Leveraging GWAS data derived from a large cooperative group trial to assess the risk of taxane-induced peripheral neuropathy (TIPN) in patients being treated for breast cancer: Part 2—functional implications of a SNP cluster associated with TIPN risk in patients being treated for breast cancer

Lustberg, Maryam B.; Wu, Xuan; Fernández-Martínez, Juan Luis; Andrés-Galiana, Enrique J. de; Philips, Santosh; Leibowitz, Jeffrey; Schneider, Bryan P.; Sonis, Stephen T.

doi:10.1007/s00520-023-07617-6

Cited by 2 publications

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The top 10 common BP terms were shown in Figure 6B , with the highest enrichment scoring of “NERVOUS SYSTEM PROCESS” (GO:0050877), indicating the key role of the nervous system in cancer (Hanahan and Monje, 2023 ). Supplementary Table S9 (Peterson et al, 2020 ; Feng et al, 2021 ; Glorieux and Buc Calderon, 2021 ; Hou et al, 2021 ; Naghshi et al, 2021 ) and Supplementary Table S10 (Martens and Mithöfer, 2005 ; Turner and Grose, 2010 ; Menezes et al, 2018 ; Arneson and Doles, 2019 ; Przygodzka et al, 2019 ; Keough and Monje, 2022 ; Ohkuni et al, 2022 ; Libretti and Aeddula, 2023 ; Lustberg et al, 2023 ) summarized the specific enrichment results in each cancer, indicating that a series of risk factors (such as neurodevelopment and cellular homeostasis) were also crucial to cancer.…”

Section: Resultsmentioning

confidence: 99%

Identification of crucial inflammaging related risk factors in multiple sclerosis

Xu,

Wang,

Ren

et al. 2024

Front. Mol. Neurosci.

View full text Add to dashboard Cite

BackgroundMultiple sclerosis (MS) is an immune-mediated disease characterized by inflammatory demyelinating lesions in the central nervous system. Studies have shown that the inflammation is vital to both the onset and progression of MS, where aging plays a key role in it. However, the potential mechanisms on how aging-related inflammation (inflammaging) promotes MS have not been fully understood. Therefore, there is an urgent need to integrate the underlying mechanisms between inflammaging and MS, where meaningful prediction models are needed.MethodsFirst, both aging and disease models were developed using machine learning methods, respectively. Then, an integrated inflammaging model was used to identify relative risk factors, by identifying essential “aging-inflammation-disease” triples. Finally, a series of bioinformatics analyses (including network analysis, enrichment analysis, sensitivity analysis, and pan-cancer analysis) were further used to explore the potential mechanisms between inflammaging and MS.ResultsA series of risk factors were identified, such as the protein homeostasis, cellular homeostasis, neurodevelopment and energy metabolism. The inflammaging indices were further validated in different cancer types. Therefore, various risk factors were integrated, and even both the theories of inflammaging and immunosenescence were further confirmed.ConclusionIn conclusion, our study systematically investigated the potential relationships between inflammaging and MS through a series of computational approaches, and could present a novel thought for other aging-related diseases.

show abstract