Το ετεροτριμερές πρωτεϊνικό σύμπλεγμα IPP (ILK-PINCH-Parvin) εντοπίζεται στις εστιακές συνδέσεις και ρυθμίζει την σηματοδότηση από την εξωκυττάρια ουσία μέσω ιντεγκρινών και αυξητικών παραγόντων, αλληλεπιδρώντας με τον κυτταροσκελετό ακτίνης και με ποικίλες σηματοδοτικές οδούς. Οι πρωτεΐνες του συμπλεγματος IPP ελέγχουν σημαντικές κυτταρικές λειτουργίες όπως ο πολλαπλασιασμός, η επιβίωση, η κυτταρική κίνηση-μετανάστευση και ενέχονται σημαντικά στην καρκινογένεση (Legate et al., 2006). Συγκεκριμένα η πρωτεΐνη ILK (integrin-linked kinase) έχει συσχετιστεί με την εξέλιξη-προαγωγή του όγκου και δυσμενή πρόγνωση στο μη μικροκυτταρικό καρκίνωμα του πνεύμονα (Ζhao et al., 2013). Η πρωτεΐνη Ras supressor protein 1 (Rsu-1), γνωστή για την ογκοκατασταλτική της δράση και την συμμετοχή της στη σηματοδοτική οδό του ογκογονιδίου Ras, πρόσφατα βρέθηκε οτι αλληλεπιδρά με την πρωτεΐνη PINCH του ΙPP συμπλέγματος και μέσω αυτής της αλληλεπίδρασης ρυθμίζει διεργασίες όπως η κυτταρική μετανάστευση και διήθηση(Gonzalez-Nieves et al., 2013). Σκοπός της παρούσας μελέτης είναι η διερεύνηση του ρόλου του IPP συμπλέγματος και της πρωτεΐνης Rsu-1 στο μη μικροκυτταρικό καρκίνωμα του πνεύμονα στον άνθρωπο καθώς και της συμμετοχής του ΙPP συμπλόκου στην σηματοδότηση από το ογκογονιδίο Ras. Για το σκοπό αυτό μελετάται η πρωτεϊνική έκφραση των ILK, PINCH, α-Parvin, β- Parvin και Rsu-1 1) σε ιστικά δείγματα μη-μικροκυτταρικού καρκινώματος του πνεύμονα σε σχέση με κλινικοπαθολογοανατομικές παραμέτρους της νόσου και 2) σε καρκινικές κυτταρικές σειρές με διαφορετικά επίπεδα ενεργοποίησης της Ras σηματοδότησης. Για τα στοιχεία του ΙΡΡ συμπλέγματος παρατηρήθηκε αυξημένη ανοσοϊστοχημική έκφραση ενώ για την πρωτεΐνη Rsu1 βρέθηκε μειωμένη στα μη μικροκυτταρικά καρκινώματα του πνεύμονα σε σχέση με το μη νεοπλασματικό παρέγχυμα του πνεύμονα. Η έκφραση των ILK και PARVA ήταν σημαντικά υψηλότερη στα χαμηλής διαφοροποίησης νεοπλάσματα και σε όγκους προχωρημένου pT αντίστοιχα. Η έκφραση της πρωτεΐνης PINCH σχετίστηκε στατιστικώς σημαντικά με την παρουσία λεμφαδενικών μεταστάσεων. Δεν παρατηρήθηκε εξάρτηση της πρωτεϊνικής έκφρασης των Rsu-1 και PINCH από τη σηματοδοτική οδό Ras. Τα αποτελέσματα υποστηρίζουν ότι η υπερέκφραση των στοιχείων του ΙΡΡ συμπλέγματος και η μειωμένη έκφραση του Rsu1 ενέχονται στην παθογένεια του καρκίνου του πνεύμονα. / The integrin-linked kinase (ILK)-PINCH-parvin (IPP) complex at integrin adhesion sites is a critical regulator of cell migration, invasion and metastasis. Deregulation of the IPP complex has been implicated in human carcinogenesis (Legate et al, 2006). Recent observations suggest that RSU-1, a protein first identified as a suppressor of v-Ras mediated cell transformation is a PINCH-binding partner that regulates PINCH mediated adhesion and migration (Gonzalez-Nieves et al., 2013). This study aims to evaluate the expression of the IPP complex and RSU-1 in human non-small cell lung carcinomas (NSCLC). Protein expression of ILK, PINCH, alpha-parvin, beta-parvin and RSU-1 in relation to clinicopathological parameters was evaluated by immunohistochemistry in 82 FFPE tissue samples of non-small cell lung cancer (NSCLC). All components of the IPP complex were overexpressed while RSU-1 was downregulated in lung cancer cells compared to non-neoplastic lung parenchyma. ILK and alpha-parvin expression was significantly higher in high grade (p=0.002) and high pT (p=0.047) tumors respectively. Expression of PINCH associated significantly with lymph node metastasis (p=0.045). Our results suggest that overexpression of the IPP complex and downregulation of RSU-1 may be implicated in lung carcinogenesis.

