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Universidad Autónoma de Madrid Facultad de Medicina
Departamento de Bioquímica
Docetaxel Response Characterization and Identification of Predictive Biomarkers in Metastatic Castration Resistant Prostate Cancer
Doctoral Thesis Mª Paz Nombela Blanco
Madrid
2019
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Universidad Autónoma de Madrid Facultad de Medicina
Departamento de Bioquímica
Docetaxel Response Characterization and Identification of Predictive Biomarkers in Metastatic Castration Resistant Prostate Cancer
Mª Paz Nombela Blanco Licenciada en Biología
Thesis Directors David Olmos Hidalgo Pedro Pablo López Casas
Spanish National Cancer Research Center (CNIO)
Madrid
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CERTIFICADO DE LOS DIRECTORES DE LA TESIS
El doctorando Mª Paz Nombela Blanco ha realizado su trabajo de Tesis Doctoral titulado Docetaxel Response Characterization and Identification of Predictive Biomarkers in Metastatic Castration Resistant Prostate Cancer en el laboratorio de Investigación Clínica en Cáncer de Próstata en el Centro Nacional de Investigaciones Oncológicas. Dicha tesis se ha realizado bajo la dirección del Dr. David Olmos Hidalgo y del Dr. Pedro Pablo López Casas, considerando que dicho trabajo reúne las condiciones necesarias para la obtención del grado de Doctor.
DIRECTOR
Dr. David Olmos Hidalgo
CO-DIRECTOR
Dr. Pedro Pablo López Casas
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“The state of mind which enables a man to do work of this kind... is akin to that of the religious worshipper or the lover; the daily effort comes from no deliberate intention
or program, but straight from the heart ” Albert Einstein
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A GRADECIMIENTOS
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Quizá este el apartado más satisfactorio de escribir dentro de una Tesis Doctoral, lo que no quiere decir que sea el más sencillo, ya que requiere hacer un ejercicio de memoria para tener presente a la cantidad de personas que me han dado su tiempo, conocimiento y apoyo para poder dar este paso en mi formación científica, pues al final esta tesis no es “mi logro” sino que es mérito conseguido y compartido con todos aquellos que en una media u otra me han acompañado a lo largo del camino para llegar a la meta.
En primer lugar agradecer, a mi director de tesis, David Olmos, la oportunidad de trabajar en su laboratorio. Gracias a la confianza que depositaron en mí tanto David como Elena he podido cumplir mi sueño. Ahora echo la vista atrás y recuerdo los inicios de esta historia, la ilusión con la que empezasteis a montar un laboratorio de la nada, con muchas dificultades (hemos pasado por tres laboratorios), pero finalmente habéis conseguido crear un grupo de investigación de gran proyección. Mi más sincera enhorabuena y gracias por haberme dejado formar parte de ello.
A mi codirector de tesis, Pedro, llegaste tarde a este barco pero a tiempo para tendernos la mano cuando lo veíamos muy negro. Gracias por haber formado parte de este proyecto, por los consejos y directrices que desde la experiencia nos has dado.
También por haber sido en muchas ocasiones mediador entre el Director y la doctoranda, además de conseguir que las reuniones fueran mucho más amenas, y es que la risa es la mejor terapia para sofocar las tensiones que surgen del estrés de una tesis.
Agradecer también a mis compañeras/os de mi grupo de investigación por su esfuerzo y su colaboración, sobre todo los últimos meses por los miles de favores que me habéis hecho para poder completar este manuscrito.
Dicen que sólo alguien que pasa por lo mismo que tú es capaz de entenderte y creo que ha sido en esta etapa de mi vida cuándo más sentido ha tenido esa frase. ¡¡Ay pollito!! ni 5000km han podido distanciarnos. Ylenia, gracias por compartir tus inquietudes científicas y dejarme aprender contigo, por darme ese soplo de confianza cuando yo la había perdido, por tenderme la mano cuando estaba en el suelo y por
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sacarme siempre una sonrisa, pues al final la tesis no lo es todo, hay que aspirar a ser feliz. Muchísimas gracias por acompañarme en este camino (y en lo que está por sin ti no hubiera sido lo mismo, te deseo lo mejor. Ya sabes, “con esfuerzo todo se consigue” antes o después todo llega, paciencia.
Agradecer a todas esas personas que aunque no formen parte de mi laboratorio, me han ayudado y facilitado mucho la realización de este trabajo. En concreto, gracias al equipo del animalario del CNIO, Isabel Blanco y Gema Luque, siempre dispuestas a ayudar, y especialmente a Flor Díaz, has sido muchas veces mis ojos y mis manos en el Barrera II, gracias por la paciencia que has tenido conmigo. Al servicio de citometría del CNB, a Carmen y Sara por vuestro apoyo y por la seguridad y tranquilidad que me habéis transmitido, porque conseguimos hacer algo sencillo de lo que parecía imposible. A Lolo, porque aun en momentos complicados no me has negado tu ayuda. A todas esas personas que con su trabajo o simplemente con su preocupación me han demostrado todo su cariño en estos años.
A Begoña Colás, ya que fue gracias a su ofrecimiento como descubrí mi gran pasión por la investigación y donde pude conocer a las dos personas responsables de decidiera embaucarme en esta aventura. Ariel y Raúl, aunque a veces fuisteis duros conmigo (todavía recuerdo los exámenes semanales de Ariel…), cimentasteis para que a nivel científico me haya convertido en quien soy. Aunque a veces haya vacilado por el camino nunca lo he olvidado: “Ten clara tu hipótesis” y “no seas china de laboratorio”
Agradecer a mi familia por su incondicional estímulo y apoyo. A mis padres porque de no ser por ellos yo no estaría hoy aquí, por su esfuerzo, dedicación y entrega, por demostrar que con poco se pueden hacer cosas muy grandes y que sólo con trabajo se consiguen los sueños. Sé que pase lo que pase siempre vais a estar ahí. A mis hermanos, Carlos, llegaste con 9 años de diferencia y te convertiste el juguete de una niña. Mi compañero de habitación, todavía hoy me despierto por las noches y pienso inconsciente que estás en la cama debajo de la mía, así, como eres tú, incondicional.
Fran, parece que desde que nací estamos compitiendo, terminamos el instituto a la vez, empezamos y termínanos la universidad a la vez, y no conformes con eso
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decidimos que era una buenísima idea sacarnos el doctorado y cómo no, teníamos que empezarlo a la vez, y bueno, aunque te has adelantado, siempre podremos decir que la familia Nombela Blanco incorporó dos doctores en 2019 (mes arriba o mes a bajo). No me olvido del otro miembro la familia, desde luego el más querido por todos con diferencia, Cuca, los días de estudio de la carrera hubieran sido muchísimo más aburridos sin tu carita peluda apoyada en mis apuntes y tus ojitos reclamando atención.
Os quiero familia.
A mis abuelos, que aunque ya no estén aquí sé que haya donde estén estarán orgullosos de todos mis logros. No os olvido.
