In recent years, great progress has been achieved towards identifying novel biomarkers in lymphoid malignancies, including chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL), at the genomic, transcriptomic and epigenomic level for accurate risk-stratification and prediction of treatment response. In paper I, we validated the prognostic relevance of a recently proposed RNA-based marker in CLL, UGT2B17, and analyzed its expression levels in 253 early-stage patients. Besides confirming its prognostic impact in multivariate analysis, we could identify 30% of IGHV-mutated CLL (M-CLL) cases with high expression and poor outcome, which otherwise lacked any other poor-prognostic marker. In paper II, we investigated the prognostic impact of a previously reported 5 CpG signature that divides CLL patients into three clinico-biological subgroups, namely naive B-cell-like CLL (n-CLL), memory B-cell-like CLL (m-CLL) and intermediate CLL (i-CLL), in 135 CLL patients using pyrosequencing. We validated the signature as an independent marker in multivariate analysis and further reported that subset #2 cases were predominantly classified as i-CLL, although displaying a similar outcome as n-CLL. In paper III, we investigated the methylation status and expression level of miR26A1 in both CLL (n=70) and MCL (n=65) cohorts. High miR26A1 methylation was associated with IGHV-unmutated (U-CLL) and shorter overall survival (OS) in CLL, while it was uniformly hypermethylated in MCL. Furthermore, overexpression of miR26A1 resulted in significant downregulation of EZH2 that in turn led to increased apoptosis. In paper IV, we performed DNA methylation profiling in 176 CLL cases assigned to one of 8 major stereotyped subsets (#1-8) in relation to non-subset CLL (n=325) and different normal B-cell subpopulations. Principal component analysis of subset vs. non-subset CLL revealed that U-CLL and M-CLL subsets generally clustered with n-CLL and m-CLL, respectively, indicating common cellular origins. In contrast, subset #2 emerged as the first defined member of the i-CLL subgroup, which in turn alludes to a distinct cellular origin for subset #2 and i-CLL patients. Altogether, this thesis confirms the prognostic significance of RNA and epigenetic-based markers in CLL, provides insight into the mechanism of miRNA deregulation in lymphoid malignancies and further unravels the DNA methylation landscape in stereotyped subsets of CLL.

Le cancer du sein inflammatoire (CSI) est l’une des formes la plus agressive en raison de son potentiel métastatique élevé. Le diagnostic est basé sur des signes cliniques avec une émergence rapide, mais en réalité ces signes sont subjectifs et non spécifiques. Malgré le traitement multidisciplinaire, le pronostic reste mauvais avec une survie à 5 ans inférieure à 50% vs 90% dans le cancer du sein non inflammatoire (CSNI). Les CSI sont rares en Europe et aux Etats-Unis, représentant moins de 2% du CS. En Afrique du Nord et en particulier en Tunisie, ils représentent plus de 5% des CS. Notre équipe a trouvé des gènes significativement plus sur-exprimés dans CSI dans une signature moléculaire indépendante des sous-types moléculaires et était composé de 79 gènes. Nous nous sommes intéressés particulièrement à MARCKS qui code pour le substrat majeur de la protéine kinase C. Dans le cadre de cette thèse, nous avons tenté de mieux comprendre les aspects épidémiologiques et cliniques des CSI associés à une distribution géographique différente. Nous analyserons les caractéristiques histo-cliniques et de pronostic sur une série de 219 patientes de CSI traitées à l'Institut Salah Azaiez (Tunis) de 2008 à 2013. Les résultats de cette série historique tunisienne ont été comparés à ceux de la littérature. Évaluer si la protéine MARCKS pourrait être un nouveau marqueur spécifique du CSI par une analyse IHC sur des échantillons de tumeurs CSI et CSNI de patientes française et tunisiennes (N = 502). Les corrélations entre l'expression de MARCKS et les critères cliniques et biologiques ont été établies. / Inflammatory Breast Cancer (IBC is one of the most aggressive breast cancers due its high metastatic potential. The diagnostic is based on clinical signs with rapid emergence but in reality these signs are subjective and non-specific. Despite the multi-modality treatment, the prognosis remains poor with survival in 5-year inferior to 50% vs 90% in non-Inflammatory Breast Cancers (non-IBC). IBC were rare in Europe and USA, represented at least 2% of breast cancer (BC), more frequent in North Africa and particularly in Tunisia which they present more than 5% of BC. Our team has found genes most significantly over-expressed in IBC given a molecular signature independent from the molecular subtypes and was composed of 79 genes. We were interested particularly to MARCKS gene that encodes for the major substrate of protein kinase C. As part of this thesis, we have attempted to better understand the epidemiological and clinical aspects of IBCs associated with a different geographical distribution. We will analyze the histo-clinical characteristics and the prognosis on a series of 219 patients with IBC treated at the Salah Azaiez Institute (Tunis) from 2008 to 2013. The results of this historical Tunisian series were compared with those of literature. Evaluate whether MARCKS protein could be a new specific marker for IBC by an IHC analysis on IBC and non-IBC tumor samples of French and Tunisian patients (N=502). Correlations between the expression of MARCKS and clinical and biological criteria were established.

