Choices in surgery for older women with breast cancer

Construction of ceRNA Networks Associated With CD8 T Cells in Breast Cancer

Background

The infiltration of CD8 T cells is usually linked to a favorable prognosis and may predict the therapeutic response of breast cancer patients to immunotherapy. The purpose of this research is to investigate the competing endogenous RNA (ceRNA) network correlated with the infiltration of CD8 T cells.

Methods

Based on expression profiles, CD8 T cell abundances for each breast cancer (BC) patient were inferred using the bioinformatic method by immune markers and expression profiles. We were able to extract the differentially expressed RNAs (DEmRNAs, DEmiRNAs, and DElncRNAs) between low and high CD8 T-cell samples. The ceRNA network was constructed using Cytoscape. Machine learning models were built by lncRNAs to predict CD8 T-cell abundances. The lncRNAs were used to develop a prognostic model that could predict the survival rates of BC patients. The expression of selected lncRNA (XIST) was validated by quantitative real-time PCR (qRT-PCR).

Results

A total of 1,599 DElncRNAs, 89 DEmiRNAs, and 1,794 DEmRNAs between high and low CD8 T-cell groups were obtained. Two ceRNA networks that have positive or negative correlations with CD8 T cells were built. Among the two ceRNA networks, nine lncRNAs (MIR29B2CHG, NEAT1, MALAT1, LINC00943, LINC01146, AC092718.4, AC005332.4, NORAD, and XIST) were selected for model construction. Among six prevalent machine learning models, artificial neural networks performed best, with an area under the curve (AUC) of 0.855. Patients from the high-risk category with BC had a lower survival rate compared to those from the low-risk group. The qRT-PCR results revealed significantly reduced XIST expression in normal breast samples, which was consistent with our integrated analysis.

Conclusion

These results potentially provide insights into the ceRNA networks linked with T-cell infiltration and provide accurate models for T-cell prediction.

Geriatric oncology: problems with under-treatment within this population

We are currently faced with an aging population, which is rapidly growing worldwide. Two thirds of cancer occurs in the over 65-year age group. Societal conceptions from the past have created ageist stereotypes; old age is associated with frailty and the elderly are perceived to be destined for deterioration and loss of independence. Cancer within the elderly is also subject to these stereotypes, with elderly cancer patients considered by some not as likely to recover as younger patients with cancer. We summarise and review the current concerns regarding elderly management and treatments utilised for the management of oncological disease in the elderly, and discuss the impact of under-treatment within this population.