Metabolic heterogeneity and immunocompetence of infiltrating immune cells in the breast cancer microenvironment (Review)

A novel model based on lipid metabolism-related genes associated with immune microenvironment predicts metastasis of breast cancer

BACKGROUND

Breast cancer (BC) is the most prevalent malignant tumor among women worldwide and a significant cause of cancer-related deaths in females. Recent studies have shown that lipid metabolism-related genes (LMRGs) exhibit prognostic potential in various types of tumors, including BC. Our study aimed to establish a novel model to predict the metastasis of BC.

METHODS

Clinical information and corresponding RNA data of patients with BC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering was performed to identify novel molecular subgroups. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues using Expression, microenvironment cell populations counter, microenvironment cell populations counter, and single-sample gene set enrichment analyses were employed to determine the tumor immune microenvironment and immune status of the identified subgroups. Functional analyses, including Gene Ontology and gene set enrichment analyses, were conducted to elucidate the underlying mechanisms. A prognostic risk model was constructed using the Least Absolute Shrinkage and Selection Operator algorithm and multivariate Cox regression analysis.

RESULTS

This study identified differential gene expression between patients with BC exhibiting metastasis and those without metastasis using public databases. Using the obtained data, we established predictive models based on six LMRGs. Furthermore, consensus clustering and prognostic score grouping analysis revealed that differentially expressed LMRGs influence tumor prognosis by regulating tumor immunity. To facilitate clinical application, we developed a nomogram integrating the risk model and clinical characteristics to accurately predict the prognosis of patients with BC.

CONCLUSION

We developed and validated a novel signature associated with LMRGs for predicting disease-free survival in patients with BC. The expression of LMRGs correlates with the immune microenvironment of patients with BC, providing new insights and improved strategies for the diagnosis and treatment of BC.

Guardians and Mediators of Metastasis: Exploring T Lymphocytes, Myeloid-Derived Suppressor Cells, and Tumor-Associated Macrophages in the Breast Cancer Microenvironment

Breast cancers (BCs) are solid tumors composed of heterogeneous tissues consisting of cancer cells and an ever-changing tumor microenvironment (TME). The TME includes, among other non-cancer cell types, immune cells influencing the immune context of cancer tissues. In particular, the cross talk of immune cells and their interactions with cancer cells dramatically influence BC dissemination, immunoediting, and the outcomes of cancer therapies. Tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and myeloid-derived suppressor cells (MDSCs) represent prominent immune cell populations of breast TMEs, and they have important roles in cancer immunoescape and dissemination. Therefore, in this article we review the features of TILs, TAMs, and MDSCs in BCs. Moreover, we highlight the mechanisms by which these immune cells remodel the immune TME and lead to breast cancer metastasis.

Identification of exosome-related gene signature as a promising diagnostic and therapeutic tool for breast cancer

Background

Exosomes are promising tools for the development of new diagnostic and therapeutic approaches. Exosomes possess the ability to activate signaling pathways that contribute to the remodeling of the tumor microenvironment, angiogenesis, and the regulation of immune responses. We aimed to develop a prognostic score based on exosomes derived from breast cancer.

Materials and methods

Training was conducted on the TCGA-BRCA dataset, while validation was conducted on GSE20685, GSE5764, GSE7904, and GSE29431. A total of 121 genes related to exosomes were retrieved from the ExoBCD database. The Cox proportional hazards model is used to develop risk score model. The GSVA package was utilized to analyze single-sample gene sets and identify exosome signatures, while the WGCNA package was utilized to identify gene modules associated with clinical outcomes. The clusterProfiler and GSVA R packages facilitated gene set enrichment and variation analyses. Furthermore, CIBERSORT quantified immune infiltration, and a correlation between gene expression and drug sensitivity was assessed using the TIDE algorithm.

Results

An exosome-related prognostic score was established using the following selected genes: ABCC9, PIGR, CXCL13, DOK7, CD24, and IVL. Various immune cells that promote cancer immune evasion were associated with a high-risk prognostic score, which was an independent predictor of outcome. High-risk and low-risk groups exhibited significantly different infiltration abundances (p < 0.05). By conducting a sensitivity comparison, we found that patients with high-risk scores exhibited more favorable responses to immunotherapy than those with low-risk scores.

Conclusion

The exosome-related gene signature exhibits outstanding performance in predicting the prognosis and cancer status of patients with breast cancer and guiding immunotherapy.

The functional roles of the circRNA/Wnt axis in cancer

CircRNAs, covalently closed noncoding RNAs, are widely expressed in a wide range of species ranging from viruses to plants to mammals. CircRNAs were enriched in the Wnt pathway. Aberrant Wnt pathway activation is involved in the development of various types of cancers. Accumulating evidence indicates that the circRNA/Wnt axis modulates the expression of cancer-associated genes and then regulates cancer progression. Wnt pathway-related circRNA expression is obviously associated with many clinical characteristics. CircRNAs could regulate cell biological functions by interacting with the Wnt pathway. Moreover, Wnt pathway-related circRNAs are promising potential biomarkers for cancer diagnosis, prognosis evaluation, and treatment. In our review, we summarized the recent research progress on the role and clinical application of Wnt pathway-related circRNAs in tumorigenesis and progression.

Validating RRP12 Expression and Its Prognostic Significance in HCC Based on Data Mining and Bioinformatics Methods

RRP12 (ribosomal RNA processing 12 homolog) is a nucleolar protein involved in the maturation and transport of eukaryotic ribosomal subunits and is a type of RNA binding protein. In recent years, considerable research has indicated that RRP12 is associated with the occurrence and development of multiple cancers. However, there is no research on RRP12 in hepatocellular carcinoma. Herein, we aimed to explore the role and significance of RRP12 in hepatocellular carcinoma.We used the TIMER and GEPIA databases to perform pan-cancer analyses of RRP12. The impact of RRP12 on the prognosis was analyzed through the GEPIA database. The relationship between RRP12 and immune cell infiltration was investigated by TIMER and GEPIA databases. Moreover, the expression of RRP12 in various liver cancer cells was evaluated by Western Blot to determine the cell line for the next experiment. Scratch test, Transwell test, and Edu tests were applied to validate the effects of RRP12 on the function of liver cancer cells. And the data were statistically analyzed.Pan-cancer analysis found that RPP12 was significantly upregulated in many cancers. Moreover, the prognostic analysis revealed that the difference in the expression of RRP12 has statistical significance for the overall survival rate and disease-free survival rate of liver cancer patients. In order to analyze the correlation between the expression level of RRP12 and clinical parameters, it was found that there was a significant negative correlation with tumor stage, tumor grade and tumor size. Univariate and multivariate analysis showed that RRP12 could be used as an independent prognostic factor for patients with hepatocellular carcinoma. Cellular experiments have proved that knocking down RRP12 can inhibit the proliferation, invasion, and metastasis of liver cancer cells.Therefore, RRP12 significantly affects the occurrence and development of HCC. Hence, RRP12 can become a potential target and prognostic biomarker for the treatment of hepatocellular carcinoma.