Les gliomes ont des conséquences dévastatrices. La morbidité et la mortalité sont élevées. Les gliomes représentent un groupe hétérogène complexe d'entités pathologiques et aucune cause n'a été identifiée pour la majorité des gliomes. Les données épidémiologiques varient d'une étude à l'autre. Le nombre de chaque sous-type histologique est trop petit, même pour un grand centre de neurochirurgie, pour permettre une bonne recherche sur chaque sous-type de gliome. Les spécificités oncologiques et cliniques (épilepsie, troubles cognitifs, troubles moteurs, etc.) nécessitent une prise en charge et une analyse spécifique. De plus, il est important de recueillir et d'enregistrer tous les nouveaux cas et le suivi sur une grande région ou un pays entier pour permettre des études fondamentales et cliniques de qualité. En effet, les études en population sont la seule façon de connaitre l'impact en pratique des différentes thérapeutiques effectuées. Les sociétés françaises impliquées en neuro-oncologie (Société Française de Neurochirurgie, Société Française de Neuropathologie, Association des Neuro-Oncologues d'Expression Française) ont récemment créé le Recensement national histologique des tumeurs primitives du système nerveux central (RnhTPSNC) ou French Brain Tumor DataBase (FBTDB) en anglais. L'objectif principal du RnhTPSNC est d'enregistrer de manière prospective tous les cas incidents de tumeur primitive du système nerveux central (TPSNC), en France, pour lesquels le diagnostic histologique est confirmé (1-3). Les objectifs à long terme du RnhTPSNC sont de créer un registre histologique et un réseau national pour : (1) réaliser des études épidémiologiques, (2) mettre en place une base de données pour favoriser toute étude clinique ou fondamentale à grande échelle, (3) permettre l'évaluation des pratiques médicales d'une région ou du pays tout entier, (4) harmoniser et optimiser la prise en charge médicale des patients atteints de TPSNC. La présente étudiante en thèse, Sonia Zouaoui, concentrera son travail sur les gliomes. D'abord, elle devra recueillir les données des patients, puis analyser les facteurs pronostiques, la survie et les prises en charges oncologiques. Deuxièmement, elle participera à l'étude de la répartition géographique des principaux types de gliomes et à la recherche de facteurs de causaux. Troisièmement, elle procédera à un inventaire du matériel cryopréservé disponible pour la réalisation d'études translationnelles. / Gliomas have devastating consequences. Morbidity and mortality are high. Gliomas represent a complex heterogeneous group of pathologic entities and no underlying cause has been identified for the majority of them. Epidemiologic data vary from study to study. The number of each histological subtype is too small, even for a big neurosurgical center, to allow a good research on each subtype of glioma. Oncological and clinical specificities (epilepsy, cognitive disorders, motor impairments, etc) require a specific care and analysis. Indeed, we need to collect and record all new cases and follow up in large area, to allow good basic and clinical studies. Furthermore, population study is the only way to know what clinicians do to the patients, and make possible evaluating the medical care. The French societies involved in Neuro-Oncology (Société Française de Neurochirurgie, Société Française de Neuropathologie, Association des Neuro-Oncologues d'Expression Française) have recently created the French Brain Tumor DataBase (FBTDB). The main objective of the FBTDB is to prospectively record all primary central nervous system tumors (PCNST), in France, for which histological diagnosis is available (1-3). The long-term goals of the FBTDB are to create a histological national registry and a national network to (1) perform epidemiological studies, (2) implement a new database and use it for setting up both clinical and basic research protocols, (3) allow the evaluation of the medical practices of an area or of the entire country, and (4) harmonize the healthcare of patients affected by PCNST at the higher level. The present PhD student, Sonia Zouaoui, will focus her work on gliomas. First, she will collect data, and will analyze prognostic factors, survival and oncological patterns of care for patients with newly diagnosed glioma in France. Secondly, she will participate in the study of geographical distribution of the main types of glioma and in search of causal factors. Thirdly, she will conduct an inventory of cryopreserved material available for translational research.

