Dicembre 2014 - Società Italiana di Citometria

Transcript

Poste Italiane S.p.A. - Sped. in Abb. Postale - D.L. 353/2003 (Conv. in L. 27/02/2004 n. 46) art. 1 com. 1 - DCB - Roma ISSN 2280-8663 - Contiene I.A.
Vol. 23, Num. 3
Dicembre 2014
Periodico della Società Italiana di Citometria
Flow cytometric analysis of circulating endothelial cells and
endothelial progenitors for clinical purposes in oncology:
urgent need for methodological standardization
Tumori solidi pediatrici: allestimento e caratterizzazione di
linee tumorali primarie per un progetto di applicazione clinica
del trapianto aploidentico di cellule staminali ematopoietiche
XXXIII CONFERENZA NAZIONALE
DI CITOMETRIA
AGGIORNAMENTI E INNOVAZIONI
DELLA CITOMETRIA
IN APPLICAZIONI CLINICHE E DI RICERCA
Palazzo Ducale - Lucca, 22 - 25 settembre 2015
Vol. 23, Num. 3
DIRETTORE RESPONSABILE
Raffaele De Vita
COMITATO EDITORIALE
Marco Danova
Dipartimento di Medicina
A.O. di Pavia
S.C. di Medicina Interna e Oncologia Medica
Ospedale Civile di Vigevano
Raffaele De Vita
Unità Biologia delle Radiazioni e Salute dell’Uomo
ENEA - Centro Ricerche Casaccia
Roma
Eugenio Erba
Istituto Ricerche Farmacologiche “Mario Negri”
Milano
Giuseppe Starace
Istituto Medicina Sperimentale CNR
Roma
Volume 23, numero 3 - Dicembre 2014
Lettere GIC
Autorizz. del trib. di Roma n° 512/92 del 17/9/92
Edizione quadrimestrale
Spedizione in abbonamento postale
Peer Review Journal
ISSN 2280-8663
Grafica: Renato Cafieri
Stampa:
Redazione:
Società
Italiana di
Citometria
SOMMARIO
Dicembre 2014
Premio di Studio “Francesco Mauro”
2
XXXIII Conferenza Nazionale di Citometria
6
Elenco/Albo Citometristi GIC Esperti
… a che punto siamo?
8
Flow cytometric analysis of circulating endothelial
cells and endothelial progenitors for clinical
purposes in oncology:
9
LA CITOMETRIA E LE SUE APPLICAZIONI
NELLA RICERCA DI BASE E NELLA CLINICA
AGGIORNAMENTI E INNOVAZIONI DELLA CITOMETRIA
IN APPLICAZIONI CLINICHE E DI RICERCA
Palazzo Ducale - Lucca, 22 - 25 settembre 2015
Sessione di esami 2015 scritto e orale
Lucca 22-25 settembre
Marco Danova, Mariangela Manzoni, Giuditta Comolli, Martina Torchio,
Giuliano Mazzini
Tumori solidi pediatrici: allestimento e caratterizzazione
di linee tumorali primarie per un progetto di
applicazione clinica del trapianto aploidentico di cellule
staminali ematopoietiche
25
Comini Marta, Bolda Federica, Beghin Alessandra, D'Ippolito Carmelita,
Ruggeri Loredana, Alberti Daniele, Bercich Luisa, Carella Graziella,
Porta Fulvio, Caruso Arnaldo, Lanfranchi Arnalda
c/o Unità Biologia delle Radiazioni e
Salute dell’Uomo
ENEA Centro Ricerche Casaccia, s.p. 016
Via Anguillarese, 301 - 00123 ROMA
06/30484671 Fax 06/30484891
e-mail: [email protected]
http://gic.casaccia.enea.it
Associato alla
Unione Stampa
Periodica Italiana
In copertina: Lucca, sede della XXXIII Conferenza
Nazionale di Citometria “Aggiornamenti e innovazioni
della Citometria in applicazioni cliniche e di ricerca”,
Palazzo Ducale, dal 22 al 25 settembre 2015, piazza
Anfiteatro vista dall’alto.
Lettere GIC Vol. 23, Num. 3 - Dicembre 2014
SOMMARIO
5
Società
Italiana di
Citometria
XXXIII
CONFERENZA NAZIONALE
DI CITOMETRIA
AGGIORNAMENTI E INNOVAZIONI
DELLA CITOMETRIA IN APPLICAZIONI
CLINICHE E DI RICERCA
N
N
N
N
N
N
N
N
N
N
N
N
N
Palazzo Ducale
Lucca, 22 - 25 settembre 2015
Con il Patrocinio ed il supporto
della Provincia di Lucca
Cellule staminali e terapie cellulari
Ciclo cellulare e apoptosi
Citogenetica molecolare
Ematologia clinica e sperimentale
Immunologia clinica e sperimentale
Medicina trasfusionale
Microbiologia clinica e sperimentale
Microscopia
Nuove tecnologie e metodologie citometriche
Oncologia clinica e sperimentale
Qualifiche e certificazioni in citometria
Scienze ambientali e biotecnologie
Tossicologia e Radioterapia
SCUOLA NAZIONALE DI CITOMETRIA
Corsi di aggiornamento
La formazione continua del Citometrista
22 settembre 2015
N Elementi base di Citometria in Ematologia
Coordinatori: A. Aiello, A. Kunkl
N Elementi base di Citometria in Immunologia
Coordinatori: A. Fattorossi, L. Zamai
Comitato Organizzatore
R. De Vita (Roma)
E. Erba (Milano)
G. Mazzini (Pavia)
G. Pirozzi (Napoli)
Comitato Scientifico
A. Aiello (Milano)
R. Chianese (Ivrea)
I. D’Agnano (Roma)
M. Danova (Pavia)
R. De Palma (Napoli)
L. Del Vecchio (Napoli)
M.G. Della Porta (Pavia)
A. Fattorossi (Roma)
D. Fenoglio (Genova)
G. Gaipa (Monza)
A. Kunkl (Genova)
F. Lanza (Cremona)
S. Lucretti (Roma)
A. Manti (Urbino)
O. Nappi (Napoli)
M. Rocchi (Bari)
M. Spanò (Roma)
V. Tirino (Napoli)
C. Usai (Genova)
A. Venditti (Roma)
L. Zamai (Urbino)
N Elementi base di Citometria in Ricerca
Coordinatori: R. Casotti, G. Pirozzi
con il Patrocinio di
Presidenza del Consiglio dei Ministri
Agenzia nazionale per le nuove tecnologie,
l’energia e lo sviluppo economico sostenibile
Consiglio Nazionale delle Ricerche
Istituto di Ricerche Farmacologiche Mario Negri”
Istituto Nazionale Tumori “Fondazione G. Pascale”
Stazione Zoologica “Anton Dohrn”
Provincia di Lucca
6
Comune di Lucca
XXXIII CONFERENZA NAZIONALE DI CITOMETRIA
Segreteria Scientifica
Società Italiana di Citometria
c/o Unità Biologia delle Radiazioni
e Salute dell'Uomo
ENEA Centro Ricerche Casaccia s.p. 016
Via Anguillarese, 301 - 00123 Roma
tel. 06 30484671 - fax 06 30484891
e-mail: [email protected] - http://gic.casaccia.enea.it
Segreteria Organizzativa
Italymeeting s.r.l.
Via Parsano, 6/b - 80067 Sorrento NA
tel. 081 8073525 – 081 8784606 - fax 081 8071930
http://www.italymeeting.it
QUOTE DI ISCRIZIONE
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I contributi scientifici saranno presentati sotto forma
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nel sito Web di CYTOMETRY B.
Saranno assegnati 4 “Premi Poster GIC” in
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Nell’ambito della Conferenza è prevista l’annuale
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ACCREDITAMENTO E.C.M.
per Corsi e Conferenza:
Biologo, Medico, Chimico, Farmacista,
Tecnico S.L.B. e Veterinario
ELENCO/ALBO DEI CITOMETRISTI ESPERTI
SESSIONE DI ESAMI 2015
Il GIC ha istituito un Albo per la figura professionale di Citometrista, suddiviso per specifici settori disciplinari.
Si svolgerà una sessione di esami, martedì 22,
riservato a Colleghi con una specifica e documentata esperienza professionale. Questa
andrà dettagliata nella apposita scheda CV da
allegare alla domanda d'iscrizione all'esame
insieme al versamento di una quota associativa
straordinaria di € 25,00. Coloro che supereranno l'esame scritto potranno sostenere l'esame
orale, il giorno seguente, nella stessa sede.
L'esame si svolgerà solo se perverranno almeno 5 iscrizioni.
CALENDARIO
martedì 22 settembre
08.30-12.30 Corsi di Aggiornamento
13.00
Esame scritto Elenco/Albo
14.00
Registrazione e allestimento
dei poster
15.00
Seminari introduttivi:
“Immunoematologia e
Metodologie Analitiche”
17.30
Apertura Conferenza
“Lettura Magistrale”
mercoledì 23 settembre
08.30-13.00 Sessione Plenaria
14.00
Sessioni Parallele
17.00-18.00 Sessione Poster
giovedì 24 settembre
08.30
Sessione Plenaria
11.00-13.00 Sessioni Parallele
14.00
Sessioni Parallele
16.30
Sessione Poster
17.00
Assemblea dei Soci
venerdì 25 settembre
08.30
Sessioni Parallele
11.00-13.00 Sessione Plenaria
PROGRAMMA SOCIALE
PRELIMINARE
martedì 22 settembre
14.00 Registrazione con Caffè
19.00 Brindisi di Benvenuto
giovedì 24 settembre
18.30 Degustazione “Sapere i Sapori … a Km 0”
venerdì 25 settembree
12.45 Sorteggio Premi scheda valutazione evento
13.00 Colazione Speciale di saluto*
15.00 Visita culturale*
*è indispensabile la prenotazione alla
Segreteria GIC con un messaggio e-mail:
[email protected] entro il 1 settembre 2015
31 maggio
RIEPILOGO SCADENZE
15 giugno
scheda iscrizione per quota ridotta
scheda iscrizione e abstract
per comunicazioni orali e poster
30 giugno
scheda e CV per Esame scritto
Elenco/Albo dei Citometristi
15 luglio
prenotazione alberghiera
1 settembre
prenotazione per le visite culturali
Ulteriori informazioni ed aggiornamenti e le schede per l’iscrizione, consultare il sito GIC:
http://gic.casaccia.enea.it
XXXIII CONFERENZA NAZIONALE DI CITOMETRIA
7
Elenco/Albo Citometristi GIC Esperti … a che punto siamo?
Sessione di esami 2015
scritto e orale
Lucca 22-25 settembre
8
Lo avevamo annunciato ufficialmente a Lucca 2013 (“Qualifica di Citometrista” su Lettere GIC Vol. 22 Num.
1 Aprile 2013) e abbiamo quasi terminato il “Primo ciclo” di esami di ammissione, con il Secondo che ripartirà nuovamente da Lucca fra pochi mesi, 22-25 settembre p.v. con la nuova sessione di esami scritto e orale
che svolgeremo, questa volta, negli stessi giorni.
Ricordiamo (per i neo-soci) che il GIC si è fatto promotore di un percorso che intende riconoscere, a beneficio esclusivo dei propri iscritti, e su base volontaria, la figura professionale di “Citometrista Esperto” istituendo uno specifico Elenco, con le peculiarità di Albo; quindi, si è posto l’obiettivo di riconoscere l’eccellenza professionale del citometrista, la qualità delle analisi e delle applicazioni citometriche in Italia. Il GIC con questa
iniziativa si pone anche l’obiettivo di promuovere la formazione e l’aggiornamento continuo dei Ricercatori e
degli Operatori professionali di questa disciplina. In pratica è un invito, nell’ambito delle proprie aree di competenza, ad attuare con correttezza e competenza la gestione degli specifici processi analitici in tutti i loro
aspetti dalla preparazione del campione, alla misura, alla interpretazione dei risultati e alla loro refertazione.
