https://jiangyanxiamm.shinyapps.io/MMprognosis/) were built based on the UPS signature and its clinical features. Analyses of calibration plots and decision curves showed clinical utility for both training and validation datasets.

Conclusions: As a result of these results, we established a genetic signature for MM based on UPS. This genetic signature could contribute to improving individualized survival prediction, thereby facilitating clinical decisions in patients with MM." name="description"> A nomogram for predicting prognosis of multiple myeloma patients based on a ubiquitin-proteasome gene signature - Figure f4 | Aging

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Research Paper Volume 14, Issue 24 pp 9951—9968

A nomogram for predicting prognosis of multiple myeloma patients based on a ubiquitin-proteasome gene signature

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Figure 4. GSVA analysis between low- and high- risk groups. (A) Volcano map showed the enriched biological processes terms between low- and high- risk groups. (B) Top 50 enriched biological processes terms. (C) Volcano map showed the enriched KEGG pathways terms between low- and high- risk groups. (D) Top 50 enriched KEGG pathways terms.