The study explored whether certain factors might be used to distinguish between people with cancer who do or do not want detailed information about their disease progress, do or do not want to be informed if their disease is no longer considered curable, and who do or do not want an estimation of life expectancy if their disease is no longer considered curable. The factors included whether an individual has an internal versus external locus of control, uses an active coping strategy or a planning coping strategy, the level of spirituality, and age. Participants consisted of 51 people with cancer from a cancer center in the state of Washington. Results indicated that 98% wanted detailed information about their disease progress, 94% wanted to be informed if their disease was no longer considered curable, and 78% wanted an estimation of life expectancy if their disease was no longer considered curable. Due to the majority of the participants endorsing the need for prognostic information none of the factors (e.g. coping strategies, locus of control, spirituality) were able to predict the information needs of the patients with cancer. Clinical implications of this study suggest that physicians have an ongoing, open dialogue with their patients about their prognostic information needs. The dialogue might be especially important for patients undergoing active treatment for cancer, since it could affect treatment decisions.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2017-07-12T15:39:14Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Dissertação Juan Luiz Coelho da Silva.pdf: 2693101 bytes, checksum: b946d507d9f21698d6349e8ecf91e259 (MD5) / Made available in DSpace on 2017-07-12T15:39:14Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Dissertação Juan Luiz Coelho da Silva.pdf: 2693101 bytes, checksum: b946d507d9f21698d6349e8ecf91e259 (MD5) Previous issue date: 2016-03-11 / FACEPE / Algumas evidências destacam mutações no gene ASXL1 como um evento importante na evolução clínica de pacientes com neoplasias hematológicas, particularmente em leucemias mieloides agudas e síndrome mielodisplásicas. Contudo, seu impacto prognóstico em neoplasias mieloproliferativas (NMP) ainda é pouco explorado. Aqui, nós caracterizamos 208 pacientes com NMP cromossomo Filadélfia (Ph) negativo (policitemia vera, PV; trombocitemia essencial, TE; mielofibrose primária, MFP), de acordo com mutações no gene ASXL1, e correlacionamos esses achados com características clinico-laboratoriais desses pacientes. A pesquisa das mutações foi realizada por sequenciamento sanger, em que polimorfismos germinativos e mutações sinonímias foram excluídas das análises. Mutações no ASXL1 foram detectadas em 22/208 pacientes (10%), das quais quatro foram observadas em pacientes com PV (4/54; 7%), onze em pacientes com TE (11/123; 9%) e sete com MFP (7/31; 22%). As características clínicas e laboratoriais foram similares entre pacientes com ASXL1 mutado e não mutado. Quando as entidades foram avaliadas individualmente (PV, TE e MFP), observou-se associação entre mutações no ASXL1 e idade mais avançada em pacientes com TE (P = 0,049) e desenvolvimento de esplenomegalia em pacientes com MFP (P = 0,026). Com uma mediana de seguimento de 5,1 anos (IC95%: 4,5 a 7,3 anos), 136 pacientes (65%) desenvolveram algum tipo de manifestação clínica, sendo o desenvolvimento de complicações vasculares o mais frequente (n=54; 26%), seguido por esplenomegalia (n=47; 22%), eventos hemorrágicos (n=30; 14%) e trombose (n=21; 10%). Mutações no gene ASXL1 não foram associadas com o desenvolvimento das referidas manifestações. Dentro deste seguimento, apenas dois pacientes evoluíram para síndrome mielodisplásica e um para leucemia mieloide aguda, todos sem mutações no gene ASXL1. / Accumulating evidences report mutation in ASXL1 as an important predictor to clinical outcomes of patients with hematological malignancies, particularly