Triple-negative breast cancer (TNBC) is a clinically heterogeneous disease that is predominantly treated with chemotherapy. Although immune checkpoint inhibitors targeting the PD-1/PD-L1 axis, such as atezolizumab (ATZ), have expanded therapeutic options, their clinical benefit remains limited, emphasizing the need for strategies that improve efficacy without increasing toxicity. Metformin (MTF), a widely prescribed antidiabetic drug, has demonstrated anticancer properties and synergistic effects with chemotherapy and immunotherapy in several tumor models. This study evaluated whether adding MTF to a chemo-immunotherapy regimen could enhance outcomes in an in vivo TNBC model. In vitro experiments were performed to determine the IC50 values of MTF and doxorubicin (DOXO) in EMT6 breast cancer cells and to assess their combined effects. In vivo studies were conducted using BALB/c mice bearing subcutaneous EMT6 tumors. Treatment was initiated when tumor volumes reached 50-120 mm³ . DOXO and ATZ were administered intraperitoneally for two weeks, with DOXO given twice weekly and ATZ once weekly. ATZ was injected at least three hours after DOXO, and MTF was provided via drinking water. Tumor growth was monitored daily and compared among treatment groups. The addition of MTF enhanced the antitumor efficacy of low-dose DOXO (0.3 mg/kg) combined with ATZ, producing tumor-growth inhibition equivalent to that achieved with a 20-fold higher DOXO dose plus ATZ. After fourteen days, tumor volumes in the triplet therapy group were reduced compared with DOXO plus ATZ alone. Importantly, mice receiving the MTF-containing regimen maintained body weight, indicating no added toxicity. These findings support metformin as an adjunct to chemo-immunotherapy.

Neoadjuvant chemotherapy (NACT) is the standard treatment for muscle-invasive bladder carcinoma (MIBC), but its efficacy varies significantly among patients. The aim of this study is the identification of biomarkers and biological processes related to the response to neoadjuvant chemotherapy (NACT) in muscle-invasive bladder carcinoma (MIBC). Fifty-eight transurethral resection (TURBT) samples and thirty cystectomy samples from NACT non-responders were analyzed using mass spectrometry. Samples were classified with sparse k-means and consensus clustering. Protein networks were built using probabilistic graphical models, grouped into functional nodes, and analyzed for activity differences. Gene set enrichment analysis was applied to identify resistance mechanisms, and results were validated using The Cancer Genome Atlas (TCGA) cohort. Proteomic analysis revealed two independent classifications in TURBT samples. The first (Layer1) divided tumors into three groups, including one NACT non-responder subtype not aligned with traditional luminal or basal classifications but characterized by high expression of targetable markers NECTIN4 and Her2. The second (Layer3) separated luminal-papillary tumors from luminal-infiltrated/luminal and basal tumors. While Layer3 groups did not differ in NACT response, they showed distinct disease-free survival outcomes. Importantly, complete response to NACT was linked to improved survival in luminal subgroups but not in basal tumors, suggesting subtype-specific prognostic implications. Finally, analysis of cystectomy samples identified unique mechanisms of resistance for each subgroup, suggesting tailored therapeutic approaches. Two classification systems were defined as follows: one identified a proteomics-based non-responder group with actionable targets, and the other linked tumor subtype to prognosis. Distinct resistance mechanisms suggest opportunities for subtype-specific therapies, supporting improved management and treatment development for MIBC patients.

Breast cancer (BC) is a global health problem. BC is a biologically heterogeneous disease in which novel immunotherapeutic strategies are needed, particularly in the metastatic setting. The NKG2D/NKG2D ligand (NKG2DL) axis is a key component of innate antitumor immunity and represents a potential therapeutic target, but its relevance in BC has not been fully characterized. We performed an in silico analysis of NKG2DL expression in BC cell lines, healthy breast tissue, and tumor samples using publicly available transcriptomic databases (DSMZCellDive, ShinyTHOR, GTEx, TCGA, Human Protein Atlas), complemented by survival analyses from TCGA and KMPlot and a narrative review of the literature. NKG2DL transcripts were consistently expressed in BC cell lines and tumor tissues, with higher expression observed in ductal histology, higher tumor stage, and basal molecular subtype. Survival analyses showed heterogeneous and generally weak associations between individual NKG2DLs and clinical outcomes. In silico proteomics data are scarce, but the narrative review showed that NKG2DLs are expressed by immunohistochemistry in tumor tissues but absent in surrounding healthy tissues. The literature review also revealed concomitant dysfunction of NKG2D+ effector cells due to multiple resistance mechanisms (including ligand shedding). We also review potential therapeutic approaches.

4589 Background: Muscle-invasive bladder carcinoma (MIBC) poses significant challenges due to high recurrence and mortality rates, coupled with the toxicity of neoadjuvant chemotherapy (NACT). This has driven the search for biomarkers to improve treatment management and patient quality of life. Methods: Fifty-eight FFPE samples from MIBC patients obtained from transurethral resection (TURBT) were studied. Microbiota analysis was performed by amplification and sequencing of the V4 variable region of the 16S rRNA gene and using Qiime2 software for taxonomic identification. Proteins were extracted and digested from TURBT samples and analyzed by mass spectrometry with data-independent acquisition. For protein identification, a reference database was built, including both the human proteome and bacteria genera proteomes identified by 16S experiments. Proteomics data were processed with Perseus and analyzed using probabilistic graphical models (PGMs) and hierarchical clustering. Results: We have information about treatment response for 56 patients. Twenty-four patients achieved a pathological complete response (43%), with a median disease-free survival of 22 months, and a median overall survival of 29.23 months . 151 bacteria genera identified by 16S experiments, were included in the metaproteomics database. In proteomics experiments, 42 bacteria and 5,111 human proteins were identified. After applying quality criteria, 13 bacteria proteins were used for the subsequent analyses. Hierarchical clustering analysis identified three groups with different microbiota protein profiles: Microbiota1, Microbiota2 and Microbiota3. These groups showed significant differences in response to NACT. A higher proportion of non-responders (73%) vs. responders (27%) was observed in Microbiota2 compared to the other groups (54% in Microbiota1 and 36% in Microbiota2), whereas a predominance of responders (64%) was observed in Microbiota3 (46% in Microbiota1 and 27% in Microbiota2) (p= 0.0481). In a previous work, our group defined three proteomics-based groups related to response to NACT (Layer1 (1.1, 1.2 and 1.3)) (Pinto et al., SEOM 2024). Significant differences were also observed in the distribution of Layer1 between the microbiota clusters. Microbiota2 had a higher representation of patients belonging to Layer1.3, characterized by a majority of non-responders and Microbiota3 had a higher proportion of patients from Layer1.1. Conclusions: To our knowledge, this is the first metaproteomics study in FFPE samples from bladder carcinoma patients for biomarker discovery. Three distinct microbiota protein profiles were identified, one with higher proportion of non-responders. The potential role of these bacteria in NACT response needs further study, highlighting metaproteomics as a promising avenue for biomarker development.