Por último, agradecer a Álvaro. Llegaste en el momento justo para que no se me pasara por la cabeza que era una buenísima idea salir de España a buscarme la vida y no conforme con eso has sufrido mano a mano las etapas más duras de mi doctorado. Dices que no tienes paciencia, pero a veces creo que tienes muchísima más de la que piensas.
Siento si en estos últimos meses mi prioridad haya sido terminar “nuestra tesis” dejando de lado otras muchas cosas también importantes. En breve empezamos una nueva etapa en nuestra vida, un nuevo reto, un salto al vacío sin paracaídas a lo desconocido y aunque pueda dar miedo, sé que de la mano conseguiremos llegar hasta el final, ¡no me sueltes!, yo no lo haré. Gracias por quererme con mis defectos y virtudes, con mi pasado, presente y futuro. Te quiero.
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S UMMARY
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Prostate cancer is the most common malignancy in men and the cause of highest mortality in developed countries. Although radical prostatectomy and radiotherapy are the established treatments for localized disease, androgen deprivation therapy represents the mainstay for the treatment of locally advanced, recurrent or metastatic prostate cancer. Chemical castration is temporarily effective in these patients, but eventually 30% of them progress and develop resistance to castration (CRPC) that can lead to the emergence of new metastases. The first line Docetaxel treatment has shown a survival benefit in patients with mCRPC, but unfortunately, part of them end up developing resistance to treatment.
The search for new response biomarkers for treatment with DOC is one of the main objectives of this doctoral thesis, using circulating tumor cells (CTCs) as a surrogate marker of the prostate tumor. In our case, we detected in CTCs the presence of two markers, related to the activity of the DOC, to define its correlation with the response:
a mitosis arrest biomarker, phospho-histone-H3 (pHH3), and apoptosis biomarker, cytokeratin M30 (CK-M30).
Preclinical models generated from metastatic prostate cancer, by orthotopic injection of human tumor cells in NOD Scid Gamma mice, have faithfully reproduced the clinical progression of patients with mCRPC and have been key to identifying and validating biomarkers in CTCs, as well as to understand the biology of prostate cancer.
On the other hand, the detection and counting of CTCs has been shown to be a sensitive marker to control the disease status during the response to treatment with DOC. In addition, we have shown that patients who are more likely to obtain a clinical benefit from DOC treatment can be pre-selected by detecting an increase in CTC pHH3 + in the first treatment cycles.
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R ESUMEN
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El cáncer de próstata es el tipo de tumor más común en hombres y el causante de la mayor tasa de mortalidad en países desarrollados. Aunque la prostatectomía radical y la radioterapia son los tratamientos establecidos para enfermedad localizada, la terapia de privación de andrógenos representa el pilar para el manejo del cáncer de próstata localmente avanzado, recurrente o metastásico. A pesar de que la castración química es temporalmente eficaz en estos pacientes, eventualmente un 30% de ellos progresan y desarrollar resistencia a la castración (CRPC) que puede derivar en la aparición de nuevas metástasis. El tratamiento con Docetaxel (DOC) en primera línea ha demostrado un beneficio en la supervivencia de los pacientes con mCRPC, pero desafortunadamente, parte de ellos acaban desarrollando resistencia al tratamiento.
La búsqueda de nuevos biomarcadores de respuesta para el tratamiento con DOC es uno de los principales objetivos de esta tesis doctoral, utilizando para ello las células tumorales circulantes (CTCs) como marcador subrogado del tumor de próstata. En nuestro caso, hemos detectado en CTCs la presencia de dos marcadores relacionados con la actividad del DOC para definir su correlación con la respuesta: un marcador de arresto en mitosis, fosfo-histona-H3 (pHH3), y un marcador de apoptosis citoqueratina M30 (CK-M30).
Los modelos preclínicos de cáncer de próstata metastásico generados mediante inyección ortotópica células tumorales humanas en ratones NOD Scid Gamma, han reproducido fidedignamente la progresión clínica de los pacientes con mCRPC y han sido claves en para identificar y validar en CTCs biomarcadores, así como para entender la biología de cáncer de próstata. Por otro lado, la detección y recuento de CTCs ha demostrado ser un marcador sensible en la monitorización del estado de la enfermedad durante la respuesta al tratamiento con DOC. Además, hemos demostrado que los pacientes con mayor probabilidad de obtener un beneficio clínico del tratamiento con DOC pueden preseleccionarse detectando un aumento de CTC pHH3 + en los primeros ciclos de tratamiento.
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T ABLE OF C ONTENTS
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AGRADECIMIENTOS ... 7 SUMMARY ... 13 RESUMEN ... 17 TABLE OF CONTENTS ... 21 ABBREVIATIONS ... 25 INTRODUCTION ... 29
1. OVERVIEW AND CLINICAL ASPECTS OF PROSTATE CANCER ... 31 1.1. Prostate anatomy and physiology ... 31 1.2. Epidemiology ... 31 1.3. Risk factors ... 32 1.4. Natural history of prostate cancer disease ... 33 1.5. Treatment ... 34 2. METASTASIS CASTRATION RESISTANT PROSTATE CANCER ... 35 2.1. Definition ... 35 2.2. Prognosis and predictive biomarkers in mCRPC ... 36 2.3. Treatment options for mCRPC patients ... 38 3. CIRCULATING TUMOR CELLS (CTCS). ... 40 3.1. Background ... 40 3.2. CTCs in prostate cancer ... 41 3.3. Isolation and detection techniques ... 43 3.4. CTCs as pharmacodynamics biomarkers in PCa... 44 4. TAXANES ... 45 4.1. Definition and action mechanism ... 45 4.2. Pharmacodynamics biomarkers to DOC therapy ... 46 4.2.1. Phospo-hitone H3 (Ser10) as a mitosis arrest biomarker ... 47 4.2.2. Cytokeratin M30 as apoptosis biomarker ... 47 4.3. Docetaxel-Resistant PCa ... 48 5. PROSTATE CANCER MOUSE MODELS ... 49
OBJETIVES ... 51 OBJETIVOS... 55 MATERIALS AND METHODS ... 59
1. CELL CULTURE ... 61 1.1. Prostate cancer cell lines ... 61 1.2. Transfection luciferase vector... 61 2. MICE STUDIES ... 62 2.1. Regulatory and ethics ... 62 2.2. Orthotopic Murine Models of Human Prostate Cancer Metastasis ... 62 2.3. Bioluminescence Images ... 64 2.4. Docetaxel treatment ... 64 3. HISTOPATHOLOGY AND IMMUNOHISTOCHEMISTRY TECHNIQUES ... 65 3.1. Hematoxylin and eosin paraffin sections staining ... 65 3.2. pHH3 immunohistochemistry (IHC) and ALU sequences in situ hybridization (ISH) ... 66 4. PROTEIN ANALYSIS ... 66 4.1. Protein extraction and quantification ... 66 4.2. Western Blot ... 67 5. PROCESSING OF MOUSE BLOOD SAMPLES AND CTCS ANALYSIS ... 67 5.1. Human CTCs isolation from mouse blood ... 67
5.2. Quantification and molecular characterization of human CTCs by Flow Cytometry ... 68