acute myeloid leukemia and myelodysplastic syndrome. However, the prognostic impact in myeloproliferative neoplasm (MPN) remains underexplored. Here, we evaluated clinical and laboratory features of 208 Philadelphia negative MPN patients (polycythemia vera, PV; essential thrombocythemia, ET; primary myelofibrosis, PMF), according to mutations in ASXL1. Screening for ASXL1 mutations were performedby Sanger sequencing. Germline variations were excluded. ASXL1 mutations were detected in 22/208 patients (10%), of which four in PV patients (4/54-7%), 11 in ET patients (11/123-9%) and seven in PMF (7/31-22%). Baseline features were similar between ASXL1-mutated and non-mutated patients. Evaluated individually (PV, ET, PMF), we observed that ET patients harboring ASXL1 mutations were older (P = 0,049) than ASXL1 non-mutated patients. Similarly, PMF patients presented higher frequency of splenomegaly in ASXL1mutated group (P = 0,026). No other features were associated with ASXL1mutations. The median follow-up was 5,1 years (CI95%: 4,5-7,3 years). One hundred and thirty six patients (65%) developed some of the clinical common manifestations, which the most frequent was vascular complications (n=54; 26%), followed by splenomegaly (n=47; 22%), bleeding (n=30;14%) and thrombosis (n=21;10%). ASXL1 mutations were not associated with development of such events. In our cohort, only two patients have evolved for myelodysplastic syndrome and one for acute myeloid leukemia, all of them without mutations in ASXL1.

Estudos de prognóstico clínico consistem na predição do curso de uma doença em pacientes e são utilizados por profissionais da saúde com o intuito de aumentar as chances ou a qualidade de sua recuperação. Sob a perspectiva computacional, a criação de um modelo prognóstico clínico é um problema de classificação, cujo objetivo é identificar a qual classe (dentro de um conjunto de classes predefinidas) uma nova amostra pertence. Este projeto visa a criar modelos prognósticos de lesões traumáticas do plexo braquial, um conjunto de nervos que inervam os membros superiores, utilizando dados de pacientes adultos com esse tipo de lesão. Os dados são provenientes do Instituto de Neurologia Deolindo Couto (INDC) da Universidade Federal do Rio de Janeiro (UFRJ) e contêm dezenas de atributos clínicos coletados por meio de questionários eletrônicos. Com esses modelos prognósticos, deseja-se identificar de maneira automática os possíveis preditores do curso desse tipo de lesão. Árvores de decisão são classificadores frequentemente utilizados para criação de modelos prognósticos, por se tratarem de um modelo transparente, cujo resultado pode ser examinado e interpretado clinicamente. As Florestas Aleatórias, uma técnica que utiliza um conjunto de árvores de decisão para determinar o resultado final da classificação, podem aumentar significativamente a acurácia e a generalização dos modelos gerados, entretanto ainda são pouco utilizadas na criação de modelos prognósticos. Neste projeto, exploramos a utilização de florestas aleatórias nesse contexto, bem como a aplicação de métodos de interpretação de seus modelos gerados, uma vez que a transparência do modelo é um aspecto particularmente importante em domínios clínicos. A estimativa de generalização dos modelos resultantes foi feita por meio de métodos que viabilizam sua utilização sobre um número reduzido de instâncias, uma vez que os dados relativos ao prognóstico são provenientes de 44 pacientes do INDC. Além disso, adaptamos a técnica de florestas aleatórias para incluir a possível existência de valores faltantes, que é uma característica presente nos dados utilizados neste projeto. Foram criados quatro modelos prognósticos - um para cada objetivo de recuperação, sendo eles a ausência de dor e forças satisfatórias avaliadas sobre abdução do ombro, flexão do cotovelo e rotação externa no ombro. As acurácias dos modelos foram