Molecular aspects of brain metastases in breast cancer

Metastatic brain tumors: from development to cutting-edge treatment

Metastatic brain tumors, also called brain metastasis (BM), represent a challenging complication of advanced tumors. Tumors that commonly metastasize to the brain include lung cancer and breast cancer. In recent years, the prognosis for BM patients has improved, and significant advancements have been made in both clinical and preclinical research. This review focuses on BM originating from lung cancer and breast cancer. We briefly overview the history and epidemiology of BM, as well as the current diagnostic and treatment paradigms. Additionally, we summarize multiomics evidence on the mechanisms of tumor occurrence and development in the era of artificial intelligence and discuss the role of the tumor microenvironment. Preclinically, we introduce the establishment of BM models, detailed molecular mechanisms, and cutting-edge treatment methods. BM is primarily treated with a comprehensive approach, including local treatments such as surgery and radiotherapy. For lung cancer, targeted therapy and immunotherapy have shown efficacy, while in breast cancer, monoclonal antibodies, tyrosine kinase inhibitors, and antibody-drug conjugates are effective in BM. Multiomics approaches assist in clinical diagnosis and treatment, revealing the complex mechanisms of BM. Moreover, preclinical agents often need to cross the blood-brain barrier to achieve high intracranial concentrations, including small-molecule inhibitors, nanoparticles, and peptide drugs. Addressing BM is imperative.

Investigating MATN3 and ASPN as novel drivers of gastric cancer progression via EMT pathways

Gastric cancer (GC) is a leading cause of cancer-related deaths globally, necessitating the identification of novel therapeutic targets. This study investigates the roles of MATN3 and ASPN in GC progression via the epithelial-mesenchymal transition (EMT) pathway. Analysis of the Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) dataset revealed that both MATN3 and ASPN are significantly upregulated in GC tissues and correlate with poor patient survival. Protein-protein interaction and co-expression analyses confirmed a direct interaction between MATN3 and ASPN, suggesting their synergistic role in EMT activation. Functional assays demonstrated that MATN3 promotes GC cell proliferation, migration, and invasion, while its knockdown inhibits these malignant behaviors and induces apoptosis. ASPN overexpression further amplified these oncogenic effects. In vivo, studies in a mouse model corroborated that co-overexpression of MATN3 and ASPN enhances tumor growth and metastasis. These findings highlight the MATN3-ASPN axis as a potential therapeutic target in GC, offering new insights into the molecular mechanisms driving GC progression.

Real-World Outcomes of Pyrotinib-Based Therapy for HER2-Positive Breast Cancer With Brain Metastases: A Multicentre, Retrospective Analysis

OBJECTIVE

This study was designed to investigate the efficacy and safety of pyrotinib-based therapy for HER2-positive breast cancer with brain metastases (BM) in the real-world setting.

METHODS

Data of HER2-positive breast cancer patients with BM treated with pyrotinib-based therapy from a multicetre, registered, real-world study were analyzed.

RESULTS

Among 45 female patients, the overall objective response rate (ORR) was 62.2%, higher in 1st/2nd-line than ≥ 3rd-line (71.0% vs. 42.9%, P = .072). The objective response rate of intracranial lesions (CNS-ORR) was 71.1 %, with a significantly higher CNS-ORR observed in the 1st or 2nd-line subgroup compared to that of ≥ 3rd-line subgroup (83.9% vs. 42.9%, P < .05). By the end of follow-up, 20 patients (44.4%) died, and the 1-year survival rate was 73.3%. The median progression-free survival (PFS) was 9.1 months (95% CI 6.7-11.5). Patients with 1 or 2 BM had a longer median PFS of 12.0 months compared to 7.7 months for those with ≥ 3 BM (P = .01). In addition, 1- or 2-line therapy and full dose exposure of pyrotinib of 320mg-400mg/day were associated with improved median PFS (all P > .05). The median intracranial PFS (CNS-PFS) was 11.4 months (95% CI 7.5-15.3). However, local intervention plus systemic treatment seemed to prolong CNS-PFS compared with systemic treatment alone (13.7 vs. 9.1 months, P = .128). Diarrhea was most common (88.9%), 24.4% grade 3.

CONCLUSIONS

The pyrotinib-based therapy is effective for HER-2 positive breast cancer with BM, especially in 1st- or 2nd-line treatment, with tolerable adverse events. However, insufficient dosing of pyrotinib may impair efficacy outcomes.

