RESUMO
The p53 tumor suppressor integrates upstream signals such as DNA damage and active oncogenes to initiate cell cycle arrest or apoptosis. This response is critical to halting inappropriate growth signals. As such, p53 activity is lost in cancer. In melanoma, however, the p53 gene is intact in a reported 94% of human cases. Rather than direct mutation, p53 is held inactive through interaction with inhibitory proteins. Here, we examine the expression of the two primary inhibitors of p53, MDM2 and MDM4, in genomic databases and biopsy specimens. We find that MDM4 is frequently overexpressed. Moreover, changes in splicing of MDM4 occur frequently and early in melanomagenesis. These changes in splicing must be considered in the design of therapeutic inhibitors of the MDM2/4 proteins for melanoma.
RESUMO
Sample mislabeling or misannotation has been a long-standing problem in scientific research, particularly prevalent in large-scale, multi-omic studies due to the complexity of multi-omic workflows. There exists an urgent need for implementing quality controls to automatically screen for and correct sample mislabels or misannotations in multi-omic studies. Here, we describe a crowdsourced precisionFDA NCI-CPTAC Multi-omics Enabled Sample Mislabeling Correction Challenge, which provides a framework for systematic benchmarking and evaluation of mislabel identification and correction methods for integrative proteogenomic studies. The challenge received a large number of submissions from domestic and international data scientists, with highly variable performance observed across the submitted methods. Post-challenge collaboration between the top-performing teams and the challenge organizers has created an open-source software, COSMO, with demonstrated high accuracy and robustness in mislabeling identification and correction in simulated and real multi-omic datasets.