6. EXPLORATORY CLINICAL TRIAL IN MCRPC PATIENTS ... 68 6.1. Study design and patient inclusion ... 68 6.2. Blood samples and CTCs analysis ... 71 6.3. Statistical analysis ... 73
RESULTS ... 75
1. METASTATIC PCA MOUSE MODELS ... 77 1.1. Development and monitorization of metastatic PCa mouse models ... 77
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1.2. Characterization of human PCa orthotopic mouse models... 79 1.2.1. Dissemination pattern of human PCa cells in NSG mice ... 79 1.2.2. Human CTCs isolation from mouse blood sample ... 83 2. DOCETAXEL TREATMENT AND BIOMARKER RESPONSE ... 85
2.1. Sensitivity and effectiveness of DOC treatment in PC3-LUC orthotopic mouse model .... 85
2.2. Detection of phamacodinamic biomarker to DOC treatment in CTCs of PC3-LUC
orthotopic xenograft mouse model. ... 87 3. DOCETAXEL TREATMENT IN MCRPC PATIENTS. ... 92 3.1. Patient characteristics and DOC treatment efficacy ... 92 3.2. Biomarker response ... 98
DISCUSION ... 103
1. HUMAN PCA ORTHOTOPIC MOUSE MODELS THEIR USE IN THE STUDY OF THE EFFECTS UPON DOC TREATMENT OF PHH3 AS PHARMACODYNAMICS RESPONSE BIOMARKER IN CTCS ... 106 2. CTC QUANTIFICATION AND ITS USE AS A PREDICTIVE MARKER OF DOC RESPONSE IN MCRPC PATIENTS ... 110 3. PHH3 AS A PHARMACODYNAMIC RESPONSE BIOMARKER OF DOC TREATMENT ... 112
CONCLUSIONS ... 113 CONCLUSIONES ... 113 REFERENCES ... 113
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A BBREVIATIONS
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ADT Androgen Deprivation Therapy
ALP Alkaline phosphatase
APC Allophycocyanin
APCCC Advanced Prostate Cancer Consensus Conference
AR Androgen receltor
AR-V7 Androgen receptor-V7
ATCC American Type Culture Collection
BLI Bioluminescent images
BRCA1 Breast cancer type 1
BRCA2 Breast cancer type 2
BSA Bovine serum albumin protein
CD45 Leukocyte common antigen
CEyBA Ethics Committee from ISCIII
CK Cytoqueratin
CK-M30 Cytokeratin M30
CRPC Castration Resistant Prostate Cancer
CTC Circulating tumor cells
DAPI 4′,6-diamidino-2-phenylindole
DEP Dielectrophoresis
DOC Docetaxel
DPX Distyrene Plasticizer Xylene mounting medium EBRT External beam Radiation Therapy
ECOG Eastern Cooperative Oncology Group EDTA Ethylenediaminetetraacetic acid EpCAM Epithelial cell adhesion molecule
ERG ETS erythroblastosis virus E26 oncogene homolog FACS Fluorescence-Activated Cell Sorting
FBS Fetal bovine serum
FDA Food and Drug Administration
FFPE Formalin-fixed paraffin-embedded FISH Fluorescent in situ hybridisation
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FITC Isothiocyanate
GEM Genetic engineering mouse models
GnRH Gonadotropin-releasing hormone
H&E Hematoxilina-eosina
HLA Human leukocyte antigen
IHC Immunohistochemistry
ISH In situ hybridization
IVIS In vivo imaging system
LDH Lactate Dehydrogenase
LUC Luciferase
mCRPC Metastatic Castration Resistant Prostate Cancer
MTS Metastasis
NCCN National Comprehensive Cancer Network
NGS Next Generation Sequencing
NLR Neutrophil-to-lymphocyte ratio
NSG Nod Scid Gamma mice
OS Overall Survival
PBMC Peripheral blood mononuclear cells
PBS Phosphate buffered saline
PCa Prostate cancer
PCWG2 Prostate Cancer Working Group
PD Pharmacodynamics
PDX Patient-derived xenografts
PE Phycoerythrin
PEI Polyethylenimine
PET-CT Positron Emission Tomography / Computed Tomography
PFS Progression free survival
pHH3 Phospo-histone 3 (Ser10)
PSA Prostate specific antigen
PSMA Prostate-specific membrane antigen+
RBC Red blood cells
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ROI Region of interest
RT-PCR Reverse transcription polymerase chain reaction TMPRSS2 Transmembrane protease serine 2
TTPP Time to PSA progression
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I NTRODUCTION
31 1. Overview and Clinical aspects of Prostate cancer
1.1. Prostate anatomy and physiology
The prostate is part of male reproductive and urinary system, it is small muscular gland which is located deep inside pelvis cavity, below the bladder and in front of the rectum and wraps around the upper part of the urethra. The size of the prostate changes with age; in younger men it is about the size of a walnut, but it can be much larger in older men (Fall et al., 2009). The main function of this gland is to make seminal fluid, the liquid in semen that protects, supports, and helps transport sperm.
Anatomically, the human prostate is a single structure divided into several distinct lobes that make up the structure of this organ: the anterior lobe, the median lobe, the lateral lobes (left and right lobes), and the posterior lobe (Fig 1A). In contrast, the mouse prostate is not merged into one compact anatomical structure (Oliveira et al., 2016). It comprises four paired lobes situated circumferentially around the urethra, immediately caudal to the urinary bladder, namely, anterior, dorsal, lateral, and ventral prostate (Fig 1B).
Figure 1: Prostate anatomy: Human prostate anatomy (A) and mouse prostate anatomy (B). SV: seminal vesicles, AP: anterior prostate, LP: lateral prostate, DP: dorsal prostate, VP: ventral prostate, U: urethra.
1.2. Epidemiology
Prostate cancer (PCa) is the second most common malignancy in men and the major cause of mortality in developed countries. Every year, 900.000 men are diagnosed with
A) B)
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the disease, which is responsible for 250.000 deaths annually, besides in Spain represents a 21% of new tumor cases in male population (Fig 2).
Therefore, the increase in the cases of this disease has made it a global health problem. This increasing in the incidence has been influencing by the efforts to find early detection tools, an example of this fact were when the prostate specific antigen (PSA) test were included like screening in the clinical practice, that promoted a dramatically increase in the number of new cases (Haas et al, 2008). Its incidence differs between countries due to coverage of PSA screening.
Figure 2: Ten leading cancer types for the estimated new cancer cases and deaths by sex, United States, 2016.
1.3. Risk factors
Although it had been proposed several causes that predispose to the development of PCa, the main risk factors that have been established are the principal risk factors that definitely established are (Rawla et al., 2019):
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Age: PCa is rare in men younger than 40, but the chance of having prostate cancer rises rapidly after age 50. About 6 in 10 cases of prostate cancer are found in men older than 65 (Bray et al., 2018).
Race or ethnicity: occurs more often in African-American men and in Caribbean men of African ancestry than in men of other races. African-American men are also more than twice as likely to die of prostate cancer as white men (Okobia et al., 2011). Prostate cancer occurs less often in Asian-American and Hispanic/Latino men than in non-Hispanic whites. The reasons for this racial and ethnic deference are not clear.