L’Elenco/Albo, sarà caratterizzato da una struttura organizzativa nella quale saranno riconosciute figure con
profili professionali, con diversi livelli e differenti aree applicative specialistiche. In pratica sarà articolato in due
livelli professionali: Citometrista Esperto “Livello Base” Citometrista Esperto “Livello Avanzato”, entrambi articolati in specifiche aree di competenza ovvero nei quattro principali campi applicativi della citometria: ematologia, immunologia, ricerca e ambiente/microbiologia.
Tornando al “percorso”, in realtà il “Primo ciclo” ha avuto inizio con la seduta di esami scritti ad Urbino, lo scorso settembre, e con le sessioni di esami orali di Napoli (svolta in febbraio) e di Milano e Roma (in marzo):
avremo così i primi idonei ad essere iscritti all’Elenco/Albo. Sebbene per una valutazione globale bisognerà
attendere la conclusione dei lavori delle Commissioni, possiamo tentare una prima valutazione preliminare di
come sta andando questa iniziativa GIC (che si è rivelata molto impegnativa dal punto di vista organizzativo)
che ha visto un notevole interesse da parte dei Soci. I più giovani sono stati ovviamente i primi a volersi cimentare con un percorso di qualificazione, anche perché sono quelli che più sentono l’esigenza di un “riconoscimento” che attesti le loro capacità professionali, in un contesto di “precarietà” del mondo del lavoro, mai così
grave come quello che stiamo vivendo.
Ci preme dire subito che sembra stia andando abbastanza bene……e lo possiamo affermare sulla base dei
risultati dello scritto di Urbino. Abbiamo avuto circa 50 iscritti suddivisi nelle diverse aree e possiamo dire che
i risultati degli esami sono stati soddisfacenti con una discreta preparazione nel loro campo di attività professionale. Va però sottolineato che entrando nel merito dei quesiti inclusi nello scritto ed a quelli più frequentemente errati è emersa una carenza di fondo che se volessimo fare un paragone con l’esame per la patente
di guida potremmo affermare che i citometristi italiani guidano bene e magari conoscono anche il codice della
strada, ma pochi sanno a cosa serve il carburatore…….e come la “Motorizzazione” è inflessibile con il numero di “quiz” anche noi abbiamo cercato di esserlo! Si potrebbe infatti discutere che una buona analisi citometrica non richiede che l’operatore conosca l’ottica o i principi di base della fluorescenza, ma noi riteniamo che
un “esperto” debba avere un bagaglio culturale che includa anche queste conoscenze di base. È dunque
emerso (ma i primi segnali erano già stati evidenziati nei colloqui di idoneità) che molti giovani (ma non
solo….) sono arrivati alla citometria partendo dalle applicazioni anziché dalle basi metodologiche/strumentali;
e questo è ancor più evidente in ambito clinico (ematologia e immunologia) dove più routinarie sono appunto le applicazioni e minori le possibilità formative di tipo tecno/metodologico. E dunque come GIC ci sentiamo
se non responsabili certamente sensibili a queste carenze di base e sarà nostro dovere ed impegno cercare
di colmarle con adeguate iniziative formative. In realtà lo abbiamo sempre fatto in passato e potremmo dire
che la “formazione citometrica” è parte del DNA del GIC, che infatti è nato agli albori della Citometria in Italia,
proprio per divulgarne le applicazioni, ma sulla base di concrete conoscenze citometriche anche strumentali.
Cogliamo quindi l’occasione proprio a Lucca di tornare sui nostri passi per rilanciare una iniziativa formativa
ovvero i Corsi pre-Congressuali che in passato hanno fatto parte di una nostra tradizione radicata. Vorremmo
poter soddisfare le esigenze di tutti (nel senso delle varie aree applicative) e dunque ne programmiamo tre,
sui tre indirizzi immunologia, ematologia e ricerca (eventuali richieste di aggiornamento in ambito ambientale
verranno accorpate al Corso “ricerca”) in cui abbiamo anche strutturato il programma di “Qualifica”; da quanto abbiamo riferito più sopra ci sembra che le lacune principali siano “di base” e su questa formazione di base
vorremmo puntare, ma per rendere questo lavoro “più mirato” vorremmo il consenso di chi vi parteciperà. A
questo scopo troverete nella “Domanda di iscrizione” una apposita opzione di preferenza (base o avanzato)
che ci aiuterà a definire l’impostazione finale dei Corsi in modo che i docenti designati sappiano quali sono le
aspettative degli allievi con cui dovranno interagire.
ATTIVITÀ SCIENTIFICA
Flow cytometric analysis of circulating endothelial cells and
endothelial progenitors for clinical purposes in oncology:
Marco Danova1, Mariangela Manzoni2, Giuditta Comolli3, Martina Torchio1, Giuliano Mazzini4
S.C. Medicina Interna ed Oncologia Medica, Ospedale Civile di Vigevano, A.O. Di Pavia, Vigevano (Pavia), Italy.
2S.C. Oncologia Medica, Ospedale Maggiore di Crema, Crema (Cremona), Italy.
3S.C. Microbiologia e Virologia, Laboratori Biotecnologie,IRCCS Fondazione “S. Matteo”, Pavia, Italy.
4Istituto di Genetica Molecolare, Consiglio Nazionale delle Ricerche, IGM-CNR, Pavia, Italy.
1
e-mail: [email protected] - [email protected]
Abstract
The possibility to quantify circulating endothelial cells
(CECs) and endothelial progenitor cells (EPCs) represent a promising tool for monitoring the clinical outcome
of tumors with the potential to assess the response to various treatments. The number of CECs and EPCs is very
low and they cannot be identified using a single marker
and often need to be discriminated by using a combination of antigens with different cell surface expression.
Flow cytometric detection of CECs and EPCs in whole
blood is the most commonly utilized method in clinical
studies, but remains a technically challenging in that no
standardized protocol for reproducible enumeration of
these cells is available. In this review, we cover the
most commonly utilized protocols to define CECs and
EPCs by flow cytometry (FCM) in different oncological
settings. For this purpose we have carefully evaluated
the most significant clinical studies, published from
2008 to 2013 that utilized FCM for CEC and/or EPC
detection in cancer patients.
The multitude of flow cytometric methodologies applied,
together with the heterogeneity of the patients enrolled in
the different trials, greatly limits comparability of results.
A lack of both a consensus on CEC and EPC phenotype
and of an inter-laboratory standardized FCM assay has
resulted in a great heterogeneity in the reported blood levels of CECs and EPCs. Consequently, inter-laboratory
variability limits the interpretation of CEC/EPC potential
to predict survival and / or response to therapy. Moreover,
reproducibility in their quantification/characterization will
only be achieved with careful inter-laboratory standardization of methodologies utilized.
Riassunto
La possibilità di quantificare le cellule endoteliali circolanti (CECs) e i progenitori endoteliali circolanti (EPCs)
rappresenta uno strumento promettente per monitorare
l’outcome clinico dei tumori e per valutare la loro risposta a vari trattamenti. Il numero di CECs e di EPCs è
molto basso e non sono identificabili con un solo marcatore ma solo mediante una combinazione di antigeni
diversamente espressi sulla superficie delle cellule. La
valutazione delle CECs e delle EPCs nel sangue periferico mediante la citometria a flusso (FCM) rappresenta la
metodica più comunemente utilizzata negli studi clinici,
pur rimanendo una sfida dal punto di vista tecnico, non
esistendo ad oggi un protocollo standardizzato e riproducibile per la conta di queste cellule. In questo articolo,
abbiamo considerato i protocolli citofluorimetrici per la
definizione di CECs e EPCs più comunemente impiegati in diversi tipi di neoplasie solide ed in diversi setting
di malattia, valutando gli studi più significativi tra quelli
pubblicati tra il 2008 ed il 2013.
Il numero di differenti metodologie basate sulla FCM,
insieme all’eterogeneità dei pazienti arruolati negli studi
clinici, limita in modo significativo la comparabilità dei
risultati. La mancanza di un consenso sulla definizione
del fenotipo di CECs ed EPCs e su un’unica procedura
analitica sufficientemente standardizzata si traduce
prima di tutto in una grande variabilità dei livelli di
CECs ed EPCs basali riportati negli studi. La grande
variabilità interlaboratorio limita fortemente l’interpretazione di un potenziale valore delle CECs e delle
EPCs nel predire la sopravvivenza e/o la risposta alla
terapia. Una futura utilizzazione in ambito clinico di questi biomarkers potrà quindi essere raggiunta solo
mediante programmi di standardizzazione delle metodologie utilizzate tra i differenti laboratori.
Key words: biomarkers, circulating endothelial cells,
endothelial progenitor cells, flow cytometry, solid
tumors.
Introduction
Circulating endothelial cells (CECs) and endothelial progenitor cells (EPCs) have been indicated as potential surrogate biomarkers of angiogenesis in cancer and other
diseases (1-3). Recent studies have demonstrated that
the number of these cells the peripheral blood (PB) of
cancer patients (pts) is altered by disease status and treatments, such as chemotherapy (CT) and anti-angiogenetic therapies. However, CECs and particularly EPCs represent a small and heterogeneous cell population in
human blood and this makes a standardized and reproATTIVITÀ SCIENTIFICA
9
ducible approach for their monitoring technically challenging (4). In addition, despite extensive research, there
is still debate about EPC defining markers. The focus of
most studies in humans has been on the expression of
stem cell markers such as cluster differentiation (CD) 34
or CD133 and endothelial antigens (Ags) such as CD31
or the kinase-insert domain (KDR), or type 2 vascular
endothelial growth factor receptor (VEGFR-2). Flow
cytometry (FCM) is the most widely utilized method for
rare event analysis such as CEC and EPC quantification
since it has the advantage of simultaneous determination
of stem and endothelial markers in a multiparametric
approach and is at the same time, a quantitative method
(5,6). With expanding interest in the field of clinical
applications for CEC and EPC quantification, the development of standardized protocols for analysis is mandatory. To date, a large variety of flow cytometric methods
to detect CECs and EPCs in pts with solid tumors have
10
been utilized, based on different combinations of surface
markers, sample-handling and staining protocols, gating
strategies and data analysis programs (6). We conducted
an extensive review of the scientific literature, in particular a Medline search using the the terms: CECs, EPCs,
FCM, biomarkers and clinical oncology. Here we report
the more important methodological findings reported in
the literature which have contributed to the different
results observed across various studies.
Flow cytometry protocols for the study of CEC and
EPC quantification in Clinical Oncology
Considering the methodologies described from 2008 to
2013 in various tumor types, the published papers were
analysed for the flow cytometric approach and the baseline values for CECs and EPCs reported (Table 1) as well
as for the panel of endothelial markers utilized (Table 2),
with the aim of emphasizing the pre-analytical and analyt-
Table 1: Methodological differences and results among different FCM-based studies of CECs and EPCs in solid tumors (FCM= flow
cytometry; CECs=circulating endothelial cells; EPCs= endothelial progenitor cells; PB= peripheral blood; pts= patients; WBC= white
blood cell; nr= number; n.a.= not assessed; ml= milliliter; µl= microliter; MNCs= mononuclear cells; PBMNCs= peripheral blood
mononuclear cells; not reported= data no reported or mentioned within the study).
Table 2: Immunophenotype of EPCs utilized
in various clinical studies
(CD= cluster differentiation; VEGFR= vascular endothelial growth
factor receptor; n.a.= not
assessed; not reported=
data no reported or mentioned within the study).
ical factors that should be carefully taken into account
when quantifying CECs and EPCs for clinical purposes.
Breast cancer (7) - Venous PB, from pts with advanced
disease, 10 milliliters (ml) was collected in ethylenediamine-tetra-acetic acid (EDTA)-containing tubes. The
PB mononuclear cell (MNC) layer was isolated using
Ficoll® density-gradient centrifugation within 12 hours
of blood collection. MNCs were then labeled with fluorescein isothiocyanate (FITC-conjugated anti-CD14 (BD
Pharmingen, San Jose, CA), phycoerythrin (PE)-conjugated anti-CD146 (BD Pharmingen, San Jose, CA) or
PE-conjugated anti-CD133 (Milteny Biotec, Auburn,
CA) with FITC-conjugated anti-VEGFR2 (BD
Pharmingen, San Jose, CA). The frequency of circulating
EPCs was determined by measuring of cells co-expressing CD133 and VEGFR2 after gating for CD14-positive
cells. Analysis was performed using a Beckman Coulter
(Fullerton, CA) flow cytometer and data were analyzed
using associated software. Results were reported as number of EPCs per 5 million MNCs.
