The emerging role of noncoding RNAs in the PI3K/AKT/mTOR signalling pathway in breast cancer.

Breast cancer persists as a major problem for the world's healthcare, thus it is essential to fully understand the complex molecular processes that cause its growth and development. ncRNAs had been discovered to serve critical roles in a variety of cellular functions, including the regulation of signalling pathways. Within different pathways, the AKT/PI3K/mTOR signalling cascade has received a lot of interest because of its role in cancer. A complex interaction between ncRNAs, notably miRNAs, lncRNAs, and circRNAs, and the AKT/PI3K/mTOR signalling pathway exerts both oncogenic and tumor-suppressive activities by targeting critical components of the pathway directly or indirectly. Through miRNA-mediated post-transcriptional regulation, lncRNA-guided chromatin remodelling, and circRNA sequestration, ncRNAs modulate the activity of PI3K, AKT, and mTOR, influencing cell proliferation, survival, and metastasis. Furthermore, ncRNAs can serve as promising biomarkers for breast cancer prognosis, diagnosis, and treatment response, as their dysregulation is commonly observed in breast cancer patients. Harnessing the potential of ncRNAs as therapeutic targets or tools for restoring pathway homeostasis holds promise for innovative treatment strategies in breast cancer. Understanding the intricate regulatory networks orchestrated by ncRNAs in this context may pave the way for novel diagnostic approaches, therapeutic interventions, and a deeper comprehension of breast cancer's molecular landscape, ultimately improving patient outcomes. This abstract underscores the emerging significance of ncRNAs in the AKT/PI3K/mTOR signaling pathway in breast cancer.

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer.

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.