Family history: PCa seems to run in some families that support the possible implication of genetic factor in the development of the disease. In fact, several inherited genes changes seem to raise PCa risk, but the probably account for only a small percentage of cases overall. For example, inherited mutations of the BRCA1 or BRCA2 genes raise the risk of breast and ovarian cancers in some families, mutations in these genes (especially in BRCA2) may also increase prostate cancer risk in some men (Castro et al., 2013).
Men with Lynch syndrome a condition caused by inherited gene changes, have an increased risk for a number of cancers, including prostate cancer (Kerr et al., 2016).
1.4. Natural history of prostate cancer disease
Fortunately, most of patients are diagnosed with localized disease. But, despite of excellent results achieved with surgery and radiotherapy unfortunately approximately 30% of cases the tumor will recur presenting biochemical progression. In these patients, androgen deprivation therapy (ADT) is initiated, either continuously or intermittently.
The vast majority of those patients will respond with decreases in PSA levels and any signs of tumor burden (Heidenreich et al., 2014).
Eventually, however, most prostate tumors will become refractory to androgen deprivation, in which the selection pressure will ultimately result in patients developing the status called castration-resistant prostate cancer (CRPC), and some of those will progress to this stage sooner than others. In the patients with CRPC phenotype without
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radiographically detectable metastases, historically it has been recommended ADT secondary therapies, such as anti-androgens, adrenal enzyme inhibitor or estrogen therapy ( Samson et al., 2002; Loblaw et al., 2007)
In some cases, patients develop radiolgraphically evidence of increased tumor burden, metastasis (mCRPC) or other clinical signs of disease progression. Despite recent therapeutic advances, this aggressive form of the disease remains lethal in most of case. The guidelines of the National Comprehensive Cancer Network (NCCN) recommend chemotherapy with docetaxel (DOC), since it was the first chemotherapy that demonstrated a survival benefit in men with mCRPC. However, half of patients do not respond to therapy or, even patients who initially respond will ultimately develop resistance, these patients will require treatment with additional therapies (Petrylak et al., 2004, Tannock et al., 2004). Currently, a number of novel treatment modalities have been proposed and emerging therapies, such as immunotherapy, that offering a potential survival benefit post-DOC (Drake et al., 2014) (Fig 3).
Figure 3: Natural history of PCa disease.
1.5. Treatment
Treatment for prostate cancer differs from one patient to another and is depending on the type and stage of cancer. Local treatments are indicated for patients with tumors in a specific and limited area of the body, these treatments may
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get rid of the cancer completely. In contrast, if the tumor has spread and disseminated outside the prostate cancer gland to other body parts, thus the systemic treatments are the most indicated in this case. The most common treatment options for prostate cancer are summarize in Table 1.
Table 1: Prostate Cancer treatment options
Local Treatments
Watchful waiting o active surveillance Radical Prostatectomy
External beam Radiation Therapy (EBRT) Brachytherapy
Systemic Treatments
Androgen Deprivation Therapies (ADT) Chemotherapy
Immuntherapy
2. Metastasis Castration Resistant Prostate Cancer 2.1. Definition
CRPC refers to the continuous progression of PCa following ADT, in which approximately 90% of patients develop metastases, mainly in the skeleton. In recent years, the definition of castration resistance has changed. With the emergence of novel CRPC therapy, it is important to determine the exact definition of castration resistance.
In March 2015, St. Gallen gathered 41 experts in the field from 17 countries and regions around the world, and held the first international consensus conference of the Advanced Prostate Cancer Consensus Conference (APCCC) (Gillessen et al., 2016). It was agreed that the diagnosis of CRPC should meet the following two conditions:
The serum testosterone level of the castrated is <1.7 nmol/l.
Biochemical progression: PSA expression levels have increased twice in a row from an interval of 1 week or >3 consecutive measurements with the lowest value increased >50% and >2 g/l, and ≥2 increases in novel lesions based on bone scanning or soft tissue lesions with the corresponding evaluation criteria of the solid tumor.
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Currently, not only is the progression of symptoms sufficient to diagnose CRPC. In recent decades, knowledge of the biology of PCa and the underlying mechanisms of resistance to disease has increased and resulted in improvements in the treatment of advanced PCa, with the emergence of several new therapies that prolong life.
Therefore, establish an appropriate treatment guide is important for maximizing clinical benefit in these patients.
2.2. Prognosis and predictive biomarkers in mCRPC
Advances in technology aimed at genomic, transcriptomic and metabolomic analysis have led to the discovery a large number of new biomarkers that may be utilized in the prediction, prognosis and response to therapy in PCa. Below, it is summarized the use of biomarkers in current clinical practice, its advantages and limitations, and possible future considerations for its use:
2.2.1. Prognostic factors
Prognostic factors have been developed to predict the overall survival in clinical practice, in turn, they have been used as an eligibility criterion in clinical trials to classify patients in risk groups based on a validated cut-off points for clinical trials in mCRPC. Over the past years, databases from large phase 3 trials have been of value to develop several prognostic nomograms (Armstrong et al., 2007, Scher et al., 2008, Scher et al., 2011). The factors included in these nomograms are: performance status, the presence of visceral, nodal and bone pattern of spread and number of metastatic sites, clinically significant pain, PSA doubling time, baseline PSA, tumor grade, and hemoglobin (to detect anemia), lactate dehydrogenase (metabolic indicator of cell turnover and cancer aggression), albumin (determines nutritional status), and alkaline phosphatase (determines the burden of bone metastases) (Dancey et al., 2010).
Furthermore, an emerging and readily available biomarker in mCRPC and other tumor types is the neutrophil-to-lymphocyte ratio (NLR). NLR, an inflammation marker, was associated with clinical outcome in several malignancies such as hepatocellular, gastric, renal cell, colorectal, and prostate cancer (Templeton et al.,
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2014). This marker was also explored for predictive properties (van Soest et al., 2015b) and several studies have showed that it could be a biomarker of response to Androgen Receptor (AR) targeted agents or chemotherapy ( Leibowitz-Amit et al., 2014; Lorente et al., 2015).
2.2.2. Circulating tumor cell (CTC) enumeration and characterization
CTCs count from whole blood has been demonstrated to be prognostic marker of overall survival in many tumor types including mCRPC. As an example, the finding of five or more CTCs before the start of chemotherapy is associated with a lower operating system (Armstrong et al., 2007); on the contrary, a fall in CTCs below five has been associated with an improvement in overall survival, similar to the benefit seen with a substantial decrease in PSA or a partial radiographic response (de Bono et al., 2008, Sonpavde et al., 2011).
However, CTCs characterization reveal their potential value and their use in liquid biopsies. In these context, de expression in CTCs of Androgen receptor-V7 (AR-V7) is a splice variant of the AR which lacks the ligand-binding domain, and remains constitutively active in the absence of ligand. The presence of AR-V7 mRNA in the CTCs of the blood of men with CRPC is associated with a lack of response to enzalutamide or abiraterone, but it is not associated with any difference in response to taxane chemotherapy ( Antonarakis et al., 2014; Antonarakis et al., 2015; Onstenk et al., 2015;
Scher et al., 2016). Taken together, AR-V7 expression in CTCs is a promising biomarker that might facilitate future treatment selection in mCRPC.
