Targeting metabolism of breast cancer and its implications in T cell immunotherapy.

Breast cancer is a prominent health issue amongst women around the world. Immunotherapies including tumor targeted antibodies, adoptive T cell therapy, vaccines, and immune checkpoint blockers have rejuvenated the clinical management of breast cancer, but the prognosis of patients remains dismal. Metabolic reprogramming and immune escape are two important mechanisms supporting the progression of breast cancer. The deprivation uptake of nutrients (such as glucose, amino acid, and lipid) by breast cancer cells has a significant impact on tumor growth and microenvironment remodeling. In recent years, in-depth researches on the mechanism of metabolic reprogramming and immune escape have been extensively conducted, and targeting metabolic reprogramming has been proposed as a new therapeutic strategy for breast cancer. This article reviews the abnormal metabolism of breast cancer cells and its impact on the anti-tumor activity of T cells, and further explores the possibility of targeting metabolism as a therapeutic strategy for breast cancer.

Combined targeting of KRT23 and NCCRP1 as a potential novel therapeutic approach for the treatment of triple-negative breast cancer.

Background: Breast cancers characterized by triple-negative status tend to be more malignant and have a poorer prognosis. A risk model for predicting breast cancer risk should be developed. Methods: We obtained gene expression and clinical characteristics data using the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) database. Differential gene screening between patients with triple-negative breast cancer (TNBC) and non-triple-negative breast cancers (NTNBC) was performed according to the "edgeR" filter criteria. Univariate and multivariate Cox regression analyses were used to construct a risk model and identify prognosis-related genes. XCELL, TIMER, EPIC, QUANTISEQ, MCPCOUNTER, EPIC, CIBERSORT-ABS, and CIBERSORT software programs were used to determine the extent of tumor immune cell infiltration. To evaluate the clinical responses to breast cancer treatment, the half maximal inhibitory concentration (IC50s) of common chemotherapeutics were calculated using "pRRophetic" and "ggplot2". Cell proliferation was assayed using cell counting kit-8 (CCK8) and 5-Ethynyl-2'-deoxyuridine (EdU) Cell Proliferation Kit. A dual-luciferase reporter assay confirmed the gene regulatory relationship of sex determining region Y-box 10 (SOX10). Results: An assessment model was established for Keratin23 (KRT23) and non-specific cytotoxic cell receptor 1 (NCCRP1) using the univariate and multivariate Cox regression analyses. In addition, high expression levels of KRT23 and NCCRP1 indicated high proliferation and poor prognosis. We also found that the gene expression patterns of multiple genes were significantly more predictive of risks and have a higher level of consistency when assessing risk. In vitro experiments showed that the expressions of KRT23 and NCCRP1 were increased in TNBCs and promoted cell proliferation. Mechanically, the dual-luciferase reporter assay confirmed that SOX10 regulated the expressions of KRT23 and NCCRP1. The risk score model revealed a close relationship between the expressions of KRT23 and NCCRP1, the tumor immune microenvironment, and chemotherapeutics. Conclusions: In conclusion, we constructed a risk assessment model to predict the risk of TNBC patients, which acted as a potential predictor for chemosensitivity.

A combination of transcriptome and methylation analyses reveals the role of lncRNA HOTAIRM1 in the proliferation and metastasis of breast cancer.

Background: DNA methylation status is strongly associated with the prognosis of breast invasive carcinoma (BRCA). Elucidating the mechanisms underlying DNA methylation coupled with determining its biological function is imperative to the effective development of treatment and prevention strategies for breast cancer. Methods: We retrieved transcriptome and DNA methylation profiles of BRCA patients from The Cancer Genome Atlas (TCGA) database, then applied the "limma" package in R software to identify differentially expressed genes (DEGs) and aberrantly methylated genes. Next, we used the "MethylMix" package to screen for methylation-driven genes, and performed univariate and multivariate Cox regression analyses to determine the prognostic value of the methylation-driven genes and clinical characteristics. We validated these findings in 51 breast cancer tissues alongside 51 corresponding normal tissues. Furthermore, we used cell experiments to clarify the biological function and underlying molecular mechanisms of HOTAIRM1 in vitro. Results: A total of 25 methylation-driven genes were identified in the dataset. Results from univariate and multivariate Cox regression showed that SYN2, HOTAIRM1, BCAS1, and ALDOC were significantly associated with patient prognosis. Immunohistochemistry and quantitative real-time polymerase chain reaction (qRT-PCR) results showed that the expression levels of SYN2 and HOTAIRM1 were negatively correlated with BRCA stage, whereas those of BCAS1 and ALDOC were positively correlated with BRCA stage. Results from in vitro experiments showed that knockdown HOTAIRM1 expression promoted breast cancer cells proliferation, clone formation, and invasion. Up-regulation of HOTAIRM1 inhibited breast cancer cells proliferation, clone formation, and invasion. Conclusions: In summary, low HOTAIRM1 expression is a significant prognostic factor for the survival of BRCA patients and thus could be a potential therapeutic target for the treatment of BRCA.