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221
Chapter 16
A Gene Ontology Tutorial in Python
Alex Warwick Vesztrocy and Christophe Dessimoz
Abstract
This chapter is a tutorial on using Gene Ontology resources in the Python programming language. 
This entails querying the Gene Ontology graph, retrieving Gene Ontology annotations, performing gene 
enrichment analyses, and computing basic semantic similarity between GO terms. An interactive version of 
the tutorial, including solutions, is available at http://gohandbook.org.
Key words Gene Ontology, Tutorial, Python
1  Introduction
One of the main goals of developing a formal ontology is to facili-
tate computational analysis. The purpose of this chapter is to pro-
vide a hands-on introduction to handling GO terms and GO 
annotations in Python. This tutorial also shows how Python can be 
used to perform GO term enrichment analyses, as well as how to 
compute the similarity between GO terms.
This tutorial uses Python, but other popular languages com-
monly used to perform GO analyses include Java, R, Perl, and 
Matlab. The Gene Ontology consortium website maintains a list of 
software libraries, accessible from
ftp://ftp.geneontology.org/pub/go/www/GO.tools_by_type.
software.shtml
An interactive version of this tutorial, with model solutions to 
all the questions, is available from the book homepage at http://
gohandbook.org.
2  Querying the Gene Ontology
A fundamental first step is to retrieve the Gene Ontology and anal-
yse that structure (Chap. 3 [1]).
Christophe Dessimoz and Nives Škunca (eds.), The Gene Ontology Handbook, Methods in Molecular Biology, vol. 1446,
DOI 10.1007/978-1-4939-3743-1_16, © The Author(s) 2017
222
One convenient Python package available to query the GO is 
GOATOOLS [2]. This package can read the GO structure stored 
in OBO format, which is available from the GO website (see 
Chap. 11 [3]). After loading this file, it is possible to traverse the 
GO structure, search for particular GO terms, and find out which 
other terms they are related to and how.
This package is available on the Python Package Index (PyPI), 
a standard repository of python libraries. As such, it is possible to 
install it locally using the command1:
              pip install goatools
The GOATOOLS package contains the functions necessary to 
parse the GO in OBO format, to query it, and to visualise the 
ontology. Using the function obo_parser.GODag() from 
GOATOOLS, the GO file can be loaded. Each GO term in the 
resulting object is an instance of the GOTerm class, which contains 
many useful attributes, such as:
●● GOTerm.name: textual definition;
●● GOTerm.namespace: the ontology the term belongs to (i.e., 
Molecular Function [MF], Biological Process [BP], or Cellular 
Component [CC]);
●● GOTerm.parents: list of parent terms;
●● GOTerm.children: list of children terms;
●● GOTerm.level: shortest distance to the root node;
1
 GOATOOLS version 0.6.4 was used to write this tutorial and the exercises. 
To install this exact version, use pip install goatools==0.6.4
Exercise 2.1
Download the GO basic file in OBO format (go-basic.obo), and 
load the GO using the function obo_parser.GODag() from 
GOATOOLS. Using this library, answer the following questions:
(a) What is the name of the GO term GO:0048527?
(b) What are the immediate parent(s) of the term GO:0048527?
(c) What are the immediate children of the term GO:0048527?
(d) Recursively find all the parent and child terms of the term 
GO:0048527. Hint: use your solutions to the previous two ques-
tions, with a recursive loop.
(e) How many GO terms have the word “growth” in their name?
(f) What is the deepest common ancestor term of GO:0048527 and 
GO:0097178?
(g) Which GO terms regulate GO:0007124 (pseudohyphal growth)? 
Hint: load the relationship tags and look for terms which define 
regulation.
Alex Warwick Vesztrocy and Christophe Dessimoz
223
GO:0048627
myoblast development
GO:0044699
single-organism process
GO:0044763
single-organism cellular process
is_a
GO:0044767
single-organism developmental process
is_a
GO:0048869
cellular developmental process
is_a is_a
GO:0048468
cell development
is_a
GO:0008150
biological_process
is_a
GO:0009987
cellular process
is_a
GO:0032502
developmental process
is_a
is_a is_a
GO:0048856
anatomical structure development
is_a
is_a
is_a
Fig. 1 Selected parts of the Gene Ontology can be visualised using the GOATOOLS library [2]
Exercise 2.2
Using the visualisation function in the GOATOOLS library, answer the 
following questions:
(a) Produce a figure similar to that in Fig. 1, for the GO term 
GO:0097190. From the visualisation, what is the name of this term?