2.2.3. Genomic markers
The fusion of ERG, a protooncogene ETS family, TMPRSS2 was first reported in 2005 and appears to be very specific to PCa, with a positive predictive value of 94%. A fusion with the 5′ untranslated region of the androgen regulated gene TMPRSS2 enables ERG overexpression (Tomlins et al., 2005). Although, the prognostic implications of TMPRSS2-ERG gene fusion detected in CTCs has been investigated in several studies of men with mCRPC, conflicting results have been obtained. Attard et al. reported an
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association between ERG rearrangements and PSA response in men treated with abiraterone in samples of tumors that received or not previous treatment and CTCs.
this study, 80% of men who had a ≥90% PSA decrease showed an ERG rearrangement, whereas 32% of men who have a ˂90% PSA decrease showed ERG rearrangement (Attard et al., 2009c).
The TMPRSS2-ERG rearrangement has also been studied as a pharmacodinamic biomaker. Danila showed that the measure of the fusion in CTCs did not predict to abiraterone response in CRPC patients (Danila et al., 2011). However, in men treated with DOC, the presence of TMPRSS2-ERG gene fusion determined in whole blood was associated with worse outcomes (Reig et al., 2016). Furthermore, Taris found that ERG expression is also associated with better response to androgen suppression in mCRPC (Taris et al., 2014).
In recent years, several publications have identified numerous mutations that are characterized in detail in metastatic biopsies of men with mCRPC (Robinson et al., 2015). One of the most exciting findings has been the detection of germline or somatic alterations that involve the DNA damage repair pathway, such as BRCA1, BRCA2 and ATM among others (Mateo et al., 2017, Castro et al., 2019). PARP inhibitors was evaluated in a phase 2 trial in which it was demonstrated response in mCRPC patients with defects in DNA repair genes (Mateo et al., 2015, Nombela et al., 2019).
These results demonstrate that specific genomic aberrations detected by next generation sequencing is feasible and can provide an effective personalized treatment approach for mCRPC.
2.3. Treatment options for mCRPC patients
Androgen deprivation therapy (ADT) is considered the primary approach to the treatment of advanced and metastatic prostate cancer or for the disease that has recurred after primary treatment (surgery or radiotherapy). Since androgens are strongly associated with the tumorigenesis of prostate cancer, the hormonal therapy
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is responsible for blocking the production or mechanism of action of these hormones (Pagliarulo et al., 2012).
Today, several different ADT can be accomplished using bilateral orchiectomy (surgical castration) or GnRH agonist therapy (inhibits testosterone synthesis from testes due to reduced amount of luteinizing hormone (LH), antiandrogen therapy (inhibits AR activation by preventing the binding of testosterone and DHT to AR), and maximum androgen blockage (MAB) (combined inhibition using both GnRH and anti- androgens) (Nguyen and Pastuszak, 2016). Overall, endocrine therapy is initially highly effective and prostate cancer patients respond initially to the hormonal blockade treatment; however, the suppression of testosterone offers control of the disease only for an average of 18 to 36 months before the disease progresses and develop the castration-resistant phase (Petrylak et al., 2004, Lam et al., 2006).
Although curative treatment or sequential therapy strategies in mCRPC have not yet been achieved or are not clear, multiple therapeutic advances have been made for these patients. In 2004, the Food and Drug Administration (FDA) recognized the chemotherapy with DOC as a first-line treatment in mCRPC, based on the data reported in TAX327 and SWOG 99-16 phase 3 clinical trials in which treatment with DOC improved the median overall survival (Tannock et al., 2004, Petrylak et al., 2004, Berthold et al., 2008). However, responses to DOC are not durable and clinical resistance eventually emerges, even in patients who initially respond to therapy. It is these patients who require an additional treatment and therapeutic options. Resistance to DOC is a significant clinical problem (Seruga and Tannock, 2011).
Although, the current treatment regime for CRPC consists primarily of chemotherapy with DOC, but other agents are also FDA approved for the treatment of mCRPC:
Cabazitaxel: another taxane that has greater suppression of microtubule dynamics, faster drug abortion, and better intracellular retention compared with DOC, and has demonstrated activity against docetaxel-resistant mCRPC cell lines (Vrignaud et al., 2013, Azarenko et al., 2014). The efficacy of cabazitaxel plus prednisone in patients with mCRPC previously treated with DOC was shown in the TROPIC trial, where
40
achieved and improvement in overall survival up to 2.4 months (de Bono et al., 2010).
Abidaterone acetate: small molecule inhibitor of cytochrome P17, which catalysis two key reactions involved in androgen biosynthesis (Attard et al., 2009b).
Abiraterone demonstrated activity in mCRPC patients prior to (COU-AA-301 trial)(de Bono et al., 2011) and after DOC administration (COU-AA-302.1 trial)(Ryan et al., 2013).
Enzalutamide: inhibits the nuclear translocation of AR, DNA binding, and coactivator recruitment (Quintela et al., 2015). Enzalutamide was approved by the FDA in the post-DOC setting based on the AFFIRM trial (Scher et al., 2012) and was subsequently approved for first-line treatment based on data from the PREVAIL trial (Beer et al., 2014).
Sipuleucel-T: immunotherapeutic. Phase III Immunotherapy for Prostate Adenocarcinoma Treatment (IMPACT) trial in patients with asymptomatic or minimally symptomatic metastatic CRPC, the treatment with sipuleucel-T demonstrated in a 4.1-month improvement in median overall survival, so that, it was approved in 2010 by FDA (Kantoff et al., 2017).
Radium-223: an alpha particle-emitting radiopharmaceutical that selectively binds to hydroxyapatite mineralization sites of bone metastases. Based on data from the Alpharadin in Symptomatic Prostate Cancer Patients trial (ALSYMPCA) in which Radium-223 significantly improved overall survival compared with placebo, it was approved by the FDA for both chemotherapy-naive and docetaxel-treated bone- metastatic CRPC (Parker et al., 2013).
3. Circulating tumor cells (CTCs).
3.1. Background
The Australian researcher Thomas Ashworth first discovered CTCs in 1869, and reported microscopic observations of cancer cells in a sample of blood from a patient with metastatic cancer. But it was in 1976 when Nowell modified the definition of CTC as tumor cells derived from primary tumors or metastatic tumors with the ability to get out of the basement membrane and invade into the blood vessels through the
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tissue matrix (Nowell, 1976). Currently, CTCs are defined as cancer cells that shed from primary solid or metastatic tumors to the peripheral blood or lymph, where they travel to colonize the distal target organs to form secondary foci of disease. They are considered the intermediate slavon between the primary tumor and the metastasis, they are candidates to act as substitutable markers measurable in blood (Alix- Panabieres and Pierga, 2014).