In most randomised controlled trials (RCTs), a large number of patients need to be followed over many years, for the clinical benefit of the drug to be accurately quantified (1). Using an early proxy, or a surrogate endpoint, in place of the direct endpoint of overall survival (OS) could theoretically shorten the duration of RCTs and minimise the exposure of patients to ineffective or toxic treatments (2, 3). This thesis examined the relationship between surrogate endpoints and OS in metastatic colorectal cancer (CRC), advanced non-small cell lung cancer (NSCLC) and metastatic breast cancer (MBC). A review of the literature identified 144 RCTs in metastatic CRC, 189 in advanced NSCLC and 133 in MBC. The publications were generally of poor quality with incomplete reporting on many key variables, making comparisons between studies difficult. The introduction of the CONSORT statement was associated with improvements in the quality of reporting. For CRC (337 arms), NSCLC (429 arms) and MBC (290 arms) there were strong relationships between OS and progression free survival (PFS), time to progression (TTP), disease control rate (DCR), response rate (RR) and partial response (PR). Correlation was also demonstrated between OS and complete response (CR) in CRC and duration of response (DOR) in MBC. However, while strong relationships were found, the proportion of variance explained by the models was small. Prediction bands constructed to determine the surrogate threshold effect size indicated that large improvements in the surrogate endpoints were needed to predict overall survival gains. PFS and TTP showed the most promise as surrogates. The gain in PFS and TTP required to predict a significant gain in overall survival was between 1.2 and 7.0 months and 1.8 and 7.7 months respectively, depending on trial size and tumour type. DCR was a better potential predictor of OS than RR. The results of this study could be used to design future clinical trials with particular reference to the selection of surrogate endpoint and trial size.

The purpose of this work is to make an attempt to quantify and model various types of cell death for a small cell lung cancer (SCLC) cell line (U1690) after exposure to a 137Cs source and as well as to compare cell survival models, the Linear-Quadratic (LQ) and Repairable Conditionally – Repairable model (RCR). This study is based on four different experiments that were taken place at Cancer Centrum Karolinska (CCK). A human small cell lung cancer (SCLC) cell line after the exposure to a 137Cs source was used for the extraction of the clonogenic cell survival curve. Additionally for the determination and quantification of various modes of cell death the method of fluorescence staining was implemented, where we categorized the cell death based on morphological characteristics. As next with the flow cytometry analysis we measured the properties of individual particles and more specifically the percentage of cells in each phase of the cell cycle. The quantification of senescent cells was performed by staining the samples with senescence associated-β-gal solution and then scoring as senescent cells those that had incorporated the substance. These data were introduced into a maximum likelihood fitting to calculate the best estimates of the parameters used by the model in section 2.8. In this model we sorted the modes of cell death into three categories: apoptotic, senescent and other types of cell death (nec/apop, necrotic, micronuclei, giant). In regards to the clonogenic cell survival assay the RCR model shows a ρ2 value that is equal to 6.10 whereas for the LQ model is 9.61. Moreover from the fluorescence microscopy and senescence assay we observed an initial increase of the probability of three different categories of cell death on day 2 and at higher doses there was saturation. On day 7 a significant induction of apoptosis in a dose and time dependent manner was evident whereas senescence was slightly increased in response to dose but not to