Head and Neck cancer (8) - Blood samples were taken
via venipuncture using a 6 ml EDTA tube. FACS analysis was carried out within three hours. Two hundreds
microliters (µl) blood containing EDTA were used per
sample. To avoid unspecific binding via Fc-receptors,
samples were incubated with 10 µl FcR-blocking reagent
(Milteny Biotec, Bergisch Gladbach, Germany) for 15
minutes at room temperature (RT). Next, the cells were
incubated with fluorochrome-labeled mononuclear antihuman mouse antibodies or appropriate isotype controls
for 20 minutes at RT. CEC: 40 µl CD31-FITC (Becton
Dickinson, Biosciences, NJ), 5 µl CD146-PE (Becton
11
12
Dickinson), 20 µl CD45-peridinincyanine (PeCy)5
(Becton Dickinson) and 5 µl 7-aminoactinomicin (ADD)
(Becton Dickinson, Biosciences). EPC: 2 µl KDR-Biotin
(Abcam, Cambridge, UK), 20 µl CD133-PE (Miltenyi
Biotec), 5 µl 7ADD (Becton Dickinson, Biosciences)
and 10 µl of CD3, CD33 and CD19-PE-Cy5 (Becton
Dickinson). Mature CECs were defined as negative for
the haematopoietic marker CD45 and positive for the
endothelial markers CD146 (P1H12) and CD31. EPCs
were defined as positive for CD133 and VEGFR-2 and
negative for the lymphocyte markers CD3, CD19. Dead
cells were excluded by the use of 7-ADD. CECs and
EPCs were expressed as number of events identified as
CECs or EPCs per 500.000 analyzed events.
Breast cancer (9) - Peripheral blood samples were collected using 4 ml Vacutainer tubes containing sodium citrate
(3.2%). From these samples, 50 µl of anticoagulated blood
was aliquoted for analysis of monocyte activation, and 3
ml was aliquoted for analysis of CECs. All samples were
stored at RT and processed within three hours. For the
CEC analysis, normal donor blood spiked with human
umbilical vascular endothelial cells (HUVECs) at approximate equivalent numbers (50:50 mixture) per leukocyte
count was used as a positive control for all experiments.
In preparation for the analysis of CECs, samples were first
enriched using a negative selection/depletion strategy.
Anticoagulated blood samples (3 mL) were transferred to
4 ml Vacutainer cell preparation tubes (CPT) (Becton
Dickinson, BioSciences Canada, Mississauga, ON). These
tubes contain a citrate anticoagulant with a Ficoll
Hypaque® (Amersham Biosciences, Freiburg, Germany)
density fluid and a polyester gel barrier which permits
one-step separation of mononuclear cells from whole
blood via centrifugation. In addition, 50 ml of Rosette
Sep1 Human CD45 depletion cocktail (StemCellTechnologies, Vancouver, BC) was added to samples before centrifugation, incubated for 20 minutes at RT, and then centrifuged at 1,700g for 30 minutes with the brake off in
order to produce an enriched sample of nucleated cells
depleted of CD451 leukocytes. This cell layer was collected, washed twice with phosphate buffered saline (PBS),
and re-suspended in 100 ml of PBS 1 1% bovine serum
albumin 1 mM-EDTA. Samples were stained with 10 µl
of anti-human PE-CD146 (cloneP1H12; BD Biosciences)
and 10 µl of antihuman FITC-CD45 (Beckman Coulter,
Fullerton CA) at RT for 15 minutes in the dark. Samples
were then washed, fixed, and permeabilized with the IntraPrep® Fix/Perm Kit (Beckman Coulter), re-suspended in
500 µl of propidium iodide (PI) (Beckman Coulter), and
incubated for 45 minutes before flow cytometric analysis.
A four color XL-MCL® (Beckman Coulter) was configured to detect the FITC-CD45 signalling FL1 (525
nanometers, nm, band pass filter), PE-CD146 in FL2 (575
nm band pass filter), and PI FL3 (625 nm band pass filter).
Flow cytometric data collection was standardized by using
a 600 events acquisition time for each sample. Flow rates
were kept below 350 events/second to minimize the effect
of coincidence events, and two wash cycles with distilled
water were processed through the flow cytometer between
each sample to minimize cell carry over between samples.
Events which were CD146-positive, CD45-negative were
considered to be CEC events; they were expressed as number of events considered CECs per 600 detected events.
Various solid tumors (10,11) - The first 3 ml of PB
(potentially contaminated with endothelial cells from the
venipuncture) were discarded and pts bearing catheters
were excluded from the study. Blood was collected in
cell processing tubes (Becton Dickinson) containing
sodium citrate and Ficoll. Within two hours, tubes were
centrifuged at RT for 25 minutes at 1,600 g. The MNCs
were transferred to a cryotube and an equal volume of
freezing medium (RPMI 1640 with 20% DMSO for a
final 10% concentration) was added to the cell suspension. Samples underwent a controlled freeze using an
isopropanol bath in a -80 °C freezer. Samples were then
stored in liquid nitrogen until the day of shipping, in
abundant dry ice and always took <7 days. After shipping, the tubes were kept in liquid nitrogen up to the day
of thawing, which was performed by washing the cells
using the same storage medium. Samples were enumerated within 60 minutes after thawing. CECs and EPCs
were evaluated by six-color FCM using the nuclear stain
Syto16 and 7-AAD and a panel of MoAbs including
anti-CD45 (to exclude hematopoietic cells), antiCD133, anti-CD31, and anti-CD146. Cell suspensions
were evaluated after red cell lysis by a FACSCanto®
(Becton Dickinson). After acquisition of at least 1 x 106
cells per blood sample, analyses were considered informative when an adequate number of cells (>100, typically
300-400) was collected in the CEC enumeration gates.
CECs were defined as DNA (Syto16)-positive, negative
for the hematopoietic marker CD45, positive for the
endothelial markers CD31 and CD146, and negative for
the progenitor marker CD133. EPCs were identified by
the expression of CD133. The combination of Syto16
and 7-AAD was used to gain insight into CEC viability.
Necrotic cells were identified as Syto16low/7-AAD+,
apoptotic cells as Syto16low/7-AAD-, and viable cells as
Syto16-bright / 7-AAD-negative. To assess and validate
the reproducibility of the procedure, in three separate
series of studies, a fresh and a frozen/thawed sample
were evaluated in triplicate by the same operator (for the
analysis of intra-reader variability) and by three different
operators (for the analysis of inter-reader variability).
For the evaluation of variability over time, fresh samples
were evaluated on the same day of collection and after
24, 48, and 72 hours; frozen samples were thawed and
investigated after 0, 2, 7, and 14 days of storage in liquid
nitrogen. Finally, duplicate frozen samples were sent
from Houston to Milan and read in duplicate (evaluated
by two different laboratories, which were blinded to each
other’s results) in the two laboratories after > 6 months
storage. Results were expressed as number of CECs or
EPCs per ml of PB. The above described methods have
been recently utilized by other authors (12-16) in different clinical settings.
Lung cancer (17) - Twenty ml of PB was collected by
inserting of a 20-gauge needle intravenously and collected in tubes containing sodium citrate (0.105 mM). All
blood samples were processed within one hour after collection. Peripheral blood MNCs were prepared by gradient centrifugation using Ficoll Hypaque® (Amersham
Biosciences, Freiburg, Germany). The expression of
cell-surface antigens was determined by four-color
immunofluorescence staining. Briefly, 100 µl PBMC
(containing 106 cells) were incubated with 10 µl FcRblocking reagent ( Milteny Biotec, Bergisch Gladbach,
Germany) for 10 minutes to inhibit non-specific binding.
Subsequently, the cells were incubated at 4 °C for 30
minutes with 10 µl PE-conjugated anti-human CD133
MoAb (Milteny Biotec, Bergisch Gladbach, Germany),
10 µl PerCP-conjugated anti-human CD34 monoclonal
antibody (MoAb) (BD Biosciences, Heidelberg,
Germany), 10 µl allophycocianin (APC)-conjugated
VEGFR2 MoAb (R&D Systems, WiesbadenNordenstadt, Germany) and 10 µl FITC-conjugatde
Annexin V MoAb (BD Biosciences, Heidelberg,
Germany). PE-, PerCP-, APC- and FITC-conjugated isotype-matched immunoglobulins (Ig)-G1 and IgG2a Abs
(DakoCytometion, Heidelberg, Germany) were used as
negative controls. The cells were washed three times to
remove unbound antibodies and finally resuspended in
400 µl FACS solution (BDBiosciences, Heidelberg,
Germany). FACS analysis was performed on a
FACSCalibur flow cytometer (BD Biosciences) and the
data were analyzed using Win-MDI 2.8 software. A minimum of 500,000 events were collected. FACS analysis
of each probe was performed in triplicate. The frequency
of EPCs in PB was determined by a two-dimensional
side-scatter/fluorescence dot-plot analysis of the samples, after excluding Annexin V-positive cells with
appropriate gating. The exclusion of Annexin V-positive
cells was performed to rule out contamination with apoptotic cells in our positive population. EPCs were defined
as CD31+, CD133+, VEGFR2+. EPC counts were
expressed as a percentage of total PB MNCs foir each
patient sample or control.
Lung cancer (18) - Peripheral blood samples were collected in EDTA tubes and circulating hematopoietic progenitor cells (HPCs) and CECs were measured using a
whole-blood flow cytometric method. CD133-positive
HPCs were defined as CD34 bright/ CD45 dim and
CECs were defined as CD34 bright / CD45-negative and
largely positive for VEGFR-2. The Abs used to carry out
analysis in this study included CD45-FITC, CD34-APC,
CD133-PE, VEGFR-2-PE and viability marker 7-AAD.
Cell populations were measured by FCM (FACSCalibur,
BD, Biosciences, Breda, The Netherlands) in a total volLettere GIC Vol. 23, Num. 3 - Dicembre 2014
ume of 1.5 ml whole blood and appropriate IgG isotypes
were used as a controls. Circulating cells from the comparison groups were assessed with CD45-FITC, CD34APC and 7-AAD. CECs were defined as CD34 bright,
CD45-, VEGFR2+, while HPCs CD34 bright, CD45
dim, CD133+.
Colon cancer (19) - Peripheral blood samples were collected in a 3 ml Vacutainer tube containing liquid
tripotassium (K3)-EDTA. Non-specific Ab binding was
blocked with 20 µl FcR-blocking reagent and 200 µl
mouse serum for 20 minutes at RT before staining with
conjugated Abs. Dead cells were excluded by 7-AAD.
CEPs, CECs and their viable subpopulations were evaluated by a four-color FCM, using the following MoAbs:
FITC-labelled anti-CD34 (8G12, BD Pharmigen, San
Jose, CA) and anti-CD106 (51-10C9, BD Pharmigen,
San Jose, CA); allophycocianin (APC)-labelled antiCD34 (8G12, BD Pharmigen, San Jose, CA) and antiCD133 (AC133, BD Pharmigen, San Jose, CA); R-PElabelled anti-CD146 (P1H12, BD Pharmigen, San Jose,
CA); CA and peridinin chlorophyll protein cyanine 5-5
(PerCP- Cy 5-5)-labelled anti-CD45 (2D1, BD
Pharmigen, San Jose, CA). Flow cytometric analysis was
carried out in whole blood without any enrichment procedure to avoid enrichment artifacts. Anticoagulated
venous blood was divided in 100 µl aliquots in two 12
x 75 ml polypropylene test-tubes and after gentle mixing,
incubated with the appropriate fluorochrome-conjugated
MoAbs at the manufacturer’s recommended concentration for 15 minutes at RT in the dark. CD34-FITC,
CD146-PE, CD45-PerCP, CD133-APC were used for the
first sample tube and CD106-FITC, CD146-PE, CD45PerCP, CD34-APC were used for the second. Stained
whole blood samples were subjected to red blood cells
lysis with 2 ml lysing solution, by vortexing and incubating for 15 minutes at RT in the dark. Prepared samples
were stored RT in the dark and analysed within one hour.
