Analyzing mRNAsi-Related Genes Identifies Novel Prognostic Markers and Potential Drug Combination for Patients with Basal Breast Cancer

Abstract

Basal breast cancer subtype is the worst prognosis subtypes among all breast cancer subtypes. Recently, a new tumor stemness index-mRNAsi is found to be able to measure the degree of oncogenic differentiation of tissues. The mRNAsi involved in a variety of cancer processes is derived from the innovative application of one-class logistic regression (OCLR) machine learning algorithm to the whole genome expression of various stem cells and tumor cells. However, it is largely unknown about mRNAsi in basal breast cancer. Here, we find that basal breast cancer carries the highest mRNAsi among all four subtypes of breast cancer, especially 385 mRNAsi-related genes are positively related to the high mRNAsi value in basal breast cancer. This high mRNAsi is also closely related to active cell cycle, DNA replication, and metabolic reprogramming in basal breast cancer. Intriguingly, in the 385 genes, TRIM59, SEPT3, RAD51AP1, and EXO1 can act as independent protective prognostic factors, but CTSF and ABHD4B can serve as independent bad prognostic factors in patients with basal breast cancer. Remarkably, we establish a robust prognostic model containing the 6 mRNAsi-related genes that can effectively predict the survival rate of patients with the basal breast cancer subtype. Finally, the drug sensitivity analysis reveals that some drug combinations may be effectively against basal breast cancer via targeting the mRNAsi-related genes. Taken together, our study not only identifies novel prognostic biomarkers for basal breast cancers but also provides the drug sensitivity data by establishing an mRNAsi-related prognostic model.

Integrative stemness characteristics associated with prognosis and the immune microenvironment in lung adenocarcinoma

“…Studies have suggested that mRNAsi might serve as an effective index for the survival, classification, and disease progression of tumor patients [25][26][27]. Huang et al found that basal breast cancer patients have high mRNAsi values [28]. In the present study, we found that the mRNAsi value in LUAD samples was higher than that in normal samples, and survival analysis revealed that patients in the high mRNAsi group had a poor prognosis.…”

Stemness Analysis Uncovers That The Peroxisome Proliferator-Activated Receptor Signaling Pathway Can Mediate Fatty Acid Homeostasis In Sorafenib-Resistant Hepatocellular Carcinoma Cells

“…We also calculated the mRNAsi for HCC samples obtained from five cohorts. A higher mRNAsi represents a lower level of differentiation of a sample ( 20 ). Survival analysis was performed only using samples obtained from patients for whom the survival duration was less than 5 years.…”

“…There is still an urgent need for reliable and robust markers that can be used for predicting the prognosis of different HCC cohorts and the effect of drug therapy, which are also of great value for the precise treatment of patients. Several studies have shown that the stemness index is effective for the prediction of prognosis and drug resistance in multiple malignancies (20)(21)(22)(23). Here, we aimed to explore the regulatory mechanism under sorafenib-resistant conditions using the stemness index.…”

Differential Expression of RAD51AP1 in Ovarian Cancer: Effects of siRNA In Vitro

“…RAD51AP1 is also significantly up-regulated in triple negative breast cancer and its overexpression is associated with poor outcome, suggestive of prognostic value in this malignancy [33]. More recently, RAD51AP1 was one of four other genes (EXO1, TRIM59 and SEPT3) that can be an independent protective prognostic factor in patients with basal breast cancer [34]. Apart from its prognostic value, the siRNA data also points towards an interesting therapeutic target.…”