Biallelic TP53 inactivation is the most important high-risk factor associated with poor survival in multiple myeloma. Classical biallelic TP53 inactivation has been defined as simultaneous mutation and copy number loss in most studies; however, numerous studies have demonstrated that other factors could lead to the inactivation of TP53. Here, we hypothesized that novel biallelic TP53 inactivated samples existed in the multiple myeloma population. A random forest regression model that exploited an expression signature of 16 differentially expressed genes between classical biallelic TP53 and TP53 wild-type samples was subsequently established and used to identify novel biallelic TP53 samples from monoallelic TP53 groups. The model reflected high accuracy and robust performance in newly diagnosed relapsed and refractory populations. Patient survival of classical and novel biallelic TP53 samples was consistently much worse than those with mono-allelic or wild-type TP53 status. We also demonstrated that some predicted biallelic TP53 samples simultaneously had copy number loss and aberrant splicing, resulting in overexpression of high-risk transcript variants, leading to biallelic inactivation. We discovered that splice site mutation and overexpression of the splicing factor MED18 were reasons for aberrant splicing. Taken together, our study unveiled the complex transcriptome of TP53, some of which might benefit future studies targeting abnormal TP53.
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