time. As for the „other types of cell death‟ category on day 7 showed a higher probability that the one on day 2 and as well as a prominent dose dependence. A dose dependent accumulation of cells in the G2/M phase of the cell cycle was induced by photons on day 2. The accumulation in the G2/M phase on day 2 is released on day 7 and simultaneously an increase of the probability of apoptosis with time was observed. The RCR model is fitted better to the experimental data rather than the LQ model. On day 2 there is a slight increase of the apoptotic and senescent probability with dose. On the other hand on day 7 the shape of the curve of apoptosis differs and we observe a sigmoidal increase with dose. At both time points the mathematical model fit the data reasonable well. Due to the fact that the clonogenic survival doesn‟t coincide with the one extracted from the fluorescence microscopy, a more accurate way of quantification of cell death need to be used (e.g. CVTL). / Ο σκοπός αυτής της μελέτης είναι η ποσοτικοποίηση και μοντελοποίηση διαφόρων τύπων κυτταρικού θανάτου μικροκυτταρικού καρκίνου πνεύμονα μετά από ακτινοβόληση με πηγή Καισίου (137Cs) καθώς και η σύγκριση μοντέλων κυτταρικής επιβίωσης, Linear-Quadratic (LQ) και Repairable Conditionally-Repairable. Η μελέτη είναι βασισμένη σε τέσσερα ξεχωριστά πειράματα τα οποία πραγματοποιήθηκαν στο Cancer Centrum Karolinska (CCK). Ανθρώπινος μικροκυτταρικός καρκίνος πνεύμονα χρησιμοποιήθηκε για τον υπολογισμό της καμπύλης κυτταρικής επιβίωσης μετά από ακτινοβόληση με πηγή Καισίου (137Cs). Επιπρόσθετα για τον προσδιορισμό και την μοντελοποίηση των διαφόρων ειδών θανάτου εφαρμόστηκε η μέθοδος της φθορίζουσας μικροσκοπίας, με την βοήθεια της οποίας κατηγοριοποιήθηκε ο κυτταρικός θάνατος βάσει μορφολογικών χαρακτηριστικών. Στη συνέχεια μέσω της κυτταρομετρίας ροής υπολογίσαμε τις ιδιότητες μεμονομένων σωματιδίων (κυττάρων) και πιο συγκεκριμένα το ποσοστό των κυττάρων σε κάθε φάση του κυτταρικού κύκλου. Η ποσοτικοποίηση των κυττάρων γήρανσης πραγματοποιήθηκε μέσω της χρώσης των δειγμάτων με διάλυμα συσχετιζόμενο με την γήρανση και μετά καταγράφηκαν σαν κύτταρα γήρανσης αυτά τα οποία είχαν ενσωματώσει την ουσία. Τα δεδομένα χρησιμοποιήθηκαν σε μια διαδικασία προσαρμογής μέγιστης πιθανοφάνειας (maximum likelihood fitting) ώστε να υπολογιστούν οι βέλτιστες τιμές των παράμετρων που χρησιμοποιούνται από το μοντέλο στην ενότητα 2.8. Στο παρόν μοντέλο έχουμε ταξινομήσει τον κυτταρικό θάνατο σε τρεις κατηγορίες: απόπτωση, γήρανση και άλλοι τύποι κυτταρικού θανάτου (νεκ/αποπ, νέκρωση, μικροπυρήνες και γίγαντες). Όσον αφορά την κλωνογόνο κυτταρική επιβίωση το RCR μοντέλο παρουσιάζει τιμή χ2 ίση με 6.10 ενώ για το LQ μοντέλο ίση με 9.61. Επιπλέον μέσω της φθορίζουσας μικροσκοπίας και της χημικής δοκιμής για την κυτταρική γήρανση παρατηρήσαμε την 2η μέρα αρχική αύξηση της πιθανότητας και για τις τρεις κατηγορίες κυτταρικού θανάτου ενώ εμφανής ήταν ο κορεσμός στις υψηλότερες δόσεις. Την 7η μέρα παρουσιάστηκε επαγωγή της απόπτωσης με δοσο/χρονο-εξαρτώμενο τρόπο καθώς και το ότι η γήρανση των κυττάρων αυξήθηκε ελάχιστα με την δόση αλλά όχι με τον χρόνο. Σχετικά με την τρίτη κατηγορία ‘άλλοι τύποι κυτταρικού θανάτου’ την 7η μέρα ανέδειξε υψηλότερη πιθανότητα συγκριτικά με την 2η μέρα καθώς και μια έκδηλη εξάρτηση με την δόση. Κατά την ανάλυση του κυτταρικού κύκλου για την 2η μέρα αναδεικνύεται συσσώρευση των κυττάρων με δοσοεξαρτώμενο τρόπο στην φάση G2/M του κυτταρικού κύκλου. Η συσσώρευση των κυττάρων στην φάση G2/M την 2η μέρα απελευθερώθηκε την 7η μέρα με ταυτόχρονη αύξηση της πιθανότητας για απόπτωση συναρτήσει της δόσης. Βρέθηκε ότι το RCR μοντέλο προσαρμόζεται καλύτερα στα πειραματικά δεδομένα σε σχέση με το LQ μοντέλο. Την 2η μέρα παρατηρήθηκε πολύ μικρή αύξηση της πιθανότητας για απόπτωση και γήρανση συναρτήσει της δόσης. Ενώ την 7η μέρα η μορφή της καμπύλης της απόπτωσης διαφοροποιήθηκε και παρατηρήθηκε σιγμοειδής αύξηση με την δόση. Το μαθηματικό μοντέλο προσαρμόζεται αρκετά καλά στα δεδομένα για την 2η και 7η μέρα. Ένας πιο ακριβής τρόπος υπολογισμού της ποσοτικοποίησης του κυτταρικού θανάτου θα πρέπει να χρησιμοποιηθεί εξ’αιτίας του γεγονότος ότι η καμπύλη της κλωνογόνου επιβίωσης δεν συμπίπτει με αυτή που παράχθηκε από την μικροσκοπία φθορισμού.

