Tailoring therapies to counter the divergent immune landscapes of breast cancer

Role of ENPP1 in cancer pathogenesis: Mechanisms and clinical implications (Review)

Cancer is a significant societal, public health and economic challenge in the 21st century, and is the primary cause of death from disease globally. Ectonucleotide pyrophosphatase/phosphodiesterase (ENPP) serves a crucial role in several biochemical processes, including adenosine triphosphate hydrolysis, purine metabolism and regulation of signaling pathways. Specifically, ENPP1, a type II transmembrane glycoprotein and key member of the ENPP family, may be upregulated in tumor cells and implicated in the pathogenesis of multiple human cancers. The present review provides an overview of the structural, pathological and physiological roles of ENPP1 and discusses the potential mechanisms of ENPP1 in the development of cancers such as breast, colon, gallbladder, liver and lung cancers, and also summarizes the four major signaling pathways in tumors. Furthermore, the present review demonstrates that ENPP1 serves a crucial role in cell migration, proliferation and invasion, and that corresponding inhibitors have been developed and associated with clinical characterization.

Evaluating the Accuracy of Large Language Model (ChatGPT) in Providing Information on Metastatic Breast Cancer

Purpose

Artificial intelligence (AI), particularly large language models like ChatGPT developed by OpenAI, has demonstrated potential in various domains, including medicine. While ChatGPT has shown the capability to pass rigorous exams like the United States Medical Licensing Examination (USMLE) Step 1, its proficiency in addressing breast cancer-related inquiries-a complex and prevalent disease-remains underexplored. This study aims to assess the accuracy and comprehensiveness of ChatGPT's responses to common breast cancer questions, addressing a critical gap in the literature and evaluating its potential in enhancing patient education and support in breast cancer management.

Methods

A curated list of 100 frequently asked breast cancer questions was compiled from Cancer.net, the National Breast Cancer Foundation, and clinical practice. These questions were input into ChatGPT, and the responses were evaluated for accuracy by two primary experts using a four-point scale. Discrepancies in scoring were resolved through additional expert review.

Results

Of the 100 responses, 5 were entirely inaccurate, 22 partially accurate, 42 accurate but lacking comprehensiveness, and 31 highly accurate. The majority of the responses were found to be at least partially accurate, demonstrating ChatGPT's potential in providing reliable information on breast cancer.

Conclusion

ChatGPT shows promise as a supplementary tool for patient education on breast cancer. While generally accurate, the presence of inaccuracies underscores the need for professional oversight. The study advocates for integrating AI tools like ChatGPT in healthcare settings to support patient-provider interactions and health education, emphasizing the importance of regular updates to reflect the latest research and clinical guidelines.

The tumor-derived cytokine Chi3l1 induces neutrophil extracellular traps that promote T cell exclusion in triple-negative breast cancer

In triple-negative breast cancer (TNBC), stromal restriction of CD8+ T cells associates with poor clinical outcomes and lack of responsiveness to immune-checkpoint blockade (ICB). To identify mediators of T cell stromal restriction, we profiled murine breast tumors lacking the transcription factor Stat3, which is commonly hyperactive in breast cancers and promotes an immunosuppressive tumor microenvironment. Expression of the cytokine Chi3l1 was decreased in Stat3-/- tumors. CHI3L1 expression was elevated in human TNBCs and other solid tumors exhibiting T cell stromal restriction. Chi3l1 ablation in the polyoma virus middle T (PyMT) breast cancer model generated an anti-tumor immune response and delayed mammary tumor onset. These effects were associated with increased T cell tumor infiltration and improved response to ICB. Mechanistically, Chi3l1 promoted neutrophil recruitment and neutrophil extracellular trap formation, which blocked T cell infiltration. Our findings provide insight into the mechanism underlying stromal restriction of CD8+ T cells and suggest that targeting Chi3l1 may promote anti-tumor immunity in various tumor types.

Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics

OBJECTIVE

To generate an image-driven biomarker (Rad_score) to predict tumor-infiltrating regulatory T lymphocytes (Treg) in breast cancer (BC).

METHODS

Overall, 928 BC patients were enrolled from the Cancer Genome Atlas (TCGA) for survival analysis; MRI (n = 71 and n = 30 in the training and validation sets, respectively) from the Cancer Imaging Archive (TCIA) were retrieved and subjected to repeat least absolute shrinkage and selection operator for feature reduction. The radiomic scores (rad_score) for Treg infiltration estimation were calculated via support vector machine (SVM) and logistic regression (LR) algorithms, and validated on the remaining patients.

RESULTS

Landmark analysis indicated Treg infiltration was a risk factor for BC patients in the first 5 years and after 10 years of diagnosis (p = 0.007 and 0.018, respectively). Altogether, 108 radiomic features were extracted from MRI images, 4 of which remained for model construction. Areas under curves (AUCs) of the SVM model were 0.744 (95% CI 0.622-0.867) and 0.733 (95% CI 0.535-0.931) for training and validation sets, respectively, while for the LR model, AUCs were 0.771 (95% CI 0.657-0.885) and 0.724 (95% CI 0.522-0.926). The calibration curves indicated good agreement between prediction and true value (p > 0.05), and DCA shows the high clinical utility of the radiomic model. Rad_score was significantly correlated with immune inhibitory genes like CTLA4 and PDCD1.

CONCLUSIONS

High Treg infiltration is a risk factor for patients with BC. The Rad_score formulated on radiomic features is a novel tool to predict Treg abundance in the tumor microenvironment.

HER2Δ16 Engages ENPP1 to Promote an Immune-Cold Microenvironment in Breast Cancer

The tumor-immune microenvironment (TIME) is a critical determinant of therapeutic response. However, the mechanisms regulating its modulation are not fully understood. HER2Δ16, an oncogenic splice variant of the HER2, has been implicated in breast cancer and other tumor types as a driver of tumorigenesis and metastasis. Nevertheless, the underlying mechanisms of HER2Δ16-mediated oncogenicity remain poorly understood. Here, we show that HER2∆16 expression is not exclusive to the clinically HER2+ subtype and associates with a poor clinical outcome in breast cancer. To understand how HER2 variants modulated the tumor microenvironment, we generated transgenic mouse models expressing either proto-oncogenic HER2 or HER2Δ16 in the mammary epithelium. We found that HER2∆16 tumors were immune cold, characterized by low immune infiltrate and an altered cytokine profile. Using an epithelial cell surface proteomic approach, we identified ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) as a functional regulator of the immune cold microenvironment. We generated a knock-in model of HER2Δ16 under the endogenous promoter to understand the role of Enpp1 in aggressive HER2+ breast cancer. Knockdown of Enpp1 in HER2Δ16-derived tumor cells resulted in decreased tumor growth, which correlated with increased T-cell infiltration. These findings suggest that HER2Δ16-dependent Enpp1 activation associates with aggressive HER2+ breast cancer through its immune modulatory function. Our study provides a better understanding of the mechanisms underlying HER2Δ16-mediated oncogenicity and highlights ENPP1 as a potential therapeutic target in aggressive HER2+ breast cancer.