Estudo retrospectivo de 119 pacientes com diagnóstico de adenocarcinoma ductal invasivo no estádio clínico III tratadas com quimioterapia neoadjuvante (FEC), mastectomia e adjuvância. Destas, 85 optaram por reconstrução mamária imediata (RMI) com retalho transverso músculo-cutâneo de reto-abdominal e 34, não. Com seguimento médio de 52,7 meses avaliou-se o tempo de hospitalização, a inter-relação com a adjuvância, recidiva local, o tempo livre de doença e o tempo total de sobrevida, concluindo-se que, apesar de aumentar o tempo de hospitalização, a RMI não interfere com os demais ítens, podendo ser indicada para pacientes portadoras de carcinoma mamário em estádio clínico avançado / A retrospective study with 119 patients diagnosed with invasive ductal adenocarcinoma of the breast treated with neoadjuvant chemotherapy (FEC), mastectomy and adjuvant therapy. Eight-five patients chose immediate breast reconstruction (IBR) with transverse rectus abdominis myocutaneous flap and, 34 did not do it. The mean follow-up was 52.7 months. Length of stay, adjuvant therapy interrelation, local recurrence, disease-free survival and overall survival were evaluated. It was concluded that despite a longer stay, IBR did not interfere with any of the other factors analyzed and may be indicated for patients with advanced breast disease

Pacientes com câncer de mama localmente avançado são submetidas à quimioterapia neoadjuvante na tentativa de reduzir a dimensão do tumor e aumentar a possibilidade da realização de uma cirurgia conservadora. Nosso grupo identificou previamente através da tecnologia de cDNA microarray, trios de genes, incluindo BZRP, CLPTM1, MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2 e XLHSRF-1, cuja expressão era capaz de predizer a resposta à quimioterapia neoadjuvante com doxorrubicina e ciclofosfamida em pacientes com câncer de mama. No presente estudo, avaliamos se a expressão destes genes é reprodutível na identificação de pacientes responsivas e não-responsivas através de RT-PCR em tempo real, que representa uma técnica mais acessível. Avaliamos inicialmente amostras de 28 pacientes anteriormente estudadas (grupo de validação técnica = 23 responsivas e cinco não-responsivas) e a seguir um grupo de 14 novas pacientes (grupo de validação biológica = 11 responsivas e três não-responsivas). Dentre os trios de genes inicialmente identificados, a expressão de RPL37A + XLHSRF-1 + NOTCH1 e RPL37A + XLHSRF-1 + NUP210 classificou corretamente 86% (24/28) das amostras do grupo de validação técnica e 71% (10/14) das amostras do grupo de validação biológica, através de análise de classificação discriminante. Desse modo, esses trios não demonstraram a mesma precisão em comparação com resultados de cDNA microarray. Uma nova análise combinatória foi realizada na procura do melhor modelo preditivo utilizando valores de expressão obtidos por RT-PCR em tempo real. Identificamos então um novo trio, composto pelos genes RPL37A, SMYD2 e MTSS1, cuja expressão classificou corretamente 93% das amostras do grupo de validação técnica (22/23 responsivas e 4/5 não-responsivas) e 79% do grupo de validação biológica (8/11 responsivas e 3/3 não-responsivas). Portanto, o teste apresentou 88% de sensibilidade e especificidade em detectar pacientes responsivas para o total de amostras analisadas. Ao verificarmos o poder de classificação do mesmo grupo de genes, utilizando os valores de expressão pela análise de cDNA microarray, observamos um resultado semelhante (91% de sensibilidade e especificidade em reconhecer as amostras responsivas). Dessa forma, demonstramos que o perfil de expressão gênica obtido com cDNA microarray é reprodutível através do uso de RT-PCR em tempo real. Um estudo integrando um maior número de pacientes e uma plataforma de cDNA microarray mais abrangente pode auxiliar na identificação de um modelo preditivo baseado em grupos de genes mais acurado para antever a resposta ao tratamento com quimioterapia baseada em doxorrubicina. / Patients with locally advanced breast cancer are submitted to primary chemotherapy as an attempt to reduce tumor dimension and increase breast conserving surgery rates. Our group has previously identified through cDNA microarray technology gene trios, including BZRP, CLPTM1, MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2 and XLHSRF-1, whose expression was capable of predicting response to neoadjuvant chemotherapy with doxorubicin and cyclophosphamide in breast cancer patients. In the current study, it was evaluated whether expression of these genes is reproducible in the identification of responsive and non-responsive patients by real time RT-PCR, which represents a more accessible technique. We initially evaluated samples from 28 patients earlier studied (technical validation group = 23 responsive and 5 non-responsive) and subsequent to a new 14 patients set (biological validation group = 11 responsive and three non-responsive). Among the initially identified gene trios, RPL37A + XLHSRF-1 + NOTCH1 and RPL37A + XLHSRF-1 + NUP210 expression correctly classify 86% (24/28) samples from the technical validation group and 71% (10/14) samples from the biological validation group, through discriminant classification analysis. Therefore, these trios didnt demonstrate the same precision as compared with cDNA microarray results. A new combinatorial analysis was also performed in search of the best predictive model using real time RT-PCR expression values. A new trio was identified, represented by RPL37A, SMYD2 and MTSS1 genes, whose expression correctly classified 93% samples from technical validation group (22/23 responsive and 4/5 non-responsive) and 79% samples from biological validation group (8/11 responsive samples and 3/3 non-responsive samples). Therefore, the test presented 88% sensibility and specificity in identifying responsive patients for all samples analyzed. By means of verifying the classification strength of the same gene group, using cDNA microarray expression values, we observed a similar result (91% sensibility and specificity in recognizing responsive samples). Thus, we demonstrated that gene expression profile obtained by cDNA microarray is reproducible through real time RT-PCR. A study integrating a larger number of patients and a more comprehensive cDNA microarray platform may help the identification of a more accurate predictive model based on gene groups to foresee response to doxorubicin-based chemotherapy treatment.

La Tomographie par Emission de Positons (TEP) au 18Fluoro-désoxyglucose (18F-FDG) est l’imagerie de référence pour la quantification in vivo du métabolisme glucidique des cellules tumorales. Elle permet, entre autre, de suivre les modifications du métabolisme tumoral en cours de chimiothérapie. Le cancer du sein regroupe différentes entités génomiques dont les comportements clinico-biologiques et la prise en charge thérapeutique divergent. L’objectif de cette thèse était d’étudier le lien entre ces diverses entités biologiques du cancer du sein et le comportement métabolique tumoral en cours de chimiothérapie néoadjuvante. Nous avons également extrait, parmi les différents paramètres métaboliques tumoraux des images TEP, les critères les plus robustes pour prédire dès la fin dès la première cure de chimiothérapie néoadjuvante la réponse histologique finale et la survie des patientes. Nous avons également appliqué un modèle de mesure de la perfusion tumorale, dérivée d’une acquisition dynamique du premier passage artériel et tumoral du 18F-FDG.Le premier article de cette thèse souligne l’impact majeur du phénotype tumoral sur le comportement métabolique en cours de chimiothérapie de la tumeur primitive mammaire. Les trois articles suivants montrent que, pour les tumeurs triple-négatives et HER2 positives, les modifications métaboliques tumorales observées par la TEP au 18F-FDG prédisent la réponse histologique complète à l’issue du traitement. Concernant le phénotype tumoral luminal/HER2 négatif, la réponse métabolique apporte surtout une information pronostique. L’imagerie TEP au 18F-FDG pourrait permettre dans un avenir proche de guider les choix thérapeutiques du clinicien, en proposant une alternative thérapeutique aux patientes non-répondeuses identifiées dès la première cure de chimiothérapie néoadjuvante. / Positron Emission Tomography (PET) with 18Fluoro-deoxyglucose (18F-FDG) is the reference imaging examination for in-vivo quantification of the glucidic metabolism of tumour cells. It allows for the monitoring of tumour metabolic changes during chemotherapy. Breast cancer comprises several distinct genomic entities with different biological characteristics and clinical behaviours, leading to different tailored treatments. The aim of this doctoral thesis was to evaluate the relationship between the different biological entities of breast cancer and the tumour metabolic behaviour during neoadjuvant chemotherapy. We have also retrieved, among the various metabolic parameters on PET images, the most reliable ones to predict, as early as after the first neoadjuvant cycle, the final tumour histologic response and patient’s outcome. We have also evaluated early changes in tumour blood flow, using a tumour first-pass model derived from an dynamic 18F-FDG-PET acquisition.The first article presented in this thesis has underlined the strong correlation between breast cancer subtypes, and the tumour metabolic behaviour during chemotherapy. The following three articles have demonstrated that tumour metabolic changes after the first neoadjuvant cycle can predict the final histologic complete response at the end of the treatment, both in triple-negative and HER2 positive tumours. Concerning the luminal/HER2 subtype, the early metabolic response mainly predicts patient’s outcome.These results should lead, in the near future, to PET-guided neoadjuvant strategies, in order to adapt the neoadjuvant treatment in poor-responding women. Such a strategy should lead to enhanced personalized medicine.