(b) Using this figure, what is the most specific term that is in the parent 
terms of both GO:0097191 (extrinsic apoptotic signalling pathway) 
and GO:0038034 (signal transduction in absence of ligand)? This is 
also referred to as the lowest common ancestor (see Chap. 12 [4]).
Furthermore, other tag-value lines such as the “relation-
ships” can be loaded with an optional argument of, e.g., 
optional_attrs=['relationship'].
The GOATOOLS library also includes functions to visualise the 
GO graph. For instance, it is possible to depict the location of a par-
ticular GO term in the ontology using the method GOTerm.draw_
lineage(). For example, the plot in Fig. 1 showing the  lineage of 
the GO term GO:0048527 was created using this function.
As an alternative to GOATOOLS and OBO files, it is possible 
to retrieve information relating to a specific term from a web ser-
vice. One such service is the EMBL-EBI QuickGO resource (see 
A Gene Ontology Tutorial in Python
224
Chap. 11; [3, 5]), which can provide descriptive information about 
GO terms in OBO-XML format. It is possible to request this 
OBO-XML file over HTTP, using a URL of the form
http://www.ebi.ac.uk/QuickGO/GTerm?id=<GO_ID>& 
format=oboxml
where <GO_ID> is replaced with the GO identifier for the term of 
interest. In Source Code 2.1, an example function to automate this 
in Python is listed, which uses the urllib library to request the OBO-
XML and the xmltodict library to parse the XML into an easy to use 
dictionary structure. Both libraries are available to install using pip, 
if required. Note that the future library was used to ensure that the 
function is both Python 2 and 3 compatible.
The dictionary structure that is returned can vary based on what 
information is available in the database. One example of an informa-
tion-rich term is GO:0043065. A visualisation of the dictionary 
Source Code 2.1. get_oboxml() function for Python 2 and 3.
from future.standard_library import install_aliases
install_aliases()
from urllib.request import urlopen
import xmltodict
def get_oboxml(go_id):
    """
  This function retrieves the OBO-XML for a 
given Gene Ontology term, using EMBL-EBI's 
QuickGO browser.
  Input: go_id - a valid Gene Ontology ID, 
e.g. GO:0048527.
    """
  quickgo_url= "http://ebi.ac.uk/QuickGO/GTerm?id="+ 
go_id+"&format=oboxml"
 oboxml = urlopen(quickgo_url)
 # Check the response
 if(oboxml.getcode() == 200):
 obodict = xmltodict.parse(oboxml.read())
 return obodict
 else:
  raise ValueError("Couldn't receive OBOXML 
from QuickGO. Check URL and try again.")
Fig. 2 Visualisation of the keys in the hierarchical dictionary structure returned by 
get_oboxml('GO:0043065')
obo
header term
format-version auto-generated-by synonymtypedef default-namespace remark id name namespace def comment synonym xref is_a relationship
id name scope defstr type to
Alex Warwick Vesztrocy and Christophe Dessimoz
225
structure for this term, created with the visualisedictionary 
package available from PyPI (using pip), has been included in Fig. 2.
The main advantage of using a web service, such as QuickGO, 
is that there is no requirement to download and parse the entire 
Gene Ontology structure; only the information required is retrieved. 
This is therefore more efficient if only a few particular terms are 
involved in an analysis. By contrast, for analyses involving many 
terms, the file-based approach described above is more suitable.
3  Retrieving GO Annotations
This section looks at manipulating the Gene Association File 
(GAF) standard, using a parser from the BioPython package [6].
Firstly, a GAF file, which contains GO annotations, shall be 
downloaded from the UniProt-GOA database [7]. Their website 
(https://www.ebi.ac.uk/GOA/downloads) lists a number of vari-
ants. For this tutorial the reduced GAF file containing only the gene 
association data for Arabidopsis thaliana is going to be used.
Annotations from GAF files can be loaded into a Python diction-
ary using an iterator from the BioPython package (Bio.UniProt.
GOA.gafiterator). Source Code 3.1 shows a simple example 
of this being used, in order to print out the protein ID for each 
annotation.
