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Pancreatic Cancer - Early Detection, Prognostic Factors, and Treatment

Ansari, Daniel LU (2014) In Lund University, Faculty of Medicine Doctoral Dissertation Series 103.
Abstract (Swedish)
Popular Abstract in Swedish

Pankreascancer, cancer i bukspottkörteln, är den fjärde vanligaste orsaken till död i

cancer och årligen insjuknar cirka 1000 patienter i Sverige. Överlevnaden är kort

med en 5-årsöverlevnad på endast 6 procent. Pankreascancer orsakar, förutom

lidande, också betydande kostnader för såväl den medicinska vården, som förluster

för samhället, exempelvis i form av förtida död.



Eftersom symtomen vid pankreascancer är vaga och ofta uppträder i ett sent skede

av sjukdomen finns det ett stort behov av att förbättra den tidiga diagnostiken.

Idag finns inga godkända diagnostiska biomarkörer för pankreascancer. Genom att

söka... (More)
Popular Abstract in Swedish

Pankreascancer, cancer i bukspottkörteln, är den fjärde vanligaste orsaken till död i

cancer och årligen insjuknar cirka 1000 patienter i Sverige. Överlevnaden är kort

med en 5-årsöverlevnad på endast 6 procent. Pankreascancer orsakar, förutom

lidande, också betydande kostnader för såväl den medicinska vården, som förluster

för samhället, exempelvis i form av förtida död.



Eftersom symtomen vid pankreascancer är vaga och ofta uppträder i ett sent skede

av sjukdomen finns det ett stort behov av att förbättra den tidiga diagnostiken.

Idag finns inga godkända diagnostiska biomarkörer för pankreascancer. Genom att

söka efter proteinsekvenser i blodprov med s.k. masspektrometri kan nya

biomarkörer för pankreascancer identifieras. Dessa markörer skulle kunna

användas inom sjukvården för att i ett tidigt skede upptäcka om en patient bär på

en tumör i pankreas innan den har spridit sig till andra organ. Då ökar möjligheten

att bota patienten med operation.



Det är väsentligt med en korrekt bedömning av prognosen för varje patient för att

styra val av behandling. Det finns flera prognostiska modeller beskrivna i

litteraturen, men det saknas fortfarande ett etablerat prognostiskt system.

Nuvarande stadieindelning, s.k. TNM-klassifikationen tar inte hänsyn till faktorer

utöver T-stadium (primärtumörens storlek och utbredning), N-stadium (spridning

till regionala lymfkörtlar) och M-stadium (förekomst av fjärrmetastaser). För

patienter som genomgår kirurgi är TNM-indelningen inte tillräckligt pålitlig för att

förutsäga den enskilde patientens prognos efter operation. En modell för

prediktering av överlevnad kan baseras på s.k. artificiella neurala nätverk, en

avancerad datoriserad optimeringsmodell som kan analysera icke-linjära samband.



Pankreascancer är svårbehandlad och det finns därmed en stor potential för

terapiförbättringar. Kirurgin (Whipples operation) har successivt förfinats och

dödsfall i samband med operation har minskat och är idag några enstaka procent.

Det är visat att centralisering av pankreaskirurgi till högvolymscentra har haft en

viktig roll i detta. Cytostatika (cellgifter) kan ges som efterbehandling efter

kirurgi eller som behandling när tumören växer så att den inte kan opereras.

Tyvärr är resistens mot cytostatika ett vanligt problem och fortsatta förbättringar

av resultaten kräver ökad förståelse av tumörbiologin och ny typ av

individanpassad behandling. MUC4 är ett cellyteprotein som ofta finns i vävnad

från patienter med pankreascancer men som saknas i normal pankreas. Detta

protein har i tidigare experimentella studier kunnat kopplas till cytostatikaresistens.

Terapi riktad mot MUC4 kan därför utgöra en framtida

behandlingsstrategi mot pankreascancer.