Radiation therapy (RT) plays a crucial role in the management of cancer, however, current standards of care have yet to account for patient specific radiation sensitivity. Raman spectroscopy (RS) is a promising technique for radiobiological studies as a way to measure radiation responses in biological samples and could provide a method for monitoring and predicting radiation response in patients. The work in this dissertation gives way to significant advances in the implementation of RS for applications in radiation oncology. Specifically, instrumentation improvements for clinical implementation of RS were achieved through the investigation and development of Raman microfluidic systems. Unique magnesium fluoride based microfluidic systems were engineered and evaluated for applications in radiobiological studies. These systems were found to yield superior spectral quality over traditional microfluidic designs. Furthermore, in order to assert RS as a key technique for clinical monitoring and prediction of radiation responses, human non-small cell lung cancer (NSCLC) and breast adenocarcinoma tumour xenograft models were investigated for Raman signatures of radiation response. These studies found that RS can identify unique and distinct signatures of radiation response in tumours, that can be tracked over time. In particular, NSCLC tumours were found to have key radiation induced modulations in cell cycle and metabolic linked spectral features- including glycogen. Breast adenocarcinoma tumours were found to exhibit distinct fluctuations in spectral features linked to cell cycle as well as protein content. In the case of NSCLC, radiation response signatures were found to be linked to tumour regression and hypoxic status of the tumour- a key factor that dictates radiation resistance in the disease. This work provides the first application of RS to measure radiation response signatures of tumours irradiated \textit{in vivo}. These results show that RS is a versatile technique that can offer insight into radiation induced molecular changes that are unique to the type of cancer and can be monitored over several days following radiation exposure. Together with improved instrumentation for radiobiological studies using microfluidics, the work presented in this dissertation further emphasizes the key role RS can have in radiation oncology and personalization of RT. / Graduate / 2019-08-21

O câncer de pulmão é responsável por aproximadamente 13% do total de casos de neoplasias malignas e por cerca de 1.4 milhões de mortes por ano em todo mundo. Esta neoplasia apresenta-se sob dois principais subtipos: câncer de pulmão de pequenas células (CPPC) e câncer de pulmão de não-pequenas células (CPNPC). Cerca de 85% dos casos de câncer de pulmão são do tipo CPNPC. Os sinais e sintomas são secundários ao crescimento do tumor primário, ao comprometimento lobo-regional, à disseminação à distância, ou são secundários às síndromes paraneoplásicas. Essas características refletem diretamente sobre as taxas de mortalidade; de cada 100 novos casos, 80 são inoperáveis e a maioria morre dentro de 3 anos. Isso significa que, apesar dos diversos avanços no diagnóstico e tratamento, o prognóstico do câncer de pulmão permanece sendo extremamente ruim, com sobrevida média de 10 meses, e cumulativa total em 5 anos de aproximadamente 12%. Atualmente, o prognóstico e a decisão terapêutica de pacientes com câncer de pulmão é baseada no TNM, Embora esse seja o procedimento considerado padrãoouro entre os profissionais de saúde, ele não leva em consideração características biológicas do tumor. Nesse contexto, a identificação de biomarcadores para câncer pode agregar importantes informações ao já estabelecido sistema TNM e resultar em tratamentos mais eficientes e em menores taxas