Exercise 2.3
Using the function get_oboxml(), listed in Source Code 2.1, answer 
the following questions:
(a) Find the name and description of the GO term GO:0048527 (lat-
eral root development). Hint: print out the dictionary returned by 
the function and study its structure, or use the visualisation in Fig. 2.
(b) Look at the difference in the OBO-XML output for the GO terms 
GO:00048527 (lateral root development) and GO:0097178 
(ruffle assembly), then generate a table of the synonymous rela-
tionships of the term GO:0097178.
Source Code 3.1
from Bio.UniProt.GOA import gafiterator
import gzip
# filename = <LOCATION OF GAF FILE>
filename = 'gene_association.goa_arabidopsis.gz'
with gzip.open(filename, 'rt') as fp:
    for annotation in gafiterator(fp):
        # Output annotated protein ID
        print(annotation['DB_Object_ID'])
A Gene Ontology Tutorial in Python
226
Recall that the latest GAF standard, version 2.1, has 17 tab- 
delimited fields, which are described in detail in Chap. 3 [1]. Some 
of them include:
●● 'DB': the protein database;
●● 'DB_Object_ID': protein ID;
●● 'Qualifier': annotation qualifier (such as NOT);
●● 'GO_ID': GO term;
●● 'Evidence': evidence code.
4  GO Enrichment or Depletion Analysis
As discussed in detail in Chap. 13 [8] one of the most common 
analyses performed on GO data is an enrichment (or depletion) 
analysis. In this tutorial, the GOEnrichmentStudy() function 
available in the GOATOOLS library (which has been seen in sec-
tion 2) will be used.
The GOEnrichmentStudy() function requires the follow-
ing arguments:
 1. the background set of terms (also known as the “population 
set”), passed as a list of GO term IDs;
 2. associations between proteins IDs and GO term IDs, passed as 
a dictionary with protein IDs as the keys and sets of associated 
GO terms as the values;
 3. the Gene Ontology structure, i.e., the output by the obo_
parser() function from GOATOOLS;
 4. whether annotations should be propagated to all parent terms, 
(defined in terms of is_a tags, only), indicated by setting the 
optional boolean parameter propagate_counts to True 
(default) or False;
Exercise 3.1
(a) Find the total number of annotations for Arabidopsis thaliana with 
NOT qualifiers. What is this as a percentage of the total number of 
annotations for this species?
(b) How many genes (of Arabidopsis thaliana) have the annotation 
GO:0048527 (lateral root development)?
(c) Generate a list of annotated proteins which have the word “growth” 
in their name.
(d) There are 21 evidence codes used in the Gene Ontology project. 
As discussed in Chap. 3 [1], many of these are inferred, either by 
curators or automatically. Find the counts of each evidence code in 
the Arabidopsis thaliana annotation file.
Alex Warwick Vesztrocy and Christophe Dessimoz
227
 5. the significance level, indicated by setting the optional parameter 
alpha to the desired cut-off (default: 0.05);
 6. the foreground set of terms (also known as “study set”), indi-
cated by setting the parameter study to a list of GO term IDs;
 7. the list of method(s) to be used to assess significance, indicated 
by setting the parameter methods to a list containing one or 
several of these elements:
(a) "bonferroni": Fisher’s exact test with Bonferroni cor-
rection for multiple testing;
(b) "sidak": Fisher’s exact test with Šidák correction for mul-
tiple testing;
(c) "holm": Fisher’s exact test with Holm–Bonferroni correc-
tion for multiple testing;
(d) "fdr": Fisher’s exact test, controlling the false discovery 
rate (see Chap. 13 [8]).
The function returns the list of over-represented and under-
represented GO terms in the population set, compared to the 
background set.
5  Computing Basic Semantic Similarities Between GO Terms
In this section, the focus is on computing semantic similarity 
between GO terms, based on ideas presented in detail in Chap. 12 
[4]. Semantic similarity measures enable us to quantify the func-
tional similarity of genes annotated with GO terms.
Recall that semantic similarity measures are broadly separated 
in two categories: graph-based and information-theoretic  measures. 
The former relies only on the structure of the Gene Ontology 
graph, whilst the latter also accounts for the information content 
of the terms.
