Global Aging and Cancer: Advancing Care Through Innovation

Geriatric Breast Cancer: Staging, Molecular Surrogates, and Treatment. A Review & Meta-analysis

Breast cancer (BC) is one of the most frequent cancers in females across the globe. Treatment recommendations for BC patients are primarily driven by patient age, staging and tumor molecular subtype. Thus, we updated the general overview of BC staging, molecular surrogates, and treatment choices for women >70 years based on a systematic study encompassing the years 2013-2023. A PRISMA guidelines and PICO framework were followed, and relevant research articles were searched using different data bases (Web of Sciences, PubMed, MEDLINE, and Scopus). Mixed Methods Appraisal Tool was used for studies quality assessment. The research articles that made it into the systematic review were compiled using qualitative criteria. In the meanwhile, heterogeneity was determined using meta-analysis with RevMan 5.4. We applied a random effects model with a 0.05 significance level. Overall, there were 4151 research articles, after screening only 17 articles with 39,906 patients were included. Conclusion: Elderly patients with breast cancer should be treated differently in an adapted way. The treatment should not be the same worldwide due to different health systems. Molecular surrogates are different in geriatric patients. Surgery is the best option for treatment in this subset of patients. We need to have therapeutic decision appointments for elderly patients with breast cancer. The guidelines and medical authority should be used in the best decision.

Identification and Development of an Age-Related Classification and Signature to Predict Prognosis and Immune Landscape in Osteosarcoma

Background. In childhood and adolescence, the prevailing bone tumor is osteosarcoma associated with frequent recurrence and lung metastasis. This research focused on predicting the survival and immune landscape of osteosarcoma by developing a prognostic signature and establishing aging-related genes (ARGs) subtypes. Methods. The training group comprised of the transcriptomic and associated clinical data of 84 patients with osteosarcoma accessed at the TARGET database and the validation group consisted of 53 patients from GSE21257. The aging-related subtypes were identified using unsupervised consensus clustering analysis. The ARG signature was developed utilizing multivariate Cox analysis and LASSO regression. The prognostic value was assessed using the univariate and multivariate Cox analyses, Kaplan-Meier plotter, time-dependent ROC curve, and nomogram. The functional enrichment analyses were performed by GSEA, GO, and KEGG analysis, while the ssGSEA, ESTIMATE, and CIBERSORT analyses were conducted to reveal the immune landscape in osteosarcoma. Results. The two clusters of osteosarcoma patients formed based on 543 ARGs, depicted a considerable difference in the tumor microenvironment, and the overall survival and immune cell infiltration rate varied as well. Among these, the selected 23 ARGs were utilized for the construction of an efficient predictive prognostic signature for the overall survival prediction. The testing in the validation group of osteosarcoma patients confirmed the status of the high-risk score as an independent indicator for poor prognosis, which was already identified as such using the univariate and multivariate Cox analyses. Furthermore, the ARG signature could distinguish different immune-related functions, infiltration status of immune cells, and tumor microenvironment, as well as predict the immunotherapy response of osteosarcoma patients. Conclusion. The aging-related subtypes were identified and a prognostic signature was developed in this research, which determined different prognoses and allowed for treatment of osteosarcoma patients to be tailored. Additionally, the immunotherapeutic response of individuals with osteosarcoma could also be predicted by the ARG signature.