In the recent years, CTCs have gained increasing importance because of their multi potential uses. Despite, all the work that has been done over the last years in clinical oncology, no method has been devised to isolate or enumerate CTCs efficiently. Only The CellSearch® remains the platform that has undergone rigorous testing and has managed to become the FDA approved method for detecting the baseline CTCs as a prognostic marker in metastatic breast, colorectal, and prostate cancers, heralding the emergence of CTC enumeration as an analytically validated tool in clinical practice (Cristofanilli et al., 2004, Cohen et al., 2008, de Bono et al., 2008). Even in the case of CellSearch®, its used is limited to some types of cancers. Primarily, the difficulty in determining CTCs is due to the fact that their quantity and frequency in the circulation are extremely low, from 1 to 100 million cells in the bloodstream (Allard et al., 2004, Nelson, 2010), which is the biggest obstacle in the isolation of CTCs. Of the various CTCs eliminated by the primary tumor, only 0.1% survive in the circulation and only 0.01% are responsible for metastasis (Balic et al., 2005).
A major advantage of CTCs compared with other minimally invasive assays is their potential utility as a liquid biopsy serving multiple critical functions (Balic et al., 2005).
On the whole, CTCs enable give biological insights of the disease condition, prognostic markers, progression and predictive biomarkers of treatment response in patients with advance disease.
3.2. CTCs in prostate cancer
CTCs are widely recognized as a biomarker in PCa. Numerous laboratory studies and clinical trials in the past two decades have shown that CTCs may be used as a biomarker to predict disease progression and survival in patients with metastatic, advanced (Olmos
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et al., 2009) or even early-stage PCa (Nagrath et al., 2007). In addition, drops in CTCs levels within the therapy has been associated with higher overall survival, similar to benefit correlated to a substantial PSA decrease or radiographic response (de Bono et al., 2008, Sonpavde et al., 2011). Besides, changes in CTCs levels usually precede PSA fluctuation being their monitoring of even greater value when changes in PSA or bone disease are difficult to evaluate (Scher et al., 2009). Despite their potential, the use of CTCs faces numerous challenges.
Given the difficulty in acquiring prostate biopsies and the importance of identifying new biomarkers (which improve PSA information) that could be used as surrogates for survival in clinical trials, PCa presents the ideal scenario for CTC research and clinical development. The initial approaches in CTC detection in patients with PCa were based on reverse transcription-PCR (RT-PCR) for detecting prostate- specific (Helo et al., 2009) or epithelial-specific markers in non–pre-enriched blood samples. These studies demonstrated the possibility of distinguishing patients from controls based on mRNA levels of the markers, but were often unable to show a direct prognostic relationship.
Due to the critical factor is the CTCs low numbers in the bloodstream, most CTC detection techniques rely heavily on enrichment methods which the aim at condensing the CTCs within a sample and separate them from unwanted hematopoietic cells to help detect and identify those (Millner et al., 2013) based on physical or biological cell properties such as size or specific marker expression. The antigen used most often for positive selection of CTCs is EpCAM (epithelial cell adhesion molecule), an epithelial marker overexpressed in some carcinomas (Shaffer et al., 2007, Nagrath et al., 2007). Nevertheless, it is well known that the epithelial signature of CTCs is altered during metastasis, interfering with the use of EpCAM as a universal marker ( Yu et al., 2013; Ruscetti et al., 2015). However, PCa cells present tissue-specific antigens, such as PSA and prostate-specific membrane antigen (PSMA), usually absent in non-epithelial cells, which could be a convincing target for immunocapture, as their levels increase in higher-grade cancers and metastatic disease and are specific to the prostate (Santana et al., 2012).
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In the last two decades, several promising methods of enrichment and detection of CTC have been developed. In general, the use of CTC as a platform for diagnosis and precision therapy in the PCa augurs a bright and promising future, but it is also supposed a great challenge. The development of more sensitive and effective devices for the enrichment and detection of CTC is urgently required. More importantly, these strategies must be validated in clinical trials of adequate size to evaluate their quality, validity and clinical practicality.
3.3. Isolation and detection techniques
Several methods have been developed for the evaluation, isolation, and enrichment of CTCs in blood, based on the physical and biological properties of these tumoral cells.
As mentioned above, CTCs are extremely rare cells in the bloodstream, so that enrichment and isolation techniques have been used for separation from peripheral blood cells. Such techniques validated or in development are summarized in:
3.3.1. Isolation based on physical properties: CTCs can also be positively or negatively isolated depending on size, density, deformability, or electric charges. Those methods consist of centrifugation, membrane- or filtration- based systems, and dielectrophoresis (DEP).
Density gradient centrifugation: isolation based on density differences between CTCs and other hematopoietic components. The mononuclear cells and CTCs have a density <1.077 g/mL, while the other blood cells and granulocytes have a density >1.077 g/mL (Morgan et al., 2007). This process generates a layered separation of different cell types based on their cellular density.
Microfabricated filters: Because the majority of blood cells are smaller than CTCs, using filters to separate CTCs from whole blood can remove the majority of peripheral blood cells (Tan et al., 2009, Lecharpentier et al., 2011).
Dielectrophresis (DEP): cells have diverse dielectric properties, according to this, DEP can be used to manipulate, transport, separate, and sort different types of cells (including CTCs). DEP separation
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techniques can achieve a single-cell-level purification (Peeters et al., 2014).
3.3.2. Isolation based on biological properties: CTCs can be distinguished from other blood components by utilizing their biological properties, such as surface antigens, cytoplasmic protein expression, and invasion capacity.
Immunomagnetic separation: this approach utilizes magnetic labeled beads for either positive selection of CTCs using cell-surface markers ( Cristofanilli et al., 2004; Shaffer et al., 2007) or negative depletion of white blood cells using anti-CD45 (leukocyte common antigen) (Karabacak et al., 2014). The leading example of the methods is the CellSearch™ assay.
Microfluidics chips: (CTC-chips) are based on devices with antibody- coated microstructures, which allow the mixing of blood cells through the generation of microvortices to significantly enhance the number of interactions between target CTCs and the antibody-coated chip surface (Nagrath et al., 2007; Krishnamurthy et al., 2013,). Such an approach enables the capture of large numbers of viable CTCs in a single step from whole blood without the need for an initial enrichment step.
After enrichment, the CTCs detection is performed, through either immunofluorescence, reverse transcription PCR (RT-PCR), flow cytometry or other techniques involving sophisticated software and microscopy.
3.4. CTCs as pharmacodynamics biomarkers in PCa
CTCs have also been studied for their utility in molecular profiling of drug targets and predicting drug responsiveness during the development of both approved and experimental agents. In general, CTCs have been used as pharmacodynamics (PD) biomarkers through two main strategies, either indirectly via their enumeration or directly through their molecular characterization.
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As mentioned before, CTC enumeration is a strong predictor of overall survival and has predictive value for patients with metastatic castration-resistant PCa (mCRPC).
Further, changes in CTC levels before and during treatment have been used to reflect the active doses of a new antitumor agents in different types of tumors, including PCa.
Clinical trials with abidaterone or enzalutamide, the CTC counts demonstrated their active dose, as well as being an early indicator of antitumor activity, as shown by their correlation with significant PSA decreases (Attard et al., 2009a, Reid et al., 2010, Scher et al., 2010).