Evaluation of nucleated cells from whole blood specimens was performed using a FACSCanto® FCM (BD
Biosciences, San Jose, CA, USA), with identical set up
parameters between samples. FCM data was analysed
using BD FACSDiva software. A range of internal quality assurance procedures was employed, including the
daily calibration of FCM optical alignment and fluidic
stability using 7-color Set Up Beads (BD Biosciences).
The precision and stability of cell count were tested by
using international quality controls purchased from the
United Kingdom National External Quality Assessment
Scheme and daily monitoring of whole-blood preparation procedures and antibodies reactivity using ImmunoTrol (Beckman Coulter, Fullerton, CA,USA) control
cells. The absolute CEC and CEP number was derived
from the absolute number of white blood cells provided
by a haematological analyser and the percentage of CEC
and CEP as determined by FCM, using the following formula: percentage of cells x white blood cell (WBC)
13
14
count/100. On the basis of appropriate analysis gates, the
following cell pupolations were defined: total CECs as
CD45-, CD146+, CD34+ and CD133-; rCECs as CD45,
CD146+, CD34+, CD106- cells; aCECs as CD45-,
CD146+, CD34+, CD106+; CEPs as CD45-, CD34+,
CD146+ and CD133+. The absolute CEC and CEP number was derived from the absolute number of WBCs provided by the hematological analyzer (Coulter, Miami,
FL) and the percentage of CECs and CEPs as determined
by FCM, using the following formula: percentage of
cells x WBC count/100.
Ovarian cancer (20) - Peripheral blood samples were collected by venipuncture using EDTA as an anticoagulant.
Then, 100 µl whole blood was labeled with PE-conjugated
anti-human VEGFR-2 and FITC-conjugated anti-human
CD34 (BD Biosciences, Franklin Lakes, NJ) by incubating
for 30 minutes at 4°C. Fluorescein isotype matched Abs
IgG1-FITC/IgG1-PE (BD Biosciences, Franklin Lakes,
NJ) were used as controls. The suspension was then incubated with FACS lysing solution (BD Biosciences,
Franklin Lakes, NJ) for 10 minutes. After washing in PBS
and fixing in 1% formaldehyde, samples were analyzed on
a FACSCalibur® instrument (BD Biosciences, Franklin
Lakes, NJ). EPCs were defined as CD34+, VEGFR2+. The
percentage of double-positive MNCs (CD34+ / VEGFR2+) was converted to cells/ml of PB using the complete
blood count.
Various cancer (5) - Peripheral blood (10 ml) was collected in heparinized tubes using a Vacutainer system (Becton
Dickinson). The first 3 ml of blood was discarded in order
to prevent contamination with CEC resulting from vascular injury. Samples were processed immediately after collection or stored at RT. Following incubation at RT in the
dark for 30 minutes, 10 ml of RBC lysing solution was
added, and the samples were incubated at RT for exactly 8
minutes. Subsequently, samples were washed twice with
10 ml cold PBS. Finally, the cells were resuspended in
1000 µl PBS for immediate flow cytometric analysis, in an
FC500-Cytometer® (Beckman Coulter) and CXP analysis
software (version 2.2). In each analysis, 1,000,000 total
events were collected. For each blood sample, isotype
matched controls were analyzed in order to set the appropriate regions. For each marker combination, samples were
analyzed in duplicate. In order to minimize false positive
events, the number of double positive events detected with
the isotype controls was subtracted from the number of
CD34+/KDR+ or CD133+/CD31+ events, respectively.
Cells expressing a specific marker combination were
reported as the percentage of the number of gated events.
Lymphocytes were used as internal negative controls and
were shown to be negative for co-expression of the above
antigens as determined by the described antibodies. The
reported flow cytometric protocol used three different
markers (CD45, CD133, and CD31) to phenotypically distinguish EPCs from mature endothelial cells and
hematopoietic progenitor cells. EPCs were detected as a
distinct CD45−/CD31+/CD133+ cell population within the
MNCs, and results were expressed as percentage of MNCs.
Lung cancer (21) - Peripheral blood was collected in
EDTA tubes with a 21-gauge needle. FCM was used to
measure the number of EPCs in PB. FACS analysis was
performed to quantify the content of circulating EPCs.
Mononuclear cells were isolated from PB using Ficoll
Hypaque® density gradient centrifugation. The expression of cell surface Ag was determined by 2-color
immunofluorescence staining. After centrifugation, the
mononuclear cell layer was carefully transferred to a
new tube, mixed with red cell lysis buffer for at least 10
minutes at 4°C and washed twice in PBS containing
0.3% bovine serum albumin. A 100 µl volume of MNCs
from PB was incubated for 30 minutes while protected
from light at 4°C, along with 20 µl FITC-conjugated
anti-human CD34 (BD Biosciences, USA) and 20 µl of
PE-conjugated anti-human VEGFR2 (R&D Systems,
USA) or with 20 µl of FITC-conjugated anti-human
CD34 and 20 µl of PE-conjugated anti-human
CD133/AC133 (eBioscience, USA). Appropriate fluorochrome-conjugated isotype-matched IgG1 and IgG2a
Abs were used for each pt and measurement of negative
controls. Cells were washed three times to remove
unbound Abs and finally re-suspended in 900 µl FACS
solution. After appropriate gating, numbers of CD34positive and CD133-positive cells were determined as
circulating EPCs in PB and expressed as the number of
cells per ml blood using a Cytomics CF500® FCM and
CPX software (Beckman Coulter, USA).
Renal cancer (22) - Two ml of PB were collected in
CellSave Preservative® tubes (Immunico, Ungtington
Valley, PA, USA) for CEC analysis; 10 ml whole blood
were collected in standard heparin tubes for CD45dim
CD34+ VEGFR2+ 7-AAD- progenitor cell analysis.
CECs were measured in 1 ml whole blood by four-color
FCM. Immunofluorescent staining was performed with
the MoAbs CD31 FITC (clone WM59, BD Pharmingen,
San Diego, CA), CD146 PE (clone P1H12, BD
Pharmingen), CD45 APC (clone T29/33, DakoCytoma tion). An IgG-PE control was measured in 0.5 ml whole
blood (CD45-APC/CD31-FITC/mouse IgG1-PE/7AAD) to measure background noise and to precisely
adjust the gates. All of the cells in the IgG-PE control
sample and the CEC test sample were acquired, representing approximately 2.5 x 106 events and 5 x 106
events, respectively. Cells were acquired using a
FACSCalibur and data were analyzed using CellQuest
3.2 software. Using this method the authors found that
median CEC levels were 6.5 ml-1 (0-15 ml-1) in healthy
adults and 16.0 ml-1 (0-179 ml-1) in pts with metastatic
carcinoma (p<.001). Progenitor cells CD45dim CD34+
VEGFR+ 7-AAD- were measured in 10 ml of progenitor-enriched whole blood with a four-color FCM assay.
Ficoll-gradient MNCs were enriched in progenitor cells
using the RosetteSep Ab cocktail (Stem Cell
Technologies Inc., Vancouver). Progenitor enriched
MNCs were distributed into control and test tubes and
treated with FcR blocking reagent (Milteny Biotech,
Bergisch Gladbach, Germany). Staining was performed
with the MoAbs CD34-FITC (clone T29/33,
DakoCytomation), CD34-APC (clone BIRMA-K3,
Dako), KDR-PE (clone 89106, R&D Systems,
Minneapolis, MN) and 7-AAD (BD Bioscience).
Controls included a control PE sample (CD-45
FITC/mouse IgG1-PE/CD34-7-AAD) assayed to accurately measure background noise and to precisely adjust
the gates. Cells were acquired using a FACSCalibur and
data were analyzed using CellQuest 3.2 software.
Results were expressed as the percentage of VEGFR2+
cells among circulating CD34+ progenitor (CD45dim
CD34+ 7-AAD- and CD45- CD34+ 7-AAD-) cells,
while CECs as number of CECs per ml of PB.
Prostate cancer (23) - Ten µl each of fluorochrome
labeled CD45, CD146, CD34 and CD309 Ab were added
to 200 µl PB. Blood was incubated in the dark at RT for
20 minutes, then 3 ml red cell lysing/fixative solution
was added and samples were further incubated for 15
minutes at RT. Excess reagents were washed away with
3 ml PBS cycles by centrifugation (200 g 5 minutes).
After the final wash, 0.5 ml of PBS was added and the
suspension was analyzed with a FACSCalibur (BD
Biosciences, San Jose, CA). Data was acquired with
Cellquest software. WBC were identified and excluded
by side scatter (SSC) and forward scatter (FSC) in conjuction with CD45PerCP, as it is known that some white
blood cells may also express endothelial and/or stem cell
markers. CD34-APC positive cells were then gated and
subsequently re-probed in a separate analysis with
CD309-PE and CD45-PerCP for EPCs or with CD146FITC and CD45-PerCP for CECs. CECs were defined
as being CD34+, CD146+, CD45-, and CD309-, EPCs
were similarly defined as being CD34+, CD309+,CD45, and CD146-. Both CECs either EPCs were expressed as
number of cells per ml of PB.
Pancreatic cancer (24) - Three ml PB was drawn in
EDTA tubes and 200 µl was subjected to immunostaining with anti-human CD45−PC5 (Immunotech,
Beckman Coulter, Brea, CA), CD31–FITC
(Immunotech), CD146-PE (Chemicon, Billerica, MA),
and 7-AAD (Immunotech). Addition of CD3-PC7
(Immunotech) or CD41-PC7 (Immunotech) was applied
in a limited analysis set. After a “lyse-no-wash” procedure with VersaLyse reagent (Immunotech),the samples
were analyzed with an FC500® FCM (BeckmanCoulter)
for the detection of three cell populations: 1) CD45−
CD31+CD146+, 2) CD45− CD31− CD146+, and 3)
CD45− CD31highCD146−. To evaluate cell viability 7AAD was applied. Blood cells were analyzed by FCM,
and flow cytometric data were subsequently processed
with Kaluza Analysis 1.0 software (Beckman Coulter).
FCM identified three blood cell populations with a disLettere GIC Vol. 23, Num. 3 - Dicembre 2014
tinct CD45, CD31, andCD146 phenotype. PB cells were
stained with Abs directed to CD45, CD31, and CD146.
Cells were not discriminated based on forward or side
scatter properties but were gated according to CD45
detection. When CD45-negative cells were evaluated for
surface expression of CD31 and CD146, three distinct
cell populations were identified: double-positive
CD31+CD146+, single-positive CD31− CD146+, and
CD31 high CD146−. When Abs to CD3 or CD41 were
included in the analysis to further characterize the three
cell populations, the CD45− CD31− CD146+ subset was
largely positive for CD3, whereas the other two cell populations were negative for CD3 expression. The CD45−
CD31highCD146− cells were partially positive for
CD41. CECs were defined as CD45 - CD31+ CD146 +
cells per ml PB.
Breast cancer (25,26) - Ten to 20 ml PB was collected in
EDTA-containing tubes and processed within 12 hours.
Peripheral blood MNCs were isolated by Ficoll densitygradient centrifugation. To quantitate EPCs, cells were
stained with PE-CD133 (Miltenyi Biotec, Auburn CA),
VEGFR-2-APC (R&D Systems, Minneapolis, MN), and
PerCP-CD45 (BD Biosciences, Franklin Lakes, NJ). An
aliquot of cells was stained with the appropriate isotype
control (mouse anti-human IgG1k). Samples were analyzed with FACSCalibur® FCM (BD Biosciences, San
Jose, CA). Three hundred thousand events were collected in the nucleated cell gate (excluding debris and
platelets). Data analysis was done using FlowJo® software (FlowJo, Ashland, OR). EPCs were defined as
CD45dim, CD133+, VEGFR2+ (26) The number of
EPCs and HPCs per ml of blood was calculated as follows: HPC/ml = (HPC events/lymphocyte events) X
absolute lymphocyte count (lymphocytes/ ml). EPC/ml =
(EPC events/lymphocyte events) X absolute lymphocyte
count (lymphocytes/ml).