One graph-based measure of semantic similarity, presented in 
Chap. 12 [4], is the inverse of the number of edges separating two 
Exercise 4.1
Perform an enrichment analysis using the list of genes with the “growth” 
keyword from exercise 3.1.c. Use the Arabidopsis thaliana annotation 
set as background, also from exercise 3.1, and the GO structure from 
exercise 2.1.
(a) Which GO term is most significantly enriched or depleted? Does 
this make sense?
(b) How many terms are enriched, when using the Bonferroni cor-
rected p-value ≤ 0.01?
(c) How many terms are enriched, when using the false discovery rate 
(a.k.a. q-value) ≤ 0.01?
A Gene Ontology Tutorial in Python
228
terms. It is possible to compute the minimum number of edges 
separating two terms (t1, t2) by first finding the deepest common 
ancestor (tDCA). Then the difference in depth between each term 
and the deepest common ancestor can be used to calculate the 
minimum distance between the terms. i.e.,
 min_ ,distance depth depth depth DCAt t t t t1 2 1 2 2( ) = ( ) + ( ) − × ( )  
Further, one example of an information-theoretic measure (see 
Chap. 12 [4]) is Resnik’s similarity measure—the information con-
tent of the most informative common ancestor of the two terms in 
question. The information content of a term is defined as the nega-
tive logarithm of its probability, which can be estimated from the 
frequency of the term in the annotation database of choice.
Acknowledgements
We thank Adrian Altenhoff, Debra Klopfenstein, and Haibao Tang 
for helpful feedback on the tutorial. CD acknowledges Swiss 
National Science Foundation grant 150654 and UK BBSRC grant 
BB/M015009/1. Open Access charges were funded by the 
University College London Library, the Swiss Institute of 
Bioinformatics, the Agassiz Foundation, and the Foundation for 
the University of Lausanne.
Open Access This chapter is distributed under the terms of the 
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits use, dupli-
cation, adaptation, distribution and reproduction in any medium 
or format, as long as you give appropriate credit to the original 
author(s) and the source, a link is provided to the Creative 
Commons license and any changes made are indicated.
Exercise 5.1
(a) GO:0048364 (root development) and GO:0044707 (single- 
multicellular organism process) are two GO terms taken from Fig. 1. 
Calculate the semantic similarity between them based on the inverse 
of the semantic distance (number of branches separating them).
(b) Calculate the information content (IC) of the GO term 
GO:0048364 (root development), based on the frequency of 
observation in Arabidopsis thaliana.
(c) Calculate the Resnik similarity measure between the same two 
terms as in part a.
Alex Warwick Vesztrocy and Christophe Dessimoz
229
The images or other third party material in this chapter are 
included in the work’s Creative Commons license, unless indicated 
otherwise in the credit line; if such material is not included in the 
work’s Creative Commons license and the respective action is not 
permitted by statutory regulation, users will need to obtain per-
mission from the license holder to duplicate, adapt or reproduce 
the material.
References
1. Gaudet P, Škunca N, Hu JC, Dessimoz C (2016) 
Primer on the gene ontology. In: Dessimoz C, 
Škunca N (eds) The gene ontology handbook. 
Methods in molecular biology, vol 1446. Humana 
Press. Chapter 3
2. Tang H, Klopfenstein D, Pedersen B et al 
(2015) GOATOOLS: tools for gene ontology, 
Zenodo
3. Munoz-Torres M, Carbon S (2016) Get GO! 
retrieving GO data using AmiGO, QuickGO, 
API, files, and tools. In: Dessimoz C, Škunca N 
(eds) The gene ontology handbook. Methods in 
molecular biology, vol 1446. Humana Press. 
Chapter 11
4. Pesquita C (2016) Semantic similarity in the 
gene ontology. In: Dessimoz C, Škunca N (eds) 
The gene ontology handbook. Methods in 
molecular biology, vol 1446. Humana Press. 