Targeting hypoxia in combination with paclitaxel to enhance therapeutic efficacy in breast and ovarian cancer

The poor vascularization of solid tumors results in oxygen-deprived areas within the tumor mass. This phenomenon is defined as tumor hypoxia and is considered to be a major contributor to tumor progression in breast and ovarian cancers due to hypoxia-cascade-promoted increased metastasizing capacity. Hence, targeting hypoxia is a strategic cancer treatment approach, however, the hypoxia-modulating drugs face several limitations in monotherapies. Here, we investigated the impact of the potent hypoxia-inducible factor inhibitory compound acriflavine on tumor cell proliferation, migration, and metabolism under hypoxic conditions. We identified that acriflavine inhibited the proliferation of breast and ovarian tumor cells. To model the potential benefits of additional hypoxia response inhibition next to standard chemotherapy, we combined acriflavine with a frequently used chemotherapeutic agent, paclitaxel. In most breast and ovarian cancer cell lines used, we identified additive effects between the two drugs. The most significant findings were detected in triple-negative breast cancer cell lines, where we observed synergism. The drug combination effectively impeded tumor growth and metastasis formation in an in vivo orthotopic triple-negative breast cancer model as well. Additionally, we demonstrated that an epithelial-mesenchymal transition inhibitory drug, rolipram, combined with acriflavine and paclitaxel, notably reduced the motility of hypoxic triple-negative breast cancer cells. In conclusion, we identified novel drug combinations that can potentially combat triple-negative breast cancer by inhibiting hypoxia signaling and hindering cell migration and metastasis formation.

Subdivision of M1 category and prognostic stage for de novo metastatic breast cancer to enhance prognostic prediction and guide the selection of locoregional therapy

BACKGROUND

Although de novo metastatic breast cancer (dnMBC) is acknowledged as a heterogeneous disease, the current staging systems do not distinguish between patients within the M1 or stage IV category. This study aimed to refine the M1 category and prognostic staging for dnMBC to enhance prognosis prediction and guide the choice of locoregional treatment.

METHODS

We selected patients with dnMBC from the SEER database (2010-2019), grouping them into training (N = 8048) and internal validation (N = 3450) cohorts randomly at a 7:3 ratio. An independent external validation cohort (N = 660) was enrolled from dnMBC patients (2010-2023) treated in three hospitals. Nomogram-based risk stratification was employed to refine the M1 category and prognostic stage, incorporating T/N stage, histologic grade, subtypes, and the location and number of metastatic sites. Both internal and external validation sets were used for validation analyses.

RESULTS

Brain, liver, or lung involvement and multiple metastases were independent prognostic factors for overall survival (OS). The nomogram-based stratification effectively divided M1 stage into three groups: M1a (bone-only involvement), M1b (liver or lung involvement only, with or without bone metastases), and M1c (brain metastasis or involvement of both liver and lung, regardless of other metastatic sites). Only subtype and M1 stage were included to define the final prognostic stage. Significant differences in OS were observed across M1 and prognostic subgroups. Patients with the M1c stage benefited less from primary tumor surgery in comparison with M1a stage.

CONCLUSION

Subdivision of the M1 and prognostic stage could serve as a supplement to the current staging guidelines for dnMBC and guide locoregional treatment.

Bridging the gap: Predicting brain metastasis in breast cancer

Chen et al explored clinicopathological features and prognostic factors, revealing advanced tumor stage, lung metastases, HER-2 overexpression, and triple-negative status as key contributors. Recent research connects astrocytes' role in brain metastasis with signaling pathways and the impact of Trastuzumab on HER-2 tumor survival. Factors such as positive HER2 status, lack of estrogen receptor expression, and liver metastasis are identified as additional risk factors. The routine use of magnetic resonance imaging, insights into gene mutations associated with metastasis, and the role of radiotherapy, including prophylaxis possibilities, is controversial in clinical practice. Understanding these risk factors in a multidisciplinary collaboration is precise for local treatments and targeted therapies, particularly for HER2+ tumors, impacting directly on longer survival.

Experimental models for cancer brain metastasis

Brain metastases are a leading cause of cancer-related mortality. However, progress in their treatment has been limited over the past decade, due to an incomplete understanding of the underlying biological mechanisms. Employing accurate in vitro and in vivo models to recapitulate the complexities of brain metastasis offers the most promising approach to unravel the intricate cellular and physiological processes involved. Here, we present a comprehensive review of the currently accessible models for studying brain metastasis. We introduce a diverse array of in vitro and in vivo models, including cultured cells using the Transwell system, organoids, microfluidic models, syngeneic models, xenograft models, and genetically engineered models. We have also provided a concise summary of the merits and limitations inherent to each model while identifying the optimal contexts for their effective utilization. This review serves as a comprehensive resource, aiding researchers in making well-informed decisions regarding model selection that align with specific research questions.