de mortalidade. Existem 5 fases distintas que conceitualizam o desenvolvimento de um biomarcador tumoral. Através dessas fases consecutivas, é possível que se desenvolvam ferramentas úteis para triagem populacional, capazes de serem implementadas na rotina clínica para predição de desfecho do paciente, resposta terapêutica e monitoramento da doença. O presente projeto avaliou o valor prognóstico dos principais genes citados na literatura como potenciais biomarcadores para CPNPC, e verificou-se que nenhum deles apresentou significância na correlação estatística que indica poder prognóstico. Além disso, identificamos e validamos o papel prognóstico da cofilina-1 por meio de dados de microarranjo e quantificação de seu imunoconteúdo em biópsias de CPNPC. Para tanto, fizemos uso de meta-análise de bancos de dados e análise densitométrica das reações imuno-histoquímicas, seguida de correlação com dados de grau de diferenciação tumoral, classificação histológica, sexo, idade e desfecho relativo a cada caso. Além disso, desenvolvemos um método de baixo custo, fácil execução e ampla aplicação e reproducibilidade, capaz de quantificar a proteína em amostras biológicas, com potencial para ser implementado na rotina clínica e aplicamos esse método em uma coorte restrospectiva de CPNPC. Confirmamos assim o papel prognóstico da cofilina-1. Estes achados seguem a lógica das fases de desenvolvimento de um biomarcador e representam um grande passo no seu processo de validação. / Lung cancer accounts for approximately 13% of all malignant tumor cases and for about 1.4 million deaths per year worldwide. This cancer has two main subtypes: Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC). About 85% of cases of lung cancer are NSCLC type. The signs and symptoms are secondary to the primary tumor growth, to regional lobe commitment and distant spread, or are secondary to paraneoplastic syndromes. These features reflect directly on mortality rates; 80 in every 100 new cases are inoperable and most die within 3 years. This means that, despite many advances in diagnosis treatment, the prognosis of lung cancer remains extremely poor, with median survival of 10 months, and total cumulative survival in 5-year of approximately 12%. Currently, prognosis and therapeutic decisions in patients with lung cancer is based on TNM. Although this procedure is considered gold standard among health professionals, it does not take into account the biological characteristics of the tumor. In this context, the identification of cancer biomarkers may add important information to the already established TNM system and result in better treatments and lower mortality rates. There are five distinct phases that conceptualize a tumor biomarker development of. Through these successive phases, it is possible to develop useful tools for population screening, capable of implementation in clinical practice for prediction of patient outcome, therapeutic response and disease monitoring. This project evaluated the prognostic value of major genes mentioned in literature as potential biomarkers for NSCLC and found that none of them showed statistical significance in the correlation that indicates prognostic power. It also identified and validated the prognostic role of cofilin-1 by microarray data and quantification of their immunocontent in biopsies of NSCLC. For this purpose, we used data metaanalysis and immunohistochemical reactions densitometric analysis, followed by correlation with data from tumor grade, histological classification, sex, age and outcome for each case. In addition, we developed a low-cost protocol, of easy implementation and wide application and reproducibility, able to quantify the protein in biological samples, with the potential to be implemented in clinical practice. We applied this method in a retrospective cohort of NSCLC and confirm the prognostic role of cofilin-1. These findings follow the logical phases of biomarker development and represent a major step in its validation process.