Colon cancer (27) -These Authors used a method publi shed by Ronzoni et al. in 2010, in order to identify even
the apoptotic CECs (APO-CECs). PB samples were collected in a 3 ml Vacutainer tube containing liquid K3EDTA as an anticoagulant and assayed the same day.
CECs and their subpopulations were evaluated by a sixcolor FCM (BD Biosciences FACSCanto) using a specific panel of MoAbs and staining solutions: R-PElabelled anti-CD146 (P1H12; BD Pharmigen, San Jose,
CA), FITC-labelled anti-CD106 (51-10C9, BD
Pharmigen, San Jose, CA) and APC-labelled anti CD133 (AC133, BD Pharmigen, San Jose, CA); phycoerythrin/Cyanin7 (PE/Cy7)-labelled anti-CD34 (8G12,
BD Pharmigen, San Jose, CA); allophycocyaninCyanin/7 (APC/Cy7)-labelled anti-CD45 (2D1, BD
Pharmigen, San Jose, CA). The Viability/Dye 7-AAD
was used to detect the viability of cells. The annexin V
Kit (Bender Medsystems,Boehringer Ingelheim) was
added in order to quantify APO-CECs. This kit contains
human FITC-conjugated Annexin V and a binding buffer
15
18
solution. CD 106-FITC, CD146-R-PE, CD 34-PE/Cy7,
CD133-APC, CD45-APC/Cy7 were used in the first
sample and CD146-R-PE, CD34-PE/Cy7, CD133 APC,
CD45 APC/Cy7 in the second. 20 µl of 7-AAD was
added to the first sample and incubated for 15 minutes at
RT in the dark. The sample was therefore measured within 15 minutes of preparation. The second sample was
centrifuged at 500g for 10 minutes at 20°C to re-pellet
the cells, washed in PBS and centrifuged again. The pellet was re-suspended in 400 ml of binding buffer, containing 5 ml of FITC-conjugated Annexin V. It was then
incubated for 10 minutes at RT in the dark and washed
again with the binding buffer. Lastly, 20 ml of 7-AAD
was added for 15 minutes at RT in the dark and the sample was analyzed within 15 minutes. On the basis of gating strategy the following cell populations were defined:
mature CECs as CD45-, CD146+,CD34+ and CD133-;
resting CECs (rCECs) as CD45-,CD146+, CD34+,
CD106-, CD133-; activated CECs (aCECs) as CD45-,
CD146+, CD34+, CD106+, CD133-; EPCs as CD45-,
CD34+, CD146+ and CD133+ and APO-CECs as
CD45-, CD146+, CD34+, CD133-, Annexin V+. The
number of CECs and APO-CECs were calculated as percentage of cells x WBC count/100.
Renal cancer (28) - Heparin anticogulated PB (100 µl)
was incubated for 30 min at 4°C with PE-conjugated
mouse anti-human VEGFR-2 (R&D, Systems), FITCconjugated mouse anti-human CD34 and PerCP-conjugated mouse anti-human CD45 antibodies (BD,
Biosciences). After incubation, the cells were lysed,
washed twice with PBS and analyzed with a 2-laser, 6color configuration FACSCanto®. Samples were stained
for CD34, VEGFR-2, and CD45 and acquired using
FSC-A/SSC-A scatter gate around the MNC population
with 100,000 gated events per sample recorded. CD45MNCs were gated for EPC quantification analysis.
CD45-CD34+VEGFR-2+ cells were identified as EPCs.
The percent of EPCs among the total number of PB
MNCs was recorded.
Osteosarcoma (29) - Peripheral blood samples (5 ml)
were collected from each patient in an EDTA tube.
Samples were shipped overnight at 4° C to the study reference laboratory. Samples were processed for analysis
within 24 hours of collection. Enumeration of CECs and
CEPs was carried out with 4-color FCM. A panel of
MoAbs, including anti-CD45 (BD Bioscience; San Jose,
CA), anti-CD31 (BD Bioscience), anti-CD146
(Chemicon; Temecula, CA) and anti-CD133 (Milteny
Biotec; Auburn, CA) were used to enumerate CECs and
CEPs while excluding hematopoietic cells. Nuclear
staining (Procount, BD Bioscience) was used to exclude
the potential interference of platelets and cellular debris
with CEC and CEP enumeration. After red blood cell
(RBC) lysis, cell suspensions were evaluated by a FACS
Calibur cell analyzer and CellQuest Pro software (BD
Bioscience) using analysis gates designed to exclude
dead cells, platelets and debris. A minimum of 100,000
events per sample were acquired to obtain the percentage
of CECs or EPCs per sample. The absolute number of
CECs and EPCs was derived using a single platform
flow cytometric analysis with the addition of Stem Count
beams (Beckman Coulter, Brea, CA). To assess counting
accuracy, the total white blood cell count of the FCM
was compared with clinical results for each subject’s
WBC count. Stained cells were determined and compared with appropriate negative controls and positive
staining was defined as being greater than nonspecific
background staining. CECs were primarily defined as
CD146+CD31+CD45-CD133and
EPCs
as
CD146+CD31+CD45-CD133+. Considering that other
research groups have incorporated other markers into the
definition of these cells, expression of the following
markers was also assayed in place of CD146: VEGFR2
/R&D Systems; Minneapolis, MN); VEGFR3 (R&D,
Systems); CD105 (Invitrogen; Carlsbad; CA); CD143
(AbD Serotec; Raleigh, NC) and CD144 (BD,
Biosciences) expression. 7-AAD staining was used to
quantify apoptotic subsets. CECs and EPCs were
expressed as number of cells per ml of PB.
Glioma (30) - Whole PB (100 µl) was incubated with the
MoAbs anti-CD45-Cy5 (BD Biosciences, Franklin
Lakes, NJ), anti-CD34-FITC (BD, Biosciences) and
anti-CD133-PE (Miltenyi Biotec, Bergisch Gladbbach,
Germany) for 30 minutes at 4 °C. RBC were then lysed
and WBCs were fixed with Uti-Lyse kit
(DakopCytomation, Glostrup, Denmark). Isotypic antibodies served as controls. Samples were analyzed with a
FACS Vantage SE (BD Biosciences). CD45dim, CD34+,
CD133+ MNCs were considered as EPCs. At least 500
CD34+ cells per sample were acquired. A complete
WBC count was performed with a cell counter and the
absolute number of EPCs per µl blood was calculated as
follows: EPCs (cell/µl)= number of EPC/(number of
WBC acquired/number of WBC per µl).
Various cancer (31) - Peripheral blood was collected
using-EDTA-containing tubes and samples were stored
at RT and examined within 8 hours after venipuncture.
CECs were defined as CD34+ CD45- CD146+ DNA
dye+ events. For analysis, samples were prepared in a
lyse-stain wash procedure with minimal sample handling. 4 ml PB were transferred to 50 ml tubes and 45
ml of 0.15 M ammonium chloride was added to induce
RBC lysis. After 20 minutes at RT the suspension was
centrifuged for 5 minutes at 1000 x g and the supernatant
was removed from the sample without disturbing the pellet. To reduce Fc-R-mediated Ab binding 50 µL CD32
MoAb (clone IV3; Stem cell Technologies, Vancouver)
was added. After 10 minutes cells were stained using a
50 µl mixture of the following MoAbs: FITC-conjugated CD34 (clone 8G12, BD Bioscience); PE-conjugated
CD105 (clone IG2;IOtest, Marseille, France); PerCPconjugated CD45 (clone 2D1,; BD Biosciences); APCLettere GIC Vol. 23, Num. 3 - Dicembre 2014
conjugated CD146 (clone 541-10B2; Milteny Biothech)
and 50 µl DNA dye DRAQ5 (Biostatus Ltd, Shepsed,
UK). After 15 minutes in darkness at RT, 45 ml PBS
were added and the suspension was centrifuged for 5
minutes at 1000 x g. Cells were then suspended in PBS
and transferred to a standard 5-ml FCM tube. Samples
were immediately acquired on a FACSCanto II FCM
with FACSDiva v6.1 software (BD, Biosciences). Data
acquisition was started by collecting ungated data from
50,000 nucleated cells (DRAQ5+) at a low flow rate of
10 µl min-1. Data acquisition was completed by acquiring the remainder of the sample at a high flow rate (120
µl min-1) with a threshold (live-gate) on CD34+ events
in a separate file. CECs were defined as CD34+,
CD45neg, CD146+ and DNA+ events. Absolute counts
were obtained by multiplying the CEC percentage whith
the CD34+ population in 4 ml of blood by the simultaneously obtained absolute CD34+ counts, obtained on the
same blood sample using the single platform flow cytometric assay according to ISHAGE guidelines.
Lung cancer (32) - Mononuclear cells were isolated from
PB by density centrifugation (Lymphoprep®). Freshly
isolated MNCs were incubated for 30 minutes at 4°C in
the dark with PE-conjugated against human KDR-Ab
(R&D Systems, Minneapolis, MN) and with CD34
FITC-conjugated Abs (Beckman Coulter, Inc Fullerton,
CA). Isotype-identical Abs served as controls. After
incubation, quantitative analysis was performed on a
Coulter Epics XL (Beckman Coulter, Inc Fullerton, CA),
measuring 1.000.000 cells per sample. EPCs were identified as CD34+/KDR+ cells and were expressed as percentage of CD34+ cells per WBC count.
Colon cancer (33) . Two hundreds µl PB was collected
into sodium citrate tubes. Ten µL of each fluorochromelabelled antibody CD45, CD146, CD34 and CD309 were
added (all from BD Biosciences, except CD309 R&D
Systems). Blood was incubated in the dark at RT for 20
minutes, then 3 ml red cell lysing/fixative solution was
added and the sample was incubated for 15 minutes on
the bench. EPCs and CECs were analyzed by FCM
(FSCS Calibur, BD, Biosciences, Oxford, UK). The Cell
Quest Pro software was used to determine cell counts
with a minimum of 100,000 events. WBCs were identified and excluded by SSC and FSC in conjunction with
CD45-PerCP. CD34-APC positive cells were then gated
and subsequently reprobed in separate analyses with
CD309-PE and CD45PerCP for EPCs or with
CD146FITC and CD45PerCP for CECs. Intra- and interassay CVs were < 24% for EPCs, < 47% for CECs, <
40% for EPCs and < 60% for CECs, respectively. EPCs
were defined as CD34+, CD45-, CD309+, while CECs
were CD34+, CD45-, CD146+. Both CECs either EPCs
were expressed as number of cells per µl PB.
Colon cancer (34) - Flow cytometry analysis was accomplished with whole blood without any enrichment procedure to avoid manipulation artifacts. EPCs were defined
as CD31+, VEGFR-2+, CD45dim, and CD133+; mature
CECs were defined as CD31bright, and VEGFR-2+, but
negative for hematopoietic markers such as CD45 and
CD133. The chromophores conjugated with the antibodies used in this study included CD31-FITC (BD
Pharmingen, San Diego, CA), CD133-PE (Miltenyi
Biotec, Auburn, CA), CD45-PerCP (BD Pharmingen),
and VEGFR2-PE (R&D Systems, Minneapolis, MN).
The MNC population was gated to avoid RBC, platelet,
cell debris, and neutrophil contamination; 100,000
events in the MNC gate were collected with a
FACSCalibur flow cytometer (BD Biosciences, San
Jose, CA, USA). Data were collected and analyzed using
CellQuest Software (BD Biosciences). EPCs were
defined as CD31+, VEGFR2+, CD45dim, CD133+,
while CECs were. Both CECs either EPCs were
expressed as number events suggestive for CECs or
EPCs per 100,000 events analyzed.
Ovarian cancer (35) - After discarding the first 2 ml after
venipuncture, PB samples were drawn: 10 ml whole
blood was collected in standard heparin tubes for circulating LVEPC analysis. FCM analysis was based on the
expression of cell surface markers CD34 and VEGFR3
in the mononuclear gate where LVEPCs are commonly
found. The samples were treated with density centrifugation, following RBC lysis. The remaining PBMNC fraction was resuspended in 100 ml cell-sorting buffer containing PBS and 0.1% bovine albumin and then incubated for 30 min at 4°C with FITC-conjugated antihuman
CD34 (eBioscience) and PE-conjugated antihuman
VEGFR3 (R&D Systems) Cell level detection by FCM
(R&D Systems) according to the manufacturer’s protocol. Fluorescent IgG1-FITC (eBioscience) / IgG1-PE
(R&D Systems) isotype matched Abs were used as control, the same isotype quantity was used. The suspension
was then incubated with FACS lysing solution for 10
minutes, according to the manufacturer’s instructions.