I delarbete I studerades värdet av masspektrometri för att påvisa proteinmarkörer i

serum tidigt i förloppet vid pankreascancer. Vid en jämförelse mellan operabel

pankreascancer, godartade pankreassjukdomar och friska individer, identifierades

134 serumproteiner som kunde särskilja grupperna från varandra, varav 40

proteiner var uppreglerade vid pankreascancer. Flera av dessa proteiner kunde via

interaktionsanalyser kopplas till p53, ett protein som har en central roll vid

uppkomst av pankreascancer. Resultaten från denna studie är ett viktigt steg i

utvecklingen av ett enkelt blodbaserat diagnostiskt test för pankreascancer.



I delarbete II utvecklades en algoritm för prognostisering av pankreascancer med

hjälp av artificiella neurala nätverk. Riskfaktorer tillgängliga i daglig klinisk praxis

och som bidrar till sämre prognos vid pankreascancer identifierades och

rangordnades. En modell togs fram som hade bättre prediktionsförmåga än

traditionell statistik analys.



I delarbete III kartlades alla patienter som genomgått Whipples operation i Lund

under perioden 2000-2012. Totalt 221 patienter inkluderades. Resultaten visade att

sedan övergången till högvolymskirurgi (definierat som 25 eller fler operationer

per år) har de operativa resultaten förbättrats vad gäller blodförlust vid operation,

operationstid, blödningskomplikationer, risk för reoperation och vårdtid. Operativ

mortalitet minskade från 4 till 0 procent.



I delarbete IV studerades uttrycket av MUC4 i vävnad från primär pankreascancer

och matchade lymfkörtelmetastaser. Resultaten visade att majoriteten av

primärtumörerna uttryckte MUC4 och att detta uttryck bibehölls i metastaserna,

vilket talar för att MUC4 är ett potentiellt behandlingsmål även vid metastaserande

sjukdom.



I delarbete V utfördes experimentella djurstudier genom transplantation av

pankreastumörcellinjer i immundefekta möss i syfte att arbeta vidare med

MUC4-proteinet. Tumörer från en av cellinjerna (Capan-1) uttryckte mest MUC4 och

bedömdes därför bäst lämpad för fortsatta studier.



I delarbete VI undersöktes den tillväxthämmande effekten av olika s.k.

epigenetiska läkemedel på pankreascancerceller. Apicidin, en s.k. HDAC-hämmare

visade sig mest effektivt och potentierade även effekten av det vanliga

pankreascancermedlet gemcitabin genom att nedreglera MUC4 i cancercellinjen

Capan-1. (Less)
Abstract
Background: Pancreatic cancer is the fourth leading cause of cancer-related death.

Only about 6% of patients are alive 5 years after diagnosis. One reason for this

low survival rate is that most patients are diagnosed at a late stage, when the tumor

has spread to surrounding tissues or distant organs. Less than 20% of cases are

diagnosed at an early stage that allows them to undergo potentially curative

surgery. However, even for patients with a tumor that has been surgically

removed, local and systemic recurrence is common and the median survival is

only 17-23 months. This underscores the importance to identify factors that can

predict postresection survival. With... (More)
Background: Pancreatic cancer is the fourth leading cause of cancer-related death.

Only about 6% of patients are alive 5 years after diagnosis. One reason for this

low survival rate is that most patients are diagnosed at a late stage, when the tumor

has spread to surrounding tissues or distant organs. Less than 20% of cases are

diagnosed at an early stage that allows them to undergo potentially curative

surgery. However, even for patients with a tumor that has been surgically

removed, local and systemic recurrence is common and the median survival is

only 17-23 months. This underscores the importance to identify factors that can

predict postresection survival. With technical advances and centralization of care,

pancreatic surgery has become a safe procedure. The future optimal treatment for

pancreatic cancer is dependent on increased understanding of tumor biology and

development of individualized and systemic treatment. Previous experimental

studies have reported that mucins, especially the MUC4 mucin, may confer

resistance to the chemotherapeutic agent gemcitabine and may serve as targets for

the development of novel types of intervention.



Aim: The aim of the thesis was to investigate strategies to improve management of

pancreatic cancer, with special reference to early detection, prognostic factors, and

treatment.