O câncer de pulmão é responsável por aproximadamente 13% do total de casos de neoplasias malignas e por cerca de 1.4 milhões de mortes por ano em todo mundo. Esta neoplasia apresenta-se sob dois principais subtipos: câncer de pulmão de pequenas células (CPPC) e câncer de pulmão de não-pequenas células (CPNPC). Cerca de 85% dos casos de câncer de pulmão são do tipo CPNPC. Os sinais e sintomas são secundários ao crescimento do tumor primário, ao comprometimento lobo-regional, à disseminação à distância, ou são secundários às síndromes paraneoplásicas. Essas características refletem diretamente sobre as taxas de mortalidade; de cada 100 novos casos, 80 são inoperáveis e a maioria morre dentro de 3 anos. Isso significa que, apesar dos diversos avanços no diagnóstico e tratamento, o prognóstico do câncer de pulmão permanece sendo extremamente ruim, com sobrevida média de 10 meses, e cumulativa total em 5 anos de aproximadamente 12%. Atualmente, o prognóstico e a decisão terapêutica de pacientes com câncer de pulmão é baseada no TNM, Embora esse seja o procedimento considerado padrãoouro entre os profissionais de saúde, ele não leva em consideração características biológicas do tumor. Nesse contexto, a identificação de biomarcadores para câncer pode agregar importantes informações ao já estabelecido sistema TNM e resultar em tratamentos mais eficientes e em menores taxas de mortalidade. Existem 5 fases distintas que conceitualizam o desenvolvimento de um biomarcador tumoral. Através dessas fases consecutivas, é possível que se desenvolvam ferramentas úteis para triagem populacional, capazes de serem implementadas na rotina clínica para predição de desfecho do paciente, resposta terapêutica e monitoramento da doença. O presente projeto avaliou o valor prognóstico dos principais genes citados na literatura como potenciais biomarcadores para CPNPC, e verificou-se que nenhum deles apresentou significância na correlação estatística que indica poder prognóstico. Além disso, identificamos e validamos o papel prognóstico da cofilina-1 por meio de dados de microarranjo e quantificação de seu imunoconteúdo em biópsias de CPNPC. Para tanto, fizemos uso de meta-análise de bancos de dados e análise densitométrica das reações imuno-histoquímicas, seguida de correlação com dados de grau de diferenciação tumoral, classificação histológica, sexo, idade e desfecho relativo a cada caso. Além disso, desenvolvemos um método de baixo custo, fácil execução e ampla aplicação e reproducibilidade, capaz de quantificar a proteína em amostras biológicas, com potencial para ser implementado na rotina clínica e aplicamos esse método em uma coorte restrospectiva de CPNPC. Confirmamos assim o papel prognóstico da cofilina-1. Estes achados seguem a lógica das fases de desenvolvimento de um biomarcador e representam um grande passo no seu processo de validação. / Lung cancer accounts for approximately 13% of all malignant tumor cases and for about 1.4 million deaths per year worldwide. This cancer has two main subtypes: Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC). About 85% of cases of lung cancer are NSCLC type. The signs and symptoms are secondary to the primary tumor growth, to regional lobe commitment and distant spread, or are secondary to paraneoplastic syndromes. These features reflect directly on mortality rates; 80 in every 100 new cases are inoperable and most die within 3 years. This means that, despite many advances in diagnosis treatment, the prognosis of lung cancer remains extremely poor, with median survival of 10 months, and total cumulative survival in 5-year of approximately 12%. Currently, prognosis and therapeutic decisions in patients with lung cancer is based on TNM. Although this procedure is considered gold standard among health professionals, it does not take into account the biological characteristics of the tumor. In this context, the identification of cancer biomarkers may add important information to the already established TNM system and result in better treatments and lower mortality rates. There are five distinct phases that conceptualize a tumor biomarker development of. Through these successive phases, it is possible to develop useful tools for population screening, capable of implementation in clinical practice for prediction of patient outcome, therapeutic response and disease monitoring. This project evaluated the prognostic value of major genes mentioned in literature as potential biomarkers for NSCLC and found that none of them showed statistical significance in the correlation that indicates prognostic power. It also identified and validated the prognostic role of cofilin-1 by microarray data and quantification of their immunocontent in biopsies of NSCLC. For this purpose, we used data metaanalysis and immunohistochemical reactions densitometric analysis, followed by correlation with data from tumor grade, histological classification, sex, age and outcome for each case. In addition, we developed a low-cost protocol, of easy implementation and wide application and reproducibility, able to quantify the protein in biological samples, with the potential to be implemented in clinical practice. We applied this method in a retrospective cohort of NSCLC and confirm the prognostic role of cofilin-1. These findings follow the logical phases of biomarker development and represent a major step in its validation process.

