Identification of a p53 target, CD137L, that mediates growth suppression and immune response of osteosarcoma cells

Establishing and Validating an Aging-Related Prognostic Signature in Osteosarcoma

Aging is an inevitable process that biological changes accumulate with time and results in increased susceptibility to different tumors. But currently, aging-related genes (ARGs) in osteosarcoma were not clear. We investigated the potential prognostic role of ARGs and established an ARG-based prognostic signature for osteosarcoma. The transcriptome data and corresponding clinicopathological information of patients with osteosarcoma were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Molecular subtypes were generated based on prognosis-related ARGs obtained from univariate Cox analysis. With ARGs, a risk signature was built by univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Differences in clinicopathological features, immune infiltration, immune checkpoints, responsiveness to immunotherapy and chemotherapy, and biological pathways were assessed according to molecular subtypes and the risk signature. Based on risk signature and clinicopathological variables, a nomogram was established and validated. Three molecular subtypes with distinct clinical outcomes were classified based on 36 prognostic ARGs for osteosarcoma. A nine-ARG-based signature in the TCGA cohort, including BMP8A, CORT, SLC17A9, VEGFA, GAL, SSX1, RASGRP2, SDC3, and EVI2B, has been created and developed and could well perform patient stratification into the high- and low-risk groups. There were significant differences in clinicopathological features, immune checkpoints and infiltration, responsiveness to immunotherapy and chemotherapy, cancer stem cell, and biological pathways among the molecular subtypes. The risk signature and metastatic status were identified as independent prognostic factors for osteosarcoma. A nomogram combining ARG-based risk signature and metastatic status was established, showing great prediction accuracy and clinical benefit for osteosarcoma OS. We characterized three ARG-based molecular subtypes with distinct characteristics and built an ARG-based risk signature for osteosarcoma prognosis, which could facilitate prognosis prediction and making personalized treatment in osteosarcoma.

Gene co-expression network for analysis of plasma exosomal miRNAs in the elderly as markers of aging and cognitive decline

BACKGROUND

Evidence has shown that microRNA (miRNAs) are involved in molecular pathways responsible for aging and age-related cognitive decline. However, there is a lack of research linked plasma exosome-derived miRNAs changes with cognitive function in older people and aging, which might prove a new insight on the transformation of miRNAs on clinical applications for cognitive decline for older people.

METHODS

We applied weighted gene co-expression network analysis to investigated miRNAs within plasma exosomes of older people for a better understanding of the relationship of exosome-derived miRNAs with cognitive decline in elderly adults. We identified network modules of co-expressed miRNAs in the elderly exosomal miRNAs dataset. In each module, we selected vital miRNAs and carried out functional enrichment analyses of their experimentally known target genes and their function.

RESULTS

We found that plasma exosomal miRNAs hsa-mir-376a-3p, miR-10a-5p, miR-125-5p, miR-15a-5p have critical regulatory roles in the development of aging and cognitive dysfunction in the elderly and may serve as biomarkers and putative novel therapeutic targets for aging and cognitive decline.