Methods: In paper I, 27 prospectively collected serum samples from resectable

pancreatic cancer (n=9), benign pancreatic disease (n=9), and healthy controls

(n=9) were analyzed by high definition mass spectrometry (HDMSE). In paper II,

an artificial neural network (ANN) model was constructed on 84 pancreatic cancer

patients undergoing surgical resection. In paper III, we investigated the effects of

transition from a low- to a high volume-center for pancreaticoduodenectomy in

221 patients. In paper IV, the grade of concordance in terms of MUC4 expression

was examined in 17 tissue sections from primary pancreatic cancer and matched

lymph node metastases. In paper V, pancreatic xenograft tumors were generated in

15 immunodeficient mice by subcutaneous injection of MUC4+ human pancreatic

cancer cell lines; Capan-1, HPAF-II, or CD18/HPAF. In paper VI, a 76-member

combined epigenetics and phosphatase small-molecule inhibitor library was

screened against Capan-1 (MUC4+) and Panc-1 (MUC4-) cells, followed by high

content screening of protein expression.



Results/Conclusion: 134 differentially expressed serum proteins were identified,

of which 40 proteins showed a significant up-regulation in the pancreatic cancer

group. Pancreatic disease link associations could be made for BAZ2A, CDK13,

DAPK1, DST, EXOSC3, INHBE, KAT2B, KIF20B, SMC1B, and SPAG5, by

pathway network linkages to p53, the most frequently altered tumor suppressor in

pancreatic cancer (I). An ANN survival model was developed, identifying 7 risk

factors. The C-index for the model was 0.79, and it performed significantly better

than the Cox regression (II). We experienced improved surgical results for

pancreaticoduodenectomy after the transition to a high-volume center (≥25

procedures/year), including decreased operative duration, blood loss, hemorrhagic

complications, reoperations, and hospital stay. There was also a tendency toward

reduced operative mortality, from 4% to 0% (III). MUC4 positivity was detected

in most primary pancreatic cancer tissues, as well as in matched metastatic lymph

