Background Brest cancer (BC) is the most common cancer in women and the second most frequent type of newly diagnosed cancer worldwide. Second, anoikis, a specific programmed death brought on by a cell's lack of contact with the extracellular matrix, is crucial for the spread of cancer. The impact of anoikis on BC patients' prognoses, however, is still unknown.
Method Via the TCGA and GEO databases, we gathered patient transcriptome and clinical group data for this investigation. The classification of subtypes A and B, subtype survival analysis, and pathway analysis were performed using anoikis-related genes (ARGs). the least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and tumor microenvironment were used to evaluate the immune microenvironment (TME). Ultimately, ten ARGs relevant to prognosis were collected, and prognostic models were created. In order to characterize the correlation of ARGS, we also performed single cell data analysis. Finally, we used real-time polymerase chain reaction (RT-PCR) to analyze the associations between the 10 prognostic ARGS and BC cells.
Results By using Kaplan-Meier (KM) and receiver operating characteristic (ROC) curve analyses, we were able to identify ten ARGS (YAP1, PIK3R1, BAK1, PHLDA2, EDA2R, LAMB3, CD24, SLC2A1, CDC25C, and SLC39A6) as BC prognosis-related ARGS. These characteristics of the high-risk group of ARGS were linked to a poor prognosis in BC patients. KEGG functional analysis revealed that the immunological state of these high- and low-risk groups was different. By building a carcinogenesis model of risk score, risk score was found to be an independent prognostic factor. YAP1, PIK3R1, BAK1, PHLDA2, EDA2R, CD24, SLC2A1, and CDC25C were all strongly expressed in BC cells, according to the results of the RT-PCR analysis. were poorly expressed in SLC39A6 and LAMB3BC cells, but were strongly expressed in BC cells. The outcomes agreed with our earlier analysis of differential expression.
Conclusion ARGS markers can be used as BC biomarkers for risk stratification and survival prediction in BC patients. Besides, ARGs can be used as stratification factors for individualized and precise treatment of BC patients.