EPCs were identified as CD34+, VEGFR3+ population.
Results were described as the percentage of
CD34+/VEGFR3+ cells among PB using the CyFlow SL
flowcytometer and FACSDIVA software (both from BD
Bioscience).
Cervical uterine cancer (36) - Peripheral blood was collected using EDTA as an anticoagulant and processed within
several hours after collection as follows: whole blood was
diluted 1:1 with PBS containing o.5% bovine serum albumin (BSA) and 2 mmol/EDTA and overlaid onto an equal
volume of Ficoll Pacque® (GE healthcare). Samples were
centrifuged at 1,800 rpm for 25 minutes at RT with no
brake. The MNC layer was carefully collected and washed
twice with cold PBS containing 0.5% BSA and 2 mmol/L
EDTA at 4°C. Red blood cells were lysed with 0.38%
ammonium chloride solution. The final MNC preparation
was resuspended with PBS containing 0.5% BSA and 2
mmol/L EDTA and then subjected in FCM-analysis. The
viability of the MNCs used for the analyses was deterATTIVITÀ SCIENTIFICA
19
20
mined by the Dye exclusion test. Isolated PB MC 107 cells
per ml of blood were pretreated with FcR-blocking reagent
(Miltenyi Biotec) to block non specific Ab binding and
incubated on ice for 25 minutes with a panel of MoAbs.
The antibody-labeled cells were analyzed using FACS Aria
flow cytometer (BD Biosciences) equipped with 2 lasers
(488 and 633 nm). Data were analyzed with FlowJo® software or FACS DIVA (BD Biosciences, Tree Star, Inc). For
the analysis of CEC candidates, at least 100,000 singlet
WBC were isolated and the frequencies of CD45-/CD31+,
CD45-/CD31+/CD146+ or CD45-/CD31+/CD105+ cells
were analyzed and expressed as a percentage of the singlet
lymphocyte population. A number of protein markers
including CD31, CD34, CD105, CD146, CD144, and
VEGFR-2 have been used to define CECs; a generally
accepted definition of CECs is CD45-, CD31+ cells
expressing CD146+, or CD105+.
Cervical uterine cancer (37) - Peripheral blood MNCs
were isolated from 15–20-ml whole blood samples, which
had been collected in EDTA-sterile tubes. Blood was
mixed with an equal volume of PBS (pH 7.4), layered on
Ficoll reagent (1077 g/ml) and centrifuged at 400 g for 20
minutes at 15–20°C. The buffy coat containing MNCs was
recovered, mixed with 50 ml PBS and centrifuged at 300g
for 10 minutes at 15–20°C. The supernatant was discarded and the cell pellet was resuspended in 1 ml PBS. An
additional 19 mL of PBS was added and samples were
centrifuged at 300g for 10 minutes at 15–20°C. Viable
cells were counted by trypan blue staining. EPCs were
identified by quadruple immunofluorescence staining and
FCM. In brief, PB MNCs were incubated for 30 minutes
at 4°C with 2 ml each FITC-conjugated mouse antihuman
CD45, PE-conjugated mouse antihuman VEGFR2,
PerCP-conjugated mouse antihuman CD34, and APCconjugated mouse antihuman CD133 (all from BD
Biosciences, Heidelberg, Germany). Cells were washed
three times in BD FACS® Buffer (BD Biosciences) at 4°C
(5 minutes per wash) then fixed in 1% paraformaldehyde.
Parallel cell samples were stained with 1 ml PI for 5 minutes to validate the live cell population. A FACSCalibur®
flow cytometer (BD Biosciences) was used and data were
analyzed with Win-MDI software, version 2.9 (Scripps
Research Institute, San Diego, CA, USA). EPCs were
identified as CD45–, CD34+, CD133+, VEGFR2+ cells
and expressed as number of cells per ml PB.
Gastric cancer (38) -Two hundreds µl blood were collected in EDTA and reacted with PE-labeled anti human
CD133 (BD Pharmigen, San Diego, USA) MoAbs antihuman CD34 (BD, Pharmigen) FITC-labeled MoAbs.
The samples were incubated for 30 minutes at 4°C in the
dark. Mouse isotype identical Abs served as control (BD
Biosciences, Franklin Lakes, NJ). The suspension was
then incubated with fluorescence-activated cell sorte
lysing solution (BD Biosciences) for 10 minutes according to the manufacturer’s instructions. After being washed
in PBS and fixed in 1% formaldehyde, the samples were
analyzed with a FACSCalibur Instrument (BD
Biosciences). They analyzed 200,000 cells by FCM within the leukocyte gate with a FACSCanto analyzer (BD
Biosciences). The percentage of PB EPCs was estimated
with a 3-color Ab panel, previously described, and an
appropriate gating strategy. Cells, that were positive for
CD34 and VEGFR-2dim, with low to medium fetal calf
serum and standard saline citrate, and positive for CD34
and CD 133 were considered EPCs and expressed as percentage of EPC cells over the WBC count per ml PB.
Discussion
Flow cytometric detection of CECs and EPCs in whole
blood is a largely utilized assay to enumerate and these
cells in clinical studies, but remains technically challenging. Generally, the number of the cell of interest is very
low and they cannot be characterized by a single marker,
but are discriminated by using a combination of antigens
with low, dim or a continuum in cell surface expression. In
addition, the multitude of flow cytometric methods
applied, which are not always sufficiently detailed,
together with the heterogeneity of the patient series, greatly limits comparability for clinical purposes (Table 3).
A lack of an inter-laboratory standardized FCM assay, as
well as the lack of a consensus on CEC and EPC phenotype has resulted in enormous heterogeneity in the
reported number of CECs and EPCs (39). Hence, to date,
even when looking at similar clinical conditions, the
overall clinical value of the studies performed is partially limited. As far as EPCs are specifically concerned, the
possible utilization of these cells as biomarkers in clinical oncology requires sensitive, simple and reproducible
methods. FCM could be considered the gold standard for
this aim, but none of the proposed antigenic combinations is considered definitive for EPCs. For the definition
of these cells, the minimal antigenic profile should
include at least one marker of immaturity (in humans
usually CD34 and/or CD133), togheter with at least one
marker of endothelial commitment (usually VEGF-2 or
KDR). Following the original characterization of circulating EPCs as CD34+ KDR+ (40), several investigators
have confirmed that this phenotype identifies cells capable of stimulating the angiogenesis in vivo.
The number of circulating CD34+ KDR+ cells is around
50-100/106 WBC (0.005-0.01%), equal to about 350700 cells/mL. Subsequently, this phenotype has been
criticized since it overlaps in part with hematopoietic
stem/progenitor cells and with CECs (39). Although the
contamination of the CD34+ KDR+ population by CECs
should be negligible, some authors suggest that the coexpression of stem cell antigen CD133 increases specificity for EPCs, as it is not expressed by mature endothelial cells (39,41). Unfortunately, the frequency of
CD34+, KDR+, CD133+ cells in PB is at least 20-fold
lower, making quantification less reliable.
Therefore, increasingly complex antigenic phenotypes
Table 3: Clinical correlation
among CEC/EPC levels
reported in FCM-based studies in different solid tumors
(FCM= flow cytometry; pts=
patients; not found= none
clinical correlation found;
n.a.= not assessed; not
reported= data no reported or
mentioned within the study;
CT= chemotherapy).
might be more specific for EPCs but have lower reproducibility thus limiting their use in clinical practice in that,
the increased complexity of the antigenic combination,
despite providing additional biological information, does
not necessarily improve the performance of the cells as
clinical biomarkers. One way to partially circumvent this
limitation is to aquire a large amount of events (1,000,000
to 2,000,000) to gather a higher number of positive events.
In the specific field of FCM (42), the need of a precise
and detailed cell immunofenotyping have addressed the
21
researchers to the use of a large series of monoclonal
antibodies and therefore a parallel large variety of fluorochromes. This have consistenly improved the analytical capability, but at the same time, have also introduced
a greath criticism mainly due to a large “cross-tallk”
from probe to probe when these are employed simultaneously in the same test tube. This kind of sophisticated
analytical approach imply a great ability of the operators
in the management of the required steps of compensation, gating and generally in the data handling and interpretation of the analytical out-put.
Another consideration is that a disease biomarker does
not only have to be highly biologically informative, but
it is required to have a strong statistical association with
clinical manifestations of the disease. Hence, instead of
widening the antigenic phenotype to increase specificity,
efforts could made toward the simplification of the identification and quantification of EPCs.
From a more technical point of view, the use of FCM for
EPC quantification is a so called “rare event analysis”
which has to deal with problems related to background
noise, which might lead to false positive results.
Consequently, signal enhancement and noise reduction
are critical. Recently, Van Craenenbroeck and colleagues
elegantly reviewed the various steps that should be taken
into account for this type of analysis (4). They focused
on pre-analytical factors such as the choice of the sample material, modality of blood collection, handling temperature and some subject-related confounding factors.
Problems related to data acquisition such as the characteristics of the flow cytometer employed, protocols for
erythrocyte depletion, wash / no wash approaches and
modality to increase the signal to noise ratio were also
included, as well as, the importance of standardized gating strategy and correct data analysis. In this summary
only in some cases have the above mentioned points
been focused upon and reported in detail and this greatly limits the comparability of the studies.
In conclusion, although significant changes in the measurement of CECs and EPCs in different oncological diseases have been reported and steps forward the definition of their potential for clinical purposes have been
achieved, their reliable identification and quantification
still remains difficult. The variety of methods used to
study CECs and EPCs in published clinical studies is
extremely broad and, even when looking at similar clinical conditions, studies may arrive at opposite conclusion. Thus, the specification of an exact method is critical. So far, the quantification of CECs and EPCs should
be considered as a work in progress and the interpretation of results should be made cautiously. Consensus on
the choice of the antigenic combination for CEC and
EPC definition together with inter-laboratory standardization are necessary before these cells may be routinely
used as clinical biomarkers
22
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QUOTA ASSOCIATIVA GIC 2015... E QUELLE ARRETRATE
Carissimo Socio,
come sai, la quota sociale, oltre ad essere la principale fonte di finanziamento per il funzionamento della nostra Società, è anche un segno annuale di adesione e partecipazione.
La quota sociale, attualmente ad un livello minimo, è un dovere che ogni Socio deve
assolvere entro il 31 marzo di ogni anno, onde evitare che la gestione delle quote con
relativi solleciti e verifiche abbia un costo superiore alla stessa quota.
La quota per il 2015 è di € 25,00 e potrà essere versata tramite assegno circolare o bancario, non trasferibile, intestato a Società Italiana di Citometria oppure tramite versamento in contanti alla Segreteria oppure mediante bonifico bancario: c/c n. 4350 c/o Banca
Nazionale del Lavoro 6385 Roma Casaccia, Via Anguillarese 301 - 00123 Roma.
Coordinate bancarie IBAN: IT 04B0100503385000000004350
indicando nella causale: Cognome e Nome del Socio e quota associativa GIC: (anno).
Con l’intento di favorire i cosidetti “non strutturati” (studenti, borsisti, etc.) la quota sociale
è ridotta a € 15,00, chi si trova in questa condizione dovrà esplicitamente dichiararlo
mediante autocertificazione contestualmente all’invio della quota annuale.
Fiduciosi della tua collaborazione e partecipazione, cogliamo l’occasione per inviarti i
nostri più cari saluti.