nodes (15/17 vs. 14/17), with a high concordance level (82%) (IV). The tumor

incidence was 100% in the xenograft model. The median MUC4 count was found

to be highest in Capan-1 tumors. α-SMA and collagen extent were also highest in

Capan-1 tumors (V). Apicidin (a histone deacetylase inhibitor) had potent

antiproliferative activity against Capan-1 cells and significantly reduced the

expression of MUC4 and its transcription factor HNF4α. The combined treatment

of apicidin and gemcitabine synergistically inhibited growth of Capan-1 cells (VI). (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Friess, Helmut, Department of General Surgery, The University Hospital Rechts der Isar, Technical University Munich, Munich, Germany
organization
publishing date
type
Thesis
publication status
published
subject
keywords
artificial neural networks, apicidin, centralization, early detection, epigenetics, high definition mass spectrometry, MUC4, pancreatic cancer, pancreaticoduodenectomy, prognostic factors, xenograft model, treatment
in
Lund University, Faculty of Medicine Doctoral Dissertation Series
volume
103
pages
180 pages
publisher
Surgery (Lund)
defense location
Lecture Room 4, Main building, Skåne University Hospital, Lund
defense date
2014-09-26 13:00
ISSN
1652-8220
ISBN
978-91-7619-023-6
language
English
LU publication?
yes
id
8ba1eb21-adda-45a0-8932-64df1568c859 (old id 4643641)
date added to LUP
2014-09-09 14:08:09
date last changed
2016-09-19 08:44:48
@phdthesis{8ba1eb21-adda-45a0-8932-64df1568c859,
  abstract     = {Background: Pancreatic cancer is the fourth leading cause of cancer-related death.<br/><br>
Only about 6% of patients are alive 5 years after diagnosis. One reason for this<br/><br>
low survival rate is that most patients are diagnosed at a late stage, when the tumor<br/><br>
has spread to surrounding tissues or distant organs. Less than 20% of cases are<br/><br>
diagnosed at an early stage that allows them to undergo potentially curative<br/><br>
surgery. However, even for patients with a tumor that has been surgically<br/><br>
removed, local and systemic recurrence is common and the median survival is<br/><br>
only 17-23 months. This underscores the importance to identify factors that can<br/><br>
predict postresection survival. With technical advances and centralization of care,<br/><br>
pancreatic surgery has become a safe procedure. The future optimal treatment for<br/><br>
pancreatic cancer is dependent on increased understanding of tumor biology and<br/><br>
development of individualized and systemic treatment. Previous experimental<br/><br>
studies have reported that mucins, especially the MUC4 mucin, may confer<br/><br>
resistance to the chemotherapeutic agent gemcitabine and may serve as targets for<br/><br>
the development of novel types of intervention.<br/><br>
<br/><br>
Aim: The aim of the thesis was to investigate strategies to improve management of<br/><br>
pancreatic cancer, with special reference to early detection, prognostic factors, and<br/><br>
treatment.<br/><br>
<br/><br>
Methods: In paper I, 27 prospectively collected serum samples from resectable<br/><br>
pancreatic cancer (n=9), benign pancreatic disease (n=9), and healthy controls<br/><br>
(n=9) were analyzed by high definition mass spectrometry (HDMSE). In paper II,<br/><br>
an artificial neural network (ANN) model was constructed on 84 pancreatic cancer<br/><br>
patients undergoing surgical resection. In paper III, we investigated the effects of<br/><br>
transition from a low- to a high volume-center for pancreaticoduodenectomy in<br/><br>
221 patients. In paper IV, the grade of concordance in terms of MUC4 expression<br/><br>
was examined in 17 tissue sections from primary pancreatic cancer and matched<br/><br>
lymph node metastases. In paper V, pancreatic xenograft tumors were generated in<br/><br>
15 immunodeficient mice by subcutaneous injection of MUC4+ human pancreatic<br/><br>
cancer cell lines; Capan-1, HPAF-II, or CD18/HPAF. In paper VI, a 76-member<br/><br>
combined epigenetics and phosphatase small-molecule inhibitor library was<br/><br>
screened against Capan-1 (MUC4+) and Panc-1 (MUC4-) cells, followed by high<br/><br>
content screening of protein expression.<br/><br>
<br/><br>
Results/Conclusion: 134 differentially expressed serum proteins were identified,<br/><br>
of which 40 proteins showed a significant up-regulation in the pancreatic cancer<br/><br>
group. Pancreatic disease link associations could be made for BAZ2A, CDK13,<br/><br>
DAPK1, DST, EXOSC3, INHBE, KAT2B, KIF20B, SMC1B, and SPAG5, by<br/><br>
pathway network linkages to p53, the most frequently altered tumor suppressor in<br/><br>
pancreatic cancer (I). An ANN survival model was developed, identifying 7 risk<br/><br>
factors. The C-index for the model was 0.79, and it performed significantly better<br/><br>
than the Cox regression (II). We experienced improved surgical results for<br/><br>
pancreaticoduodenectomy after the transition to a high-volume center (≥25<br/><br>
procedures/year), including decreased operative duration, blood loss, hemorrhagic<br/><br>
complications, reoperations, and hospital stay. There was also a tendency toward<br/><br>
reduced operative mortality, from 4% to 0% (III). MUC4 positivity was detected<br/><br>
in most primary pancreatic cancer tissues, as well as in matched metastatic lymph<br/><br>
nodes (15/17 vs. 14/17), with a high concordance level (82%) (IV). The tumor<br/><br>
incidence was 100% in the xenograft model. The median MUC4 count was found<br/><br>
to be highest in Capan-1 tumors. α-SMA and collagen extent were also highest in<br/><br>
Capan-1 tumors (V). Apicidin (a histone deacetylase inhibitor) had potent<br/><br>
antiproliferative activity against Capan-1 cells and significantly reduced the<br/><br>
expression of MUC4 and its transcription factor HNF4α. The combined treatment<br/><br>
of apicidin and gemcitabine synergistically inhibited growth of Capan-1 cells (VI).},
  author       = {Ansari, Daniel},
  isbn         = {978-91-7619-023-6},
  issn         = {1652-8220},
  keyword      = {artificial neural networks,apicidin,centralization,early detection,epigenetics,high definition mass spectrometry,MUC4,pancreatic cancer,pancreaticoduodenectomy,prognostic factors,xenograft model,treatment},
  language     = {eng},
  pages        = {180},
  publisher    = {Surgery (Lund)},
  school       = {Lund University},
  series       = {Lund University, Faculty of Medicine Doctoral Dissertation Series},
  title        = {Pancreatic Cancer - Early Detection, Prognostic Factors, and Treatment},
  volume       = {103},
  year         = {2014},
}