Chapter 12
5. Binns D, Dimmer E, Huntley R et al (2009) 
QuickGO: a web-based tool for Gene Ontology 
searching. Bioinformatics 25:3045–3046
6. Cock PJA, Antao T, Chang JT et al (2009) 
Biopython: freely available Python tools for 
computational molecular biology and bioinfor-
matics. Bioinformatics 25:1422–1423
7. Huntley RP, Sawford T, Mutowo-Meullenet P 
et al (2015) The GOA database: gene Ontology 
annotation updates for 2015. Nucleic Acids Res 
43:D1057–63
8. Bauer S (2016) Gene-category analysis. In: 
Dessimoz C, Škunca N (eds) The gene ontology 
handbook. Methods in molecular biology, vol 
1446. Humana Press. Chapter 13
A Gene Ontology Tutorial in Python


A Gene Ontology Tutorial in Python

Functional role of ALK-related signal cascades on modulation of epithelial-mesenchymal transition and apoptosis in uterine carcinosarcoma

CASE REPORT Open Access
Good outcome following liver
transplantation using pericardial-
peritoneum window for hepato-atrial
anastomosis to overcome advanced
hepatic alveolar echinococcosis and
secondary Budd-Chiari Syndrome - a case
report
Konrad Kobryń1*, Rafał Paluszkiewicz1, Krzysztof Dudek1, Urszula Ołdakowska-Jedynak2, Michał Korba1,
Joanna Raszeja-Wyszomirska2, Piotr Remiszewski1, Michał Grąt1, Piotr Milkiewicz2, Waldemar Patkowski1
and Marek Krawczyk1
Abstract
Background: This report presents a case of a 57- year old female with advanced Hepatic Alveolar Echinococcosis
causing a secondary Budd-Chiari Syndrome due to infiltration of the suprahepatic inferior vena cava treated
successfully by liver transplantation.
Case presentation: A temporary veno-venous bypass was introduced, but a typical end to end cavo-caval
anastomosis wasn’t possible in this case. In order to access a disease free part of the inferior vena cava,
an oval window of the diaphragm was excised, providing communication between the peritoneum and
pericardium. A vascular clamp was placed onto the right atrium which allowed for an atrial-caval anastomosis. The
remainder of hepatectomy was performed in a conventional manner. In the post-operative period and during the
18 month follow-up there were no complications. The patient remains in good general condition with optimal graft
function.
Conclusions: A hepato-atrial anastomosis with a pericardial-peritoneum window during liver transplantation is feasible
and extends the curability potential for patients with advanced Hepatic Alveolar Echinococcosis considered for liver
transplantation.
Keywords: Atrium–IVC anastomosis, Budd-Chiari Syndrome, Hepatic alveolar Echinococcosis, Liver transplantation,
Pericardial-peritoneum window, Case report
* Correspondence: konradkobryn@gmail.com
1Department of General, Transplant and Liver Surgery, Medical University of
Warsaw, Poland. Banacha Street 1a, 02-097 Warsaw, Poland
Full list of author information is available at the end of the article
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Kobryń et al. BMC Surgery  (2017) 17:5 
DOI 10.1186/s12893-017-0205-2
Background
Advanced hepatic alveococcosis due to its volume may
interfere with the hepatic veins and inferior vena cava
(IVC) causing Budd-Chiari syndrome (BCS) which is an
indication for liver transplantation (LTx). The throm-
bosis and stricture may be found at any point, ranging
from the hepatic veins to the right atrium along the IVC
[1, 2]. When this is the case, hepatectomy of the dis-
eased liver requires supra hepatic IVC clamping at
the right atrium, with later end-to-end anastomosis
with the donor liver IVC cuff [3–5]. Our report pre-
sents a rare approach during hepatectomy, periopera-
tive management and excellent postoperative results
of the patient.
Case presentation
A 57 year old female patient was qualified for LTx due
to BCS caused by an advanced Echinococcus multilocu-
laris infection. The patient received Albendazole treat-
ment for several years which was terminated two years
prior to transplantation due to a developed post-drug
pancytopenia. No other anthelminthic drugs were ad-
ministered until LTx. Furthermore, portal hypertension,
esophageal and gastric varices, portal hypertensive gas-
tropathy, and ascites were present at time of transplant
qualification. Celiac disease, gastro-esophageal reflux
disease (GERD), and L1 vertebral fracture were associat-
ing commorbidities.
The size of the alveolar lesion in segments III–VIII
was 110 × 75 × 70 mm (Fig. 1a) and involved the hepatic
vein confluence, causing narrowing of the IVC lumen
with mild but disturbed blood flow. The intrahepatic
IVC was free of abnormalities. The lesion occluded the
left and middle hepatic veins, extending towards the
confluence of the right hepatic vein with the IVC
(Fig. 1b). The lumen was narrowed, with an organized
thrombus visible on ultrasound, but blood flow was
maintained.
