. IHBC enrichment in AGS is evident by comparing micrograph A (CK19 does not stain IHBCs) with micrograph B (CK7 stains all component of the ductular reaction). Micrographs B and E compare CK19 and CK7 immunostaining in BA taken at the time of transplant; C and F are the same at the time of the Kasai operation. Note in E the periportal localization and lower enrichment of IHBCs. Note also the absence of RDCs and HPCs in AGS (A). HPCs are shown as arrowheads in B and C. *P < 0.01 versus AGS; **P < 0.0001 versus AGS. Magnification, ×200 in all micrographs.
Figure 3
Figure 3
Correlation between the extent of RDCs (A) or IHBCs (B) and the number of HPCs. The number of HPCs showed a significant positive correlation with the extension of ductular reaction (r = 0.506, P < 0.0001) (A) and a significant but inverse correlation with the expansion of IHBCs (r = −0.511, P < 0.0001) (B). HPCs, RDCs, and IHBCs were measured as outlined in the method section and shown in Figures 1 and 2.
Figure 4
Figure 4
Dual immunofluorescence staining for CK7 (tetramethylrhodamine B isothiocyanate) and the hepatocellular microsomal marker LKM-1 (FITC) in AGS (A) and BA (B). In C, dual immunofluorescence staining for CK7 (tetramethylrhodamine B isothiocyanate) and the hepatocellular canalicular marker BSEP (FITC) in AGS is shown. IHBCs clearly express hepatocellular markers (LKM-1, cytoplasmic; and BSEP, canalicular) and are much more represented in AGS than in BA. In BA, they are mainly located in the periportal area, in strict contiguity with CK7-positive/LKM-negative/BSEP-negative ductular cells. Magnification: ×400 (A and B), ×600 (C and D).
Figure 5
Figure 5
Cell expression of HNF4α and HNF6 in serial sections from AGS and BA. RDCs, HPCs, and IHBCs are identified by immunoreactivity for CK7 (A and D). In both cholangiopathies (AGS: A–C, and BA: D and E), HNF4α (B and E), and HNF6 (C and F) share a similar pattern of expression, where hepatocytes and IHBC are positive for HNF4α and HNF6, whereas RDCs (arrows, see also insets in E and F) and bile ducts are positive for HNF6 and negative for HNF4α. Magnification: ×400 in all micrographs, ×600 in insets.
Figure 6
Figure 6
Immunophenotype of IHBC is different in AGS compared with BA. A shows the expression of the HNF1β transcription factor (a transcription factor regulated by Jagged1/Notch signaling and involved in biliary differentiation) by IHBCs, RDCs, and HPCs in a representative case of biliary atresia. B shows instead the lack of expression of the HNF1β transcription factor by IHBCs in a representative sample of AGS. Double immunostaining for CK7 (TrueBlue) and HNF1β (horseradish peroxidase). Magnification: ×200 in all micrographs, ×600 in insets.
Figure 7
Figure 7
Proliferation (Ki67-positive nuclei) and replicative arrest ratio (p21/Ki67-positive nuclei) of hepatocytes in AGS, BA-Tx, and BA-Kasai compared with NL. In all diseases, hepatocyte proliferation (A) was markedly enhanced with respect to NL (dotted column); moreover, the hepatocyte replicative arrest ratio was significantly reduced in AGS, BA-Tx, and BA-Kasai with respect to NL (B). *P < 0.01 versus NL; **P < 0.0001 versus NL.
Figure 8
Figure 8
Different pattern of fibrosis between AGS (A and C) and BA (B and D) (Masson’s trichrome staining; magnification, ×200) expressed by septal thickness (A and B) and pericellular fibrosis (C and D). The column plots below show the mean (±SD) and data distribution for septal thickness (in micrometers) (E) and pericellular fibrosis (semiquantitative assessment, see Assessment of Fibrosis under Materials and Methods for details) (F) in AGS and BA. Statistical significance (*P < 0.01) calculated by using the Student’s t-test. Plots in G and H show the correlation between the septal thickness and the extent of RDCs (G) and IHBCs (H). Septal thickness significantly and directly correlated with the extent of RDCs (r = 0.742, P < 0.0001) and inversely with the IHBC area (r = −0.620, P < 0.0001) (A and B).

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