Rewiring of the Endocrine Network in Triple-Negative Breast Cancer

Understanding and harnessing triple-negative breast cancer-related microbiota in oncology

Bacterial inhabitants of the body have the potential to play a role in various stages of cancer initiation, progression, and treatment. These bacteria may be distal to the primary tumour, such as gut microbiota, or local to the tissue, before or after tumour growth. Breast cancer is well studied in this context. Amongst breast cancer types, Triple Negative Breast Cancer (TNBC) is more aggressive, has fewer treatment options than receptor-positive breast cancers, has an overall worse prognosis and higher rates of reoccurrence. Thus, an in-depth understanding of the bacterial influence on TNBC progression and treatment is of high value. In this regard, the Gut Microbiota (GM) can be involved in various stages of tumour progression. It may suppress or promote carcinogenesis through the release of carcinogenic metabolites, sustenance of proinflammatory environments and/or the promotion of epigenetic changes in our genome. It can also mediate metastasis and reoccurrence through interactions with the immune system and has been recently shown to influence chemo-, radio-, and immune-therapies. Furthermore, bacteria have also been found to reside in normal and malignant breast tissue. Several studies have now described the breast and breast tumour microbiome, with the tumour microbiota of TNBC having the least taxonomic diversity among all breast cancer types. Here, specific conditions of the tumour microenvironment (TME) - low O2, leaky vasculature and immune suppression - are supportive of tumour selective bacterial growth. This innate bacterial ability could enable their use as delivery agents for various therapeutics or as diagnostics. This review aims to examine the current knowledge on bacterial relevance to TNBC and potential uses while examining some of the remaining unanswered questions regarding mechanisms underpinning observed effects.

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.