The donor liver was retrieved from a 43 year old dead
brain donor (DBD) matching the recipient’s blood type
and similar weight and height values. The LTx began on
the 16th September, 2014 with the use of an extra-
corporeal veno-venous bypass. The portal vein and
hepatoduodenal ligament was difficult to dissect as it
was embodied in post-inflammatory scar tissue. The
suprahepatic IVC along with the surrounding diaphragm
was involved in the alveolar lesion. A 10 × 10 cm win-
dow of the diaphragm was excised creating an opening
of the right pleural cavity and pericardium (Fig. 2). Thus,
with the exposure of the pericardial part of the IVC, the
vascular clamp was placed on the atrium because the
whole IVC was infiltrated by the lesion. The infrahepatic
part of the IVC was clamped in a standard procedure.
Both ends of the IVC were then cut, and the liver was
explanted along with its intrahepatic IVC (Fig. 3a). The
clamping of the right atrium caused cardiac arrhythmia
and the electrocardiogram showed signs of myocardial
ischemia. This was managed by the anesthesiologist and
hemodynamic stability was achieved throughout the
operation.
Two 24 fr pleural drains were placed into the apex
and base of the right pleural space. The supra hepatic
IVC of the donor graft was sutured directly to the right
atrium using an end-to-end anastomosis. The excised
window in the diaphragm was minimized by suturing its
free ends together without the use of a Prolene patch,
and without complete closure of the diaphragm in order
to avoid stenosis of the IVC–atrium anastomosis. Com-
munication between the pericardium and right pleural
cavity was intentionally sustained to allow for fluid
drainage. After completion of the portal anastomosis
clamps from the IVC and portal vein were removed. A
Fig. 1 Pre-Transplant CT-scans presenting: a Computed Tomography of a 110 × 75 × 70 mm hepatic alveolar echinoccocal cyst located in
segments III–VIII; b Hepatic vein thrombosis – Budd-Chiari Syndrome
Kobryń et al. BMC Surgery  (2017) 17:5 Page 2 of 5
mild, 1-min reperfusion syndrome with a systolic pres-
sure of 60 mmHg was observed after 8 h 6 min of cold
ischemia. At that point, pleural drainage was enabled.
Further steps during transplantation were performed
in a standard procedure. Intraoperative blood loss was
estimated at 1000 ml; thus, 2 units of red blood con-
centrate and 4 units of fresh frozen plasma were
transfused. The anhepatic phase was 136 min. Total
operation time was 6.5 h.
An abdominal ultrasound was performed on the first
post-operative day (POD), showing good vascular flow.
An echocardiography performed on the second POD
found no abnormalities. The pleural drain was removed
on the third POD and a chest X-ray confirmed no signs
of pneumothorax or effusion in the right pleural space.
Time in the intensive transplant care unit was 3.5 days.
The immunosuppressive regimen consisted of tacroli-
mus 0.05 mg/kg × 2 and prednisolone 20 mg × 1. The
patient’s liver tests recovered gradually. Computed tom-
ography showed satisfactory and functioning hepato-
atrial anastomosis (Fig. 4a and b). She was discharged on
POD 25 and continued with tacrolimus 7 mg × 2, myco-
phenolate mofetil 500 mg × 2 and albendazole treatment
400 mg × once daily. Intolerance of the latter drug was
not observed during hospitalization. At an 18-month
follow-up and recurrence free period, the patient is
doing well with good overall outcome and graft
function.
Discussion
Hepatic alveolar echinococcosis (HAE) is a parasitic dis-
ease that develops slowly. Very often, the first symptoms
manifest, as in our case of E. multilocularis (Fig. 3b), at
a very advanced, mature stage. In the first imaging
examinations, HAE can resemble a tumor like hepato-
cellular carcinoma. Clinical signs, such as mechanical
jaundice, repetitive cholangitis, liver abscess, portal
hypertension, esophageal varices, and sepsis are second-
ary to the disease. Additionally, Budd-Chiari Syndrome
might be present [3–6].
Surgical resection usually is the main treatment for
this disease; however, because alveolar symptoms tend to
be absent for a long period of time, the cysts tend to be
very advanced at diagnosis. Large lesions without
response to drug treatment and with invasion of the vas-
cular tree (Fig. 3c) of the liver will eventually develop
BCS, thus should be directly qualified for LTx. This
seems to be the only final treatment for HAE, and 90%
of patients die within 10 years without surgery [4–7].