estimadas entre 77% e 88%, utilizando o método de validação cruzada leave-one-out. Esses modelos evoluirão com a inclusão de novos dados, provenientes da contínua chegada de novos pacientes em tratamento no INDC, e serão utilizados como parte de um sistema de apoio à decisão clínica, de forma a possibilitar a predição de recuperação de um paciente considerando suas características clínicas. / Studies of prognosis refer to the prediction of the course of a disease in patients and are employed by health professionals in order to improve patients\' recovery chances and quality. Under a computational perspective, the creation of a prognostic model is a classification task that aims to identify to which class (within a predefined set of classes) a new sample belongs. The goal of this project is the creation of prognostic models for traumatic injuries of the brachial plexus, a network of nerves that innervates the upper limbs, using data from adult patients with this kind of injury. The data come from the Neurology Institute Deolindo Couto (INDC) of Rio de Janeiro Federal University (UFRJ) and they are characterized by dozens of clinical features that are collected by means of electronic questionnaires. With the use of these prognostic models we intended to automatically identify possible predictors of the course of brachial plexus injuries. Decision trees are classifiers that are frequently used for the creation of prognostic models since they are a transparent technique that produces results that can be clinically examined and interpreted. Random Forests are a technique that uses a set of decision trees to determine the final classification results and can significantly improve model\'s accuracy and generalization, yet they are still not commonly used for the creation of prognostic models. In this project we explored the use of random forests for that purpose, as well as the use of interpretation methods for the resulting models, since model transparency is an important aspect in clinical domains. Model assessment was achieved by means of methods whose application over a small set of samples is suitable, since the available prognostic data refer to only 44 patients from INDC. Additionally, we adapted the random forests technique to include missing data, that are frequent among the data used in this project. Four prognostic models were created - one for each recovery goal, those being absence of pain and satisfactory strength evaluated over shoulder abduction, elbow flexion and external shoulder rotation. The models\' accuracies were estimated between 77% and 88%, calculated through the leave-one-out cross validation method. These models will evolve with the inclusion of new data from new patients that will arrive at the INDC and they will be used as part of a clinical decision support system, with the purpose of prediction of a patient\'s recovery considering his or her clinical characteristics.

Orientador: Robson Francisco Carvalho / Resumo: Adenocarcinoma ductal do pâncreas (PDAC) é extremamente agressivo, possui prognóstico desfavorável e não existem biomarcadores satisfatório para a doença ou identificação de indivíduos com alto risco de morbidade e mortalidade. A complexidade celular e molecular do câncer de pâncreas leva a inconsistências nas validações clínicas de muitas proteínas que foram avaliadas como biomarcadores prognósticos da doença. O secretoma tumoral desempenha um papel crucial na proliferação e metástase de células PDAC, bem como na resistência a tratamentos terapêuticos, que juntos contribuem para um pior resultado clínico. Assim, a enorme quantidade de dados proteômicos do câncer de pâncreas que foram gerados a partir de diferentes tipos de amostras e técnicas de espectrometria de massa pode ser integrada para a seleção de proteínas secretadas compartilhadas relevantes para o diagnóstico e prognóstico da doença. O objetivo do presente estudo foi realizar uma meta-análise combinando dados do proteoma do câncer de pâncreas e secretome publicamente para identificar novos potenciais biomarcadores de doenças. Realizamos uma meta-análise integrando dados de espectrometria de massa obtidos de duas revisões sistemáticas da literatura sobre câncer de pâncreas, que selecionaram independentemente 20 estudos do secretoma e 35 do proteoma. Em seguida, realizamos análises de predição de proteínas secretadas usando sete ferramentas ou bancos de dados “in silico”, que identificaram 39 proteínas compartilhada... