Prospects and Challenges of Different Delivery Systems in Breast Tumors Therapy.

Breast cancer (BC) is the most prevalent malignancy in women. The emergence of targeted therapies and advancements in comprehensive treatment protocols have significantly improved survival outcomes for patients with early-stage BC. However, individuals with refractory BC, particularly those who have received multiple lines of therapy or presented with distant metastases at diagnosis, continue to face challenges due to the limitations of conventional antibodies and cytotoxic agents in meeting therapeutic needs.

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.

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.

A combination of transcriptome and methylation analyses reveals the role of lncRNA 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.