O câncer de pulmão é responsável por aproximadamente 13% do total de casos de neoplasias malignas e por cerca de 1.4 milhões de mortes por ano em todo mundo. Esta neoplasia apresenta-se sob dois principais subtipos: câncer de pulmão de pequenas células (CPPC) e câncer de pulmão de não-pequenas células (CPNPC). Cerca de 85% dos casos de câncer de pulmão são do tipo CPNPC. Os sinais e sintomas são secundários ao crescimento do tumor primário, ao comprometimento lobo-regional, à disseminação à distância, ou são secundários às síndromes paraneoplásicas. Essas características refletem diretamente sobre as taxas de mortalidade; de cada 100 novos casos, 80 são inoperáveis e a maioria morre dentro de 3 anos. Isso significa que, apesar dos diversos avanços no diagnóstico e tratamento, o prognóstico do câncer de pulmão permanece sendo extremamente ruim, com sobrevida média de 10 meses, e cumulativa total em 5 anos de aproximadamente 12%. Atualmente, o prognóstico e a decisão terapêutica de pacientes com câncer de pulmão é baseada no TNM, Embora esse seja o procedimento considerado padrãoouro entre os profissionais de saúde, ele não leva em consideração características biológicas do tumor. Nesse contexto, a identificação de biomarcadores para câncer pode agregar importantes informações ao já estabelecido sistema TNM e resultar em tratamentos mais eficientes e em menores taxas de mortalidade. Existem 5 fases distintas que conceitualizam o desenvolvimento de um biomarcador tumoral. Através dessas fases consecutivas, é possível que se desenvolvam ferramentas úteis para triagem populacional, capazes de serem implementadas na rotina clínica para predição de desfecho do paciente, resposta terapêutica e monitoramento da doença. O presente projeto avaliou o valor prognóstico dos principais genes citados na literatura como potenciais biomarcadores para CPNPC, e verificou-se que nenhum deles apresentou significância na correlação estatística que indica poder prognóstico. Além disso, identificamos e validamos o papel prognóstico da cofilina-1 por meio de dados de microarranjo e quantificação de seu imunoconteúdo em biópsias de CPNPC. Para tanto, fizemos uso de meta-análise de bancos de dados e análise densitométrica das reações imuno-histoquímicas, seguida de correlação com dados de grau de diferenciação tumoral, classificação histológica, sexo, idade e desfecho relativo a cada caso. Além disso, desenvolvemos um método de baixo custo, fácil execução e ampla aplicação e reproducibilidade, capaz de quantificar a proteína em amostras biológicas, com potencial para ser implementado na rotina clínica e aplicamos esse método em uma coorte restrospectiva de CPNPC. Confirmamos assim o papel prognóstico da cofilina-1. Estes achados seguem a lógica das fases de desenvolvimento de um biomarcador e representam um grande passo no seu processo de validação. / Lung cancer accounts for approximately 13% of all malignant tumor cases and for about 1.4 million deaths per year worldwide. This cancer has two main subtypes: Small Cell Lung Cancer (SCLC) and Non-Small Cell Lung Cancer (NSCLC). About 85% of cases of lung cancer are NSCLC type. The signs and symptoms are secondary to the primary tumor growth, to regional lobe commitment and distant spread, or are secondary to paraneoplastic syndromes. These features reflect directly on mortality rates; 80 in every 100 new cases are inoperable and most die within 3 years. This means that, despite many advances in diagnosis treatment, the prognosis of lung cancer remains extremely poor, with median survival of 10 months, and total cumulative survival in 5-year of approximately 12%. Currently, prognosis and therapeutic decisions in patients with lung cancer is based on TNM. Although this procedure is considered gold standard among health professionals, it does not take into account the biological characteristics of the tumor. In this context, the identification of cancer biomarkers may add important information to the already established TNM system and result in better treatments and lower mortality rates. There are five distinct phases that conceptualize a tumor biomarker development of. Through these successive phases, it is possible to develop useful tools for population screening, capable of implementation in clinical practice for prediction of patient outcome, therapeutic response and disease monitoring. This project evaluated the prognostic value of major genes mentioned in literature as potential biomarkers for NSCLC and found that none of them showed statistical significance in the correlation that indicates prognostic power. It also identified and validated the prognostic role of cofilin-1 by microarray data and quantification of their immunocontent in biopsies of NSCLC. For this purpose, we used data metaanalysis and immunohistochemical reactions densitometric analysis, followed by correlation with data from tumor grade, histological classification, sex, age and outcome for each case. In addition, we developed a low-cost protocol, of easy implementation and wide application and reproducibility, able to quantify the protein in biological samples, with the potential to be implemented in clinical practice. We applied this method in a retrospective cohort of NSCLC and confirm the prognostic role of cofilin-1. These findings follow the logical phases of biomarker development and represent a major step in its validation process.