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis and there are no satisfactory biomarkers for the disease or identification of individuals at high risk of morbidity and mortality. The cellular and molecular complexity of pancreatic cancer leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. Tumor secretome plays a crucial role in PDAC cell proliferation and metastasis, as well as in resistance to therapeutic treatments, which together contribute to a worse clinical outcome. Thus, the massive amount of proteomic data from pancreatic cancer that have been generated from different studies can be integrated into the selection of shared secreted proteins relevant to the prognosis of the disease. The aim of the present study was to perform a metaanalysis combining pancreatic cancer proteome and secretome publicly data to identify new potential disease biomarkers. We performed a meta-analysis integrating mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we performed prediction analyses of secreted proteins using seven “in silico” tools or databases, which identified 39 proteins shared between the secretome and the proteome data. Notably, the expression of 31 genes of these proteins was upregulated in pancreatic adenocarcinoma samp... (Complete abstract click electronic access below) / Doutor

京都大学 / 0048 / 新制・論文博士 / 博士(社会健康医学) / 乙第13292号 / 論社医博第13号 / 新制||社医||10(附属図書館) / (主査)教授 川上 浩司, 教授 平井 豊博, 教授 伊達 洋至 / 学位規則第4条第2項該当 / Doctor of Public Health / Kyoto University / DFAM

Objectives: Ductal carcinoma in situ (DCIS) is a non-invasive lesion of an increasing clinical importance. Individual risk assessment is essential for an optimal treatment. Our objective was to identify clinical and molecular characteristics of a subgroup of DCIS with an unfavorable prognosis. Methods: In a population study, we analyzed women with DCIS diagnosed within one mammography screening unit. In the experimental part of this work, we conducted a comparative analysis of five biological markers in normal tissue, DCIS and invasive breast cancer by means of gene expression analysis and analysis of loss of heterozygosity (LOH). Results: We demonstrated a high proportion of pure (no invasive component) DCIS (14.41%) of all breast lesions described as malignant. In our sample, we saw a homogeneous distribution of risk factors without noting a clear pattern identifying high-risk subtypes. We noted significant differences in clinical management of tumors with similar characteristics, which demonstrates the present state of limited use of clinical predictors. In the laboratory experiment, we showed differences in loss of heterozygosity (LOH) between DCIS and invasive breast cancer for BRCA1 (8.69% vs. 44.74%) and BRCA2 (9.52% vs. 45.0%). In contrast, we did not find any differences for p53 (31.82%...