Meanwhile, previous studies have demonstrated the utility of transcriptional and genomic profiling in CellSearch-detected CTCs from patients with PCa (Shaffer et al., 2007, Leversha et al., 2009). Androgen receptor (AR) chromosomal amplifications have been detected in CTCs from patients with mCRPC by fluorescent in situ hybridization (FISH). In addition, other works have been studied the impact of TMPRSS2-ERG rearrangements using CTC FISH detection (Attard et al., 2009c). As previously mentioned, according to published studies the expression of AR-V7 in CTC would be a valuable tool to guide the selection of treatment in mCRPC (Antonarakis et al., 2014;
Antonarakis et al., 2015; Nakazawa et al., 2015; Scher et al., 2016).
Importantly, CTCs may differ in their phenotype between primary tumor and metastatic sites, as Miyamoto et al demonstrated by RNA sequencing from primary tumors, CTCs and metastasis (Miyamoto et al., 2015). These and other results lead us to believe that not only CTC count but also their molecular characterization may be shed light on mechanisms of resistance to therapy and helps to predict the likelihood of response to a given therapy for specific patients.
4. Taxanes
4.1. Definition and action mechanism
As previously mentioned, taxanes chemotherapy is the first available options for treat the patients who have shown resistance to ADT treatment and have developed CRPC disease. DOC was identified in the 1980s, is a semi-synthetic taxane analogue from the European yew (Taxus baccata) (Gligorov and Lotz, 2004).
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The mechanism of action of DOCl is not fully understood, it mainly exerts its cytotoxic activity through the stabilization of microtubules (Cortes and Pazdur, 1995).
During mitosis, microtubule polymers (composed of α- and β-tubulin heterodimers) rapidly polymerize and depolymerize to orchestrate an orderly separation of chromosomes. DOC binds β-tubulin, stabilizing microtubule structures and altered the mitotic spindle architecture. Cells susceptible to Docetaxel-induced cytotoxicity undergo mitotic arrest, cell proliferation block (Seruga et al., 2011)and ultimately, induces B-cell lymphoma 2 (Bcl-2) phosphorylation that prevents its heterodimerization and leads to caspase activation and apoptosis (Haldar et al., 1996, Nehme et al., 2001); in addition, DOC has been able to induce apoptosis by nuclear interaction of Smac-DIABLO with surviving thought to antagonize the function of inhibitors of apoptosis proteins (Kim et al., 2006). In another hand, it was demonstrated that DOC have some antiandrogenic properties by reducing the expression of AR on CRPC cells (Gan et al., 2009) and is also believed that being able to block nuclear translocation of AR, which is microtubule dependent (Fitzpatrick and de Wit, 2014; van Soest et al., 2015a).
4.2. Pharmacodynamics biomarkers to DOC therapy
Predicting the DOC response are necessary to identify patients who do not respond early to avoid ineffective and potentially toxic therapy. Biomarker response identification is one of the most active areas of research currently in CRPC, and advances in this field will eventually aid to determine the best treatment options.
Based on the action mechanism of taxanes, pharmacodynamics studies in different tumors have been focused on drug effects characterization on cell membrane antigens in CTCs and / or the selective reduction of genetically distinct CTCs subpopulations. Regarding the CTCs molecular characterization, several biomarkers are were included as exploratory pharmacodynamics biomarkers in the last decade, for instance: HER2 (Riethdorf et al., 2010) , γ-H2AX (Wang et al., 2010), EGFR (Maheswaran et al., 2008), ALK (Pailler (Pailler et al., 2013), AR signaling (Miyamoto et al., 2012), among others. This doctoral thesis is proposed to study the
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use of Phospho-histone H3 (Ser10) (pHH3) and Cytokeratin M30 (CK-M30) as CTC pharmacodynamics biomarkers to DOC treatment in patients with mCRPC.
4.2.1. Phospo-hitone H3 (Ser10) as a mitosis arrest biomarker
Proliferation markers that are expressed in the specific phases of the cell cycle provide greater prognostic value and possibilities for therapeutic intervention in cancers. Phosphorylation of histone H3 occurs at Ser 10 almost exclusively during late G2 phase, prophase, and M phase of the cell cycle in order to help coordinate chromatin condensation (Hendzel et al., 1997). High pHH3 expression has been shown to correlate with shorter survival in a variety of tumors such melanomas (Ladstein et al., 2012, Tetzlaff et al., 2013), carcinomas (Nakashima et al., 2013, Nowak et al., 2014, Skaland et al., 2007) and neuronal tumors (Kim et al., 2007). Interestingly, other groups have shown that the accumulation of pHH3 is also a marker of G2/M arrest mitosis induction (Raab et al., 2011; Olmos et al., 2011; Martinez et al., 2015).
4.2.2. Cytokeratin M30 as apoptosis biomarker
In 2001, Mehes et al. showed that in patients with metastatic breast cancer, most CTCs are apoptotic (Mehes et al., 2001), which supports the idea that metastasis is an extremely inefficient process (Forte et al., 2016). Rossi et al. evaluated, in a small series of patients with breast cancer, the presence of CK-M30 in CTC using the CellSearch platform and concluded that changes in CK-M30 levels in CTC during treatment could be used to evaluate Real time response / drug resistance (Rossi E (Rossi et al., 2010), subject reported in other subsequent studies ( Rossi et al., 2012; Kallergi et al., 2013) . This suggests that CTCs that survive despite treatment can be used to design therapeutic strategies aimed at attacking this resistant population.
CK-M30 is a neo-epitope released by caspase cleavage at cytokeratin 18 in early apoptosis cascade, it is not detectable in vital epithelial cells and it is generally reported as a stable biomarker, specific for epithelial cell apoptosis (Rossi et al., 2010).
48 4.3. Docetaxel-Resistant PCa
This resistance can arise through alterations in tubulin that impair the binding of taxane to microtubules (Galletti et al., 2007). It has been demonstrated that the expression of different isoforms of β-tubulin correlates with taxane resistance because the formation of heterodimers with different isoforms could affect the dynamic properties of microtubules. In addition, elevated βIII-tubulin expression in tumors has been linked to cancer progression and poorer overall survival during DOC therapy (Ploussard et al., 2010), as well as mutations in tubulin α and β are associated with taxane resistance in vitro (Hari et al., 2003, Martello et al., 2003). Interestingly, regarding to the microtubule alteration, it has been demonstrated that ERG interacts directly with tubulin and may block taxane activity by reducing available binding sites in microtubules (Galletti et al., 2014, Tsourlakis et al., 2014).
In addition, analysis of CTCs from patients with CRPC receiving taxane therapy found a significant correlation between AR cytoplasmic sequestration and clinical response to therapy (Darshan et al., 2011). A preclinical study found that prostate cancer xenografts expressing AR-V7, which does not require microtubule-based transport, had resistance to DOC (Thadani-Mulero et al., 2014).
One of the most investigated features in taxane resistance mechanism in mCRPC is overexpression of ATP-binding cassette (ABC) or multidrug resistance (MDR) transporters (Sharom, 2008). These proteins are transmembrane ATP-dependent efflux pumps that have the ability to carry drugs out of the cells. The worst clinical outcome and PCa toxicities have been associated with the expression of ABCB1 and its allelic variants (Kawai et al., 2000), suggesting that block of ABCB1 could represent a new approach for resensitization to DOC treatment (Zhu et al., 2015).
