Neoadjuvância e metastização no tumor da mama - Estudo de biomarcadores numa série do Algarve - Susana, Liliana Maria Ferreira (2023)
Breast cancer in women is one of the most prevalent tumours nationally and worldwide. Is a type of cancer characterised by its complex aetiology and clinical, morphological, and molecular heterogeneity. We need to know specifically the populations that we attend. Evaluating parameters like histological type, grade, TMN staging, hormone receptors, HER2+ and ki67% status allows for an assessment of the different subtypes (Luminal-A, luminal-B, HER2+ enriched, basal like/Triple Negative (TNBC)), with predictive value regarding prognosis and future therapies. The introduction of neoadjuvant therapy in breast cancer allows for a better control of high-risk metastatic disease. Here, we characterise a series of patients from Algarve with breast cancer who underwent neoadjuvant chemotherapy. A retrospective study was conducted between January 2001 and August 2022, in the Barlavento region, with a total of 254 patients reported. The main years for diagnosis were: 2021 (15,4%), 2012 (9,8%), 2022 (8,3%) and 2016 (7,5%). Mean age was 51,909 ± 12,032 years and median age was 52 years, with ages ranging from 22 to 79 years old. The main subtypes (n=234) obtained were HR+ (37,2%), TNBC (21,8%), triple positive (11,1%) and ER+ (10,3%). The main molecular subtypes (n=104) were: Basal-like (35,6%), Luminal-A (25,0%) and Luminal-B (22,1% of all cases). We also verified a statistic association between the type of therapeutic response for QTNA and the histologic subtype where, for a complete response, there is a higher number of TNBC (p-value=0,000), HER2+ and triple positives tumours (p-value=0,000). From the results, it was possible to observe that the HER2+ subtype was not the most prevalent. Our population was younger than expected. It is crucial to characterize the population we treat. This study has given us a better characterization of the breast cancer problem in Algarve and provides a series of clues for future depth and analysis of this data.