Es wurden 177 Patientinnen mit zwischen 1999 und 2005 an der Universitätsfrauenklinik Leipzig operativ therapiertem Mammakarzinom und vorangegangener Stanzbiopsie, für die vollständige Befunde vorlagen und bei denen keine neoadjuvante Chemotherapie stattfand, hinsichtlich der prognostischen und prädiktiven Faktoren und deren Vergleich zwischen Stanzbiopsie und dem endgültigen Tumorexzidat untersucht. Unsere Daten zeigten, dass die Stanzbiopsie in der Einschätzung des Differenzierungsgrades mit einer Konkordanz von 62,9% und der Lymphgefäßinvasion mit einer Konkordanz in 69,8% keine hohe Genauigkeit besitzt. Bezüglich des histologischen Typs mit einer Übereinstimmung von 77%, der Östrogen- und Progesteronrezeptorbestimmung mit Konkordanzen von 87% und 83% sowie hinsichtlich des Her-2/neu-Status mit einer Konkordanz von 79% fand sich eine moderate bis gute Übereinstimmung mit dem Exzidat, wobei zu diskutieren ist, ob bei initial an der Stanzbiopsie negativem Östrogen- und/oder Progesteronrezeptorstatus oder auch bei positivem Progesteronrezeptor- und negativem Östrogenrezeptornachweis eine erneute immunhistochemische Hormonrezeptoruntersuchung am Exzidat erfolgen sollte sowie ob bei einer Konkordanzrate des Her-2/neu von weniger 95% immer eine zweite Bestimmung am Operationspräparat als Basis einer definitiven Therapieplanung durchgeführt werden muß. In 8,5% wurde an der Biopsie keine Malignität festgestellt. Der Vergleich des Malignitätsgrades mit der Tumorkategorie als auch mit dem Lymphknotenstatus zeigte keine signifikante Korrelation. Eine fortgeschrittene Tumorkategorie war mit dem Vorhandensein von Lymphknotenmetastasen korreliert.:1.Einleitung 2 1.1 Epidemiologie des Mammakarzinoms 2 1.2 Ätiologie und Pathogenese des Mammakarzinoms 2 1.2.1 Risikofaktoren des Mammakarzinoms 2 1.2.2 Molekulare Subtypisierung des Mammakarzinoms 4 1.3 Histologische Typen des Mammakarzinoms 6 1.4 Histopathologisches Grading des Mammakarzinoms 8 1.5 Metastasierung des Mammakarzinoms 9 1.6 Hormonrezeptoren und Her-2/neu 11 1.6.1 Östrogen- und Progesteronrezeptoren 11 1.6.2 Her-2/neu-Rezeptor 14 1.7 Prognostische und prädiktive Faktoren 14 1.7.1 Der histologische Typ als prognostischer Faktor 15 1.7.2 Das Grading als prognostischer Faktor 16 1.7.3 Lymphgefäßinvasion als prognostischer Faktor 17 1.7.4 Östrogen- und Progesteronrezeptorstatus als prognostischer und prädiktiver Faktor 18 1.7.5 Her-2/neu als prognostischer und prädiktiver Faktor 19 1.7.6 Tumorgröße und Lymphknotenstatus als prognostische Faktoren 20 1.8 Diagnostik des Mammakarzinoms 21 1.9 Therapie des Mammakarzinoms 24 1.9.1 Operative Therapie 24 1.9.2 Strahlentherapie 25 1.9.3 Adjuvante systemische Therapie 25 1.9.4 Primäre systemische Therapie 26 2. Zielstellung 28 3. Patientinnen, Material und Methoden 30 3.1 Datenerhebung 30 3.2 Histopathologische Aufarbeitung und Befunderhebung 30 3.3 Immunhistochemische Hormonrezeptorbestimmung und Her-2/neu-Analyse 31 3.4 Statistische Auswertung 34 4. Ergebnisse 4.1 Altersverteilung des Patientinnenkollektivs 35 4.2 Vergleich des histologischen Tumortyps zwischen Stanzbiopsie und Exzidat 35 4.3 Vergleich des histopathologischen Malignitätsgrades zwischen Stanzbiopsie und Tumorexzidat 41 4.4Vergleich der Lymphgefäßinvasion zwischen Stanzbiopsie und Tumorexzidat 44 4.5 Vergleich des Östrogen- und Progesteronrezeptorstatus zwischen Stanzbiopsie und Tumorexzidat 46 4.5.1 Östrogenrezeptoren 46 4.5.2 Progesteronrezeptoren 47 4.5.3 Her-2/neu-Rezeptorstatus 48 4.5.4 Vergleichende Darstellung der Östrogen- mit den Progesteronrezeptoren sowie der Hormonrezeptoren mit dem Her-2/neu-Status 51 4.6 Fehlender Nachweis von Malignität an der Stanzbiopsie 55 4.7 Vergleichende Auswertung des histopathologischen Malignitätsgrades und der lokalen Tumorausdehnung (pT) am endgültigen Tumorexzidat 57 4.8 Vergleichende Auswertung des Differenzierungsgrades und des Lymphknotenstatus (pN) zum Zeitpunkt der Operation 58 4.9 Vergleichende Auswertung der lokalen Tumorausdehnung (pT) und des Lymphknotenstatus (pN) zum Zeitpunkt der Operation 60 4.10 Zusammenfassung der Ergebnisse 62 5. Diskussion 63 5.1 Der histologische Typ 63 5.2 Der histologische Malignitätsgrad 65 5.3 Lymphgefäßinvasion 67 5.4 Hormonrezeptorstatus 67 5.5 Her-2/neu-Status 70 5.6 Vergleich des Malignitätsgrades mit der lokalen Tumorausdehnung und dem Lymphknotenstatus 73 6. Zusammenfassung 74 Tabellenverzeichnis 77 Abbildungsverzeichnis 79 Literaturverzeichnis 81 Erklärung 95 Danksagung 96