LTx due to HAE has been reported to have in-
creased morbidity and mortality. A thorough examin-
ation is compulsory with MRI and three-dimensional
computed tomography reconstruction in order to
minimize intraoperative risk [7]. An early remark on
the use of veno-venous bypass allows for better intra-
operative preparation and greatly minimizes the risk
of bowel congestion, shortens the hepatectomy time
and limits the need for excessive maneuvers with the dis-
eased liver, reducing the risk of tissue impairment and ex-
cessive bleeding [8–12]. A pericardial-peritoneum window
as a procedure has been reported many times, but is per-
formed due to malignant diseases or pericardial effusion
and not during LTx [8–10, 12–14].
Several authors state that a pericardial-peritoneum
window acts as a collection chamber for pericardial
fluid, which is later absorbed through the peritoneum
Fig. 2 Clamp applied to the right atrium and positioning of
the sutures
Fig. 3 a Explanted diseased liver; b Alveolar Cyst with E. multilocularis in the explanted liver; c Strictured lumen of the supra hepatic inferior vena
cava, which was invaded by an alveolar lesion (marked by needle). Dissected diaphragm measured 10 × 10 cm
Kobryń et al. BMC Surgery  (2017) 17:5 Page 3 of 5
[9, 10]. In our opinion, the implantation of the donor
liver through such a suprahepatic atrium-IVC cuff
end-to-end anastomosis allows both lobes of the liver
to firmly press against the diaphragm. This creates a
continuation of the thoracic-abdominal barrier, simul-
taneously avoiding future diaphragmatic hernia. Thus,
leaving a 20-40-mm opening around the IVC anasto-
mosis avoids its occlusion in the future, provides
prompt drainage of fluid, and leaves the diaphragm
under less tension. There has been several publica-
tions, mainly for initial BCS, presenting different solu-
tions of cavoplasty in order to perform an atrial-caval
anastomosis [15, 16]. Though principles are similar,
our report presents how to manage a rare case of
advanced HAE and in result secondary BCS.
Conclusions
LTx is feasible when performing an IVC hepato-atrial
anastomosis. Patient’s outcome is not impaired, and the
post-operative results, follow up, and quality of life is
good. Therefor even advanced cases of HAE may be suc-
cessfully treated with liver transplantation.
Abbreviations
BCS: Budd-Chiari Syndrome; CD: Celiac Disease; EV: Esophageal Varices;
GERD: Gastro-Esophageal Reflux Disease; HAE: Hepatic Alveolar
Echinococcosis; IVC: Inferior vena cava; LTx: Liver transplantation; PDPS:
Post-drug pancytopenia syndrome; PHG: Portal Hypertensive Gastropathy;
POD: Post-operative day
Acknowledgements
Not Applicable.
The authors have adhered to CARE guidelines/methodology.
Funding
There is no funding to be declared for the preparation of this manuscript.
The publication fee will be funded by the Medical University of Warsaw.
Availability of data and materials
The datasets generated and/or analysed during the current study are
available from the corresponding author on reasonable request.
Authors’ contributions
KK designed the report; KK, RP, KD, MKo performed the surgical
procedure; PM, JR-W, UO-J post-operatively treated the patient; KK
collected the patient’s clinical data; KK, RP, JR-W, PR, MG, PM, WP,
MKo analyzed the data; KK, RP, PM, MKr wrote and revised the paper.
All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
The authors did obtain written permission from the patient to publish the
manuscript and permission is extended to the publication of images in this
case report.
Ethics approval and consent to participate
The authors did attain the permission of the Medical University of Warsaw
Bioethics Committee (reference # AKBE157/16) to publish the data and
written, informed consent to participate was obtained from the patient.
Author details
1Department of General, Transplant and Liver Surgery, Medical University of
Warsaw, Poland. Banacha Street 1a, 02-097 Warsaw, Poland. 2Department of
Hepatology and Internal Diseases, Medical University of Warsaw, Warsaw,
Poland.
Received: 27 July 2016 Accepted: 6 January 2017
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Good outcome following liver transplantation using pericardial-peritoneum window for hepato-atrial anastomosis to overcome advanced hepatic alveolar echinococcosis and secondary Budd-Chiari Syndrome - a case report

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