LA SEGRETERIA
23
Tumori solidi pediatrici:
allestimento e caratterizzazione di linee tumorali primarie
per un progetto di applicazione clinica del trapianto aploidentico
di cellule staminali ematopoietiche
Comini Marta1, Bolda Federica1, Beghin Alessandra1, D'Ippolito Carmelita2, Ruggeri Loredana3,
Alberti Daniele4, Bercich Luisa5, Carella Graziella6, Porta Fulvio2, Caruso Arnaldo7,
Lanfranchi Arnalda1
U.O. Microbiologia e Virologia, Sezione di Ematologia e Coagulazione, Laboratorio Cellule Staminali,
Ospedale dei Bambini, Brescia
2U.O. Oncoematologia Pediatrica e Trapianto Midollo Osseo, Ospedale dei Bambini, Brescia
3Divisione di Ematologia ed Immunologia Clinica, Dipartimento di Medicina, Università di Perugia, Perugia
4U.O. Chirurgia Pediatrica, Ospedale dei Bambini, Brescia
5U.O. Anatomia e Istologia Patologica, Spedali Civili, Brescia
6U.O. Reumatologia e Immunologia Clinica, Spedali Civili, Brescia
7Sezione di Microbiologia, Dipartimento di Medicina Molecolare e Traslazionale, Università di Brescia, Brescia
1
Introduzione
I tumori solidi dell’età pediatrica sono patologie caratterizzate da una prognosi infausta, pur non rappresentando
un’entità numerica rilevante, hanno un impatto socialmente significativo, sia per la peculiarità del paziente, sia
per la complessità dei trattamenti somministrati.
I tumori solidi costituiscono circa il 22% di tutte le neoplasie pediatriche (Tab.1) ed escludendo il primo anno di
vita, in cui prevalgono patologie di origine genetica e
condizioni morbose perinatali, costituiscono la principale causa di morte non traumatica della prima e della
seconda infanzia.
Tab.1 - Rapporto AIRTUM 2012 •TUMORI INFANTILI, incidenza delle neoplasie pediatriche in Italia.
Le forme che esordiscono in stadio avanzato e in fase
metastatica sono definite ad alto rischio e la sopravvivenza libera da malattia (DFS), in questi casi, è inferiore
al 20%, poiché si osserva mancata responsività alle terapie standard.
I trattamenti tradizionali per i tumori solidi pediatrici
includono principalmente la chirurgia, la radioterapia e
la chemioterapia, utilizzate individualmente o in combinazione. Malgrado l’efficacia nel rallentare la progressione della malattia e nel prolungare la vita del paziente
affetto da tumore, i trattamenti standard hanno forti limiti in termini di efficacia e sicurezza.1
Alcuni tumori quali Rabdomiosarcoma, Neuroblastoma,
Sarcoma di Ewing, hanno una maggiore probabilità di
sviluppare resistenza o di recidivare.2,3,4,5,6,7
In questi pazienti un approccio standard con chemioterapia e/o radioterapia non è sufficiente per permettere la
guarigione; questo evidenzia la necessità di nuove strategie terapeutiche: nuove tecniche di trapianto e l’utilizzo
di terapie cellulari sono attualmente oggetto di intensi
studi da parte di molti gruppi internazionali e alcuni
trials clinici sono già stati intrapresi.
Il trapianto aploidentico di cellule staminali ematopoietiche, cioè il trapianto da donatore HLA-semicompatibile
potrebbe rappresentare un approccio terapeutico immunologico. Come ampiamente documentato nel caso delle
leucemie, in questo tipo di trapianto si osserva una reazione chiamata GvL (Graft versus Leukemia), cioè una
reazione delle cellule del donatore nei confronti delle
cellule leucemiche residue del ricevente.8,9,10,11,12
Studi successivi hanno dimostrato come lo stesso concetto possa essere traslato anche ai tumori solidi. Si parla in
questo caso di GvT (Graft versus Tumor).13,14
Un ruolo fondamentale nella reazione di alloreattività è
svolto dalle cellule Natural Killer (NK)15,16 del donatore.
L’effetto antileucemico esercitato dalle cellule NK è
mediato dal mismatch tra recettori KIR del donatore e
molecole HLA I del ricevente: se i linfociti NK interagiscono con cellule allogeniche, è possibile che uno o più
25
KIR17 non riconoscano il loro ligando e quindi risultino
alloreattivi; cellule NK del donatore si attiveranno così
secondo il meccanismo di MISSING SELF e porteranno
ad uccisione di cellule prive di quel ligando, cioè cellule
tumorali del ricevente.
Aspetto interessante delle cellule NK, inoltre, è il fatto di
non indurre GvHD (Graft versus Host Disease) post trapianto, cioè una reazione del trapianto contro il ricevente che rappresenta anche una delle maggiori complicanze trapiantologiche.
Il trapianto aploidentico di cellule staminali ematopoietiche,
quindi, potrebbe dimostrarsi una possibile alternativa terapeutica immunologica in tumori ad alto ed altissimo rischio.
Scopo del lavoro
Lo scopo del lavoro è stato quello di disegnare un progetto sperimentale per individuare e selezionare il
miglior donatore aploidentico da utilizzare nel trapianto
di cellule staminali come terapia alternativa in pazienti
pediatrici affetti da tumori solidi ad alto rischio
(Rabdomiosarcoma, Neuroblastoma, Sarcoma di Ewing)
e medio rischio (Tumore di Wilms).
26
Pazienti e Metodi
Il numero totale di pazienti arruolati è stato 29: 17
maschi e 12 femmine.
Alla diagnosi l’età media dei pazienti era compresa tra 0
e 16 anni (età media 5,4 anni, mediana 4 anni), ma con
circa due terzi dei pazienti aventi età inferiore ai 5 anni
(19/29 pazienti).
In base al tipo di tumore i pazienti erano suddivisi in: 8
affetti da Rabdomiosarcoma (RMS), 12 da
Neuroblastoma (NB), 3 da Sarcoma di Ewing (ES) e 6 da
Tumore di Wilms (WT) (Fig.1).
Il disegno sperimentale ha previsto l’allestimento di
linee tumorali primarie, cioè di linee tumorali allestite a
partire da tessuto neoplastico prelevato dai pazienti al
momento della biopsia o dell’asportazione di massa eseguita a fini diagnostici e terapeutici. Il materiale neoplastico così ottenuto è stato disgregato meccanicamente ed
enzimaticamente e messo in coltura in modo da ottenere
una coltura paziente e tumore specifica.
I pazienti di cui sono state allestite le colture tumorali
sono stati 26; su tutte le linee sono state eseguite analisi
di immunoistochimica con l’utilizzo di marcatori tumorali specifici per le patologie diagnosticate con l’intento
di valutare la percentuale di tumoralità. Contestualmente
è stata effettuata sulle stesse una caratterizzazione citofluorimetrica ai fini di una valutazione fenotipica. Sono
state analizzate 5 fra le linee di Rabdomiosarcoma: 3
tumorali e 2 non tumorali, 5 fra le linee di Tumore di
Wilms: 3 tumorali e 2 non tumorali, 4 fra le linee di
Neuroblastoma: 2 tumorali e 2 non tumorali, e 1 di
Sarcoma di Ewing, più 3 linee commerciali: Linea
Immortalizzata di Rabdomiosarcoma SJRH, Linea
Immortalizzata di Neuroblastoma IMR32, Linea
Fig.1 - Pazienti suddivisi in base al tipo di tumore: in blu sono
rappresentati gli 8 pazienti affetti da Rabdomiosarcoma
(RMS), in rosso i 12 pazienti affetti da Neuroblastoma (NB), in
verde i 3 pazienti affetti da Sarcoma di Ewing (ES) e in viola i
6 pazienti affetti da Tumore di Wilms (WT). L’incidenza dei
diversi tipi di tumore è espressa anche in %.
Immortalizzata di Sarcoma di Ewing SK-NEP-1, utilizzate come riferimento.
La scelta dei marcatori da inserire nel nuovo pannello
(Tab.2) si è basata su dati in letteratura.18,19,20,21,22
Sono stati scelti come controlli negativi alcuni marcatori
emopoietici, in quanto i tumori solidi non hanno origine
emopoietica e risultano quindi negativi per questo tipo di
marcatori. La negatività per tali marcatori permette,
infatti, di fare un primo grande screening tra tumori ematopoietici e non.
Sono stati poi inseriti marcatori staminali e mesenchimali per le colture in esame che spesso overesprimono marcatori di adesione normalmente espressi in cellule normali.23
È stato inserito anche un marcatore endoteliale per valutare gli aspetti di neoangiogenesi.
Tab.2 - Pannello dei marcatori utilizzati suddivisibili per tipologia: nel primo riquadro, in alto a sinistra, i marcatori emopoietici CD45, CD34, CD14, HLA-DR, CD56 e CD133 anche
marcatore di staminalità, nel secondo, i marcatori mesenchimali CD44, CD29, CD73, CD105, CD90, HLA-ABC ed infine in
basso CD31 marcatore endoteliale e CD271, CD71, MIC-A/B,
CD112, CD155, CD9, CD58, CD99, MIOGENINA marcatori
tumorali.
Infine sono stati scelti marcatori tumorali,
così definiti perché più tipicamente espressi a livello di cellule tumorali.
In seguito sono state effettuate: la tipizzazione HLA dei pazienti la cui coltura è
risultata essere neoplastica, la valutazione
dell’attività NK dei donatori dei pazienti
mancanti di un ligando secondo valutazione HLA, sia verso linee cellulari blastizzate con PHA (PhytoHemAgglutinin),
che verso le linee cellulari allestite da
tumore primario.
In 2 casi è stato eseguito il trapianto di
cellule staminali ematopoietiche mediante selezione di cellule CD34+ da prodotto
aferetico del donatore individuato, a cui è
seguita la valutazione del chimerismo post trapianto per
la quantificazione della presenza delle cellule del donatore nel ricevente.
Risultati e Discussione
L’allestimento e la valutazione immunoistochimica delle
colture primarie ha mostrato i seguenti risultati (Fig.2):
Rabdomiosarcoma: 3 su 8 delle colture (37,5%) valutate
come neoplastiche (2 con percentuale pari al 70%, 1 con
percentuale pari al 90%), 4 su 8 come non neoplastiche e
in 1 caso non si ha avuto crescita cellulare.
Neuroblastoma: 3 su 11 delle colture (27,3%) valutate
come neoplastiche (1 con percentuale pari al 40%, 1 con
percentuale pari al 80% e 1 caso in cui le cellule hanno
morfologia neoplastica ma la percentuale di tumoralità
non è valutabile), 7 su 11 non neoplastiche e in 1 caso
non si ha avuto crescita cellulare.
Sarcoma di Ewing: 1 su 1 coltura (100%) valutata come
neoplastica (con percentuale di tumoralità pari al 90%).
Tumore di Wilms: 4 su 6 delle colture (66,7%) valutate
come neoplastiche (con percentuali di tumoralità variabili tra 70% e 95%) e 2 su 6 non neoplastiche.
Dall’analisi di questi dati si vede, quindi, come la percentuale di successo per la riuscita di una coltura valutabile come neoplastica sia variabile nelle diverse linee
tumorali, ma soprattutto per i diversi tipi di tumore.
Per quanto riguarda la valutazione fenotipica effettuata
tramite analisi citofluorimetrica, i dati mostrati riguardano le linee valutate precedentemente dall’analisi immunoistochimica come neoplastiche. Da essi emerge
un’elevata espressione, riscontrabile in tutti i tipi di
tumore, di recettori normalmente rappresentati sulle cellule di tipo mesenchimale (Fig.3a). In particolare si può
osservare un’espressione elevata ed una deviazione standard ridotta per i marcatori mesenchimali CD44, CD105
e CD90. Nel caso del CD73, invece, l’espressione è più
eterogenea.
L’espressione di tali marcatori a livello di linee tumorali
va a conferma di quanto riportato in letteratura24,25: spesso si tratta di molecole di adesione che si trovano fisioLettere GIC Vol. 23, Num. 3 - Dicembre 2014
Fig. 2 - Valutazione delle colture tumorali attraverso analisi
immunoistochimica: gli istogrammi mostrano, per ogni tipo di
patologia, in arancione il numero e la percentuale di colture
valutate neoplastiche, in grigio il numero e la percentuale di
quelle non neoplastiche ed in azzurro il numero e la percentuale delle colture non valutabili per mancata crescita cellulare.
logicamente espresse sulla membrana di cellule normali
coinvolte in processi come la migrazione o l’interazione
cellula-cellula, la proliferazione o il differenziamento,
ma su cellule tumorali possono essere up-regolate e funzionare da regolatori positivi per la progressione tumorale e i processi di metastatizzazione. Quest’ultimo processo, infatti, dipende fortemente dalla motilità cellulare e
dal potenziale migratorio dipendente a sua volta proprio
dalle molecole di adesione. Si è osservato che le molecole di adesione sono coinvolte in tutti gli steps del processo metastatico.