Levels of inflammatory cytokines are another class of promising biomarkers associated with DOC response in patients with mCRPC. Inflammation has clearly been implicated in prostate carcinogenesis (De Marzo et al., 2007). Several studies have evaluated the correlation between inflammatory cytokines and outcomes of patients with mCRPC treated with DOC. DOC-induced decreases in interleukin-6 (IL-6)
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(Domingo-Domenech et al., 2006, Ignatoski et al., 2009) and macrophage inhibitory cytokine 1 (MIC1) have been shown to correlate with PSA response. Zhao et al.
demonstrated that an increase in MIC1 levels after first cycle in men with CRPC was predictive of DOC resistance (Zhao et al., 2009).
5. Prostate cancer mouse models
Mouse models play a central role in the study of the etiology, prevention and treatment of human PCa. Although culture cell lines are extremely useful in understanding the biology of PCa, they are not capable of recreating the complex cellular interactions within the tumor microenvironment that are key in the initiation and progression of cancer.
PCa mouse models can be divided into two categories: genetic engineering mouse models (GEM) and xenograft models. Just to mention that, one of the main reticence of the use of GEM are not only the biological differences between the mouse prostate and the human, but also with other tissues that can affect the phenotypes (Bavik et al., 2006). In addition, at a practical level, generating GEM models usually have higher costs and longer time frames to generate results compared to xenograft models, which can be a disadvantage.
Within the group of xenografts it is necessary to differentiate between patient- derived xenografts (PDXs) and cell line xenografts. PDX is generated through human tumor tissue from patient being directly implanted or injected into an immunocompromised mouse (Lin et al., 2014). Its main drawback is that it is often quite difficult to establish, since they require high quality tumor tissue (Godebu et al., 2014;
Russell et al., 2015). However, it is believed that PDX models represent the future of personalized or individualized medicine, since they are capable of encompassing greater genomic, epigenetic and proteomic diversity within the PCa (Rosfjord E., Biochem Pharmacol, 2014). In the case of cell line xenograft models, PCa cells are commonly implanted into immunocompromised mice either subcutaneously or injected orthotopically into the prostate. Orthotopic models have the advantage of growth within the prostate microenvironment, and in a number of models metastasis occurs at
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high rates. This model is used most often for drug studies, due to its reproducibility, quick experimental timeframe, and relative ease of experimental setup (Ko et al., The xenograft models described earlier have all proved extremely useful in evaluating the biology of human prostate cancer and are used routinely to evaluate prostate cancer therapies in a relatively quick and lower-cost way of evaluating new therapies in prostate cancer and mechanisms of therapeutic resistance. A major disadvantage of such models is that most xenografts and PCa cell lines are derived from clinically aggressive lesions, they may not reflect the biology of precursor or less aggressive lesions (Ittmann et al., 2013).
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O BJETIVES
53
The general aim of this thesis is to establish a preclinical platform of disseminated/advanced prostate cancer using orthotopic xenografts to identify and/or validates biomarkers for prostate cancer. As a proof of the concept, we have used a CRPC model to develop markers of response and resistance to Docetaxel, which we would later validate in mCRPC patients treated with that drug. For this reason, the following objectives have been set:
1. Development and in vivo characterization of prostate cancer metastatic mouse models by orthotopic injection of human prostate cancer cells from an established cell line.
2. To study the range of activity of Docetaxel treatment in orthotopic xenograft PCa mouse models.
3. To establish a methodology to quantify, isolate and characterize circulating biomarkers in orthotopic xenograft PCa mouse models.
4. Clinical evaluation of the efficiency of Docetaxel treatment in patients with metastatic castration resistant patients, as well as search for new pharmacodynamics biomarkers in circulating tumor cells, such as mitosis arrest (pHH3) and apoptosis markers (CK-M30).
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O BJETIVOS
56
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El objetivo general de esta tesis es establecer una plataforma preclínica de cáncer de próstata metastásico utilizando xenoinjertos ortotópicos para desarrollar y/o validar biomarcadores para el cáncer de próstata. Como prueba del concepto, hemos utilizado un modelo de CRPC para desarrollar marcadores de respuesta y resistencia al Docetaxel, que luego validaríamos en pacientes con mCRPC tratados con ese medicamento. Por este motivo, se han establecido los siguientes objetivos:
1. Desarrollo y caracterización in vivo de modelos murinos de metástasis de cáncer de próstata mediante inyección ortotópica de células tumorales humanas establecidas de cáncer de próstata.
2. Estudiar el rango de actividad del tratamiento con Docetaxel en modelos de ratón de cáncer de próstata con xenoinjerto ortotópico de células tumorales humanas establecidas de cáncer de próstata.
3. Establecer una metodología para aislar y caracterización de biomarcadores en células tumorales circulantes en modelos de ratón de cáncer de próstata con xenoinjerto ortotópico.
4. Evaluación clínica de la eficacia del tratamiento con Docetaxel en pacientes con enfermedad metastásica resistente a la castración, así como la búsqueda de nuevos biomarcadores farmacodinámicos en células tumorales circulantes, como marcadores de arresto mitótico (pHH3) y/o de apoptosis (CK-M30).
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M ATERIALS AND M ETHODS
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61 1. Cell culture
1.1. Prostate cancer cell lines
The established human PCa cell lines used were originally purchased from the American Type Culture Collection (ATCC).
5. LNCaP (ATCC CRL-1740): derived from left supraclavicular lymph node metastasis. They are androgen-dependent cells.
6. PC3 (ATCC CRL-1435): derived from a bone metastasis of a grade IV prostatic adenocarcinoma. PC3 are lacking the AR that is the reason of their androgen- independent status.
7. 22RV1 (ATCC CRL-2505): human prostate carcinoma epithelial cell line derived from a xenograft that was serially propagated in mice after castration-induced regression and relapse.
8. C4-2 (ATCC CRL-3314): cells were isolated from a human prostate cancer LNCaP cell subcutaneous xenograft tumor of castrated mouse. Exhibits androgen independent growth.
The cell lines are cultured in RPMI-1640 with phenol red as a pH indicator (Lonza) and are supplemented with 10% of fetal bovine serum (FBS, SIGMA). The cultures are maintained in an incubator at 37°C, 5% CO2 and 90% of humidity. The culture medium was replaced every 2-3 days.
All cell lines were authenticated with Cell Line Authentication GenePrint® 10 System by CNIO Genomic Unit and they were tested for Mycoplasma using MycoAlertTM Detection Kit (Lonza).
1.2. Transfection luciferase vector
Luminescent prostate cancer cell lines were generated by transfection with a plasmid encoding firefly luciferase (pGL4.51, Promega) (Fig 4). First of all, the prostate cancer cells PC3 and 22Rv1 were plated at 70-80% of confluence in 10 ml of complete media in 100mm of diameter plates. Ten micrograms of plasmid were transfected using 40µl of PEI (Polyethylenimine) as a positively charged polymeric transfection reagent. The cells