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京都大学 / 新制・課程博士 / 博士(人間健康科学) / 甲第23121号 / 人健博第83号 / 新制||人健||6(附属図書館) / 京都大学大学院医学研究科人間健康科学系専攻 / (主査)教授 椎名 毅, 教授 藤井 康友, 教授 平井 豊博 / 学位規則第4条第1項該当 / Doctor of Human Health Sciences / Kyoto University / DFAM

Depuis peu, l’immunothérapie a émergé comme une nouvelle stratégie chez les patients atteint de Cancer Bronchique Non à Petites Cellules (CBNPC), confirmant ainsi le rôle du système immunitaire dans cette maladie. Malgré ces nouveaux traitements (thérapies ciblées, immunothérapie), les taux de réponses restent faibles avec un impact modeste sur la survie globale. Des biomarqueurs sont donc nécessaire pour définir les populations cibles de ces traitements. Une des pistes explorées est le statut immunitaire des patients, en effet celui-ci a un impact pronostic et pourrait influencer la réponse aux traitements standards tels que la chimiothérapie, les thérapies ciblées et même l’immunothérapie. Parmi les cellules du système immunitaire, les cellules Natural Killer (NK) auraient un rôle effecteur dans le CBNPC. Il est maintenant clairement établit que les cellules NK favorisent la mise en place d’une immunité adaptative fonctionnelle et efficace. Ainsi une altération des fonctions NK pourrait être un mécanisme associé à l’échappement à l’immunité adaptative de la tumeur. Dans notre première étude, nous avons mis en évidence que les exosomes de cellules dendritiques stimulaient les cellules NK via NKp30, cette activité étant associée à un gain de survie sans progression chez des malades inopérables porteurs d’un CBNPC avancé. Notre second projet a révélé, pour la première fois, un rôle pronostic des transcrits de NCR3 (gène de NKp30) chez des patients naïfs de tout traitement. L’activation des cellules NK via NKp30 pourrait être une stratégie efficace d’immunomodulation chez les patients atteints de CBNPC avancé. Ces travaux confirment le rôle important des cellules NK dans le CBNPC avancé. / Recently, immunotherapy has emerged as a new strategy in Non-Small Cell Lung Cancer (NSCLC) patients, confirming the key role of the immune system in this disease. Despite these new treatments (targeted therapies, immunotherapy), response rates remain low with a modest impact on overall survival. Biomarkers are needed to define the target population of these treatments. One of the options explored is the immune status; indeed the immune status of cancer patients has a prognosis impact and may influence the response to standard treatments such as chemotherapy, targeted therapies and even immunotherapy. Among the immune cells, Natural Killer cells (NK) have an effector role in NSCLC. It is now established that NK cells can promote a functional and efficient adaptive immunity. Therefore, an impaired NK functions could be a mechanism associated with the escape from adaptive immunity of the tumor. In our first study, we demonstrated that exosomes from dendritic cells stimulated NK cells through NKp30, this activity is being associated with improved survival in advanced NSCLC. Our second project has revealed, for the first time, a independent prognostic role of NCR3 transcript (NKp30 gene) for naïve advanced NSCLC. Activation of NK cells via NKp30 could be an effective strategy for immunomodulation in advanced NSCLC patients. These studies confirm a major role of NK cells in advanced NSCLC.