Un aspetto interessante e visibile dalle analisi citofluorimetriche (Fig.3b) è il fatto che se si va a confrontare
l’espressione del marcatore CD44 nelle linee primarie di
Rabdomiosarcoma (RMS), Neuroblastoma (NB),
Sarcoma di Ewing (ES) e nelle linee immortalizzate di
riferimento, in tutti e tre i tipi di tumore si può osservare
una diminuzione nell’espressione del CD44 nella linea
immortalizzata. L’espressione del marcatore CD44 nella
linea immortalizzata SJRH (RMS) è pari a 59,5% valore
inferiore rispetto alle linee primarie di RMS, la cui
espressione è in media attorno al 100%; l’espressione
nella linea immortalizzata IMR-32 (NB) è pari a 79,1%
inferiore rispetto alle linee primarie di NB; la cui espressione è in media attorno al 100%, l’espressione nella
linea immortalizzata SK-NEP-1 (ES) è pari a 47,9%
inferiore rispetto alla linea primaria ES, la cui espressione è 98,6%.
Il CD44, in generale, è un marcatore espresso su cellule di
vari tipi tumorali, ma specificatamente per il
Rabdomiosarcoma e il Neuroblastoma può anche fornire
informazioni utili per predire il comportamento e la prognosi del tumore26. L’espressione di CD44, infatti, si correla in modo inversamente proporzionale con
27
Fig. 3 - Espressione dei marcatori mesenchimali nelle linee cellulari analizzate: ogni gruppo di pazienti è rappresentato in colore diverso in base al tipo di tumore sviluppato; in blu sono rappresentati i 3 pazienti RMS e con colore più scuro la linea immortalizzata SJRH
di riferimento, in rosso i 2 pazienti NB e con colore più scuro la linea immortalizzata IMR32 di riferimento, in verde il paziente ES e
con colore più scuro la linea immortalizzata SK-NEP-1 di riferimento e in viola i 3 pazienti WT.
a) Espressione dei marcatori mesenchimali CD44, CD105, CD90, CD73.
b) Confronto dell’espressione del marcatore CD44 tra linee primarie e linee immortalizzate.
l’aggressività del tumore: nei pazienti con cellule tumorali CD44 fortemente positive si ha una migliore sopravvivenza, le linee che invece mostrano più bassa espressione
per CD44 sono più aggressive e si correlano con una prognosi infausta. Dalle analisi eseguite è visibile una diminuzione nell’espressione del CD44 nella linea immortalizzata rispetto alle linee primarie dello stesso tumore.
Per quanto riguarda i marcatori emopoietici è importante mettere in evidenza la bassa espressione di CD45
(sempre inferiore a 1%). Questo dato permette di discriminare tra tumori ematologici e non: la sua mancata
espressione, permette, quindi, di caratterizzare tutte le
linee tumorali come non ematologiche.
Sempre all’interno dei marcatori emopoietici è interessante valutare l’espressione di CD56 (Fig.4), identificato
28
come marcatore emopoietico, in quanto marcatore per le
cellule NK, ma spesso presente ad alti livelli nei tessuti
tumorali. In letteratura viene spesso riportata una correlazione tra l’espressione di CD56 e la sopravvivenza
libera da malattia nel Sarcoma di Ewing: bassa o mancata espressione di CD56 si correla ad una prognosi
migliore. CD56, perciò, può essere considerato un marcatore prognostico per il ES27. Nelle linee analizzate si
evidenzia espressione di CD56 nel ES e nella linea
immortalizzata SK NEP-1 di riferimento. Nel WT i dati
mostrano lo stesso trend di espressione. I dati relativi ai
pazienti affetti da RMS, invece, mostrano molta variabilità di espressione e quelli affetti da NB bassa espressione. Le linee immortalizzate di riferimento hanno espressione molto elevata di CD56 e maggiore rispetto alle
linee primarie, a riprova del fatto che si tratta di linee
aggressive caratterizzate da una prognosi infausta.
Nell’ambito invece dei marcatori tumorali è importante
valutare i dati relativi all’espressione dei ligandi dei
recettori attivatori: CD155 e CD112, ligandi del recettore attivatorio DNAM-128, e MIC A/B, ligando per il
recettore attivatorio NKG2D. La presenza sulla superficie delle cellule target di queste molecole aumenta il processo di lisi da parte delle cellule NK. Le analisi mostrano mancata espressione di questi ligandi (Fig.5a). Questo
è sfavorevole ai fini della possibilità di lisi, ma meccanismo frequente in cellule tumorali proprio per evadere
l’immunosorveglianza. La mancata espressione non
definisce però le cellule target come insensibili alla lisi
NK mediata, perché come è noto l’attivazione delle cellule NK è sempre il risultato del reclutamento di molteplici recettori attivatori.
Fig.4 - Espressione del marcatore CD56 nelle linee cellulari analizzate: ogni gruppo di pazienti è rappresentato in colore diverso in
base al tipo di tumore sviluppato; in blu sono rappresentati i 3 pazienti RMS e con colore più scuro la linea immortalizzata SJRH di
riferimento, in rosso i 2 pazienti NB e con colore più scuro la linea immortalizzata IMR32 di riferimento, in verde il paziente ES e con
colore più scuro la linea immortalizzata SK-NEP-1 di riferimento e in viola i 3 pazienti WT.
Fig.5 - Espressione dei marcatori tumorali nelle linee cellulari analizzate: ogni gruppo di pazienti è rappresentato in colore diverso in
base al tipo di tumore sviluppato; in blu sono rappresentati i 3 pazienti RMS e con colore più scuro la linea immortalizzata SJRH di
riferimento, in rosso i 2 pazienti NB e con colore più scuro la linea immortalizzata IMR32 di riferimento, in verde il paziente ES e con
colore più scuro la linea immortalizzata SK-NEP-1 di riferimento e in viola i 3 pazienti WT.
a) Espressione dei marcatori dei ligandi dei recettori attivatori: CD155, CD112, MIC A/B.
b) Espressione dei marcatori tumorali: CD10, CD99, CD58, CD9, CD271.
Per quanto riguarda gli altri marcatori tumorali: CD10,
CD99, CD58, CD9, CD271, l’espressione è variabile da
paziente a paziente, più che da linea a linea, mentre nelle
linee immortalizzate l’espressione è più alta per tutti i
marcatori (Fig.5b). Questo può essere spiegato dal fatto
che l’espressione di determinati recettori di superficie
può rappresentare differenti stadi di maturazione e/o
evoluzione tumorale tra i vari pazienti oltre che differenti espressioni correlate a diversi tessuti e organi.
Il marcatore CD99, inserito nel pannello di analisi perché
marcatore immunoistochimico diagnostico e univoco per il
Sarcoma di Ewing, è effettivamente espresso solo in questa linea, ma solo nella linea immortalizzata SK-NEP-1.
Dopo analisi sia immunoistochimica che citofluorimetrica delle linee tumorali allestite, è stata effettuata la tipizzazione HLA degli 11 pazienti la cui coltura è stata valutata come neoplastica.
Lo scopo del nostro lavoro è stato quello di analizzare
l’alloreattività di un potenziale donatore studiandone la
capacità di killing contro la linea tumorale non solo
paziente specifica, ma anche tumore-paziente specifica.
La valutazione dell’HLA ha permesso di escludere dalla
prosecuzione dello studio tutti i
pazienti con profilo Bw4, C1,
C2 (2/11 pazienti), 5/11 pazienti sono ancora in corso di studio
e nei restanti 4 casi i pazienti
sono risultati mancanti di un
recettore: 2/11 casi missing
Bw4, 2/11 missing C1 (Tab.3).
Di questi 4 pazienti mancanti di
un ligando, sono stati effettuati
anche gli studi di citotossicità
sia su linee blastizzate con PHA
(linea tumorale paziente specifica), che sulle colture primarie
allestite (linea tumorale tumore-paziente specifica) (Tab.3). 2
pazienti sono stati avviati al trapianto, in quanto non responsivi alle terapie farmacologiche
standard di aggressione al
tumore e quindi fortemente
indicati dal punto di vista terapeutico.
Il trapianto aploidentico è stato
Tab.3 - Risultati relativi alle tipizzazioni HLA e alle analisi di citotossicità eseguite nei pazienti eseguito dopo specifico trattamancanti di un ligando (missing Bw4 o missing C1).
29
Tab. 4 - Dati relativi all’esecuzione del trapianto e al monitoraggio dei pazienti post trapianto. I dati di chimerismo sono espressi in
% di cellule del donatore attecchite.
mento chemioterapico dei pazienti e raggiungimento di
una condizione di remissione completa o parziale. La
preparazione del graft è stata effettuata mediante la raccolta di cellule staminali ematopoietiche CD34+ da
mobilizzazione aferetica, in relazione al peso corporeo
del ricevente. Il razionale è stato quello di selezionare
cellule staminali CD34+ come precursori di sottopopolazioni emopoietiche che si differenzieranno in vivo nella
nicchia stromale anche come cellule NK effettrici.
Nella Tab.4 è possibile prendere in esame i dati relativi
all’esecuzione del trapianto e al follow up dei 2 pazienti
avviati alla terapia trapiantologica.
Il processo trapiantologico ha permesso, comunque, di
offrire una sopravvivenza di 7 mesi per il PZ.3 e 3 anni
per il PZ.4 rispetto ad un atteso di 1/2 mesi per entrambi.
Nella Tab.4 sono riportati anche i dati di valutazione di
chimerismo effettuati con metodica molecolare utilizzando per l’amplificazione del DNA un kit commerciale
(AmpFlSTR® Identifiler® Plus PCR Amplification Kit);
si può osservare come la prima valutazione effettuata a
15 gg dal trapianto mostri un attecchimento del 100%
per entrambi i pazienti, il secondo dato invece è l’ultimo
di una serie di analisi di chimerismo effettuate a step successivi e mostra un risultato di chimerismo misto che
preludeva o confermava una recidiva di malattia.
30
Conclusione
In conclusione il nostro lavoro ha voluto mostrare come
le cellule NK alloreattive possano rappresentare una strategia terapeutica nei tumori solidi infantili grazie all’effetto Graft-versus-Tumor, già documentato in letteratura
come GvL per le leucemie. In tale strategia terapeutica
identificare un donatore aploidentico alloreattivo è fondamentale; per la scelta dello stesso è essenziale disporre di un modello in vitro che predica la capacità di lisi
delle cellule NK nei confronti delle cellule neoplastiche
del ricevente. Tale modello prevede l’allestimento di colture primarie tumore e paziente specifiche e la loro caratterizzazione non solo attraverso valutazioni immunoistochimiche, ma anche citofluorimetriche. La citofluorimetria, infatti, ha permesso di caratterizzare le linee cellulaATTIVITÀ SCIENTIFICA
ri da noi allestite e derivate da tumore in base al loro
immunofenotipo evidenziando eterogeneità interindividuale oltre che intraindividuale. I tumori facenti parte
dello studio rappresentano un gruppo relativamente raro
ed eterogeneo di neoplasie non-ematologiche e richiedono procedure multiple per il loro screening diagnostico e
la loro classificazione. Essi necessitano perciò anche
della citofluorimetria multiparametrica, utile tecnica di
caratterizzazione complementare alle istopatologie e alle
altre procedure diagnostiche convenzionali. Anche se
ancora di difficile applicazione per questo scopo a causa
della difficoltà di ottenere linee tumorali da singolo clone
e a causa della scarsa disponibilità di marcatori tumore
specifici, il nostro lavoro mette in evidenza un suo contributo nell’arricchire le informazioni ottenibili da un
modello in vitro per poter meglio mimare quello che
potrebbe avvenire in vivo.
L’obiettivo finale è, infatti, migliorare le opportunità
terapeutiche, i criteri di scelta di possibili donatori e le
possibili predizioni di efficacia trapiantologica.
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31

Dicembre 2014 - Società Italiana di Citometria

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