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Biomedical subjects

Susana Bravo

Publications and source records attributed to Susana Bravo.

2 recordsLinked to original sources

Bovine Colostrum-Derived Extracellular Vesicles Impair Cancer Cell Proliferation Through Transcriptional Dysregulation.

Milk-derived extracellular vesicles (EVs) are a promising source of molecules with therapeutic potential. Bovine colostrum is particularly enriched in EVs, which carry cargo of proteins involved in immune regulation, development and cellular signalling. Some studies have explored their role as bioactive anti-cancer agents, however, their mechanistic effects remain underexplored. Here, we show that colostrum-derived EVs (Col-EVs) exert anti-proliferative effects in gastrointestinal cancer models, including cell lines and patient-derived organoids, which is independent of apoptosis induction. Using a multi-modal approach combining proteomics, imaging and functional assays, we demonstrate that Col-EVs induce a reversible growth-arrest state, characterized by widespread transcriptional and RNA-processing dysregulation, chromatin compaction, nuclear reorganization and cytoskeletal remodelling. Proteomic analyses reveal that Col-EV treatment disrupts key components of the transcriptional machinery and cell cycle regulatory pathways, effects that are reversible upon EV withdrawal and can be rescued pharmacologically using an EZH2 inhibitor. Col-EVs enhance the sensitivity of cancer cells as well to DNA-targeting chemotherapies such as 5-fluorouracil, indicating their potential as modulatory adjuvants rather than cytotoxic agents. Overall, our findings reveal that Col-EVs can reversibly suppress cancer cell proliferation by reprogramming transcriptional and nuclear architecture, offering a natural, biocompatible strategy for modulating tumour growth and sensitizing cancer cells to conventional therapies.

Extracellular Vesicles

Identification of a Proteomic Signature for Predicting Immunotherapy Response in Patients With Metastatic Non-Small Cell Lung Cancer.

Immunotherapy has improved survival rates in patients with cancer, but identifying those who will respond to treatment remains a challenge. Advances in proteomic technologies have enabled the identification and quantification of nearly all expressed proteins in a single experiment. Integrating mass spectrometry with high-throughput technologies has facilitated comprehensive analysis of the plasma proteome in cancer, facilitating early diagnosis and personalized treatment. In this context, our study aimed to investigate the predictive and prognostic value of plasma proteome analysis using the SWATH-MS (Sequential Window Acquisition of All Theoretical Mass Spectra) strategy in newly diagnosed patients with non-small cell lung cancer (NSCLC) receiving pembrolizumab therapy. We enrolled 64 newly diagnosed patients with advanced NSCLC treated with pembrolizumab. Blood samples were collected from all patients before and during therapy. A total of 171 blood samples were analyzed using the SWATH-MS strategy. Plasma protein expression in metastatic NSCLC patients prior to receiving pembrolizumab was analyzed. A first cohort (discovery cohort) was employed to identify a proteomic signature predicting immunotherapy response. Thus, 324 differentially expressed proteins between responder and non-responder patients were identified. In addition, we developed a predictive model and found a combination of seven proteins, including ATG9A, DCDC2, HPS5, FIL1L, LZTL1, PGTA, and SPTN2, with stronger predictive value than PD-L1 expression alone. Additionally, survival analyses showed an association between the levels of ATG9A, DCDC2, SPTN2 and HPS5 with progression-free survival (PFS) and/or overall survival (OS). Our findings highlight the potential of proteomic technologies to detect predictive biomarkers in blood samples from NSCLC patients, emphasizing the correlation between immunotherapy response and the idenfied protein set.

Humans