Tumor Microenvironment-Mediated Immune Profiles Characterized by Distinct Survival Outcome and Immunotherapeutic Efficacy in Breast Cancer

Computational pathology to improve biomarker testing in breast cancer: how close are we?

The recent advancements in breast cancer precision medicine have highlighted the urgency for the precise and reproducible characterization of clinically actionable biomarkers. Despite numerous standardization efforts, biomarker testing by conventional methodologies is challenged by several issues such as high inter-observer variabilities, the spatial heterogeneity of biomarkers expression, and technological heterogeneity. In this respect, artificial intelligence-based digital pathology approaches are being increasingly recognized as promising methods for biomarker testing and subsequently improved clinical management. Here, we provide an overview on the most recent advances for artificial intelligence-assisted biomarkers testing in breast cancer, with a particular focus on tumor-infiltrating lymphocytes, programmed death-ligand 1, phosphatidylinositol-3 kinase catalytic alpha, and estrogen receptor 1. Challenges and solutions for this integrative analysis in pathology laboratories are also provided.

Cancer Vaccine Therapeutics: Limitations and Effectiveness-A Literature Review

In recent years, there has been a surge of interest in tumor microenvironment-associated cancer vaccine therapies. These innovative treatments aim to activate and enhance the body's natural immune response against cancer cells by utilizing specific antigens present in the tumor microenvironment. The goal is to achieve a complete clinical response, where all measurable cancer cells are either eliminated or greatly reduced in size. With their potential to revolutionize cancer treatment, these therapies represent a promising avenue for researchers and clinicians alike. Despite over 100 years of research, the success of therapeutic cancer vaccines has been variable, particularly in advanced cancer patients, with various limitations, including the heterogeneity of the tumor microenvironment, the presence of immunosuppressive cells, and the potential for tumor escape mechanisms. Additionally, the effectiveness of these therapies may be limited by the variability of the patient's immune system response and the difficulty in identifying appropriate antigens for each patient. Despite these challenges, tumor microenvironment-targeted vaccine cancer therapies have shown promising results in preclinical and clinical studies and have the potential to become a valuable addition to current cancer treatment and "curative" options. While chemotherapeutic and monoclonal antibody treatments remain popular, ongoing research is needed to optimize the design and delivery of these therapies and to identify biomarkers that can predict response and guide patient selection. This comprehensive review explores the mechanisms of cancer vaccines, various delivery methods, and the role of adjuvants in improving treatment outcomes. It also discusses the historical background of cancer vaccine research and examines the current state of major cancer vaccination immunotherapies. Furthermore, the limitations and effectiveness of each vaccine type are analyzed, providing insights into the future of cancer vaccine development.

Characterization of the immune environment in pregnancy-associated breast cancer

Pregnancy-associated breast cancer (PrBC) is a rare and clinically challenging condition. Specific immune mechanisms and pathways are involved in maternal-fetal tolerance and tumor-host immunoediting. The comprehension of the molecular processes underpinning this immune synergy in PrBC is needed to improve patients' clinical management. Only a few studies focused on the immune biology of PrBC and attempted to identify bona fide biomarkers. Therefore, clinically actionable information remains extremely puzzling for these patients. In this review article, we discuss the current knowledge on the immune environment of PrBC, in comparison with pregnancy-unrelated breast cancer and in the context of maternal immune changes during pregnancy. A particular emphasis is given to the actual role of potential immune-related biomarkers for PrBC clinical management.

Tumor-infiltrating immune cells based TMEscore and related gene signature is associated with the survival of CRC patients and response to fluoropyrimidine-based chemotherapy

Background

Tumor-infiltrating immune cells (TIICs) are associated with chemotherapy response. This study aimed to explore the prognostic value of a TIIC-related tumor microenvironment score (TMEscore) in patients with colorectal cancer (CRC) who underwent chemotherapy and construct a TMEscore-related gene signature to determine its predictive value.

Methods

Gene profiles of patients who underwent fluoropyrimidine-based chemotherapy were collected, and their TIIC fractions were calculated and clustered. Differentially expressed genes (DEGs) between clusters were used to calculate the TMEscore. The association between the TMEscore, chemotherapy response, and survival rate was analyzed. Machine learning methods were used to identify key TMEscore-related genes, and a gene signature was constructed to verify the predictive value.

Results

Two clusters based on the TIIC fraction were identified, and the TMEscore was calculated based on the DEGs of the two clusters. The TMEscore was higher in patients who responded to chemotherapy than in those who did not, and was associated with the survival rate of patients who underwent chemotherapy. Three machine learning methods, support vector machine (SVM), decision tree (DT), and Extreme Gradient Boosting (XGBoost), identified three TMEscore-related genes (ADH1C, SLC26A2, and NANS) associated with the response to chemotherapy. A TMEscore-related gene signature was constructed, and three external cohorts validated that the gene signature could predict the response to chemotherapy. Five datasets and clinical samples showed that the expression of the three TMEscore-related genes was increased in tumor tissues compared to those in control tissues.

Conclusions

The TIIC-based TMEscore was associated with the survival of CRC patients who underwent fluoropyrimidine-based chemotherapy, and predicted the response to chemotherapy. The TMEscore-related gene signature had a better predictive value for response to chemotherapy than for survival.

Crosstalk of three novel types of programmed cell death defines distinct microenvironment characterization and pharmacogenomic landscape in breast cancer

Background

Prior studies have highlighted that novel programmed cell death (PCD) modalities, including ferroptosis, pyroptosis, and necroptosis, are correlated with tumor progression and antitumor immunity. Nonetheless, comprehensive analysis of tumor microenvironment (TME) profiles mediated by the crosstalk of distinct PCD forms has not been conducted in breast cancer (BC).

Methods

Here, we curated 34 identified PCD-associated genes (PCDAGs) and applied the consensus clustering algorithm to establish PCD-mediated tumor patterns in BC. Subsequently, based on prognostic differentially expressed genes extracted from distinct PCD-mediated patterns, we applied the LASSO algorithm to construct CD_Score. Furthermore, the correlation analysis between CD_Score and TME features, molecular subtypes, clinicopathological characteristics, drug response, and immunotherapeutic efficacy was performed.

Results

Three distinct PCD-clusters were determined among 2,038 BC samples, which did not only display different clinical outcomes but highly correlated to the established immunological tumor phenotypes: “desert,” “excluded,” and “inflamed” immune profiles. Based on the CD_Score derived from the PCD-related gene signature, BC patients could be stratified into CD_Score-low and -high group, of which the former displayed satisfactory survival outcome and enhanced immune infiltration. Further exploration identified that the CD_Score-high group significantly correlated with elevated neoantigen load and higher mutation frequency in SMGs (e.g., TP53 and MAP3K1) and reduced expression of immune checkpoint proteins.

Conclusions

This research is the first to emphasize the close relationship between distinct cell death modalities and the diversity and complexity of immune infiltration in TME. We established the CD_Score, which could help enhance our cognition of TME features and facilitate the clinical application of immunotherapy.